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@article{175475,
        author = {Yashshree Kokate and Sakshi Jadhav and Rutuja Katakdhond and Shehnaz Siddique},
        title = {Fraud Detection and Prevention in Banking Sector},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {3178-3181},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175475},
        abstract = {Fraud presents a major obstacle in the banking sector, resulting in monetary losses and diminishing trust of the customer. This study investigates a system for fraud detection and prevention that utilizes machine learning (ML) and deep learning (DL) and algorithms, including Support Vector Machines (SVM), Decision Trees and Neural Networks. Essential methods like Synthetic Minority SMOTE method, standardizing features, and digital Know Your Customer (e-KYC) verification is put into action. The system incorporates real-time tracking and automated noti- fications to improve fraud detection. Effectiveness is assessed via classification. metrics and visualization methods, showcasing its efficiency in detecting fraudulent deals},
        keywords = {Fraud Prevention, Fraud Detection, New Account Fraud, Syn- thetic Identities, Digital Banking, Identity Verification, Fraud- ulent transactions, Stolen Identities, Fake identities, Automated Fraud Tools, AI- generated Information, Fraud as a service, Fi- nancial Crimes, Machine Learning, Analytics, Proactive Monitor- ing, Customer safeguarding, Regulatory Compliance, Financial Reputation, Protection, Client education on fraud, Staff training on fraud,},
        month = {April},
        }