TRANSFORMING FINANCIAL SERVICES: THE STRATEGIC ROLE OF ARTIFICIAL INTELLIGENCE IN FRAUD DETECTION, RISK MITIGATION, AND CUSTOMER ENGAGEMENT

Authors

  • Triveni Visvesvaraya Technological University, Centre for PG Studies, Department of MBA, Kalaburagi, Karnataka, India
  • Sharanagoud S Biradar

DOI:

https://doi.org/10.59415/mjacs.349

Keywords:

Artificial Intelligence Financial Services, Fraud Detection, Risk Mitigation, Customer Engagement, Machine Learning(ML), Predictive and, Analytics, Digital Transformation, FinTech, Ethical AI, Regulatory Compliance.

Abstract

Artificial Intelligence (AI) is rapidly becoming a transformative force, in the financial services industry, revolutionizing traditional practices and, creating strategic value across key operational domains. This article critically examines the evolving role of AI in three vital areas: fraud detection, risk mitigation, and customer engagement. As digital transactions grow exponentially and, cyber threats become more sophisticated, financial institutions are leveraging AI-powered tools to detect and prevent fraudulent activities in real time. Advanced machine learning(ML) algorithms, anomaly detection techniques, and behavioral pattern recognition are helping institutions identify suspicious activities proactively, thereby minimizing financial losses and ensuring regulatory compliance.

In the realm of risk mitigation, AI enhances the accuracy and speed of credit scoring, risk forecasting, and portfolio management through real-time analytics and predictive modeling. These tools support agile decision-making and enable firms to respond more effectively to market volatility and credit risk exposure. Simultaneously, AI is reshaping customer engagement through intelligent chatbots, personalized financial recommendations, and sentiment analysis, driving improvements in user experience, satisfaction, and long-term loyalty.

The article draws from current academic literature, empirical studies, and industry cases are examples to explore the strategic benefits, practical applications, and implementation challenges, of AI in financial services. Despite its promise, several barriers—such as concerns over data privacy, ethical usage, regulatory uncertainty, & the need for robust technological infrastructure—continue to hinder widespread AI adoption. This paper concludes by advocating for strong AI governance, investment in talent and digital infrastructure, and collaborative regulatory frameworks as essential enablers of sustainable, AI-driven innovatively in the financial sector.

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References

1. Aisha Al-Obaidi, et al. (2024). Artificial intelligence and its impact on financial services innovation. Journal of Financial Technology, 12(1), 35–48.

2. Association of Certified Fraud Examiners (ACFE). (2023). Global fraud report 2023. https://www.acfe.com

3. Bank of America. (2023). Erica virtual assistant reaches 1.5 billion client interactions. Bank of America Newsroom. https://newsroom.bankofamerica.com

4. Basel Committee on Banking Supervision. (2022). Principles for the effective management and supervision of climate-related financial risks. Bank for International Settlements.

5. Capgemini. (2023). World FinTech Report 2023. https://www.capgemini.com/research/world-fintech-report-2023

6. Deloitte Insights. (2023). AI and risk management in financial services: From automation to transformation. Deloitte Center for Financial Services. https://www2.deloitte.com

7. Deepu Komati. (2025). Role of AI in personalized banking and risk optimization. International Journal of Financial Services, 9(2), 22–37.

8. HDFC Bank. (2022). Eva chatbot performance report. HDFC Bank Annual Report. https://www.hdfcbank.com

9. IBM. (2022). Financial risk analytics report. IBM Institute for Business Value. https://www.ibm.com

10. IBM Institute for Business Value. (2023). AI in banking and financial services: Strategy and governance. https://www.ibm.com/thought-leadership/institute-business-value

11. Juniper Research. (2023). AI in FinTech: Market trends and forecasts 2023–2028. https://www.juniperresearch.com

12. Kasula, R. (2023). The role of ethical AI in banking and customer protection. Journal of Financial Ethics and Governance, 7(4), 45–59.

13. KPMG. (2023). Global AI survey: Trust and transparency in financial AI systems. https://home.kpmg

14. Mastercard. (2022). Decision intelligence platform: AI in fraud prevention. Mastercard White Paper. https://www.mastercard.com

15. McKinsey & Company. (2023). AI in financial services: Opportunities, risks, and strategy. McKinsey Global Banking Practice. https://www.mckinsey.com

16. McKinsey & Company. (2023). Global banking AI survey 2023. https://www.mckinsey.com

17. Oxford Economics & Citibank. (2022). The future of work in finance: Automation, AI, and workforce implications. https://www.oxfordeconomics.com

18. PayPal. (2023). AI risk management in payment systems. PayPal Developer Blog. https://www.paypal.com

19. PwC. (2023). Financial services 2023 outlook: Embracing AI for competitive advantage. https://www.pwc.com

20. PwC. (2023). Financial services workforce survey. https://www.pwc.com

21. RBI (Reserve Bank of India). (2023). Discussion paper on artificial intelligence governance in financial services. https://www.rbi.org.in

22. Shujie Feng. (2024). AI-based forecasting and algorithmic trading in emerging markets. Asian Journal of Financial Analytics, 15(1), 58–70.

23. Sudheer Obbu. (2025). Artificial intelligence and data science in banking risk systems. Journal of Digital Finance, 18(1), 11–29.

24. Trivedi, A., & Kumar, S. (2024). Real-time fraud detection using AI-powered chatbots in financial institutions. International Journal of Financial Innovation, 6(3), 101–115.

25. Tyagi, M., et al. (2025). AI-powered anomaly detection in high-volume banking transactions. Journal of Machine Learning in Finance, 10(2), 76–90.

26. World Economic Forum & Deloitte. (2023). Ethical AI in financial services: A governance roadmap. https://www.weforum.org

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Published

2026-06-01

How to Cite

TRANSFORMING FINANCIAL SERVICES: THE STRATEGIC ROLE OF ARTIFICIAL INTELLIGENCE IN FRAUD DETECTION, RISK MITIGATION, AND CUSTOMER ENGAGEMENT. (2026). MLAC Journal for Arts, Commerce and Sciences (m-JACS) ISSN: 2584-1920, 4(5), 179-186. https://doi.org/10.59415/mjacs.349

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