US credit unions have been subject to a strict regulation of their commercial lending which included both requirements for enhanced organizational practices and a cap on the proportion of business loans relative to assets (imposed in 1998 by US Congress). Since 2003, however, these limitations have been steadily relaxed, a process which has resulted in an increase in credit union business lending activity. Using data from the universe of US credit unions we provide comprehensive evidence that expansion of the business loan portfolio increases the risk of the asset side of the credit union. This is the case even for credit unions which benefit from partnership with the SBA, for which we observe an initial increase in the risk of non-SBA backed loans (an overconfidence effect) which reverses over time (a learning effect). Our results suggest, furthermore, that the risk of business loans is exacerbated for credit unions which initiate their business loan activity and which do so rapidly. In the second part of our analysis we provide descriptive and quasi-experimental evidence that expansions of credit union activity into business loans are associated with lower subsequent growth rates of deposits. This result is similar to the reaction to risk indicators found in the banking literature and might give an ex-ante incentive for the CU that could work as a market-based stabilization mechanism complementary to that of explicit regulation.

This paper empirically characterizes relationship lending using data from more than 20,000 loans of a Spanish bank to small and medium enterprises (SMEs). The study analyzes the pricing determinants of loans to firms based on the entire previous bank–firm relationship, allowing for the identification of nonlinear pricing patterns in the bank–firm relationship. We show that firms only start capitalizing the gains of relationship lending when the relationship extends beyond two years. This reduction in the loan rate spread charged is driven by the opaque firms, for which the acquisition of “soft” information is especially relevant. Finally, we find that relationship lending significantly mitigates the increased costs of refinancing loans along two dimensions: relationship duration and having additional contracts—other than loans—with the bank.

This paper provides early evidence on the effect of global regulation mandating a switch from loan loss provisioning (LLP) based on incurred credit losses (ICLs) to LLP based on expected credit losses (ECLs). Using a sample of systemically important banks from 74 countries, we find that ECL provisions are more predictive of future bank risk than ICL provisions. Corroborating that the switch to ECL provisioning results in more information to assess bank risk, we also observe that the announcement of a larger first‐time impact of the accounting change elicits lower stock returns and higher changes in credit default swap spreads. Critically, these patterns are most pronounced when credit conditions deteriorate. Additional analyses show that the higher information content of the ECL model stems from the provisions for nondefaulted loans, which did not exist under ICL. Our study contributes to the debate on the effect of the ECL model on procyclicality, an especially pressing issue in the context of the current pandemic.

We analyze a sample of large international banks in major advanced economies and examine the impact that bank-specific factors have on an institution's solvency risk and its contribution to systemic risk. We focus on the five categories that the Basel Committee on Banking Supervision has recently proposed as indicators of systemic importance. Our findings suggest that unstable funding is the main factor driving systemic risk. Furthermore, the combination of significant trading activities with global presence appears to exacerbate spillover risks to the global financial system. Interestingly, whereas trading activities contribute to the build-up of correlated or ‘wrong-way’ risk they help to mitigate individual solvency risk. Conversely, a decentralized approach to liquidity management seems to alleviate individual solvency risk but amplifies the transmission of financial distress across the financial system. This suggests that a macro-prudential approach to financial regulation should focus not only on scaling up micro-prudential measures but also on enabling the efficient transfer of risk between financial institutions.

Several studies have analyzed discretionary accruals to address earnings-smoothing behaviors in the banking industry. We argue that the characteristic link between accruals and earnings may be nonlinear, since both the incentives to manipulate income and the practical way to do so depend partially on the relative size of earnings. Given a sample of 15,268 US banks over the period 1996–2011, the main results in this paper suggest that, depending on the size of earnings, bank managers tend to engage in earnings-decreasing strategies when earnings are negative (“big-bath”), use earnings-increasing strategies when earnings are positive, and use provisions as a smoothing device when earnings are positive and substantial (“cookie-jar” accounting). This evidence, which cannot be explained by the earnings-smoothing hypothesis, is consistent with the compensation theory. Neglecting nonlinear patterns in the econometric modeling of these accruals may lead to misleading conclusions regarding the characteristic strategies used in earnings management.

To date, an operational measure of systemic risk capturing nonlinear tail-comovements between system-wide and individual bank returns has not yet been developed. This paper proposes an extension of the CoVaR methodology in Adrian and Brunnermeier (2011) to capture the asymmetric response of the banking system to positive and negative shocks to the market-valued balance sheets of individual banks. Building on a comprehensive sample of U.S. banks in the period 1990–2010, the evidence in this paper shows that ignoring asymmetries that feature tail-interdependences may lead to a severe underestimation of systemic risk. On average, the relative impact on the system of a fall in individual market value is sevenfold that of an increase. Moreover, the downward bias in systemic-risk measuring from ignoring this asymmetric pattern increases with bank size. In particular, the conditional tail-comovement between the banking system and a bank that is losing market value belonging to the top size-sorted decile is nearly 5.5 times larger than the unconditional tail-comovement versus 3.3 times for banks in the bottom decile. The asymmetric model also produces much better fitting, with the restriction that gives rise to the standard symmetric model being rejected for most firms in the sample, particularly, in the segment of large-scale banks. This result is important from a regulatory and supervisory perspective, since the asymmetric generalization enhances the capacity to monitor systemic interdependences.

We use the CoVaR approach to identify the main factors behind systemic risk in a set of large international banks. We find that short-term wholesale funding is a key determinant in triggering systemic risk episodes. In contrast, we find weaker evidence that either size or leverage contributes to systemic risk within the class of large international banks. We also show that asymmetries based on the sign of bank returns play an important role in capturing the sensitivity of system-wide risk to individual bank returns. Since short-term wholesale funding emerges as the most relevant systemic factor, our results support the Basel Committee’s proposal to introduce a net stable funding ratio, penalizing excessive exposure to liquidity risk.