Open AccessDETECTING CREDIT CARD FRAUD USING MACHINE LEARNING ALGORITHMS
Author(s) -
Olexander Shmatko,
Volodimir Fedorchenko,
Dmytro Prochukhan
Publication year - 2021
Publication title -
interconf
Language(s) - English
Resource type - Journals
ISSN - 2709-4685
DOI - 10.51582/interconf.19-20.08.2021.037
Subject(s) - credit card , credit card fraud , debit card , computer science , database transaction , algorithm , atm card , random forest , financial transaction , the internet , machine learning , computer security , artificial intelligence , payment , database , world wide web
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.