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@article{198848,
        author = {Ashwini Bhimrao Sarode and Nitin Prakash},
        title = {A Study on Fraud Detection in Banking Transactions Using Business Analytics at ICICI Bank Nagpur},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {11913-11920},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=198848},
        abstract = {There is increasing concern in banking transactions now that fraud has turned advanced due to the rapid increase in online financial services and digital banking. This paper will concentrate on the use of business analytics in the identification and prevention of fraud schemes with particular reference to ICICI Bank, Nagpur. The study concentrates on the application of the analytical methods of data mining, machine learning, and predictive modeling to detect the suspicious transactional patterns and reducing the financial risks. The research design is a descriptive study with secondary data as the basis, which is based on journals, reports, and banking publications. It points to the power of real time transaction monitoring, anomaly detection and risk scoring systems to enhance the accuracy of the detection of fraud. The results demonstrate that business analytics is quite effective to increase the number of fraud detection systems, decrease losses and increase customer trust. Nonetheless, other challenges in the study are high false positives, data privacy, and compatibility with already existing banking systems. The study works out the conclusion that to enhance the systems used in fraud detection in the banking industry, it is crucial to constantly develop new technologies and use the latest analytics},
        keywords = {—Risk Management, Digital Banking, Fraud Detection, Business Analytics, Banking Transactions, Machine Learning, ICICI Bank.},
        month = {April},
        }