Difficulties in Financial Risk Management: A Review of AI Applications

Manisha Kalra; Rohit Markan

Abstract

This paper analyses several uses of artificial intelligence (AI) techniques in financial risk management. Financial technology has significantly transformed company operations, requiring an adaptation within the financial industry. Financial risk management need reorganization owing to the reduced effectiveness of previously used solutions. The artificial intelligence methodologies shown their effectiveness and enabled swift, economical, and improved financial risk management in financial institutions and enterprises. This research seeks to clarify the use of AI methodologies in financial risk management and to provide possible directions for future implementation and advancement. The analysis included analysing various papers, books, and publications about AI applications in financial risk management. A thorough evaluation of relevant literature was conducted to determine the extent to which AI methodologies, especially machine learning, may be used in financial risk management. Artificial intelligence has significantly improved market risk and credit risk management via data preparation, risk modelling, stress testing, and model validation. Artificial intelligence techniques may be beneficial for guaranteeing data quality, enhancing data via text mining, and detecting fraud. Financial technology will persist in shaping the financial sector by requiring adaptation to new settings and business models. Therefore, it is expected that artificial intelligence will be included into the financial risk management system.