The Role of Predictive Analytics in Enhancing Financial Decision-Making and Risk Management in Saudi Arabia

Abstract

This study examines how predictive analytics (PA) may improve risk management and financial decision-making in the Kingdom of Saudi Arabia, with a focus on advancements that support the country’s Vision 2030 economic transformation program. As a subset of data analytics and machine learning, predictive analytics helps financial institutions better manage portfolio risk, evaluate creditworthiness, foresee future trends, and fight fraud. PA has becoming more widely used in Saudi Arabia by capital markets, insurance companies, fintech startups, and commercial banks to increase operational effectiveness and regulatory compliance. In order to evaluate how PA is being applied across industries, the study consults contemporary policy frameworks, institutional reports, and empirical case studies. The integration of PA technologies in real-time fraud detection, liquidity forecasting, investment plan optimization, and credit rating receives special emphasis. Persistent issues are also noted in the study, such as a lack of data infrastructure, unclear regulations, and a workforce scarcity. To fully realize PA’s potential in promoting a robust and globally competitive financial sector, these challenges must be overcome. In keeping with Saudi Arabia’s long-term strategic objectives, the report ends with legislative and institutional recommendations meant to encourage PA adoption, harmonize innovation with regulatory frameworks, and promote sustainable finance sector growth.