Banks may be unable to refinance short-term liabilities in case of solvency concerns. To manage this risk, banks can accumulate a buffer of liquid assets, or strengthen transparency to communicate solvency. While a liquidity buffer provides complete insurance against small shocks, transparency covers also large shocks but imperfectly. Due to leverage, an unregulated bank may choose insufficient liquidity buffers and transparency. The regulatory response is constrained: while liquidity buffers can be imposed, transparency is not verifiable. Moreover, liquidity requirements can compromise banks’ transparency choices, and increase refinancing risk. To be effective, liquidity requirements should be complemented by measures that increase bank incentives to adopt transparency.

Banks can make suboptimal liquidity choices and gamble for lender of last resort (LOLR) support. Endogenous bailout rents are driven by the need to preserve bankers' incentives under uncertain net worth. In equilibrium, banks can herd in risk management, choosing suboptimal liquidity when they expect others to do so. Optimal liquidity can be restored by quantitative requirements, but such regulation is costly. An LOLR policy incorporating bank capital information can reduce distorting rents and allow for a more efficient solution, but may only be possible in transparent economies.

Banks increasingly use short-term wholesale funds to supplement traditional retail deposits. Existing literature mainly points to the “bright side” of wholesale funding: sophisticated financiers can monitor banks, disciplining bad but refinancing good ones. This paper models a “dark side” of wholesale funding. In an environment with a costless but noisy public signal on bank project quality, short-term wholesale financiers have lower incentives to conduct costly monitoring, and instead may withdraw based on negative public signals, triggering inefficient liquidations. Comparative statics suggest that such distortions of incentives are smaller when public signals are less relevant and project liquidation costs are higher, e.g., when banks hold mostly relationship-based small business loans.

Traditional theory suggests that higher bank profitability (or franchise value) dissuades bank risk-taking. We highlight an opposite effect: higher profitability loosens bank borrowing constraints. This enables profitable banks to take risk on a larger scale, inducing risk-taking. This effect is more pronounced when bank leverage constraints are looser, or when new investments can be financed with senior funding (such as repos). The model’s predictions are consistent with some notable cross-sectional patterns of bank risk-taking in the run-up to the 2008 crisis.

We revisit the link between bailouts and bank risk taking. Bailout expectations create moral hazard – increase bank risk taking. However, when an individual bank’s success depends on both its effort and the overall stability of the banking system, bailouts that shield banks from contagion may increase their incentives to invest prudently and so reduce bank risk taking. This systemic insurance effect is more important when bailout rents are low while contagion risk is high. The optimal policy is then to make bailouts not difficult, but “effective” : associated with lower rents. We further show that, besides better bank resolution, a powerful means to reduce bailout rents is higher ex ante bank capital, since it implies a larger bank equity cushion that can be expropriated in a resolution. This highlights an important complementarity between bank capital regulation and bailouts as tools to enhance financial stability.

We study the interaction between relationship banking and short-term arm’s length activities of banks, called trading. We show that a bank can use the franchise value of its relationships to expand the scale of trading, but may allocate too much capital to trading ex post, compromising its ability to build relationships ex ante. This effect is reinforced when trading is used for risk shifting. Overall, combining relationship banking and trading offers benefits under small-scale trading, but distortions may dominate when trading is unbridled. This suggests that trading by banks, while benign historically, might be distortive with deeper financial markets.

We study the composition of bank loan portfolios during the transition of the real sector to a knowledge economy where firms increasingly use intangible capital. Exploiting heterogeneity in bank exposure to the compositional shift from tangible to intangible capital, we show that exposed banks curtail commercial lending and reallocate lending to other assets, such as mortgages. We estimate that the substantial growth in intangible capital since the mid-1980s explains around 30% of the secular decline in the share of commercial lending in banks’ loan portfolios. We provide suggestive evidence that this reallocation increased the riskiness of banks’ mortgage lending.

We present a new dataset on the dynamics of non-performing loans (NPLs) during 92 banking crises since 1990. The data show similarities across crises in NPL buildup but much heterogeneity in the pace of NPL resolution. We document how high and unresolved NPLs deepen post-crisis recessions and use a machine learning approach to establish pre-crisis predictors of NPL problems. These predictors—a set of weak macroeconomic, institutional, corporate, and banking sector conditions—help shed light on post-COVID-19 NPL vulnerabilities.

This paper studies the significant variation in the cross-section of standalone and systemic risk of large banks during the recent financial crisis to identify bank specific factors that determine risk. We find that systemic risk grows with bank size and is inversely related to bank capital, and this effect exists above and beyond the effect of bank size and capital on standalone bank risk. Our results contribute to the ongoing debate on the merits of imposing systemic risk-based capital requirements on banks.

We study the effects of technological change on financial intermediation, distinguishing between innovations in information (data collection and processing) and communication (relationships and distribution). Both follow historical trends towards an increased use of hard information and less in-person interaction, which are accelerating rapidly. We evaluate more recent innovations, such as the combination of data abundance and artificial intelligence, and the rise of digital platforms. We argue that the rise of new communication channels can lead to the vertical and horizontal disintegration of the traditional bank business model. Specialized providers of financial services can chip away activities that do not rely on access to balance sheets, while platforms can interject themselves between banks and customers. We discuss limitations to these challenges to the traditional bank business model, and the resulting policy implications.