The project focuses on analyzing loan applications using historical data from the Small Business Administration (SBA) to determine whether a loan should be approved or denied. The primary goal is to develop predictive models to estimate the probability of loan default, known as Probability of Default (PD). This helps banks and regulators assess credit risk, decide on loan approvals, and determine the necessary capital reserves to mitigate financial risks.
The overarching purpose is to maximize profitability for banks while minimizing the risks associated with defaults. This involves leveraging SBA data to inform loan approval decisions and improve the efficiency of the loan guarantee program.