How does information sharing affect consumers' usage of FinTech credit? Using a unique dataset of ``Buy Now, Pay Later (BNPL)" users from a large digital platform and exploiting a credit reporting policy change, we document that consumers significantly reduce their usage of BNPL credit when the BNPL lender becomes subject to credit reporting regulation. This reduction is more pronounced among borrowers with previous default records, who also become more disciplined in repayment behaviors, than those without such records. The decrease in BNPL usage also leads to a reduction in online consumption, supporting the financial constraint hypothesis. Our results suggest that information sharing can help alleviate overborrowing and overspending, with stronger effects observed among younger borrowers, those who previously consumed more, or those with credit cards. We also highlight the synergies between BNPL lending and Big Tech platforms' ecosystems, which imperfectly substitute for formal enforcement institutions.

The past decade has witnessed a phenomenal rise of digital wallets, and the COVID-19 pandemic further accelerated their adoption globally. Such e-wallets provide not only a conduit to external bank accounts but also internal payment options, including the ever-popular Buy-Now-Pay-Later (BNPL). We examine, for the first time, e-wallet transactions matched with merchant and consumer information from a world-leading provider based in China, with around one billion users globally and a business model that other e-wallet providers quickly converge to. We document that internal payment options, especially BNPL, dominate both online and on-site transactions. BNPL has greatly expanded credit access at the extensive margin through its adoption in two-sided payment markets. While BNPL crowds out other e-wallet payment options, it expands FinTech credit to underserved consumers. Exploiting a randomized experiment, we also find that e-wallet credit through BNPL substantially boosts consumer spending. Nevertheless, users, especially those relying on e-wallets as their sole credit source, carefully moderate borrowing when incurring interest charges. The insights likely prove informative for economies transitioning from cash-heavy to cashless societies where digital payments and FinTech credit see the largest growth and market potential.

We conduct a within-county analysis using detailed zip code level data to document new findings regarding the origins of the biggest financial crisis since the Great Depression. The recent sharp increase in mortgage defaults is significantly amplified in subprime zip codes that experience an unprecedented relative growth in mortgage credit from 2002 to 2005. This expansion in mortgage credit to subprime zip codes occurs despite sharply declining relative (and in some cases absolute) income growth in these neighborhoods. In fact, 2002 to 2005 is the only period in the last 18 years when income and mortgage credit growth are negatively correlated. We show that the expansion in mortgage credit to subprime zip codes and its dissociation from income growth is closely correlated with the increase in securitization of subprime mortgages. Finally, we show that all of our key findings hold in markets with very elastic housing supply that have low house price growth during the credit expansion years. Overall, our findings favor a supply-based explanation for credit expansion over income-based or house price expectations-based hypotheses.