Understanding Calculation Settings—Primary Borrower and Credit Score Methods
January 2019

Identifying the primary borrower on any loan can be a tricky task—but it doesn’t have to be. This blog post will provide examples to guide you to an understanding on how this is done exactly in the Visible Equity system.

Please note (this is important!) that the blog post has two sections. The first section describes how to assign a primary borrower from various options. The second section describes a loan-centric approach for determining which score should be used for original, current, or previous credit scores—even if that score does not belong to your primary borrower.

Specifically for Visible Equity users, it may be helpful to view the Calculation Settings page in a separate tab as you read this post.


Section 1—Identify the Primary Borrower

Let’s first state the obvious. A lone borrower on a loan is the primary borrower. This setting really only matters when multiple borrowers are operating together on a single loan. With that, let’s quickly identify the three scenarios within the default “standard” setting for identifying a primary borrower.

Case 1. Single Borrower. When a loan has only one borrower, that borrower is the Primary Borrower.

Case 2. Multiple Borrowers—Primary Borrower Is Specified by Client. When a loan has multiple borrowers, an institution can specify which borrower should be listed as primary on the loan, as denoted within the data file containing the loan.

Case 3. Multiple Borrowers—Primary Borrower Not Specified. In the event a loan has multiple borrowers and none are specified as a Primary Borrower, Visible Equity will apply the following rules:

  1. First, check which borrower has both an original score and an updated score. If only one borrower has both scores, then that borrower is the Primary Borrower.
  2. Next, if multiple borrowers have both an original and an updated score, the Primary Borrower is the one with the newest updated score.
  3. Lastly, if multiple borrowers have both an original and an updated score and the newest updated score for all borrowers is the same date, then borrower with the highest score becomes the Primary Borrower.

Now, let’s use an example to identify which borrower will be primary when using our standard method versus the other non-standard methods. We have a loan with three borrowers—Mario, Luigi, and Yoshi. Assuming a loan origination date of 05/01/2017 and a reporting date of 11/30/2018 (understanding where you stand in reference to these dates is of vital importance!), refer to the information in the table below to identify the primary borrower in each scenario. The table shows a credit score and the associated pull date for each of our borrowers on the loan. In each scenario, we’ll identify the primary borrower and the calculated credit score migration.

Standard: Recall the three cases listed above to identify our primary borrower using the standard method. We have three borrowers, so the first case is out. Assume that a primary borrower has not been pre-designated within the data file containing the loan, forcing us to pass on the second case as well. So, using case three we look for borrowers with both an original and updated score. Yoshi does not meet that criteria and is ruled out. Mario and Luigi tie in terms of the newest date since both have a score on the 16th of October. To break the tie, we take the higher score—Luigi’s 725.

Primary Borrower: Luigi

Credit Score Migration: 675 to 725 = +50

To demonstrate this one step further, let’s assume that Luigi’s newest pull date remains as October 16th, but that Mario’s newest pull date was actually on October 30th. Also assume that both scores remain the same. Mario’s score of 655 is lower than Luigi’s 725, but Mario’s pull date is newer, and thus, Mario would be our primary borrower. The date plays a key role.

Highest Most Recent: The key in this method is that dates are excluded from the method logic. We have three borrowers, and therefore look at the current score for each of them, assigning primary to whichever borrower has the highest recent score. While it is true that Yoshi’s score was pulled nearly a year prior to his counterparts’ scores, neither Mario or Luigi can touch Yoshi’s 800 score.

Note that in this example the loan will no longer report any credit score migration. Why not? Well, because we are strictly assigning whichever borrower has the highest score right now, regardless of their history. Yoshi has no history behind the 800 score, and thus, no applicable migration.

Primary Borrower: Yoshi

Credit Score Migration: Not Reported

Highest Original: The key is in the title of the method—original. If it ain’t the original score, it don’t matter. The primary borrower will forever be determined by which borrower owned the highest score at loan origination. Then our primary borrower is Luigi, right? WRONG. Remember my parenthetical, italicized comment above the table? That’s where this comes in. This is part of separate discussion, (explained by this blog post!), but sufficeth to say that Yoshi’s score is counted as an original credit score because the date of his score is closer to the loan origination date than it is to our reporting date. If we were to view the same loan as of the 10/31/2017 data date, Luigi would be our primary borrower because he has the highest original score and because Yoshi’s score would be closer to the reporting date than the loan origination date. Tricky, eh?

Primary Borrower: Yoshi

Credit Score Migration: No Reported

Lowest: This is almost identical to our standard method. Like the standard, we need to have both an original and an updated score. Again, we look for the scores with the newest pull date. From there, instead of taking the highest score possible, we take the lowest. Mario and Luigi have the same pull date of October 16th, as previously stated. The lower score belongs to Mario, and he will be listed as our primary.

Primary Borrower: Mario

Credit Score Migration: 615 to 645 = +40

Lowest Most Recent: Just like the Highest Most Recent method, dates are excluded here. We look at the most recent score for each borrower and take the lowest score. Mario takes the cake again with this method.

Primary Borrower: Mario

Credit Score Migration: 615 to 645 = +40

Those are our current methods for identifying your primary borrowers. Note that based on the selected method, it could be perfectly reasonable for the primary borrower to change from one borrower to another based on the data presented in the reported data date. Does your institution do something different to identify primary borrowers? Read on to see what other customizations can be made to credit scores in Visible Equity’s Calculation Settings.


Section 2—Loan-Centric Credit Scores

In all of the examples above, we were dealing with different ways of determining the primary borrower and the credit score migration of that borrower. However, we do work with institutions that, for various reasons, prefer to report credit scores (including migration) on a loan level, rather than on a borrower level. As a result, a loan's credit score migration could be across two different borrowers. The settings described below, when tweaked appropriately, allow institutions to do just that. We’ll explain each one here and will use a similar table with some new numbers and dates. Assuming a loan origination date of 05/01/2017, a reporting date of 11/30/2018, and that we are using the Standard primary borrower method, refer to the table to identify which scores will be selected in each scenario. Again, we will determine which score is used and will calculate the credit score migration. In these cases, you’ll see that migration is being calculated between scores from different borrowers.

Mario is our primary borrower because, under the standard method for borrower designation, he is the only borrower on this loan with both an original and updated credit score. With a current score of 700, he has a positive 85-point credit score migration. Not too shabby, right? But, with other borrowers and scores to consider, we could change these loan-centric settings to report Mario’s loan in a different scoring bucket (for better or for worse) to change the migration score.

The default option for each setting is the standard method. When standard is used, a loan will only consider scores from the designated primary borrower and cannot cross scores from other borrowers on the loan. With that stated, we’ll limit our remaining discussion to the non-standard methods for each setting below.


Setting: Most Recent Credit Score Method

Highest Score: We have three borrowers and look at the most recently listed score for each of them while disregarding the score’s pull date. Yoshi has the highest recent score among the three borrowers, even though his most recent score is also his original score. Keep in mind that most recent does not necessarily mean updated—thus, Yoshi’s most recent 800 score will be used. Instead of the loan appearing with a 700 credit score, it will show an 800 score.

Will migration be calculated between the Mario’s original 615 and Yoshi’s 800 scores? Not quite. It is true that the 800 will appear as the most recent credit score on the loan; however, migration is calculated, by default, between original and updated scores. Yoshi’s 800 is not an updated score. Instead, we’ll use Mario’s 700 as our updated score to calculate migration.

Result: Yoshi, 800

Credit Score Migration: 615 to 700 = +85

Best Date, Highest Score: The date matters here. We are reporting as of November 2018, so we look at the recent scores for each borrower and find the score with a pull date that is closest to our reporting date. If an exact calendar date tie exists, we’ll use the better score. There is no date tie in our example, and Luigi wins outright based on his 10/30/2018 pull date. We will use Mario’s original score and Luigi’s recent score to calculate migration.

Migration is still going to be calculated on Mario’s scores of 615 and 700. Again, this is because we are dealing with most recent, not updated.

Result: Luigi, 680

Credit Score Migration: 615 to 700 = +85

Setting: Original Credit Score Method

Highest Score: Mario is our primary borrower, but perhaps we don’t want to use his original credit score to report on this loan. Yoshi’s higher 800 score is as of the origination date, so we’ll use that. This example actually does show migration being calculated between borrowers. Our original score is now an 800, and we migrate 100 points downward based on Mario’s updated 700 score.

Result: Yoshi, 800

Credit Score Migration: 800 to 700 = -100

Setting: Previous Credit Score Method

Previous credit scores are not as commonly used, so let’s quickly explain them. The previous score falls directly behind whichever score is counted as the updated score. If a borrower only has one score on a loan, no previous score exists; if our three borrowers had a total of 5 scores, 15 scores, and 100 scores to their names, respectively, then the previous score would be the 4th, 14th, and 99th scores, respectively. Make sense?


Highest Score: Yoshi has no previous score. Luigi’s previous score is 745 and Mario’s is 590. We’ll use Luigi’s higher 745 as the previous score on the loan. Credit score migration is typically calculated from the original score to the updated score, so I’ll show that result below.

Result: Luigi, 745

Credit Score Migration: 615 to 700 = +85

Setting: Updated Credit Score Method

Highest Score: While the date is technically excluded in this method, I’ll restate this key factor again. In order to be counted as an updated score, the score must occur after the original score. Yoshi’s 800 score cannot be used as a result. Luigi and Mario both have updated, non-original scores. Since we are not looking for the best date here, we’ll simply use the higher updated score—Mario’s 700.

Result: Mario, 700

Credit Score Migration: 615 to 700 = +85


While Mario remains our primary borrower, his scores were only used once out of the five examples listed above. In the other cases, scores from his co-borrowers were used, affecting the loan’s credit score migration in different ways.

As a final note, this section touched on how credit score migration is calculated. While the default is to calculated between original and updated scores, it is still feasible to report on migration in different ways, such as original to most recent or previous to updated. Visible Equity is equipped to help you report migration in this manner.


Do you feel comfortable with the settings your portfolio has in place? Maybe you’re asking yourself what you should do next, or if VE has any recommended settings. The standard options do work well in most cases. While it might feel strange to deviate from the standard settings, we could argue that the best option would be to use the Highest Original as the Primary Borrower Setting, and the Highest Score for the other credit score methods.

Hopefully this has given some helpful insight as to how these calculation settings are handled. Please contact our client success team if you’d like to change your portfolio settings in any way. We’ll be glad to help.

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