Risk Mitigation in AI-Driven Financial Systems: Ensuring Stability and Trust
Keywords:
AI-driven finance, risk mitigation, algorithmic bias, financial security, model governance, regulatory complianceAbstract
Artificial Intelligence (AI) has transformed the financial sector by enhancing decision-making, automating processes, and improving customer experiences. However, the rapid integration of AI-driven solutions has also introduced various risks, including bias, security vulnerabilities, regulatory non-compliance, and ethical concerns. This research paper explores the critical challenges associated with AI-driven financial systems and presents effective risk mitigation strategies. Through empirical experiments and analysis, the study evaluates the impact of different mitigation techniques on risk reduction. The results demonstrate that a combination of robust model governance, adversarial testing, bias detection algorithms, and regulatory alignment can significantly enhance the resilience of AI-powered financial systems. The findings provide valuable insights into safeguarding financial institutions from AI-induced risks while ensuring innovation and efficiency in financial operations.
References
[1] S. Chitimoju, "AI-Driven Threat Detection: Enhancing Cybersecurity through Machine Learning Algorithms," Journal of Computing and Information Technology, vol. 3, no. 1, 2023.
[2] G. Karamchand, "The Impact of Cloud Computing on E-Commerce Scalability and Personalization," Aitoz Multidisciplinary Review, vol. 3, no. 1, pp. 13-18, 2024.
[3] S. Chitimoju, "Ethical Challenges of AI in Cybersecurity: Bias, Privacy, and Autonomous Decision- Making," Journal of Computational Innovation, vol. 3, no. 1, 2023.
[4] G. Karamchand, "The Road to Quantum Supremacy: Challenges and Opportunities in Computing," Aitoz Multidisciplinary Review, vol. 3, no. 1, pp. 19-26, 2024.
[5] G. Karamchand, "The Role of Artificial Intelligence in Enhancing Autonomous Networking Systems," Aitoz Multidisciplinary Review, vol. 3, no. 1, pp. 27-32, 2024.
[6] S. Chitimoju, "The Risks of AI-Generated Cyber Threats: How LMs Can Be Weaponized for Attacks," International Journal of Digital Innovation, vol. 4, no. 1, 2023.
[7] G. K. Karamchand, "Artificial Intelligence: Insights into a Transformative Technology," Journal of Computing and Information Technology, vol. 3, no. 1, 2023.
[8] H. Azmat, "Artificial Intelligence in Transfer Pricing: A New Frontier for Tax Authorities?," Aitoz Multidisciplinary Review, vol. 2, no. 1, pp. 75-80, 2023.
[9] S. Chitimoju, "Using Large Language Models for Phishing Detection and Social Engineering Defense," Journal of Big Data and Smart Systems, vol. 4, no. 1, 2023.
[10] G. K. Karamchand, "Automating Cybersecurity with Machine Learning and Predictive Analytics,"
Journal of Computational Innovation, vol. 3, no. 1, 2023.
[11] S. Chitimoju, "A Survey on the Security Vulnerabilities of Large Language Models and Their Countermeasures," Journal of Computational Innovation, vol. 4, no. 1, 2024.
[12] G. K. Karamchand, "Exploring the Future of Quantum Computing in Cybersecurity," Journal of Big Data and Smart Systems, vol. 4, no. 1, 2023.
[13] A. Nassar and M. Kamal, "Ethical dilemmas in AI-powered decision-making: a deep dive into big data-driven ethical considerations," International Journal of Responsible Artificial Intelligence, vol. 11, no. 8, pp. 1-11, 2021.
[14] S. Chitimoju, "Mitigating the Risks of Prompt Injection Attacks in AI-Powered Cybersecurity Systems," Journal of Computing and Information Technology, vol. 4, no. 1, 2024.
[15] G. K. Karamchand, "From Local to Global: Advancements in Networking Infrastructure," Journal of Computing and Information Technology, vol. 4, no. 1, 2024.
[16] S. Chitimoju, "The Evolution of Large Language Models: Trends, Challenges, and Future Directions," Journal of Big Data and Smart Systems, vol. 5, no. 1, 2024.
[17] S. Chitimoju, "The Impact of AI in Zero-Trust Security Architectures: Challenges and Innovations," International Journal of Digital Innovation, vol. 5, no. 1, 2024.
[18] B. Liu, B. Xiao, X. Jiang, S. Cen, X. He, and W. Dou, "Adversarial Attacks on Large Language Model‐Based System and Mitigating Strategies: A Case Study on ChatGPT," Security and Communication Networks, vol. 2023, no. 1, p. 8691095, 2023.
[19] G. K. Karamchand, "Networking 4.0: The Role of AI and Automation in Next-Gen Connectivity,"
Journal of Big Data and Smart Systems, vol. 5, no. 1, 2024.
[20] H. Azmat and Z. Huma, "Comprehensive Guide to Cybersecurity: Best Practices for Safeguarding Information in the Digital Age," Aitoz Multidisciplinary Review, vol. 2, no. 1, pp. 9-15, 2023.
[21] G. K. Karamchand, "Mesh Networking for Enhanced Connectivity in Rural and Urban Areas,"
Journal of Computational Innovation, vol. 4, no. 1, 2024.
[22] S. Chitimoju, "Enhancing Cyber Threat Intelligence with NLP and Large Language Models,"
Journal of Big Data and Smart Systems, vol. 6, no. 1, 2025.
[23] G. K. Karamchand, "Scaling New Heights: The Role of Cloud Computing in Business Transformation," International Journal of Digital Innovation, vol. 5, no. 1, 2024.
[24] M. Rizvi, "Enhancing cybersecurity: The power of artificial intelligence in threat detection and prevention," International Journal of Advanced Engineering Research and Science, vol. 10, no. 5,
pp. 055-060, 2023.
[25] S. M. Darwish, "A bio-inspired credit card fraud detection model based on user behavior analysis suitable for business management in electronic banking," Journal of Ambient Intelligence and Humanized Computing, vol. 11, no. 11, pp. 4873-4887, 2020.
[26] S. Chitimoju, "Federated Learning in Cybersecurity: Privacy-Preserving AI for Threat Detection,"
International Journal of Digital Innovation, vol. 6, no. 1, 2025.
