Machine Learning Techniques Used for Detection Fraudulent Transactions

• Author(s): Ankita Rai
• Paper ID: 1704427
• Page: 264-267
• Published Date: 12-05-2023
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 6 Issue 11 May-2023

Abstract

Fraud is a big problem for banks, business, and people. It can cause many harm like losing money, trust, and respect. The old ways of detecting fraud are not so good because they are slow and can miss tricky types of fraud. But machine learning can help by catching fraud right away. This paper talks about how to use machine learning to find fraud. There are different ways to use machine learning like supervised learning and unsupervised learning, decision trees, neural networks, and finding anomalies. But there are also some problems withusing machine learning for fraud, like making sure the data is good, keeping privacy safe, and doing the right thing. In this paper there are examples of how people use machine learning to stop fraud in credit cards, insurance, and medical care. These examples show that machine learning can be very good at catching fraud right away.

Keywords

Fraud detection, machine learning, Supervised learning, unsupervised learning, decision tree, neural networks, anomaly detection, data privacy ethical considerations.

Citations

IRE Journals:
Ankita Rai "Machine Learning Techniques Used for Detection Fraudulent Transactions" Iconic Research And Engineering Journals Volume 6 Issue 11 2023 Page 264-267

IEEE:
Ankita Rai "Machine Learning Techniques Used for Detection Fraudulent Transactions" Iconic Research And Engineering Journals, 6(11)