BankLoan_Performance_Analysis

This repository contains a Bank Loan Analysis project using SQL, designed to demonstrate data analysis and risk assessment for a banking portfolio. It showcases how SQL can be used to generate customer, branch, and loan insights, perform risk segmentation, and track loan performance metrics.

Project Structure

1. 01_Create_Tables.sql

   • Createed database and all necessary tables: Branches, Customers, Loans, Payments
   • Includes data types, primary keys, and foreign key relationships

2. 02_load_sample_data.sql

   • Inserted scenario-oriented sample data to simulate real-world banking situations
   • Includes diverse customer incomes, loan sizes, terms, and statuses

3. 03_data_quality_tests.sql

   • Performed data validation: null checks, duplicates, outliers, etc
   • Ensures data integrity before analysis

4. 04_kpi_queries.sql

   • Calculated key metrics & KPIs:
     • Customer-level: total loans, loan-to-income ratio, default counts
     • Branch-level: total loans, average interest rate, NPA %, NPA amount
     • Risk segmentation: low, medium, high-risk customers
     • Time-based trends: monthly new loans, monthly defaults
     • Interest rate analysis by loan term
     • Produces insights for portfolio risk assessment and performance monitoring

ER Diagram

Visual representation of the database structure and relationships.

Query Outputs

• Sample outputs for KPIs and analysis
  • NPA % per branch.png
  • Risk_Segmentation.png

Notes

• All sample data is fictional and designed for demonstration purposes.
• Queries are written in standard T-SQL for MS SQL Server, but can be adapted for other relational databases.

Author

Priyasi Shah – Aspiring SQL Developer / Data Analyst

• GitHub: https://github.com/PriyasiShah1211
• LinkedIn: https://www.linkedin.com/in/priyasi-shah/