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Assessing Prospective CECL Methodologies: Vintage

Brandy Aycock
April 28, 2017
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Part of a MST Blog Series examining prospective CECL-compliant methodologies 

The road to CECL compliance ends in identifying the CECL methodology (or methodologies) that best suits the institution and its loan portfolios as well as complies with CECL guidance and regulator demands. 

All the activities involved in preparing for CECL – gathering and assessing the quality of your loan data, internal planning and third party counsel, analysis and testing – have one ultimate goal: to identify the most suitable CECL methodology or methodologies for your institution.

A suitable methodology is one that accommodates your particular loan portfolio; is efficient as well as compliant; proves through shadow analysis and stress testing to provide a defensible and accurate as well as reasonable and supportable allowance forecast; and has the least negative effect, perhaps even a positive impact, on earnings and operations.

FASB has been steadfast in not specifying or even suggesting appropriate CECL methodologies. Because each institution is different, with different types of loan portfolios and different underwriting principles, the method or methodologies you choose must be determined by your unique blend of products, portfolios and markets as well as the quality and quantity of your available loan level data.

“Lenders pride themselves and differentiate themselves by their underwriting,” MST Advisory’s Shane Williams said. “Each lender does it differently and usually markets that as a reason to do business with them. Differentiators in underwriting include geography, debt coverage, collateral values, terms, guarantees and numerous other criteria that separate one institution from another. If a lender has its own way of underwriting, then it should have its own risk profile and deserve specialized modeling to forecast that risk. Customized analysis and modeling are required.”

That doesn’t mean a lender has to build its methodology from scratch, only that it must choose a methodology based on its own policy and circumstance. Most institutions have relied on historical loss analysis to estimate their allowance under the incurred loss standard, but under a rule that requires estimating loss based on assumptions that start on day one of the loan and follow it to its likely conclusion, an estimate based simply on what happened last year won’t fly – or comply. Given the need to adopt a more sophisticated methodology, most institutions will have to consider methodologies other than historical loss, though their loss histories will certainly be included in the calculus.

For insights on prospective CECL methodologies, we asked the advisors of MST Advisory, consultants helping lenders through the discovery and decisions that will lead to choosing and implementing a CECL methodology.

Vintage Methodology

Vintage is essentially a method for pooling, Shane Williams explained, wherein loans are organized by their date of origination, year to year.

“I prefer the vintage method,” he said of his work with MST Advisory clients, “but the challenge is that losses have been minimal over the last few years and most institutions don’t have enough loss data to estimate expected losses. When you segment by year and every year is zero, you don’t have trendable performance.

“You do have to report in a vintage fashion for CECL,” he added, “but for modeling purposes we have been going back to looking at cohorts, watching the behavior of those loans over time, not segregating them by year. That’s how we’re finding sufficient loss data to create an estimate.”

“The vintage model is helpful because you can aggregate the loans by origination dates into pools with loan level information,” explained Shelly Biggs. It also allows the bank to develop and understand the loss curve, so they can more easily see where a certain cohort of loans – subsets of loan-to-value and FICO, etc. – are likely to encounter losses, then manage their portfolios accordingly.

“A vintage methodology is appropriate for lenders with a wide range of loan types and therefore multiple loan pools,” Biggs said. “It is typically used for consumer, small balance loans where there are many loans in a pool. It is a less stringent process as it allows the lender to determine an expected loss of one pool of loans and apply it to other similar loans of other vintages. It is also helpful in refining underwriting guidelines based on loss history of certain characteristics. For example, changing FICO and loan-to-value levels in the guidelines. ”

To estimate according to a vintage methodology:

  • Identify vintage pools and segregate loans by vintage by FICO or loan-to-value bands
  • Calculate loss rates for each vintage
  • Determine historical losses for each vintage
  • Adjust for pool-specific factors, including development and monitoring of risk appetite metrics
  • Adjust for economic variables and other qualitative and quantitative factors
  • Apply that cumulative loss as an expected loss to other similar loans of outstanding vintages

“A lender needs comprehensive origination as well as current loan-to-value information for a vintage approach to be useful,” Biggs said, adding that borrower FICO scores are also key to an accurate loss projection. “Data must be reconciled to the general ledger, and there must be no gaps in the data. If there are gaps, they must be addressed to get an accurate reading. If the gap is in the origination loan-to-value data, the institution will likely have to turn to public data, such as the Case Schiller Home Price Index, to fill it.”

She noted that institutions should treat loans with policy or underwriting exceptions separately. “You will have to assign a factor to loans with exceptions so it is apparent in a vintage estimate. Exceptions can be a separate vintage analysis. Regulators also review loans with underwriting exceptions and look for production where these exceptions are limited. Exceptions are something your regulator is certain to ask about.”

 


About the CECL Methodology Panel

Dorsey Baskin is recently retired from the National Professional Standards Group of Grant Thornton LLP and serving as an independent consultant to MST Advisory clients. His roles at Grant Thornton included national leadership of the firm’s innovation function, technical accounting and audit advisor for the banking industry audit and consulting practice, and national professional practice director.

Shane Williams, a senior advisor for MST Advisory, works with banks and credit unions to set priorities, identify data needs, implement allowance technology, run shadow analyses and identify appropriate methodologies in preparation for accounting for loan losses under CECL.  Shane counts more than 25 years of financial and risk management experience as a banker, in software development and delivery, and as a consultant to major financial institutions.

For more than 30 years Shelly Biggs has provided leadership in risk management expertise as an executive with and consultant to the nation’s largest financial institutions. Her areas of expertise include: Development of risk and reporting framework, ALLL, CECL, corporate finance (quarterly SEC reporting), reconciliation of finance and risk data, regulatory reporting and earnings call reports. Shelly has provided Risk Management related guidance for lending practices for commercial (CRE & C&I), mortgage, consumer (auto and credit cards) credit topics, including loan underwriting, due diligence, appraisal review, portfolio analysis, loan loss modeling, organization of the credit department, development of credit policies and procedures, risk and credit management reporting, management of regulatory recommendations and complex projects. Shelly is an advisor with MST Advisory.

Learn more about MST Advisory Services.

 

 

About the Author

Brandy Aycock

Brandy Aycock is Director of Event Marketing at Abrigo.

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About Abrigo

Abrigo enables U.S. financial institutions to support their communities through technology that fights financial crime, grows loans and deposits, and optimizes risk. Abrigo's platform centralizes the institution's data, creates a digital user experience, ensures compliance, and delivers efficiency for scale and profitable growth.

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