Discretionary loan loss provision behavior in the US banking industry

Abstract

Earnings management can be either opportunistic, adding noise to reported earnings, or informative about a firm's underlying economic performance, adding valuable information to financial reports. This study examines earnings management in banks with differing levels of information asymmetry. Specifically, we compare earnings management between public and private banks by using discretionary loan-loss provisions (DLLPs) as proxies. Employing a large dataset of US public and private banks from 1986:Q1 to 2013:Q4, this study provides evidence of stronger earnings management behavior in public banks versus private banks. The evidence remains robust under a battery of sensitivity tests. Since incentives for earnings management are more relevant within a specific context, we identify the conditions that motivate different earnings management incentives, which allows us to better observe specific managerial motives. Greater DLLPs observed in public banks are utilized to send private information to investors, consistent with the signaling hypothesis. We also find evidence that capital requirements alter DLLPs, consistent with the capital management hypothesis. Banks with relatively low (high) earnings tend to decrease (increase) their earnings through manipulation of DLLPs, inconsistent with our income-smoothing hypothesis. The study extends to current debates on earnings management between public and private firms, and also provides a better understanding of the determinants of earnings management.

Banking sector earnings management using loan loss provisions in the Fintech era

“…Aristei and Gallo (2019) show that banks facing increasing levels of risk had higher LLPs and also engaged in earnings management practices to stabilise their earnings over time. Tran et al (2019) find evidence of greater earnings management in public banks than private banks. Balla and Rose (2015) investigate whether the tightening of accounting constraints associated with the Securities and Exchange Commission (SEC)'s 1998 SunTrust decision affected the relationship between earnings and loan loss provisioning for US banks.…”

What drives bank income smoothing? Evidence from Africa

“…Income smoothing is a type of earnings management. Existing studies such as Tran et al (2020) show that US banks use discretionary loan loss provisions to manage earnings or to smooth income. Ozili (2017a) examined income smoothing using loan loss provisions by Western European banks and found that Western European banks use loan loss provisions to smooth income in the post-financial crisis period.…”

Examining Managerial Misbehavior in Asian Banks through Loan Loss Provisions*☆

“…Hence, it is expected that the conflict between managers and shareholders could mutate into a conflict between the controlling shareholder and minority shareholders, also known as Type II agency conflict. As described by Tran et al (2020), owners with smaller stakes in a firm are more likely to adopt rational apathy because they bear most of the costs of monitoring (e.g., costs of storing, retrieving, and processing information) while receiving a limited share of gains from monitoring. Hence, these shareholders are more likely to use simple low-cost heuristics such as earnings-based benchmarks to assess banks' performance, which leads to greater incentives for bank managers to manipulate earnings for the appearance of better performance.…”

“…First, to the best of our knowledge, discretionary managerial behavior in the Asian banking sector has not yet been widely studied (Sarkar et al, 2008). Only a few studies have focused on single-country samples (Barth et al, 1999;Healy and Wahlen, 1999;Park and Shin, 2004;Sarkar et al, 2008), but most of these studies are centered on developed markets (Cornett et al, 2009;Leventis and Dimitropoulos, 2012;Tran et al, 2020), and only a few deal with the Asian region (Aguilera and Crespi-Cladera, 2016;Andres and Vallelado, 2008;Claessens and Yurtoglu, 2013;Tan, 2014), with the subsequent downside of weak extrapolation to a wider institutional context. Consequently, we intend to close this gap in the empirical literature by considering a comprehensive multi-country sample from the unexplored Asian banking industry.…”