ECL Framework based on IFRS 9 Guidelines
## Expected Credit Loss (ECL) Framework based on IFRS 9 Guidelines
This project involved developing a comprehensive Expected Credit Loss (ECL) framework in Excel, adhering strictly to the International Financial Reporting Standard 9 (IFRS 9) guidelines. The framework is crucial for financial institutions to accurately provision for potential credit losses.
### Key Components
* **Scorecard Modelling**: Developed credit scorecards to assess the probability of default (PD) for different borrower segments.
* **Prepayment Modelling**: Incorporated models to estimate the likelihood of early loan repayments, impacting the effective interest rate and expected cash flows.
* **Forward-Looking Scenarios**: Integrated multiple forward-looking macroeconomic scenarios (e.g., optimistic, base, pessimistic) to adjust PD, Loss Given Default (LGD), and Exposure at Default (EAD) in line with IFRS 9 requirements.
* **TTC PD to PIT PD Conversion**: Developed methodologies to convert Through-the-Cycle (TTC) PDs (used in Basel framework) to Point-in-Time (PIT) PDs, which are required for IFRS 9 ECL calculations. This involved integrating with existing Basel framework and ICAAP (Internal Capital Adequacy Assessment Process) models.
* **Model Validation and Implementation**: Established a robust process for validating the ECL model's accuracy and ensuring its proper implementation within the financial reporting system.
### Technical Skills
* Deep understanding of IFRS 9 and Basel III regulations.
* Proficiency in Excel for complex financial modeling and scenario analysis.
* Ability to integrate different risk models (TTC vs. PIT PD).
* Model validation and documentation.
### Significance
This ECL framework provides a robust and compliant solution for calculating expected credit losses, enabling financial institutions to meet regulatory requirements and enhance their risk management capabilities. It offers a transparent and systematic approach to provisioning, reflecting the forward-looking nature of credit risk.