Risk Management Revolutionized: Data Mining Approaches for Financial Forecasting

Abstract

The integration of data mining techniques into financial forecasting has ushered in a transformative era in risk management. By harnessing advanced algorithms and computational power, financial institutions can now analyze vast datasets to uncover hidden patterns, predict market trends, and proactively manage risks. This paper explores the evolution of data mining in financial forecasting, examines various methodologies employed, presents comparative analyses of their effectiveness, and discusses the implications for future financial risk management strategies.