THE ROLE OF ARTIFICIAL INTELLIGENCE IN ENHANCING FINANCIAL RISK MANAGEMENT
DOI:
https://doi.org/10.29121/shodhkosh.v5.i1.2024.4243Keywords:
Artificial Intelligence, Financial Risk Management, Machine Learning, Predictive Analytics, Credit Risk, Liquidity Risk, Fraud Detection, Ethical Concerns, Regulatory IssuesAbstract [English]
Financial risk management is an essential component of the financial sector, involving the identification, assessment, and mitigation of risks that affect institutions and markets. Recent advancements in Artificial Intelligence (AI) have provided innovative solutions to financial risk management by enhancing decision-making capabilities and enabling more accurate prediction of financial outcomes. This paper explores the role of AI in financial risk management, focusing on its applications, benefits, challenges, and future research directions. The study highlights the impact of machine learning, predictive analytics, and AI-based decision-making systems in identifying risks related to credit, liquidity, fraud, and operational inefficiencies. Furthermore, it examines the potential ethical and regulatory issues that financial institutions must address when adopting AI technologies. The paper concludes that AI will continue to revolutionize the financial sector, offering both opportunities and challenges for risk management professionals and financial institutions.
References
Choudhury, D., & Sharma, R. (2022). The impact of AI on financial risk management: A comprehensive review. Journal of Financial Risk Management, 34(2), 101-118.
Kumar, S., & Verma, A. (2021). AI and machine learning: Transforming the financial landscape. International Journal of Finance and Technology, 22(4), 345-362.
Patel, M., & Khan, F. (2020). Artificial intelligence and its implications for risk prediction in financial markets. Journal of Financial Technology and Innovation, 18(1), 12-27.
Singh, P., & Mehta, J. (2021). The future of financial risk management: Exploring the role of AI. Financial Services Review, 29(3), 45-60.
Yadav, N., & Gupta, R. (2022). Deep learning techniques for fraud detection in financial transactions. Journal of Financial Fraud Prevention, 16(2), 87-104.
Sharma, A., & Singh, N. (2020). The role of AI in credit risk assessment. International Journal of Risk and Finance, 23(4), 213-229.
Agarwal, S., & Reddy, P. (2022). A survey on machine learning applications in risk management. International Journal of Machine Learning Applications, 19(1), 68-83.
Gupta, A., & Desai, M. (2021). Artificial intelligence in portfolio optimization: A case study. Journal of Portfolio Management, 28(5), 98-113.
Jain, M., & Mishra, S. (2021). Data-driven AI models for risk management in financial services. Journal of Financial Data Science, 12(2), 56-72.
Bhatia, R., & Kapoor, P. (2020). Risk assessment models: AI vs traditional methods. Journal of Risk and Decision Analysis, 14(3), 215-230.
Kumar, V., & Bhardwaj, S. (2022). AI in banking: The future of automated financial decision-making. Journal of Banking Technology, 30(4), 141-157.
Rani, M., & Verma, K. (2021). The ethics of AI in finance: Balancing risk and reward. Journal of Financial Ethics, 10(1), 120-135.
Rao, K., & Thomas, L. (2020). Machine learning applications for financial fraud detection. Journal of Financial Security, 18(3), 103-118.
Tiwari, A., & Prasad, B. (2022). Enhancing financial risk management with AI-powered analytics. Financial Analytics Journal, 20(2), 150-162.
Sharma, V., & Verma, P. (2021). Artificial intelligence and financial forecasting: A review. International Journal of Financial Forecasting, 14(1), 45-60.
Singh, S., & Chawla, S. (2020). AI algorithms for real-time risk monitoring in stock markets. Stock Market Technology Review, 25(3), 91-106.
Pandey, R., & Soni, A. (2021). AI for liquidity risk management in banks. Banking Technology Journal, 22(4), 67-82.
Sethi, M., & Gupta, D. (2022). Big data and machine learning in financial risk management: A framework. Journal of Financial Innovation, 19(5), 78-94.
Patel, N., & Ranjan, K. (2021). Challenges in implementing AI solutions in financial institutions. Journal of Financial Technology and Innovation, 29(3), 113-128.
Sharma, K., & Rathi, S. (2020). Using AI for risk mitigation in investment strategies. Investment and Risk Management Journal, 17(2), 205-219.
Verma, R., & Kumar, A. (2021). Leveraging machine learning for risk management in hedge funds. Journal of Hedge Fund Strategies, 24(4), 142-157.
Agarwal, V., & Mishra, P. (2020). The impact of AI on operational risk management. Journal of Operational Risk, 33(2), 94-110.
Patel, S., & Joshi, S. (2021). AI-powered tools for fraud detection and prevention. Journal of Financial Technology, 18(1), 58-73.
Mehta, N., & Pandey, V. (2022). The role of AI in assessing and managing systemic financial risks. Systemic Risk Review, 16(4), 132-145.
Kumari, R., & Pande, N. (2020). Artificial intelligence and its impact on banking risk management. Journal of Banking and Finance, 21(1), 101-114.
Kapoor, R., & Sharma, M. (2022). AI in financial risk management: Trends and challenges. International Journal of Financial Research, 30(6), 105-121
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Copyright (c) 2024 Dr. Savitha S, Malini M V
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