Financial Fraud Detection in Plastic Payment Cards using Isolation Forest Algorithm

  • et al.
N/ACitations
Citations of this article
4Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The need for technology has always found space in Financial Transaction as the number of fraud in financial transactions increases day by day. In this research we have proposed a new methodology by using the isolation forest algorithm and local outlier detection algorithm to detect the financial fraud. A standard data set is used in experimentation to classify a transaction occurred is a fraudulent or not. We have used neural networks and machine learning for classification. We have focused on the deployment of anomaly detection algorithms that is Local Outlier Factor and Isolation Forest algorithm (IFA) on financial fraud transactions data.

Cite

CITATION STYLE

APA

Kumar, A. … Mahto, S. K. (2021). Financial Fraud Detection in Plastic Payment Cards using Isolation Forest Algorithm. International Journal of Innovative Technology and Exploring Engineering, 10(8), 132–136. https://doi.org/10.35940/ijitee.g8873.0610821

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free