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Prediction of Customer Lifetime Value and Fraud Detection in BFSI using Machine Learning

Sawant, Vaibhav Subhash (2022) Prediction of Customer Lifetime Value and Fraud Detection in BFSI using Machine Learning. Masters thesis, Dublin, National College of Ireland.

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Finance has a profound impact and relation to every person on the globe as it decides the way of life the individual is going lead. Banks and Financial Institutions are at the center of the financial or capitalist world. Both these entities are trying to adopt the new technology to reach a more significant number of people, contributing to higher profits. While dealing with the competition in the world market, the BSFI is experiencing different problems that make it difficult to survive. One such problem is obtaining suitable potential customers from the business perspective. While dealing with such competitive challenges, the domain is also dealing with some problems caused due to technological advancement in the business. More than 1.6 billion financial losses were accounted for in recent years due to various frauds in the domain. This makes it a severe problem to be addressed on priority.This research closely studies the two major problems faced by the BFSI domain, i.e., Fraud detection and calculating the Customer Lifetime Value, and responds with the application of the computing field of Machine learning. Much data available publicly for research purposes was collected, One from the Banking and the other from the Insurance domain. The nature of the data, the research question was studied conscientiously, and based on these parameters, the machine learning models, namely Support vector machine, Extreme Gradient boosting, Bernoulli Naïve Bayes, Decision tree, and Random Forest models were used for the Detection of Frauds in the transaction and calculating the CLV.

Item Type: Thesis (Masters)
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
H Social Sciences > HG Finance > Insurance
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: 10 Mar 2023 17:17
Last Modified: 10 Mar 2023 17:17

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