Review on Credit Card Fraud Detection using Data Mining Classification Techniques & Machine Learning Algorithms
Year: 2020
Type: preprint
Abstract: Data mining (DM) involves a core algorithm that enables data deeper than basic insights and knowledge. In fact, data mining is more part of knowledge discovery process. Credit card (CC) providers provide multiple cards to their customers. All credit card users must be genuine and sincere. Giving a card to any kind of mistake can lead to a financial crisis. Due to the rapid growth in cashless transactions, it is unlikely, Fake transactions can also be increased. A fraudulent transaction can be identified by studying credit cards of various behaviors as a previous transaction history data set. If there is any deviation from the available cost pattern, it is a bogus transaction. DM & machine learning techniques (MLT) are widely applied in credit card fraud detection (CCFD). In this survey paper we show an indication of various widely available DM & MLT for detecting credit card fraud.
Source: SSRN Electronic Journal
Authors: Rahul Goyal, Amit Kumar Manjhvar
Institution: Madhav Institute of Technology & Science
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3157031617