02Project
Credit Risk Analysis
Overview
A credit risk analysis project evaluating borrower behavior, default risk and loan characteristics to support data-driven credit decision-making.
Problem
Loan amounts, interest rates, credit history length and loan intent don't reveal high-risk borrowers on their own -- they need to be cleaned, enriched and queried before they become useful for a lending decision.
Approach
SQL was used extensively in DBeaver against a MySQL database to clean and enrich the dataset with calculated fields, running aggregations, window functions, subqueries and conditional logic to segment borrowers and identify high-risk profiles.
Results
An interactive Power BI dashboard visualizes risk categories, loan amounts by age group and credit purpose, making it easier to identify high-risk borrowers and monitor the portfolio.
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