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Internship Project

Securitisation Risk Intelligence
Dashboard

End-to-end IFRS9 credit risk monitoring for an auto loan portfolio — 3-page Power BI dashboard with 8-page project report.

Portfolio ₹317.8M
Total Loans 500
Avg CIBIL 739.2
Default Rate 6.6%
Total ECL ₹11.7M
Stage 1 Share 86%
Live Dashboard Download Report GitHub Repo
Overview

Project Overview & Objectives

A comprehensive credit risk intelligence system built on Power BI, designed to monitor, analyse, and visualise an auto loan securitisation portfolio in compliance with IFRS9 standards.

Problem Statement
Auto loan portfolios require continuous monitoring for credit deterioration under IFRS9. Manual reporting is slow, error-prone, and lacks visual drill-down capability for risk officers and stakeholders.
Solution Built
A 3-page interactive Power BI dashboard providing real-time portfolio health monitoring, ECL analysis, borrower segmentation, and automated risk driver identification using DAX and data modelling.
Project Objectives
  • Monitor portfolio health across IFRS9 Stage 1, 2, and 3 classifications
  • Identify and rank key risk drivers influencing ECL Provision using Key Influencers visual
  • Segment borrowers by demographics, vehicle type, employment, and credit profile
  • Track monthly default rate, net loss rate, recovery, and repayment trends
  • Provide a single-view executive KPI dashboard for stakeholder reporting
  • Deliver an 8-page project report documenting methodology, findings, and recommendations
Dashboard

Dashboard Walkthrough

Three interconnected pages covering risk analysis, borrower segmentation, and executive KPIs.

Tech Overview Dashboard
Tech_Overview — Risk Driver Analysis
Page 1 of 3

Decomposes the total portfolio balance across key risk dimensions — IFRS9 Stage, Vehicle Type, Employment Type, and Age Band. Uses Power BI's Key Influencers visual to automatically identify which factors most strongly drive ECL Provision increases.

Decomposition Tree
Key Influencers Visual
Stage-wise Summary Table
Key Insights Panel
State & Region Filters
Total Exposure ₹317.8M
Stage 1 ₹272.9M
Stage 3 ECL avg ₹209.4K
Top Vehicle SUV
Tech Analysis Dashboard
Tech_Analysis — Borrower & Portfolio Segmentation
Page 2 of 3

Deep-dives into customer demographics and credit profiling. Analyses recoveries vs repayments monthly trends, portfolio distribution by employment type, and income vs exposure scatter analysis per IFRS9 stage.

Portfolio vs ECL by Stage
Recoveries vs Repayments Trend
Balance by Employment Type
Loan Distribution Donut
Income vs Exposure Scatter
Total ECL ₹11.7M
Total Loans 500
Avg Delinquency 21.2 Days
Avg DTI 19.5%
Tech Insights Dashboard
Tech_Insights — Main KPI Dashboard
Page 3 of 3

Executive-level single-view dashboard covering all critical portfolio KPIs. Includes monthly default rate trends, net loss rate, delinquency distribution by DPD bucket, borrower CIBIL scatter, and IFRS9 stage-wise risk summary table.

5 KPI Cards
Balance by Age Segment
Delinquency by DPD Bucket
Borrower Credit Profile
Monthly Default Rate Trend
Net Loss Rate Trend
IFRS9 Stage Risk Summary
Avg CIBIL 739.2
Default Rate 6.6%
Delinquent 115 Loans
Current DPD 86.76%
Stack

Tech Stack & Tools

Technologies used to build, model, and deploy the dashboard.

Power BI
Dashboard development, visuals & report publishing
DAX
KPI measures, ECL calculations, stage logic
SQL Server
Source data extraction & querying
Python
Data cleaning, ECL preprocessing pipeline
Power Query
ETL transformations & data shaping
Data Modelling
Star schema design — fact & dimension tables
IFRS9
Credit risk staging & ECL framework
GitHub
Version control & portfolio hosting
Findings

Key Findings & Insights

Critical risk intelligence extracted from the portfolio analysis.

86%
Strong Portfolio Quality
86% of the total portfolio balance sits in IFRS9 Stage 1 — indicating strong overall credit quality with low default risk.
₹209K
Stage 3 ECL Driver
Stage 3 is the #1 influencer of ECL Provision increase with an average ECL of ₹209.4K — highest despite lowest exposure.
SUV
Highest Asset Exposure
SUVs contribute the largest share of total portfolio balance at ₹95.3M, followed by MUVs at ₹82.4M across all stages.
739
Above-Average CIBIL
Average CIBIL score of 739.2 indicates above-average borrower creditworthiness across the portfolio.
6.6%
Default Rate Alert
6.6% of loans are in Stage 3 (non-performing). 115 delinquent loans identified with 86.76% of accounts current at 0 DPD.
88M
Professional Dominance
Professional borrowers hold the highest portfolio balance at ₹88M, followed by Salaried at ₹85M across all vehicle categories.
IFRS9 Stage-wise Risk Summary
Stage Current Balance ECL Provision Loan Share Status
Stage 1 ₹272,932,661.65 ₹2,792,098.27
86%
Performing
Stage 2 ₹27,153,397.92 ₹1,648,395.03
8.5%
Under Watch
Stage 3 ₹17,699,142.57 ₹7,222,459.60
5.5%
Non-Performing
Total ₹317,785,202.14 ₹11,662,952.90
100%
Full Portfolio
Report

Project Report

An 8-page comprehensive internship project report documenting the full methodology, analysis, and recommendations.

Securitisation Risk Intelligence — Project Report
8 pages | IFRS9 Framework | Auto Loan Portfolio | Power BI | Internship Project
Executive Summary Problem Statement Data Architecture IFRS9 Methodology ECL Framework Dashboard Design Key Findings Recommendations
Download PDF