Credit losses

What Are Credit Losses?

Credit losses refer to the amount of money a lender, such as a bank or financial institution, expects to lose or has already lost due to borrowers failing to repay their debts. These losses arise when a borrower defaults on a loan or other form of credit, rendering the outstanding balance uncollectible. Managing and accounting for credit losses is a fundamental aspect of risk management within the financial services industry, and they directly impact a firm's financial accounting and overall profitability. Credit losses represent a key risk exposure for any entity that extends credit, from large commercial banks to small businesses offering trade credit.

History and Origin

The concept of credit losses is as old as lending itself, evolving alongside the complexity of financial systems. Historically, lenders would write off bad debt only after it became evident that a borrower could not or would not pay, a method known as the "incurred loss" model. However, major financial crises often highlighted the shortcomings of this backward-looking approach, as credit losses were recognized too late, exacerbating economic downturns.

A pivotal moment for the recognition of credit losses occurred during the 2007–2008 credit crisis, triggered largely by widespread defaults on subprime mortgages. This crisis revealed how the delayed recognition of loan losses could propagate systemic risk throughout the financial system, leading to a freeze in interbank lending and substantial losses for financial institutions globally. The International Monetary Fund estimated that large U.S. and European banks collectively lost over $1 trillion from toxic assets and bad loans between January 2007 and September 2009.

In response, international and national accounting standard setters introduced forward-looking methodologies. The International Accounting Standards Board (IASB) issued IFRS 9 (International Financial Reporting Standard 9) in 2014, effective from January 2018, which introduced the Expected Credit Losses (ECL) framework. I⁵n the United States, the Financial Accounting Standards Board (FASB) released the Current Expected Credit Loss (CECL) standard (ASC 326) in 2016, which became effective for most public entities in 2020 and for private entities from December 2022. B⁴oth IFRS 9 and CECL aim to provide more timely recognition of credit losses by requiring entities to estimate future losses over the lifetime of a financial instrument, incorporating forward-looking information.

Key Takeaways

Credit losses represent the uncollectible portion of loans or receivables extended by a lender.
They are a primary component of credit risk, impacting a financial institution's profitability and balance sheet.
Modern accounting standards, such as IFRS 9 and CECL, mandate a forward-looking approach to estimating credit losses.
Timely recognition of credit losses is crucial for financial stability and transparent reporting.
Estimating credit losses involves significant judgment, considering historical data, current conditions, and future economic forecasts.

Formula and Calculation

Under modern accounting standards like CECL and IFRS 9, credit losses are generally estimated using an expected credit loss (ECL) model, which considers the probability of default (PD), loss given default (LGD), and exposure at default (EAD).

The basic conceptual formula for an individual exposure's expected credit loss is:

\text{ECL} = \text{PD} \times \text{LGD} \times \text{EAD}

Where:

(\text{PD}) = Probability of Default risk – The likelihood that a borrower will fail to meet its contractual obligations.
(\text{LGD}) = Loss Given Default – The percentage of the exposure that a lender expects to lose if a default occurs, after considering any recoveries from collateral or other sources.
(\text{EAD}) = Exposure At Default – The total value of the outstanding credit exposure at the time of default.

For a portfolio of loans, the sum of individual ECLs or a collective assessment based on similar risk characteristics is typically used to determine the total allowance for doubtful accounts.

Interpreting Credit Losses

The interpretation of credit losses depends on the context and the entity reporting them. For a bank, higher credit losses typically indicate a deterioration in the quality of its loan portfolio or a worsening economic downturn. This can lead to reduced profitability, as credit losses are expensed on the income statement, and may require the bank to set aside more capital.

Investors and analysts examine trends in credit losses to assess a financial institution's credit quality, underwriting standards, and overall financial health. A rising trend in credit losses could signal future financial distress, while stable or declining credit losses suggest effective risk management and a healthy economic environment. The reported allowance for credit losses also provides insight into management's expectations of future losses.

Hypothetical Example

Consider "Horizon Lending," a financial institution with a retail lending division. On January 1st, Horizon lends $100,000 to Client A for a small business venture.

Based on its historical data and current economic forecasts, Horizon Lending estimates:

Probability of Default (PD) for loans to similar new businesses: 2%
Loss Given Default (LGD) for unsecured business loans: 50%
Exposure At Default (EAD) for this loan: $100,000

Horizon Lending would calculate the expected credit losses for Client A's loan as:

\text{ECL} = 0.02 \times 0.50 \times \$100,000 = \$1,000

Even though Client A is current on payments, Horizon Lending would immediately recognize an allowance of $1,000 for expected credit losses on its balance sheet. If, six months later, Client A misses several payments and Horizon Lending reassesses the loan, they might determine that the credit risk has significantly increased due to the business struggling. The PD might be revised to 10%, triggering the recognition of "lifetime" expected credit losses rather than just 12-month expected losses, leading to a larger allowance for impairment.

Practical Applications

Credit losses are central to several areas within finance and banking:

Financial Reporting: Financial institutions and other businesses that extend credit must report expected and incurred credit losses on their financial statements in accordance with accounting standards like IFRS 9 or CECL. This provides transparency to investors regarding the quality of their assets.
L³oan Underwriting and Pricing: Lenders incorporate the likelihood of credit losses into their loan pricing models, charging higher interest rates or fees for borrowers with higher perceived default risk to compensate for anticipated losses.
Regulatory Compliance and Capital Adequacy: Regulators require banks to hold sufficient capital requirements against potential credit losses to absorb unexpected shocks and maintain financial stability. This often involves rigorous stress testing scenarios to evaluate resilience under adverse conditions.
Portfolio Management: Banks actively manage their loan portfolio by diversifying exposure, monitoring credit quality, and identifying concentrations of risk that could lead to significant credit losses. The management of non-performing loans is a critical component of this activity.

Limitations and Criticisms

While forward-looking credit loss models like CECL and IFRS 9 aim to improve financial reporting, they face several limitations and criticisms:

Complexity and Judgment: Estimating future credit losses requires significant judgment, complex models, and vast amounts of data, including forward-looking macroeconomic forecasts. This complexity can make the calculation process challenging, particularly for smaller institutions, and may introduce an elevated risk of management bias affecting the financial statements.
P²rocyclicality Concerns: A major criticism, particularly of CECL, is its potential to be procyclical. In an economic downturn, forward-looking models require banks to increase their loan loss provisions significantly, which reduces reported earnings and capital. This could lead to a reduction in lending precisely when businesses and consumers need credit the most, potentially exacerbating the downturn.
D¹ata Requirements: The models demand extensive historical data on credit performance and macroeconomic variables, which may not always be readily available or perfectly predictive of future conditions.
Volatility in Financial Statements: The need to frequently update expected credit loss estimates based on changing economic forecasts can lead to increased volatility in a bank's reported earnings and capital ratios.

Credit Losses vs. Loan Loss Provisions

Credit losses and loan loss provisions are closely related but distinct financial terms. Credit losses represent the actual or estimated amount of money that a lender will not collect from outstanding loans and receivables. It is the underlying economic loss due to borrower default.

In contrast, loan loss provisions are an expense item recorded on a bank's income statement to build up the allowance for doubtful accounts on the balance sheet. This allowance is a contra-asset account that reduces the net carrying value of the loan portfolio to reflect the estimated future credit losses. Therefore, loan loss provisions are the accounting entry made to anticipate and cover estimated credit losses, allowing banks to recognize these potential losses before they actually occur. While credit losses reflect the event of uncollectibility, provisions are the financial accounting mechanism used to set aside funds for those expected losses.

FAQs

Q: How do credit losses impact a bank's profitability?

A: When a bank recognizes credit losses, it records a corresponding expense (loan loss provision) on its income statement. This reduces the bank's net income and, consequently, its profitability.

Q: Are credit losses the same as bad debt?

A: Yes, in general usage, credit losses are synonymous with bad debt or uncollectible accounts. Both terms refer to amounts owed that are deemed unrecoverable.

Q: What is the main difference between the old "incurred loss" model and the new "expected credit loss" (ECL) model?

A: The old "incurred loss" model recognized credit losses only when there was objective evidence that a loss had occurred. The new Expected Credit Losses (ECL) model requires entities to estimate and provision for losses over the lifetime of a loan, incorporating forward-looking information, even if a loss event has not yet happened. This makes ECL more proactive and timelier.

Q: How do economic conditions affect credit losses?

A: Economic conditions significantly influence credit losses. In a strong economy, employment is high and businesses thrive, leading to lower default risk and fewer credit losses. Conversely, an economic downturn typically results in higher unemployment, reduced business profitability, and consequently, an increase in credit losses. Banks must factor these macroeconomic forecasts into their credit loss estimations.