Firms are increasingly collecting and analyzing data from a wide range of sources. How do these data affect the interaction between firms and financial markets?

Using the staggered adoption of data technologies on firms’ websites, we show that customers’ data partially substitutes for the information that managers learn from financial markets. Data availability improves managers’ internal information about future product demand and reduces firms’ reliance on stock prices for investment decisions by about one half. The effect is consistent with data technologies replacing the informational role of stock prices. This “replacement effect” is robust to alternative explanations and reverses back under data-privacy restrictions. Our findings suggest that the diffusion of data technologies weakens the informational role of financial markets in guiding real investment decisions.

How does online bank expansion (digital-only depository institutions that originate loans without human intermediation) affect consumer credit markets? Using loan-level data from Germany, we show that online banks cherry-pick low-risk borrowers, generating adverse selection on traditional banks. We document three facts. First, the market is segmented across lender types. Online banks serve the lowest-risk borrowers, traditional banks the medium-risk segment, and fintechs the highest-risk segment. Second, online banks attract these borrowers by offering substantially lower rates, an advantage that diminishes with risk. Using historical branch density as an instrument, we isolate the supply-side mechanism of this pattern. Third, traditional banks more exposed to online bank expansion experience a deterioration in their borrower pool and charge higher rates as a result. A parsimonious model with lenders who observe the same application information but use it differently rationalizes these facts. Traditional banks use coarse pricing, a legacy of costly manual underwriting for a standardized product, while online banks use finer pricing and cherry-pick the best borrowers from within traditional banks' pricing cells. Our findings highlight that technological development in credit markets can generate important distributional consequences.

This paper studies the consequences of privacy regulation by exploiting Google’s 2019 data-access restriction. We document a key trade-off: stronger privacy protections increase loan applications, suggesting higher demand, but lead to tighter screening and reduced credit supply. This contraction disproportionately excludes economically and socially marginalized applicants. Using bureau records, we quantify the "FinTech ladder effect,'" whereby early digital credit access enables long-term borrowing. Privacy-driven rejections lower the likelihood of obtaining credit by 13.7 percentage-points even after four years. A structural model decomposes the welfare effects and shows that regulation raises consumer surplus by 0.23-0.60% but reduces lender profits by 20-23%.