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Current Expected Credit Loss (CECL) Standard Update: Best Practices for Implementation

Written on January 31, 2018

Introduction to CECL

In June 2016, the Financial Accounting Standards Board (FASB) issued Accounting Standards Update (ASU) No. 2016-13, Financial Instruments – Credit Losses (Topic 326)

The current expected credit loss (CECL) standard marks a significant shift in the way credit losses on many financial assets, especially loans, are recorded. Under the standard, the ASU requires that banks estimate and record credit losses on loans and other assets (e.g., HTM debt securities) within the scope of the CECL model based on expected loss over the contractual life of the loan (considering prepayments). The goal of the new standard is to improve investor and financial statement user access to more timely information about credit losses and likely would require banks to record losses sooner than under current GAAP.

The standard applies to all banks, savings associations, credit unions and financial institution holding companies, regardless of asset size. More details on the standard can be found here.

While banks have until 2020 or 2021 to implement CECL, they must plan for adoption now. Most banks do not currently collect the level of disaggregated data that will be required to calculate the life of the loan estimate and should promptly begin exploring the right measurement method and new processes for their organization. Significant judgment will be required in forecasting, and banks should begin speaking with advisors and planning immediately. Bank executives should also start educating their finance executives, investors and stakeholders about the new standard and how it will change their metrics and integrate with budgeting and planning.

CECL Implementation Best Practices

CECL does not require that a particular method is used to estimate expected credit losses. Institutions can leverage practical methods relevant to the circumstance[1]; actual estimation methods will range anywhere from simplistic approaches to sophisticated models. For larger institutions, the decision to leverage predictive models may be straightforward. However, smaller institutions, especially those under $10 billion, are weighing the costs and benefits of a variety of approaches. Given the range of possibilities, many are struggling with the decision.

A Broad Spectrum of CECL-compliant Methods

A wide variety of methods, falling on a spectrum between a model-based and analytical approach will be considered CECL‑compliant.

  • A model-based approach leverages predictive models to forecast future borrower behavior based on statistical analysis of historical loss information. A modeled approach streamlines the reserving process and offers the most potential crossover use for risk management purposes. But these benefits are not without cost; the initial and ongoing investment in developing and maintaining models can be a significant barrier.
  • An analytical approach consists of personnel using subjective judgment to arrive at the expected credit loss based on analyses performed in spreadsheets. An analytical approach requires relatively low up-front investment and is easy to implement. However, a primarily analytical approach will resemble the qualitative adjustment process under the current collective reserve, which many banks consider to be onerous due to the high level of subjective judgment and manual nature of the process.

Regardless of the method used, the same objectives must be met: relevant variables need to be identified, the relationship between the variables and losses need to be estimated, and the entire end-to-end process will be subject to Sarbanes-Oxley controls.

The Enhanced Analytical Approach

Both the model approach and the analytical approach have advantages and disadvantages but, for some banks, the answer may be somewhere in the middle. SS&C Primatics refers to this as an enhanced analytical approach. Put simply, the enhanced analytical approach combines the advantages of a modeled and analytical approach and minimizes the disadvantages of each. An enhanced analytical approach applies more rigor and consistency to the reserving process than a purely analytical approach and allows the bank to leverage current reserving processes and data. Leveraging a simple, easy to understand model reduces risk and makes model risk management significantly easier than that of a complex model.

The Foundation of a Successful CECL Reserving Process

It is imperative to keep in mind that CECL preparation is more than just a temporary project. In other words, the decisions made between now and adoption (2020 for SEC filers, and 2021 for all others) will be part of a process that will continue indefinitely.

When evaluating a particular method, in addition to asking will this be compliant, banks should ask themselves, how will this contribute to a successful process in the long run? The distinction between compliance and success is an important one. CECL compliance means meeting the requirements in the standard. However, a successful CECL implementation is about more than just checking a box. The elements of a successful CECL reserving process will include:

  • An integrated process that joins the allowance estimate with data, disclosures and analytics in a controlled, scalable and repeatable manner
  • A dynamic reporting framework that conveys a cohesive narrative explaining what happened and why, period over period
  • A controls framework that includes full audit trails, role-based permissions, segregation of duties and data lineage

The basis of a successful CECL transition will require much more than a CECL-compliant estimate. Success will require taking a holistic view of the end-to-end reserving process and leveraging the right tools to get the job done efficiently and effectively.

[1]     Financial Accounting Standards Board (FASB) Accounting Standards Update (ASU) No. 2016-13, Financial Instruments-Credit Losses (326-20-55-7).

 

 

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