We study the broad question about the sources of FinTech lending growth by examining a specific representative product for which the technologies of both FinTech and the incumbent competitors can be identified and compared—small business lending. We test whether the presence of incumbents employing different technologies affects FinTech penetration, and find more FinTech lending where large/out-of-market banks are more prevalent. Using stress test exposures and Community Reinvestment Act examinations as instruments, we find that FinTech credit more often substitutes for loans by large/out-of-market banks than small/in-market banks. Results are consistent with FinTech advantages in processing hard information, rather than hardening soft information

This paper investigates the impact of introducing junior unsecured loans (i.e., FinTech loans) into the small business lending market. Using French administrative data, we find that firms experience a 13% increase in bank credit after receiving a FinTech loan. We use propensity score matching procedures and a shift-share instrument to account for credit demand. The credit increase only occurs when FinTech borrowers invest in new assets, and Fintech borrowers are subsequently more likely to pledge collateral to banks. This suggests that firms use FinTech loans to acquire assets that they then pledge to banks, thereby increasing total borrowing capacity

Borrowers' use of cashless payments improves their access to capital from FinTech lenders and predicts a lower probability of default. These relationships are stronger for cashless technologies providing more precise information, and for outflows. Cashless payment usage complements other signals of borrower quality. We rationalize these empirical findings using a framework in which borrowers signal their lower likelihood of diverting cash flows through payment technology choice, and screening accuracy is further strengthened by informational complementarities. The informational synergy we uncover provides a rationale for the joint rise of cashless payments and FinTech lending, as well as for open banking

We present results from a field experiment that introduced digital payroll accounts to unbanked factory workers to examine how inexperienced consumers learn to use a new financial technology. We find that exposure to payroll accounts leads to increased account use, accelerated learning, and avoidance of common consumer protection risks. Those receiving electronic wage payments gradually build trust in the technology, learn to use accounts without assistance, and avoid illicit fees. Using experimental variation in assignment to bank versus mobile money accounts, we show that these impacts are concentrated in mobile money accounts, the newer, more complex, and less trusted financial technology

We study the nature and effects of cultural biases in choice under risk and uncertainty by comparing peer-to-peer loans the same individuals ( lenders ) make alone and after observing robo-advised suggestions. When unassisted, lenders are more likely to choose co-ethnic borrowers, facing 8% higher defaults and 7.3pp lower returns. Robo-advising does not affect diversification but reduces lending to high-risk co-ethnic borrowers. Lenders in locations with high inter-ethnic animus drive the results, even when borrowers reside elsewhere. Biased beliefs explain these results better than a conscious taste for discrimination: lenders rarely override robo-advised matches to ethnicities they discriminated against when unassisted.

We study gender differences in on-time loan payment responsiveness to collection mechanisms using randomized dunning text messages sent to 17,545 FinTech borrowers. Reminder text messages significantly reduce delinquency rates relative to a no-message control, with messages incorporating social or financial incentives proving more effective. Women are more responsive to social pressure, while men are more sensitive to financial incentives. These results are robust to observable control variables and matching methods. Channel analyses indicate that gender differences in responsiveness to the existence and size of the incentive explain the observed gender differences under the social incentive treatment. However, only gender differences in sensitivity to the existence of incentives explain the gender difference in financial incentive treatments. These findings inform practitioners and policymakers that some seemingly gender-neutral practices may create unintended gender disparities in financial markets

Fraud indicators within the Paycheck Protection Program (PPP), a major COVID relief program, are highly geographically concentrated. ZIP codes and counties with high rates of suspicious PPP loans are strongly socially connected, with evidence that fraud spreads spatially over time through social networks. Individuals in suspicious social media groups have higher rates of PPP fraud, and socially connected ZIP codes frequently use the same specific FinTech lenders, consistent with social networks influencing detailed loan decisions. Our findings suggest that more proactive data analysis is needed for fraud prevention, detection, and prosecution to prevent the social spread of fraudulent schemes

An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.