Utilizing Machine Learning to Enhance Risk Assessment at Tamara

Abstract

Tamara executives have a constant concern regarding the risks they face. One of them is with regards to defaulting (non-paying) customers, as they must mitigate this risk for their business to survive and grow. By utilizing the petroleum of today (data), they can better mitigate the risk associated with defaulting customers. Deploying Machine learning models can be used to analyze and to determine the risk levels involved in accepting/rejecting customers. This project aims at addressing the problem caused by defaulting customers, which massively have a negative impact on the bottom-line of Tamara.