Work

Detecting Credit Card Fraud Using Machine Learning Algorithms

Year: 2021

Type: article

Abstract: Today the banking sector offers its clients many different financial services such as ATM cards, Internet banking, Debit card, and Credit card, which allows attracting a large number of new customers. This article proposes an information system for detecting credit card fraud using a machine learning algorithm. Usually, credit cards are used by the customer around the clock, so the bank's server can track all transactions using machine learning algorithms. It must find or predict fraud detection. The dataset contains characteristics for each transaction and fraudulent transactions need to be classified and detected. For these purposes, the work proposes the use of the Random Forest algorithm.

Source: InterConf

DOI: 10.51582/interconf.19-20.08.2021.037

Authors: Olexander Shmatko, Volodimir Fedorchenko, Dmytro Prochukhan

Institutions: National Technical University "Kharkiv Polytechnic Institute", Kharkiv National University of Radio Electronics

Language: English

Topic: Imbalanced Data Classification Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W3193979397

FWCI: 0.29

Cites:

Cited by: 6

Related to: 10