FICO®scoring is the most misunderstood facet of credit reporting. Before undertaking any actions in an attempt to improve your borrower's score, it's important that you first understand "why they have the score they have." The biggest surprise to most loan originators is that your tri merge report hides most of your borrower's credit data.
"When reviewing a tri merge credit report, you are able to see only 1/3 of the consumer's actual credit history."
It's difficult, (depending on your credit provider - it may be impossible) to accurately assess your borrower's credit file based on reviewing a tri-merge report, as the logic used in creating the report, hides most (two thirds) of the consumer's credit data. Here's an example,
Most creditors report data to all three repositories (Experian, Trans Union and Equifax.) Every tri-merge report contains data from all three sources, but you don't want to see three examples of every trade line (three copies of each mortgage, car loan and credit card...) so CRAs employ a de-duping process we refer to as "pick and choose logic." Essentially, all examples of a given trade line are compared, and the most recent version containing the most derogatory data is selected and placed on your credit report. The other two versions of that item are suppressed and an abbreviation or code is added to the trade line to reflect which repositories contain data from that creditor. The problem with this method is readers assume that what they see on their tri-merge report is the same data that appears on the other "hidden" repositories - rarely is this the case.
This is why you can conduct a line-by-line review of a file that has significant differences in the FICO scores between the three repositories and be unable to determine "why" the scores are different. The answer is hidden in the 2/3rds of the data you cannot see. This is also the reason why so many rescoring attempts end in failure. Credit Technologies created a simple, free solution to this problem. With a single mouse click, we compare the data on all three repository files and highlights the variations. We call this the ability to see "the data behind the score". This makes it simple for you to determine why the scores are different, and what steps are required to reach the needed score goals...
Read the rest of this article at http://www.ctne.ws/fico