Gambo, Muhammad Liman and Zainal, Anazida and Kassim, Mohamad Nizam (2022) A Convolutional Neural Network model for Credit Card Fraud detection. In: 2022 International Conference on Data Science and Its Applications, ICoDSA 2022, 6 - 7 July 2022, Bandung, Indonesia.
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Official URL: http://dx.doi.org/10.1109/ICoDSA55874.2022.9862930
Abstract
Nowadays, online transactions through various ecommerce platforms are becoming more prevalent, and Credit Card (CC) is significantly used in various online transactions. However, Credit Card Fraud (CCF) strategies continue to evolve with the business transformation, causing customers as well as the financial institutions to lose billions of dollars annually. Hence, effective detection of fraudulent transactions initiated by fraudsters from the voluminous array of normal transactions is ever necessary. Hence, a Convolutional Neural Network (CNN) model for credit card fraud detection is proposed in this study using Adaptive Synthetic (ADASYN) sampling technique to address the imbalance dataset. The proposed model has achieved 0.9982, 0.9965, and 0.9999, accuracy, precision, and recall, respectively compared to other existing studies.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | adaptive synthetic sampling technique, convolutional neural network, credit card fraud detection, imbalanced dataset, online transactions |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Computing |
| ID Code: | 98908 |
| Deposited By: | Widya Wahid |
| Deposited On: | 08 Feb 2023 05:18 |
| Last Modified: | 08 Feb 2023 05:18 |
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