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CECL: Embracing Needed Change

Date: Feb 09, 2017 @ 07:00 AM
Filed Under: Risk Management

After years of deliberation dating back to the 2008 financial crisis, the Financial Accounting Standards Board (FASB) issued the highly anticipated Current Expected Credit Loss accounting standard (CECL) on June 16, 2016. After the financial crisis, the incurred loss model was criticized for recognizing insufficient losses too late because institutions were prohibited from reserving against future expected losses. In hindsight; this was most evident when loan-loss reserves were at their lowest in decades during the years immediately preceding the financial crisis.¹ CECL aims to avoid this scenario by requiring institutions to measure all expected credit losses for all financial instruments measured at amortized cost.

Industry experts, regulators, auditors and preparers, have deemed the CECL accounting standard one of the most impactful changes for financial institutions, with the potential for profound ramifications outside of the finance department. In order to generate an expected credit-loss estimate, financial institutions will implement new methodologies, consider a broad range of information and contend with a voluminous amount of data.

In addition to the reserving process, the transition to an expected loss model has the potential to change the way that financial institutions manage their business significantly. While CECL will not impact actual borrower defaults, the requirement to measure lifetime expected credit losses on all assets in scope at origination will result in earlier financial statement recognition of credit losses. Institutions may be prompted to revisit lending profitability measurements, loan underwriting criteria and interest rate pricing. Unbeknownst to the borrower, this could result in a more stringent review process and tighter lending criteria.

Although the FASB and regulators have asserted that many financial institutions will be able to leverage their current reserving and risk management frameworks as a basis for CECL implementation, all institutions face a project to get to CECL-compliant reserve estimates. Like any project, a roadmap will be necessary; however, before launching a gap analysis, institutions should begin to address the areas of management judgment that are integral to an expected credit-loss estimate.  These include:

  • Generating forward-looking estimates and evaluating modeling approaches. Loss estimation methodologies will evolve, especially for smaller institutions that may be implementing a forward-looking estimate for the first time. Institutions will need to identify practical approaches specific to their portfolios that meet the requirements of the standard. Take the decision to invest in an econometric model as an example. As noted above, it may be possible for institutions – particularly smaller ones – to leverage existing reserving systems. But it is a fair question to ask whether this will lead to an effective and efficient process in the long run. When determining whether to reflect the forecast in the allowance estimate primarily through qualitative adjustments vs. a modeled approach, institutions should assess the costs and benefits of an automated process while considering controls, auditability, ease of use, maintenance, anticipated impact to reporting and analytics, etc.
  • Considering implications for reporting and analytics. In addition to new disclosure requirements, analytics will be more important than ever due to the estimate’s sensitivity to changes in the forecast and the potential for volatility under the new framework. Institutions should anticipate questions from stakeholders, auditors and regulators - keeping in mind that CECL aims to promote transparency by providing financial-statement users with more decision-useful information about the credit risk inherent in the portfolio. Automated reporting that isolates changes in expected credit losses to changes in forecasted conditions and business environments at the instrument level will be optimal to meet the institution’s reporting requirements. 
  • Facilitating the integration of systems and data. CECL will broaden the range of information considered in the credit-loss estimate and is expected to result in an increase in the overall amount of data needed to estimate credit losses. Historical data such as loss and prepayment activity over the asset’s life, under a variety of economic conditions and the credit risk characteristics leading up to default, will serve as the basis for the estimate. Historical data will be combined with forecasted conditions to generate expected credit losses over the contractual life. During a recent survey of finance professionals conducted by SS&C, 47 percent of respondents cited managing massive amounts of data as their top concern related to the CECL transition. The integration of data and processes located in disparate systems - core banking, credit, finance, forecasts and models - will be critical to the reserving process and will be a major focus for many financial institutions over the next few years.

With an effective date of 2020 for SEC-registrants and 2021 for all others, institutions impacted by the accounting standards update have begun planning for their transition to CECL. Preparation for the CECL requirement is more than just a temporary project. When assessing the body of work required for the transition to CECL, institutions should begin with the end in mind. The decisions made during CECL preparation will be in place for the indefinite future. Best practices leveraging technology-enabled automation, and integrated risk and finance results can help banking professionals get the job done efficiently while delivering cost savings over the long term. Larger institutions may leverage sophisticated end-to-end technology to handle the reporting required by the new standard, while smaller institutions might choose to hire vendors to manage an a la carte selection of tools.
¹ According to FDIC data, loan loss reserves in 2006 were 1.5% for commercial banks, one of the lowest quarterly NCO rates for the industry

Head of Product Solutions & Operations | SS&C Primatics
John Lankenau is the head of product solutions and operations at SS&C Primatics. He has extensive financial services industry experience, with an emphasis on complex loan systems integrating risk and finance. In addition to building software, John’s experience includes auditing the models and estimation processes for some of the biggest financial institutions in the United States for a Big 4 firm. John is a frequent speaker on emerging issues such as CECL, the integration of risk and finance, and stress testing, as well as a regular contributor to industry publications. John has a bachelor’s degree in Mathematics and Economics from Carleton College in Minnesota and a Master’s degree in Operations Research from the University of Michigan, Ann Arbor.
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