Card Fraud Detection Using Artificial Neural Network and Multilayer Perception Algorithm

Year : 2023 | Volume :01 | Issue : 01 | Page : –
By

Baku Agyo Raphael,

Bisen Gambo Adashu,

Andrew Ishaku Wreford,

  1. Lecturer Department of Computer Science, Federal University Wukari Nigeria
  2. Lecturer Department of Computer Science, Kwararafa University Wukari Nigeria
  3. Lecturer Department of Computer Science, Federal University Wukari Nigeria

Abstract

Fraud has posed a significant challenge for merchants, especially in the online business sector, over the course of many years. This is primarily due to the advancements in technology that have made credit card transactions a common method of payment. Credit card fraud refers to the unauthorized use of a credit card by an individual for personal purposes, without the owner’s consent and with no intention of paying for the incurred expenses or engaging in deceptive activities to gain financial advantage. Given the efforts made by fraudsters to disguise their transactions as legitimate, this study introduces an artificial neural network model powered by a machine learning algorithm to identify and detect fraudulent activities in credit card transactions. The researchers effectively filtered and cleansed the dataset sourced from Kaggle machine learning repository selection techniques. The experiment was set up on a 64-bit Windows OS on an Intel (R) Core (TM) i5-3530 QM CPU @ 2.40 GHZ. Python 3.10 via Anaconda environment using Jupyter notebook was used as the integrated development environment. Dataset exploration, reading, scaling and performance evaluation were done successfully. The study result found prediction accuracy of 0.9184, which is equivalent to 92% at step 716 with 4.6 ms conducted per step and also loss metric based on binary entropy of 2.0%. The study recommends future research and advancement in artificial neural network by hybridizing deep neutral network and Relu neural network for multi-perception optimized performance.

Keywords: Entropy, classifier, credit card fraud, artificial neural network (ANN)

[This article belongs to International Journal of Algorithms Design and Analysis Review(ijadar)]

How to cite this article: Baku Agyo Raphael, Bisen Gambo Adashu, Andrew Ishaku Wreford. Card Fraud Detection Using Artificial Neural Network and Multilayer Perception Algorithm. International Journal of Algorithms Design and Analysis Review. 2023; 01(01):-.
How to cite this URL: Baku Agyo Raphael, Bisen Gambo Adashu, Andrew Ishaku Wreford. Card Fraud Detection Using Artificial Neural Network and Multilayer Perception Algorithm. International Journal of Algorithms Design and Analysis Review. 2023; 01(01):-. Available from: https://journals.stmjournals.com/ijadar/article=2023/view=116584

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Regular Issue Subscription Original Research
Volume 01
Issue 01
Received June 21, 2023
Accepted July 3, 2023
Published August 24, 2023
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