Measuring the impact of enterprise risk management on performance, value, and risk indicators of Borsa Istanbul XBANK companies with data mining prediction models

Abstract

Risk management (RM) is viewed by organizations from a holistic perspective instead of a silo-based point of view and a change in basic assumptions has occurred in recent years. The comprehensive approach to RM that is developed based on a holistic perspective and is adopted by companies is called enterprise risk management (ERM). From the general point of view, it is expected that companies will have sustainable operations, improved performance and value, and controlled risks by using the ERM concept. In this article, the relations of ERM adaptation with firm performance, firm value, and risks were researched through ordinal variables such as the implementation level of ERM and the sophistication level of the organizational structure of ERM in regression models based on panel data (PD). Empirical evidence depending on a sample of ten banking companies listed on the Borsa Istanbul (BIST) Banks index (XBANK) for the period from 2019 to 2022 confirms the above basic argument for firm performance, firm value, and the insolvency risk of banks in general terms. In addition, the prediction accuracy of PD models is calculated for the performance, value, and risk indicators of banks, and the partial least squares regression model is proposed as the alternative prediction model of data mining.