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

Abstract

PurposeThis paper analyzes banking sector earnings management using loan loss provisions (LLPs) in the Fintech era.Design/methodology/approachRegression methodology was used to examine earnings management in the Fintech era.FindingsThe findings show evidence for bank income smoothing using LLPs. There is greater income smoothing in the second-wave Fintech era compared to the first-wave Fintech era, and the presence of strong institutions did not lower income smoothing in the second-wave era. Bank income smoothing is also greater in (1) Bank of International Settlement (BIS) and EU countries than in non-EU countries and G7 countries, (2) well-capitalized banking sectors and (3) during economic booms in the second-wave Fintech era.Practical implicationsThe competition for loans and deposits by banks and Fintech lenders in the second-wave Fintech era created additional incentives for banks to engage in income smoothing to report competitive and stable earnings.Originality/valueThe study uses a unique approach to detect country-level earnings management in the banking sector. Also, this study extends the bank earnings management literature by introducing the Fintech era as a determinant of the extent of bank earnings management.

Determinants of bank income smoothing using loan loss provisions in the United Kingdom

“…Previous studies, such as Ozili and Outa (2017), Peterson and Arun (2018) and Delis et al (2017), used the nonperforming loan variable to control for the effect of loan default on bank provisions. These studies show that banks that expect high nonperforming loans will keep higher LLP (see Vasilakopoulos et al, 2018;Ozili, 2022), therefore, a positive sign for the NPL coefficient is predicted. This implies a positive relationship between LLP and NPL.…”

“…The loan loss provisions ratio (LLP) is the dependent variable. The "LLP" variable is derived following the approach of Ozili (2022). It is derived by multiplying the nonperforming loan ratio (NPL) data with the loan loss coverage ratio (LLC) data as shown below.…”

“…Previous studies, such as Ozili (2022) and Delis et al (2017), used the Lernex index to control for the impact of bank market power on the size of loan loss provisions. Ozili (2022) and Delis (2017) argue that banks with high market power usually have weak incentives to minimise credit risk. They are more likely to lend to high-risk borrowers (Delis et al, 2017), and such banks are more likely to keep fewer LLPs in order to increase their profit levels which will further reinforce their market power in the banking industry.…”

The Impact of Trust On E-Marketing And Customer Satisfaction In The Commercial Banks Of A Developing Country

“…One of the most important managerial tasks in the corporation is the marketing role which is critical to its performance (Boshoff & Nel, 2021). Until supported by an aggressive marketing campaign that aims to recognise the needs of the consumer and improve the revenue and profits that the institution strives to accomplish, the capacity of any organisation to generate products and provides services is constrained (Ozili, 2020). The evolution of the banks' marketing activity over time has contributed to a shift in the methodology and viewpoint of business management, where this development has gone through several phases and where banking marketing plays a vital role in the banking institution's administrative layout (Floros, Giordani, & Judge, 2014).…”

Does financial inclusion reduce non-performing loans and loan loss provisions?

“…Non-performing loans are important indicators of bank soundness and stability (Nkusu, 2011). Loan loss provision is also an important indicator of bank safety from a prudential regulatory perspective (Ozili, 2021c). Bank supervisors require banks to reduce the size of non-performing loans (Boudriga et al, 2009), and to keep sufficient loan loss provisions to mitigate their credit risk exposure (Ozili, 2017).…”