The Effect of Operational Risk, Credit Risk And Revenue Diversification on Profitability

This study aims to determine the effect of Operational Risk, Credit Risk and Income Diversification on Profitability in banking companies listed on the IDX for the 2016-2020 period.The analytical method used is Panel Data Regression analysis. The results obtained from this study: i) Operational Risk has a positive and significant effect on profitability in banking companies listed on the IDX for the 2016-2020 period. ii) Credit Risk has a negative and significant effect on profitability in banking companies listed on the IDX for the 2016-2020 period. iii) Income Diversification has a negative and significant effect on profitability in banking companies listed on the IDX for the 2016-2020 period. iv) Operational Risk, Credit Risk and Diversification have a positive and significant simultaneously positive and significant effect on Profitability in Banking companies listed on the IDX for the 2016-2020 period.

Estimation of Maximum Potential Losses for Digital Banking Transaction Risks Using the Extreme Value-at-Risks Method

The application of industry 4.0 in banking presents many challenges, with several operational risks related to downtime and timeout services due to system failures. One of the operational risk management steps is to estimate the value of the maximum potential losses. The purpose of this study is to estimate the maximum potential losses for digital banking transaction risks. The method used for estimating risks is the EVaR method. There are several steps in this study. The first step is to resample the data using MEBoot. This process is a simulation of the operational risk loss data of digital banking. Next, the threshold value is determined to obtain the extreme data value. Then, a Kolmogorov–Smirnov test is conducted to fit the data with the GPD. Afterward, the GPD parameter is estimated. Then, EVaR is calculated using a portfolio approach to obtain a combination of risk values as maximum potential losses. The analysis results show that the maximum potential loss is IDR144,357,528,750.94. The research results imply that the banks need to pay attention to the maximum potential losses of digital financial transactions as a reference for risk management. Therefore, banks can anticipate the adequacy of reserve funds for these potential risks.

The Endogeneity Quagmire Empirical Evidence from Telecommunication Industry of Pakistan

Purpose: The current research aims to analyze the particular quagmire of endogeneity by considering panel data with the renowned challenge of limited periods. Design/Methodology/Approach: More specifically, the empirical methodology is applied to a novel sector of Telecommunications in Pakistan by analyzing the possible relationship between Operational Risk and a Telecommunication company’s financial performance. The efficacy of the results is further tested by additional tests of GMM. Operational risk in the study is proxied with three variables. Performance is measured in terms of Returns with respect to Equity holders and Total Assets. From the point of view of management, Asset utilization is also used as a proxy for financial performance. Findings: Results show a presence of a significant and a negative relationship between operational risk and management performance and returns, thereby emphasizing the importance of operational risk management for enhanced performance in light of the theory of performance frontiers introduced by Schmenner and Swink in 1998. Implications/Originality/Value: The results suggest that the focus on operational risk management should be revitalized if the firms seek improved performance and a sustainable competitive advantage.