Project Overview
This section outlines a conceptual approach to Expected Credit Loss (ECL) and credit risk analysis aligned with IFRS 9 principles. The methodology reflects hands-on exposure to credit portfolio monitoring, risk segmentation, and risk-based decision support in a financial services environment.
Credit Risk Assessment Framework
- Customer credit behavior and repayment patterns
- Loan product and exposure characteristics
- Historical delinquency and default trends
- Forward-looking macroeconomic risk indicators
ECL Modeling Approach (IFRS 9)
Stage 1 – Performing Assets
- 12-month Expected Credit Loss calculation
- Low credit risk exposure
- Continuous monitoring using early warning indicators
Stage 2 – Underperforming Assets
- Lifetime Expected Credit Loss estimation
- Significant Increase in Credit Risk (SICR)
- Migration analysis based on delinquency behavior
Stage 3 – Credit-Impaired Assets
- Lifetime ECL with default recognition
- Higher probability of default and loss severity
- Focus on recovery and collateral effectiveness
Key ECL Components
- Probability of Default (PD): Likelihood of borrower default
- Loss Given Default (LGD): Estimated loss after recoveries
- Exposure at Default (EAD): Outstanding exposure at default
ECL = PD × LGD × EAD
Analytical Techniques Applied
- Portfolio segmentation based on risk characteristics
- Delinquency and migration trend analysis
- Risk categorization (Low / Medium / High)
- Sensitivity analysis using macroeconomic scenarios
Business Impact & Risk Insights
- Early identification of high-risk customer segments
- Support for risk-based provisioning and capital planning
- Improved monitoring of credit quality deterioration
- Enhanced risk mitigation and policy decision support
Tools & Skills Applied
- Excel-based ECL models and automated MIS reporting
- Dashboard-driven credit risk monitoring
- Data analysis for portfolio-level insights