Future loss expectations

What Are Future Loss Expectations?

Future loss expectations refer to the anticipated financial losses that an entity, particularly a financial institution, expects to incur in the future. In modern financial accounting standards, this concept is primarily formalized as Expected Credit Loss (ECL). Unlike historical accounting practices that recognized losses only after they had occurred, future loss expectations require entities to proactively estimate and account for potential future losses, especially those arising from credit risk. This forward-looking approach aims to provide a more realistic and timely representation of a firm's financial health, enabling better risk management and capital planning for loan portfolios.

History and Origin

The evolution of accounting for future loss expectations stems largely from lessons learned during the 2007–2008 global financial crisis. Prior to this period, many accounting standards operated under an "incurred loss" model, where losses were only recognized when objective evidence of impairment existed. Critics argued that this approach led to a "too little, too late" recognition of losses, exacerbating the crisis by delaying the acknowledgment of deteriorating asset quality.
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In response, international and U.S. accounting standard-setters developed new frameworks that mandated a more forward-looking approach to credit losses. The International Accounting Standards Board (IASB) issued IFRS 9 Financial Instruments in July 2014, which became effective on January 1, 2018, for most affected companies. ⁴³This standard introduced the Expected Credit Loss (ECL) model, requiring entities to recognize expected losses over the lifetime of a financial instrument, considering past events, current conditions, and forecast information. ⁴¹, ⁴²Similarly, in the United States, the Financial Accounting Standards Board (FASB) issued Accounting Standards Update (ASU) 2016-13, commonly known as the Current Expected Credit Loss (CECL) model, in June 2016. CECL became effective for public U.S. Securities and Exchange Commission (SEC) filing institutions in the first quarter of 2020.. ³⁹, ⁴⁰Both IFRS 9 and CECL fundamentally shifted from an incurred loss to an expected loss approach, compelling organizations to anticipate and provision for future losses earlier.. ³⁸More information on IFRS 9 can be found on the IFRS Foundation website.

Key Takeaways

• Future loss expectations, primarily formalized as Expected Credit Loss (ECL), represent an accounting and risk management methodology to anticipate and provision for potential financial losses.
• This approach mandates that entities estimate losses based on current conditions, historical data, and forward-looking information, rather than waiting for losses to be incurred.
• The framework is a direct response to criticisms of prior accounting standards, which were seen as delaying loss recognition during economic downturns.
• The calculation of future loss expectations typically involves the Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD).
• Implementing future loss expectations requires robust data, advanced modeling capabilities, and continuous monitoring of credit risk factors.

Formula and Calculation

The most common formula for calculating future loss expectations, particularly Expected Credit Loss (ECL), involves three key components:

Where:

• (\mathbf{PD}) (Probability of Default) is the likelihood that a borrower will fail to meet their debt obligations within a specified timeframe. It is often estimated using internal credit risk models, historical default data, and external credit ratings.
  *³⁶, ³⁷ (\mathbf{LGD}) (Loss Given Default) is the percentage of the outstanding exposure that a lender expects to lose if a default occurs, after accounting for any recoveries (e.g., from collateral).
  *³⁴, ³⁵ (\mathbf{EAD}) (Exposure at Default) is the total value that a lender is exposed to at the time a default occurs. For loans, this might be the outstanding principal balance, plus any undrawn commitments that could be drawn down before default.

³², ³³These components are typically multiplied together to quantify the potential average loss across a portfolio of similar financial assets.

³¹## Interpreting Future Loss Expectations

Interpreting future loss expectations, particularly ECL, requires understanding the forward-looking nature of the estimate. A higher ECL indicates a greater anticipated loss from a loan or portfolio of loans. This figure is not a guarantee of actual losses but rather a probability-weighted average of potential outcomes. For financial institutions, the ECL directly impacts the provision for credit losses on their balance sheet, affecting reported earnings and capital reserves.

The interpretation also depends on the "stage" of the financial assets under IFRS 9. For instance, Stage 1 assets, where credit risk has not significantly increased, recognize 12-month ECL. In contrast, Stage 2 and Stage 3 assets (where credit risk has significantly increased or the asset is credit-impaired) require recognition of lifetime ECL, reflecting a more severe outlook on potential losses. ²⁹, ³⁰The shift to this model ensures that even for performing loans, a provision for expected losses is made from the point of origination, reflecting ongoing credit risk rather than waiting for an actual default.

Hypothetical Example

Consider a small business loan granted by a bank for $1,000,000 with a term of five years. At the time of origination, the bank assesses the following:

1. Probability of Default (PD): Based on the borrower's credit history and industry outlook, the bank estimates a 1.5% chance of default over the next 12 months.
2. Loss Given Default (LGD): If a default occurs, the bank expects to recover 60% of the loan value due to collateral. Therefore, the LGD is 40% (100% - 60%).
3. Exposure at Default (EAD): The outstanding loan balance at the potential time of default is expected to be $900,000.

Using the ECL formula, the bank's 12-month future loss expectations (ECL) would be:

The bank would record a provision of $5,400 as its initial expected credit loss for this loan, even though the borrower has not yet shown any signs of distress. This amount would be adjusted periodically based on changes in the borrower's creditworthiness, economic conditions, and other relevant factors, potentially shifting to a lifetime ECL if the credit risk significantly increases.

Practical Applications

Future loss expectations, particularly through ECL models, are fundamental to modern financial risk management and accounting across various sectors.

• Banking and Lending: Banks use ECL to assess potential losses in their loan portfolios, set appropriate capital reserves, and comply with regulatory requirements such as Basel III. ²⁸The Basel Committee on Bank Supervision's frameworks require banks to hold sufficient capital buffers against credit losses.. ²⁷Stress testing, often mandated by regulators, also incorporates a forward-looking perspective on potential losses under adverse scenarios.
  ²⁶* Corporate Finance: Non-financial corporations apply ECL to their trade receivables, lease receivables, and other financial assets to reflect potential credit losses in their financial statements. ²⁴, ²⁵This provides a more transparent view of the collectibility of their assets.
• Insurance: Insurers use future loss expectations to price policies and allocate reserves for anticipated claims, particularly in long-duration contracts where future payouts are uncertain.
  ²², ²³* Investment Management: Investors and analysts incorporate ECL assessments when evaluating the credit risk of debt securities and other financial instruments, influencing investment decisions and portfolio construction.
  ²¹* Auditing and Compliance: The new accounting standards necessitate rigorous internal controls and data governance to accurately estimate and report future loss expectations, requiring closer collaboration between finance and risk management departments.
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Limitations and Criticisms

While the shift to future loss expectations aims to improve financial reporting, the models and their application are subject to several limitations and criticisms:

• Complexity and Subjectivity: The estimation of future loss expectations, particularly PD, LGD, and EAD, relies heavily on complex statistical models and significant management judgment, especially regarding forward-looking economic forecasts. ¹⁷, ¹⁸, ¹⁹This subjectivity can lead to variability in estimates across different entities and may be susceptible to manipulation.
  ¹⁵, ¹⁶* Data Requirements: Accurate ECL calculations demand extensive historical data, current information, and reasonable and supportable forecasts of future economic conditions. ¹³, ¹⁴For some newer or smaller entities, or in unique financial products, adequate data may be scarce or difficult to obtain, making reliable estimates challenging.
  ¹²* Procyclicality Concerns: There are concerns that future loss expectations could be procyclical, meaning they might amplify economic downturns. During a recession, higher expected losses would lead to increased provisions, which reduces regulatory capital and could compel banks to cut lending, further tightening credit and worsening the economic climate.
  ¹¹* Forecasting Challenges: Predicting future economic conditions with accuracy is inherently difficult, especially during times of high uncertainty or unprecedented events like a pandemic. ⁹, ¹⁰The "reasonable and supportable" forecast horizon, which can vary, introduces a degree of estimation uncertainty. ⁷, ⁸The Global Association of Risk Professionals (GARP) discusses these challenges in their article "Are CECL and IFRS 9 Reasonable and Supportable?".

⁶## Future Loss Expectations vs. Incurred Loss Model

The fundamental difference between future loss expectations (as seen in ECL models like CECL and IFRS 9) and the incurred loss model lies in the timing of loss recognition.

Under the traditional incurred loss model, losses on financial assets were only recognized when there was objective evidence that a loss event had occurred. This backward-looking approach meant that banks and other entities could not provision for potential losses until a default was probable or actual, leading to delayed recognition of credit deterioration. ⁵For example, a bank would only record a loan loss reserve when a borrower missed payments or filed for bankruptcy.

In contrast, future loss expectations, driven by the ECL framework, require entities to anticipate and account for losses over the entire expected life of a financial instrument from the moment it is originated. ³, ⁴This is a forward-looking approach that considers historical experience, current conditions, and reasonable and supportable forecasts of future economic conditions. ¹, ²Even for loans that are currently performing well, an entity must establish a reserve for potential future losses. This shift aims to provide a more timely and comprehensive reflection of credit risk on the balance sheet and in earnings, ultimately fostering greater financial stability.

FAQs

Q1: What is the primary purpose of future loss expectations?

A1: The primary purpose of future loss expectations is to enable more timely and forward-looking recognition of potential financial losses, particularly credit losses, in an entity's financial statements. This helps provide a more accurate picture of financial health and encourages proactive risk management.

Q2: How do future loss expectations differ from traditional accounting for losses?

A2: Traditional accounting often used an "incurred loss" model, where losses were recognized only after they had occurred. Future loss expectations require entities to anticipate and provision for losses based on forecasts and probabilities, even before an actual loss event has taken place. This makes accounting for financial assets more dynamic and responsive to changing economic conditions.

Q3: What are the key components used to calculate Expected Credit Loss (ECL)?

A3: The three key components are the Probability of Default (PD), which is the likelihood of a borrower defaulting; the Loss Given Default (LGD), which is the percentage of exposure expected to be lost if a default occurs; and Exposure at Default (EAD), which is the total amount exposed at the time of default.

Q4: Are future loss expectations only relevant for banks?

A4: While initially a significant focus for banks due to their large loan portfolios and regulatory frameworks, future loss expectations (ECL) apply to a wide range of financial institutions and non-financial corporations that hold financial assets like trade receivables, lease receivables, and other debt instruments.

Q5: What are some challenges in implementing future loss expectations?

A5: Key challenges include the complexity of developing and maintaining robust models, the reliance on subjective forward-looking economic forecasts, the significant data requirements, and concerns about potential procyclicality, where increased loss provisions during downturns could exacerbate economic stress.