Expected Credit Losses Background and Overview- I

Expected Credit Losses Background and Overview- I

Expected Credit Losses Background and Overview- I

  • Posted by kalyani
  • On December 7, 2023
  • 0 Comments

By

Share via

Share

Expected Credit Losses (ECL) is a financial accounting term that refers to the estimated loss an organization expects to incur from its loan portfolio over a specific period.

The concept of ECL is relatively new and has grown in significance within the banking industry, especially in the aftermath of the 2008 financial crisis.

Background of Expected Credit Loss

The Expected credit losses are governed by IFRS 9 as issued by IASB and ASC 326 as issued by FASB. The ECL model requires organizations to use historical data, current conditions, and reasonable and supportable forecasts to calculate the anticipated credit losses over the financial asset’s life. It also requires financial institutions to take a more proactive approach to managing credit risk, as they must recognize expected losses as soon as they are identified.

This proactive approach will lead to more accurate financial reporting, improved risk management, and better decision-making.

Global events that highlighted the need for change

The Financial Crisis Advisory Group (FCAG) was established by the FASB and the International Accounting Standards Board (IASB) amid the 2008 financial crisis to aid in the identification of potential enhancements to financial reporting.

Historically, U.S. Generally Accepted Accounting Standards (GAAP) for reporting credit losses relied on the “incurred loss” approach; under this methodology, recognition was postponed until the loss was likely.

Unfortunately, the global financial crisis of 2007 and 2008 brought this strategy’s inherent flaws to light. Due to their failure to meet the criteria from an accounting standpoint, several financial institutions could not record credit losses.

The market’s expectations and the accounting reports were at odds with one another because analysts devalued the securities while using their estimations and judgments based on forward-looking data.

The FCAG soon recognized the flaw in the incurred loss model for disclosing credit losses and recommended introducing substitutes considering historical data and future projections.

FASB-issued accounting standard update- Standards Issued

In 2016, the FASB provided Accounting Standards Update (ASU) 2016- 13 to resolve these issues with credit loss reporting.

  • Amortized cost basis reporting of impaired financial assets replaced previous rules in Codification.
  • ASU 2016-13 updated accounting for available-for-sale debt securities, requiring them to be assessed individually when fair value is lower than the threshold for credit losses, the amount reported under the amortized cost basis as outlined in Subtopic 326-30 Financial Instruments—Credit Losses.
  • Existing GAAP required an “incurred loss” methodology for recognizing credit losses that delayed recognition until it was probable that a loss had been incurred. Financial institutions and users expressed concern that this restricted the ability to record expected credit losses that did not yet meet the “probable” threshold.
  • More useful data about anticipated credit losses on financial instruments and other promises to extend credit is made available to readers of financial statements by ASU 2016-13. As a result, the incurred loss impairment approach for financial assets is replaced with a methodology that considers anticipated credit losses and necessitates considering a wider variety of reasonable and supported information.

Amendments to ASU 2016-13 through 2019-04

The FASB assisted stakeholders in implementing the amendments to ASU 2016-13, noting areas that needed clarification and correction. This led to the FASB issuing ASU 2019-04, which makes amendments to Topic 326 and other topics.

Entities and Industries affected

The financial services industry is not the only one affected by this update, as it applies to all industries. Companies were frustrated by accounting rules restricting them from booking more reserves, and investors had to develop their expected loss estimates based on less reliable external proxies.

The extent to which an entity is affected may vary depending on its asset composition and application of existing GAAP. Some entities will have an easier transition to the guidelines than others.

Applicability of ASC 326

ASC 326, known as the Current Expected Credit Loss (CECL) standard. The Financial Accounting Standards Board (FASB) announced an accounting guideline in 2016. The standard requires companies to measure and report their expected credit losses on financial assets, including loans, trade receivables, and debt securities.

The applicability of ASC 326 depends on the type of company and its reporting requirements. However, here are the main applicability criteria:

  • Public companies: For fiscal years commencing from December 15, 2022, as well as interim periods within those fiscal years, public corporations must implement the CECL regulation.
  • Private companies and EGCs: Based on the standard updates no. 2016-13, ASC 326 is applicable for the fiscal years commencing from December 15, 2022, as well as any interim periods during those fiscal years. Private companies must implement the CECL regulation.
  • Non-public business entities (NPEBs):NPEBs, which are not required to follow GAAP, are not required to adopt the CECL standard.

It is important to note that companies can adopt the CECL standard earlier than the mandatory adoption date.

Methods to Calculate ECL

Expected Credit Loss (ECL) measures the estimated average amount of losses a financial institution expects to incur due to default or non-payment of its customers. There are different methods to calculate ECL, but some of the commonly used methods are:

  • Probability of Default (PD) x Loss Given Default (LGD) x Exposure at Default (EAD) method: This method calculates ECL by multiplying the probability of default of a customer, the loss that the financial institution is expected to incur if the customer defaults, and the amount of exposure the financial institution has to the customer at the time of default.
  • Discounted Cash Flow (DCF) method: This method calculates ECL by estimating the expected cash flows from the customer’s future payments, discounted to their present value. The estimated future cash flows’ current value is then compared to the outstanding balance to determine the ECL.
  • Loss Rate method: This method calculates ECL by estimating the historical loss rates for similar loans or customers and applying those rates to the outstanding balance to estimate the ECL.

Aging Method:

This method is a common technique that is used to calculate the expected credit loss (ECL) of a loan portfolio or a financial instrument. This method estimates the probability of default and the expected loss over a given time horizon by grouping the loans or financial instruments into different categories based on age.

Challenges while calculating the Expected Credit Loss (ECL)

Calculating the expected credit loss (ECL) for a loan portfolio or financial instrument can be a complex and challenging task involving various uncertainties and risks. Some of the challenges that someone might face while calculating ECL include the following:

  • Data quality and availability: The accuracy of the ECL calculation depends on the quality and availability of data, such as historical default rates, loss-given default (LGD), and probability of default (PD). If the information is inaccurate, contradictory, or prejudiced, it can lead to inaccurate ECL estimates.
  • Estimating future scenarios: The ECL calculation requires future economic and borrower behavior assumptions. Evaluating these scenarios can be difficult, and errors in assumptions can lead to significant differences in ECL estimates.
  • The complexity of financial instruments: Some financial instruments, such as structured products or derivatives, can be complex and difficult to value, making it challenging to estimate ECL accurately.
  • Expertise and resources: Calculating ECL requires risk management, accounting, and finance expertise. Organizations may need to invest in training and hiring staff with the necessary skills and expertise to perform accurate ECL calculations.
  • Changes in market conditions: The ECL calculation is sensitive to changes in market conditions, such as interest rates, inflation, or unemployment rates. If market conditions change rapidly or unexpectedly, ECL estimates may need to be revised frequently to reflect these changes.

Challenges while implementing ASC 326

Here are some challenges that Private companies and EGCs may face while implementing ASC 326 – These companies often have limited resources. As a result, they may lack the sophisticated data analytics tools needed to comply with ASC 326. Additionally, private companies are not subject to the same level of scrutiny as public companies, which may lead to less rigorous documentation and testing of credit loss estimates. Finally, private companies face challenges estimating expected credit losses for less liquid financial instruments, such as privately held debt securities.

The main challenges companies face when implementing ASC 326 include the following:

  • Adopting new credit loss models.
  • Gathering data.
  • Establishing new internal controls.
  • Ensuring that financial reporting systems comply with the new standard.

5 steps Mode

The five steps model in Expected Credit Loss (ECL) is framework financial institutions use to estimate and account for credit losses. The five steps are as follows:

  • Identify the scope of the portfolio: The first step involves identifying the financial instruments subject to the ECL calculation. Financial instruments may include loans, trade receivables, and other assets with significant credit risk.
  • Assess the credit risk: The second step involves assessing the credit risk of the financial instruments in the portfolio. This involves identifying the likelihood of default, the amount of loss that could be incurred in the event of default, and the expected timing of the default. This step requires using historical data, macroeconomic factors, and other information to estimate credit risk.
  • Calculate the ECL: Once the credit risk has been assessed, the next step is calculating the ECL for each financial instrument in the portfolio. This involves using one of the methods mentioned earlier (such as PD x LGD x EAD, DCF, Loss Rate, or Statistical models) to estimate the expected credit losses for each financial instrument.
  • Recognize the ECL: The fourth step involves recognizing the ECL as a provision or an allowance in financial statements. The provision or allowance should reflect the expected credit losses for the financial instruments in the portfolio, considering the probability of default, the amount of loss that could be incurred in the event of default, and the expected timing of the default.
  • Monitor the ECL: The final step involves monitoring and updating the ECL regularly. The ECL should be reviewed and revised whenever there is a significant change in the credit risk of the financial instruments in the portfolio, such as changes in economic conditions or changes in the creditworthiness of the borrowers.

Conclusion

Expected Credit Loss (ECL) measures the estimated average amount of losses a financial institution expects to incur due to default or non-payment of its customers.

The calculation of ECL is a complex process that involves assessing the credit risk of the financial instruments in the portfolio, estimating the expected credit losses, and recognizing the ECL as a provision or an allowance in the financial statements.

The implementation of ECL is important for financial institutions as it provides a structured approach for estimating and accounting for credit losses, which helps to ensure that the financial statements give a reliable and accurate representation of the institution’s financial position and performance.

 5

0 Comments

Leave Reply

Your email address will not be published. Required fields are marked *