ECL
The International Accounting Standards Board (IASB) introduced IFRS 9 – Financial Instruments in July 2014, setting out a principles-based standard for recognizing and accounting for credit losses. This standard replaced the old approach with a forward-looking expected credit loss (ECL) framework, requiring businesses, especially banks, to account for potential losses early, rather than waiting for them to occur.
However, developing and maintaining accurate ECL models can be tricky, especially during uncertain economic times when reliable data is hard to come by. IFRS 9 makes it essential to properly calculate, account for, and disclose expected credit losses. This approach not only impacts financial reporting but also plays a role in the regulatory treatment of provisions within the Basel capital framework. In this overview, we’ll dive into the challenges of expected credit losses calculation and its implications under IFRS 9.
ECL Under IFRS 9 vs. Impairment Provisions of IAS 39
Under IFRS 9, impairment provisions are based on the expected credit loss model, which estimates p otential future economic losses on an asset. This is a forward-looking approach, requiring businesses to recognize credit losses even at the asset’s initial recognition, based on expected future events and conditions.
In contrast, the older IAS 39 model followed a backward-looking approach, where impairment provisions were made only for losses that had already occurred during the reporting period. Provisions under IAS 39 required concrete evidence of impairment as of the reporting date, making it reactive rather than proactive.
The shift to expected credit losses under IFRS 9 aims to provide more timely and realistic recognition of credit risks, enhancing financial reporting accuracy and aligning provisions with anticipated economic conditions.
Key Factors in the Calculation of Expected Credit Loss (ECL)
When determining expected credit loss under IFRS 9, several essential elements come into focus, ensuring an accurate and forward-looking approach to assessing credit risk. These factors include:
- Exposure at Default (EAD): EAD refers to the estimated amount of credit exposure a company would face if a default occurs at any given time. For instance, if a company is calculating expected credit losses for its bond investments, the EAD for each bond would be its amortized cost balance recorded in its books on the reporting date. This provides a clear view of the potential exposure tied to each asset.
- Probability of Default (PD): PD is the projected likelihood that a particular asset, such as a loan or investment, will go into default. This probability is often derived from historical data, market trends, and current economic conditions, giving a statistical estimate of default risk over a specific time horizon.
- Loss Given Default (LGD): LGD represents a company’s potential financial loss if the default occurred. The value and availability of collateral tied to the asset are critical in calculating this factor. For example, if collateral exists, its valuation and the ease of recovery significantly reduce the LGD, whereas unsecured assets typically result in higher losses.
- ECL Formula: The formula for calculating expected credit losses is: ECL = EAD x PD x LGD.
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- However, this basic formula often requires customization to align with a company’s unique circumstances. Adjustments may include sensitivity analyses, specific methodologies for different asset classes, and discounting factors based on the expected life of each asset.
- These refinements ensure that the expected credit losses calculation is robust and reflects the true credit risk.
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By considering these factors comprehensively, businesses can adopt a proactive approach to managing credit risks, which is a cornerstone of the IFRS 9 framework.
Different Approaches for ECL Calculation under IFRS 9
IFRS 9 offers two main approaches for calculating the Expected Credit Loss model, based on the nature and complexity of financial assets:
- General Approach:
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- Often called the three-stage approach, this method evaluates how changes in credit risk affect the expected credit losses calculation over the asset’s life.
- The key feature is distinguishing between 12-month ECL and lifetime ECL, depending on whether there has been a significant increase in the asset’s credit risk.
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- Simplified Approach:
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- Designed for short-term receivable balances, this approach requires lifetime ECL to be recognized from the beginning, without tracking changes in credit risk.
- This simplifies the process, avoiding complex models for straightforward assets that don’t need detailed risk movement analysis.
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These approaches help tailor expected credit losses calculations based on the asset type and credit risk exposure, ensuring compliance with IFRS 9 guidelines.
How to Spot a Significant Increase in Credit Risk for ECL Calculation
When figuring out if there’s a notable rise in credit risk for calculating Expected Credit Loss, you need to dive into the following key details about the asset or receivable account in question:
- Shifts in external market indicators, like changes in the cost of debt or equity.
- Signs of adverse operational or economic changes impacting the business.
- Negative trends in internal value indicators, such as a drop in credit ratings.
- Fluctuations in the market value of collateral or noticeable changes in repayment behavior.
- A steep decline in operating performance or frequent payment defaults.
By keeping an eye on these factors, businesses can better assess credit risk changes and stay ahead in managing expected credit losses calculations effectively.
Challenges in Updating an ECL Calculation Model
Companies often face several hurdles when revising their Expected Credit Loss calculation models, including:
- Difficulty in obtaining reliable external information, such as company ratings, macroeconomic factors, and discount rates, needed for accurate ECL calculations.
- Limited availability of detailed internal historical data to identify trends and tailor calculations effectively.
- Integrating company and industry-specific factors into the ECL model to reflect unique business characteristics.
- Proper documentation of the model and its underlying assumptions to facilitate seamless updates when required.
- Adapting the model to reflect significant business changes or economic fluctuations impacting the company’s operations.
Addressing these challenges is crucial to maintaining the accuracy and relevance of expected credit losses models in dynamic environments.
How AHG Supports You in Implementing and Reviewing ECL Calculation Models
With extensive experience working with diverse clients and a team specialized in IFRS accounting, AHG offers a range of consulting and advisory services to assist your business with Expected Credit Loss calculations, including:
- Addressing any questions you have about expected credit losses calculations and IFRS 9 requirements.
- Developing ECL calculation models tailored to your company’s specific assets.
- Assisting in documenting the rationale behind chosen approaches and key assumptions.
- Reviewing your existing ECL models to ensure they are complete and fully compliant with IFRS 9 standards.
- Helping integrate ECL models into ERP systems to streamline and automate calculations effectively.
If you’re looking for more insights on ECL calculations under IFRS 9 or have any questions, reach out to us for a one-hour free consultation. We’ll guide you through the latest updates and industry best practices to keep your business on the right track.
Conclusion
Thus we have come to know the most important points about ECL Under IFRS 9 vs. Impairment Provisions of IAS 39, Key Factors in the Calculation of Expected Credit Loss (ECL), Different Approaches for ECL Calculation under IFRS 9,How to Spot a Significant Increase in Credit Risk for ECL Calculation and Challenges in Updating an ECL Calculation Model.
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