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Online fraud prediction using Machine Learning Models

Ayyakutty Ramesh, Ajay Krishnaa (2023) Online fraud prediction using Machine Learning Models. Masters thesis, Dublin, National College of Ireland.

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Abstract

This study introduces an innovative approach to detecting online bank fraud by combining machine learning with ensemble approaches. Online bank fraud could be a major issue for the financial sector since it causes considerable costs and harms buyers confidence within the banking sector. The objective of this research project is to make a fraud detection system that can dependably separate between honest to goodness and fraudulent transactions, decreasing the monetary hazard for both business and their customers. The ponder begins with a profound jump into the current writing on the subject of online bank fraud detection and the numerous distinctive machine learning strategies that have been created to combat it. Information on the design requirements, such as data pretreatment, model selection, and the creation of the ensemble technique, are provided next. The primary results of this study show that the ensemble approach is better to the more common machine learning ensemble methods. The suggested approach improves upon existing methods in terms of detection accuracy, precision, recall, and F1-score. To improve fraud detection effectiveness, the study highlights the value of mixing model predictions. These results have substantial ramifications for the financial sector since the suggested approach may improve security and inspire confidence in digital exchanges.

Item Type: Thesis (Masters)
Supervisors:
Name
Email
Haque, Rejwanul
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
H Social Sciences > HG Finance > Banking
Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Tamara Malone
Date Deposited: 08 Nov 2024 11:55
Last Modified: 08 Nov 2024 11:55
URI: https://norma.ncirl.ie/id/eprint/7169

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