Skip to main content

Looking for Valuant? You are in the right place!

Valuant is now Abrigo, giving you a single source to Manage Risk and Drive Growth

Make yourself at home – we hope you enjoy your new web experience.

Looking for DiCOM? You are in the right place!

DiCOM Software is now part of Abrigo, giving you a single source to Manage Risk and Drive Growth. Make yourself at home – we hope you enjoy your new web experience.

Looking for TPG Software? You are in the right place!

TPG Software is now part of Abrigo. You can continue to count on the world-class Investment Accounting software and services you’ve come to expect, plus all that Abrigo has to offer.

Make yourself at home – we hope you enjoy being part of our community.

CECL Q factors: Be ready to answer 3 questions

Mary Ellen Biery
June 24, 2024
Read Time: 0 min

Q factors under CECL vs. under incurred loss model

Understanding the quantitative side of the CECL calculation is the start to applying qualitative adjustments under CECL. Learn how to develop defensible qualitative factors, or Q factors.

Would you like other articles on CECL and Q Factors in your inbox?

This post was updated to account for the CECL standard's implementation across financial institutions.
Popular CECL Topic

What happened to Q factors under CECL?

Qualitative factors, or Q factors, play an important role in calculating the allowance for credit losses. But banks and credit unions have needed to adjust how they tackle developing these adjustments under CECL, the current expected credit loss standard. 

Q factors – more specifically, “What’ll happen to my Q factors under CECL?” was a popular topic among bankers before the final 2023 deadline for implementing the new accounting standard. Controls around Q factors remain important, since they are an area of attention from auditors and examiners.

Before CECL, many financial institutions often relied on qualitative factors for a larger percentage of their reserve when calculating the allowance for credit loss (ACL). That practice evolved as several years of good credit quality put downward pressure on the quantitative portion of the estimate under the incurred loss method. Financial institutions adjusted the qualitative portion of the allowance in an effort to ensure sufficient reserves.  

As banks and credit unions transitioned to CECL, a central question among them was how the use of Q factors under the new standard would compare with existing practices. Another common question from institutions was what percentage of quantitative vs. qualitative components would be expected by auditors and examiners. 

Abrigo advisors and outside CECL experts weigh in on the topics here.

First Step

Understand the quantitative analysis

While there’s no universal answer to either question because banks and credit unions and their loan portfolios and loss experiences can differ so much from each other, CECL experts agree that the first step to applying Q factors under CECL is a solid understanding of the quantitative side of your financial institution’s CECL calculation. After all, said Garver Moore, Abrigo Vice President of Strategy, “The purpose of the qualitative factors is to address what’s not in the losses expected from the quantitative baseline analysis.”

Graham Dyer, Chief Accountant and Accounting Principles Partner at Grant Thornton LLP, has said those involved in the allowance should consider three questions as it relates to Q factors. He outlined these questions as follows at a recent Abrigo  ThinkBIG Conference:

1. What is not captured by the model that requires you to make this adjustment?

2. Is the adjustment directionally consistent?

3. Is he adjustment quantitatively appropriate?

Justify the need for qualitative adjustments

“Tell me what is not in that model -- why you need an adjustment in the first place,” Dyer said.

Some methodologies necessitate the use of more Q factors than others, said Regan Camp, Vice President at Abrigo. “It really depends on the type of methodology you’re leveraging.”  The COVID-19 pandemic illustrates this. Quantitative models incorporating loss-rate forecasts based on unemployment estimates were complicated by the impact of government stimulus payments and other factors.

Documenting the reasoning behind adjustments tied to qualitative factors is important. “We continue to see clients making adjustments for things that we say, ‘Can you show me why that’s not captured by your model?’ And it’s not something they’ve considered,” Dyer said. Building that logic into the process of estimating the allowance is important. 

Support for the direction & amount

Whether the adjustment is up or down also needs to make sense, as does the amount of the adjustment. This last issue can sometimes be difficult for financial institutions to address, Dyer said. “Sometimes it’s helpful to have quantitative methods to try to put boundaries around those things as much as possible,” he said. “You at least have to tell me not just why I adjusted but why I made it this much.”

Experts also suggest scratching the numerical Q factor adjustments an institution used under the incurred loss model.

Learn more about qualitative factors under CECL with this whitepaper

Some financial institutions might say, “’Here are my Q factor adjustments. Do I keep that and start from there?’” said Gordon Dobner, Partner in BKD’s National Financial Services Group at ThinkBIG. But Dobner cautioned against a mindset of, " 'In incurred, I had 75 basis points. So that's my starting point.'”

Dyer agreed. CECL is a “wholly different approach” than the incurred loss methodology, he said. “I can’t see why you wouldn’t start from a pretty blank sheet of paper.”

Reliable, Consistent

A framework for Q factor adjustments

A qualitative scorecard for the allowance provides a framework that enables the financial institution’s management team to determine reasonable and supportable Q factor adjustments to the quantitative baseline estimate. The scorecard is a reliable and consistent mechanism that can be backtested against subsequent performance, too.

Here’s how scorecard development works:

  1. Review the quantitative model(s)/methodology that will be used to calculate the baseline loss estimate.
  2. Identify quantitative metrics that assist in framing various risk scenarios, from minor to major.
  3. Leverage peer analysis against historical loss experience to determine a high- and low-mark estimation framework.
  4. Identify appropriate scorecard frameworks to specific circumstances and institution preferences.
  5. Create a qualitative scorecard for each allowance pool based on the broadly or uniquely identified selections (or a combination of both).

Currently, many institutions use the same Q factor for the entire portfolio, but under CECL, qualitative adjustments may differ on a pool-by-pool basis. “Depending on the nature of the asset, not all of the factors may be relevant and other factors also may be relevant and should be considered,” according to a 2019 Frequently Asked Questions (FAQs) on CECL by regulators.

A qualitative adjustment scorecard can simplify the quarterly process of developing and documenting Q factors, especially if the scorecard can be interconnected with the financial institution’s CECL model.

“To assess a Q factor, you have to know what’s in the quantitative model and the limitations of it,” said Moore. “A qualitative scorecard, therefore, should ensure that the qualitative aspects are not ignorant of the quantitative aspects. They should ‘talk’ to each other.”

This is also an advantage of the scorecard when it comes to financial reporting from period to period. As credit losses associated with Q factors are recognized and the quantitative portion of the allowance is updated, the concomitant qualitative factor adjustments drop off the scorecard.

 

Conclusion

Adjustments to allowance estimates for qualitative factors didn't go away under CECL. And while it’s impossible to provide a blanket assessment of how every institution’s Q factor adjustments will compare to those under the incurred-loss method, it’s a certainty that auditors and regulators will remain focused on understanding the reasoning behind adjustments, as well as how the adjustments were determined. Using a qualitative scorecard can make this process easier and more consistent for financial institutions.

Effective model validation is key to compliance and success. Learn about the 4 Elements of effective CECL model validation

DOWNLOAD Keep me informed
About the Author

Mary Ellen Biery

Senior Strategist & Content Manager
Mary Ellen Biery is Senior Strategist & Content Manager at Abrigo, where she works with advisors and other experts to develop whitepapers, original research, and other resources that help financial institutions drive growth and manage risk. A former equities reporter for Dow Jones Newswires whose work has been published in

Full Bio

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.

Make Big Things Happen.