AI-Based Real-Time Financial Risk Management

AI-Based Real-Time Financial Risk Management

Bhavik U. Swadia (GLS University, India), J. Anand (SRM Valliammai Engineering College, India), K. L. Meera (Jain University, India), Azeem Ahmad Khan (Al-Baha University, Saudi Arabia), Sarfaraz Javed (Sohar University, Oman), and Manesh R. Palav (Dr. D.Y.Patil Vidyapeeth, India)
DOI: 10.4018/979-8-3693-7367-5.ch006
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Abstract

Conventional methods of risk management frequently prove insufficient due to the unpredictable behaviour of the market and the perpetually increasing intricacy of financial products. This investigation concentrates on the application of artificial intelligence in real-time financial risk management, with a particular emphasis on big data analytics, natural language processing, and machine learning. AI systems are capable of efficiently analysing vast quantities of structured and unstructured data in order to anticipate market trends, identify emergent threats, and provide valuable insights. In addition to enhancing the accuracy and efficacy of risk assessment, AI-powered solutions also assist in the implementation of proactive risk mitigation strategies. This article offers a thorough examination of the current methods, challenges, and forthcoming advancements in financial risk management, with a particular emphasis on the potential of artificial intelligence to enhance this field.
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