Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{195390,
        author = {Dr.Thanseena Bai R and Dr jeena R},
        title = {Application of AI and Machine learning in detection and prevention of frauds by banks in India},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {373-380},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=195390},
        abstract = {Artificial Intelligence (AI) and Machine Learning (ML) are reshaping the global financial domain and the Indian banking industry. With the emergence of electronic transactions and rapid financial inclusion, banks are increasingly prone to complex and large-scale fraudulent activities. Conventional detection mechanisms have proven inadequate to manage and mitigate these evolving risks, thereby it promote and accelerates the adoption of AI-based fraud detection systems. This research paper examines the application of AI and ML technologies such as supervised and unsupervised learning, neural networks and natural language processing in detecting and preventing financial frauds in Indian banks. AI models facilitates real-time transaction monitoring, anomaly detection and predictive analytics, allowing banks to identify fraudulent behaviour patterns rapidly and take preventive action. The study also examines the comparative adoption of AI technologies in public and private sector banks through thematic analysis, highlighting tools like RBI’s mulehunter.AI and AI-driven systems in institutions such as SBI, HDFC and ICICI Bank. While AI improves operational efficiency, customer service and compliance, the paper also explores the ethical challenges, algorithmic bias, data privacy and cybersecurity vulnerabilities associated with these systems. The findings suggest that the integration of AI in the Indian banking sector has strengthened fraud prevention frameworks, enhanced decision-making accuracy and reduced financial losses. The study concludes that AI and ML are not merely technological add-ons but essential tools for fostering a resilient, secure and trustworthy financial ecosystem in India.},
        keywords = {},
        month = {April},
        }