International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 3 May-June 2024 Submit your research before last 3 days of June to publish your research paper in the issue of May-June.

Fraud Prediction and Verification of Smart Credit Card using Machine Learning Techniques

Author(s) Prajapnoor Baswaraj, Praveen Kumar, Dr. B. U. Anu Barathi
Country India
Abstract This study unveils a powerful method for smart credit card fraud detection and verification. This system integrates data preprocessing, feature engineering, and real-time prediction using a hybrid model that incorporates supervised machine learning algorithms, an encoder, and LSTM networks. A supervised LSTM network sorts transactions, while an unsupervised Autoencoder finds outliers. Assessment criteria strike a balance between recall and accuracy. Alerts are sent by the system upon detection of fraud, and it runs in real-time. Compliance, scalability, and constant monitoring are key points. To close the gap between ease and safety in contemporary monetary transactions, this project offers a state-of-the-art method for strengthening the security of smart credit cards.
Keywords LSTM, AUTOENCODER, ANOMALY
Field Engineering
Published In Volume 6, Issue 2, March-April 2024
Published On 2024-03-25
Cite This Fraud Prediction and Verification of Smart Credit Card using Machine Learning Techniques - Prajapnoor Baswaraj, Praveen Kumar, Dr. B. U. Anu Barathi - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.13541
DOI https://doi.org/10.36948/ijfmr.2024.v06i02.13541
Short DOI https://doi.org/gtn327

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