Implementing the Current Expected Credit Loss model (ASC 326-20): A roadmap

Entities that have not yet adopted should be preparing to implement the current expected credit loss (CECL) model for measuring credit losses, which is effective for fiscal years beginning after Dec. 15, 2022 (e.g., calendar year 2023). The following article provides financial statement preparers with an overview of CECL and observations to consider during implementation. While the CECL model is applied to financial assets measured at amortized cost, this article focuses on its application to financing receivables from parties that are not under common control. (Loans and receivables between entities under common control are not within the scope of the “Credit Losses” standard (Topic 326).)



    Accounting Standards Update (ASU) 2016-13 was issued by the Financial Accounting Standards Board (FASB) in June 2016 and has been codified, along with corresponding amendments thereto, as Accounting Standards Codification (ASC) Topic 326 “Financial Instruments – Credit Losses.” Subtopic 326-20 to the credit losses standard contains guidance on the CECL model and replaces the legacy as-incurred model based on guidance in Topics 310, “Receivables,” and 450, “Contingencies.” The application of the CECL model is expected to result in the earlier recognition of credit losses as compared to legacy methods of estimating allowances for uncollectible amounts.

    Applying the CECL model should result in the measurement of credit losses reflective of a reporting entity’s historical credit loss experience, as well as its current and expected credit loss-related activity. Accordingly, a reporting entity will use internal data (including both historical information and information derived from reasonable and supportable forward-looking forecasts) and may also incorporate external data when estimating credit losses. Under the CECL model, as outlined in ASC 326-20, reporting entities will recognize an allowance for credit losses as a reduction of the related pool of financial assets carried at amortized cost. The CECL model is applied to estimate credit losses on financial assets carried at amortized cost such as financing receivables, including loans receivables and net investments in leases; accounts receivables and contract assets; and off-balance sheet credit exposures such as financial guarantees and loan commitments.

    Expected losses should be measured using relevant information about past events and historical experience, current conditions, and reasonable and supportable forecasts. Forecast periods may or may not cover the expected term of the respective pool of financial assets. When developing the expected term of a financial asset pool, reporting entities should consider the average contractual term of such pool and the impact thereon of prepayment trends and expected recoveries (e.g., collateral repossession). For periods beyond those for which the reporting entity is able to reasonably and supportably forecast, the reporting entity will revert to historical loss information using a reasonable and consistently applied method, the “reversion method.”

    The CECL model should be applied on a collective basis by pool of financial assets with similar risk characteristics as of each reporting date. As stated in ASC 326-20-30-2, only if a financial asset does not share similar risk characteristics with the entity’s other financial assets would it be evaluated on an individual basis. A company should remove the asset from its pool or reassign it to a different pool when the risk characteristics change, such as if there is evidence of credit deterioration.

    Selected changes

    Expected credit losses

    When applying the CECL model established in ASC 326, entities estimate losses over the life of a pool of financial assets using pool-based assumptions to capture the risk of loss, even if remote, and incorporate credit loss estimates derived from reasonable and supportable forecasts reflective of assumed future economic conditions. This is a change from legacy U.S. generally accepted accounting principles (GAAP), which requires recognition when a loss is probable and the amount thereof is reasonably estimable. In addition, the CECL model broadens the range of data that is included in the measurement of the allowance for credit losses to include reasonable and supportable forecasts. As discussed above, entities will apply a reasonable and consistently applied reversion method for periods beyond those covered by a reasonable and supportable forecast, whereby credit loss estimates will revert entirely to historical loss information.

    Collateral-dependent loans

    Under ASC 326-20-35-5, a loan is collateral-dependent when the borrower is experiencing financial difficulty and the lender (i.e., the reporting entity) expects repayment thereof to be provided substantially through the operation or sale of the collateral for such loan. A reporting entity assesses whether a borrower is experiencing financial difficulty as of the reporting date. Consistent with legacy U.S. GAAP, the CECL model requires the estimate of expected credit losses to be based on the fair value of the collateral when the entity determines foreclosure is probable. For collateral-dependent assets where the borrower is in financial difficulty and repayment is expected to be provided substantially through operation or sale of the collateral, the standard permits the election of a practical expedient whereby, if elected, the allowance for credit losses, and therefore net carrying amounts, of collateral-dependent assets are determined based on the fair value of the collateral as of the reporting date. If the reporting entity determines that repayment or satisfaction of the loan depends on the sale of the collateral, then the fair value of such collateral is adjusted for estimated costs to sell.

    Loan commitments and financial guarantees

    As stated in ASC 326-20-30-11, the credit losses standard includes off-balance sheet credit exposures, unless unconditionally cancellable by the issuer thereof, not accounted for as insurance within its scope. Examples of such off-balance sheet exposures include commitments to fund loans and noncontingent financial guarantees. The expected credit losses liability for off-balance sheet credit exposures should be estimated in a manner similar to how the entity estimates its allowance for credit losses on its loan portfolio. For unfunded loan commitments not accounted for as derivatives, an entity should incorporate estimates of the likelihood that the loan will be funded and its expected credit losses on future fundings when estimating an allowance for credit losses thereon. When all or a portion of a commitment is funded, the reporting entity will adjust its allowance for credit losses for such loan.

    A financial guarantee of a borrower’s repayment in a lending arrangement is an off-balance sheet credit exposure of the guarantor and within the scope of ASC 326-20. An entity that has provided such a financial guarantee should recognize an allowance for credit losses representing the amount it expects to pay related to expected credit losses. In other words, an entity would recognize an allowance for credit losses on a pool of similar financial guarantees based on its current expectation of how much it will pay to fulfill such guarantees. The liability for expected credit losses on financial guarantees is recognized separate and apart from amounts recognized in connection with Topic 460 “Guarantees.”

    ASC 326-20-30-11 indicates that an entity’s allowance for credit losses on off-balance sheet credit exposures should be recognized as a liability on the balance sheet, and adjustments to the liability for the estimate should be reported as credit loss expense in earnings for each reporting period.


    The objectives of required disclosures under the CECL model remain the same as objectives of current required credit quality disclosures. The CECL model continues to require disclosures such as:

    • A description of credit quality indicators, the amortized cost basis by credit quality indicator, and the date (or date range) in which the credit quality indicator was last updated.
    • A description of the entity’s accounting policies and methodology and a description of factors that influenced management’s estimate, including past events, current conditions, and reasonable and supportable forecasts about the future.
    • A discussion of risk characteristics relevant to each portfolio segment.
    • Identification of changes to the entity’s accounting policies, changes to the methodology from the prior period, management’s rationale for those changes, and the quantitative effect of those changes.

    New disclosure requirements under the CECL model are, as written in ASC 326-20:

    • A description of how expected loss estimates are developed.
    • A discussion of the changes in the factors that influenced management’s current estimate of expected credit losses and the reasons for those changes (for example, changes in portfolio composition, underwriting practices, and significant events or conditions that affect the current estimate but were not contemplated or relevant during a previous period).
    • Reasons for significant changes in the amount of write-offs, if applicable.
    • A discussion of the reversion method applied for periods beyond the reasonable and supportable forecast period.

    CECL implementation roadmap

    Data analysis

    Start by assessing the data available to properly segment assets and determine the inputs into the CECL model. Identify what additional data is needed to prepare the CECL model. Examples of information that will be available internally include collateral type, origination year and maturity date, original and current loan balance, interest rates, payment history, historical loss information, prepayment estimates, and borrower credit data.

    External data potentially needed includes the Consumer Price Index, unemployment statistics, borrower trends, and peer data. Historical loss information gathered during internal information assessment can be adjusted for “differences in current asset-specific risk characteristics, such as differences in underwriting standards, portfolio mix, or asset term within a pool at the reporting date or when an entity’s historical loss information is not reflective of the contractual term of the financial asset or group of financial assets,” as described in ASC 326-20-30-8. The external data can be used to adjust historical loss data as well as develop the reasonable and supportable forecasts to adjust the historical loss information. Applying the CECL model is not only a finance function and may necessitate input from various departments, including credit, asset management, and finance, if those functions are established within a company. The CECL model estimate is scalable, and its level of sophistication is driven by the sophistication of the financial assets and the entity establishing the credit loss estimate.

    Asset segmentation

    Once available data is assessed, the assets should be segmented to estimate credit losses on the portfolio. ASC 326-20-30-2 requires a reporting entity to use a “pooled” approach to estimate expected credit losses for financial assets with similar risk characteristics. “If an entity determines that a financial asset does not share risk characteristics with its other financial assets, the entity shall evaluate the financial asset for expected credit losses on an individual basis,” the ASC states. “If a financial asset is evaluated on an individual basis, an entity also should not include it in a collective evaluation.” The risk characteristics chosen to segment the assets should be those that most impact credit performance.

    The ASC provides the following examples of risk characteristics for pooling assets:

    • Internal or external (third-party) credit score or credit ratings
    • Risk ratings or classification
    • Financial asset type
    • Collateral type
    • Loan size
    • Effective interest rate
    • Term
    • Geographical location of borrower or collateral
    • Industry of the borrower
    • Vintage (year originated)
    • Historical or expected credit loss patterns
    • Reasonable and supportable forecast periods

    For example, if the loan portfolio consists of loans collateralized by multifamily real estate assets across the U.S., the entity may determine a number of the above characteristics to be relevant, including risk ratings, remaining loan term, or year originated. If the loans in the portfolio are in the same geographic location and collateralized by various real estate asset types, with some being riskier than others, then collateral type may be the most relevant risk characteristic.

    Choose methodology

    An entity should select a method or methods that are practical and relevant given the facts and circumstances. The method or methods chosen may vary on the basis of the type of financial assets, the entity’s ability to predict the timing of cash flows, the information available to the entity, ASC 326-20-55-7 notes.

    Once a methodology is identified, an entity should quantify the cumulative historical losses incurred over the lifetime of the assets being evaluated. The guidance in ASC 326-20 indicates that the historical loss information should reflect the contractual term of the financial asset or group of financial assets. When determining how many periods to include when determining the historical loss information, an entity should consider various factors, such as whether the number of periods being used appropriately represents asset-specific risk characteristics and/or a full economic cycle. An entity may also choose the historical periods it wishes to include throughout the life of the assets.

    An entity “shall consider the need to adjust historical loss information to reflect the extent to which management expects current conditions and reasonable and supportable forecasts to differ from the conditions that existed for the period over which historical information was evaluated,” ASC 326-20-30-9 states. ASC 326-20 does not require an entity to develop reasonable and supportable forecasts over the contractual term of a financial asset, and these forecasts should not involve undue cost or effort. “For periods beyond which the entity is able to make or obtain reasonable and supportable forecasts of expected credit losses, an entity shall revert to historical loss information,” it states.

    The guidance does not specify a particular methodology to apply, but the following are examples of methodologies an entity may utilize when applying the CECL model:

    • Discounted cash flow: Based on the present value of expected future cash flows, discounted at the loan’s effective interest rate. This method will project cash flows over the life of the loan and should be adjusted based on projections, which would incorporate factors such as amortizing payments, prepayments, delinquencies, and defaults. 
    • Loss-rate: Loss-rate methods may be applied collectively or to individual loans, and are based on historical loss rates, as further described in ASC 326-20-55. Evaluate current conditions and reasonable and supportable forecasts to adjust historical loss rates to reflect current conditions and forecasted changes and apply the expected loss rate to the amortized cost basis by portfolio segment. An example of a loss-rate is the weighted average remaining maturity (WARM), which uses an average annual charge-off rate that is applied to the contractual term and is adjusted for estimated prepayments to determine the unadjusted historical charge-off rate for the remaining balances. FASB Staff Q&A Topic 326, No. 1 addresses whether the WARM method is an acceptable method to estimate expected credit losses. The FASB Staff Q&A indicates that the WARM method may be appropriate when applying the CECL model, but that care should be taken when selecting its use. For example, the WARM method is not appropriate for financial pools that lack homogeneity and that do not have a loss history with a predictive pattern. The WARM method, however, may be appropriate for larger pools with predictable loss histories. When considering the WARM method for estimating credit losses, reporting entities should make sure that the pools of financial assets to which the WARM method will be applied have been segregated to a level that creates a level of homogeneity and predictable loss history to substantiate its use.
    • Probability-of-default: This method generally considers the following for each pool of financial assets to which it is applied: (a) probability of default over a given time period; (b) amount of expected loss due to default; and (c) balance of the pool of financial assets.

    Management should consider the risks of its pooled assets and select a methodology that appropriately estimates losses in light of those risks. Once management determines which methodology to use, they will input the data to determine the estimated losses, and evaluate whether it appears reasonable. The methodology and results should be discussed with the audit/finance committee and other stakeholders as appropriate.

    ASU 2016-13 indicates that adoption of the CECL model requires a modified retrospective approach, meaning that an entity will record a cumulative-effect adjustment to the balance sheet as of the beginning of the first reporting period in which the guidance is effective, which is Jan. 1, 2023, for entities with a calendar year-end.

    Establish controls

    As the entity is determining the methodology and data inputs to use to properly calculate the expected losses, it should make sure appropriate internal controls are established and documented as well. The controls should address the implementation process as well as ongoing calculation and recognition, as well as address the involvement of the various functions and stakeholders. Policies should be updated to reflect the methodology adopted by management, sources of key data inputs, and rationale for judgments made. Many controls will already be in place from the entity’s legacy methodology, in which case existing controls should be reviewed to make sure they are adequate. An entity should establish additional controls when and if necessary. In addition to review and approval controls, consideration should also be made for access controls, such as password protection, and appropriate information technology controls to prevent loss of data.

    Ongoing monitoring

    It is recommended that the methodology be established prior to implementation to make sure there is adequate time for testing and reporting on the impact adoption will have. Once ASC 326-20 has been adopted, ongoing monitoring is necessary to make sure internal and external changes are reflected in the method used to estimate credit losses.


    Get in touch with our specialists

    View All Specialists
    Erin Todd headshot

    Erin Todd

    CPA, Partner
    lucas matesa

    Lucas Matesa

    CPA, Audit Partner

    Matthew Derba

    CPA, Partner

    Looking for the full list of our dedicated professionals here at CohnReznick?



    Let’s start a conversation about your company’s strategic goals and vision for the future.

    Please fill all required fields*

    Please verify your information and check to see if all require fields have been filled in.

    Please select job function
    Please select job level
    Please select country
    Please select state
    Please select industry
    Please select topic

    Related services

    Our solutions are tailored to each client’s strategic business drivers, technologies, corporate structure, and culture – addressing any industry-specific needs.

    This has been prepared for information purposes and general guidance only and does not constitute legal or professional advice. You should not act upon the information contained in this publication without obtaining specific professional advice. No representation or warranty (express or implied) is made as to the accuracy or completeness of the information contained in this publication, and CohnReznick LLP, its partners, employees and agents accept no liability, and disclaim all responsibility, for the consequences of you or anyone else acting, or refraining to act, in reliance on the information contained in this publication or for any decision based on it.