Credit Risk Analysis
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Credit Risk Analysis

Skills
Tableau
EDA
Data Cleaning
Project Type
Personal Project

Introduction

  • Objective: Evaluate current loan clients' behavior and identify trends to increase number of low-risk borrowers
  • Focus Areas:
    • Analyze customer demographics, financial factors, and loan purposes
    • Identify high-risk profiles and growth opportunities
  • Key Recommendations:
    • Targeted marketing for low-risk segments
    • Age-specific loan products
    • Enhanced risk controls for business and vacation loans
    • Dashboard for real-time trend monitoring

Methodology

  • Data Preparation:
    • Cleaned data by removing duplicates, handling missing values (via imputation), and standardizing variables like loan amounts, durations, and client demographics.
    • Filtered data to focus on relevant client segments and loan attributes for the analysis.
  • Analysis workflow:
    • Conducted exploratory data analysis (EDA) to uncover patterns and outliers.
    • Segmented clients based on demographic (age, gender) and financial factors (account balances, housing status).
    • Applied statistical techniques to identify correlations between client attributes and credit risk.
    • Built visualizations to track loan purposes, amounts, durations, and high-risk trends across segments.

Findings and Insights

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Recommendations

Recommendations are tailored for each department to develop strategies aligned with the shared objective

Marketing &Sales team

1. Targeted Marketing for Low-Risk Segments
  • Focus Groups: Male homeowners with 2-3 jobs and stable savings/checking accounts with an aim to buy car or TV
  • Rationale: These clients represent the typical low-risk profile and have shown consistent financial behavior. Marketing efforts directed at this segment are likely to yield safer loans.
 

Product team

2. Introduce Age-Specific Loan Products
  • For Young Adults (High-Risk Segment):
    • Offer smaller loan amounts with shorter durations to reduce risk.
    • Pair loans with financial literacy programs to improve repayment behavior.
  • For Middle-Aged Clients (Low to Medium Risk):
    • Provide larger loans for stable purposes like home improvement or education.
  • Rationale: Tailored loan products align with financial needs and risk tolerance for each age group. This encourages more borrowing while managing risks effectively.
 

Business Development team

3. Incentivize Business and Vacation Loans with Risk Controls
  • Business Loans: Partner with local businesses to provide guarantees or collateralized loans.
  • Vacation Loans: Introduce capped loan amounts and shorter terms to mitigate risk.
  • Rationale: These purposes have the highest average loan amounts and durations. By adding stricter controls, lenders can safely expand these loan categories.
 

Data Analytics & IT team

4. Build a dashboard for the management team to keep track of and observe the trend over time
  • Leveraging existing customer and financial data to identify trends in loan purposes, risk profiles, and borrower demographics.
5. Use Data-Driven Risk Models for Pre-Approval
  • Leverage existing financial and demographic data to pre-approve low-risk clients.
  • Use dynamic risk models to flag high-risk borrowers early and adjust loan terms accordingly.
  • Reason: Automating risk detection ensures safer lending and improves efficiency in borrower onboarding
 
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