Building a predictive model to assess credit risk and reduce loan default rates.
Scenario interviews help us assess your thought process, creativity, and comfort with ambiguity. At the same time, the scenarios represent real client engagements so they allow you to gain insight into the work we do.
A financial institution wants to improve its credit risk analysis process to make more informed lending decisions. The institution has historical data on past loan applications, including details on borrowers, loan attributes, and whether the loans were paid back in full or defaulted. The goal is to build a predictive model that can accurately assess the credit risk of new loan applicants and help reduce the default rate.
You are given a dataset containing the below attributes. Answer the questions in the scenario after reviewing the below dataset.