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@article{203977,
        author = {Shradha Dash and Samruddhi Salunkhe and Vaidehi Biramane and Shruti Ghanvat and Saniya Dhagare},
        title = {FraudShield AI : AI- Based Payment Fraud Detection System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {2332-2336},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=203977},
        abstract = {Online payment fraud has increased rapidly with the growth of digital transactions, UPI payments, and mobile banking services. This paper presents the implementation of PayGuard: AI-Based Payment Fraud Detection System, which helps detect and prevent fraudulent payment activities using Artificial Intelligence and Machine Learning techniques. The system analyzes transaction details such as payment amount, transaction time, user behavior, device information, and transaction history to identify suspicious activities in real time. Additionally, the system stores user transaction records and generates instant fraud alerts and personalized security recommendations to improve payment safety. AI algorithms are used to recognize unusual transaction patterns and reduce the risk of fake or unauthorized payments. The proposed system aims to improve digital payment security, reduce financial fraud, and increase user trust in online payment platforms.},
        keywords = {Artificial Intelligence (AI), Machine Learning, Payment Fraud Detection, Digital Payments, Cyber Security.},
        month = {June},
        }