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Latest Research

2024-05-23T00:00:00.000-05:00

2024-04-25T00:00:00.000-05:00

Household Pulse: Balances through February 2024

2024-04-16T00:00:00.000-05:00

Hidden costs of homeownership: Race, income, and lender differences in loan closing costs

2024-04-03T00:00:00.000-05:00

Scaling to $1 Million: How Small Businesses Fare by Owner Race and Gender

2024-04-02T00:00:00.000-05:00

The rise in retail investing: Roles of the economic cycle and income growth

2024-03-27T00:00:00.000-05:00

How did advance Child Tax Credit payments affect households’ 2021 tax year outcomes and spending response?

2024-03-25T00:00:00.000-05:00

Checking in on Real Incomes after February Labor Market Data

2024-02-23T00:00:00.000-05:00

Balancing restarted student loan payments and a mortgage: How will household budgets adapt?

2024-01-25T00:00:00.000-05:00

Household Pulse: Balances through October 2023

2023-11-20T00:00:00.000-05:00

The Purchasing Power of Household Incomes: Worker outcomes through August 2023 by income and race

2023-07-12T00:00:00.000-05:00

Household Pulse: Balances through March 2023

Household Cash Buffer Management from the Great Recession through COVID-19

2023-06-21T00:00:00.000-05:00

Measuring the gap: Refinancing trends and disparities during the COVID-19 pandemic

2023-06-15T00:00:00.000-05:00

Household Pulse & Cash Buffer Management throughout the pandemic

2023-05-26T00:00:00.000-05:00

The potential borrower impact of proposed IDR reforms

JPMorgan Chase Institute Take

2023-05-24T00:00:00.000-05:00

Cash or credit: Small business use of credit cards for cash flow management

Cities and Local Communities

2023-01-31T00:00:00.000-05:00

Downtown Downturn: The Covid Shock to Brick-and-Mortar Retail

2022-12-12T00:00:00.000-05:00

The Dynamics and Demographics of U.S. Household Crypto-Asset Use

2022-11-15T00:00:00.000-05:00

How families used the advanced Child Tax Credit

2022-10-27T00:00:00.000-05:00

The Purchasing Power of Household Incomes from 2019 to 2022

2022-09-13T00:00:00.000-05:00

Household Pulse through June 2022: Gains for most, but not all

Last Updated with June 2022 data

2022-08-31T00:00:00.000-05:00

Who benefits from the 2022 student debt cancellation?

JPMorgan Chase Institute

2022-08-15T00:00:00.000-05:00

Expanding Access to Unemployment Insurance

Spending and Job-Finding Impacts of Expanded Unemployment Benefits

2022-07-26T00:00:00.000-05:00

Credit and the Family: The Economic Consequences of Closing the Credit Gap of US Couples

2022-06-28T00:00:00.000-05:00

Income Driven Repayment: Who needs student loan payment relief?

2022-06-21T00:00:00.000-05:00

Household Pulse: The State of Cash Balances through March 2022

Last Updated with March 2022 data

2022-05-26T00:00:00.000-05:00

Healthcare spending through the Pandemic: the impact of high-cost medical events on household finances

2022-05-19T00:00:00.000-05:00

Racial Income Inequality Dynamics

Big Data Insights from 2013 through COVID-19

2022-05-03T00:00:00.000-05:00

Small business owner liquid wealth at firm startup and exit

2022-04-20T00:00:00.000-05:00

Rising prices for fuel, rent, and food eat into families’ financial gains

2022-04-18T00:00:00.000-05:00

Lessons learned from the Pandemic Unemployment Assistance Program during COVID-19

2022-04-11T00:00:00.000-05:00

Post-COVID Consumer Spending in New York City

2022-03-29T00:00:00.000-05:00

Reading Inflation Expectations from the Treasury Market

Insights from Institutional Investor Trading Activity

2022-03-02T00:00:00.000-05:00

What do Fed rate hikes mean for U.S. households’ financial health?

2022-02-23T00:00:00.000-05:00

Household Pulse: The State of Cash Balances at Year End

Last Updated with December 2021 data

2022-02-17T00:00:00.000-05:00

Will this tax season be a boost or bust?

2021-12-15T00:00:00.000-05:00

Year in Review: 10 Key charts that summarize 2021

2021-12-09T00:00:00.000-05:00

Did the Paycheck Protection Program Support Small Business Activity?

2021-11-30T00:00:00.000-05:00

The COVID Shock to Online Retail: The persistence of new online shopping habits and implications for the future of cities

2021-11-15T00:00:00.000-05:00

Household Cash Balance Pulse: Family Edition

Last updated with September 2021 data

2021-10-21T00:00:00.000-05:00

How did landlords fare during COVID?

2021-10-18T00:00:00.000-05:00

The Online Platform Economy through the Pandemic

2021-09-21T00:00:00.000-05:00

How did the distribution of income growth change alongside the hot pre-pandemic labor market and recent fiscal stimulus?

2021-09-15T00:00:00.000-05:00

Household Finances Pulse: Cash Balances during COVID-19

Last updated with July 2021 data

2021-08-31T00:00:00.000-05:00

The Governor’s choice: Continue or end expanded unemployment benefits?

2021-08-17T00:00:00.000-05:00

Spending after Job Loss from the Great Recession through COVID-19

The Roles of Financial Health, Race, and Policy

2021-07-29T00:00:00.000-05:00

When unemployment insurance benefits are rolled back

Impacts on job finding and the recipients of the Pandemic Unemployment Assistance Program

2021-06-30T00:00:00.000-05:00

Financial outcomes by race during COVID-19

2021-06-23T00:00:00.000-05:00

Small Business Finances in Illinois during the COVID-19 Pandemic

2021-06-15T00:00:00.000-05:00

The Local Commerce Data Series

2021-05-04T00:00:00.000-05:00

Family cash balances, income, and expenditures trends through 2021

A distributional perspective

2021-04-19T00:00:00.000-05:00

Retail Spending Response to Local Conditions during COVID-19

2021-04-06T00:00:00.000-05:00

Local Commerce Data Series: Pandemic Spending

2021-04-01T00:00:00.000-05:00

Balancing accessibility and fraud prevention in housing assistance

2021-03-17T00:00:00.000-05:00

Who Benefits from Student Debt Cancellation?

2021-03-11T00:00:00.000-05:00

Renters vs. Homeowners

Income and Liquid Asset Trends during COVID-19

2021-03-04T00:00:00.000-05:00

Small business ownership and liquid wealth

2021-02-24T00:00:00.000-05:00

The First 100 Days and Beyond

Data-Driven Policies to Support Inclusive Economic Recovery and Equitable Long-Term Growth

2021-02-10T00:00:00.000-05:00

Unemployment insurance, job search, and spending during the pandemic

2021-01-27T00:00:00.000-05:00

The Paycheck Protection Program

Small Business Balances, Revenues, and Expenses in the Weeks after Loan Disbursement

2021-01-21T00:00:00.000+05:30

The Stock Market and Household Financial Behavior

2020-12-16T00:00:00.000-05:00

Household Cash Balances during COVID-19: A Distributional Perspective

2020-12-15T00:00:00.000-05:00

The New Year’s Cliff: How the Expiration of Unemployment Benefits Will Affect Families

2020-12-02T00:00:00.000-05:00

Tapping Home Equity

Income and Spending Trends Around Cash-Out Refinances and HELOCs

Did Mortgage Forbearance Reach the Right Homeowners?

Income and Liquid Assets Trends for Homeowners during the COVID-19 Pandemic

2020-11-19T00:00:00.000-05:00

Small Business Expenses during COVID-19

Home Advantage? Resident Retail Distances and Small Business Financial Outcomes

2020-10-15T00:00:00.000-05:00

The unemployment benefit boost: Initial trends in spending and saving when the $600 supplement ended

2020-10-01T00:00:00.000-05:00

Student Loan Debt: Who is Paying it Down?

Evidence from administrative banking data, credit bureau student loan data, and public records on race

2020-08-10T00:00:00.000+05:30

Expanded Unemployment Benefits and the Impact of Inaction

2020-07-31T00:00:00.000-05:00

Data Dialogue: The Initial Impact of COVID-19 on Consumer Spending and Local Economies

2020-07-22T00:00:00.000+05:30

Small Business Owner Race, Liquidity, and Survival

Racial Gaps in Small Business Outcomes

2020-07-20T00:00:00.000-04:00

Small Business Financial Outcomes during the COVID-19 Pandemic

2020-07-16T00:00:00.000-05:00

Report Consumption Effects of Unemployment Insurance during the COVID-19 Pandemic

2020-07-15T00:00:00.000-05:00

Consumption Effects of Unemployment Insurance during the COVID-19 Pandemic

2020-07-01T00:00:00.000-05:00

The Early Impact of COVID-19 on Local Commerce Report

Changes in Spend Across Neighborhoods and Online

2020-07-01T00:00:00.000+05:30

Fed watchers now turn their attention to September

2020-06-26T00:00:00.000+05:30

The Housing Wealth Effect in the Post-Great Recession Period

Evidence from Big Data

2020-06-25T00:00:00.000+05:30

Initial Impacts of the Pandemic Reflect that Families Changed their Saving and Spending Behavior

2020-06-24T00:00:00.000+05:30

Small Business Financial Outcomes during the Onset of COVID-19

2020-06-03T00:00:00.000+05:30

Data Dialogue: National Urban League, PolicyLink, and the Joint Center for Political and Economic Studies Discuss Racial, Economic, and Social Equity

The Early Impact of COVID-19 on Local Commerce

2020-05-29T00:00:00.000+05:30

Data Dialogue: The Economic Impacts of COVID-19 on Small Business

2020-05-27T00:00:00.000-04:00

The Initial Household Spending Response to COVID-19 Part 2

Evidence from Credit Card Transactions - Part 2

2020-05-20T00:00:00.000-04:00

Tracking Spillovers During the Taper Tantrum

Evidence from Institutional Investor Transactions in Emerging Markets

2020-05-14T00:00:00.000-04:00

The Initial Household Spending Response to COVID-19

Evidence from Credit Card Transactions

2020-05-04T00:00:00.000-04:00

How COVID-19 is impacting local economies and small businesses

A Cash Flow Perspective on the Small Business Sector

2020-04-20T00:00:00.000+05:30

Racial Gaps in Financial Outcomes

Big Data Evidence

2020-04-16T00:00:00.000-04:00

How COVID-19 could widen racial gaps in financial outcomes

2020-04-09T00:00:00.000-04:00

Forbearance for mortgages a short-term solution; savings programs for the long term

2020-04-01T00:00:00.000-04:00

Small Business Cash Liquidity in 25 Metro Areas

2020-03-31T00:00:00.000-05:00

Expanded unemployment insurance may lessen impact of layoffs

JPMorgan Chase Institute take

2020-03-31T00:00:00.000-04:00

Who benefits from a tax-payment deadline extension?

2020-03-24T00:00:00.000-04:00

Coronavirus may impact workers' income volatility

2020-03-20T00:00:00.000-04:00

Quick liquidity to small businesses could mitigate impacts from coronavirus

2020-03-06T00:00:00.000-05:00

Tax Refunds and Household Spending

2020-03-01T00:00:00.000-05:00

The potential economic impacts of COVID-19 on families, small businesses, and communities

Insights from five years of big data research

2019-12-04T00:00:00.000-05:00

Small Business Financial Outcomes in Miami Communities

2019-11-21T00:00:00.000-05:00

The Gender Gap: Exploring Consumer and Small Business Financial Health

2019-11-05T00:00:00.000-05:00

Financial and Physical Health in a Changing Healthcare Market

2019-10-31T00:00:00.000-04:00

Bridging the Gap

How Families Use the Online Platform Economy to Manage their Cash Flow

2019-10-23T00:00:00.000-04:00

Weathering Volatility 2.0

A Monthly Stress Test to Guide Savings

2019-09-30T00:00:00.000-04:00

Place Matters

Small Business Financial Health in Urban Communities

2019-09-26T00:00:00.000-04:00

In Conversation: Experts on Student Loan Payments and JPMC Institute Research

2019-08-12T00:00:00.000-04:00

Facing Uncertainty

Small Business Cash Flow Patterns in 25 U.S. Cities

2019-07-31T00:00:00.000+05:30

Data and Collaboration for Good

The JPMorgan Chase Institute 2nd Annual Conference on Economic Research

2019-07-01T00:00:00.000-04:00

Student Loan Payments

Evidence from 4 Million Families

2019-06-01T00:00:00.000-04:00

Trading Equity for Liquidity

Bank Data on the Relationship Between Liquidity and Mortgage Default

The San Francisco Economy

Household and Small Business Financial Outcomes

2019-05-09T00:00:00.000-04:00

How Data Can Improve the Financial Health of U.S. Small Businesses

2019-05-01T00:00:00.000-04:00

The Small Business Sector in Urban America

Growth and Vitality in 25 Cities

2019-04-01T00:00:00.000-05:00

The Online Platform Economy in 27 Metro Areas

The Experience of Drivers and Lessors

2019-03-22T00:00:00.000-05:00

Technology and the Future of Work

2019-03-01T00:00:00.000-05:00

How Families Manage Tax Refunds and Payments

2019-02-01T00:00:00.000-05:00

Gender, Age, and Small Business Financial Outcomes

2019-01-15T00:00:00.000-05:00

Does the Timing of Central Bank Announcements Matter?

Trade-Level Data on Hedge Fund Behavior Before Swiss National Bank Meetings

2018-12-04T00:00:00.000-05:00

Local Commerce Index

The Local Commerce Index (LCI) is a measure of the monthly year-over-year growth rate of everyday debit and credit card spending by over 64 million de-identified Chase customers across 14 metro areas in the US. The LCI is an alternative view of the health and vibrancy of the US consumer.

Estimating Family Income from Administrative Banking Data

A Machine Learning Approach

2018-12-01T00:00:00.000-05:00

Deferred Care

How Tax Refunds Enable Healthcare Spending

Shopping Near and Far: Local Commerce in the Digital Age

Insights from 4 Billion Transactions across the United States

2018-10-23T00:00:00.000-05:00

Measuring the Online Platform Economy

How Banking and Survey Data Compare

2018-10-01T00:00:00.000-04:00

Falling Behind

Bank Data on the Role of Income and Savings in Mortgage Default

On the Rise

Out-of-Pocket Healthcare Spending in 2017

2018-09-01T00:00:00.000-05:00

The Online Platform Economy in 2018

Drivers, Workers, Sellers, and Lessors

2018-08-29T00:00:00.000-04:00

JPMorgan Chase Institute 2018 Inaugural Conference on Economic Research

2018-07-01T00:00:00.000-04:00

Growth, Vitality, and Cash Flows

High-Frequency Evidence from 1 Million Small Businesses

2018-06-20T00:00:00.000-05:00

Where are all the Contingent Workers?

2018-06-12T00:00:00.000-04:00

FX Markets Move on Surprise News

Institutional Investor Trading Behavior around Brexit, the U.S. Election, and the Swiss Franc Floor

2018-04-01T00:00:00.000-04:00

Filing Taxes Early, Getting Healthcare Late

Insights from 1.2 Million Households

2018-03-15T00:00:00.000-04:00

Healthcare When It’s Needed

How to Mitigate High Costs and Deferred Care

2018-03-01T00:00:00.000-05:00

The Commercial Vibrancy of Chicago Neighborhoods, 2016

2018-02-01T00:00:00.000-05:00

Bend, Don’t Break

Small Business Financial Resilience After Hurricanes Harvey and Irma

Weathering the Storm

The Financial Impacts of Hurricanes Harvey and Irma on One Million Households

Local Consumer Commerce in the Wake of a Hurricane

2017-12-14T00:00:00.000-05:00

Institute Insights for Open Enrollment

2017-12-01T00:00:00.000-05:00

Mortgage Modifications after the Great Recession

New Evidence and Implications for Policy

2017-11-01T00:00:00.000-04:00

Paying a Premium

Dynamics of the Small Business Owner Health Insurance Market

2017-10-10T00:00:00.000-04:00

Younger and Lower Income Consumers Drive Small Business Spending

2017-09-06T00:00:00.000-04:00

Coping with Medical Costs through Life

2017-09-01T00:00:00.000-04:00

Paying Out-of-Pocket

The Healthcare Spending of 2 Million U.S. Families

Mapping Segments in the Small Business Sector

2017-05-01T00:00:00.000-04:00

The Gender Gap in Financial Outcomes

The Impact of Medical Payments

2017-04-20T00:00:00.000-04:00

The Consumer Spending Response to Mortgage Resets

2017-04-01T00:00:00.000-04:00

The Consumer Spending Response to Mortgage Resets Report

Microdata on Monetary Policy

2017-03-17T00:00:00.000-04:00

The Monthly Stress-Test on Family Finances

2017-03-01T00:00:00.000-05:00

Consumption Inequality

What’s in Your Shopping Basket?

Going the Distance

Big Data on Resident Access to Everyday Goods

Seniors Lead the Slowdown in Local Consumer Commerce

2017-02-09T00:00:00.000-05:00

Why Managing Expenses Is Not an Easy Task

2017-02-01T00:00:00.000-05:00

Coping with Costs

Big Data on Expense Volatility and Medical Payments

2017-01-18T00:00:00.000-05:00

The Ups and Downs of Small Business Employment

2017-01-01T00:00:00.000-05:00

The Ups and Downs of Small Business Employment Report

Big Data on Payroll Growth and Volatility

2016-11-15T00:00:00.000-05:00

Is the Online Platform Economy the Future of Work?

2016-11-01T00:00:00.000-05:00

The Online Platform Economy

Has Growth Peaked?

2016-11-01T00:00:00.000-04:00

Shedding Light on Daylight Saving Time

2016-09-21T00:00:00.000-04:00

For Small Businesses: Cash is King

2016-09-09T00:00:00.000-04:00

Big Spend on the Weekend:

The Local Consumer Commerce Index declined in May

2016-09-01T00:00:00.000-04:00

Cash is King: Flows, Balances, and Buffer Days

Evidence from 600,000 Small Businesses

2016-08-18T00:00:00.000-05:00

Past 65 and Still Working

Big Data Insights on Senior Citizens’ Financial Lives

2016-07-14T00:00:00.000-04:00

A Year of Low Gas Prices: The Consumer Response in 15 Metro Areas

2016-07-11T00:00:00.000-04:00

The Consumer Response to Lower Gas Prices

2016-07-01T00:00:00.000-04:00

The Consumer Response to a Year of Low Gas Prices

Evidence From 1 Million People

2016-06-29T00:00:00.000-04:00

Good Things Come in Small (Business) Packages

2016-05-05T00:00:00.000-05:00

The Online Platform Economy: Who earns the most?

2016-04-13T00:00:00.000-04:00

Taking the Financial Stress Out of Tax Time

2016-03-29T00:00:00.000-04:00

The Local Consumer Commerce Index

How did everyday spending fare in December 2015?

2016-02-18T00:00:00.000-05:00

Understanding Income Volatility and the Role of the Online Platform Economy

2016-02-09T00:00:00.000-05:00

Dining Out or Eating In: Where does your city rank?

Spending Growth at Restaurants

2016-02-08T00:00:00.000-05:00

Consumption Inequality: Where does your city rank?

Spending by the Top Income Quintile

2016-02-04T00:00:00.000-05:00

Travel for Business or Pleasure: Where does your city rank?

Share of Spending by Visitors to the Metro Area

2016-02-01T00:00:00.000-05:00

Paychecks, Paydays, and the Online Platform Economy

Big Data on Income Volatility

The Online Platform Economy Trajectory

What is the growth trajectory?

2016-01-31T00:00:00.000-05:00

Recovering from Job Loss

The Role of Unemployment Insurance

2016-01-18T00:00:00.000-05:00

Economic Contributions by Seniors

Spending by Consumers 65 years and Older

2016-01-07T00:00:00.000-05:00

Big Data to Build Sharper Profiles of Consumer Commerce at the City Level

2016-01-01T00:00:00.000-05:00

Boutiques or Big Box Stores: Where does your city rank?

Share of Spending at Small and Medium Enterprises

2015-12-01T00:00:00.000-05:00

Profiles of Local Consumer Commerce

Insights from 12 Billion Transactions in 15 U.S. Metro Areas

2015-10-01T00:00:00.000-04:00

How Falling Gas Prices Fuel the Consumer

Evidence From 25 Million People

2015-05-01T00:00:00.000-04:00

Weathering Volatility

Big Data on the Financial Ups and Downs of U.S. Individuals

Small Business Data Resources

Diverse Ownership

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Regional Employment

Economic Activity

Where did recent gas price declines affect consumers the most?

JPMCI HOSP Geographic Data Visualization Tool

Major Market Events Data Visualization Tool

Infographic: How Falling Gas Prices Fuel the Consumer

Infographic: Weathering Volatility

Small Business Data Dashboard

Small businesses are an economically important component of the US economy and a key driver of production, employment, and growth.

How Much Cash Buffer Do You Need?

Data Visualization

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Global Banking Annual Review 2023: The Great Banking Transition

The Global Banking Annual Review 2023: The Great Banking Transition

Banking has had to chart a challenging course over the past few years, during which institutions faced increased oversight, digital innovation, and new competitors, and all at a time when interest rates were at historic lows. The past few months have also brought their share of upsets, including liquidity woes and some bank failures. But, broadly speaking, a favorable wind seems to have returned to the industry’s sails. The past 18 months have been the best period for global banking overall since at least 2007, as rising interest rates have boosted profits in a more benign credit environment.

About the authors

This report is a collaborative effort by Debopriyo Bhattacharyya, Miklós Dietz , Alexander Edlich , Reinhard Höll , Asheet Mehta , Brian Weintraub , and Eckart Windhagen , representing views from McKinsey’s Global Banking Practice.

Below the surface, too, much has changed: balance sheet and transactions have increasingly moved out of traditional banks to nontraditional institutions and to parts of the market that are capital-light and often differently regulated—for example, to digital payments specialists and private markets, including alternative asset management firms. While the growth of assets under management outside of banks’ balance sheets is not new, our analysis suggests that the traditional core of the banking sector—the balance sheet—now finds itself at a tipping point. Given the size of this movement, we have broadened the scope of this year’s Global Banking Annual Review to define banks as including all financial institutions except insurance companies.

In this year’s review, we focus on this “Great Banking Transition,” analyzing causes and effects and considering whether the improved performance in 2022–23 and the recent rise in interest rates in many economies could change its dynamics. To conclude, we suggest five priorities for financial institutions as they look to reinvent and future-proof themselves. The five are: exploiting leading technologies (including AI), flexing and potentially even unbundling the balance sheet, scaling or exiting transaction business, leveling up distribution, and adapting to the evolving risk landscape .

All financial institutions will need to examine each of their businesses to assess where their competitive advantages lie across and within the three core banking activities of balance sheet, transactions, and distribution. And they will need to do so in a world in which technology and AI will play a more prominent role, and against the backdrop of a shifting macroeconomic environment and heightened geopolitical risks.

The past 18 months brought banks their highest highs and lowest lows

The recent upturn arises from the sharp increase in interest rates in many advanced economies, including a 500-basis-point rise in the United States. The higher interest rates enabled a long-awaited improvement in net interest margins, which boosted the sector’s profits by about $280 billion in 2022 and lifted return on equity (ROE) to 12 percent in 2022 and an expected 13 percent in 2023, compared with an average of just 9 percent since 2010 (Exhibit 1).

Over the past year, the banking sector has continued its journey of continuous cost improvement: the cost-income ratio dropped by seven percentage points from 59 percent in 2012 to about 52 percent in 2022 (partially driven by margin changes), and the trend is also visible in the cost-per-asset ratio (which declined from 1.6 to 1.5).

See past reports:

• 2022: Banking on a sustainable path
• 2021: The great divergence
• 2020: A test of resilience
• 2019: The last pit stop? Time for bold late-cycle moves
• 2018: Banks in the changing world of financial intermediation
• 2017: Remaking the bank for an ecosystem world
• 2016: A brave new world for global banking
• 2015: The fight for the customer
• 2014: The road back

The ROE growth was accompanied by volatility over the past 18 months. This contributed to the collapse or rescue of high-profile banks in the United States and the government-brokered takeover of one of Switzerland’s oldest and biggest banks. Star performers of past years, including fintechs and cryptocurrency players, have struggled against this backdrop.

Performance varied widely within categories. While some financial institutions across markets have generated a premium ROE, strong growth in earnings, and above-average price-to-earnings and price-to-book multiples, others have lagged (Exhibit 2). While more than 40 percent of payments providers have an ROE above 14 percent, almost 35 percent have an ROE below 8 percent. Among wealth and asset managers, who typically have margins of about 30 percent, more than one-third have an ROE above 14 percent, while more than 40 percent have an ROE below 8 percent. Bank performance varies significantly, too. These variations indicate the extent to which operational excellence and decisions relating to cost, efficiency, customer retention, and other issues affecting performance are more important than ever for banking. Strongest performers tend to use the balance sheet effectively, are customer centric, and often lead on technology usage.

Between 2017 and 2022, payment providers, capital market infrastructure providers, and asset managers, as well as investment banks and brokers-dealers increased their price to earnings, whereas other financial institutions including GSIB (global systematically important banks), universal banks, and nonbank lenders saw a decline in their price to earnings.

Payment providers, investment banks and broker dealers also increased their earnings per share more than the other types of institutions. Consequently, these two types of institutions come out best in terms of value creation and total return to shareholders among financial institutions during this five-year period.

The geographic divergence we have noted in previous years also continues to widen. Banks grouped along the crescent formed by the Indian Ocean, stretching from Singapore to India, Dubai, and parts of eastern Africa, are home to half of the best-performing banks in the world (Exhibit 3). In other geographies, many banks buoyed by recent performance are able to invest again. But in Europe and the United States, as well as in China and Russia, banks overall have struggled to generate their cost of capital.

One aspect of banking hasn’t changed, however: the price-to-book ratio, which was at 0.9 in 2022. This measure has remained flat since the 2008 financial crisis and stands at a historic gap to the rest of the economy—a reflection that capital markets expect the duration-weighted return on equity to remain below the cost of equity. While the price-to-book ratio reflects some of the long-term systematic challenges the sector is facing, it also suggests the possible upside: every 0.1-times improvement in the price-to-book ratio would cause the sector’s value added to increase by more than $1 trillion.

Looking to the future, the outlook for financial institutions is likely to be especially shaped by four global trends. First, the macroeconomic environment has shifted substantially, with higher interest rates and inflation figures in many parts of the world, as well as a possible deceleration of Chinese economic growth. An unusually broad range of outcomes is suddenly possible, suggesting we may be on the cusp of a new macroeconomic era. Second, technological progress continues to accelerate, and customers are increasingly comfortable with and demanding about technology-driven experiences. In particular, the emergence of generative AI could be a game changer, lifting productivity by 3 to 5 percent and enabling a reduction in operating expenditures of between $200 billion and $300 billion, according to our estimates. Third, governments are broadening and deepening regulatory scrutiny of nontraditional financial institutions and intermediaries as the macroeconomic system comes under stress and new technologies, players, and risks emerge. For example, recently published proposals for a final Basel III “endgame” would result in higher capital requirements for large and medium-size banks, with differences across banks. And fourth, systemic risk is shifting in nature as rising geopolitical tensions increase volatility and spur restrictions on trade and investment in the real economy.

The Great Transition for the balance sheet, transactions, and payments has gained momentum

In this context, the future dynamics of the Great Transition are critical for the banking sector overall. Evidence of the transition’s profound effect on the sector to date abounds. For example, between 2015 and 2022, more than 70 percent of the net increase of financial funds ended up off banking balance sheets, held by insurance and pension funds, sovereign wealth funds and public pension funds, private capital, and other alternative investments, as well as retail and institutional investors (Exhibit 4).

The shift off the balance sheet is a global phenomenon (Exhibit 5). In the United States, 75 percent of the net increase in financial funds ended up off banking balance sheets, while the figure in Europe is about 55 percent.

The growth of private debt is another manifestation of the transition away from traditional financial institutions. Private debt saw its highest inflows in 2022, with growth of 29 percent, driven by direct lending.

Beyond the balance sheet, transactions and payments also are shifting. For example, consumer digital payment processing conducted by payments specialists grew by more than 50 percent between 2015 and 2022 (Exhibit 6).

The oscillating interest rate environment will affect the Great Transition, but exactly how remains to be seen. We may be going through a phase in which a long-term macroeconomic turning point—including a higher-for-longer interest rate scenario and an end to the asset price super cycle—changes the attractiveness of some models that were specifically geared to the old environment, while other structural trends, especially in technology, continue. Fundamentally, the question for banks is to what extent they can offer the products in high demand at a time when risk capacity is broadening and many clients and customers are searching for the highest deposit yields.

Focusing on five priorities can help banks capture the moment

Regardless of the macroeconomic developments, financial institutions will have to adapt to the changing environment of the Great Transition, especially the trends of technology, regulation, risk, and scale. Mergers and acquisitions may gain importance.

As financial institutions consider how they want to change, we outline five priorities which, though not an exhaustive list, can serve as thought starters (Exhibit 7).

• Exploit technology and AI to improve productivity, talent management, and the delivery of products and services. This includes applying AI and advanced analytics to deploy process automation, platforms, and ecosystems. Other principles associated with success include operating more like a tech company to scale the delivery of products and services; cultivating a cloud-based, platform-oriented architecture; and improving capabilities to address technology risks. Distinctive technology development and deployment will increasingly become a critical differentiator for banks.
• Flex and even unbundle the balance sheet. Flexing implies active use of syndication, originate-to-distribute models, third-party balance sheets (for example, as part of banking-as-a-service applications), and a renewed focus on deposits. Unbundling, which can be done to varying degrees and in stages, pushes this concept further and can mean separating out customer-facing businesses from banking as a service and using technology to radically restructure costs.
• Scale or exit transaction business. Scale in a market or product is a key to success, but it can be multifaceted. Institutions can find a niche in which to go deep, or they can look to cover an entire market. Banks can aggressively pursue economies of scale in their transactions business, including through M&A (which has been a major differentiator between traditional banks and specialists) or by leveraging partners to help with exits.
• Level up distribution to sell to customers and advise them directly and indirectly, including through embedded finance and marketplaces and by offering digital and AI-based advisory. An integrated omnichannel approach could make the most of automation and human interaction, for example. Deciding on a strategy for third-party distribution—which could be via partnerships to create embedded finance opportunities or platform-based models—can create opportunities to serve customer needs including with products outside the institution’s existing business models.
• Adapt to changing risks. Financial institutions everywhere will need to stay on top of the ever-evolving risk environment. In the macroeconomic context, this includes inflation, an unclear growth outlook, and potential credit challenges in specific sectors such as commercial real estate exposure. Other risks are associated with changing regulatory requirements, cyber and fraud risk, and the integration of advanced analytics and AI into the banking system. To manage these risks, banks could consider elevating the risk function to make it a true differentiator. For example, in client discussions, product design, and communications they could highlight the bank’s resilience based on its track record of managing systemic risk and liquidity. They could also further strengthen the first line and embed risk in day-to-day activities, including investing in new risk activities driven by the growth of generative AI. Underlying changes in the real economy will likely continue in unexpected ways, requiring banks to remain ever more vigilant.

All these priorities have significant implications for financial institutions’ capital plans, including the more active raising and return of capital. As financial institutions reexamine their businesses and identify their relative competitive advantages in each of the balance sheet, transactions, and distribution components, they will need to ensure that they are positioned to generate adequate returns. And they will need to do so in a very different macroeconomic and geopolitical environment and at a time when AI and other technologies are potentially changing the environment and with a broader set of competitors. Scale and specialization will be determinant, as will value-creating diversification. Minimum economies of scale are also likely to shift, especially where technology and data are the drivers of scale. The years ahead will likely be more dynamic than the immediate past, with the gap between winners and losers increasing even more. Now is the time to begin charting the path forward.

Debopriyo Bhattacharyya is a director of solution delivery in McKinsey’s Gurugram office;  Miklós Dietz is a senior partner in the Vancouver office; Alexander Edlich and Asheet Mehta are senior partners in the New York office, where Brian Weintraub is a partner; Reinhard Höll is a partner in the Berlin office, and Eckart Windhagen is a senior partner in the Frankfurt office.

The authors would like to thank the following colleagues for their contributions to this report: Mayank Aggarwal, Krishna Bhattacharya, Alessio Botta, Andrea Cappo, Miguel Leiria Carvalho, Cristina Catania, Matt Cooke, Alison Corsi, Julie Crothers, Anubhav Das, Chris Depin, Thorsten Ehinger, Nnenna Elumogo, Xiyuan Fang, Fuad Faridi, Max Flötotto, Suhrid Gajendragadkar, Jeff Galvin, Amit Garg, Jonathan Godsall, Peter Gumbel, Nils Jean-Mairet, Rushabh Kapashi, Attila Kincses, Ida Kristensen, Matthieu Lemerle, Kate McCarthy, Jared Moon, Jesus Moreno, Marie-Claude Nadeau, Jatin Pant, Thomas Poppensieker, Angela Samper, Gokhan Sari, Manu Saxena, Kai Schindelhauer, Simone Schöberl, Joydeep Sengupta, Vishnu Sharma, Mark Staples, Vik Sohoni, Gregor Theisen, Marco Vettori, and Nicole Zhou.

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Key opportunity spaces for the pharmaceuticals sector in 2024.

Chris: Heading into 2024, we're seeing a really exciting opportunity to revisit the pharmaceutical sector given some of the underperformance we saw in 2023. We've got investors sentiments actually pretty bearish for the group right now. And we think that's going to be a really nice opportunity for investors to look at a fairly well positioned group at record low valuations.

Chris: We're really excited about the innovation more broadly across the sector. If you just think about 2023, we had the first disease modifying Alzheimer's drug fully approved by the FDA. If you look at oncology market, we had new technologies, things like CAR-T, bispecific antibodies, ADCs, meaningfully improving standard of care in a number of tumor types. These are huge markets where you haven't seen innovation in the last decade or longer.

Chris: The GLP one category. This year has been really an exciting year. We're estimating that this will be over a hundred billion revenue opportunity for the sector by the time we go out to the early 2030s. And that would make the GLP-1s the largest therapeutic market we've ever seen. We're expecting the capacity for the GLP-1s to double in 2024, increase another 50% in 2025, and that should really alleviate the bottlenecks we have from the capacity standpoint.

Chris: As we think about M&A, the themes really remain growth and innovation and that should lead to further consolidation of the small and mid-cap biotech sector, particularly the higher quality names. What we're seeing is a pivot away from larger, more complex transactions that we saw in the past. And instead what the industry seems to be doing is looking at these kind of smaller assets that are easier to integrate.

Chris: As I think about healthcare reform, the big focus for us is going to be on drug price negotiations. This is really coming about because of the inflation reduction act, which is allowing the US government for the first time to directly negotiate drug pricing with the pharmaceutical industry. Many of these are going to make drugs more affordable for seniors, which is great. But for the drug industry specifically, we're got to really watch to see how these negotiations go. It's a big overhang for the sector. One we think is manageable, but obviously we've got to watch exactly how these negotiations play out.

Lisa: Things to watch for in 2024 when we think about healthcare services specific to managed care and facilities, one, utilization trends. If you think about 2023, we saw an uptick in Medicare advantage utilization trends, we anticipate that those trends will carry forward into the first half of 2024. Second, GLP-1, the impact on both sides. How will this impact the commercial market? How will it impact PBMs? Third, the presidential election.

Lisa: GLP-1 were a big area of topic in 2023. They are currently not covered by Medicare or Medicaid. However, as we move into 2024, We'll need a legislative change for them to be covered.

We recently conducted a survey of 50 of the top 500 companies in the country, a large percentage of them are saying they're not going to cover it for weight loss, so we'll have to wait and see what happens.

Lisa: As we think about the medical costs and pharmacy costs in 24, we're getting back to normalization. Post covid, we had two years where people did not go to the doctor. They did not have surgical procedures done.

We had anticipated coming into 23 that we would see a higher acuity level. what we saw this year is that both cardiac procedures as well as orthopedic procedures, were higher than expected.

As we go into 2024, we expect that trend to continue within Medicare Advantage. On the commercial side, we have generally seen in line, utilization trends across the commercial population.

Lisa: As we think about potential legislative changes for the PBM, pharmacy benefit management business. One of the areas that they're trying to drive is more transparency in the business model. We believe any of the legislation is pretty benign to the current industry as we see it and therefore remain positive on the industry.

Environmental Social Governance is growing in every geography around the globe. It’s in the headlines, high up on the agendas of corporations, and at the forefront of investor interest.

Even though it started to take shape in the 1960s, ESG has gained significant momentum in recent years, with 2020 standing out as a milestone year in this space. Adoption across the global asset management industry more than doubled, with total ESG funds growing more than 100 percent. And companies are now rally more ambitious ESG goals.

What’s driving the move from momentum to mainstream?

This is ESG Investing, Unpacked.

ESG Investing looks at an asset, like equities or bonds, through an Environmental, Social and Governance lens.

The goal is to determine whether the asset makes a positive impact. For example, fighting climate change or supporting safe working conditions. Governance is all about how a company balances stakeholder interests: How are decisions made? What processes are in place? Who benefits?

Here’s another way to think about it: The “E” and “S” are the end results. The “G” determines how these results are achieved.

This data helps investors make better-informed decisions.

The rise of ESG investing is based on a few points in history. Among them are the social movements against the Vietnam war and apartheid in South Africa, when companies faced divestments in opposition.

In 1981, the first major U.S. organization that advances responsible investing was founded: The U.S. Sustainable Investment Forum. And key events created global awareness of environmental issues.

In 2008, the Financial Crisis called into question the industry’s social license to operate: How can the financial system works for everyone and not just shareholders? In 2015, 196 countries signed the Paris Agreement to reduce carbon emissions.

Most recently, the COVID-19 pandemic demonstrated the connectivity between crises: Public health, climate change and social inequality. In response, companies prioritized even more ambitious goals around ESG.

Three main ESG Investing strategies are growing quickly. Negative Screening typically excludes investments related to weapons, tobacco and fossil fuels. While exclusions were historically based on moral or religious preferences, now it’s about the financial risk associated with the negative impact of industries, such as human health for tobacco and climate change for fossil fuels.

ESG Integration has become the leading strategy. It focuses on how companies incorporate ESG criteria into their daily activities to achieve long-term financial performance. Then, ESG considerations and timelines are factored into risk analysis and investment decisions moving forward.

Impact Investing is the newest strategy. It intentionally aims to create positive social and environmental impact that is actively measured, as well as financial return. Like investing in the private debt of a company with a business model aimed at providing access to high-quality education for students from low-income backgrounds. Impact Investing is becoming increasingly common because more people want their money to contribute to the United Nation’s Sustainable Development Goals.

The ESG lens can be applied to any asset class. While equity is the most common, representing half of total ESG assets under management, green bonds are on the rise. Typically purchased by institutional investors, they help finance a company’s specific project climate-related or environmental project.

Sustainability-linked bonds are also gaining traction. These are performance-based and tied to whether the issuer achieves pre-defined ESG objectives within a set timeline.

Many investors are now looking beyond ESG targets and are increasingly focused on measurable results with clear plans. This trend, along with wanting more of a say in a company’s ESG practices, is expected to continue for the next several years.

Heightened regulation including environmental, employment, and civil protections, is another factor driving ESG market growth. Around 90 percent of oversight was implemented in the last 20 years and 50 percent arrived after 2010.

Europe leads this effort, where public companies are required to report implemented policies and where regulations are constantly evolving to reflect broader sustainability goals. Take the EU Green Deal, a set of policies to help the EU reduce emissions 55 percent by 2030 and reach net zero by 2050.

But sustainability challenges are global and require mobilized capital to solve them, all countries are working on ESG. Asia is beginning to implement its own regulations, and the U.S. administration is currently working on its own standards as well.

For the next several years, innovation will continue to shape the ESG landscape. From advancements in clean energy, like the growing hydrogen market, to how companies will deliver on advancing racial equality, and the upcoming public investments on clean infrastructures, all eyes are on ESG.

How healthy is the US economy? Could a recession be coming? How do investors feel about the current economic situation?

While none of us can see into the future, yield curves can help us map what lies ahead, answering these questions and many more with surprisingly-high levels of accuracy. So what exactly is a yield curve and how can one little line tell us so much? "

This is "Yield Curves: Unpacked.

In a nutshell, a yield curve is found on a graph that compares bond yields to maturity dates. Once plotted, the points are joined together with a line, forming the familiar yield curve. Here are four terms you'll need to understand to wrap your head around yield curves.

Bonds are debt securities issued by governments and corporations to raise money. In other words, bonds are a loan from an investor to an issuer. If an investor buys a Treasury bond, for example, they're essentially lending money to the U.S. government. Coupons are fixed interest payments, which investors receive periodically. This is the same as the interest paid on any loan, such as a mortgage or personal loan.

Maturity is when a bond's term comes to an end. This can be from 1 year to more than 10 years. At this point, the investor will get back the money they paid for the bond.

Yields are the returns made on a bond. The simplest version of yield is calculated by dividing the interest rate by the bond's current market price. Longer-term bonds will have higher yields-- in a stable economic environment, anyway. This is because they're considered riskier investments, as there's more time for market conditions and bond prices to change.

While a price change doesn't affect the fixed coupon payment, it does affect the yield. When prices go up, yields go down, making the bond less appealing. When long-term bonds have higher yields than short-term bonds, this forms the typical upward slope of a yield curve from left to right. A steeper slope can signal better economic conditions ahead, with higher growth and inflation, meaning better returns on long-term bonds.

Yield curves can also invert and slope in the opposite direction. This happens when short-term bonds have higher yields than long-term bonds. It's rare, but it can signal that an economic slowdown or even a recession is coming. This is particularly true of the U.S. Treasury yield curve, which tracks yields on short- and long-term treasuries. If you hear someone talking about the yield curve, they're likely referring to this one. And it's predicted past recessions with a great degree of accuracy.

How is this possible? First, the Treasury yield curve is a good reflection of investor sentiment. If investors expect interest rates to fall in the future, they might buy longer-term bonds to lock in the current rate, pushing up the price and lowering the yield. This is one way a yield curve can invert.

Low interest rates are usually associated with a weak economic environment, which is why this pattern can spell bad news for the economy-- if investors are correct, of course. Another reason is simply that the Treasury yield curve is so widely watched. Potential signs of a flattening curve may be enough to put markets in a spin.

There can be many reasons behind the pattern seen on a yield curve. And it's hard to account for all the forces at play within the bond market. But whatever the reasons might be, the Treasury yield curve will remain a strong signal of economic activity.

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• Open access
• Published: 18 June 2021

Financial technology and the future of banking

• Daniel Broby   ORCID: orcid.org/0000-0001-5482-0766 1  

Financial Innovation volume  7 , Article number:  47 ( 2021 ) Cite this article

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This paper presents an analytical framework that describes the business model of banks. It draws on the classical theory of banking and the literature on digital transformation. It provides an explanation for existing trends and, by extending the theory of the banking firm, it illustrates how financial intermediation will be impacted by innovative financial technology applications. It further reviews the options that established banks will have to consider in order to mitigate the threat to their profitability. Deposit taking and lending are considered in the context of the challenge made from shadow banking and the all-digital banks. The paper contributes to an understanding of the future of banking, providing a framework for scholarly empirical investigation. In the discussion, four possible strategies are proposed for market participants, (1) customer retention, (2) customer acquisition, (3) banking as a service and (4) social media payment platforms. It is concluded that, in an increasingly digital world, trust will remain at the core of banking. That said, liquidity transformation will still have an important role to play. The nature of banking and financial services, however, will change dramatically.

Introduction

The bank of the future will have several different manifestations. This paper extends theory to explain the impact of financial technology and the Internet on the nature of banking. It provides an analytical framework for academic investigation, highlighting the trends that are shaping scholarly research into these dynamics. To do this, it re-examines the nature of financial intermediation and transactions. It explains how digital banking will be structurally, as well as physically, different from the banks described in the literature to date. It does this by extending the contribution of Klein ( 1971 ), on the theory of the banking firm. It presents suggested strategies for incumbent, and challenger banks, and how banking as a service and social media payment will reshape the competitive landscape.

The banking industry has been evolving since Banca Monte dei Paschi di Siena opened its doors in 1472. Its leveraged business model has proved very scalable over time, but it is now facing new challenges. Firstly, its book to capital ratios, as documented by Berger et al ( 1995 ), have been consistently falling since 1840. This trend continues as competition has increased. In the past decade, the industry has experienced declines in profitability as measured by return on tangible equity. This is partly the result of falling leverage and fee income and partly due to the net interest margin (connected to traditional lending activity). These trends accelerated following the 2008 financial crisis. At the same time, technology has made banks more competitive. Advances in digital technology are changing the very nature of banking. Banks are now distributing services via mobile technology. A prolonged period of very low interest rates is also having an impact. To sustain their profitability, Brei et al. ( 2020 ) note that many banks have increased their emphasis on fee-generating services.

As Fama ( 1980 ) explains, a bank is an intermediary. The Internet is, however, changing the way financial service providers conduct their role. It is fundamentally changing the nature of the banking. This in turn is changing the nature of banking services, and the way those services are delivered. As a consequence, in order to compete in the changing digital landscape, banks have to adapt. The banks of the future, both incumbents and challengers, need to address liquidity transformation, data, trust, competition, and the digitalization of financial services. Against this backdrop, incumbent banks are focused on reinventing themselves. The challenger banks are, however, starting with a blank canvas. The research questions that these dynamics pose need to be investigated within the context of the theory of banking, hence the need to revise the existing analytical framework.

Banks perform payment and transfer functions for an economy. The Internet can now facilitate and even perform these functions. It is changing the way that transactions are recorded on ledgers and is facilitating both public and private digital currencies. In the past, banks operated in a world of information asymmetry between themselves and their borrowers (clients), but this is changing. This differential gave one bank an advantage over another due to its knowledge about its clients. The digital transformation that financial technology brings reduces this advantage, as this information can be digitally analyzed.

Even the nature of deposits is being transformed. Banks in the future will have to accept deposits and process transactions made in digital form, either Central Bank Digital Currencies (CBDC) or cryptocurrencies. This presents a number of issues: (1) it changes the way financial services will be delivered, (2) it requires a discussion on resilience, security and competition in payments, (3) it provides a building block for better cross border money transfers and (4) it raises the question of private and public issuance of money. Braggion et al ( 2018 ) consider whether these represent a threat to financial stability.

The academic study of banking began with Edgeworth ( 1888 ). He postulated that it is based on probability. In this respect, the nature of the business model depends on the probability that a bank will not be called upon to meet all its liabilities at the same time. This allows banks to lend more than they have in deposits. Because of the resultant mismatch between long term assets and short-term liabilities, a bank’s capital structure is very sensitive to liquidity trade-offs. This is explained by Diamond and Rajan ( 2000 ). They explain that this makes a bank a’relationship lender’. In effect, they suggest a bank is an intermediary that has borrowed from other investors.

Diamond and Rajan ( 2000 ) argue a lender can negotiate repayment obligations and that a bank benefits from its knowledge of the customer. As shall be shown, the new generation of digital challenger banks do not have the same tradeoffs or knowledge of the customer. They operate more like a broker providing a platform for banking services. This suggests that there will be more than one type of bank in the future and several different payment protocols. It also suggests that banks will have to data mine customer information to improve their understanding of a client’s financial needs.

The key focus of Diamond and Rajan ( 2000 ), however, was to position a traditional bank is an intermediary. Gurley and Shaw ( 1956 ) describe how the customer relationship means a bank can borrow funds by way of deposits (liabilities) and subsequently use them to lend or invest (assets). In facilitating this mediation, they provide a service whereby they store money and provide a mechanism to transmit money. With improvements in financial technology, however, money can be stored digitally, lenders and investors can source funds directly over the internet, and money transfer can be done digitally.

A review of financial technology and banking literature is provided by Thakor ( 2020 ). He highlights that financial service companies are now being provided by non-deposit taking contenders. This paper addresses one of the four research questions raised by his review, namely how theories of financial intermediation can be modified to accommodate banks, shadow banks, and non-intermediated solutions.

To be a bank, an entity must be authorized to accept retail deposits. A challenger bank is, therefore, still a bank in the traditional sense. It does not, however, have the costs of a branch network. A peer-to-peer lender, meanwhile, does not have a deposit base and therefore acts more like a broker. This leads to the issue that this paper addresses, namely how the banks of the future will conduct their intermediation.

In order to understand what the bank of the future will look like, it is necessary to understand the nature of the aforementioned intermediation, and the way it is changing. In this respect, there are two key types of intermediation. These are (1) quantitative asset transformation and, (2) brokerage. The latter is a common model adopted by challenger banks. Figure  1 depicts how these two types of financial intermediation match savers with borrowers. To avoid nuanced distinction between these two types of intermediation, it is common to classify banks by the services they perform. These can be grouped as either private, investment, or commercial banking. The service sub-groupings include payments, settlements, fund management, trading, treasury management, brokerage, and other agency services.

How banks act as intermediaries between lenders and borrowers. This function call also be conducted by intermediaries as brokers, for example by shadow banks. Disintermediation occurs over the internet where peer-to-peer lenders match savers to lenders

Financial technology has the ability to disintermediate the banking sector. The competitive pressures this results in will shape the banks of the future. The channels that will facilitate this are shown in Fig.  2 , namely the Internet and/or mobile devices. Challengers can participate in this by, (1) directly matching borrows with savers over the Internet and, (2) distributing white labels products. The later enables banking as a service and avoids the aforementioned liquidity mismatch.

The strategic options banks have to match lenders with borrowers. The traditional and challenger banks are in the same space, competing for business. The distributed banks use the traditional and challenger banks to white label banking services. These banks compete with payment platforms on social media. The Internet heralds an era of banking as a service

There are also physical changes that are being made in the delivery of services. Bricks and mortar branches are in decline. Mobile banking, or m-banking as Liu et al ( 2020 ) describe it, is an increasingly important distribution channel. Robotics are increasingly being used to automate customer interaction. As explained by Vishnu et al ( 2017 ), these improve efficiency and the quality of execution. They allow for increased oversight and can be built on legacy systems as well as from a blank canvas. Application programming interfaces (APIs) are bringing the same type of functionality to m-banking. They can be used to authorize third party use of banking data. How banks evolve over time is important because, according to the OECD, the activity in the financial sector represents between 20 and 30 percent of developed countries Gross Domestic Product.

In summary, financial technology has evolved to a level where online banks and banking as a service are challenging incumbents and the nature of banking mediation. Banking is rapidly transforming because of changes in such technology. At the same time, the solving of the double spending problem, whereby digital money can be cryptographically protected, has led to the possibility that paper money will become redundant at some point in the future. A theoretical framework is required to understand this evolving landscape. This is discussed next.

The theory of the banking firm: a revision

In financial theory, as eloquently explained by Fama ( 1980 ), banking provides an accounting system for transactions and a portfolio system for the storage of assets. That will not change for the banks of the future. Fama ( 1980 ) explains that their activities, in an unregulated state, fulfil the Modigliani–Miller ( 1959 ) theorem of the irrelevance of the financing decision. In practice, traditional banks compete for deposits through the interest rate they offer. This makes the transactional element dependent on the resulting debits and credits that they process, essentially making banks into bookkeeping entities fulfilling the intermediation function. Since this is done in response to competitive forces, the general equilibrium is a passive one. As such, the banking business model is vulnerable to disruption, particularly by innovation in financial technology.

A bank is an idiosyncratic corporate entity due to its ability to generate credit by leveraging its balance sheet. That balance sheet has assets on one side and liabilities on the other, like any corporate entity. The assets consist of cash, lending, financial and fixed assets. On the other side of the balance sheet are its liabilities, deposits, and debt. In this respect, a bank’s equity and its liabilities are its source of funds, and its assets are its use of funds. This is explained by Klein ( 1971 ), who notes that a bank’s equity W , borrowed funds and its deposits B is equal to its total funds F . This is the same for incumbents and challengers. This can be depicted algebraically if we let incumbents be represented by Φ and challengers represented by Γ:

Klein ( 1971 ) further explains that a bank’s equity is therefore made up of its share capital and unimpaired reserves. The latter are held by a bank to protect the bank’s deposit clients. This part is also mandated by regulation, so as to protect customers and indeed the entire banking system from systemic failure. These protective measures include other prudential requirements to hold cash reserves or other liquid assets. As shall be shown, banking services can be performed over the Internet without these protections. Banking as a service, as this phenomenon known, is expected to increase in the future. This will change the nature of the protection available to clients. It will change the way banks transform assets, explained next.

A bank’s deposits are said to be a function of the proportion of total funds obtained through the issuance of the ith deposit type and its total funds F , represented by α i . Where deposits, represented by Bs , are made in the form of Bs (i  =  1 *s n) , they generate a rate of interest. It follows that Si Bs  =  B . As such,

Therefor it can be said that,

The importance of Eq. 3 is that the balance sheet can be leveraged by the issuance of loans. It should be noted, however, that not all loans are returned to the bank in whole or part. Non-performing loans reduce the asset side of a bank’s balance sheet and act as a constraint on capital, and therefore new lending. Clearly, this is not the case with banking as a service. In that model, loans are brokered. That said, with the traditional model, an advantage of financial technology is that it facilitates the data mining of clients’ accounts. Lending can therefore be more targeted to borrowers that are more likely to repay, thereby reducing non-performing loans. Pari passu, the incumbent bank of the future will therefore have a higher risk-adjusted return on capital. In practice, however, banking as a service will bring greater competition from challengers and possible further erosion of margins. Alternatively, some banks will proactively engage in partnerships and acquisitions to maintain their customer base and address the competition.

A bank must have reserves to meet the demand of customers demanding their deposits back. The amount of these reserves is a key function of banking regulation. The Basel Committee on Banking Supervision mandates a requirement to hold various tiers of capital, so that banks have sufficient reserves to protect depositors. The Committee also imposes a framework for mitigating excessive liquidity risk and maturity transformation, through a set Liquidity Coverage Ratio and Net Stable Funding Ratio.

Recent revisions of theory, because of financial technology advances, have altered our understanding of banking intermediation. This will impact the competitive landscape and therefor shape the nature of the bank of the future. In this respect, the threat to incumbent banks comes from peer-to-peer Internet lending platforms. These perform the brokerage function of financial intermediation without the use of the aforementioned banking balance sheet. Unlike regulated deposit takers, such lending platforms do not create assets and do not perform risk and asset transformation. That said, they are reliant on investors who do not always behave in a counter cyclical way.

Financial technology in banking is not new. It has been used to facilitate electronic markets since the 1980’s. Thakor ( 2020 ) refers to three waves of application of financial innovation in banking. The advent of institutional futures markets and the changing nature of financial contracts fundamentally changed the role of banks. In response to this, academics extended the concept of a bank into an entity that either fulfills the aforementioned functions of a broker or a qualitative asset transformer. In this respect, they connect the providers and users of capital without changing the nature of the transformation of the various claims to that capital. This transformation can be in the form risk transfer or the application of leverage. The nature of trading of financial assets, however, is changing. Price discovery can now be done over the Internet and that is moving liquidity from central marketplaces (like the stock exchange) to decentralized ones.

Alongside these trends, in considering what the bank of the future will look like, it is necessary to understand the unregulated lending market that competes with traditional banks. In this part of the lending market, there has been a rise in shadow banks. The literature on these entities is covered by Adrian and Ashcraft ( 2016 ). Shadow banks have taken substantial market share from the traditional banks. They fulfil the brokerage function of banks, but regulators have only partial oversight of their risk transformation or leverage. The rise of shadow banks has been facilitated by financial technology and the originate to distribute model documented by Bord and Santos ( 2012 ). They use alternative trading systems that function as electronic communication networks. These facilitate dark pools of liquidity whereby buyers and sellers of bonds and securities trade off-exchange. Since the credit crisis of 2008, total broker dealer assets have diverged from banking assets. This illustrates the changed lending environment.

In the disintermediated market, banking as a service providers must rely on their equity and what access to funding they can attract from their online network. Without this they are unable to drive lending growth. To explain this, let I represent the online network. Extending Klein ( 1971 ), further let Ψ represent banking as a service and their total funds by F . This state is depicted as,

Theoretically, it can be shown that,

Shadow banks, and those disintermediators who bypass the banking system, have an advantage in a world where technology is ubiquitous. This becomes more apparent when costs are considered. Buchak et al. ( 2018 ) point out that shadow banks finance their originations almost entirely through securitization and what they term the originate to distribute business model. Diversifying risk in this way is good for individual banks, as banking risks can be transferred away from traditional banking balance sheets to institutional balance sheets. That said, the rise of securitization has introduced systemic risk into the banking sector.

Thus, we can see that the nature of banking capital is changing and at the same time technology is replacing labor. Let A denote the number of transactions per account at a period in time, and C denote the total cost per account per time period of providing the services of the payment mechanism. Klein ( 1971 ) points out that, if capital and labor are assumed to be part of the traditional banking model, it can be observed that,

It can therefore be observed that the total service charge per account at a period in time, represented by S, has a linear and proportional relationship to bank account activity. This is another variable that financial technology can impact. According to Klein ( 1971 ) this can be summed up in the following way,

where d is the basic bank decision variable, the service charge per transaction. Once again, in an automated and digital environment, financial technology greatly reduces d for the challenger banks. Swankie and Broby ( 2019 ) examine the impact of Artificial Intelligence on the evaluation of banking risk and conclude that it improves such variables.

Meanwhile, the traditional banking model can be expressed as a product of the number of accounts, M , and the average size of an account, N . This suggests a banks implicit yield is it rate of interest on deposits adjusted by its operating loss in each time period. This yield is generated by payment and loan services. Let R 1 depict this. These can be expressed as a fraction of total demand deposits. This is depicted by Klein ( 1971 ), if one assumes activity per account is constant, as,

As a result, whether a bank is structured with traditional labor overheads or built digitally, is extremely relevant to its profitability. The capital and labor of tradition banks, depicted as Φ i , is greater than online networks, depicted as I i . As such, the later have an advantage. This can be shown as,

What Klein (1972) failed to highlight is that the banking inherently involves leverage. Diamond and Dybving (1983) show that leverage makes bank susceptible to run on their liquidity. The literature divides these between adverse shock events, as explained by Bernanke et al ( 1996 ) or moral hazard events as explained by Demirgu¨¸c-Kunt and Detragiache ( 2002 ). This leverage builds on the balance sheet mismatch of short-term assets with long term liabilities. As such, capital and liquidity are intrinsically linked to viability and solvency.

The way capital and liquidity are managed is through credit and default management. This is done at a bank level and a supervisory level. The Basel Committee on Banking Supervision applies capital and leverage ratios, and central banks manage interest rates and other counter-cyclical measures. The various iterations of the prudential regulation of banks have moved the microeconomic theory of banking from the modeling of risk to the modeling of imperfect information. As mentioned, shadow and disintermediated services do not fall under this form or prudential regulation.

The relationship between leverage and insolvency risk crucially depends on the degree of banks total funds F and their liability structure L . In this respect, the liability structure of traditional banks is also greater than online networks which do not have the same level of available funds, depicted as,

Diamond and Dybvig ( 1983 ) observe that this liability structure is intimately tied to a traditional bank’s assets. In this respect, a bank’s ability to finance its lending at low cost and its ability to achieve repayment are key to its avoidance of insolvency. Online networks and/or brokers do not have to finance their lending, simply source it. Similarly, as brokers they do not face capital loss in the event of a default. This disintermediates the bank through the use of a peer-to-peer environment. These lenders and borrowers are introduced in digital way over the internet. Regulators have taken notice and the digital broker advantage might not last forever. As a result, the future may well see greater cooperation between these competing parties. This also because banks have valuable operational experience compared to new entrants.

It should also be observed that bank lending is either secured or unsecured. Interest on an unsecured loan is typically higher than the interest on a secured loan. In this respect, incumbent banks have an advantage as their closeness to the customer allows them to better understand the security of the assets. Berger et al ( 2005 ) further differentiate lending into transaction lending, relationship lending and credit scoring.

The evolution of the business model in a digital world

As has been demonstrated, the bank of the future in its various manifestations will be a consequence of the evolution of the current banking business model. There has been considerable scholarly investigation into the uniqueness of this business model, but less so on its changing nature. Song and Thakor ( 2010 ) are helpful in this respect and suggest that there are three aspects to this evolution, namely competition, complementary and co-evolution. Although liquidity transformation is evolving, it remains central to a bank’s role.

All the dynamics mentioned are relevant to the economy. There is considerable evidence, as outlined by Levine ( 2001 ), that market liberalization has a causal impact on economic growth. The impact of technology on productivity should prove positive and enhance the functioning of the domestic financial system. Indeed, market liberalization has already reshaped banking by increasing competition. New fee based ancillary financial services have become widespread, as has the proprietorial use of balance sheets. Risk has been securitized and even packaged into trade-able products.

Challenger banks are developing in a complementary way with the incumbents. The latter have an advantage over new entrants because they have information on their customers. The liquidity insurance model, proposed by Diamond and Dybvig ( 1983 ), explains how such banks have informational advantages over exchange markets. That said, financial technology changes these dynamics. It if facilitating the processing of financial data by third parties, explained in greater detail in the section on Open Banking.

At the same time, financial technology is facilitating banking as a service. This is where financial services are delivered by a broker over the Internet without resort to the balance sheet. This includes roboadvisory asset management, peer to peer lending, and crowd funding. Its growth will be facilitated by Open Banking as it becomes more geographically adopted. Figure  3 illustrates how these business models are disintermediating the traditional banking role and matching burrowers and savers.

The traditional view of banks ecosystem between savers and borrowers, atop the Internet which is matching savers and borrowers directly in a peer-to-peer way. The Klein ( 1971 ) theory of the banking firm does not incorporate the mirrored dynamics, and as such needs to be extended to reflect the digital innovation that impacts both borrowers and severs in a peer-to-peer environment

Meanwhile, the banking sector is co-evolving alongside a shadow banking phenomenon. Lenders and borrowers are interacting, but outside of the banking sector. This is a concern for central banks and banking regulators, as the lending is taking place in an unregulated environment. Shadow banking has grown because of financial technology, market liberalization and excess liquidity in the asset management ecosystem. Pozsar and Singh ( 2011 ) detail the non-bank/bank intersection of shadow banking. They point out that shadow banking results in reverse maturity transformation. Incumbent banks have blurred the distinction between their use of traditional (M2) liabilities and market-based shadow banking (non-M2) liabilities. This impacts the inter-generational transfers that enable a bank to achieve interest rate smoothing.

Securitization has transformed the risk in the banking sector, transferring it to asset management institutions. These include structured investment vehicles, securities lenders, asset backed commercial paper investors, credit focused hedge and money market funds. This in turn has led to greater systemic risk, the result of the nature of the non-traded liabilities of securitized pooling arrangements. This increased risk manifested itself in the 2008 credit crisis.

Commercial pressures are also shaping the banking industry. The drive for cost efficiency has made incumbent banks address their personally costs. Bank branches have been closed as technology has evolved. Branches make it easier to withdraw or transfer deposits and challenger banks are not as easily able to attract new deposits. The banking sector is therefore looking for new point of customer contact, such as supermarkets, post offices and social media platforms. These structural issues are occurring at the same time as the retail high street is also evolving. Banks have had an aggressive roll out of automated telling machines and a reduction in branches and headcount. Online digital transactions have now become the norm in most developed countries.

The financing of banks is also evolving. Traditional banks have tended to fund illiquid assets with short term and unstable liquid liabilities. This is one of the key contributors to the rise to the credit crisis of 2008. The provision of liquidity as a last resort is central to the asset transformation process. In this respect, the banking sector experienced a shock in 2008 in what is termed the credit crisis. The aforementioned liquidity mismatch resulted in the system not being able to absorb all the risks associated with subprime lending. Central banks had to resort to quantitative easing as a result of the failure of overnight funding mechanisms. The image of the entire banking sector was tarnished, and the banks of the future will have to address this.

The future must learn from the mistakes of the past. The structural weakness of the banking business model cannot be solved. That said, the latest Basel rules introduce further risk mitigation, improved leverage ratios and increased levels of capital reserve. Another lesson of the credit crisis was that there should be greater emphasis on risk culture, governance, and oversight. The independence and performance of the board, the experience and the skill set of senior management are now a greater focus of regulators. Internal controls and data analysis are increasingly more robust and efficient, with a greater focus on a banks stable funding ratio.

Meanwhile, the very nature of money is changing. A digital wallet for crypto-currencies fulfills much the same storage and transmission functions of a bank; and crypto-currencies are increasing being used for payment. Meanwhile, in Sweden, stores have the right to refuse cash and the majority of transactions are card based. This move to credit and debit cards, and the solving of the double spending problem, whereby digital money can be crypto-graphically protected, has led to the possibility that paper money could be replaced at some point in the future. Whether this might be by replacement by a CBDC, or decentralized digital offering, is of secondary importance to the requirement of banks to adapt. Whether accommodating crytpo-currencies or CBDC’s, Kou et al. ( 2021 ) recommend that banks keep focused on alternative payment and money transferring technologies.

Central banks also have to adapt. To limit disintermediation, they have to ensure that the economic design of their sponsored digital currencies focus on access for banks, interest payment relative to bank policy rate, banking holding limits and convertibility with bank deposits. All these developments have implications for banks, particularly in respect of funding, the secure storage of deposits and how digital currency interacts with traditional fiat money.

Open banking

Against the backdrop of all these trends and changes, a new dynamic is shaping the future of the banking sector. This is termed Open Banking, already briefly mentioned. This new way of handling banking data protocols introduces a secure way to give financial service companies consensual access to a bank’s customer financial information. Figure  4 illustrates how this works. Although a fairly simple concept, the implications are important for the banking industry. Essentially, a bank customer gives a regulated API permission to securely access his/her banking website. That is then used by a banking as a service entity to make direct payments and/or download financial data in order to provide a solution. It heralds an era of customer centric banking.

How Open Banking operates. The customer generates data by using his bank account. A third party provider is authorized to access that data through an API request. The bank confirms digitally that the customer has authorized the exchange of data and then fulfills the request

Open Banking was a response to the documented inertia around individual’s willingness to change bank accounts. Following the Retail Banking Review in the UK, this was addressed by lawmakers through the European Union’s Payment Services Directive II. The legislation was designed to make it easier to change banks by allowing customers to delegate authority to transfer their financial data to other parties. As a result of this, a whole host of data centric applications were conceived. Open banking adds further momentum to reshaping the future of banking.

Open Banking has a number of quite revolutionary implications. It was started so customers could change banks easily, but it resulted in some secondary considerations which are going to change the future of banking itself. It gives a clear view of bank financing. It allows aggregation of finances in one place. It also allows can give access to attractive offerings by allowing price comparisons. Open Banking API’s build a secure online financial marketplace based on data. They also allow access to a larger market in a faster way but the third-party providers for the new entrants. Open Banking allows developers to build single solutions on an API addressing very specific problems, like for example, a cash flow based credit rating.

Romānova et al. ( 2018 ) undertook a questionnaire on the Payment Services Directive II. The results suggest that Open Banking will promote competitiveness, innovation, and new product development. The initiative is associated with low costs and customer satisfaction, but that some concerns about security, privacy and risk are present. These can be mitigated, to some extent, by secure protocols and layered permission access.

Discussion: strategic options

Faced with these disruptive trends, there are four strategic options for market participants to con- sider. There are (1) a defensive customer retention strategy for incumbents, (2) an aggressive customer acquisition strategy for challenger banks (3) a banking as a service strategy for new entrants, and (4) a payments strategy for social media platforms.

Each of these strategies has to be conducted in a competitive marketplace for money demand by potential customers. Figure  5 illustrates where the first three strategies lie on the tradeoff between money demand and interest rates. The payment strategy can’t be modeled based on the supply of money. In the figure, the market settles at a rate L 2 . The incumbent banks have the capacity to meet the largest supply of these loans. The challenger banks have a constrained function but due to a lower cost base can gain excess rent through higher rates of interest. The peer-to-peer bank as a service brokers must settle for the market rate and a constrained supply offering.

The money demand M by lenders on the y axis. Interest rates on the y axis are labeled as r I and r II . The challenger banks are represented by the line labeled Γ. They have a price and technology advantage and so can lend at higher interest rates. The brokers are represented by the line labeled Ω. They are price takers, accepting the interest rate determined by the market. The same is true for the incumbents, represented by the line labeled Φ but they have a greater market share due to their customer relationships. Note that payments strategy for social media platforms is not shown on this figure as it is not affected by interest rates

Figure  5 illustrates that having a niche strategy is not counterproductive. Liu et al ( 2020 ) found that banks performing niche activities exhibit higher profitability and have lower risk. The syndication market now means that a bank making a loan does not have to be the entity that services it. This means banks in the future can better shape their risk profile and manage their lending books accordingly.

An interesting question for central banks is what the future Deposit Supply function will look like. If all three forms: open banking, traditional banking and challenger banks develop together, will the bank of the future have the same Deposit Supply function? The Klein ( 1971 ) general formulation assumes that deposits are increasing functions of implicit and explicit yields. As such, the very nature of central bank directed monetary policy may have to be revisited, as alluded to in the earlier discussion on digital money.

The client retention strategy (incumbents)

The competitive pressures suggest that incumbent banks need to focus on customer retention. Reichheld and Kenny ( 1990 ) found that the best way to do this was to focus on the retention of branch deposit customers. Obviously, another way is to provide a unique digital experience that matches the challengers.

Incumbent banks have a competitive advantage based on the information they have about their customers. Allen ( 1990 ) argues that where risk aversion is observable, information markets are viable. In other words, both bank and customer benefit from this. The strategic issue for them, therefore, becomes the retention of these customers when faced with greater competition.

Open Banking changes the dynamics of the banking information advantage. Borgogno and Colangelo ( 2020 ) suggest that the access to account (XS2A) rule that it introduced will increase competition and reduce information asymmetry. XS2A requires banks to grant access to bank account data to authorized third payment service providers.

The incumbent banks have a high-cost base and legacy IT systems. This makes it harder for them to migrate to a digital world. There are, however, also benefits from financial technology for the incumbents. These include reduced cost and greater efficiency. Financial technology can also now support platforms that allow incumbent banks to sell NPL’s. These platforms do not require the ownership of assets, they act as consolidators. The use of technology to monitor the transactions make the processing cost efficient. The unique selling point of such platforms is their centralized point of contact which results in a reduction in information asymmetry.

Incumbent banks must adapt a number of areas they got to adapt in terms of their liquidity transformation. They have to adapt the way they handle data. They must get customers to trust them in a digital world and the way that they trust them in a bricks and mortar world. It is no coincidence. When you go into a bank branch that is a great big solid building great big facade and so forth that is done deliberately so that you trust that bank with your deposit.

The risk of having rising non-performing loans needs to be managed, so customer retention should be selective. One of the puzzles in banking is why customers are regularly denied credit, rather than simply being charged a higher price for it. This credit rationing is often alleviated by collateral, but finance theory suggests value is based on the discounted sum of future cash flows. As such, it is conceivable that the bank of the future will use financial technology to provide innovative credit allocation solutions. That said, the dual risks of moral hazard and information asymmetries from the adoption of such solutions must be addressed.

Customer retention is especially important as bank competition is intensifying, as is the digitalization of financial services. Customer retention requires innovation, and that innovation has been moving at a very fast rate. Until now, banks have traditionally been hesitant about technology. More recently, mergers and acquisitions have increased quite substantially, initiated by a need to address actual or perceived weaknesses in financial technology.

The client acquisition strategy (challengers)

As intermediaries, the challenger banks are the same as incumbent banks, but designed from the outset to be digital. This gives them a cost and efficiency advantage. Anagnostopoulos ( 2018 ) suggests that the difference between challenger and traditional banks is that the former address its customers problems more directly. The challenge for such banks is customer acquisition.

Open Banking is a major advantage to challenger banks as it facilitates the changing of accounts. There is widespread dissatisfaction with many incumbent banks. Open Banking makes it easier to change accounts and also easier to get a transaction history on the client.

Customer acquisition can be improved by building trust in a brand. Historically, a bank was physically built in a very robust manner, hence the heavy architecture and grand banking halls. This was done deliberately to engender a sense of confidence in the deposit taking institution. Pure internet banks are not able to do this. As such, they must employ different strategies to convey stability. To do this, some communicate their sustainability credentials, whilst others use generational values-based advertising. Customer acquisition in a banking context is traditionally done by offering more attractive rates of interest. This is illustrated in Fig.  5 by the intersect of traditional banks with the market rate of interest, depicted where the line Γ crosses L 2 . As a result of the relationship with banking yield, teaser rates and introductory rates are common. A customer acquisition strategy has risks, as consumers with good credit can game different challenger banks by frequently changing accounts.

Most customer acquisition, however, is done based on superior service offering. The functionality of challenger banking accounts is often superior to incumbents, largely because the latter are built on legacy databases that have inter-operability issues. Having an open platform of services is a popular customer acquisition technique. The unrestricted provision of third-party products is viewed more favorably than a restricted range of products.

The banking as a service strategy (new entrants)

Banking from a customer’s perspective is the provision of a service. Customers don’t care about the maturity transformation of banking balance sheets. Banking as a service can be performed without recourse to these balance sheets. Banking products are brokered, mostly by new entrants, to individuals as services that can be subscribed to or paid on a fee basis.

There are a number banking as a service solutions including pre-paid and credit cards, lending and leasing. The banking as a service brokers are effectively those that are aggregating services from others using open banking to enable banking as a service.

The rise of banking as a service needs to be understood as these compete directly with traditional banks. As explained, some of these do this through peer-to-peer lending over the internet, others by matching borrows and sellers, conducting mediation as a loan broker. Such entities do not transform assets and do not have banking licenses. They do not have a branch network and often don not have access to deposits. This means that they have no insurance protection and can be subject to interest rate controls.

The new genre of financial technology, banking as a service provider, conduct financial services transformation without access to central bank liquidity. In a distributed digital asset world, the assets are stored on a distributed ledger rather than a traditional banking ledger. Financial technology has automated credit evaluation, savings, investments, insurance, trading, banking payments and risk management. These banking as a service offering are only as secure as the technology on which they are built.

The social media payment strategy (disintermediators and disruptors)

An intermediation bank is a conceptual idea, one created solely on a social networking site. Social media has developed a market for online goods and services. Williams ( 2018 ) estimates that there are 2.46 billion social media users. These all make and receive payments of some kind. They demand security and functionality. Importantly, they have often more clients than most banks. As such, a strategy to monetize the payments infrastructure makes sense.

All social media platforms are rich repositories of data. Such platforms are used to buy and sell things and that requires payments. Some platforms are considering evolving their own digital payment, cutting out the banks as middlemen. These include Facebook’s Diem (formerly Libra), a digital currency, and similar developments at some of the biggest technology companies. The risk with social media payment platform is that there is systemic counter-party protection. Regulators need to address this. One way to do this would be to extend payment service insurance to such platforms.

Social media as a platform moves the payment relationship from a transaction to a customer experience. The ability to use consumer desires in combination with financial data has the potential to deliver a number of new revenue opportunities. These will compete directly with the banks of the future. This will have implications for (1) the money supply, (2) the market share of traditional banks and, (3) the services that payment providers offer.

Further research

Several recommendations for research derive from both the impact of disintermediation and the four proposed strategies that will shape banking in the future. The recommendations and suggestions are based on the mentioned papers and the conclusions drawn from them.

As discussed, the nature of intermediation is changing, and this has implications for the pricing of risk. The role of interest rates in banking will have to be further reviewed. In a decentralized world based on crypto currencies the central banks do not have the same control over the money supply, This suggest the quantity theory of money and the liquidity preference theory need to be revisited. As explained, the Internet reduces much of the friction costs of intermediation. Researchers should ask how this will impact maturity transformation. It is also fair to ask whether at some point in the future there will just be one big bank. This question has already been addressed in the literature but the Internet facilities the possibility. Diamond ( 1984 ) and Ramakrishnan and Thakor ( 1984 ) suggested the answer was due to diversification and its impact on reducing monitoring costs.

Attention should be given by academics to the changing nature of banking risk. How should regulators, for example, address the moral hazard posed by challenger banks with weak balance sheets? What about deposit insurance? Should it be priced to include unregulated entities? Also, what criteria do borrowers use to choose non-banking intermediaries? The changing risk environment also poses two interesting practical questions. What will an online bank run look like, and how can it be averted? How can you establish trust in digital services?

There are also research questions related to the nature of competition. What, for example, will be the nature of cross border competition in a decentralized world? Is the credit rationing that generates competition a static or dynamic phenomena online? What is the value of combining consumer utility with banking services?

Financial intermediaries, like banks, thrive in a world of deficits and surpluses supported by information asymmetries and disconnectedness. The connectivity of the internet changes this dynamic. In this respect, the view of Schumpeter ( 1911 ) on the role of financial intermediaries needs revisiting. Lenders and borrows can be connected peer to peer via the internet.

All the dynamics mentioned change the nature of moral hazard. This needs further investigation. There has been much scholarly research on the intrinsic riskiness of the mismatch between banking assets and liabilities. This mismatch not only results in potential insolvency for a single bank but potentially for the whole system. There has, for example, been much debate on the whether a bank can be too big to fail. As a result of the riskiness of the banking model, the banks of the future will be just a liable to fail as the banks of the past.

This paper presented a revision of the theory of banking in a digital world. In this respect, it built on the work of Klein ( 1971 ). It provided an overview of the changing nature of banking intermediation, a result of the Internet and new digital business models. It presented the traditional academic view of banking and how it is evolving. It showed how this is adapted to explain digital driven disintermediation.

It was shown that the banking industry is facing several documented challenges. Risk is being taken of balance sheet, securitized, and brokered. Financial technology is digitalizing service delivery. At the same time, the very nature of intermediation is being changed due to digital currency. It is argued that the bank of the future not only has to face these competitive issues, but that technology will enhance the delivery of banking services and reduce the cost of their delivery.

The paper further presented the importance of the Open Banking revolution and how that facilitates banking as a service. Open Banking is increasing client churn and driving banking as a service. That in turn is changing the way products are delivered.

Four strategies were proposed to navigate the evolving competitive landscape. These are for incumbents to address customer retention; for challengers to peruse a low-cost digital experience; for niche players to provide banking as a service; and for social media platforms to develop payment platforms. In all these scenarios, the banks of the future will have to have digital strategies for both payments and service delivery.

It was shown that both incumbents and challengers are dependent on capital availability and borrowers credit concerns. Nothing has changed in that respect. The risks remain credit and default risk. What is clear, however, is the bank has become intrinsically linked with technology. The Internet is changing the nature of mediation. It is allowing peer to peer matching of borrowers and savers. It is facilitating new payment protocols and digital currencies. Banks need to evolve and adapt to accommodate these. Most of these questions are empirical in nature. The aim of this paper, however, was to demonstrate that an understanding of the banking model is a prerequisite to understanding how to address these and how to develop hypotheses connected with them.

In conclusion, financial technology is changing the future of banking and the way banks intermediate. It is facilitating digital money and the online transmission of financial assets. It is making banks more customer enteric and more competitive. Scholarly investigation into banking has to adapt. That said, whatever the future, trust will remain at the core of banking. Similarly, deposits and lending will continue to attract regulatory oversight.

Availability of data and materials

Diagrams are my own and the code to reproduce them is available in the supplied Latex files.

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Research evolution in banking performance: a bibliometric analysis

• S. M. Shamsul Alam 1 ,
• Mohammad Abdul Matin Chowdhury   ORCID: orcid.org/0000-0001-6860-2305 1 &
• Dzuljastri Bin Abdul Razak 1  

Future Business Journal volume  7 , Article number:  66 ( 2021 ) Cite this article

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Banking performance has been regarded as a crucial factor of economic growth. Banks collect deposits from surplus and provide loans to the investors that contribute to the total economic growth. Recent development in the banking industry is channelling the funds and participating in economic activities directly. Hence, academic researchers are gradually showing their concern on banking performance and its effect on economic growth. Therefore, this study aims to explore the academic researchers on this particular academic research article. By extracting data from the web of Science online database, this study employed the bibliometrix package (biblioshiny) in the ‘R’ and VOSviewer tool to conduct performance and science mapping analyses. A total of 1308 research documents were analysed, and 36 documents were critically reviewed. The findings exhibited a recent growth in academic publications. Three major themes are mainly identified, efficiency measurement, corporate governance effect and impact on economic growth. Besides, the content analysis represents the most common analysis techniques used in the past studies, namely DEA and GMM. The findings of this study will be beneficial to both bank managers and owners to gauge a better understanding of banking performance. Meanwhile, academic researchers and students may find the findings and suggestions to study in the banking area.

Introduction

The financial services formed a significant contributory trademark in the overall economic growth by stimulating employment, offering vast avenues for investment and services to the consumers and the society [ 1 ]. Thus, economic development is led by economic growth whereby required capital is provided by the financial services [ 2 ]. Suggestively, capital creation by the financial services industry through accumulation and mobilisation of resources is considered the most crucial economic growth strategy component [ 3 ]. The banking system associates with creating funds by accumulating funds from surplus and channelling them to the investors as credit; those exhibit excellent ideas to generate a surplus in the economy but lack the capital to implement such ideas [ 4 , 5 ]. Accordingly, the banking system plays a vital role to pledge the leading role of finance in economic development and promoting stable and healthy financial and economic development [ 6 ].

Banking performance has been regarded as a crucial factor of economic growth [ 7 ]. Efficiency and productivity change measures are rapidly used to evaluate banking performance. Academic researchers have been focusing on the efficiency and productivity of banking institutions for a long period, while economic growth is carried out in the discussions. Discovering research activities on banking efficiency and productivity in economic growth enables researchers to identify the local and international input to this particular discipline. More so, it will enable researchers to identify the ‘hot spots’ discussed by academic researchers and find the research gaps [ 8 ]. Indeed, banking performance in standings is a broad scientific topic, and estimating research activities might not be useful. For instance, research activities in this area extended to several constituents such as methodological approaches, banking approaches. In the current study, banking efficiency and productivity are considered as banking performance that contributes to the economic growth of an economy. Therefore, the main objective of this study is to explore the research activities of banking performance to economic growth. The investigation of banking performance research activities will enable the researchers to find the present directions of the research area and thus speculates the future research suggestions. Besides, it will also enable to expound the depth of past research activities and themes on banking performance relating to the economic growth measurements.

The use of the bibliometric method is appropriate to demonstrate the research shape and activity, volume and growth in a specific discipline [ 9 ]. A bibliometric method is a quantitative application of bibliometric data [ 10 ]. It analyses a wide-ranging quantity of published research articles employing the statistical tool to identify trends and citations or/and co-citations of a certain theme by year, author, country, journal, theory, method, and research constituent [ 11 ]. Significantly, this technique further distinguishes key research themes and active researchers, countries and institutions for future research planning and funding [ 12 ]. Scholars apply this method for several reasons: to reveal emerging trends in published research articles and journal performance, cooperation patterns, and research elements, and to reconnoitre the intellectual edifice of an exact domain in the existing literature [ 9 , 13 ].

Minimal studies have used bibliometric analysis related to banks. For instance, Violeta and Gordana have employed bibliometric analysis to spot the trends of DEA application in banking [ 14 ]. Another study conducted by Ikra et al. applied the bibliometric method to Islamic banking efficiency [ 15 ]. By an extensive search on the Scopus, Web of Science and Google Scholar, no such study was found related to bibliometric analysis on banking performance to the economic growth. Nevertheless, this study will be the first attempt to conduct bibliometric methods on the banking performance to the economic growth that could be the basis for future studies.

The findings of this study unfolded several contributions to both policymakers, bank managers and academic researchers. Firstly, the findings would benefit the policymakers regarding the contribution and trends of banking performance. It would allow them to take necessary initiatives to promote and improve banking performance, thus economic development. Meanwhile, bank managers may utilise the findings to strengthen their banking operations by acknowledging key factors that contributed to the performance. Finally, academic researchers are enabled to detect the current trend and topics related to the banking area that leads to further studies.

Bibliometric analysis has achieved enormous popularity in social sciences research in the current years [ 9 , 16 , 17 , 18 ]. The popularity of bibliometric analysis is observed from the development, accessibility and availability of software, for instance, Leximancer, Gephi, VOSviewer, Biblioshiny and publication databases (Web of Science and Scopus). Further, the rapid growth of bibliometric analysis in scientific production has emerged from business research to information science [ 9 ]. The popularity of bibliometric methodology in social science research is not a trend but moderately an image of its usefulness for constructing high research impact by handling excessive scientific data [ 9 ].

The bibliometric analysis is beneficial for briefing the trends in the research documents classifying ‘blind spots’ and ‘hot spots’, and finding a more inclusive understanding of the published research documents [ 19 ]. In detail, this analysis empowers the recognition of the most advanced (hot spots) and the less established topics (blind spots) within the documents that, shared with other bibliometric procedures, recommend future research avenues. The bibliometric analysis uncovers several ascriptions, such as unveiling emerging trends in documents and the performance of journals, research constituents and collaboration patterns and discovering the intellectual edifice of an exact domain in the existing literature [ 13 , 18 ]. The data that apply in this analysis incline to be immense (hundreds, thousands) and unbiased in nature (publications and citations number, keywords occurrences and topics). However, its explanations often depend on both subjective (thematic analysis) and objective (performance analysis) assessments formed through well-versed techniques and procedures [ 9 ]. Therefore, this study applied bibliometric analysis to examine the general perspective on banking performance and economic growth.

Two categories are mainly manifest in the bibliometric techniques, namely, performance and science mapping. Precisely, research elements’ contributions are accounted for in the performance analysis, while the connections between research elements are focused on science mapping [ 9 ]. This study follows performance analysis, science mapping and network analysis suggested by Donthu et al. [ 9 ].

Data extraction process

Two primary databases, the Web of Science and the Scopus, are commonly used in the bibliometric analysis [ 20 ]. Both databases are prominent for the peer-reviewed published research articles. The data for this analysis were a collection of bibliographic data from the Web of Science. The Web of Science (WoS) is a multidisciplinary online database providing access to several citation databases, namely Science Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI), Emerging Sources Citation Index (ESCI), Arts and Humanities Citation Index (AHCI), Conference Proceedings Citation Index, Index Chemicus and Current Chemical Reactions [ 18 , 21 ].

This study has applied a two-stage data extraction process, following Bretas and Alon, Alon et al. and Apriliyanti and Alon [ 16 , 22 , 23 ] as shown in Fig.  1 . The choice of the keywords is crucial to ensure that it covers the total body of published documents on banking performance and economic growth [ 21 ]. Accordingly, the selection of keywords was carried out by reviewing several abstracts and authors’ keywords in most related literature on the Web of Science. The selected keywords were executed in the WoS online database on 9 August 2021. A combination of keyword search terms was considered; (1) ‘banking performance*’ to nail all discrepancies of the term such as the role of the bank, bank efficiency, bank productivity, banking efficiency, banking productivity, banking performance, bank performance, upon refining the search by including only research articles from the categories; economics, business finance, business, management, operations research management, social sciences mathematical measures and documents written in English.

The second stage extracted raw data from the online database combined, checked for duplicate documents and merged using ‘R’. Further, the documents were filtered in the ‘biblioshiny’ tool to omit book chapters and conference proceedings. After the extraction process for the bibliometric analysis, several impactful documents were selected based on local and global citations to conduct content analysis. The content analysis allowed the researcher to identify the leading research scopes and trends. Further, it allows identifying the streams and recommendations for future studies [ 22 ]. A total of 36 documents were selected to conduct a comprehensive review and valuation of the documents.

Performance analysis

Performance analysis investigates the contributions of academic research elements to a particular discipline [ 24 ]. This analysis is naturally descriptive, which is the hallmark of bibliometric analysis [ 9 ]. It is a standard method in reviews to exhibit the performance of various research elements such as authors, countries, institutions and sources similar to the profile or background of respondents generally presented in empirical studies, albeit more statistically [ 9 , 18 ]. Many measures exist in the performance analysis; hence, the most protuberant measurements are publications number and citations per research constituent or year. The publication is considered productivity, whereby citation measures influence an impact [ 9 ]. Besides, citation per document and h -index associate both publications and citations with evaluating research performance [ 18 ].

Table 1 presents the publication’s performance of banking performance. The results show a total number of 1308 documents published from 1972 to the present. Among 2275 contributed authors, a total of 202 authors were solely, and 2106 authors collaborated to the publications. A total of 31,458 citations received by published documents lead to an average of 629.16 citations per year, while 775 in h -index and 1023 in g -index. Hence, the banking efficiency field acknowledged productivity of research published by an average of 26.16 documents per year whereby nearly two authors (CI = 1.9) published one article, and standardised collaboration is 0.43 (between 0 and 1).

The annual production of scientific publications on banking efficiency is presented in Fig.  2 . The first research article related to banking performance was published by Fraser and Rose [ 25 ], who studied the effect of new bank appearance in the market on bank performance. The annual growth of publications on banking performance or banking efficiency is recorded to 12.39%. The publications are significantly increasing in recent periods, especially from 2016 to the present. However, the mandated growth in publications is observed between 2004 and 2015, while earlier periods (1972–2003) were quite sluggish. In these consequences, academic researchers have started to focus on banking performance or banking efficiency in the recent period. As a result, it can be concluded that banking performance and its sphere are shaping upwards through the research contributions.

Annual Scientific production

Science mapping

Science mapping investigates the connections between research elements [ 26 ] that relates to the intellectual connections and structural networks within research constituents [ 9 ]. The science mapping includes citation analysis, bibliographic coupling, co-citation analysis, co-occurrence network, collaboration techniques. When combined with network analysis, these techniques are instrumental in exhibiting the research area’s bibliometric edifice and intellectual structure [ 27 ].

Citation analysis

The citation analysis is a fundamental approach for science mapping that runs on the assumption that citations reproduce intellectual contributions and impact the research horizons [ 28 ]. This analysis shows the impact of published documents by measuring the number of citations they received [ 9 ]. Accordingly, it enables the discovery of the most influential and informative documents in a research constituent. Thus, it allows gathering insights into that constituent’s intellectual dynamics [ 9 ]. Table 2 presents the top 20 impactful and influential documents in the field of banking performance or efficiency. The analysis has discovered that a total of 1112 documents (85%) out of 1308 documents received global citations. The global citations refer to the number of citations received in the overall Web of Science citations. However, 196 documents (about 15%) have not received any citation; meanwhile, 130 documents (about 10%) received only one citation. A document written by Berger An received the highest number (665) of citations which was published in 1997. The second most influential document was written by Seiford [51] received a total of 549 citations, followed by the document written by Back (2013) received 512 citations. In fact, a total of four documents written by Berger An rank in the top 20 impactful research articles in the field of banking performance or efficiency.

Factually, the majority of the documents without citations was published in a recent period. At the same time, the highly cited documents were published quite earlier. To detect the immediate influence of more recent documents is to apply the measurement of an average citation per year [ 29 ]. By evaluating the average citations per year, nine out of ten documents are also among the top 10 documents. Perpetually, Beck [45] holds the highest number of average citations per year (56.89), followed by Berger An (2013) ranked second position (51.44) and Beltratti A (2012) ranked the following position (48.40). Based on the citation analysis, it can be elucidated that Berger An is the most influential author in the banking efficiency research constituent.

Co-occurrence analysis

Co-occurrence analysis was projected by Callon et al. [ 30 ], considered as content analysis that is useful in plotting the strength of connotation within keywords in textual data. In other words, co-occurrence analysis is an approach that investigates the actual content of the document itself [ 9 ]. It maps the pertinent literature straight from the associations of keywords shared by research articles [ 24 , 27 , 31 , 32 ]. The co-occurrence analysis deduces words to appear recurrently in a cluster. It exhibits conceptual or semantic groups of various topics or sub-topics considered by research constituents [ 9 , 24 ]. Cobo and Herrera signified that spotted clusters could be applied with few objectives [ 24 ]. For instance, they can be applied to analyse their progression by gauging extension across successive subperiods and measuring the research area through performance analysis. Figure  3 displays the co-occurrence of keywords within the bank efficiency research constituent. As the focus of this research, bank performance represents the larger node associated with corporate governance, financial performance, financial crisis, nonperforming loans and others. In these scenarios, the red-coloured cluster depicts that these subtopics or variables are directly associated related to the bank performance theme due to repetitive co-occurrence of those words. Likewise, the green-coloured cluster represents a theme related to bank efficiency associated with performance and ownership. In the same cluster, the nonparametric data envelopment analysis is extensively used to measure commercial banks' technical and cost efficiency and productivity. Parametric stochastic frontier analysis is narrowly observed in efficiency measurements comparably. The green-coloured cluster depicts the determinants of bank profitability including other impactful variables such as risk, competition, corporate governance. This cluster applied panel data in order to examine performance, financial development as well as economic growth. Each of the cluster identifies the interacted themes used in the published documents using co-occurrence of keywords.

Co-occurrence of keywords, Tool: VOSviewer. Note the nodes represent the keywords, and the edges between words present their occurrence of interactions. Each colour of nodes represents a cluster/theme. The size of the node presents a greater frequency of occurrence

Collaboration networks

Collaboration analysis explores the associations within researchers in a particular constituent. It is a formal way of intellectual association among researchers [ 33 , 34 ]. Therefore, it is crucial to understand how researchers associate among themselves [ 9 ]. In the presence of growing theoretical and methodological complexity in research, intellectual networking (collaboration) has become commonplace [ 33 ]. Indeed, collaboration or interaction among researchers enables improvements in academic research; for instance, greater interactions among diverse researchers allow richer insights and greater clarity [ 35 ]. Researchers who collaborate form a network named ‘invisible collages’ whose research can help improve undertakings in the study field [ 36 ]. Figure  4 presents the collaboration network of authors those co-authored academic articles in banking efficiency. Based on the collaboration network, Wanke P (Universidade Federal do Rio de Janeiro) was the most collaborated author who co-authored with four authors from different institutions in different countries. At the same time, Matousek, R (University Kent), Hasan, I (Rensselaer Polytechnic Institute) and Mamatzakis, E (University of Sussex), have also exhibited as greater collaborative researchers. In these consequences, authors from different institutions and from different parts of the world are collaborating to the banking performance/efficiency field.

Source : VOSviewer. Note the nodes represent the authors, and the size represents the frequency of contribution, the colour presents a cluster or a particular group, and the link shows the link among authors that collaborated for research articles

Authors’ collaboration networks.

Bibliographic coupling

Co-authorship or collaborative networks within the authors and other crucial facets in the collaboration networks are the collaboration of author-affiliated countries and institutions [ 31 ]. Figure  5 exhibits the collaboration network within authors’ affiliated organisations. University Malaya and University Utara Malaysia, University Malaya and University Putra Malaysia, University Malaya and University Fed Rio de Janeiro all depict a strong collaboration network. In general, all the institutions display an embellishment among the institutions within the same region.

Source : VOSviewer

Bibliographic coupling of author-affiliated institutions.

Similar to co-authors’ affiliated institutions, the collaboration of authors’ country presents a steady association among authors’ connections that allow exploring comparative and concurrent research works. Figure  6 represents the network of collaborative authors’ affiliation countries. These countries include South Africa and the USA, England and the USA, Australia and the USA, Malaysia and the USA, Germany and the USA, representing a high proportion of authors’ affiliated institutions are in the USA with this country performing as a hub of co-authorship publications from 1972 to 2021.

Collaborative authors’ affiliated countries

This study discusses trending themes based on the bibliometric findings and reviews of highly cited and most recent documents (see Appendix 1 ). It also indicated the type of study, theories, methods and main findings to suggest comprehensive future studies.

Research directions

Between 1991 and 2010, studies related to banking performance have posited several antecedents to banking performance. Figure  7 displays the trend topics based on author keywords that appeared between 1972 and 2010. Studies in this period mainly focused on mergers and acquisitions, information technology and transition economies that emerged from universal banking deregulation and bank privatisation. The financial crisis during 2008–2009 drew the attention of scholars to evaluate the banking performance. Idiosyncratically, this phenomenon has been acknowledged by researchers from 2010 to 2015, focusing on the role of corporate governance in the performance of the banking industry, including compensation, risk management, determinants of stock returns, capital buffer, productivity. Idiosyncratically, a vast of studies were conducted on Chinese commercial banks and the effect on their economic growth.

Source : Biblioshiny analysis. Note the frequency of terms selected 3 times for 1972–2010, 5 times for 2011–2015, 10 times for 2016–2021

Trend topics in different periods.

In the recent period (2016–2021), diverse factors posited in the studies that dominantly present a significant interest from banking scholars. While studies earlier mainly focusing on efficiency and its contributing factors, recent periods extended research directions to multiple constituents. For example, how banks diversified their services and the role of human capital efficiency to the banking performance [ 37 ]. Bose et al. employed the effect of green banking on the performance that underpins the inclusion of the environmental sustainability approach by the banking industry [ 38 ]. Meanwhile, Bhattacharyya et al. showed the effect of CSR expenditures and financial inclusion on the performance that define the social sustainability indicator of the banks [ 39 ]. Repeatedly, the role and structure of the board, categorisation of deposits and loans, risk exposures (business cycle), macroeconomic factors were also acknowledged in recent banking performance studies [ 40 , 41 , 42 , 43 ]. Idiosyncratically, scholars recently focus the components of sustainability of the banking industry from economic, environmental and social aspects [ 44 ]. Furthermore, the effect of banking and its stability on economic growth has been broadly carried out in the recent period. Moreover, the development of studies was taken into account, which implies the contribution to the economic growth of particular regions. Based on the earlier and recent studies, it is precisely observed the diversification of research constituents in relation to bank performance studies. Earlier studies (up to 2015) mainly measured banking performance or efficiency based on accounting measurements, while recent studies started to include market measurements principally based on stock returns performance. On the other hand, the rise of Islamic banking and finance influenced academic researchers to compare the business models [ 45 ], banking efficiencies [ 46 ] between conventional and Islamic banks, and efficiency for Islamic banks [ 5 ].

Based on the review of impactful documents published from 1990 to 2010, two particular objectives were identified: the effect of the board of directors or ownership on the bank performance [ 47 , 48 , 49 ] and measurement of efficiency, including cost and profit efficiency [ 50 , 51 , 52 ]. These constituents extended during 2011–2020 by the inclusion of risk-taking management [ 53 ], CEO incentives [ 54 ], contributing factors including capital, banking crises on banking performance [ 42 , 55 , 56 , 57 ]. Meanwhile, the Islamic banking system got crucial attention from academic researchers. Accordingly, several studies evaluated and compared efficiency between Islamic and conventional banks [ 45 , 58 , 59 ]. Nevertheless, the role of the banking industry in economic growth was included in the research constituents in the recent decade. For example, Xu, Santana and a few more scholars investigated the correlation between financial intermediation and economic growth [ 57 , 60 , 61 ]. In recent years, scholars extended the banking-related research constituents to diverse areas. The effect of human capital efficiency [ 37 ], green banking [ 38 ], CSR expenditures [ 39 ] and bank stability was included to measure banking performance. These extensions of research themes within banking performance studies posited a significant interest by academic researchers.

Apparently, almost all documents adopted the quantitative method in measuring banking performance research constituents. However, studies that measured banking efficiency mainly applied nonparametric analysis DEA [ 5 , 51 ], while SFA was adopted by limited studies [ 37 , 42 , 43 ]. On the other hand, regression analysis was predominantly applied to investigate banking performance from 1990 to 2010 [ 49 , 50 ]. In recent studies, academic researchers have vastly adopted GMM (generalised method of moments) to examine the contributing factors on banking performance [ 39 , 42 , 57 , 60 ]. These methods are dominating the banking-related studies throughout the publication periods. Over the periods, scholars have developed DEA applications in several categories, such as bootstrap, networking. Meanwhile, GMM with different approach (dynamic and system) techniques exploited panel data primarily extracted from Bankscope, Datastream, annual reports etc.

Main findings

Earlier, banking inefficiencies were substantially observed low, negatively affecting profitability and marketability [ 50 , 51 ]. This trend was continuously depicted in studies [ 52 ]. However, Berger et al. evidenced better efficiency for larger banks than smaller banks [ 50 ]. On the contrary, Seiford and Zhu posited an adverse effect of bank size on marketability [ 51 ]. More so, Rehman et al. found larger banks are less efficient than smaller banks [ 40 ]. Hence, Moudud-Ul-Huq posited diverse impacts of bank size and competition on performance [ 62 ]. So, banking size is deemed to have a substantial effect on the overall performance of banks. However, Adesina embellished that diversification of services and choices of management decisions on loans (nonperforming, debt issuances) [ 63 , 64 ] and deposits [ 41 ] affect the banking performance [ 37 ]. Moreover, board structure affects banking performance [ 40 , 65 ], while higher human capital efficiency enhances banking performance [ 37 ].

Generally, foreign-owned banks provide better service, greater profitability and are better efficient than local banks. This phenomenon was evidenced in several studies; for example, Bonin et al. and other scholars demonstrated that foreign-owned banks are more cost-efficient than other banks [ 48 ]. However, this trend did not exist for Islamic banks as local banks showed better efficiency than foreign peers [ 58 ] and more efficient than conventional [ 59 ]. Meanwhile, state-owned or government-owned commercial banks were less efficient and provided poorer services [ 48 , 49 , 52 ]. But these banks’ efficiency was higher than urban/rural banks during credit risk shock [ 41 ]. Nevertheless, banking efficiency and performance substantially depend on diversification of services, managerial adequacy, ownership, types and size.

Studies have evidenced financial development and thus the banking industry’s role in economic growth [ 60 ]. In the nineteenth century, the establishment of the savings bank demonstrated city growth in Prussia [ 66 ]. Potentially, banks provide investment capital to increase per capita GDP [ 43 ]. However, Haini documented a contrasting effect of banking development on economic growth through a push out of private investment due to high levels of the banking sector [ 67 ]. However, Stewart and Chowdhury proved that a stable banking sector lessens the negative impact of a crisis on GDP growth and provides economic resilience in both developed and developing countries. Overall, findings elaborated a crucial link between banking sector development and economic growth.

Future study suggestions

This study has recommended several scopes for future studies in the hybrid review, mainly through bibliometric findings and the structured review of impactful articles [ 11 ]. In other words, the recommendations for future studies are made by observing and analysing discussions on highly cited and recent cited documents. Overall findings and analyses raised several questions that need to be addressed for future studies.

Firstly, does the banking sector improve economic growth in the least developed countries? Prior studies mainly focused on developed and developing economies, but less attention was given to least developed countries. Secondly, vast studies investigated contributing factors of banking performance, while political instability has been ignored. Future studies might include political instability on the banking performance. Apart from it, nonperforming loans can be another addition to future studies, and even few studies documented it. Thirdly, how do banks perform during the pandemic crisis, for instance, COVID-19? The current pandemic crisis can be a significant factor in banking performance related to future studies, including efficiency, mortgages, loan recovery, deposits and business services. The studies can include consumer behaviour (due to restricted movements, safety measurements), green banking (online transaction and services), financial technologies (inclusion of nonbanking services) and the contribution or continuance of economic activities in the country during and after the pandemic crisis.

Significantly, prior studies have ignored the current trend of FinTech inclusion in banking performance. Fourthly, will FinTech takeover the banking services and diminish banks in the near future? Future studies may investigate the effect of FinTech applications on banking. More so, future studies may explore the banking industry’s barriers, challenges and threats due to FinTech growth. Fifthly, almost all studies employed quantitative analysis related to banking performance. Therefore, future studies may use qualitative methods to explore the opportunities and practices of banks and their performance. Sixthly, the majority of the studies either applied parametric or econometric techniques to investigate the bank performance. Recent developments in technologies and methods may provide easy and robust results in such related studies as using machine learning for data analysis and predicting banking efficiency and productivity determinants. Seventhly, past studies mostly followed the intermediation approach, which scarcely included production and operating approach measurement. Future studies may extend the efficiency analysis using productivity growth analysis. Further, the majority of the studies observed efficiency only. Future studies can include a productivity change index along with an efficiency analysis. Finally, GMM and regression were broadly applied to investigate the effect of antecedents of banking performance and link to economic growth. Future studies may adopt other advanced data analysis techniques such as partial least squares, structural equations and other econometric techniques.

Conclusions

The main purpose of this study is to explore the trends and research activities in banking performance and the economic growth research domain. To achieve this objective, a bibliometric analysis was applied and performed several analyses, namely citation, co-occurrence of keywords, the collaboration between authors and coupling between institutions and countries, and discussion by reviewing most cited and most recent influential research articles. This study presents the most common themes, sub-themes associated with highly cited documents and authors; furthermore, the content analysis identified the research directions, research objectives, methodologies, topics and findings.

Based on the reviewing literature, the efficiency theory, banking theory mainly intermediation approach and nonparametric technique, namely data envelopment analysis along with econometric method, regression was used in the published documents. The findings of this study, along with future study suggestions, could be beneficial to bankers as well as academic researchers and students studying banking performance and its role in the economy.

Limitations

The most crucial limitation in any bibliometric analysis is the database selection. It means selecting the data and the limits of its interpretation [ 68 ]. This study has three key limitations; firstly, it has chosen ‘Web of Science’, one of the largest online databases to gather data on banking performance research articles from 1972 to 2021 and refined based on subject categories and language (English). The database could be improved if other databases were included and also if book chapters and conference proceedings were added. Secondly, the selection of keywords; although selected keywords are deemed to be most relevant to encompass the majority of articles related to banking performance, there is always an opportunity to search further articles by using additional keywords. Lastly, this study could not conduct co-citation analysis due to the unavailability of cited documents in Web of Science data format.

Availability of data and materials

The data collected from the Web of Science online database were saved on Microsoft excel and remained with authors. The data are available upon request.

Abbreviations

Data envelopment analysis

Generalized method of moments

• Web of Science

Collaboration index

Chief executive officer

Corporate social responsibility

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S. M. Shamsul Alam, Mohammad Abdul Matin Chowdhury & Dzuljastri Bin Abdul Razak

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Alam, S.M.S., Chowdhury, M.A.M. & Razak, D.B.A. Research evolution in banking performance: a bibliometric analysis. Futur Bus J 7 , 66 (2021). https://doi.org/10.1186/s43093-021-00111-7

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• Banking performance
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Return-to-Office Orders: A Survey Analysis of Employment Impacts

How did employers expect return-to-office (RTO) orders to affect employment? Were those expectations correct? We use special questions from the Richmond Fed business surveys to shed light on these questions. Overall, RTO orders were expected to reduce employment, but there was both substantial uncertainty and heterogeneity in expectations. Some employers even expected that RTO would increase employment. Ex post, employers believe RTO orders had a muted effect on employment. We find that the service sector was more likely to both issue RTO orders and expect and experience a reduction in employment.

The COVID-19 pandemic changed the way that both employers and employees think about the location of work. 1 The advent of remote work en masse in 2020 has been followed by a gradual implementation of requiring workers to work from the office, at least for some of their workweek. These forced return-to-office (RTO) orders have come with controversy: Many employers have implemented these policies, while many employees have resisted.

In this article, we attempt to shed light on the effects of RTO by reporting on special questions we asked in the March Richmond Fed business surveys . Specifically, these questions shed light on both the anticipated and realized employment outcomes of RTO orders from the employer's perspective. We find that uncertainty in the decision-making process was prevalent, but also that realized outcomes were generally muted. RTO did have an expected and actual negative effect on employment, but only in some sectors and for some employers. For others, RTO was a means of increasing employment. Our results highlight the large uncertainty in the pandemic, the heterogeneity of firms and the large heterogeneity of workers.

Why Examine the Impacts of RTO Orders?

This survey builds on a recent literature investigating the implications of remote work for workers, businesses and local economies . Uniquely, it attempts to discern how business leaders anticipated RTO policies would impact their firms as well as the actual impact on employment within their firms. Although there is work evaluating the benefits and costs to employers in terms of productivity or labor/non-labor costs, 2 there has been little work to understand the firm-by-firm implication of articulating and enforcing an RTO order.

Research indicates that hybrid options are highly valued by employees , 3 but how many separations can be attributed to an RTO policy? There is evidence that managers value in-person work more than employees, 4 but does that result in actual separations when RTO orders are implemented? Our results suggest the effects of these policies were muted.

There is also evidence of wide variation in employee hybrid-work preferences and in their willingness to pay for the option to work from home 5 as well as evidence that the value workers place on the "amenity" of remote or hybrid work has implications for aggregate wage changes in the macroeconomy. 6 Our work indicates this heterogeneity in preferences may have dampened the effect of RTO orders on employment. Our results are consistent with a literature that is still relatively mixed about the net effect on employers and workers of remote or on-site policies.

Methodology

The Federal Reserve Bank of Richmond has surveyed CEOs and other business leaders across the Fifth Federal Reserve District 7 for almost 30 years, currently gathering around 200-250 responses per month. The survey panel underweights the smallest firms and, due to the history of the survey, manufacturing firms make up about one-third of respondents even though they make up a much smaller share of establishments in the Fifth District or the nation.

In addition to a series of questions about variables such as demand, employment and prices, respondents are commonly asked a set of ad hoc questions. Here, we focus on a set of questions asked in March 2024 regarding the extent to which respondents articulated and enforced a mandatory RTO policy and what they expected upon its implementation. Emily Corcoran reported on employers' on-site general expectations for employees and how those have changed. But here, we focus on business leaders' expectations of RTO policy effects, providing insight into the anticipated and unanticipated employment effects of RTO orders. We begin by assessing whether the establishment implemented RTO. These results are tabulated in Table 1.

Overall, explicit RTO orders were relatively rare, with only 20 percent of respondents articulating RTO orders in the last three years. This small percentage is partly because 37 percent of respondents — many of them manufacturing firms — were fully on-site before the end of 2020, and an additional 26 percent of respondents said RTO wasn't applicable for their companies. 8 Of the remaining companies, there is a roughly equal split between firms that have an explicit RTO policy (20 percent of the full sample) and those that do not (16 percent of the full sample).

We asked these 20 percent of employers about the expected consequences of issuing RTO orders. Did they expect workers to quit because of these policies? Were they sure about the effect on employment? We also asked employers about their assessment of realized outcomes. Did workers quit as anticipated? Did RTO help the firm recruit workers?

What Did Employers Expect, and What Actually Happened?

Perhaps surprisingly, we found two-thirds of employers expected no impact on (net) employment from RTO orders, while 16 percent were too unsure of the impact to answer (Table 2). Among the 18 percent that expected some impact, the anticipated outcome was split between those that expected a decrease in employment (11 percent) and those that expected an increase (7 percent).

Why might employment increase? One possibility derives from employees feeling more connected to their co-workers with greater mentoring opportunities when in the office. 9 This could reduce quitting and improve hiring, as one survey respondent reported that, "...the employees that [formerly] chose to work remotely decided that they were more productive in the office. We are [now] 90+ percent in the office."

Additionally, RTO orders have often been hybrid, 10 potentially allowing the benefits of office culture to be obtained without sacrificing all of the flexibility associated with remote work.

We also asked employers about their evaluation of outcomes, and the results are given in Table 3. Here, a greater percentage reported no impact (82 percent), while 4 percent assessed that RTO had decreased employment, and 4 percent assessed that RTO had actually increased employment. (Nine percent were still unsure.)

Sectoral level analysis reveals employment impacts (both expected and realized) were concentrated in the service sector. In manufacturing, no firms concretely expected a change in employment (though some were unsure), and ex post they believe RTO did not cause them to lose workers. In services, however, only 59 percent expected no impact, while 16 percent expected a negative impact on employment. Ex post, impact on employment was less than expected.

While our analysis is suggestive, there are a few limitations. Foremost, our effective sample size was small, meaning some of these results could be driven by sampling error. Second, it has been years since some employers implemented RTO policies, so their memories of their expectations could be inaccurate. Third, our survey did not control for any other firm changes — such as changes in wages or product demand — that could confound our findings. Fourth, although our findings provide insight into net employment gains and losses, they do not speak to hiring and firing separately. 11

With these caveats in mind, however, our results show that RTO — while still a common topic of conversation — is not necessarily important to employers' and workers' employment decisions. Concerns about employment effects ex ante mostly did not materialize. Employment effects that did materialize were concentrated in services and resulted in a net gain of employees in some cases, rather than a loss.

Grey Gordon is a senior economist and Sonya Ravindranath Waddell is a vice president and economist, both in the Research Department of the Federal Reserve Bank of Richmond. The authors thank Jason Kosakow for helping to develop and execute the survey and for providing the tabulations underlying this analysis and thank RC Balaban, Zach Edwards and Claudia Macaluso for providing feedback on an earlier draft.

See, for example, the 2023 paper " The Evolution of Work From Home " by Jose Maria Barrero, Nicholas Bloom and Steven Davis.

See, for example, the 2024 working paper " The Big Shift in Working Arrangements: Eight Ways Unusual " by Steven Davis.

See, for example, the 2023 working paper " How Hybrid Working From Home Works Out " by Nicholas Bloom, Ruobing Han and James Liang.

See the previously cited paper " How Hybrid Working From Home Works Out ."

See, for example, the 2021 working paper " Why Working From Home Will Stick " by Jose Maria Barrero, Nicholas Bloom and Steven Davis.

See, for example, the 2024 working paper " Job Amenity Shocks and Labor Reallocation (PDF) " by Sadhika Bagga, Lukas Mann, Aysegul Sahin and Giovanni Violante.

The Fifth District comprises the District of Columbia, Maryland, North Carolina, South Carolina, Virginia and most of West Virginia.

Those who answered "not applicable" are presumably firms where work is necessarily done in person.

See, for example, the 2023 article " About a Third of U.S. Workers Who Can Work From Home Now Do So All the Time " by Kim Parker.

The previously cited article by Emily Corcoran noted that 38 percent of firms are in the office in between one and four days a week.

See the 2022 article " Changing Recruiting Practices and Methods in the Tight Labor Market " by Claudia Macaluso and Sonya Ravindranath Waddell for an analysis of how hiring practices have changed in the tight labor market that has prevailed since 2020.

This article may be photocopied or reprinted in its entirety. Please credit the authors, source, and the Federal Reserve Bank of Richmond and include the italicized statement below.

V iews expressed in this article are those of the authors and not necessarily those of the Federal Reserve Bank of Richmond or the Federal Reserve System.

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BofA Study: Percentage of American Workers Feeling Financially Well Rises to 47%

May 21, 2024 at 8:00 AM Eastern

2024 Workplace Benefits Report finds financial wellness gender gap widening and greater concern over cost-of-living increases

CHARLOTTE, NC – Today, 47% of American workers feel financially well, up from 42% at this time last year. This is according to Bank of America's 14th annual Workplace Benefits Report, “The Resurging Workforce." Conducted in partnership with Bank of America Institute , the report also found that 53% of employees are concerned that economic uncertainty will affect their long-term retirement savings, down from 63% in 2023.

Meanwhile, the gap in financial wellness between men and women continues to grow, with 53% of men reporting good financial wellness compared to 36% of women. In addition, employees expressed concern about inflation, with 76% of workers saying that the cost of living is outpacing growth in their salary or wages, compared to 67% in June 2023.

“Despite concerns about the cost of living and plans to limit expenses, more employees are feeling confident about their financial well-being,” said Lorna Sabbia, Head of Workplace Benefits at Bank of America. “However, there is still work to be done to address gender equity, as women continue to report much lower financial wellness scores than men.”

Based on nationwide surveys of nearly 1,000 employees and more than 800 employers, the report analyzed employee financial well-being and retirement preparedness, the state of the workplace, benefits trends and more.

Key Insights:

• 6 in 10 workers are limiting current expenses. Many employees say they are taking proactive steps to improve their financial wellness, including limiting expenses (62%), paying down debt (43%) and adding to emergency funds (41%).
• Job loyalty remains high. 70% of employees plan to keep their jobs for the next year, with good work/life balance as the top reason employees want to stay (66%). Of those who plan to leave, compensation (52%) was the top reason for the switch, followed by career growth (45%).
• Pay equity is becoming a powerful recruitment tool. Only 44% of employers currently address pay equity. However, those with pay equity initiatives in place notice an impact, with 78% reporting an improvement in attracting top talent vs. 50% without such initiatives.
• There’s a potential disconnect in retirement health care expenses. Most Americans drastically underestimate the cost of health care in retirement. Current research [1] shows that a retired 65-year-old couple could need more than $350,000 in savings to cover their retirement health care expenses. However, according to this new Bank of America report, only 7% of employees think their yearly health expenses in retirement could total even $10,000.

Additional Findings:

• There’s a divide between working caregivers and employers. While most employers (81%) say they offer support to caregivers, 61% of caregivers are not aware of available support. This is significant, considering a little more than half of the employees (52%) we surveyed identify as caregivers, and 49% of caregivers are not comfortable self-identifying to their employers.
• American workers are beginning to re-prioritize retirement savings. The number of employees prioritizing long-term retirement savings is slowly trending upwards (33% today, up from 31% in 2023). This has become their top financial goal, overtaking those focused on short-term financial needs last year.
• Debt assistance is emerging as an attractive benefit. Employers are starting to explore ways they can support employees with debt, with 37% now offering student loan repayment assistance.
• Wellness reimbursements are becoming a new benefit trend. According to the data, 48% of employees want their company to offer a Lifestyle Spending Account (LSA), which can help employees pay for a range of wellness expenses and encourage healthy behaviors. Examples of qualified expenses may include gym memberships, mediation classes and camping supplies. However, only 29% of employers currently offer an LSA.

More findings, including actionable steps for employers, are available in the Bank of America 2024 Workplace Benefits Report.

Workplace Benefits Report Methodology

Escalent surveyed a national sample of 955 employees who are working full-time and participate in 401(k) plans, and 804 employers who offer both a 401(k) plan and have sole or shared responsibility for decisions made in the plan. The survey was conducted between November 22, 2023, and January 4, 2024. To qualify for the survey, employees had to be current participants of a 401(k) plan and employers had to offer a 401(k) plan option. Neither was required to work with Bank of America. Bank of America was not identified as the sponsor of the study.

About Bank of America Institute

Bank of America Institute is dedicated to uncovering powerful insights that move business and society forward. Established in 2022, the Institute is a think tank that draws on data and analyses from across the bank and the world to provide timely and original perspectives on the economy, sustainability, and global transformation. The Institute leverages the depth and breadth of the bank’s proprietary data, from approximately 68 million consumer and small business clients, 56 million verified digital users, $4.2 trillion in total payments in 2022 and $1.4 trillion in consumer and wealth management deposits. From this robust data set, the Institute provides a unique perspective on the health of the economy. It also elevates thought leadership from throughout the bank that addresses long-term trends and shares these findings with the general public.

Bank of America

Bank of America is one of the world’s leading financial institutions, serving individual consumers, small and middle-market businesses and large corporations with a full range of banking, investing, asset management and other financial and risk management products and services. The company provides unmatched convenience in the United States, serving approximately 69 million consumer and small business clients with approximately 3,800 retail financial centers, approximately 15,000 ATMs (automated teller machines) and award-winning digital banking with approximately 57 million verified digital users. Bank of America is a global leader in wealth management, corporate and investment banking and trading across a broad range of asset classes, serving corporations, governments, institutions and individuals around the world. Bank of America offers industry-leading support to approximately 4 million small business households through a suite of innovative, easy-to-use online products and services. The company serves clients through operations across the United States, its territories and more than 35 countries. Bank of America Corporation stock is listed on the New York Stock Exchange (NYSE: BAC).

Bank of America is a marketing name for the Retirement Services business of Bank of America Corporation (“BofA Corp.”). Banking activities may be performed by wholly owned banking affiliates of BofA Corp., including Bank of America, N.A., Member FDIC. Brokerage and Investment advisory services are provided by wholly owned non-bank affiliates of BofA Corp., including MLPF&S, a dually registered broker-dealer and investment adviser and Member SIPC. 

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[1] Employee Benefits Research Institute, Issue Brief no. 599, January 18, 2024.

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New York Fed Releases New Podcast and Research Focused on Veterans in the Labor Force

NEW YORK—The Federal Reserve Bank of New York today released the latest episode of its “ Bank Notes ” podcast, titled “Veterans in the Labor Force.”

In this episode, experts working across the military-connected population discuss the reasons for the labor force participation gap between veterans and nonveterans. A previous Liberty Street Economics blog post from May 2023 found that veterans are 22% more likely to be out of the labor force than comparable nonveterans. This episode also addresses some of the most widely held misperceptions about career paths within the military and the outcomes and experiences of military service. Additionally, experts highlight educational and vocational opportunities unique to veterans and military families.

In conjunction with the release of the podcast episode, the New York Fed also released a Liberty Street Economics blog post on veterans’ experiences in the labor market, focusing on employment, labor force participation, and real earnings. Today’s post builds on a related 2023 blog post about veterans. Similar to that previous New York Fed research , the new research shows that one year later the gaps in employment and labor force participation between veterans and comparable nonveterans still persist, while the employment gap has slightly widened. However, while nonveterans were still outearning veterans in 2021, the new research shows that the veteran real earnings gap has now disappeared.

Key findings from the research include:

• While the veteran employment gap shrank temporarily after the pandemic recession, it has since reopened and stands at 4.74 percentage points, up from 3.99 in April 2023.
• The labor force participation gap between veterans and comparable nonveterans has rebounded after shrinking immediately after the pandemic. The gap is now larger in April 2024 than in April 2023 or April 2022. 
• The real weekly earnings gap between veterans and comparable nonveterans disappeared as of the spring of 2022.

Understanding labor market disparities between veterans and nonveterans is important to studying disparities in the economy overall. For additional resources on the New York Fed’s work related to understanding how macroeconomic trends vary across geographic, demographic, and socioeconomic boundaries, check out our Equitable Growth Indicators , Economic Inequality Research Series , and Economic Inequality & Equitable Growth resources.

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What’s Up with Inflation Expectations in Japan?

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FRBSF Economic Letter 2024-13 | May 20, 2024

Both actual inflation and inflation expectations increased recently in Japan after decades of being undesirably low. An estimate based on nominal and real Japanese bond yields adjusted for liquidity and other risk premiums confirms that investors’ long-term inflation expectations have also increased. However, projections indicate that further increases are less likely and that long-term expected inflation in Japan is likely to remain anchored below the Bank of Japan’s 2% inflation target.

Inflation in Japan was below desirable levels for decades, including episodes of actual deflation. In response, the Bank of Japan tried various policies to raise inflation, including the adoption of a formal 2% inflation target in 2013. However, none of those efforts succeeded in achieving a persistent rise in inflation (see Christensen and Spiegel 2019 for a review). Since spring 2022, though, there has been a notable and seemingly lasting increase in Japanese inflation. Moreover, there are tentative signs that inflation expectations in Japan may have moved up in response to the spike in inflation. For example, surveys indicate that professional forecasters have lifted both their short-term forecasts for inflation in 2024 and their long-term expectations for average inflation over the coming decade.

This upturn in inflation and measures of expected inflation coincides with a booming stock market—Japan’s Nikkei index recently surpassed its previous 1989 all-time high—suggesting investor optimism. At the same time, though, measures of economic growth over the last couple of quarters have been disappointing, which may reflect declining economic momentum.

Given Japan’s difficulty escaping its long history of undesirably low inflation, the sustainability of the recent upturn remains in question. In this Economic Letter , we turn to Japanese bond markets to produce market-based estimates of investors’ expectations for future inflation using a novel model of nominal and real Japanese government bond yields described in Christensen and Spiegel (2024). Our yield curve model is the first to account for liquidity risk in real yields while also adjusting for inflation and deflation risk premia. Our results indicate that long-term inflation expectations have increased over the past couple of years, above levels indicated by recent survey data. However, our model projections suggest that further increases are less likely and that long-term expectations for future inflation will remain anchored below Japan’s 2% inflation target.

Recent inflation developments in Japan

Consumer price index (CPI) inflation in Japan has been well below the 2% target adopted by the Bank of Japan in 2013 for much of this century. This has included several periods of declining prices, such as during the Global Financial Crisis and the COVID-19 pandemic (Figure 1).

Figure 1 Japanese CPI inflation

The increase in inflation since spring 2022 may have changed Japanese inflation dynamics in a lasting way. One noticeable change is that inflation has remained elevated for several months. Also, there are early signs that inflation expectations in Japan may have started to respond. Figure 2 shows that professional forecasters surveyed by Consensus Economics have progressively lifted their monthly responses for the short-term inflation outlook for 2024, reflected in the median projection (solid blue line) and range of forecasts (dashed blue lines). Perhaps more importantly, they also raised their long-term expectations for average inflation over the next 10 years. These are reported every six months and are shown as a green data point for the 10-year forecast as of each corresponding survey date.

Figure 2 Short-and long-term Japanese CPI inflation forecasts

Given Japan’s history of unsuccessful attempts at raising inflation, it remains unclear whether recent increases in inflation are likely to be sustained. One risk is that long-term inflation expectations could return to their pre-pandemic lower levels, as has happened in the past. Maintaining long-term inflation expectations that are anchored near the Bank of Japan’s 2% inflation target is likely necessary for achieving and sustaining that target.

Using bond pricing to estimate inflation expectations

Following our work in Christensen and Spiegel (2024), we generate market-based estimates of expected long-term Japanese inflation. We examine yields for inflation-indexed bonds issued by the Japanese government from January 2005 to the end of March 2024. We also include a sample of Japanese nominal zero-coupon government bond yields from 1995 through the end of March 2024.

Japanese inflation-indexed bonds have always protected against inflation by adjusting interest payments, known as coupons, and principal payments to compensate holders for increases in the Japanese CPI from issuance to maturity. However, inflation-indexed bonds issued since 2013 also provide “deflation protection,” in that they pay off their nominal payment at maturity if deflation has occurred over the lifetime of the bond. Due to Japan’s very low inflation and occasional deflation over the past 20 years, this protection has turned out to be valuable—worth well over half a percentage point for extended periods.

The difference between nominal and inflation-adjusted yields on bonds of the same maturity, commonly known as the breakeven inflation (BEI) rate, is widely used to assess inflation expectations. However, there are three distinctions between the BEI rate implied by Japan’s inflation-indexed bonds and expected inflation. First, BEI rates contain an inflation risk premium, which is the additional positive or negative return required by investors to compensate for exposure to risk associated with future inflation. Second, BEI rates also reflect the value of deflation protection discussed earlier. This enhancement raises the value of inflation-indexed bonds and hence pushes down their real yields, which can distort upwards the measurement of inflation expectations through BEI rates. Finally, variation in the relative liquidity between the tiny inflation-indexed bond market, which represents only about 1% of government debt in Japan, and the huge nominal Japanese government bond market can add an additional layer of distortion.

Using the Christensen and Spiegel (2024) model, we adjust observed BEI rates for all three distortions, namely inflation risk premia, deflation protection, and liquidity. We also incorporate the semiannual 10-year forecasts of CPI inflation from the Consensus Economics survey of professional forecasters into our model estimation. As shown by Kim and Orphanides (2012), incorporating these external forecasts tends to improve the plausibility over long horizons. However, to ensure our results are driven by market data, we minimize the impact of the survey information by only including the survey forecasts once every two years. We use the April forecasts in uneven years since 2005.

Result of BEI according to components

Figure 3 breaks out some components of the 10-year BEI rates produced by our model. The red line shows the observed 10-year BEI rate without any adjustment. Although it has trended up since 2020, it remained well below the Bank of Japan’s 2% inflation target. After adjustments for liquidity risk premiums and the value of deflation protection, we are left with the adjusted 10-year BEI rate (light blue line). The wedge between the two 10-year BEI rates is driven primarily by the value of the deflation protection. This wedge was small prior to 2013 because the indexed bonds trading at that time did not provide this protection. Importantly, after these adjustments, long-term BEI rates in Japan have been generally lower than unadjusted BEI rates would suggest.

Figure 3 Japan’s 10-year breakeven inflation components

Our model, combined with our assumption of no arbitrage in the deep and liquid Japanese bond market, can also be used to gauge investors’ expected inflation over the next 10 years, shown in the figure as a dark blue line. Finally, we calculate the residual 10-year inflation risk premium (green line) by deducting our estimated 10-year expected inflation from the 10-year adjusted BEI rate. Our estimate of expected inflation has been relatively stable and usually remains well above the observed 10-year BEI rate. In contrast, our estimate of the 10-year inflation risk premium has been volatile and almost always negative.

Most of the recent increase in unadjusted 10-year BEI rates reflects the increase in the inflation risk premium, which has turned positive as the risk of very low inflation has declined. This is a sign that the outlook for inflation in Japan is now more balanced than it has been over the past 10 years. In comparison, 10-year expected inflation has experienced a more modest but still notable uptick since 2020.

Outlook for long-term inflation expectations

So where do Japan’s long-term inflation expectations go from here? To offer an answer, we follow the approach of Christensen, Lopez, and Rudebusch (2015) and simulate paths over a 10-year horizon, accounting for the shape of the nominal and real yield curves and investors’ embedded forward-looking expectations as of the end of our sample.

Figure 4 extends our estimate from Figure 3 to show the median projection for our 10-year expected inflation through 2034 (dashed dark blue line). The median projection suggests that 10-year expected inflation is predicted to drop to a level close to 1.20% within the next 24 months and stay there for the remainder of the projection period. However, the wide range of the 99% confidence bands around our median estimate (dashed light blue lines) reflects sizable uncertainty around this point prediction, particularly at long horizons.

Figure 4 Projections of 10-year expected inflation in Japan

For perspective, Figure 4 also shows that our estimates of 10-year expected inflation tended to be above the Consensus Economics survey results, shown by the biennial green data points used in our model estimation. This suggests that bond investors appear to have been more optimistic than professional forecasters about the long-term outlook for inflation in Japan since 2005. The mild upward bias leads us to conclude that further increases in expected long-term inflation in Japan are likely to be limited. Moreover, long-term expected inflation will most likely remain anchored at a level somewhat below the 2% target set by the Bank of Japan. Note, however, that our projections and confidence bands suggest that investors do not expect a return to Japanese deflation over the next 10 years and allows for long-term inflation expectations to remain anchored around current levels.

After several decades of very low and at times negative price changes, inflation in Japan recently surged above the 2% inflation target set by the Bank of Japan in 2013. At the same time, survey evidence suggests that inflation expectations in Japan have moved higher. However, mixed signals from Japanese economic activity and Japanese equity markets raise the question of whether this increase in Japanese inflation will be sustained.

In this Letter , we estimate long-term Japanese inflation expectations using a novel model of nominal and real Japanese government bond yields that adjusts for inflation risk, liquidity risk, and the deflation protection afforded by Japanese inflation-indexed bonds issued since 2013. Our estimates confirm that investors’ long-term expected inflation has trended up over the past couple of years. However, our projections suggest that long-term expected inflation is not likely to increase much further in the coming years, leaving inflation expectations in Japan anchored at a level below the Bank of Japan’s 2% inflation target.

Christensen, Jens H.E., Jose A. Lopez, and Glenn D. Rudebusch. 2015. “A Probability-Based Stress Test of Federal Reserve Assets and Income.” Journal of Monetary Economics 73, pp. 26–43.

Christensen, Jens H.E., and Mark M. Spiegel. 2019. “ Negative Interest Rates and Inflation Expectations in Japan .” FRBSF Economic Letter 2019-22 (August 26).

Christensen, Jens H.E., and Mark M. Spiegel. 2022. “Monetary Reforms and Inflation Expectations in Japan: Evidence from Inflation-Indexed Bonds.” Journal of Econometrics 231(2), pp. 410–431.

Christensen, Jens H.E., and Mark M. Spiegel. 2024. “Inflation Expectations, Liquidity Premia and Global Spillovers in Japanese Bond Markets.” FRB San Francisco Working Paper 2024-12.

Kim, Don H., and Athanasios Orphanides. 2012. “Term Structure Estimation with Survey Data on Interest Rate Forecasts.” Journal of Financial and Quantitative Analysis 47(1), pp. 241–272.

Opinions expressed in FRBSF Economic Letter do not necessarily reflect the views of the management of the Federal Reserve Bank of San Francisco or of the Board of Governors of the Federal Reserve System. This publication is edited by Anita Todd and Karen Barnes. Permission to reprint portions of articles or whole articles must be obtained in writing. Please send editorial comments and requests for reprint permission to [email protected]

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Is Fidelity Select Banking (FSRBX) a Strong Mutual Fund Pick Right Now?

There are plenty of choices in the Sector - Finance category, but where should you start your research? Well, one fund that might be worth investigating is Fidelity Select Banking ( FSRBX Quick Quote FSRBX - Free Report ) . FSRBX bears a Zacks Mutual Fund Rank of 1 (Strong Buy), which is based on various forecasting factors like size, cost, and past performance.

FSRBX is one of many Sector - Finance funds to choose from. Sector - Finance mutual funds provide investors with a diversified and stabilized investment approach focused on the financial space, which is a notoriously large, complex, and heavily-regulated industry. These funds include everything from insurance companies and exchanges to banks and investment giants; interest rates can impact the players of this space as well.

History of Fund/Manager

Fidelity is responsible for FSRBX, and the company is based out of Boston, MA. Since Fidelity Select Banking made its debut in June of 1986, FSRBX has garnered more than $373.37 million in assets. Matt Reed is the fund's current manager and has held that role since September of 2016.

Performance

Investors naturally seek funds with strong performance. This fund carries a 5-year annualized total return of 5.66%, and it sits in the bottom third among its category peers. But if you are looking for a shorter time frame, it is also worth looking at its 3-year annualized total return of 0.31%, which places it in the middle third during this time-frame.

It is important to note that the product's returns may not reflect all its expenses. Any fees not reflected would lower the returns. Total returns do not reflect the fund's [%] sale charge. If sales charges were included, total returns would have been lower.

When looking at a fund's performance, it is also important to note the standard deviation of the returns. The lower the standard deviation, the less volatility the fund experiences. Over the past three years, FSRBX's standard deviation comes in at 26.85%, compared to the category average of 22.4%. Over the past 5 years, the standard deviation of the fund is 30.52% compared to the category average of 25.6%. This makes the fund more volatile than its peers over the past half-decade.

Risk Factors

Investors should not forget about beta, an important way to measure a mutual fund's risk compared to the market as a whole. FSRBX has a 5-year beta of 1.14, which means it is likely to be more volatile than the market average. Because alpha represents a portfolio's performance on a risk-adjusted basis relative to a benchmark, which is the S&P 500 in this case, one should pay attention to this metric as well. FSRBX's 5-year performance has produced a negative alpha of -5.36, which means managers in this portfolio find it difficult to pick securities that generate better-than-benchmark returns.

Costs are increasingly important for mutual fund investing, and particularly as competition heats up in this market. And all things being equal, a lower cost product will outperform its otherwise identical counterpart, so taking a closer look at these metrics is key for investors. In terms of fees, FSRBX is a no load fund. It has an expense ratio of 0.77% compared to the category average of 1.24%. So, FSRBX is actually cheaper than its peers from a cost perspective.

Investors should also note that the minimum initial investment for the product is $0 and that each subsequent investment has no minimum amount.

Fees charged by investment advisors have not been taken into considiration. Returns would be less if those were included.

Bottom Line

Overall, Fidelity Select Banking ( FSRBX ) has a high Zacks Mutual Fund rank, and in conjunction with its comparatively similar performance, average downside risk, and lower fees, this fund looks like a great potential choice for investors right now.

Your research on the Sector - Finance segment doesn't have to stop here. You can check out all the great mutual fund tools we have to offer by going to www.zacks.com/funds/mutual-funds to see the additional features we offer as well for additional information. And don't forget, Zacks has all of your needs covered on the equity side too! Make sure to check out Zacks.com for more information on our screening capabilities, Rank, and all our articles as well.

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Water security is critical for poverty reduction, but billions will remain without water access unless urgent action is taken

WASHINGTON, May 20, 2024 — Access to safe drinking water and sanitation, reliable water-supply for agriculture and industry, and protection against droughts and floods are essential for human and economic development, a World Bank report released on Monday states.

Over the past 20 years, the number of people lacking safe drinking water and basic sanitation has increased by 197 million and 211 million, respectively. Today, over two billion people still lack access to safe drinking water, and 3.5 billion are deprived of safely managed sanitation facilities. Resulting infectious diseases contribute to at least 1.4 million annual deaths and 50% of global malnutrition.

Lack of access to safe water and sanitation is particularly harmful in childhood, Water for Shared Prosperity , a report released at the 10 th World Water Forum in Bali, Indonesia by the World Bank Group and the Government of Indonesia, says. Inadequate and unsafe water affects early childhood development, and time spent fetching water, inadequate sanitation and hygiene and droughts or floods disrupt learning and lead to school dropouts.

Climate change is amplifying water-related risks. Driven by global emissions, developing countries are most affected by climate shocks. Between 2000 and 2021, developing countries experienced more severe droughts and longer lasting floods than advanced economies, with long-term effects on nutrition, school attendance and economic welfare. Developing countries disproportionately rely on water-dependent sectors, particularly agriculture, for employment. Globally, over 800 million people are at high-risk of droughts and twice as many live in flood-risk hotspots.

“To improve livelihoods, significant reforms and investments are needed to provide efficiently managed water and sanitation services to those without access, and to strengthen resilience against hydro-climatic risks,” said World Bank Vice President for East Asia and the Pacific Manuela V. Ferro , who is leading the World Bank team at the World Water Forum.

Water for Shared Prosperity offers specific recommendations on how to improve water security in developing countries: Protecting depleting aquifers and unevenly distributed freshwater resources will require more international cooperation, implementing proven nature-based solutions such as reforestation and investing in water storage infrastructure to prevent run-off and make water available in dry periods.

Policies to upgrade housing, and land use regulations to prevent construction in flood-prone areas can reduce exposure. Early warning systems and insurance can help households and farmers cope with extreme hydro-climatic shocks.

Reforming water tariffs and poorly-targeted subsidies, while ensuring affordability for low-income households, can help maintain and expand services and allocate scarce water resources fairly. Service providers will also need to enhance their operations, reducing water losses and lowering operating costs. Supported by policies that ensure transparency and accountability, the private sector can offer valuable expertise to enhance efficiency and manage complex infrastructure.

A spotlight section of the report examines how Indonesia, the host of this year's triennial World Water Forum, is addressing water security challenges. Indonesia has made significant investments to enhance resilience to climate-related risks, including investments in 61 dams to store water and increase irrigated areas.  A Community-Based Water Supply Program has provided more than 24 million people with improved water facilities. The government has prioritized reducing pollution and environmental degradation in the Citarum River Basin in West Java, and is pioneering treatment of peat water to making it suitable for drinking through the National Urban Water Supply project.

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