Fraud Detection in Credit Card Transaction Using ANN and SVM
- Title
- Fraud Detection in Credit Card Transaction Using ANN and SVM
- Creator
- Shaji A.; Binu S.; Nair A.M.; George J.
- Description
- Digital Payment fraudulent cases have increased with the rapid growth of e-commerce. Masses use credit card payments for both online and day-to-day purchasing. Hence, payment fraud utilizes a billion-dollar business, and it is growing fast. The frauds use different patterns to make the transactions from the cardholders account, making it difficult for the organization or the users to detect fraudulent transactions. The studys principal purpose is to develop an efficient supervised learning technique to detect credit card fraudulent transactions to minimize the customers and organizations losses. The respective classification accuracy compares supervised learning techniques such as deep learning-based ANN and machine learning-based SVM models. This studys significant outcome is to find an efficient supervised learning technique with minimum computational time and maximum accuracy to identify the fraudulent act in credit card transactions to minimize the losses incurred by the consumers and banks. 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
- Source
- Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Vol-383, pp. 187-197.
- Date
- 2021-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Artificial neural network; Credit card fraud detection; SMOTE; Support vector machine
- Coverage
- Shaji A., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; Binu S., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; Nair A.M., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; George J., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India
- Rights
- Restricted Access
- Relation
- ISSN: 18678211; ISBN: 978-303079275-6
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Shaji A.; Binu S.; Nair A.M.; George J., “Fraud Detection in Credit Card Transaction Using ANN and SVM,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/20615.