research paper on business finance

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals

Finance articles from across Nature Portfolio

Latest research and reviews.

Analysing the impact of digital technology diffusion on the efficiency and convergence process of the commercial banking industry of Pakistan

• Ting Li Liu
• Muhammad Mateen Naveed
• Muhammad Tahir Naveed

Data selection and collection for constructing investor sentiment from social media

Effect of government expenditure on real economic growth in ECOWAS: assessing the moderating role of corruption and conflict

• Olalekan Charles Okunlola
• Imran Usman Sani
• Olajide O. Oyadeyi

A comprehensive framework for understanding microfinance performance evaluation methods

• Javier Sierra
• Victoria Muriel-Patino
• Fernando Rodríguez-López

In quest of perceived transaction cost’s impact on fintech users’ intention: the moderating role of situational factors

• Haifeng Zhao
• Nosherwan Khaliq

Bitcoin’s bubbly behaviors: does it resemble other financial bubbles of the past?

• Sergio Luis Náñez Alonso
• Javier Jorge-Vázquez
• David Sanz-Bas

News and Comment

Hunger, debt and interest rates

Financial imperatives to food system transformation

Finance is a critical catalyst of food systems transformation. At the 2021 United Nations Food Systems Summit, the Financial Lever Group suggested five imperatives to tap into new financial resources while making better use of existing ones. These imperatives are yet to garner greater traction to instigate meaningful change.

• Eugenio Diaz-Bonilla
• Brian McNamara

Central bank digital currencies risk becoming a digital Leviathan

Central bank digital currencies (CBDCs) already exist in several countries, with many more on the way. But although CBDCs can promote financial inclusivity by offering convenience and low transaction costs, their adoption must not lead to the loss of privacy and erosion of civil liberties.

• Andrea Baronchelli
• Hanna Halaburda
• Alexander Teytelboym

ESG performance of ports

An article in Case Studies on Transport Policy quantifies the environmental, social, and governance performances of three ports.

• Laura Zinke

Venture capital accelerates food technology innovation

Start-ups are now the predominant source of innovation in all categories of food technology. Venture capital can accelerate innovation by enabling start-ups to pursue niche areas, iterate more rapidly and take more risks than larger companies, writes Samir Kaul.

Challenges for a climate risk disclosure mandate

The United States and other G7 countries are considering a framework for mandatory climate risk disclosure by companies. However, unless a globally acceptable hybrid corporate governance model can be forged to address the disparities among different countries’ governance systems, the proposed framework may not succeed.

• Paul Griffin
• Amy Myers Jaffe

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Finance and Financial Data

• Analyst Reports
• Earnings Call Transcripts
• Private Companies & Startups
• Stocks & Bonds
• Deals and M&A
• Commodities
• ESG / Sustainability
• Real Estate This link opens in a new window
• Finding Financial Data
• Top-Ranked Finance Journals

Ask a Librarian

You will be connected with a business specialist first, if available.

A Selection of Top-Ranked Finance Journals

• Accounting Review
• Financial Analysts Journal
• Journal of Banking & Finance
• Journal of Corporate Finance
• Journal of Finance
• Journal of Financial Economics
• Journal of Portfolio Management
• Quantitative Finance
• Review of Financial Studies

Search NYU's Electronic Journal Subscriptions by Title

• Search by E-Journal Title

Resources for Finding Finance Scholarship

• ABI/INFORM This link opens in a new window ABI/INFORM features full-text journals, dissertations, working papers, key business, and economics periodicals. Researchers can locate country- and industry-focused reports, and its international focus provides a picture of companies and business trends around the world.
• Business Source Complete This link opens in a new window Business Source Complete is a full text database of articles from popular, scholarly, and trade publications. Subjects covered include management, economics, finance, accounting, international business. Dates of coverage: 1886 to present.
• Google Scholar This link opens in a new window Google Scholar is a central search for scholarly literature. It covers disciplines and sources, peer-reviewed papers, theses, books, abstracts and articles, from academic publishers, professional societies, preprint repositories, universities and other scholarly organizations.
• << Previous: Finding Financial Data
• Next: FAQs >>
• Last Updated: Jun 13, 2024 8:36 PM
• URL: https://guides.nyu.edu/finance

• Youth Program
• Wharton Online

Research Papers / Publications

Research Topics & Ideas: Finance

120+ Finance Research Topic Ideas To Fast-Track Your Project

If you’re just starting out exploring potential research topics for your finance-related dissertation, thesis or research project, you’ve come to the right place. In this post, we’ll help kickstart your research topic ideation process by providing a hearty list of finance-centric research topics and ideas.

PS – This is just the start…

We know it’s exciting to run through a list of research topics, but please keep in mind that this list is just a starting point . To develop a suitable education-related research topic, you’ll need to identify a clear and convincing research gap , and a viable plan of action to fill that gap.

If this sounds foreign to you, check out our free research topic webinar that explores how to find and refine a high-quality research topic, from scratch. Alternatively, if you’d like hands-on help, consider our 1-on-1 coaching service .

Overview: Finance Research Topics

• Corporate finance topics
• Investment banking topics
• Private equity & VC
• Asset management
• Hedge funds
• Financial planning & advisory
• Quantitative finance
• Treasury management
• Financial technology (FinTech)
• Commercial banking
• International finance

Corporate Finance

These research topic ideas explore a breadth of issues ranging from the examination of capital structure to the exploration of financial strategies in mergers and acquisitions.

• Evaluating the impact of capital structure on firm performance across different industries
• Assessing the effectiveness of financial management practices in emerging markets
• A comparative analysis of the cost of capital and financial structure in multinational corporations across different regulatory environments
• Examining how integrating sustainability and CSR initiatives affect a corporation’s financial performance and brand reputation
• Analysing how rigorous financial analysis informs strategic decisions and contributes to corporate growth
• Examining the relationship between corporate governance structures and financial performance
• A comparative analysis of financing strategies among mergers and acquisitions
• Evaluating the importance of financial transparency and its impact on investor relations and trust
• Investigating the role of financial flexibility in strategic investment decisions during economic downturns
• Investigating how different dividend policies affect shareholder value and the firm’s financial performance

Investment Banking

The list below presents a series of research topics exploring the multifaceted dimensions of investment banking, with a particular focus on its evolution following the 2008 financial crisis.

• Analysing the evolution and impact of regulatory frameworks in investment banking post-2008 financial crisis
• Investigating the challenges and opportunities associated with cross-border M&As facilitated by investment banks.
• Evaluating the role of investment banks in facilitating mergers and acquisitions in emerging markets
• Analysing the transformation brought about by digital technologies in the delivery of investment banking services and its effects on efficiency and client satisfaction.
• Evaluating the role of investment banks in promoting sustainable finance and the integration of Environmental, Social, and Governance (ESG) criteria in investment decisions.
• Assessing the impact of technology on the efficiency and effectiveness of investment banking services
• Examining the effectiveness of investment banks in pricing and marketing IPOs, and the subsequent performance of these IPOs in the stock market.
• A comparative analysis of different risk management strategies employed by investment banks
• Examining the relationship between investment banking fees and corporate performance
• A comparative analysis of competitive strategies employed by leading investment banks and their impact on market share and profitability

Private Equity & Venture Capital (VC)

These research topic ideas are centred on venture capital and private equity investments, with a focus on their impact on technological startups, emerging technologies, and broader economic ecosystems.

• Investigating the determinants of successful venture capital investments in tech startups
• Analysing the trends and outcomes of venture capital funding in emerging technologies such as artificial intelligence, blockchain, or clean energy
• Assessing the performance and return on investment of different exit strategies employed by venture capital firms
• Assessing the impact of private equity investments on the financial performance of SMEs
• Analysing the role of venture capital in fostering innovation and entrepreneurship
• Evaluating the exit strategies of private equity firms: A comparative analysis
• Exploring the ethical considerations in private equity and venture capital financing
• Investigating how private equity ownership influences operational efficiency and overall business performance
• Evaluating the effectiveness of corporate governance structures in companies backed by private equity investments
• Examining how the regulatory environment in different regions affects the operations, investments and performance of private equity and venture capital firms

Asset Management

This list includes a range of research topic ideas focused on asset management, probing into the effectiveness of various strategies, the integration of technology, and the alignment with ethical principles among other key dimensions.

• Analysing the effectiveness of different asset allocation strategies in diverse economic environments
• Analysing the methodologies and effectiveness of performance attribution in asset management firms
• Assessing the impact of environmental, social, and governance (ESG) criteria on fund performance
• Examining the role of robo-advisors in modern asset management
• Evaluating how advancements in technology are reshaping portfolio management strategies within asset management firms
• Evaluating the performance persistence of mutual funds and hedge funds
• Investigating the long-term performance of portfolios managed with ethical or socially responsible investing principles
• Investigating the behavioural biases in individual and institutional investment decisions
• Examining the asset allocation strategies employed by pension funds and their impact on long-term fund performance
• Assessing the operational efficiency of asset management firms and its correlation with fund performance

Hedge Funds

Here we explore research topics related to hedge fund operations and strategies, including their implications on corporate governance, financial market stability, and regulatory compliance among other critical facets.

• Assessing the impact of hedge fund activism on corporate governance and financial performance
• Analysing the effectiveness and implications of market-neutral strategies employed by hedge funds
• Investigating how different fee structures impact the performance and investor attraction to hedge funds
• Evaluating the contribution of hedge funds to financial market liquidity and the implications for market stability
• Analysing the risk-return profile of hedge fund strategies during financial crises
• Evaluating the influence of regulatory changes on hedge fund operations and performance
• Examining the level of transparency and disclosure practices in the hedge fund industry and its impact on investor trust and regulatory compliance
• Assessing the contribution of hedge funds to systemic risk in financial markets, and the effectiveness of regulatory measures in mitigating such risks
• Examining the role of hedge funds in financial market stability
• Investigating the determinants of hedge fund success: A comparative analysis

Financial Planning and Advisory

This list explores various research topic ideas related to financial planning, focusing on the effects of financial literacy, the adoption of digital tools, taxation policies, and the role of financial advisors.

• Evaluating the impact of financial literacy on individual financial planning effectiveness
• Analysing how different taxation policies influence financial planning strategies among individuals and businesses
• Evaluating the effectiveness and user adoption of digital tools in modern financial planning practices
• Investigating the adequacy of long-term financial planning strategies in ensuring retirement security
• Assessing the role of financial education in shaping financial planning behaviour among different demographic groups
• Examining the impact of psychological biases on financial planning and decision-making, and strategies to mitigate these biases
• Assessing the behavioural factors influencing financial planning decisions
• Examining the role of financial advisors in managing retirement savings
• A comparative analysis of traditional versus robo-advisory in financial planning
• Investigating the ethics of financial advisory practices

The following list delves into research topics within the insurance sector, touching on the technological transformations, regulatory shifts, and evolving consumer behaviours among other pivotal aspects.

• Analysing the impact of technology adoption on insurance pricing and risk management
• Analysing the influence of Insurtech innovations on the competitive dynamics and consumer choices in insurance markets
• Investigating the factors affecting consumer behaviour in insurance product selection and the role of digital channels in influencing decisions
• Assessing the effect of regulatory changes on insurance product offerings
• Examining the determinants of insurance penetration in emerging markets
• Evaluating the operational efficiency of claims management processes in insurance companies and its impact on customer satisfaction
• Examining the evolution and effectiveness of risk assessment models used in insurance underwriting and their impact on pricing and coverage
• Evaluating the role of insurance in financial stability and economic development
• Investigating the impact of climate change on insurance models and products
• Exploring the challenges and opportunities in underwriting cyber insurance in the face of evolving cyber threats and regulations

Quantitative Finance

These topic ideas span the development of asset pricing models, evaluation of machine learning algorithms, and the exploration of ethical implications among other pivotal areas.

• Developing and testing new quantitative models for asset pricing
• Analysing the effectiveness and limitations of machine learning algorithms in predicting financial market movements
• Assessing the effectiveness of various risk management techniques in quantitative finance
• Evaluating the advancements in portfolio optimisation techniques and their impact on risk-adjusted returns
• Evaluating the impact of high-frequency trading on market efficiency and stability
• Investigating the influence of algorithmic trading strategies on market efficiency and liquidity
• Examining the risk parity approach in asset allocation and its effectiveness in different market conditions
• Examining the application of machine learning and artificial intelligence in quantitative financial analysis
• Investigating the ethical implications of quantitative financial innovations
• Assessing the profitability and market impact of statistical arbitrage strategies considering different market microstructures

Treasury Management

The following topic ideas explore treasury management, focusing on modernisation through technological advancements, the impact on firm liquidity, and the intertwined relationship with corporate governance among other crucial areas.

• Analysing the impact of treasury management practices on firm liquidity and profitability
• Analysing the role of automation in enhancing operational efficiency and strategic decision-making in treasury management
• Evaluating the effectiveness of various cash management strategies in multinational corporations
• Investigating the potential of blockchain technology in streamlining treasury operations and enhancing transparency
• Examining the role of treasury management in mitigating financial risks
• Evaluating the accuracy and effectiveness of various cash flow forecasting techniques employed in treasury management
• Assessing the impact of technological advancements on treasury management operations
• Examining the effectiveness of different foreign exchange risk management strategies employed by treasury managers in multinational corporations
• Assessing the impact of regulatory compliance requirements on the operational and strategic aspects of treasury management
• Investigating the relationship between treasury management and corporate governance

Financial Technology (FinTech)

The following research topic ideas explore the transformative potential of blockchain, the rise of open banking, and the burgeoning landscape of peer-to-peer lending among other focal areas.

• Evaluating the impact of blockchain technology on financial services
• Investigating the implications of open banking on consumer data privacy and financial services competition
• Assessing the role of FinTech in financial inclusion in emerging markets
• Analysing the role of peer-to-peer lending platforms in promoting financial inclusion and their impact on traditional banking systems
• Examining the cybersecurity challenges faced by FinTech firms and the regulatory measures to ensure data protection and financial stability
• Examining the regulatory challenges and opportunities in the FinTech ecosystem
• Assessing the impact of artificial intelligence on the delivery of financial services, customer experience, and operational efficiency within FinTech firms
• Analysing the adoption and impact of cryptocurrencies on traditional financial systems
• Investigating the determinants of success for FinTech startups

Commercial Banking

These topic ideas span commercial banking, encompassing digital transformation, support for small and medium-sized enterprises (SMEs), and the evolving regulatory and competitive landscape among other key themes.

• Assessing the impact of digital transformation on commercial banking services and competitiveness
• Analysing the impact of digital transformation on customer experience and operational efficiency in commercial banking
• Evaluating the role of commercial banks in supporting small and medium-sized enterprises (SMEs)
• Investigating the effectiveness of credit risk management practices and their impact on bank profitability and financial stability
• Examining the relationship between commercial banking practices and financial stability
• Evaluating the implications of open banking frameworks on the competitive landscape and service innovation in commercial banking
• Assessing how regulatory changes affect lending practices and risk appetite of commercial banks
• Examining how commercial banks are adapting their strategies in response to competition from FinTech firms and changing consumer preferences
• Analysing the impact of regulatory compliance on commercial banking operations
• Investigating the determinants of customer satisfaction and loyalty in commercial banking

International Finance

The folowing research topic ideas are centred around international finance and global economic dynamics, delving into aspects like exchange rate fluctuations, international financial regulations, and the role of international financial institutions among other pivotal areas.

• Analysing the determinants of exchange rate fluctuations and their impact on international trade
• Analysing the influence of global trade agreements on international financial flows and foreign direct investments
• Evaluating the effectiveness of international portfolio diversification strategies in mitigating risks and enhancing returns
• Evaluating the role of international financial institutions in global financial stability
• Investigating the role and implications of offshore financial centres on international financial stability and regulatory harmonisation
• Examining the impact of global financial crises on emerging market economies
• Examining the challenges and regulatory frameworks associated with cross-border banking operations
• Assessing the effectiveness of international financial regulations
• Investigating the challenges and opportunities of cross-border mergers and acquisitions

Choosing A Research Topic

These finance-related research topic ideas are starting points to guide your thinking. They are intentionally very broad and open-ended. By engaging with the currently literature in your field of interest, you’ll be able to narrow down your focus to a specific research gap .

When choosing a topic , you’ll need to take into account its originality, relevance, feasibility, and the resources you have at your disposal. Make sure to align your interest and expertise in the subject with your university program’s specific requirements. Always consult your academic advisor to ensure that your chosen topic not only meets the academic criteria but also provides a valuable contribution to the field. 

If you need a helping hand, feel free to check out our private coaching service here.

You Might Also Like:

thank you for suggest those topic, I want to ask you about the subjects related to the fintech, can i measure it and how?

Please guide me on selecting research titles

Submit a Comment Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

• Print Friendly

• Harvard Business School →
• Faculty & Research →
• Featured Topics
• Business & Environment
• Business History
• Entrepreneurship
• Globalization
• Health Care
• Human Behavior & Decision-Making
• Social Enterprise
• Technology & Innovation

Dynamics of Demand for Index Insurance: Evidence from a Long-Run Field Experiment

This paper estimates how experimentally-manipulated experiences with a novel financial product, rainfall index insurance, affect subsequent insurance demand. Using a seven-year panel, we develop three main findings. First, recent experience matters for demand, consistent with overinference from small samples. Second, spillovers also matter, in the sense that the recent payout experience of village co-residents affects insurance demand about as much as one's own recent payout experience. Third, the spillover effect decays as time passes while the effect of one's own experience does not. We discuss implications of this analysis for commercial sustainability of this complicated but promising risk management technology.

This paper estimates how experimentally-manipulated experiences with a novel financial product, rainfall index insurance, affect subsequent insurance demand. Using a seven-year panel, we develop three main findings. First, recent experience matters for demand, consistent with overinference from small samples. Second, spillovers also matter, in the...

Expectations of Returns and Expected Returns

We analyze time-series of investor expectations of future stock market returns from six data sources between 1963 and 2011. The six measures of expectations are highly positively correlated with each other, as well as with past stock returns and with the level of the stock market. However, investor expectations are strongly negatively correlated with model-based expected returns. The evidence is not consistent with rational expectations representative investor models of returns.

We analyze time-series of investor expectations of future stock market returns from six data sources between 1963 and 2011. The six measures of expectations are highly positively correlated with each other, as well as with past stock returns and with the level of the stock market. However, investor expectations are strongly negatively correlated...

• August 2014

Mortgage Convexity

Most home mortgages in the United States are fixed-rate loans with an embedded prepayment option. When long-term rates decline, the effective duration of mortgage-backed securities (MBS) falls due to heightened refinancing expectations. I show that these changes in MBS duration function as large-scale shocks to the quantity of interest rate risk that must be borne by professional bond investors. I develop a simple model in which the risk tolerance of bond investors is limited in the short run, so these fluctuations in MBS duration generate significant variation in bond risk premia. Specifically, bond risk premia are high when aggregate MBS duration is high. The model offers an explanation for why long-term rates could appear to be excessively sensitive to movements in short rates and explains how changes in MBS duration act as a positive-feedback mechanism that amplifies interest rate volatility. I find strong support for these predictions in the time series of US government bond returns.

Most home mortgages in the United States are fixed-rate loans with an embedded prepayment option. When long-term rates decline, the effective duration of mortgage-backed securities (MBS) falls due to heightened refinancing expectations. I show that these changes in MBS duration function as large-scale shocks to the quantity of interest rate risk...

• Working Paper

Financial Repression in the European Sovereign Debt Crisis

By the end of 2013, the share of government debt held by the domestic banking sectors of Eurozone countries was more than twice its 2007 level. We show that this type of increasing reliance on the domestic banking sector for absorbing government bonds generates a crowding out of corporate lending. For a given domestic firm, new debt is less likely to be a loan—i.e., the loan supply contracts—when local banks have purchased more domestic sovereign debt and when that debt is risky (as measured by CDS spreads). These effects are most pronounced in the period following the second Greek bailout in early 2010.

By the end of 2013, the share of government debt held by the domestic banking sectors of Eurozone countries was more than twice its 2007 level. We show that this type of increasing reliance on the domestic banking sector for absorbing government bonds generates a crowding out of corporate lending. For a given domestic firm, new debt is less likely...

Faculty Unit

Our intellectual roots are based in a long line of scholars from Robert Merton whose collaborative work on risk management and option pricing won him the Nobel Prize in Economics in 1997, to John Lintner who co-created the Capital Asset Pricing Model and made significant contributions to dividend policy , and Gordon Donaldson whose work helped shape the field of corporate finance . We strive to understand how managers and firms make value-enhancing decisions; and how financial institutions, markets, and instruments contribute to this process. Our approach to research is distinguished by its unique combination of theory, empirical analysis, mathematical modeling, and field observations at companies.

The Finance Unit produces research addressing issues of present and future importance to managers, regulators, and policy-makers.

Recent Publications

Driving scale with otto.

• June 2024 |
• Faculty Research

Investor Influence on Media Coverage: Evidence from Venture Capital-Backed Startups

• Working Paper |

Real Growth in Space Manufacturing Output Substantially Exceeds Growth in the Overall Space Economy

• Acta Astronautica

MStudio and Djoli: Accelerating Startup Growth in Francophone Africa

Private equity and digital transformation, creditor-on-creditor violence and secured debt dynamics, bank runs and interest rates: a revolving lines perspective, production complementarity and information transmission across industries.

• Journal of Financial Economics

Does the Case for Private Equity Still Hold?

Demand-and-supply imbalance risk and long-term swap spreads.

• April 2024 |

HBS Working Knowlege

• 18 Jun 2024

How Natural Winemaker Frank Cornelissen Innovated While Staying True to His Brand

Central banks missed inflation red flags. this pricing model could help., what your non-binary employees need to do their best work, harvard business publishing.

• December 9, 2020

Give Employees Cash to Purchase Their Own Insurance

Hbr guide to buying a small business: think big, buy small, own your own company.

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

•  We're Hiring!
•  Help Center

Business & Finance

• Most Cited Papers
• Most Downloaded Papers
• Newest Papers
• Save to Library
• Financial Reporting Follow Following
• Essays Follow Following
• Cross-Cultural Studies Follow Following
• Accounting and Auditing Follow Following
• Information Systems Audit Follow Following
• Technology Management Follow Following
• Logistics Follow Following
• Supply Chain Management Follow Following
• Anglo-Boer War 1899-1902 Follow Following
• Employees’ Job Satisfaction Follow Following

Enter the email address you signed up with and we'll email you a reset link.

• Academia.edu Publishing
•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

• DOI: 10.34069/ai/2023.63.03.1
• Corpus ID: 258898259

The impact of debt and equity decisions on business performance: Evidence from International Airline Corporation

• Qaiser Aman , Sultan Altass
• Published in Revista Amazonía investiga 30 April 2023
• Business, Economics

Related Papers

Showing 1 through 3 of 0 Related Papers

Global Growth Is Stabilizing for the First Time in Three Years

But 80% of world population will experience slower growth than in pre-COVID decade

WASHINGTON, June 11, 2024 — The global economy is expected to stabilize for the first time in three years in 2024—but at a level that is weak by recent historical standards, according to the World Bank’s latest Global Economic Prospects report.

Global growth is projected to hold steady at 2.6% in 2024 before edging up to an average of 2.7% in 2025-26. That is well below the 3.1% average in the decade before COVID-19. The forecast implies that over the course of 2024-26 countries that collectively account for more than 80% of the world’s population and global GDP would still be growing more slowly than they did in the decade before COVID-19.

Overall, developing economies are projected to grow 4% on average over 2024-25, slightly slower than in 2023. Growth in low-income economies is expected to accelerate to 5% in 2024 from 3.8% in 2023. However, the forecasts for 2024 growth reflect downgrades in three out of every four low-income economies since January. In advanced economies, growth is set to remain steady at 1.5% in 2024 before rising to 1.7% in 2025.

“Four years after the upheavals caused by the pandemic, conflicts, inflation, and monetary tightening, it appears that global economic growth is steadying,” said Indermit Gill, the World Bank Group’s Chief Economist and Senior Vice President. “ However, growth is at lower levels than before 2020. Prospects for the world’s poorest economies are even more worrisome. They face punishing levels of debt service, constricting trade possibilities, and costly climate events. Developing economies will have to find ways to encourage private investment, reduce public debt, and improve education, health, and basic infrastructure. The poorest among them—especially the 75 countries eligible for concessional assistance from the International Development Association—will not be able to do this without international support.”

This year, one in four developing economies is expected to remain poorer than it was on the eve of the pandemic in 2019. This proportion is twice as high for countries in fragile- and conflict-affected situations. Moreover, the income gap between developing economies and advanced economies is set to widen in nearly half of developing economies over 2020-24 —the highest share since the 1990s. Per capita income in these economies—an important indicator of living standards—is expected to grow by 3.0% on average through 2026, well below the average of 3.8% in the decade before COVID-19.

Global inflation is expected to moderate to 3.5% in 2024 and 2.9% in 2025, but the pace of decline is slower than was projected just six months ago. Many central banks, as a result, are expected to remain cautious in lowering policy interest rates. Global interest rates are likely to remain high by the standards of recent decades—averaging about 4% over 2025-26, roughly double the 2000-19 average.

“Although food and energy prices have moderated across the world, core inflation remains relatively high—and could stay that way,” said Ayhan Kose, the World Bank’s Deputy Chief Economist and Director of the Prospects Group . “That could prompt central banks in major advanced economies to delay interest-rate cuts. An environment of ‘higher-for-longer’ rates would mean tighter global financial conditions and much weaker growth in developing economies.”

The latest Global Economic Prospects report also features two analytical chapters of topical importance. The first outlines how public investment can be used to accelerate private investment and promote economic growth. It finds that public investment growth in developing economies has halved since the global financial crisis, dropping to an annual average of 5% in the past decade. Yet public investment can be a powerful policy lever. For developing economies with ample fiscal space and efficient government spending practices, scaling up public investment by 1% of GDP can increase the level of output by up to 1.6% over the medium term.

The second analytical chapter explores why small states—those with a population of around 1.5 million or less—suffer chronic fiscal difficulties. Two-fifths of the 35 developing economies that are small states are at high risk of debt distress or already in it. That’s roughly twice the share for other developing economies. Comprehensive reforms are needed to address the fiscal challenges of small states. Revenues could be drawn from a more stable and secure tax base. Spending efficiency could be improved —especially in health, education, and infrastructure. Fiscal frameworks could be adopted to manage the higher frequency of natural disasters and other shocks. Targeted and coordinated global policies can also help put these countries on a more sustainable fiscal path.

Download the full report: https://bit.ly/GEP-June-2024-FullReport

Download growth data:   https://bit.ly/GEP-June-2024-Data

Download charts: https://bit.ly/GEP-June-2024-Charts

Regional Outlooks:

East Asia and Pacific:  Growth is expected to decelerate to 4.8% in 2024 and to 4.2% in 2025. For more, see  regional overview.

Europe and Central Asia:  Growth is expected to edge down to 3.0% in 2024 before moderating to 2.9% in 2025. For more, see  regional overview .

Latin America and the Caribbean:  Growth is expected to decline to 1.8% in 2024 before picking up to 2.7% in 2025. For more, see  regional overview .

Middle East and North Africa:  Growth is expected to pick up to 2.8% in 2024 and 4.2% in 2025. For more, see  regional overview.

South Asia:  Growth is expected to slow to 6.2% in 2024 and remain steady at 6.2% in 2025. For more, see regional overview.

Sub-Saharan Africa: Growth is expected to pick up to 3.5% in 2024 and to 3.9% in 2025. For more, see  regional overview.

Website:  www.worldbank.org/gep

Facebook:  facebook.com/worldbank

X (Twitter):  twitter.com/worldbank

YouTube:  youtube.com/worldbank

This site uses cookies to optimize functionality and give you the best possible experience. If you continue to navigate this website beyond this page, cookies will be placed on your browser. To learn more about cookies, click here .

Create an account

Create a free IEA account to download our reports or subcribe to a paid service.

Overview and key findings

Tracking cop28 progress.

• United States
• Latin America and the Caribbean
• European Union
• Middle East
• Japan and Korea
• Southeast Asia

Cite report

IEA (2024), World Energy Investment 2024 , IEA, Paris https://www.iea.org/reports/world-energy-investment-2024, Licence: CC BY 4.0

Share this report

• Share on Twitter Twitter
• Share on Facebook Facebook
• Share on LinkedIn LinkedIn
• Share on Email Email
• Share on Print Print

Report options

The world now invests almost twice as much in clean energy as it does in fossil fuels…, global investment in clean energy and fossil fuels, 2015-2024, …but there are major imbalances in investment, and emerging market and developing economies (emde) outside china account for only around 15% of global clean energy spending, annual investment in clean energy by selected country and region, 2019 and 2024, investment in solar pv now surpasses all other generation technologies combined, global annual investment in solar pv and other generation technologies, 2021-2024, the integration of renewables and upgrades to existing infrastructure have sparked a recovery in spending on grids and storage, investment in power grids and storage by region 2017-2024, rising investments in clean energy push overall energy investment above usd 3 trillion for the first time.

Global energy investment is set to exceed USD 3 trillion for the first time in 2024, with USD 2 trillion going to clean energy technologies and infrastructure. Investment in clean energy has accelerated since 2020, and spending on renewable power, grids and storage is now higher than total spending on oil, gas, and coal.

As the era of cheap borrowing comes to an end, certain kinds of investment are being held back by higher financing costs. However, the impact on project economics has been partially offset by easing supply chain pressures and falling prices. Solar panel costs have decreased by 30% over the last two years, and prices for minerals and metals crucial for energy transitions have also sharply dropped, especially the metals required for batteries.

The annual World Energy Investment report has consistently warned of energy investment flow imbalances, particularly insufficient clean energy investments in EMDE outside China. There are tentative signs of a pick-up in these investments: in our assessment, clean energy investments are set to approach USD 320 billion in 2024, up by more 50% since 2020. This is similar to the growth seen in advanced economies (+50%), although trailing China (+75%). The gains primarily come from higher investments in renewable power, now representing half of all power sector investments in these economies. Progress in India, Brazil, parts of Southeast Asia and Africa reflects new policy initiatives, well-managed public tenders, and improved grid infrastructure. Africa’s clean energy investments in 2024, at over USD 40 billion, are nearly double those in 2020.

Yet much more needs to be done. In most cases, this growth comes from a very low base and many of the least-developed economies are being left behind (several face acute problems servicing high levels of debt). In 2024, the share of global clean energy investment in EMDE outside China is expected to remain around 15% of the total. Both in terms of volume and share, this is far below the amounts that are required to ensure full access to modern energy and to meet rising energy demand in a sustainable way.

Power sector investment in solar photovoltaic (PV) technology is projected to exceed USD 500 billion in 2024, surpassing all other generation sources combined. Though growth may moderate slightly in 2024 due to falling PV module prices, solar remains central to the power sector’s transformation. In 2023, each dollar invested in wind and solar PV yielded 2.5 times more energy output than a dollar spent on the same technologies a decade prior.

In 2015, the ratio of clean power to unabated fossil fuel power investments was roughly 2:1. In 2024, this ratio is set to reach 10:1. The rise in solar and wind deployment has driven wholesale prices down in some countries, occasionally below zero, particularly during peak periods of wind and solar generation. This lowers the potential for spot market earnings for producers and highlights the need for complementary investments in flexibility and storage capacity.

Investments in nuclear power are expected to pick up in 2024, with its share (9%) in clean power investments rising after two consecutive years of decline. Total investment in nuclear is projected to reach USD 80 billion in 2024, nearly double the 2018 level, which was the lowest point in a decade.

Grids have become a bottleneck for energy transitions, but investment is rising. After stagnating around USD 300 billion per year since 2015, spending is expected to hit USD 400 billion in 2024, driven by new policies and funding in Europe, the United States, China, and parts of Latin America. Advanced economies and China account for 80% of global grid spending. Investment in Latin America has almost doubled since 2021, notably in Colombia, Chile, and Brazil, where spending doubled in 2023 alone. However, investment remains worryingly low elsewhere.

Investments in battery storage are ramping up and are set to exceed USD 50 billion in 2024. But spending is highly concentrated. In 2023, for every dollar invested in battery storage in advanced economies and China, only one cent was invested in other EMDE.

Investment in energy efficiency and electrification in buildings and industry has been quite resilient, despite the economic headwinds. But most of the dynamism in the end-use sectors is coming from transport, where investment is set to reach new highs in 2024 (+8% compared to 2023), driven by strong electric vehicle (EV) sales.

The rise in clean energy spending is underpinned by emissions reduction goals, technological gains, energy security imperatives (particularly in the European Union), and an additional strategic element: major economies are deploying new industrial strategies to spur clean energy manufacturing and establish stronger market positions. Such policies can bring local benefits, although gaining a cost-competitive foothold in sectors with ample global capacity like solar PV can be challenging. Policy makers need to balance the costs and benefits of these programmes so that they increase the resilience of clean energy supply chains while maintaining gains from trade.

In the United States, investment in clean energy increases to an estimated more than USD 300 billion in 2024, 1.6 times the 2020 level and well ahead of the amount invested in fossil fuels. The European Union spends USD 370 billion on clean energy today, while China is set to spend almost USD 680 billion in 2024, supported by its large domestic market and rapid growth in the so-called “new three” industries: solar cells, lithium battery production and EV manufacturing.

Overall upstream oil and gas investment in 2024 is set to return to 2017 levels, but companies in the Middle East and Asia now account for a much larger share of the total

Change in upstream oil and gas investment by company type, 2017-2024, newly approved lng projects, led by the united states and qatar, bring a new wave of investment that could boost global lng export capacity by 50%, investment and cumulative capacity in lng liquefaction, 2015-2028, investment in fuel supply remains largely dominated by fossil fuels, although interest in low-emissions fuels is growing fast from a low base.

Upstream oil and gas investment is expected to increase by 7% in 2024 to reach USD 570 billion, following a 9% rise in 2023. This is being led by Middle East and Asian NOCs, which have increased their investments in oil and gas by over 50% since 2017, and which account for almost the entire rise in spending for 2023-2024.

Lower cost inflation means that the headline rise in spending results in an even larger rise in activity, by approximately 25% compared with 2022. Existing fields account for around 40% total oil and gas upstream investment, while another 33% goes to new fields and exploration. The remainder goes to tight oil and shale gas.

Most of the huge influx of cashflows to the oil and gas industry in 2022-2023 was either returned to shareholders, used to buy back shares or to pay down debt; these uses exceeded capital expenditure again in 2023. A surge in profits has also spurred a wave of mergers and acquisitions (M&A), especially among US shale companies, which represented 75% of M&A activity in 2023. Clean energy spending by oil and gas companies grew to around USD 30 billion in 2023 (of which just USD 1.5 billion was by NOCs), but this represents less than 4% of global capital investment on clean energy.

A significant wave of new investment is expected in LNG in the coming years as new liquefaction plants are built, primarily in the United States and Qatar. The concentration of projects looking to start operation in the second half of this decade could increase competition and raise costs for the limited number of specialised contractors in this area. For the moment, the prospect of ample gas supplies has not triggered a major reaction further down the value chain. The amount of new gas-fired power capacity being approved and coming online remains stable at around 50-60 GW per year.

Investment in coal has been rising steadily in recent years, and more than 50 GW of unabated coal-fired power generation was approved in 2023, the most since 2015, and almost all of this was in China.

Investment in low-emissions fuels is only 1.4% of the amount spent on fossil fuels (compared to about 0.5% a decade ago). There are some fast-growing areas. Investments in hydrogen electrolysers have risen to around USD 3 billion per year, although they remain constrained by uncertainty about demand and a lack of reliable offtakers. Investments in sustainable aviation fuels have reached USD 1 billion, while USD 800 million is going to direct air capture projects (a 140% increase from 2023). Some 20 commercial-scale carbon capture utilisation and storage (CCUS) projects in seven countries reached final investment decision (FID) in 2023; according to company announcements, another 110 capture facilities, transport and storage projects could do the same in 2024.

Energy investment decisions are primarily driven and financed by the private sector, but governments have essential direct and indirect roles in shaping capital flows

Sources of investment in the energy sector, average 2018-2023, sources of finance in the energy sector, average 2018-2023, households are emerging as important actors for consumer-facing clean energy investments, highlighting the importance of affordability and access to capital, change in energy investment volume by region and fuel category, 2016 versus 2023, market sentiment around sustainable finance is down from the high point in 2021, with lower levels of sustainable debt issuances and inflows into sustainable funds, sustainable debt issuances, 2020-2023, sustainable fund launches, 2020-2023, energy transitions are reshaping how energy investment decisions are made, and by whom.

This year’s World Energy Investment report contains new analysis on sources of investments and sources of finance, making a clear distinction between those making investment decisions (governments, often via state-owned enterprises (SOEs), private firms and households) and the institutions providing the capital (the public sector, commercial lenders, and development finance institutions) to finance these investments.

Overall, most investments in the energy sector are made by corporates, with firms accounting for the largest share of investments in both the fossil fuel and clean energy sectors. However, there are significant country-by-country variations: half of all energy investments in EMDE are made by governments or SOEs, compared with just 15% in advanced economies. Investments by state-owned enterprises come mainly from national oil companies, notably in the Middle East and Asia where they have risen substantially in recent years, and among some state-owned utilities. The financial sustainability, investment strategies and the ability for SOEs to attract private capital therefore become a central issue for secure and affordable transitions.

The share of total energy investments made or decided by private households (if not necessarily financed by them directly) has doubled from 9% in 2015 to 18% today, thanks to the combined growth in rooftop solar installations, investments in buildings efficiency and electric vehicle purchases. For the moment, these investments are mainly made by wealthier households – and well-designed policies are essential to making clean energy technologies more accessible to all . A comparison shows that households have contributed to more than 40% of the increase in investment in clean energy spending since 2016 – by far the largest share. It was particularly pronounced in advanced economies, where, because of strong policy support, households accounted for nearly 60% of the growth in energy investments.

Three quarters of global energy investments today are funded from private and commercial sources, and around 25% from public finance, and just 1% from national and international development finance institutions (DFIs).

Other financing options for energy transition have faced challenges and are focused on advanced economies. In 2023, sustainable debt issuances exceeded USD 1 trillion for the third consecutive year, but were still 25% below their 2021 peak, as rising coupon rates dampened issuers’ borrowing appetite. Market sentiment for sustainable finance is wavering, with flows to ESG funds decreasing in 2023, due to potential higher returns elsewhere and credibility concerns. Transition finance is emerging to mobilise capital for high-emitting sectors, but greater harmonisation and credible standards are required for these instruments to reach scale.

A secure and affordable transitioning away from fossil fuels requires a major rebalancing of investments

Investment change in 2023-2024, and additional average annual change in investment in the net zero scenario, 2023-2030, a doubling of investments to triple renewables capacity and a tripling of spending to double efficiency: a steep hill needs climbing to keep 1.5°c within reach, investments in renewables, grids and battery storage in the net zero emissions by 2050 scenario, historical versus 2030, investments in end-use sectors in the net zero emissions by 2050 scenario, historical versus 2030, meeting cop28 goals requires a doubling of clean energy investment by 2030 worldwide, and a quadrupling in emde outside china, investments in renewables, grids, batteries and end use in the net zero emissions by 2050 scenario, 2024 and 2030, mobilising additional, affordable financing is the key to a safer and more sustainable future, breakdown of dfi financing by instrument, currency, technology and region, average 2019-2022, much greater efforts are needed to get on track to meet energy & climate goals, including those agreed at cop28.

Today’s investment trends are not aligned with the levels necessary for the world to have a chance of limiting global warming to 1.5°C above pre-industrial levels and to achieve the interim goals agreed at COP28. The current momentum behind renewable power is impressive, and if the current spending trend continues, it would cover approximately two-thirds of the total investment needed to triple renewable capacity by 2030. But an extra USD 500 billion per year is required in the IEA’s Net Zero Emissions by 2050 Scenario (NZE Scenario) to fill the gap completely (including spending for grids and battery storage). This equates to a doubling of current annual spending on renewable power generation, grids, and storage in 2030, in order to triple renewable capacity.

The goal of doubling the pace of energy efficiency improvement requires an even greater additional effort. While investment in the electrification of transport is relatively strong and brings important efficiency gains, investment in other efficiency measures – notably building retrofits – is well below where it needs to be: efficiency investments in buildings fell in 2023 and are expected to decline further in 2024. A tripling in the current annual rate of spending on efficiency and electrification – to about USD 1.9 trillion in 2030 – is needed to double the rate of energy efficiency improvements.

Anticipated oil and gas investment in 2024 is broadly in line with the level of investment required in 2030 in the Stated Policies Scenario, a scenario which sees oil and natural gas demand levelling off before 2030. However, global spare oil production capacity is already close to 6 million barrels per day (excluding Iran and Russia) and there is a shift expected in the coming years towards a buyers’ market for LNG. Against this backdrop, the risk of over-investment would be strong if the world moves swiftly to meet the net zero pledges and climate goals in the Announced Pledges Scenario (APS) and the NZE Scenario.

The NZE Scenario sees a major rebalancing of investments in fuel supply, away from fossil fuels and towards low-emissions fuels, such as bioenergy and low-emissions hydrogen, as well as CCUS. Achieving net zero emissions globally by 2050 would mean annual investment in oil, gas, and coal falls by more than half, from just over USD 1 trillion in 2024 to below USD 450 billion per year in 2030, while spending on low-emissions fuels increases tenfold, to about USD 200 billion in 2030 from just under USD 20 billion today.

The required increase in clean energy investments in the NZE Scenario is particularly steep in many emerging and developing economies. The cost of capital remains one of the largest barriers to investment in clean energy projects and infrastructure in many EMDE, with financing costs at least twice as high as in advanced economies as well as China. Macroeconomic and country-specific factors are the major contributors to the high cost of capital for clean energy projects, but so, too, are risks specific to the energy sector. Alongside actions by national policy makers, enhanced support from DFIs can play a major role in lowering financing costs and bringing in much larger volumes of private capital.

Targeted concessional support is particularly important for the least-developed countries that will otherwise struggle to access adequate capital. Our analysis shows cumulative financing for energy projects by DFIs was USD 470 billion between 2013 and 2021, with China-based DFIs accounting for slightly over half of the total. There was a significant reduction in financing for fossil fuel projects over this period, largely because of reduced Chinese support. However, this was not accompanied by a surge in support for clean energy projects. DFI support was provided almost exclusively (more than 90%) as debt (not all concessional) with only about 3% reported as equity financing and about 6% as grants. This debt was provided in hard currency or in the currency of donors, with almost no local-currency financing being reported.

The lack of local-currency lending pushes up borrowing costs and in many cases is the primary reason behind the much higher cost of capital in EMDE compared to advanced economies. High hedging costs often make this financing unaffordable to many of the least-developed countries and raises questions of debt sustainability. More attention is needed from DFIs to focus interventions on project de-risking that can mobilise much higher multiples of private capital.

Subscription successful

Thank you for subscribing. You can unsubscribe at any time by clicking the link at the bottom of any IEA newsletter.

• Browse All Articles
• Newsletter Sign-Up

Marketing →

• 07 May 2024
• Cold Call Podcast

Lessons in Business Innovation from Legendary Restaurant elBulli

Ferran Adrià, chef at legendary Barcelona-based restaurant elBulli, was facing two related decisions. First, he and his team must continue to develop new and different dishes for elBulli to guarantee a continuous stream of innovation, the cornerstone of the restaurant's success. But they also need to focus on growing the restaurant’s business. Can the team balance both objectives? Professor Michael I. Norton discusses the connections between creativity, emotions, rituals, and innovation – and how they can be applied to other domains – in the case, “elBulli: The Taste of Innovation,” and his new book, The Ritual Effect.

• 29 Feb 2024

Beyond Goals: David Beckham's Playbook for Mobilizing Star Talent

Reach soccer's pinnacle. Become a global brand. Buy a team. Sign Lionel Messi. David Beckham makes success look as easy as his epic free kicks. But leveraging world-class talent takes discipline and deft decision-making, as case studies by Anita Elberse reveal. What could other businesses learn from his ascent?

• 17 Jan 2024

Psychological Pricing Tactics to Fight the Inflation Blues

Inflation has slowed from the epic rates of 2021 and 2022, but many consumers still feel pinched. What will it take to encourage them to spend? Thoughtful pricing strategies that empower customers as they make purchasing decisions, says research by Elie Ofek.

• 05 Dec 2023

What Founders Get Wrong about Sales and Marketing

Which sales candidate is a startup’s ideal first hire? What marketing channels are best to invest in? How aggressively should an executive team align sales with customer success? Senior Lecturer Mark Roberge discusses how early-stage founders, sales leaders, and marketing executives can address these challenges as they grow their ventures in the case, “Entrepreneurial Sales and Marketing Vignettes.”

Tommy Hilfiger’s Adaptive Clothing Line: Making Fashion Inclusive

In 2017, Tommy Hilfiger launched its adaptive fashion line to provide fashion apparel that aims to make dressing easier. By 2020, it was still a relatively unknown line in the U.S. and the Tommy Hilfiger team was continuing to learn more about how to serve these new customers. Should the team make adaptive clothing available beyond the U.S., or is a global expansion premature? Assistant Professor Elizabeth Keenan discusses the opportunities and challenges that accompanied the introduction of a new product line that effectively serves an entirely new customer while simultaneously starting a movement to provide fashion for all in the case, “Tommy Hilfiger Adaptive: Fashion for All.”

• Research & Ideas

Are Virtual Tours Still Worth It in Real Estate? Evidence from 75,000 Home Sales

Many real estate listings still feature videos and interactive tools that simulate the experience of walking through properties. But do they help homes sell faster? Research by Isamar Troncoso probes the post-pandemic value of virtual home tours.

• 17 Oct 2023

With Subscription Fatigue Setting In, Companies Need to Think Hard About Fees

Subscriptions are available for everything from dental floss to dog toys, but are consumers tiring of monthly fees? Elie Ofek says that subscription revenue can provide stability, but companies need to tread carefully or risk alienating customers.

• 29 Aug 2023

As Social Networks Get More Competitive, Which Ones Will Survive?

In early 2023, TikTok reached close to 1 billion users globally, placing it fourth behind the leading social networks: Facebook, YouTube, and Instagram. Meanwhile, competition in the market for videos had intensified. Can all four networks continue to attract audiences and creators? Felix Oberholzer-Gee discusses competition and imitation among social networks in his case “Hey, Insta & YouTube, Are You Watching TikTok?”

• 26 Jun 2023

Want to Leave a Lasting Impression on Customers? Don't Forget the (Proverbial) Fireworks

Some of the most successful customer experiences end with a bang. Julian De Freitas provides three tips to help businesses invest in the kind of memorable moments that will keep customers coming back.

• 31 May 2023

With Predictive Analytics, Companies Can Tap the Ultimate Opportunity: Customers’ Routines

Armed with more data than ever, many companies know what key customers need. But how many know exactly when they need it? An analysis of 2,000 ridesharing commuters by Eva Ascarza and colleagues shows what's possible for companies that can anticipate a customer's routine.

• 30 May 2023

Can AI Predict Whether Shoppers Would Pick Crest Over Colgate?

Is it the end of customer surveys? Definitely not, but research by Ayelet Israeli sheds light on the potential for generative AI to improve market research. But first, businesses will need to learn to harness the technology.

• 24 Apr 2023

What Does It Take to Build as Much Buzz as Booze? Inside the Epic Challenge of Cannabis-Infused Drinks

The market for cannabis products has exploded as more states legalize marijuana. But the path to success is rife with complexity as a case study about the beverage company Cann by Ayelet Israeli illustrates.

• 07 Apr 2023

When Celebrity ‘Crypto-Influencers’ Rake in Cash, Investors Lose Big

Kim Kardashian, Lindsay Lohan, and other entertainers have been accused of promoting crypto products on social media without disclosing conflicts. Research by Joseph Pacelli shows what can happen to eager investors who follow them.

• 10 Feb 2023

COVID-19 Lessons: Social Media Can Nudge More People to Get Vaccinated

Social networks have been criticized for spreading COVID-19 misinformation, but the platforms have also helped public health agencies spread the word on vaccines, says research by Michael Luca and colleagues. What does this mean for the next pandemic?

• 02 Feb 2023

Why We Still Need Twitter: How Social Media Holds Companies Accountable

Remember the viral video of the United passenger being removed from a plane? An analysis of Twitter activity and corporate misconduct by Jonas Heese and Joseph Pacelli reveals the power of social media to uncover questionable situations at companies.

• 06 Dec 2022

Latest Isn’t Always Greatest: Why Product Updates Capture Consumers

Consumers can't pass up a product update—even if there's no improvement. Research by Leslie John, Michael Norton, and Ximena Garcia-Rada illustrates the powerful allure of change. Are we really that naïve?

• 29 Nov 2022

How Much More Would Holiday Shoppers Pay to Wear Something Rare?

Economic worries will make pricing strategy even more critical this holiday season. Research by Chiara Farronato reveals the value that hip consumers see in hard-to-find products. Are companies simply making too many goods?

• 26 Oct 2022

How Paid Promos Take the Shine Off YouTube Stars (and Tips for Better Influencer Marketing)

Influencers aspire to turn "likes" into dollars through brand sponsorships, but these deals can erode their reputations, says research by Shunyuan Zhang. Marketers should seek out authentic voices on YouTube, not necessarily those with the most followers.

• 25 Oct 2022

Is Baseball Ready to Compete for the Next Generation of Fans?

With its slower pace and limited on-field action, major league baseball trails football in the US, basketball, and European soccer in revenue and popularity. Stephen Greyser discusses the state of "America's pastime."

• 18 Oct 2022

When Bias Creeps into AI, Managers Can Stop It by Asking the Right Questions

Even when companies actively try to prevent it, bias can sway algorithms and skew decision-making. Ayelet Israeli and Eva Ascarza offer a new approach to make artificial intelligence more accurate.

Eight new alumni for the EDHEC PhD in Finance programme

In the past twelve months, eight PhD in Finance candidates, all executive track participants, successfully defended their PhD theses. As we look ahead, with more than 25 candidates currently working on their PhD dissertations, we’re excited about these recent achievements and our commitment to making a positive impact on the innovation and careers of our alumni in the financial industry.

In the past twelve months, eight PhD candidates coming from Germany, India, Singapore, Switzerland, the United Kingdom, and the USA, all executive track participants, successfully defended their PhD theses. The diverse research topics of these new EDHEC PhD alumni can be found below and abstracts are available here .  

Essays on Asset Management and Crypto Asset Pricing by Ainsley To

Adviser: Laurent Calvet; External Examiner: Wei Xiong (University of Princeton)

Essays in Climate Finance by Rahul Bhattarcharjee 

Adviser: Gianfranco Gianfrate; External Examiner: Marco Grotteria (London Business School)

Understanding on Technological Origin of the Value Premium Dynamics by Andy Tang

Adviser: Laurent Calvet; External Examiner: Sebastien Betermier (McGill University) 

Disentangling the Low Risk Effect - The Role of Volatility and Correlation in the Low-Risk Anomaly by Lukas Elmiger 

Adviser: Nikolaos Tessaromatis; External Examiner: Harrison Hong (Columbia University)  

Essays on the Transmission of Unemployment and Monetary-Policy Shocks in the EU by Aravind Srinivasan

Adviser: Raman Uppal; External Examiner: Eric Swanson (University of California, Irvine) 

Forecasting long-term US equity returns with a steady-state Bayesian VAR by Edoardo Cilla 

Adviser: Mirco Rubin; External Examiner: Francis X. Diebold (University of Pennsylvania)

Essays on machine learning and the cross-section of stock returns by Maximilian Sauer 

Adviser: Raman Uppal; External Examiner: Paolo Zaffaroni (Imperial College London) 

Analyzing The Dynamics of Financial Communication Language: Measuring Financial Constraints using Embeddings and Measuring Sentiment of Non-GAAP Disclosures by Joseph Poulous 

Adviser: Arnt Verriest (KU Leuven); External Examiner: Edith Leung (Erasmus University of Rotterdam) 

At EDHEC, the dissertation work starts in the first year of the programme with the drafting of a proposal to be submitted at the beginning of the second year and intensifies as course requirements wane. PhD candidates are required to communicate the progress of their dissertation research to faculty and peers at two formal presentations scheduled in the second and third years of the programme. The dissertation should be completed and defended at the end of the third year of the programme. During all phases of the dissertation process, candidates work closely with their advisor.

Dissertation topics are selected for their academic and industry relevance and according to each candidate’s research interests and professional goals. The dissertation should make a significant contribution to the advancement of knowledge and practices in the field and should be of sufficient originality and quality for publication in leading peer-reviewed journals.

As we look ahead, with more than 25 candidates currently working on their PhD dissertations, we’re excited about these recent achievements and our commitment to making a positive impact on the innovation and careers of our alumni in the financial industry

More information on the programme curriculum is available here . 

Other articles you may be interested in

• Key figures
• Our Strategy
• Sustainability at EDHEC
• The EDHEC brand
• Ranking & Accreditations
• About EDHEC Entrepreneurs
• Our incubators
• Startups & Responsability
• Our startups
• EDHEC Centre for Responsible Entrepreneurship (ECRE)
• GENERATIONS powered by EDHEC fund
• International
• Being an EDHEC alumni
• Being an EDHEC student
• Being an EDHEC teacher and researcher
• French Recruiters
• International Recruiters
• EDHEC Business Club
• Start-up Partnerships
• International Partnerships
• Educational Collaboration
• Train your employees
• Publications
• Press and study partners
• Graduate Programmes
• Sponsor a chair, support our fundation
• EDHEC foundation
• Teachers and Researchers Recruitment
• Staff Recruitment
• Student life
• Career Services
• Student associations
• Health & Well being
• Diversity and Inclusion
• EDHEC Talents
• Talents Prépas
• Respect for Others
• Financial Aids
• Accommodation
• Academic partners
• International Students Office (ISO)
• Studying Abroad - Incoming & Outgoing
• BBA Business Management Track
• BBA Global Business Track
• BBA Online Track
• International Admissions
• Tuition fees & scholarships
• Careers & Studies
• Master in Management - Data Science & AI for Business track
• Master in Management Business Management Track
• Master in Management - Finance track
• Global Master in Management (GETT)
• MSc in Accounting & Finance
• MSc in Climate Change & Sustainable Finance - EDHEC/MinesParis - PSL
• MSc in Corporate Finance & Banking
• MSc in Financial Engineering
• MSc in International Finance
• MSc in Creative Business & Social Innovation
• MSc in Data Analytics & Artificial Intelligence
• MSc in Entrepreneurship & Innovation
• MSc in Global & Sustainable Business
• MSc in Management & Leadership
• MSc in Marketing Analytics
• MSc in Marketing Management
• MSc in Strategy, Organisation & Consulting
• LL.M. in Law & Tax Management
• MSc in Data Analytics and Artificial Intelligence
• MSc & Global MBA Double Degree
• MBA programme
• MBA Experience
• Your Career
• Admissions & Fees
• Executive MBA – Part-Time
• Executive MBA - Healthcare Innovation & Technology (HIT) – Part-Time
• Online MBA – Part-Time
• How to finance my MBA?
• Am I eligible for EDHEC scholarships?
• Evaluate your profile
• MBA Insights
• Alumni Stories
• Events & Meet-Ups
• Global MBA – Full-Time
• Executive Degree Programmes
• Executive Certificates
• Customised Programmes
• How to finance my EDHEC Executive Education programme?
• Events & Meet Ups
• A rigorous Finance curriculum
• Faculty Research expertise
• PhD Class profile
• Executive Track in Focus
• Facilities & Resources
• PhD in Finance Forum
• Admissions, Fees & Funding
• EDHEC Online
• Accounting, Control and Law
• Data Science, Economics & Finance
• Strategy, Entrepreneurship and Operations
• Management and Humanities
• Professors and Researchers
• Research seminars
• Scientific press review
• EDHEC Pedagogy
• Recruitments
• EDHEC Augmented Law Institute
• EDHEC Infra & Private Assets
• EDHEC-Risk Climate Impact Institute
• EDHEC Centre for Responsible Entrepreneurship
• EDHEC NewGen Talent Centre
• Scientific Portfolio (an EDHEC Venture)
• Leadership Development Chair
• Diversity & Inclusion Chair
• Family Business Chair
• Criminal Risks Management Chair
• Management in Innovative Health Chair
• Foresight, Innovation and Transformation Chair
• UNESCO Chair
• Climate Finance Research
• My EDHEC Store

A generative AI reset: Rewiring to turn potential into value in 2024

It’s time for a generative AI (gen AI) reset. The initial enthusiasm and flurry of activity in 2023 is giving way to second thoughts and recalibrations as companies realize that capturing gen AI’s enormous potential value is harder than expected .

With 2024 shaping up to be the year for gen AI to prove its value, companies should keep in mind the hard lessons learned with digital and AI transformations: competitive advantage comes from building organizational and technological capabilities to broadly innovate, deploy, and improve solutions at scale—in effect, rewiring the business  for distributed digital and AI innovation.

About QuantumBlack, AI by McKinsey

QuantumBlack, McKinsey’s AI arm, helps companies transform using the power of technology, technical expertise, and industry experts. With thousands of practitioners at QuantumBlack (data engineers, data scientists, product managers, designers, and software engineers) and McKinsey (industry and domain experts), we are working to solve the world’s most important AI challenges. QuantumBlack Labs is our center of technology development and client innovation, which has been driving cutting-edge advancements and developments in AI through locations across the globe.

Companies looking to score early wins with gen AI should move quickly. But those hoping that gen AI offers a shortcut past the tough—and necessary—organizational surgery are likely to meet with disappointing results. Launching pilots is (relatively) easy; getting pilots to scale and create meaningful value is hard because they require a broad set of changes to the way work actually gets done.

Let’s briefly look at what this has meant for one Pacific region telecommunications company. The company hired a chief data and AI officer with a mandate to “enable the organization to create value with data and AI.” The chief data and AI officer worked with the business to develop the strategic vision and implement the road map for the use cases. After a scan of domains (that is, customer journeys or functions) and use case opportunities across the enterprise, leadership prioritized the home-servicing/maintenance domain to pilot and then scale as part of a larger sequencing of initiatives. They targeted, in particular, the development of a gen AI tool to help dispatchers and service operators better predict the types of calls and parts needed when servicing homes.

Leadership put in place cross-functional product teams with shared objectives and incentives to build the gen AI tool. As part of an effort to upskill the entire enterprise to better work with data and gen AI tools, they also set up a data and AI academy, which the dispatchers and service operators enrolled in as part of their training. To provide the technology and data underpinnings for gen AI, the chief data and AI officer also selected a large language model (LLM) and cloud provider that could meet the needs of the domain as well as serve other parts of the enterprise. The chief data and AI officer also oversaw the implementation of a data architecture so that the clean and reliable data (including service histories and inventory databases) needed to build the gen AI tool could be delivered quickly and responsibly.

Creating value beyond the hype

Let’s deliver on the promise of technology from strategy to scale.

Our book Rewired: The McKinsey Guide to Outcompeting in the Age of Digital and AI (Wiley, June 2023) provides a detailed manual on the six capabilities needed to deliver the kind of broad change that harnesses digital and AI technology. In this article, we will explore how to extend each of those capabilities to implement a successful gen AI program at scale. While recognizing that these are still early days and that there is much more to learn, our experience has shown that breaking open the gen AI opportunity requires companies to rewire how they work in the following ways.

Figure out where gen AI copilots can give you a real competitive advantage

The broad excitement around gen AI and its relative ease of use has led to a burst of experimentation across organizations. Most of these initiatives, however, won’t generate a competitive advantage. One bank, for example, bought tens of thousands of GitHub Copilot licenses, but since it didn’t have a clear sense of how to work with the technology, progress was slow. Another unfocused effort we often see is when companies move to incorporate gen AI into their customer service capabilities. Customer service is a commodity capability, not part of the core business, for most companies. While gen AI might help with productivity in such cases, it won’t create a competitive advantage.

To create competitive advantage, companies should first understand the difference between being a “taker” (a user of available tools, often via APIs and subscription services), a “shaper” (an integrator of available models with proprietary data), and a “maker” (a builder of LLMs). For now, the maker approach is too expensive for most companies, so the sweet spot for businesses is implementing a taker model for productivity improvements while building shaper applications for competitive advantage.

Much of gen AI’s near-term value is closely tied to its ability to help people do their current jobs better. In this way, gen AI tools act as copilots that work side by side with an employee, creating an initial block of code that a developer can adapt, for example, or drafting a requisition order for a new part that a maintenance worker in the field can review and submit (see sidebar “Copilot examples across three generative AI archetypes”). This means companies should be focusing on where copilot technology can have the biggest impact on their priority programs.

Copilot examples across three generative AI archetypes

• “Taker” copilots help real estate customers sift through property options and find the most promising one, write code for a developer, and summarize investor transcripts.
• “Shaper” copilots provide recommendations to sales reps for upselling customers by connecting generative AI tools to customer relationship management systems, financial systems, and customer behavior histories; create virtual assistants to personalize treatments for patients; and recommend solutions for maintenance workers based on historical data.
• “Maker” copilots are foundation models that lab scientists at pharmaceutical companies can use to find and test new and better drugs more quickly.

Some industrial companies, for example, have identified maintenance as a critical domain for their business. Reviewing maintenance reports and spending time with workers on the front lines can help determine where a gen AI copilot could make a big difference, such as in identifying issues with equipment failures quickly and early on. A gen AI copilot can also help identify root causes of truck breakdowns and recommend resolutions much more quickly than usual, as well as act as an ongoing source for best practices or standard operating procedures.

The challenge with copilots is figuring out how to generate revenue from increased productivity. In the case of customer service centers, for example, companies can stop recruiting new agents and use attrition to potentially achieve real financial gains. Defining the plans for how to generate revenue from the increased productivity up front, therefore, is crucial to capturing the value.

McKinsey Live Event: Unlocking the full value of gen AI

Join our colleagues Jessica Lamb and Gayatri Shenai on April 8, as they discuss how companies can navigate the ever-changing world of gen AI.

Upskill the talent you have but be clear about the gen-AI-specific skills you need

By now, most companies have a decent understanding of the technical gen AI skills they need, such as model fine-tuning, vector database administration, prompt engineering, and context engineering. In many cases, these are skills that you can train your existing workforce to develop. Those with existing AI and machine learning (ML) capabilities have a strong head start. Data engineers, for example, can learn multimodal processing and vector database management, MLOps (ML operations) engineers can extend their skills to LLMOps (LLM operations), and data scientists can develop prompt engineering, bias detection, and fine-tuning skills.

A sample of new generative AI skills needed

The following are examples of new skills needed for the successful deployment of generative AI tools:

• data scientist:
• prompt engineering
• in-context learning
• bias detection
• pattern identification
• reinforcement learning from human feedback
• hyperparameter/large language model fine-tuning; transfer learning
• data engineer:
• data wrangling and data warehousing
• data pipeline construction
• multimodal processing
• vector database management

The learning process can take two to three months to get to a decent level of competence because of the complexities in learning what various LLMs can and can’t do and how best to use them. The coders need to gain experience building software, testing, and validating answers, for example. It took one financial-services company three months to train its best data scientists to a high level of competence. While courses and documentation are available—many LLM providers have boot camps for developers—we have found that the most effective way to build capabilities at scale is through apprenticeship, training people to then train others, and building communities of practitioners. Rotating experts through teams to train others, scheduling regular sessions for people to share learnings, and hosting biweekly documentation review sessions are practices that have proven successful in building communities of practitioners (see sidebar “A sample of new generative AI skills needed”).

It’s important to bear in mind that successful gen AI skills are about more than coding proficiency. Our experience in developing our own gen AI platform, Lilli , showed us that the best gen AI technical talent has design skills to uncover where to focus solutions, contextual understanding to ensure the most relevant and high-quality answers are generated, collaboration skills to work well with knowledge experts (to test and validate answers and develop an appropriate curation approach), strong forensic skills to figure out causes of breakdowns (is the issue the data, the interpretation of the user’s intent, the quality of metadata on embeddings, or something else?), and anticipation skills to conceive of and plan for possible outcomes and to put the right kind of tracking into their code. A pure coder who doesn’t intrinsically have these skills may not be as useful a team member.

While current upskilling is largely based on a “learn on the job” approach, we see a rapid market emerging for people who have learned these skills over the past year. That skill growth is moving quickly. GitHub reported that developers were working on gen AI projects “in big numbers,” and that 65,000 public gen AI projects were created on its platform in 2023—a jump of almost 250 percent over the previous year. If your company is just starting its gen AI journey, you could consider hiring two or three senior engineers who have built a gen AI shaper product for their companies. This could greatly accelerate your efforts.

Form a centralized team to establish standards that enable responsible scaling

To ensure that all parts of the business can scale gen AI capabilities, centralizing competencies is a natural first move. The critical focus for this central team will be to develop and put in place protocols and standards to support scale, ensuring that teams can access models while also minimizing risk and containing costs. The team’s work could include, for example, procuring models and prescribing ways to access them, developing standards for data readiness, setting up approved prompt libraries, and allocating resources.

While developing Lilli, our team had its mind on scale when it created an open plug-in architecture and setting standards for how APIs should function and be built.  They developed standardized tooling and infrastructure where teams could securely experiment and access a GPT LLM , a gateway with preapproved APIs that teams could access, and a self-serve developer portal. Our goal is that this approach, over time, can help shift “Lilli as a product” (that a handful of teams use to build specific solutions) to “Lilli as a platform” (that teams across the enterprise can access to build other products).

For teams developing gen AI solutions, squad composition will be similar to AI teams but with data engineers and data scientists with gen AI experience and more contributors from risk management, compliance, and legal functions. The general idea of staffing squads with resources that are federated from the different expertise areas will not change, but the skill composition of a gen-AI-intensive squad will.

Set up the technology architecture to scale

Building a gen AI model is often relatively straightforward, but making it fully operational at scale is a different matter entirely. We’ve seen engineers build a basic chatbot in a week, but releasing a stable, accurate, and compliant version that scales can take four months. That’s why, our experience shows, the actual model costs may be less than 10 to 15 percent of the total costs of the solution.

Building for scale doesn’t mean building a new technology architecture. But it does mean focusing on a few core decisions that simplify and speed up processes without breaking the bank. Three such decisions stand out:

• Focus on reusing your technology. Reusing code can increase the development speed of gen AI use cases by 30 to 50 percent. One good approach is simply creating a source for approved tools, code, and components. A financial-services company, for example, created a library of production-grade tools, which had been approved by both the security and legal teams, and made them available in a library for teams to use. More important is taking the time to identify and build those capabilities that are common across the most priority use cases. The same financial-services company, for example, identified three components that could be reused for more than 100 identified use cases. By building those first, they were able to generate a significant portion of the code base for all the identified use cases—essentially giving every application a big head start.
• Focus the architecture on enabling efficient connections between gen AI models and internal systems. For gen AI models to work effectively in the shaper archetype, they need access to a business’s data and applications. Advances in integration and orchestration frameworks have significantly reduced the effort required to make those connections. But laying out what those integrations are and how to enable them is critical to ensure these models work efficiently and to avoid the complexity that creates technical debt  (the “tax” a company pays in terms of time and resources needed to redress existing technology issues). Chief information officers and chief technology officers can define reference architectures and integration standards for their organizations. Key elements should include a model hub, which contains trained and approved models that can be provisioned on demand; standard APIs that act as bridges connecting gen AI models to applications or data; and context management and caching, which speed up processing by providing models with relevant information from enterprise data sources.
• Build up your testing and quality assurance capabilities. Our own experience building Lilli taught us to prioritize testing over development. Our team invested in not only developing testing protocols for each stage of development but also aligning the entire team so that, for example, it was clear who specifically needed to sign off on each stage of the process. This slowed down initial development but sped up the overall delivery pace and quality by cutting back on errors and the time needed to fix mistakes.

Ensure data quality and focus on unstructured data to fuel your models

The ability of a business to generate and scale value from gen AI models will depend on how well it takes advantage of its own data. As with technology, targeted upgrades to existing data architecture  are needed to maximize the future strategic benefits of gen AI:

• Be targeted in ramping up your data quality and data augmentation efforts. While data quality has always been an important issue, the scale and scope of data that gen AI models can use—especially unstructured data—has made this issue much more consequential. For this reason, it’s critical to get the data foundations right, from clarifying decision rights to defining clear data processes to establishing taxonomies so models can access the data they need. The companies that do this well tie their data quality and augmentation efforts to the specific AI/gen AI application and use case—you don’t need this data foundation to extend to every corner of the enterprise. This could mean, for example, developing a new data repository for all equipment specifications and reported issues to better support maintenance copilot applications.
• Understand what value is locked into your unstructured data. Most organizations have traditionally focused their data efforts on structured data (values that can be organized in tables, such as prices and features). But the real value from LLMs comes from their ability to work with unstructured data (for example, PowerPoint slides, videos, and text). Companies can map out which unstructured data sources are most valuable and establish metadata tagging standards so models can process the data and teams can find what they need (tagging is particularly important to help companies remove data from models as well, if necessary). Be creative in thinking about data opportunities. Some companies, for example, are interviewing senior employees as they retire and feeding that captured institutional knowledge into an LLM to help improve their copilot performance.
• Optimize to lower costs at scale. There is often as much as a tenfold difference between what companies pay for data and what they could be paying if they optimized their data infrastructure and underlying costs. This issue often stems from companies scaling their proofs of concept without optimizing their data approach. Two costs generally stand out. One is storage costs arising from companies uploading terabytes of data into the cloud and wanting that data available 24/7. In practice, companies rarely need more than 10 percent of their data to have that level of availability, and accessing the rest over a 24- or 48-hour period is a much cheaper option. The other costs relate to computation with models that require on-call access to thousands of processors to run. This is especially the case when companies are building their own models (the maker archetype) but also when they are using pretrained models and running them with their own data and use cases (the shaper archetype). Companies could take a close look at how they can optimize computation costs on cloud platforms—for instance, putting some models in a queue to run when processors aren’t being used (such as when Americans go to bed and consumption of computing services like Netflix decreases) is a much cheaper option.

Build trust and reusability to drive adoption and scale

Because many people have concerns about gen AI, the bar on explaining how these tools work is much higher than for most solutions. People who use the tools want to know how they work, not just what they do. So it’s important to invest extra time and money to build trust by ensuring model accuracy and making it easy to check answers.

One insurance company, for example, created a gen AI tool to help manage claims. As part of the tool, it listed all the guardrails that had been put in place, and for each answer provided a link to the sentence or page of the relevant policy documents. The company also used an LLM to generate many variations of the same question to ensure answer consistency. These steps, among others, were critical to helping end users build trust in the tool.

Part of the training for maintenance teams using a gen AI tool should be to help them understand the limitations of models and how best to get the right answers. That includes teaching workers strategies to get to the best answer as fast as possible by starting with broad questions then narrowing them down. This provides the model with more context, and it also helps remove any bias of the people who might think they know the answer already. Having model interfaces that look and feel the same as existing tools also helps users feel less pressured to learn something new each time a new application is introduced.

Getting to scale means that businesses will need to stop building one-off solutions that are hard to use for other similar use cases. One global energy and materials company, for example, has established ease of reuse as a key requirement for all gen AI models, and has found in early iterations that 50 to 60 percent of its components can be reused. This means setting standards for developing gen AI assets (for example, prompts and context) that can be easily reused for other cases.

While many of the risk issues relating to gen AI are evolutions of discussions that were already brewing—for instance, data privacy, security, bias risk, job displacement, and intellectual property protection—gen AI has greatly expanded that risk landscape. Just 21 percent of companies reporting AI adoption say they have established policies governing employees’ use of gen AI technologies.

Similarly, a set of tests for AI/gen AI solutions should be established to demonstrate that data privacy, debiasing, and intellectual property protection are respected. Some organizations, in fact, are proposing to release models accompanied with documentation that details their performance characteristics. Documenting your decisions and rationales can be particularly helpful in conversations with regulators.

In some ways, this article is premature—so much is changing that we’ll likely have a profoundly different understanding of gen AI and its capabilities in a year’s time. But the core truths of finding value and driving change will still apply. How well companies have learned those lessons may largely determine how successful they’ll be in capturing that value.

The authors wish to thank Michael Chui, Juan Couto, Ben Ellencweig, Josh Gartner, Bryce Hall, Holger Harreis, Phil Hudelson, Suzana Iacob, Sid Kamath, Neerav Kingsland, Kitti Lakner, Robert Levin, Matej Macak, Lapo Mori, Alex Peluffo, Aldo Rosales, Erik Roth, Abdul Wahab Shaikh, and Stephen Xu for their contributions to this article.

This article was edited by Barr Seitz, an editorial director in the New York office.

Explore a career with us

Related articles.

The economic potential of generative AI: The next productivity frontier

Rewired to outcompete

Meet Lilli, our generative AI tool that’s a researcher, a time saver, and an inspiration