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.

Why you should consider using a qualitative scoring matrix

Sageworks
March 12, 2014
Read Time: 0 min

Banks and credit unions often cite the qualitative and environmental factors as one of their biggest challenges within the allowance for loan and lease losses (ALLL). During a recent webinar, Sageworks consultants discussed how to document qualitative factors. In addition to ensuring directional consistency, another consideration for justifying adjustments is to use a qualitative scoring matrix, as discussed in the clip below.

From the video:

Another way of documenting and applying the qualitative factors is to consider a qualitative scoring matrix. We have some snippets and examples from our ALLL solution up on our screen at this time. Essentially, the goal is to develop this qualitative scoring matrix and pick trend selections. As you see on our solution, I can select improvements: slight improvements, same, slight decline, decline, etc. You’re able to pick those and assign values to them, and you would then be more objective.

What’s an example to make this sound more clear? Well, imagine your economic risk factor; the economic qualitative factor you have. Rather than just saying, “Yeah, I’m going to put 10 basis points on that and make that happen,” or using that as a filler, the goal is to have a driver. As in, a piece of data or multiple pieces of data that back that. Now, I’m using the economic risk factors in my example because it’s the most common one used, it’s the most common one understood and has an almost agreed upon supporting data point. For example, unemployment index for your given area can be very supportive of that. So if that’s your key indicator, you could look at unemployment index and see it’s dropped. Therefore, it is an improvement, and you would then go and pick an improvement trend, which automatically has a value tied to it. It takes away that subjectivity part. You can say, “Oh, the trend of my data went this way, I saw it the same direction and it’s very clear.”

Now, you have to develop that matrix and keep that matrix locked in. If you go in and adjust values to the matrix over time, you’re making it more subjective because you’re altering it. It’s important to create it and keep it that way going forward. Considering a qualitative scoring matrix can be a very helpful way to document, defend and help limit the subjectivity that we said was a very big obstacle.

For more on how to add objectivity and directional consistency to the qualitative factors, download the whitepaper on qualitative risk factors.

About the Author

Sageworks

Raleigh, N.C.-based Sageworks, a leading provider of lending, credit risk, and portfolio risk software that enables banks and credit unions to efficiently grow and improve the borrower experience, was founded in 1998. Using its platform, Sageworks analyzed over 11.5 million loans, aggregated the corresponding loan data, and created the largest

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.