CECL –WHY IT’S A BIG DEAL AND WHAT YOU NEED TO KNOW TO FULFILL YOUR OVERSIGHT ROLE
New Jersey Bankers Association Annual Conference
May 2017
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TODAY’S PRESENTERS
Faye MillerPartner, National Professional Standards [email protected]
Martin CaineMember of the Firm, Wolf & Company, [email protected]
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WHAT IS CECL?
CECL (Current Expected Credit Losses) Vastly different approach for establishing the allowance and recognizing credit losses Applies to loans/leases, other receivables, commitments to lend and HTM securities
Comes into effect in 2020 for CYE SEC filers and 2021 for all others Early adoption permitted 2019
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WHY IS CECL A BIG DEAL?
Significant increases to the allowance are likely Provide for expected losses rather than incurred Even if risk of loss is remote Recognize allowance on purchased financial assets Limited circumstances in which you can conclude based solely on the collateral that no allowance is necessary Recognize expected credit losses on HTM securities regardless of impairment status
Ramifications to regulatory capital ratios
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MANAGEMENT ACTION ITEMS
Analyze requirements and assess needs Internal/external expertise Data Systems/applications
Develop plan Implementation timeline/team Methodologies/processes/controls Filling data gaps Modify current systems or invest in new Monitor developments and discuss with constituents
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MANAGEMENT ACTION ITEMS
Test, refine and implementMonitor progress/adherence to timeline Decide on early adoptionMonitor developments and refine as necessary Regulatory views, TRG interpretations, feedback from auditors Conduct independent assessments/test internal controls Run parallel approach and refine Address ramifications to capital, credit extension, investment philosophy, etc
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Implementation Considerations
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Determine Loan Pools
Identify an appropriate methodology
Obtain sufficient historical loss data
Implementation Considerations
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Determine Loan Pools
Identify an appropriate methodology
Developreasonable and supportable forecasts
Obtain sufficient historical loss
data
LOAN POOLS
Loan pooling is a critical decision point; impacting all subsequent actions.
The concept of “impaired” loans is eliminated – an estimated credit loss should only be measured individually if there are no similar risk characteristics with other loans.
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PURCHASED CREDIT DETERIORATED ASSETS (PCD)
Will be able to gross up the allowance for expected credit losses for purchased assets with a more than insignificant deterioration in credit quality.
This will be applied more broadly to purchased loans than the current accounting for purchased credit impaired loans, which generally only applies to impaired assets.
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APPROPRIATE METHODOLOGY
The standard is explicitly scalable and allows preparers to develop estimation methods that are appropriate and practical for their circumstances. FASB concluded that different outcomes for expected credit losses are acceptable, given different levels of complexity and sophistication. One model but many methods Methodology by loan segment should be determined early; relevant data (i.e. historical losses, risk characteristics such as geography, LTV, vintage, etc.) and software needs may vary. Industry standards and best practices will emerge.
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CHOOSING A METHOD
Choosing a method is a critical decision point
One model but many methods Historical loss‐rate (most common method now) DCF Vintage analysis Migration analysis/ Roll‐rate Probability‐of‐default/exposure at default/loss given default Other ?
Entity required to apply judgment to develop estimation methods that are appropriate, practical, and consistent with the principles of the guidance, while being consistent with strategic direction i.e. scalable)
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HISTORICAL LOSS DATA
An entity’s loss history loss remains as the starting point and generally provides a basis for expected credit losses.GAAP does not specify a particular methodology for determining historical credit loss experience. “That methodology may vary depending on the size of the entity, the range of the entity’s activities, the nature of the entity’s financial assets, and other factors.” [ASU 326‐20‐55‐2] The loan segment and the chosen method will determine the data needs. Consider the impact of loans that will be assessed individually (removed from the pool)
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REASONABLE AND SUPPORTABLE FORECASTS
The adjustments for current conditions and reasonable and supportable forecasts may continue to be qualitative, similar to the approach applied by many institutions today.
More robust quantitative models and/or greater segmentation may result in a smaller qualitative component, depending on the circumstances. Q‐Factor adjustments may be more significant because of the life‐of‐loan measurement period. Qualitative analysis may not always be directionally consistent with current trends/events.For example, an increase in delinquency rates may have been previously considered/anticipated when estimating expected credit losses.
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IMPACTS OF CECL STANDARD ON SECURITIES AFS
Impairment accounting for AFS debt securities:
Currently – Credit losses are recorded as direct write‐downs based on expected cash flows. Subsequent increases in expected cash flows are amortized to interest income.
New –Use of an allowance is required to record impairment, which will allow for reversal if the value subsequently increases. Certain other refinements are included in the standard.
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GOVERNING BODY QUESTIONS TO ASK
Is tone at the top appropriate?
Are internal/external resources sufficient and qualified?
Is there a detailed plan with key milestones completed as planned?
Are appropriate policies, procedures and controls in place?
What independent assessments will be performed?
What information will be made available to governing body?
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SUPPLEMENTARY SECTION ‐ EXAMPLES
The FASB material is copyrighted by the Financial Accounting Foundation, 401 Merritt 7, Norwalk, CT 06856, and is reproduced with permission.
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EXAMPLE – PROBABILITY OF DEFAULT METHOD
Expected loss = Probability of default x Loss given default x Exposure at default
Bank has a pool of loans with an outstanding balance of $30 million. Management estimates the probability of these loans going in to default to be 5% and the loss given default to be 20%.
5% x 20% x $30 million=$300,000 expected losses
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