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Portfolio Risk & CECL CECL Accounting CECL Methodologies CECL Models

Crafting an effective CECL Q factor framework for stronger risk management

Kate Randazzo
October 9, 2024
Read Time: 0 min

How to build a successful Q factor framework under CECL

Understanding the quantitative side of the CECL calculation means developing defensible qualitative factors, or Q factors. Learn best practices to adjust for risk.

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Takeaway 1

Q factors offer a way to adjust for risks that aren't fully captured in historical data or quantitative models

Takeaway 2

Building a robust Q factor framework requires a systematic approach, regular monitoring, and periodic updates.

Takeaway 3

Smaller institutions can benefit from a streamlined approach focused on the most relevant, local risks.

CECL questions answered

How Q factors work under CECL

Qualitative factors, or Q factors, play a crucial role in calculating the allowance for credit losses (ACL), especially under the CECL (current expected credit loss) standard. As banks and credit unions adjust to this new accounting framework, questions around the development and control of Q factors under CECL have become a central focus—both for institutions and their auditors.

Before CECL, financial institutions often relied heavily on Q factors to supplement their allowance estimates, particularly when quantitative data was pressured by periods of strong credit quality. However, with the transition to CECL, many institutions questioned how these qualitative adjustments would evolve and what balance between quantitative and qualitative components auditors would expect. Today, Q factors offer a way to adjust for risks that aren't fully captured in historical data or quantitative models.

In this blog, we explore how banks and credit unions have adapted their approach to Q factors under CECL and share insights from an Abrigo advisory webinar on managing this critical part of the ACL process.

Understanding Q factors

Why Q factors are crucial to CECL success

The CECL standard, introduced by the Financial Accounting Standards Board (FASB), requires financial institutions to estimate expected losses over the life of a loan. This approach contrasts with the incurred loss model, which only required losses to be recorded once they became likely. Under CECL, institutions must account for both quantitative and qualitative factors to adjust for potential risks that historical data alone may not capture.

CECL Q factors are adjustments made based on qualitative considerations, such as changes in economic conditions, shifts in loan portfolio characteristics, or management decisions. These factors help address risks not adequately reflected in past data.

During Abrigo's Q factor webinar, Advisory Services Manager Zach Struble highlighted that a good framework "removes some of the subjectivity" that can come with making qualitative adjustments. He explained, "With a framework, especially something like a scorecard, we have an assessment of risk and an interpretation of what management thinks as well as a mathematical value that's tied to it."

The challenge for many institutions is determining how much weight to assign to each Q factor. As Struble put it, "Not all factors are created equal." He advised institutions to evaluate their specific risks and adjust accordingly. For example, "If you're an institution that operates on the coast, you probably have real seasonal risk from weather... that should carry much more weight."

Financial institutions frequently encounter evolving risks, many of which can't be quantified through historical loss data alone. This is where Q factors become essential, offering a way to adjust for future uncertainties, management's insights, and external factors such as regulatory changes or local economic shifts.

Without incorporating Q factors, an institution's CECL calculation might underestimate future losses, leading to compliance issues or missed opportunities to mitigate risks. 

Properly applied, Q factors allow financial institutions to make their risk assessments more forward-looking and comprehensive.

Learn more about qualitative factors under CECL with this whitepaper. 

Best practices

Key components of an effective CECL Q factor framework

Building a robust Q factor framework requires a systematic approach. Here are some best practices for setting up this framework:

  1. Identify relevant Q factors: Start by determining which qualitative factors are relevant to your institution. Typical Q factors include changes in underwriting standards, shifts in economic conditions, concentrations in specific loan types or industries, and changes in portfolio composition.

  2. Assign weights to Q factors: Not all Q factors will have equal importance. For example, local economic conditions might weigh more heavily for a regional bank, while a national institution might focus on broader market trends. Assign appropriate weights to ensure that the most significant factors are given priority in your calculations.

  3. Incorporate stress testing: Consider integrating stress testing into your Q factor framework. By simulating different economic scenarios, institutions can better understand how their loan portfolios might perform under adverse conditions and adjust their Q factors accordingly.

  4. Monitor and update regularly: A CECL Q factor framework is not a “set it and forget it” tool. Institutions should regularly review and update their Q factors to ensure they reflect current conditions. This is particularly important during periods of economic volatility, regulatory change, or significant portfolio shifts.

  5. Documentation and support: Regulators expect transparency in the CECL Q factor process. Financial institutions should document the rationale for each Q factor adjustment, including supporting data and evidence. This ensures that auditors can easily trace decisions and verify compliance.

The role of auditors and ongoing monitoring

As institutions implement CECL, auditors are paying close attention to Q factors. As Abrigo Advisory Services Manager Jared Mills pointed out, "The regulatory expectation is that if we’re going to have that much reliance on Q factors... then we will also have a good supportive model behind it." This means institutions must ensure that every Q factor adjustment is backed by data, whether it’s through a scorecard or a more informal approach.

Auditors want to see that adjustments are not only justified but also consistently applied. In addition to the initial setup, ongoing monitoring of Q factors is critical. Institutions should periodically review how their Q factors are performing, making adjustments as necessary to align with changes in market conditions or portfolio risk.

Regular reviews can also help identify areas where more or fewer qualitative adjustments are needed, ensuring that institutions remain compliant while also improving the accuracy of their credit loss estimates.

Looking forward

CECL Q factor considerations for community financial institutions

For smaller financial institutions, managing Q factors can be especially challenging due to limited resources or less complex risk profiles. However, this doesn't mean that Q factors are any less critical. In fact, smaller institutions can benefit from a more streamlined approach that focuses on the most relevant risks, such as local economic conditions or concentrations in specific loan types.

Leveraging automation and technology, such as Abrigo’s CECL software, can help smaller institutions manage these Q factors more effectively, ensuring compliance while freeing up staff to focus on other critical tasks.

Incorporating a strong Q factor framework into your CECL process is not only a regulatory requirement but also a strategic advantage. By addressing risks that aren’t captured in quantitative data alone, institutions can create a more comprehensive and forward-looking allowance for credit losses. Regular monitoring and updates to the Q factor framework will ensure that it remains relevant and effective in managing the uncertainties of the future.

If your institution is looking to improve its CECL process or needs guidance on Q factor implementation, Abrigo’s advisory services team is here to help. Contact us to learn more about how we can support your institution in building a robust CECL framework.

This blog was written with the assistance of ChatGPT, an AI large language model, and was reviewed and revised by Abrigo's subject-matter expert.

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About the Author

Kate Randazzo

Content Marketing Manager
Kate Randazzo is a Content Marketing Manager at Abrigo, where she works with industry thought leaders to create digital content that helps financial institutions better serve their customers. Before joining Abrigo, Kate managed social media and produced articles for Campbell University’s quarterly magazine and other university content initiatives. She earned

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