Systemic Risk Measures and Machine Learning Algorithms in Islamic and Conventional Financial Institutions

Abstract

Due to global economic volatility, financial institution risk management has become a major concern since risk expands due to the inherent interconnectedness within the sector, impacting stability and credit supply. Using machine learning as a forecasting instrument, the study examined systemic risk in GCC and ASEAN in Islamic and conventional financial institutions. The study highlighted machine learning's potential to forecast outcomes accurately; and how to adjust regulatory policies to mitigate systemic events.