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@article{173692,
        author = {Likitha P and Devireddy Dhanesh Satya Rambabu and Ganireddy Vinay and Bandaru Dileep Kumar and K Komali},
        title = {Online Transactions and UPI Fraud Detection},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {1385-1391},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=173692},
        abstract = {The increasing adoption of digital transactions, particularly through the Unified Payments Interface (UPI), has led to a surge in financial fraud, posing serious threats to users and financial institutions. Traditional fraud detection systems, which rely on predefined rule-based approaches, often struggle to adapt to evolving fraud tactics and handle the massive volume of transaction data. This research presents a machine learning-based fraud detection system that enhances the accuracy and efficiency of identifying fraudulent activities in UPI transactions.
The proposed approach utilizes the Random Forest algorithm to analyse transactional patterns and detect anomalies in real-time. Unlike conventional rule-based systems, machine learning models continuously adapt to new fraud patterns, improving detection accuracy while minimizing false positives and negatives. Additionally, an automated alert mechanism is integrated into the system to notify stakeholders immediately when fraudulent transactions are detected, enabling timely intervention.
By leveraging advanced data processing techniques and real-time analysis, this system offers a scalable and robust solution for fraud detection in digital payment ecosystems. The research demonstrates how machine learning can significantly enhance security in UPI transactions, ensuring a safer and more reliable digital financial environment. Future work may focus on integrating deep learning techniques and real-time behavioural analytics to further strengthen fraud prevention mechanisms.},
        keywords = {Machine Learning, Random Forest Algorithm, Anomaly Detection, Automated Alert Mechanism, Financial Fraud Prevention},
        month = {March},
        }