Credit Risk Management Can Gear Up Bank Performance – Moderating Effect of Interest Rate in Developed Countries

Abstract

This research explores the role of interest rate as a moderator in credit risk management, influencing the performance of banking industry in selected developed countries using a two-step GMM model. The annual data of the top 10 banks of the selected 10 developed countries ranging from 2001 to 2020 was used. The developed countries or G-10 are Belgium, Canada, France, Germany, Italy, Japan, Sweden, Switzerland, the United Kingdom, and the United States, which are the originators of the Basel Accords. Bank performance, proxied by ROA, ROE, ATO, and NPM, is dependent. Interest rate is a moderator, independent and indexed, developed after netting off lending interest rate (LIR), interest rate spread (IRS) & net interest margin (NIM). The credit risk management index (CRM index) was derived after netting off the effects of extra ordinary financing of net loans and leases, negativity of nonperforming loans, and secured cushioning of risk-weighted assets. The results confirmed that CRM improves the growth of banking, especially in case of ROA, ROE, and NPM, improves more by the induction of the moderator of the interest rate index and enhances more with the induction of the interaction. This research guides for rearranging the determinants of CRM, identifying loopholes of CRM, fixing interest rates, and looking after natural fixation of interest rate. CRM policies should be stringent, security analysis must be centralized, offered interest rate must be natural and savings must be used in a productive usage rather than multiple financing at lower interest rates. The research contributed two indexes, the CRM index and the interest rate index (IR index), which were developed by NPLs, NLLs, RWAs and LIR, IRS, and NIM, respectively. The results highlighted that loanable fund theory is starving without remedial measures of CRM for leakage of “credit”, drainage of “capital” or seepage of “money”. The researcher selected ten developed countries with the 10 highest scoring banks in a period of 2001-2020 and used a two-stage GMM technique.