Applying Machine Learning to Analyze ATM Cash Withdrawal Patterns and Develop Optimization Model: Insights from Credit and Debit Card Transactions in India

Abstract

Data analysis through Machine learning is becoming very pivotal and valuable for organizations. Banks are considered to be the backbone of our Economy. Banks in India are striving for resource optimization and cost cutting and use of ATMs has proved to be very cost effective strategy deployed by banks in India which benefits not only the banks but also customers. Indian scheduled commercial banks are reckoned globally for their best practices. The study has been undertaken with the objective of : Grouping the banks into clusters according to how their ATMs are used to withdraw cash using credit cards and debit cards; understanding the distribution of ATM cash withdrawals through credit cards and debit cards within each clusters and analyzing the relationship between the number of ATMs and ATM cash withdrawals made through credit and debit cards within each cluster, and to gain insights into how this relationship varies within and between clusters. In a nutshell, the research paper aims at analyzing the pattern of ATMs cash withdrawals of scheduled commercial banks in India done through credit card and debit cards through various machine learning techniques. The Viksit Bharat Mission envisions a developed India by fostering financial inclusivity, economic growth, and technological advancement. Optimizing the use of ATM machines in India can significantly contribute to these goals by ensuring efficient resource allocation and enhanced accessibility to banking services. The outcome of this research are expected to enable banks in framing strategies for optimizing their resources.