International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Fraud Detection on Bank Payment |
|---|---|
| ABSTRACT | With the swift expansion of digital banking and online payment platforms, financial fraud has emerged as a significant concern for both banks and customers. Conventional methods for detecting fraud often struggle to pinpoint suspicious transactions in real-time. This project introduces a Real-Time Fraud Detection System for Bank Payments that utilizes machine learning, Apache Kafka, and Streamlit to efficiently and accurately identify fraudulent transactions. The system in question employs a trained machine learning model to evaluate transaction characteristics such as the transaction amount, account balances, transaction timing, and details of the sender and receiver. Apache Kafka is utilized for real-time data streaming, facilitating the ongoing collection and processing of transaction information. The system categorizes transactions as legitimate or fraudulent based on defined probability thresholds, ensuring quick and dependable fraud detection. |
| AUTHOR | USHA K, MOHAMMED MOINUDDIN, RAJABHAKSHI M, AMITH M, DARSHAN P Mentor, Department of Computer Science and Engineering, Jain Institute of Technology, Davanagere, Karnataka, India UG, Department of Computer Science and Engineering, Jain Institute of Technology, Davanagere, Karnataka, India |
| VOLUME | 180 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1401012 |
| pdf/12_Fraud Detection on Bank Payment.pdf | |
| KEYWORDS | |
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