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ItemEssays on Fintech, AI, and Innovation in Finance(Georgia Institute of Technology, 2024-04-25) Du, WendiThe dissertation consists of five essays on FinTech, AI and innovation in finance. These essays center around how innovation and capital market influence each other, and how to use cutting-edge technologies like machine learning and AI to address the economic questions that would otherwise remain unanswered. In the first essay, I investigate the redeployability channel of trademarks' collateral value. Using a novel court decision that exogenously weakens trademark redeployability, I find a 3.4 percentage point reduction in affected firms’ book leverage, equivalent to a 16.9\% decrease in their average book leverage. By using firm-level trademark portfolio data and employing natural language processing (NLP) techniques, including ChatGPT, I show that firms with more licensed trademarks (i.e., those more exposed to the court ruling), experience a stronger negative impact. Additionally, affected firms are less likely to pledge their registered trademarks as collateral afterward. When they do pledge, they pledge a greater number of trademarks, as well as more valuable ones. Affected firms also register fewer new trademarks in the future. In sum, my results highlight the value of trademark collateral in enhancing firms' debt capacity through its redeployability channel. In the second essay, we develop a text-based measure of firm-level inflation exposure from earnings calls. Our deep learning model identifies sentences discussing price changes, while distinguishing price increases from decreases and inputs from outputs. Our aggregate inflation exposure measure strongly correlates with official inflation measures. Firms with higher inflation exposure experience negative stock price reactions to earnings calls. The price reaction is attenuated when a firm has pricing power. Further, firms with higher inflation exposure have higher future costs of goods sold and lower operating cash flows. They perform worse on Consumer Price Index (CPI) release days when CPI exceeds the consensus forecast. In the third essay, we explore the area of emerging technologies which can potentially transform business and society but are difficult to identify and prone to hype and uncertainty. We construct a dictionary of emerging technology phrases from earnings calls using deep learning techniques and document an immediate positive stock market reaction to firms’ discussions of emerging technologies. We find that the positive reaction is more pronounced when firms discuss emerging technologies early in their life cycle. Firms with lower ex-ante credibility, such as a prior history of earnings management, innovate less ex-post and experience poorer long-term returns. Overall, our results highlight when firms' discussions of emerging technologies convey credible information to investors. The fourth essay examines whether managers walk the talk on the environmental and social discussion. We train a deep-learning model on various corporate sustainability frameworks to construct a comprehensive Environmental and Social (E\&S) dictionary. Using this dictionary, we find that the discussion of environmental topics in the earnings conference calls of U.S. public firms is associated with higher pollution abatement and more future green patents. Similarly, the discussion of social topics is positively associated with improved employee ratings. The association with E\&S performance is weaker for firms that give more non-answers and when the topic is immaterial to the industry. Overall, our results provide some evidence that firms do walk their talk on E\&S issues. In the final essay, we address the limitations of generic training schemes in the realm of financial language models. We propose a novel domain specific Financial LANGuage model (FLANG) which uses financial keywords and phrases for better masking. We further extend it to include span boundary objective and in-filing objective, utilizing the fact that many financial terminologies are phrases. Additionally, the evaluation benchmarks in the field have been limited. To this end, we contribute the Financial Language Understanding Evaluation (FLUE), an open-source comprehensive suite of benchmarks for the financial domain. These include new benchmarks across 5 NLP tasks in financial domain as well as common benchmarks used in the previous research. Experiments on these benchmarks suggest that our model outperforms those in prior literature on a variety of NLP tasks.
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ItemEssays on responsible and sustainable finance(Georgia Institute of Technology, 2023-04-25) Malakar, BaridhiThe dissertation consists of three essays on responsible and sustainable finance. I show that local communities should be seen as stakeholders to decisions made by corporations. In the first essay, I examine whether the imposition of fiduciary duty on municipal advisors affects bond yields and advising fees. Using a difference-in-differences analysis, I show that bond yields reduce by 9\% after the imposition of the SEC Municipal Advisor Rule. Larger municipalities are more likely to recruit advisors after the rule is effective and experience a greater reduction in yields. However, smaller issuers do not seem to significantly benefit from the SEC Rule in terms of offering yield. Using novel hand-collected data, I find that the average advising fees paid by issuers does not increase after the regulation. In the second essay, we analyze the impact of \$40 billion of corporate subsidies given by U.S. local governments on their borrowing costs. We find that winning counties experience a 15.2 bps increase in bond yield spread as compared to the losing counties. The increase in yields is higher (18 -- 26 bps) when the subsidy deal is associated with a lower jobs multiplier or when the winning county has a lower debt capacity. However, a high jobs multiplier does not seem to alleviate the debt capacity constraints of local governments. Our results highlight the potential costs of corporate subsidies for local governments. In the third essay, we provide new evidence that the bankruptcy filing of a locally-headquartered and publicly-listed manufacturing firm imposes externalities on the local governments. Compared to matched counties with similar economic trends, municipal bond yields for affected counties increase by 10 bps within a year of the firm’s bankruptcy filing. Counties that are more economically dependent on the industry of the bankrupt firm are more affected and do not immediately recover from the negative impact of the corporate bankruptcy. Our results highlight that local communities are major stakeholders in public firms and how they are adversely affected by corporate financial distress. The final essay examines whether managers walk the talk on the environmental and social discussion. We train a deep-learning model on various corporate sustainability frameworks to construct a comprehensive Environmental and Social (E\&S) dictionary. Using this dictionary, we find that the discussion of environmental topics in the earnings conference calls of U.S. public firms is associated with higher pollution abatement and more future green patents. Similarly, the discussion of social topics is positively associated with improved employee ratings. The association with E\&S performance is weaker for firms that give more non-answers and when the topic is immaterial to the industry. Overall, our results provide some evidence that firms do walk their talk on E\&S issues.
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ItemEssays on financial intermediation and household finance(Georgia Institute of Technology, 2020-07-14) Paradkar, Nikhil DilipThis dissertation consists of three essays on the intersection of financial intermediation and household finance. In the first essay, using proprietary account-level data from a major credit bureau, I examine the impact of stress tests on bank risk-taking in the U.S. consumer credit card market. I decompose credit supply and demand effects by exploiting credit card--level data on limits and balances matched to both consumers and banks. For the same consumer, I examine the lending response of banks experiencing higher stress test--induced capital requirements (i.e., high-exposure banks) relative to less-exposed banks. I find that the earlier rounds of stress tests induced high-exposure banks to sharply reduce credit limits, especially for ex-ante risky borrowers. In contrast, in later rounds of stress tests, high-exposure banks increased limits for risky consumers. Consistent with higher bank risk-taking in later rounds, cards issued by highly exposed banks have a higher ex-post likelihood of default. Additionally, I document that more affected non-prime borrowers are more likely to default subsequently, and that this effect is markedly pronounced for the low-income and less-educated consumer segments. My findings suggest that stress test--induced increases in capital requirements can encourage higher bank risk-taking, with distributional consequences for consumer creditworthiness. In the second essay, using comprehensive credit bureau data, we study how obtaining marketplace lending (MPL) credit impacts consumers' future borrowing capacities and outcomes. We find that MPL borrowers' credit scores improve temporarily after loan origination relative to observably similar bank borrowers and borrowers with unmet credit demand, but MPL borrowers default at higher rates subsequently. We show that the initial improvement in capacities is somewhat mechanical, while the subsequent deterioration in outcomes indicates MPLs' screening is weaker relative to banks. MPL screening relative to banks is especially weaker when banks have relationship-based information and when MPL platforms provide less information to MPL investors. In the third essay, using comprehensive credit card--borrower--bank matched data of approximately 500 million credit cards in the U.S., we analyze how a sharp unexpected decline in banks' short-term wholesale funding in 2008 affected their consumers. We decompose credit supply and demand effects using the sudden dry-up of short-term wholesale funding (which accounted for 17.8% of bank funding pre-2008) and account-level data on credit card limits and balances. For the same consumer, credit card issuers experiencing a 10% greater decline in wholesale funding reduced credit limits by 0.9% more relative to other issuers. Consumers' aggregate card balances decreased by 0.32% for a 1% reduction in aggregate limits induced by the wholesale funding liquidity shock. We document significant heterogeneity in the pass-through of the bank liquidity shocks with banks cutting credit limits by more for credit-constrained consumers (e.g., lower credit-score and higher credit utilization consumers). These consumers respond by cutting their consumption as they are less able to borrow from alternate sources. Moreover, this consumption decline is long-lasting for these credit-constrained consumers. Our results highlight that when banks face liquidity shocks, they are more likely to pass on these shocks to consumers who are least able to hedge against them. Consequently, our results show who bears the real costs of fragile bank funding structures.