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This Power BI project explores bank loan data to identify trends in loan approvals, customer profiles, and repayment behavior. The interactive dashboard provides insights into default risks, loan distribution, and key financial metrics, enabling better decision-making.

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mayur-42/Bank-Loan-Report-Analysis

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Bank Loan Report Analysis📊

🌟 Problem Statement

To evaluate the performance of our lending activities and assess the quality of our loan portfolio, we need to create a comprehensive report that distinguishes between 'Good Loans' and 'Bad Loans' based on specific loan status criteria.


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Dashboards

📈 Dashboard 1: Summary

This dashboard provides a high-level overview of loan performance and key financial metrics. Summary

📊 Key Metrics:

  • Total Loan Applications
  • Total Funded Amount
  • Total Amount Received
  • Average Interest Rate
  • Average Debt-to-Income Ratio (DTI)

📋 Good Loan KPIs:

  • Good Loan Application Percentage
  • Good Loan Applications
  • Good Loan Funded Amount
  • Good Loan Total Received Amount

📋 Bad Loan KPIs:

  • Bad Loan Application Percentage
  • Bad Loan Applications
  • Bad Loan Funded Amount
  • Bad Loan Total Received Amount

📊 To monitor the performance of loans, a grid view report categorized by 'Loan Status' will be created. This report will provide insights into:

  • Total Loan Applications
  • Total Funded Amount
  • Total Amount Received
  • Month-to-Date (MTD) Funded Amount
  • MTD Amount Received
  • Average Interest Rate
  • Average Debt-to-Income Ratio (DTI)

📈 Dashboard 2: Overview

This dashboard visually represents critical loan-related metrics and trends using various chart types.

Summary

Chart Requirements:

  • Monthly Trends by Issue Date
  • Regional Analysis by State
  • Loan Term Analysis
  • Employee Length Analysis
  • Loan Purpose Breakdown
  • Home Ownership Analysis

📈 Dashboard 3: Details

The Details Dashboard provides a consolidated view of all essential loan data, offering a holistic snapshot of key loan metrics and borrower profiles.

Details

Objective:

The primary objective of the Details Dashboard is to serve as a one-stop solution for accessing vital loan data, helping users gain deeper insights into:

Loan portfolio performance

Borrower profiles

Loan status trends


📂 Dataset

Source: Bank-Loan-Report

  • The dataset includes information on loan applicants, such as loan status, income, credit history, and repayment records.
  • Data is cleaned and transformed for accurate analysis.

🛠️ Tools & Technologies

  • SQL: Data extraction and transformation.
  • Tableau: Data visualization and dashboard creation.
  • Excel: Initial data exploration and preprocessing.

🚀 Insights & Findings

  • High-income applicants have a higher loan approval rate.
  • Borrowers with a good credit history are more likely to repay loans on time.
  • Specific customer segments have a higher risk of default.

💡 Future Enhancements

  • Add predictive modeling for loan approval recommendations.
  • Integrate external financial data for deeper insights.
  • Enhance visuals with advanced Tableau features.

👤 Author

Mayur Jambe

Feel free to explore, fork, and contribute to this project. Feedback and suggestions are highly appreciated! 🌟

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This Power BI project explores bank loan data to identify trends in loan approvals, customer profiles, and repayment behavior. The interactive dashboard provides insights into default risks, loan distribution, and key financial metrics, enabling better decision-making.

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