Understanding Customer Behaviour in Fintech

Soni, Dhruvi Manish (2024) Understanding Customer Behaviour in Fintech. Masters thesis, Dublin, National College of Ireland.

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Abstract

The research aimed to investigate the key factors (accessibility and trust) influencing consumer behaviour in the Indian fintech sector and predict customer satisfaction in the Indian Fintech services. Machine Learning algorithms and Neural Network models were employed for predicting the customer satisfaction in Fintech services. Among Random Forest Classifiers, ANN, DNN, RNN, and MLP models, RNN with a hyperparameter tuning approach achieved the highest accuracy of 70%. The comparative analysis between the findings generated by the analysis and the findings from the previously existing literature helped to understand the uniqueness as well as the effectiveness of this entire research study related to FinTech and Customer behaviour. Findings of this revealed that geographical location (such as residence in urban or rural areas) had a positive effect on the attitude and intention of customers. Machine learning and deep learning models were found to be highly effective for the prediction of customer behaviour in the fintech industry. In this context, from the developed ML models, random forest with hyperparameter optimization emerged as the best-fitted model due to its highest accuracy

Item Type:	Thesis (Masters)
Supervisors:	Name Email Byrne, Brian UNSPECIFIED
Subjects:	H Social Sciences > HF Commerce > Marketing > Consumer Behaviour H Social Sciences > HG Finance > Fintech T Technology > T Technology (General) > Information Technology > Fintech Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in FinTech
Depositing User:	Ciara O'Brien
Date Deposited:	05 Aug 2025 14:19
Last Modified:	05 Aug 2025 14:19
URI:	https://norma.ncirl.ie/id/eprint/8438

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