Advancing Credit Card Fraud Detection Through Explainable Machine Learning Methods

Title

Advancing Credit Card Fraud Detection Through Explainable Machine Learning Methods

Creator

Adhegaonkar V.R.; Thakur A.R.; Varghese N.

Description

The world of finance has experienced a significant shift in the way money flows, due to the advancements in technologies such as online banking, card payments, and QR-based payment systems. These innovative banking payment facilities are offered by ensuring the safety of the transaction and ensuring that only the authorized customer can access and utilize these banking services. Credit card fraud is innovative way to cheat the user of the card. Government all over the word encouraging to the people for the uses of digital money. This research work focuses on analyzing the machine learning database by using a labelled dataset to classify legitimate and fraudulent business transactions with explainable AI. This study is based on decision tree, logistic regression, support vector machine and random forest machine learning techniques. 2024 IEEE.

Source

2nd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2024, pp. 792-796.

Date

2024-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Credit card fraud; Explainable model; Machine Learning

Coverage

Adhegaonkar V.R., Christ University, Dept of Business Management, Pune, India; Thakur A.R., Sri Balaji University, Dept of Business Management, Pune, India; Varghese N., Christ University, Dept of Business Management, Pune, India

Rights

Restricted Access

Relation

ISBN: 979-835032753-3

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/IDCIoT59759.2024.10467999

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190145545&doi=10.1109%2fIDCIoT59759.2024.10467999&partnerID=40&md5=f6f1220ab34db963bc6ab60aed17c866