Abstract
Abstract: In today's changing economic world, banks are working hard to understand how different groups of people behave financially. They use information like what kind of job a person has, whether they are married, and their level of education to create strategies that encourage people to open term deposit accounts, especially during tough economic times. This study uses a detailed set of data from Kaggle and applies machine learning tools like Random Forest, Logistic Regression, and Decision Trees to understand the complex patterns of how people behave with their money, and what influences their choices, particularly when the economy is down. A new feature called 'economic conditions' was introduced in this study to better understand how people's financial choices change in normal and downturn phases. The standout performer in this study was the Random Forest tool, which showed an accuracy of about 87.8% in predicting if a person would open a term deposit account or not. This study helps banks create strategies that are more in tune with what people want and need, making banking a more personalized and satisfying experience for everyone.
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