Understanding CECL - Current Expected Credit Losses

What is CECL?

CECL stands for “current expected credit losses.” It’s the new methodology for estimating allowances for credit losses issued by the Financial Accounting Standards Board (FASB). Previously, companies could calculate their bad debt reserve based on years past. For example, if last year a company wrote off $500,000 in bad debt from a handful of accounts, the next year they could earmark roughly the same amount for credit impairment. The FASB’s update now mandates that companies include forward-looking, or predictive, information in calculations of bad debt.

This change came about after the recession, which rendered the traditional approach – of preparing for the future by understanding the past – fairly useless. Businesses that only look backwards for future guidance were creating blind spots that could have potentially catastrophic effects. Just because a company paid you on time and in terms in the past doesn’t mean they’re going to do so in the future – and unfortunately, many companies learned this the hard way.

CECL requires companies to have a proactive view of their potential credit losses and record an impairment (deduction) to their revenues as a result of potential losses. These three tenets are among the most important:

  1. It requires forward-looking data: This means it’s no longer sufficient to solely consider prior losses.
  2. It requires that assets be grouped (“clustered”) by risk profiles rather than by type. This means loans and accounts receivable cannot be considered a single entity. Companies must be able to segment and define risk factors for each business relationship.
  3. It requires consistent reporting for losses across a company so that a partner, like an auditor, can stress test. This includes monitoring and revalidation based on both company-specific and overarching market indicators.

CECL Accounting Standard: Not Just for Banks

There’s a misconception that CECL only applies to financial institutions. The reality is it’s for almost every company that needs to be compliant with the Generally Accepted Accounting Principles (GAAP) – which means any company having a contractual relationship that will bring in cash in the future. Companies that extend business credit, for example, are obligated to be GAAP compliant. If your company issues the following, you’re required to comply with CECL.

  • Trade receivables
  • Loans
  • Net investments
  • Debt securities

CECL Effective Date Delayed

Public companies with more than $200 million in outstanding loans, receivables, or revenue that file with the SEC are required to start complying during their first reporting period after December 15, 2019. Private companies and the remainder of public companies have until the first reporting period following December 16, 2022.

CECL Model Example

A forward-looking loss forecasting model helps comply with existing regulations and also serves as an important tool for mitigating risks from credit impairments, which are inherent in a global customer portfolio. Remember, business losses begin with a single company in a portfolio. However, those single companies can be related to dozens or hundreds of other companies in a corporate family tree, which can have a domino effect on corporate exposure.

Dun & Bradstreet, as the global leader in commercial data and analytics, offers proprietary business insights that can effectively evaluate and rank the financial risk assigned to each account in your portfolio. These evaluations include things such as the likelihood of financial embarrassment (the D&B® Failure Score) or the likelihood that a business will no longer be viable as a going concern (the D&B® Viability Rating). Both would directly impact your ability to transform open receivables to cash. Incorporating backwards-looking historical data such as GDP, investment figures, employment figures, labor changes, and payroll changes won’t provide much predictive insight. Applying predictive analytics that are unique to Dun & Bradstreet can help US companies prepare and organize their approach to risk mitigation across their portfolio of accounts, based on the potential risk of credit losses.

New Considerations for Calculating a Bad Debt Reserve Model

Calculating a bad debt reserve model based on historical and current collections patterns can lead to incorrect assignment. One common strategy in such models is to cap the reserve at prior year losses and retrograde the reserve based on the age of the receivables. This clustering approach leads to the stair-stepping of the reserve, where exposure, if held at a higher rate for companies with balances over 90 days, is slightly less for those receivables between 60 and 90 days and even less reserve based on receivables open only 30 days past due. But assignment based solely on the receivables’ age is reactive to changing market conditions at best and, at worst, can lead to significant misclassification of risk. For example, if your receivables are clustered without consideration for the actual risk profile of the business, you might be restricting cash flow by withholding more than required for impairment.

Calculating a CECL-Compliant Bad Debt Reserve Model

The table below explains the differences in calculating a CECL-compliant bad debt reserve model:

Backward looking – Relying on historical and current collections patterns Forward-looking – Predictive approach using best-in-class machine learning and AI models built on the market-leading database of commercial unsecured trade experiences
Manual – Too many dependencies on manual exceptions, rendering models unable to scale Automated – Fully automated model building that combines both company-specific risk profiles and macro-economic factors
Reactive – Responsive to customer behavior Predictive – Incorporates changes to individual company performance and global market events to provide a fully integrated view of risk
Portfolio/Asset-Based – Segmentation based on asset class and type. Applying distinct measure independently and rolling up. Account-Level Risk Assessment – Evaluation of risk begins with a company, applies to all future obligations; adjust for loss based on time left in relationship

Automating Risk-Based Assessments for CECL Compliance

Another problem with calculating a bad debt reserve model based on historical and current collections patterns is that it limits your options for automation. Automating the impairment process is a goal for many organizations. However, using the legacy rate of write-offs based on age of receivables as the primary calculation often misclassifies high-value partnerships. For example, some major public companies pay late but are not in financial distress. This approach also fails to consider corporate exposure across the family tree, which means it ignores risk associated with a business partner’s hierarchical relationships. The best approach avoids clustering of receivables based on single characteristics, such as type or current delinquency. Consequently, Dun & Bradstreet considers the business’s overall risk, along with the effectiveness of collecting receivables as they age, to provide a complete assignment for reserve on an account-by-account basis through an automated risk-based assessment.

How Dun & Bradstreet Helps With CECL Compliance

While the FASB doesn’t require companies to use external data for CECL compliance, it does encourage the use of all valuable external data – and most companies using only internal data will find it difficult to meet all the requirements of the CECL outline: forward-looking, account-centric, predictive modeling that can be automated and is defensible. Current expected credit loss prediction begins by understanding your customers and the market at each point in history.

Dun & Bradstreet is uniquely prepared to support companies with stress-testing loss prediction models by including macroeconomic factors and predictions into the modeling. We provide a unique blend of micro- and macro-level analytics to ensure the broadest network of protections against unexpected credit losses. Our optimized loss forecasting models provide a repeatable, automated approach to loss forecasting and planning. We incorporate the assignable risk of a business, the interdependent risk among related business entities, and the age of the receivables to provide a framework that can more accurately reflect potential impairment, without overstating or understating the relationship. The approach doesn’t ignore the impact that aging receivables add to the risk of future collections; it automatically incorporates all mitigating factors to provide an empirical reserve that is balanced and appropriate.

With the aggressive timeline and encouragement to continue to improve loss forecasting models, the strategy behind CECL – look forward and anticipate change to truly reflect the potential risk of each contractual obligation – is both logical, practical, and ready to be adopted.

If you’d like to learn more about CECL, please email me and we can schedule a time to talk.