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E1d Using Machine Learning to Predict Young Adult’s Financial Behavior
Short Description
The purpose of this study is to investigate the role of non-credit information in predicting less than optimal financial behaviors. In this study, we test whether individual characteristics, financial status, financial education, and financial knowledge successfully predict AFS usage by using machine learning methodologies. For the ACCI conference, we expect to expand this to credit usage in addition to AFS usage. We evaluate the performance of our machine learning model and suggest the criteria to choose the optimal models based on the prediction purposes.
Type of presentation
Accepted Oral Presentation