Tag Archives: financial services

Artificial Intelligence in Investment Decision-Making: A Pusan National University Perspective

Artificial intelligence (AI) is reshaping modern finance, supporting applications such as stock market forecasting, portfolio management, and investment advice. However, researchers from Pusan National University and their international collaborators argue that accurate market predictions do not always translate into better investment decisions. Instead, they suggest that financial AI should be assessed by its ability to improve real-world decision-making rather than prediction accuracy alone.

To address this challenge, Professor Yoontae Hwang of Pusan National University and Professor Stefan Zohren of the University of Oxford developed the Signature-Informed Transformer (SIT), a decision-focused AI framework. Rather than concentrating solely on predicting future prices, the model learns from how markets evolve and how different assets influence one another, enabling it to optimise investment decisions while accounting for risk. Published in the Proceedings of the 43rd International Conference on Machine Learning on 30 April 2026, the study lists Professor Hwang as first author.

The researchers evaluated the SIT framework using equity market data from the United States and China. Compared with conventional forecasting-based methods, the decision-focused approach delivered stronger risk-adjusted returns and more consistent wealth accumulation. According to Professor Hwang, the findings suggest that future financial AI systems should prioritise decision quality over prediction accuracy to achieve better investment outcomes.

In a second study, the research team investigated whether the reported success of financial AI can be reliably trusted. Analysing 164 studies on large language models (LLMs) in finance published between 2023 and 2025, they identified several recurring sources of bias that could overstate model performance. These included the unintended use of future information, survivor bias resulting from the exclusion of failed companies, unrealistic evaluation settings, and the omission of practical considerations such as transaction costs. Published in the Proceedings of the 43rd International Conference on Machine Learning on 1 May 2026, the study lists Professor Hwang as co-first author.

To improve research quality, the team introduced a Structural Validity Framework, a practical checklist designed to help researchers evaluate whether financial AI systems are tested under realistic conditions and whether their reported performance is likely to generalise beyond laboratory settings. The framework encourages more transparent and rigorous evaluation practices that better reflect real-world financial markets.

Together, the two studies highlight a common principle: AI should be designed to support meaningful financial decisions and evaluated using realistic benchmarks. Looking ahead, the researchers envision AI-powered “flight simulators” for financial markets, enabling institutions and regulators to test investment strategies, financial products, and market shocks in virtual environments before they affect real investors. Such advances could ultimately promote more transparent financial advice and more trustworthy AI systems.

More information: Yoontae Hwang et al, Signature-Informed Transformer for Asset Allocation, Proceedings of the 43rd International Conference on Machine Learning. DOI: 10.48550/arXiv.2510.03129

Journal information: Proceedings of the 43rd International Conference on Machine Learning Provided by Pusan National University

Housing Market Inflated by Pandemic Loan Fraud

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For many Americans hoping to buy a home, the past several years have been exceptionally difficult. Between the end of 2019 and the end of 2022, the median sales price of homes in the United States rose by 35%, according to the Federal Reserve Bank of St. Louis. Although economists have largely attributed the surge to pandemic-related migration and remote work trends, new research suggests another important factor contributed significantly to the housing boom: fraud linked to government pandemic relief loans.

Researchers from the McCombs School of Business at The University of Texas at Austin found that fraudulent borrowing through the Paycheck Protection Program (PPP) accounted for roughly 22.5% of the average increase in housing prices during 2020 and 2021. The study was conducted by finance professors Samuel Kruger and John Griffin, along with doctoral student Prateek Mahajan. Their findings suggest that pandemic loan fraud affected not only taxpayers but also ordinary homebuyers who purchased properties at inflated prices.

The PPP was introduced as an emergency federal program to help small businesses survive the economic disruption caused by COVID-19. Although the government supplied the funding, banks and fintech firms were responsible for distributing the loans. In the rush to move money quickly, the program lacked sufficient safeguards to prevent fraudulent applications. Earlier work by the same researchers identified at least $117 billion in suspicious lending activity, much of it concentrated in specific geographic areas.

To understand how fraudulent borrowers used the funds, the researchers analysed housing purchases across 18,761 ZIP codes covering 93% of the U.S. population. They discovered that areas with the highest concentrations of suspected PPP fraud experienced housing price growth that was 5.8% higher than areas with the lowest fraud levels. Individuals suspected of fraudulent borrowing were also 17% more likely than average to purchase homes, particularly in regions where housing supply was already limited.

The researchers concluded that fraudulent pandemic lending had a larger effect on housing prices than other commonly cited pandemic-era factors, including migration patterns and remote work. Beyond housing, the study also found connections between PPP fraud and increased spending on automobiles, furniture, restaurants, grocery stores, and financial services. According to Kruger, many ordinary homeowners may ultimately suffer financial losses if inflated housing demand fades and property values decline.

The findings also raise broader concerns about long-term economic consequences. Griffin noted similarities with the 2008 financial crisis, when inflated housing markets contributed to widespread mortgage defaults and banking instability. The researchers argue that future government relief programs must include stronger safeguards from the beginning to reduce fraud and prevent economic distortions. Their study highlights how large-scale fraudulent transfers can ripple through the economy, affecting not only public finances but also housing affordability and financial stability.

More information: John Griffin et al, Did pandemic relief fraud inflate house prices? Journal of Financial Economics. DOI: 10.1016/j.jfineco.2026.104275

Journal information: Journal of Financial Economics Provided by University of Texas at Austin

Mobile Money Helps the Poor, but Confidence Matters

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Mobile money is helping millions of people without traditional bank accounts participate more fully in the economy. Still, a new study suggests that trust, fairness and effective regulation will ultimately determine whether the system succeeds in reducing poverty. With more than two billion registered mobile money accounts worldwide and nearly $1.7 trillion processed annually, phone-based financial services are becoming an increasingly important part of daily life, particularly in low- and middle-income countries.

Researchers at the University of East London reviewed more than a decade of evidence on mobile money, analysing 65 studies published between 2014 and 2026. Their findings show that mobile money can help users send and receive funds more easily, save money securely, cope with emergencies and support small business activities. The study was published in the Journal of Financial Services Marketing.

According to the researchers, mobile money has proven especially valuable as an anti-poverty tool because it expands financial access for people who are unbanked or underserved by traditional banking systems. It can reduce the cost of transferring money, improve household resilience during financial shocks, support women and rural communities, and strengthen cash flow for micro, small and medium-sized enterprises. In some regions, the benefits have been particularly striking.

The study points to evidence from Kenya, where access to M-Pesa helped lift an estimated 194,000 households out of poverty. Many of the gains were seen among female-headed households, highlighting the potential of mobile money to improve economic inclusion and opportunity for vulnerable groups. Researchers say these findings demonstrate the significant social and economic potential of accessible digital financial systems.

However, the authors caution that mobile money is not a guaranteed solution to poverty. Its effectiveness depends not only on access to mobile phones, but also on public confidence in the system, strong consumer protections and balanced regulation. They warn that excessive taxes or restrictive policies can discourage use, especially among low-income populations. In Uganda, for example, transaction taxes on mobile money were linked to a sharp decline in usage among poorer users.

Co-author Godfried Adaba said mobile money can provide people with a safer and easier entry into financial life, but stressed that access alone is insufficient without trust and supportive systems. Kirk Chang added that mobile money works best when users, service providers and regulators work together to empower communities rather than create new forms of exclusion or risk. Looking ahead, the researchers say more studies are needed to examine how taxation, fraud, artificial intelligence, regulation and emerging digital finance technologies will shape the future of mobile money.

More information: Godfried Adaba et al, Mobile money: Systematic review, multilevel framework, and research agenda, Journal of Financial Services Marketing. DOI: 10.1057/s41264-026-00370-x

Journal information: Journal of Financial Services Marketing Provided by University of East London

Digital Finance Platforms Offer New Opportunities for Small Businesses

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A new study suggests that simple digital finance tools, including mobile money services, may help small businesses strengthen their long-term competitiveness rather than simply improving access to banking services. Led by researchers at the University of East London, the study examined 113 micro, small and medium-sized enterprises (MSMEs) in Ghana and found that businesses gained the greatest benefits when digital finance tools became integrated into everyday operations rather than being used only for transactions. Firms reported improvements in efficiency, customer service and flexibility.

Mobile money services allow people and businesses to send, receive and store money using mobile phones without requiring a traditional bank account. The researchers say mobile phones are increasingly becoming strategic business tools for many small firms, helping them manage finances, reach customers and compete in rapidly changing markets. The study was conducted by researchers from the Royal Docks School of Business and Law together with partners in Ghana.

The findings could have implications beyond the African case study. Across many developing economies, millions of small businesses still face barriers related to banking, credit and digital infrastructure. The researchers suggest that accessible financial technology could help smaller firms compete more effectively, strengthen local economies and improve resilience during economic shocks and periods of uncertainty.

Lead author Godfried Adaba, Lecturer in Business Analytics, said, “Our findings show that digital finance can also become a strategic tool that helps small businesses compete and innovate. The wider lesson is that digital finance works best when it is simple enough for everyday use and deeply embedded into how businesses operate.” The research, published in Global Business Review, also found that ease of use mattered more than many experts had expected, with businesses far more likely to adopt tools they viewed as simple and reliable.

Co-author Francis Frimpong said, “Ease of use is not a minor issue for small businesses. Indeed, it is often the deciding factor. If digital finance systems are too complex or difficult to trust, many firms simply will not use them. That matters globally because it shows that successful FinTech innovation must be about creating tools ordinary businesses can use confidently every day.” The researchers added that policymakers, banks and technology companies should focus not only on expanding digital access, but also on improving usability, trust and digital skills among small business owners.

More information: Godfried Adaba et al, From Inclusion to Advantage: FinTech Adoption and Competitive Strategy Among MSMEs in Ghana, Global Business Review. DOI: 10.1177/09721509261428912

Journal information: Global Business Review Provided by University of East London

When transparency goes too far, markets suffer

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Transparency has become a fashionable mantra in modern finance. Opening up the inner workings of markets is widely assumed to improve decision-making, protect investors, and help regulators spot problems before they spiral out of control. From this perspective, more information appears synonymous with healthier markets, greater accountability, and reduced risk. As a result, transparency is often treated as an unquestioned virtue rather than a policy choice with trade-offs.

Recent academic research, however, suggests that this faith in transparency may be misplaced. Michael Sockin, a finance scholar, argues that making too much information publicly available can actually weaken financial outcomes. By modelling the interaction between corporate bond markets and short-term lending markets, he finds that reduced transparency can sometimes produce better results for the economy as a whole. When detailed information is freely available, companies may be incentivised to take on riskier projects, increasing the likelihood of widespread instability.

Sockin cautions that additional data does not automatically lead to wiser behaviour. In some cases, excessive transparency encourages looser credit conditions, allowing firms to borrow more easily even when their underlying risk is rising. This can result in more corporate defaults and heavier losses for investors. Those losses often spill over into institutions such as pension funds and insurance companies, where financial stress can have serious long-term consequences for households and retirees.

At the centre of this analysis are repurchase agreement markets, commonly known as repo markets. These markets function much like financial pawnshops, allowing large institutional investors to raise short-term cash by temporarily selling securities to lenders, with an agreement to buy them back later at a slightly higher price. Although they operate largely out of public view, repo markets are essential to the smooth functioning of the financial system and support trillions of dollars in daily lending.

Over the past two decades, regulators have sought to increase transparency in both bond and repo markets through detailed reporting systems. These reforms were intended to reduce uncertainty and promote confidence. Sockin’s models suggest that while such measures can expand participation and boost lending, they also reduce discipline. With detailed information readily available, lenders may underestimate risk, while borrowers become less cautious, leading to an overall decline in investment quality.

This framework also helps explain the dynamics of the 2008 global financial crisis. Years of expanding transparency and easy credit encouraged greater risk-taking, leaving the system vulnerable when asset values collapsed. When confidence evaporated, lenders abruptly withdrew, markets froze, and companies struggled to refinance their debts. Sockin’s conclusion is not that transparency is harmful in itself, but that it has limits. A moderate approach — providing general price information without revealing every transaction detail — may preserve discipline and reduce the likelihood of future crises.

More information: Michael Sockin, Informational frictions in funding and credit markets, Journal of Economic Theory. DOI: 10.1016/j.jet.2025.106101

Journal information: Journal of Economic Theory Provided by University of Texas at Austin

A Growing Banking Sector Means Higher Borrower Costs

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When banks become crowded within a lending market, the familiar logic of supply and demand begins to unravel. In most markets, an increase in suppliers would normally drive prices down, benefiting consumers through greater competition. Lending, however, appears to follow a different set of rules. New research shows that as the number of banks operating in a local market rises, borrowers may actually face higher costs rather than lower ones, challenging long-held assumptions about competition in financial services.

The research finds that a greater density of banks leads to higher loan prices, measured through interest rates. Specifically, for every six additional banks operating within a county, average interest rates increase by around seven basis points. While that figure may appear modest at first glance, it can translate into meaningful additional costs for large loans and long repayment periods. The finding runs directly against the intuitive idea that more choice among lenders should naturally result in cheaper credit.

This counterintuitive outcome emerges from how banks assess and manage risk. Lending decisions are shaped not only by observable financial data but also by how much private information a bank has about a borrower. Some banks are better than others at screening applicants, either because of superior analytical tools or because they have deeper relationships with local firms. When one bank approves a borrower that others have rejected, it can trigger concerns that negative information has been missed.

These concerns intensify as the number of banks in a market increases. In a crowded environment, winning a borrower may feel less like a success and more like a warning sign. Banks may worry that competitors uncovered unfavourable information that they themselves failed to detect. To compensate for that uncertainty, lenders raise interest rates as a form of protection against potential default. Rather than pricing loans aggressively, they adopt a more cautious stance.

This dynamic closely resembles what economists describe as the “winner’s curse”. In highly competitive auctions, the winning bidder often pays more than the asset is truly worth because they were the most optimistic participant. In lending markets, securing a borrower in a sea of competitors can similarly suggest that the lender has underestimated the borrower’s risk. The higher interest rate becomes a buffer against the possibility that the loan turns out to be a bad bet.

Competition also affects the volume and quality of lending. As the number of banks grows, total lending increases significantly, but so does risk. Higher lending volumes are accompanied by a greater probability of default, indicating that banks are extending credit more broadly and to riskier borrowers. In addition, repeated borrowing from the same bank can result in higher interest charges, as the lender gains deeper insight into the borrower’s true risk profile and adjusts pricing accordingly.

Taken together, these findings point to a surprising conclusion: more competition is not always better for borrowers. In more concentrated banking markets, lenders may feel less exposed to hidden information and therefore offer more favourable rates. This has important implications for regulators, who often promote competition by discouraging mergers or forcing banks to divest branches. It also offers practical insight for small businesses, which may benefit from considering bank concentration when deciding where to operate or seek financing.

More information: Cesare Fracassi et al, Adverse Selection in Corporate Loan Markets, Journal of Finance. DOI: 10.1111/jofi.70011

Journal information: Journal of Finance Provided by University of Texas at Austin

Mounting Systemic Threats in US Leveraged Loan Market Could Spark Next Financial Crisis, Study Warns

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A recent study by the University of Bath uncovered troubling distortions in the U.S. leveraged loan market, raising concerns that a new financial crisis could be on the horizon. According to the research, loans with high levels of leverage are being systematically underpriced, particularly by non-bank lenders—often referred to as “shadow banks”—that operate outside the scope of traditional financial regulation. This mispricing, the authors argue, poses a systemic risk that may go undetected until it manifests in severe economic instability.

Leveraged loans, typically extended to borrowers with substantial debt burdens or subpar credit histories, have seen default rates soar to their highest levels in four years. Data from the Financial Times in December 2024 indicated that the U.S. leveraged loan default rate had climbed to 7.2%, marking its highest point since the end of 2020. Many indebted companies are turning to distressed debt exchanges as a last-ditch effort to avoid bankruptcy. These arrangements often erode investor recovery rates, underscoring the fragility and precariousness of this market segment.

Dr Ru Xie, Associate Professor of Finance at the University of Bath’s School of Management and lead author of the study titled Leveraged Loans: Is High Leverage Risk Priced In?, emphasised that the risk associated with leverage is not being adequately priced in—especially by non-bank financial institutions. Since 2014, the pricing of leverage risk has deteriorated markedly, with the sharpest decline evident among the riskiest borrowers. These are typically clients of shadow lenders who issue loans with minimal protective covenants and then package these loans into securities to be sold on secondary markets. The diminished risk premium, particularly for the most vulnerable segments, suggests a breakdown in how financial markets evaluate and compensate for credit risk.

The study portrays a market landscape reshaped by structural changes over the past decade. The rapid ascent of non-bank lenders, the explosive growth of collateralised loan obligations (CLOs), and the proliferation of covenant-lite loan structures have created a breeding ground for systemic vulnerability. Unlike traditional banks, non-bank lenders are not subject to the same rigorous oversight, yet they now originate a significant share of new leveraged loans. This decentralisation of credit risk, with weak documentation standards and limited transparency, leaves regulators in a difficult position—largely unable to see or address the full extent of risk accumulating within the system.

Professor David Newton, co-author of the report, warned that these risks should not be viewed solely through a credit lens. “With today’s heightened geopolitical tensions—from global trade disruptions to military conflicts—and continued market volatility, the mispricing of leverage risk takes on macroprudential significance,” he said. “Should a wave of distress emerge among leveraged borrowers—particularly those financed by shadow banks—we could witness a new credit or banking crisis that escapes regulatory detection until it is too late.” His remarks highlight the growing divide between the visible portions of the financial system and the opaque, complex web of lending arrangements that now operate primarily out of view.

The researchers identified two primary forces driving this decline in risk sensitivity. First, the growing use of covenant-lite loans, which lack the performance-based protections traditionally embedded in lending agreements, significantly increases information asymmetry. With fewer covenants, banks and other lenders have reduced incentives or capacity to monitor borrower behaviour, especially when loans are bundled into CLOs and sold off in tranches. Second, the increasing securitisation of these loans further weakens the alignment of interest between originators and investors. As the risk is passed downstream to third-party investors, the original lenders retain little incentive to uphold rigorous underwriting standards.

In light of these findings, the authors call for more robust regulatory scrutiny of non-bank lenders and the structures they employ. They argue that opaque securitisation practices, coupled with weak documentation and loose lending standards, have enabled a build-up of systemic risk that traditional oversight mechanisms are ill-equipped to address. Global financial authorities, including the European Central Bank and the Bank of England, have recently voiced similar concerns about shadow banking and the unchecked expansion of leveraged lending. The University of Bath study adds an urgent academic perspective to this growing chorus, underscoring the need for coordinated policy action before the next crisis takes root.

The research presents a sobering assessment of the leveraged loan market’s trajectory in the United States. It suggests that without meaningful reform, the current path of underpricing leverage risk—driven by shadow lending, weakened oversight, and a securitisation-fuelled boom—could culminate in a destabilising financial event. As policymakers, investors, and regulators grapple with mounting economic uncertainty and complex global risks, this study serves as both a warning and a call to pre-emptively address the structural vulnerabilities now embedded within modern credit markets.

More information: Ru Xie et al, Leveraged loans: is high leverage risk priced in?, Inderscience Online Journals. DOI: 10.1504/IJBAAF.2025.146550

Journal information: Inderscience Online Journals Provided by University of Bath

Dodging the Red Zone: How Automated Bank Alerts Help Prevent Expensive Overdrafts

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Automatic bank alerts have emerged as a remarkably effective tool in reducing the financial strain overdraft charges impose on consumers. According to new research conducted in the United Kingdom, customers who automatically sign up to receive alerts warning them that their bank balance is approaching zero—or has just dipped below it—experience significantly fewer overdraft fees and associated charges. The impact is substantial and widespread: analysts estimate that the charge reduction could lead to annual savings of between £170 million and £240 million across the country. Notably, the most significant benefits are seen among low-income customers, who are often the most heavily penalised by overdraft structures and least able to afford the fees.

The policy underpinning these alerts dates back to 2018 when the UK government mandated that major banks must automatically issue warnings to customers without arranged overdraft agreements when their accounts move into deficit. This came in response to the staggering £2.6 billion in annual overdraft fees consumers were collectively paying—many unaware that they had even entered overdraft. Financial regulators enlisted a team of researchers to study how customers at two large banks responded to early versions of the alerts to optimise the initiative. These banks had begun trialling the system before the nationwide policy took effect, offering a valuable opportunity to track behavioural changes over time.

The researchers found a significant reduction—up to 19 per cent—in fees related to overdrafts and insufficient funds once the alerts were introduced. Notably, the timing of the alert played a crucial role in its effectiveness. Notifications that arrived just as customers slipped into overdraft proved more successful than those sent hours or days in advance. The immediacy of the message seemed to trigger a stronger behavioural response, prompting customers to take quick action to avoid or minimise fees. This insight highlights the value of precision in financial communication: alerts must be timely and relevant to influence consumer behaviour meaningfully.

One of the key voices behind the study was Professor Matthew Osborne, an associate professor of marketing at the University of Toronto Mississauga, who is also affiliated with the Rotman School of Management. He noted that banks have long profited from customers’ lack of awareness regarding overdraft fees, with many consumers only discovering the existence of such charges once they appear on their statements. Before the introduction of automatic alerts, these fees comprised an estimated 15 to 20 per cent of bank revenue. Even more striking is that around half of those fees were paid by fewer than five per cent of customers—many of whom lived in deprived areas and paid as much as £380 annually in overdraft charges, roughly equivalent to two per cent of their income.

Although banks had technically been required since 2012 to offer alerts on an opt-in basis, the uptake was minimal, with fewer than one in ten customers signing up. The switch to automatic alerts reversed this dynamic, with the overwhelming majority choosing not to opt-out. A follow-up survey revealed that most recipients found the alerts helpful, and over two-thirds reported taking action in response. These actions typically involved moving funds from savings, cutting discretionary spending, or borrowing small sums from family or friends. Surprisingly, relatively few customers transferred their debt to lower-interest credit cards—a behaviour the researchers suggest warrants further study, as it could offer another route to reducing personal financial strain.

In light of the findings, the British government has broadened the scope of the alert programme. More banks and types of overdrafts are now covered, new caps have been introduced on the charges that can be levied, and there are stronger requirements for clear, transparent communication of fees. While personal responsibility remains vital to financial management, the research illustrates that well-designed tools can dramatically improve outcomes for individuals who might otherwise be repeatedly penalised. As Professor Osborne observed, keeping track of one’s money is essential—but without the right tools, even the most diligent customers can stumble. In this case, a simple nudge delivered at the right moment has proven to be a powerful mechanism for financial well-being.

More information: Matthew Osborne et al, Sending Out an SMS: Automatic Enrollment Experiments for Overdraft Alerts, Journal of Finance. DOI: 10.1111/jofi.13404

Journal information: Journal of Finance Provided by University of Toronto, Rotman School of Management

ChatGPT’s Shortcomings Indicate It’s Not Ready to Supplant Finance Experts

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Large language models such as ChatGPT have demonstrated proficiency in selecting multiple-choice answers on financial licensing exams, yet they encounter difficulties when tasked with more complex, nuanced activities. This was highlighted in a study by Washington State University, which scrutinised over 10,000 responses from artificial intelligence models, including BARD, Llama, and ChatGPT, to questions from financial exams.

The study, spearheaded by DJ Fairhurst from WSU’s Carson College of Business, involved the models not only selecting answers but also articulating the reasoning behind their choices. These explanations were then evaluated against those given by human finance professionals. Among the models, two iterations of ChatGPT emerged as the most adept at these tasks. Nevertheless, even these versions exhibited significant inaccuracies when addressing more intricate subjects.

DJ Fairhurst remarked, “It’s far too early to be concerned about ChatGPT completely taking over finance jobs.” He explained that while the model performs admirably with well-documented broad concepts, it struggles significantly with unique, specific issues. This study, published in the Financial Analysts Journal, included questions from licensing exams like the Securities Industry Essentials exam and the Series 6, 7, 65, and 66, aiming to mirror tasks that financial professionals might actually undertake.

The researchers took the assessment a step further by requiring the models to produce written explanations for their answers, specifically choosing questions that reflect the practical job tasks of financial professionals. Fairhurst emphasised the necessity of probing beyond the models’ ability to select correct answers to understand their capabilities.

Of all the models tested, the paid version of ChatGPT, version 4.0, was most closely aligned with human expert responses, showing a substantial lead in accuracy—18 to 28 percentage points higher than its counterparts. Interestingly, when the researchers fine-tuned an earlier version of ChatGPT, version 3.5, by providing examples of correct responses and explanations, it nearly matched and occasionally exceeded the performance of version 4.0.

Despite these advances, both versions of ChatGPT still fell short in certain areas. They performed well in reviewing securities transactions and monitoring financial market trends. Still, their responses were less accurate in specialised scenarios such as assessing clients’ insurance coverage and tax status.

Fairhurst, Greene, and WSU doctoral student Adam Bozman are further exploring ChatGPT’s limitations and capabilities in a new project involving evaluating potential merger deals. By focusing on deals concluded after September 2021, a period beyond ChatGPT’s training data, they aim to gauge the model’s effectiveness in real-world scenarios. Preliminary results suggest that the AI model is not particularly adept at these tasks.

The researchers concluded that while ChatGPT may alter the employment landscape for entry-level analysts in investment banks, it is more suitable as a supportive tool rather than a replacement for seasoned financial professionals. The evolving role of AI could potentially lead to a reduction in junior analyst positions, not because ChatGPT outperforms them but because it can handle the more routine tasks that have traditionally been assigned to them. This shift, as Fairhurst notes, could make the traditional practice of hiring a large number of junior analysts and retaining only the best a more costly approach.

More information: Douglas (DJ) Fairhurst et al, How Much Does ChatGPT Know about Finance? Financial Analysts Journal. DOI: 10.1080/0015198X.2024.2411941

Journal information: Financial Analysts Journal Provided by Washington State University

The Impact of Self-Donations on Fundraising Success — Creators Who Invest in Their Own Campaigns See Improved Outcomes

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Researchers from the City University of New York and the University of Texas at Austin have recently contributed to the Journal of Marketing with a study assessing self-donations’ impact on crowdfunding achievements. Titled “Self-Donations and Charitable Contributions in Online Crowdfunding: An Empirical Analysis,” and authored by Zhuping Liu, Qiang Gao, and Raghunath Singh Rao.

According to Giving USA, a record $557.16 billion was donated by Americans in 2023 to support various causes, including education, religion, human services, and public health. While traditional charities have long relied on celebrity endorsements, galas, public service announcements, and extensive advertising campaigns to raise funds, modern online crowdfunding platforms like GoFundMe and DonorsChoose offer a more direct approach. These platforms connect projects directly with potential donors, thereby bypassing the need for costly marketing strategies.

The study reveals that campaign organizers who personally contribute to their crowdfunding initiatives significantly increase their chances of success. This act of self-donation not only serves as a strong endorsement of the project’s value but also accelerates the pace and volume of contributions from others, enhancing the overall probability of meeting funding targets. The increasing dependence of non-profit and educational initiatives on crowdfunding platforms underscores the effectiveness of self-donation in bolstering these efforts.

An extensive analysis of millions of donations made through DonorsChoose, a platform where educators seek financial support for classroom supplies and educational projects, was conducted. The findings indicate that when teachers visibly contribute to their projects, it effectively communicates the project’s worth and their commitment to it. Liu emphasizes that the success of self-donation hinges not just on the amount given but also on the timing and visibility of the contributions.

By investing their funds, educators can attract additional support, which is crucial, especially for projects at the initial stage or for new users on the platform without a well-established reputation. Gao notes that larger self-donations are particularly impactful, increasing the likelihood of achieving the fundraising goals. Moreover, projects with self-donations often follow up with impact letters to donors, providing further indirect evidence of a project’s quality and its correlation with self-donation.

There is a strong case for platforms to encourage visible self-donations to enhance the efficiency of matching donors with high-quality projects. This could be achieved by promoting self-donations on project landing pages or tailoring project recommendations based on donor preferences. Such strategies could significantly improve campaign success rates.

Promoting self-donation as a fundraising strategy could be transformative for school administrators and district leaders. Given the constraints of school budgets, empowering teachers with effective fundraising tools can substantially improve the educational quality of students. From the standpoint of platforms like DonorsChoose, facilitating and promoting self-donation can augment the efficacy of their services.

The concept of self-donation extends beyond the educational sector, applying to political campaigns and corporate social responsibility (CSR) initiatives. Political candidates frequently use personal funds to demonstrate their commitment, while companies may donate some of their profits to boost their public image. In each scenario, self-contribution is a potent indicator of dedication and quality, influencing the actions of others.

Crowdfunding platforms might consider developing features that simplify the process for project organizers to make visible self-donations and highlight these contributions to potential donors. Furthermore, providing guidelines or best practices for strategically timing self-donations could maximize their impact.

For Chief Marketing Officers, self-donation visibility is critical to fundraising success. It is crucial to manage the risks associated with anonymous self-donations. The timing, frequency, and amount of self-donations should be strategically planned to maximize their fundraising impact. Ideally, an initial self-donation can significantly boost a project’s chances of success.

Rao concludes that by leveraging self-donation as a signalling mechanism, educators can enhance their likelihood of successfully funding their projects, thereby enriching students’ educational experiences. Crowdfunding platforms can improve service offerings by supporting and advocating for self-donation strategies.

The dynamics of self-donation could vary in more complex situations where funds go directly to fundraisers, potentially raising ethical concerns. Future research could expand this inquiry by exploring self-donation’s effects in diverse contexts.

More information: Zhuping Liu et al, Self-Donations and Charitable Contributions in Online Crowdfunding: An Empirical Analysis, Journal of Marketing. DOI: 10.1177/00222429241260687

Journal information: Journal of Marketing Provided by American Marketing Association

How Certain Regions Assist Citizens in Evading Expensive Debt During Difficult Periods

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A recent national study offers compelling evidence that generous unemployment insurance benefits during the COVID-19 pandemic significantly reduced reliance on high-cost credit. Conducted by Rachel Dwyer and Stephanie Moulton of Ohio State University and published in Nature Human Behaviour, the research demonstrated that lower-income individuals in states with more generous benefits were much less likely to acquire new credit cards, personal finance loans, payday loans or other alternative financial service offerings. The findings underscore the critical role that unemployment insurance can serve in preventing low-income Americans from falling further into economic hardship. Moulton explained that providing more generous benefits helps avoid types of debt that are costly to individuals and society at large, a crucial insight for policymakers, economists, researchers, and individuals interested in social welfare and economic policies.

The study’s robust methodology included a large sample size of 2.3 million Americans, monitored from late 2019 through the end of 2021 using data from Experian. By analyzing the variability in unemployment insurance benefits across states and the timing of benefit expansions and contractions, the researchers could assess how these factors influenced the avoidance of costly debt. Dwyer emphasized the importance of unemployment insurance as a critical safety net component, affecting many people during the economic downturn induced by the pandemic.

Their analysis showed that enhanced unemployment benefits led to decreased usage of costly credit, particularly among the lowest-income households. For instance, the probability of these consumers taking out new credit cards was 9.7% lower in states where benefits were most generous. This trend was even more pronounced with alternative financial service loans, such as payday loans, often outside traditional banking channels and with high interest rates.

Moulton noted the disparity between income groups during the pandemic, explaining that while higher-income households might have used savings or credit cards to manage temporary unemployment, the lowest-income groups often had no such options. With savings or access to traditional credit, these consumers could turn to expensive credit options as a last resort, indicating a significant reliance on less desirable financial solutions when state support was lacking.

The study also explored other consumer behaviours during the recession, like spending on existing credit cards and applying for loans, regardless of approval status. Dwyer’s team found that lower-income consumers consistently fared better in states with generous benefits, suggesting that state support played a crucial role in economic stability for these individuals. These findings also contribute to the broader debate about the efficacy and return on investment of government programs like unemployment insurance, indicating that such programs not only assist individuals directly but also prevent broader economic repercussions like increased credit costs and potential bankruptcies.

The study underscores the potential societal gains from such government interventions by highlighting the link between state-provided benefits and reduced high-cost borrowing. Moulton concluded that preventing high-interest borrowing not only helps individuals avoid financial pitfalls but also mitigates costs that society might eventually bear, demonstrating the ripple effects of economic policies on the broader financial ecosystem.

More information: Lawrence M. Berger et al, Inequality in high-cost borrowing and unemployment insurance generosity in US states during the COVID-19 pandemic, Nature Human Behaviour. DOI: 10.1038/s41562-024-01922-8

Journal information: Nature Human Behaviour Provided by The Ohio State University

A Suggested Reporting Mechanism to Mitigate Bank Runs

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The recent collapses of Silicon Valley Bank and two other financial institutions, following panic-induced runs on deposits, have ignited a longstanding discourse in bank regulation: determining the delicate balance between transparency and discretion. Regulators necessitate comprehensive insight into a bank’s balance sheet to enable timely intervention before its demise. However, an excess of openness could trigger premature withdrawals from a salvageable institution, exacerbating the crisis it aims to avert.

Novel research from Texas McCombs has pinpointed a potential equilibrium: an “optimal reporting system” with the potential to forestall future financial tumult. As articulated by Ronghuo Zheng, associate professor of accounting, in this proposed framework, occurrences akin to the tumultuous events witnessed at Silicon Valley Bank and its counterparts would be rendered less probable or calamitous. A central bone of contention with the existing system lies in its adoption of fair-value accounting. This methodology appraises a bank’s assets at prevailing fair market values rather than initial costs.

Nevertheless, a notable exception exists within this paradigm: the non-mandatory disclosure of so-called HTM (Held-To-Maturity) securities at fair value. These encompass 10-year U.S. Treasury bonds intended for retention until maturity. Under this exemption, a bank reports a $100 T-bond at its face value of $100 despite potential fluctuations in its market worth. For instance, on February 13th, a $100 10-year T-bond was valued at $97.16, marking a loss of $2.84.

Typically, such losses remain confined to accounting entries since the bank harbours no intent to liquidate these bonds. However, in March 2023, Silicon Valley Bank was compelled to offload these securities to meet withdrawal demands from substantial depositors. This development triggered a domino effect, prompting additional withdrawals and further bond sales, ultimately culminating in losses amounting to $1.8 billion. This predicament might have been averted had the bank disclosed the market value of its bonds, asserts Zheng. Armed with such information, regulators could have preempted the unfolding crisis.

What does an optimal reporting system entail? Drawing on a prevalent bank-run model, Zheng and Gaoqing Zhang from the University of Minnesota concluded that an optimal system would highlight the riskiest banks while protecting less vulnerable ones from debilitating runs. Striking this balance involves requiring full disclosure under certain conditions but not under others. For example, banks experiencing paper losses on HTM securities would be required to disclose such losses, alerting regulators to potential distress.

Conversely, banks reaping paper gains on HTM securities could report them to reassure depositors, albeit up to a specified threshold. Each bank would be assigned its unique threshold, customised to its susceptibility to runs and its exposure to systemic shocks like economic downturns. Gains surpassing this threshold would remain unreported. Explaining the rationale behind setting a threshold for good news, Zheng elucidates that it’s a preventive measure to shield medium-risk banks from unnecessary panic. If some banks report substantial asset gains while others report moderate gains, depositors may question the latter’s stability despite their medium risk profiles. By capping the reporting of gains across all banks, Zheng’s framework homogenises perceptions of low- and medium-risk banks among depositors, safeguarding solvent institutions from unwarranted and destabilising runs. “We only want to report the very bad banks,” emphasises Zheng. “If you are not too bad, you can stay silent.”

More information: Gaoqing Zhang et al, Optimal Reporting Systems in Bank Runs, The Accounting Review. DOI: 10.2308/TAR-2021-0626

Journal information: The Accounting Review Provided by The University of Texas at Austin