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Expected Credit Loss Formula

Expected Credit Loss Formula:

\[ ECL = PD \times LGD \times EAD \]

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1. What is Expected Credit Loss?

Expected Credit Loss (ECL) is a forward-looking impairment model introduced under IFRS 9 accounting standards. It requires financial institutions to recognize expected credit losses at the time financial instruments are initially recognized, rather than waiting for a credit event to occur.

2. How Does the Calculator Work?

The calculator uses the ECL formula:

\[ ECL = PD \times LGD \times EAD \]

Where:

Explanation: The ECL model incorporates forward-looking information and requires staging of financial assets based on credit risk deterioration.

3. Importance of ECL Calculation

Details: ECL calculation is crucial for financial institutions to comply with IFRS 9 requirements, manage credit risk effectively, and maintain adequate provisions for potential loan losses. It provides a more timely recognition of credit losses compared to the incurred loss model.

4. Using the Calculator

Tips: Enter PD and LGD as decimal values between 0 and 1 (e.g., 0.05 for 5%), and EAD in USD. All values must be valid and within acceptable ranges.

5. Frequently Asked Questions (FAQ)

Q1: What is the difference between ECL and the incurred loss model?
A: ECL is forward-looking and recognizes losses earlier, while the incurred loss model only recognizes losses after a credit event has occurred.

Q2: How are the three stages defined in IFRS 9?
A: Stage 1: Performing assets with no significant credit deterioration; Stage 2: Assets with significant credit deterioration; Stage 3: Credit-impaired assets.

Q3: What time horizon should be used for ECL calculation?
A: For Stage 1 assets, 12-month ECL; for Stage 2 and 3 assets, lifetime ECL should be calculated.

Q4: How should PD, LGD, and EAD be estimated?
A: These parameters should be based on historical data, adjusted for current conditions and reasonable forward-looking information.

Q5: Are there specific requirements for ECL modeling?
A: Yes, models must be robust, validated regularly, and incorporate multiple economic scenarios to capture different possible outcomes.

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