Credit risk management in bank: Impacts of IFRS 9 and Basel 3

Abstract

The expected loss approach (ECL) defined by IFRS 9 replaced the old incurred loss approach (IAS 39) in the international accounting standard setter. In Europe, the IFRS 9 are accompanied by new regulatory frameworks (BCBS), opinion, technical standards (EBA) which do not always provide the same methodological and operational implications of the accounting standard setter. Many aspects of IFRS 9 have been studied, but this paper analyzes its interdependencies and overlaps with the credit risk framework for financial intermediaries (also Basel 3). Using a case study, the purpose of this paper is to investigate the ECL, its main impacts on coverage ratio of a loan’s portfolio. The main findings are: usually, the rules laid down for Stage 1 of IFRS 9 do not reduce the excess coverage produced on a portfolio in bonis; in the presence of impaired loans IAS 39 generates a lack of funds; the lifetime ECL (Stage 2 of IFRS 9) imposes excess of provisions because it does not consider the effect of coverage produced by expected premiums; for loan portfolios with short repayment times, the excess of provisions produced by IFRS 9 compensates the lack of coverage of the capital requirement. From the academic research perspective, this paper contributes to the literature on ECL model in several ways. First, it adds knowledge to the research on the relationship between Credit Risk Management framework and accounting standard IFRS 9. Second, it also links our findings related to ECL approach with potential implications for the financial sector, policymakers and regulators.

Impact of COVID-19 in Policy Implementation on Third Party Funds Case Study: Banking in Makassar City, Indonesia

“…Based on the paired sample statistical test results in table 8 that there are significant differences for capital quality (CAR), asset quality (NPL), management quality (NPM), profit quality (ROA, ROE and BOPO), liquidity quality (LDR), risk sensitivity market (IER) and quality of third party funds (Saving Account/SA, Current Account/CA and Time Deposit/TD) on the average number and standard deviation of the banking sector before and during the covid 19 pandemic. These findings are comparable to research conducted by Porretta et al (2020 ) which explains that third party funds are funds originating from the community in making demand deposits, loans or other transactions which are then redistributed for the welfare of the community. Third party funds from the public are very important in banks because the dominant bank has funds from third party funds.…”

“…In addition, with the existence of third party funds, the function of banking as an institution of trust and an intermediary function that collects funding from the public, and distributes it to the public, in the form of loans can be realized. Meanwhile, Porretta et al (2020) explains that the credit risk management process in the banking sector must know the regulatory system framework, and accounting, before making a plan, which is useful for policy makers (Porretta et al 2020…”

Sensitivities-based method and expected shortfall for market risk under FRTB: its impact on options risk capital

“…Therefore, the described situation approximates possible impacts via SbM; in particular, the calculations show a high risk capital associated with SA. The estimations also reflect an effort to build relationships with IMA ES, consistent with the analysis proposed by Orgeldinger (2018) and Porretta and Agnese (2021). Also, the above implications for emerging economies' risk capital complement the studies of Majumder andLi (2018) andValerio Roncagliolo andVillamonte Blas (2022).…”

“…They report a more significant impact on banks adopting SA. In turn, Porretta and Agnese (2021) examine FRTB impacts on capital the requirement for different banking groups, classified according to their tier-1 capital size. They analyse risk capital changes from the current to the revised regulation and for both approaches, SA and IMA.…”

“…However, under FRTB, logical reasonings should be put forward to support possible SbM implementations for a general portfolio. Logical reasonings respond to the requirement of building quantitative relations between SA-SbM and IMA-ES, as well as measuring risk capital impacts via SbM (Orgeldinger (2018) and Porretta and Agnese (2021)). Additionally, ES metric's statistical performance and risk capital impacts should be investigated, particularly for financial options portfolios.…”