How do Held-to-Maturity (HTM) securities that limit the impacts of banks’ unrealized capital loss on the regulatory capital measures affect banks’ exposure to deposit run risks when policy rates increase? And how should regulators design policies on classifying securities as HTM jointly with bank capital regulation? To answer these questions, we develop a model of bank runs in which banks classify long-term assets as HTM or Asset-for-Sale (AFS). Banks trade off the current cost of issuing equity to meet the capital requirement when the interest rate increases against increasing future run risks when the interest rate increases further in the future. When banks underestimate interest rate risks or have limited liability to depositors in the event of default, capping held-to-maturity long-term assets and mandating more equity capital issuance may reduce the run risks of moderately capitalized banks. Using bank-quarter-level data from Call Reports, we provide empirical support for the model’s testable implications.

A unique natural experiment in China – the city-level staggered introduction of admin-istrative approval centers (AAC) – reduces bank loan processing times by substantially speeding up the process of registering collateral without affecting credit decisions. Fol-lowing the establishment of an AAC, firms significantly reduce their cash holdings. State-owned enterprises are less affected. Cash flow sensitivity of cash holdings de-creases, as does the cash flow sensitivity of investment. The share of short-term debt increases, while inventory holdings and reliance on trade credit decrease. Defaults also decrease. These results suggest that timely access to credit has important implications on firms’ financial management.

This paper revisits the default-crash risk relation in the context of China. We find that firms with higher default risk have lower stock price crash risk both in monthly and yearly frequencies. To identify the causal effect, we use the first-ever default event in China’s onshore bond market in 2014 as an exogenous shock to the strength of implicit guarantees. The negative relation arises from the active involvement of the government before 2014 and creditors after 2014 in corporate governance. Consistent with the external scrutiny mechanism, the impact of default risk on stock price crashes is stronger in situations in which creditors are more likely to engage in active monitoring (i.e., firms with higher liquidation costs, lower liquidation value, and higher levels of information asymmetry), with these effects primarily observed in the post-2014 period. Overall, our study highlights the role of the “invisible hand” in the absence of the “visible hand.”

This paper examines how the integration of artificial intelligence (AI) and big data affects banking operations, emphasizing the crucial role of big data in unlocking the full potential of AI. Leveraging a comprehensive dataset of over 4.5 million loans issued by a leading commercial bank in China and exploiting a policy mandate as an exogenous shock, we document significant improvements in credit rating accuracy and loan performance, particularly for SMEs. Specifically, the adoption of AI and big data reduces the rate of unclassified credit ratings by 40.1% and decreases loan default rates by 29.6%. Analyzing the bank's phased implementation, we find that integrating big data analytics substantially enhances the effectiveness of AI models. We further identify significant heterogeneity: improvements are especially pronounced for unsecured and short-term loans, borrowers with incomplete financial records, first-time borrowers, long-distance borrowers, and firms located in economically underdeveloped or linguistically diverse regions. Our findings underscore the powerful synergy between big data and AI, demonstrating their joint capability to alleviate information frictions and enhance credit allocation efficiency.

We conceptually identify and empirically verify the features distinguishing FinTech platforms from non-financial platforms using marketplace lending data. Specifically, we highlight three key features: (i) Long-term contracts introducing default risk at both the individual and platform levels; (ii) Lenders’ investment diversification to mitigate individual default risk; (iii) Platform-level default risk leading to greater asymmetric user stickiness and rendering platform-level cross-side network effects (p-CNEs), a novel metric we introduce, crucial for adoption and market dynamics. We incorporate these features into a model of two-sided FinTech platform with potential failures and endogenous participation and fee structures. Our model predicts lenders’ single-homing, occasional lower fees for borrowers, asymmetric p-CNEs, and the predictive power of lenders’ p-CNEs in forecasting platform failures. Empirical evidence from China’s marketplace lending industry, characterized by frequent market entries, exits, and strong network externalities, corroborates our theoretical predictions. We find that lenders’ p-CNEs are systematically lower on declining or well-established platforms compared to those on emerging or rapidly growing platforms. Furthermore, lenders’ p-CNEs serve as an early indicator of platform survival likelihood, even at the initial stages of market development. Our findings provide novel economic insights into the functioning of multi-sided FinTech platforms, offering valuable implications for both industry practitioners and financial regulators.

We provide a novel explanation for the geographic dispersion of borrower-lender relationships based on information frictions rather than competition. Firms may strategically select distant banks to increase lenders’ information production costs, securing larger loans under information-insensitive contracts. Our model predicts that higher-quality firms prefer distant lenders for information-insensitive contracts, while lower-quality firms use local lenders with information-sensitive terms. Using transaction-level data from a major Chinese bank, we find strong empirical support: higher-rated firms exhibit greater propensity for distant borrowing; local loans show stronger negative correlation between amounts and interest rates; and distant loan pricing demonstrates weaker sensitivity to defaults.

Recently, the Chinese Government has strengthened the enforcement of bankruptcy laws to protect creditors’ rights. This study shed light on the effect of creditor protection on asset-debt maturity mismatch by employing a quasi-natural experiment in China. The results show that creditor protection mitigates maturity mismatch, and the effect is more pronounced among financially constrained firms. Results remain robust after the dynamic effects test, placebo test, propensity score matching approach, entropy balancing method, and controlling for COVID-19 shocks. Mechanism tests show that creditor protection decreases the cost of debt and reduces over-investment. The effect of creditor protection is pronounced in private companies, financially independent companies, and companies with secured loans. Creditor rights can alleviate maturity mismatch in firms with medium ownership concentration and managerial ownership levels. Economic consequences studies suggest that creditor protection reduces corporate default risk. This study reveals the mechanism and effect of creditor protection on asset-debt maturity mismatch in emerging markets, providing recommendations to policymakers for assessing and improving bankruptcy law regimes.

“How does a firm’s bankruptcy affect its regional environment?” is an open empirical question that has received little attention in the literature. We hypothesize that because enterprises provide funds to protect their regional environment, their default risk negatively impacts that environment. We analyze the impact of corporate default risk on environmental deterioration in the international setting to answer this question. Using a firm-level corporate default risk quarterly data from 2013q1 to 2020q4, we find that corporate default risk is positively associated with CO2 emissions and decomposed components. These findings are reliable in low-income and highly uncertain countries but weak in countries having more market competition. We also find that the negative impact of corporate default risk on the environment is more robust in countries with more population density and fewer forest area thresholds. Finally, using the instrumental variable approach, we provide preliminary evidence that firm-level political risk (for US and Canadian firms only) increases corporate default risk, leading to a degrading environment. Our findings are robust to alternative measurements of a firm’s default risk and environmental deterioration. Our research will help environmental authorities to consider corporate default risk as a determinant when formulating environmental-related strategies.

This study examines how firm-level exposure to the COVID-19 pandemic affects the speed of leverage adjustment among 3260 US-listed firms from 2019q1 to 2022q1. Using a novel measure of COVID-19 exposure, we find that higher exposure significantly reduces the speed at which firms adjust their leverage towards target levels. This effect is more pronounced for financially constrained firms and those operating in competitive markets. We further show that COVID-19 exposure adversely impacts corporate liquidity, default risk, and financial flexibility. Our findings highlight the role of exogenous shocks in shaping corporate financing decisions.

Using a large sample of US individuals, we show that individuals with higher levels of trust have lower likelihoods of default in household debt and higher net worth. The effect is driven by trust values inherited from cultural and family backgrounds more than by trust beliefs about others. We demonstrate a causal impact of trust on financial outcomes by extracting the component of trust correlated with early-life ex- periences. The effect of trust is more pronounced among females, those with lower education, lower income, lower financial literacy, and higher debt-to-income ratio. Further evidence suggests that enhancing individuals’ trust, to the right amount, can improve household financial well-being.