A banking institution wants to track how loans are being funded and collected across different states, age groups, and loan types. The goal is to:
- Identify where the highest loan disbursals are happening.
- Detect categories with the most defaults or delays.
- Understand how collections vary across branches.
- Support better loan planning and recovery strategies.
This Power BI Dashboard provides a comprehensive analysis of loan disbursements, defaults, and collections to help banks make data-driven decisions.
- Total Funded Amount
- Total Interest Recovered
- Total Loan Default Amount
- Principal Recovered
- Average Rate of Interest
- Disbursement Trend (YoY)
- Age-wise Loan Distribution
- State, Region, & City-wise Funded Amount
- Top Defaulter States & Regions
- Branch-wise Collections & Recovery Rates
- Year-Wise Trend: Interest vs Loan Amount
- State, Region & City-wise funded amount.
- Category-wise loan funded (Home, Business, Trade, etc.).
- Funded Amount Growth (YoY).
- Age-wise loan funded distribution.
- Identification of high-risk regions & categories.
- YoY Collection Growth & Recovery Trends.
- Branch-wise revenue & recovery rates.
- Collection by Age Group.
- Category-wise Collection Analysis.
- Patna shows high default rates → stricter credit checks required.
- Other states performing well → implement location-specific risk profiling.
- 26–35 age group = most active borrowers → potential for premium loan offers.
- 18–25 & 46–55 age groups in Patna = high defaults → targeted risk management.
- 35–50 age group = largest loan volume → suitable for long-term lending products.
- Longer-duration loans = higher interest rates & mostly verified.
- Shorter-duration loans = often not verified → compliance concern.
- Patna region = highest recovery on defaulted loans → effective collection strategies.
- Reduce Defaults → Stricter loan checks & filtering processes.
- Focus on Strong States → Increase funding in Uttar Pradesh & Punjab with flexible loan offers.
- Targeted Marketing → Promote loans to the 26–35 age group via mobile apps & SMS.
- Analyze YoY Trends → Investigate why funding declined post-2018.
- Branch-wise Monitoring → Track delinquent loans monthly & set default alerts (>10%).
- Improve Recovery → Launch recovery drives in low-performing cities.
- Risk-based Interest Rates → Link interest rates to regional risk (Red/Yellow/Green Zones).
- Tool: Power BI
- Data Source: Loan Disbursement & Collection Dataset (CSV/XLSX)
- Visualization Techniques: DAX Measures, YoY Growth Calculations, Drill-Through Filters, Hierarchical Mapping