CreditRiskAnalysis

Customer Credit Risk Analysis

The project assigned to me during the second sprint involves Data Preprocessing.

Throughout this sprint, I dived into the understanding of how to rectify imperfections within data, convert data types, and manage missing as well as duplicate values.

Project Insight

This project is an endeavor to analyze the Risk of Default in Loan Repayment, with the main objective to provide invaluable insights that could be leveraged by banks for credit assessment of potential borrowers. The following is a summary of the conclusions that I've drawn post-project completion.

Upon a deep data analysis, and subsequent testing, we were able to answer the following enquiries:

1. Is there a correlation between the presence of children and the likelihood of defaulting on a loan? The data suggests no correlation, as it is seen that families without children also exhibit a default rate analogous to those with children.

2. Is there a correlation between marital status and the likelihood of defaulting on a loan? The data illustrates that clients either in a civil partnership or of unmarried family status bear a higher percentage of default rate compared to clients who are married or divorced.

3. Is there a correlation between income echelons and the likelihood of defaulting on a loan? Clients at the lower end of the income spectrum have a higher risk of default, and this risk are weaken as their income inflates.

4. How does the differences in loan purposes influence the probability of defaulting on a loan? Clients who borrow for property-related reasons exhibit the lowest risk of default, trailed by those borrowing for marriage-related reasons. Borrowing for educational and automobile-related reasons are associated with the highest risk of default.

Drawing from the analysis, the following recommendations can be made for the marketing team:

1. Concentrate marketing endeavors towards individuals who are married or divorced as they demonstrate a lower likelihood of defaulting on a loan compared to those in a civil partnership or of unmarried family status.

2. Income level should be a primary consideration when evaluating creditworthiness and risk. Clients with lower income levels are at a higher risk of default, so it may be wise to establish lower credit limits or propose more affordable payment schemes for these clients.

3. Amplify the promotion of loans for property-related purposes, as clients borrowing for these reasons display the least risk of default.