APPLICATION OF AI IN BIG DATA ANALYTICS TO FINANCIAL RISK FORECASTING

Abstract

Artificial intelligence (AI) is increasingly asserting its important role in many fields, especially healthcare and finance, thanks to its ability to process and analyze large amounts of diverse data, detecting complex relationships that are difficult for traditional methods to recognize. In the medical field, AI has proven to be outstandingly effective in diagnosis and treatment support. Similarly, in finance, AI is being strongly applied to risk forecasting, especially credit risk and market risk. Machine learning and deep learning models help increase the accuracy of predictions, processing both traditional and unstructured data. However, the implementation of AI also comes with challenges such as ethics, privacy, and transparency in the model. This study aims to overview the applications of AI in financial risk forecasting, and analyze the potential and challenges to overcome to optimize risk management efficiency in the context of big data.