AI and Big Data for Systemic Financial Stability: How Predictive Analytics Can Detect Systemic Risks in Banking Systems

Abstract

Artificial intelligence (AI) and Big Data have lately emerged as extremely effective in enhancing systemic financial stability through predictive analytics that can forewarn on upcoming risks before things get worse. By combining state-of-the-art machine learning algorithms with a larger amount of financial databases, banks and regulatory bodies are more accurate in sensing early warning signs, credit risk, and also tracking systemic vulnerabilities. Not only do these breakthroughs enhance risk management performances, but they also help to form proactive decision-making models that cushion the financial markets against crisis situations. This paper discusses the potential role and opportunities of AI and Big Data in the identification of systemic financial risk, with examples of the applications and challenges, as well as points on how it could be used in the future banking system, where resilience is systemic.