By Jeff Mandel and Marlin Brandt
RISMEDIA, January 5, 2011—If you ask your neighbor, your friends or your banker what a credit score is, you’re likely to get all kinds of answers. Which of the following is right:
-Your credit score is technically a statistical method of assessing your ability and likelihood to pay back your debt (creditworthiness).
-Credit scores are based on several different factors, including your payment history, amount of outstanding debt, length of credit history, use of new credit and types of credit used.
-Credit scores are primarily based on credit report information, which is typically sourced from credit bureaus.
-Credit scores often come from any of the three largest credit bureaus in the U.S. (Experian, Equifax and TransUnion).
-Credit scores range between 300 and 990, depending on the scoring system and algorithms used (i.e., FICO, NextGen, CE Score and VantageScore).
Before there were credit scores, human judgment was the primary factor used to evaluate a borrower’s credit worthiness and/or risk. This process was very subjective and created a lot of variability in the results. Many lenders spent an enormous amount of resources training employees on how to observe consumer credit behavior as the basis for judging risk when lending money. Not only was this a slow process, but due to human error, it was also inconsistent and unreliable.
Lending institutions have created and used credit scoring systems in various forms for around 50 years. However, it was not until the 1980s that scores were somewhat standardized using a point system that scored the primary variables found on an individual’s credit record. This newer system helped to eliminate much of the subjectivity and variability that had existed with other attempts at standardization.
However, this process was still connected to the spontaneous measurements of the consumer’s credit report and did not consider the actual payment behaviors of a consumer.
Credit scoring took a major step forward when statistical models began using combinations of credit data. These next generation computer “predictability” models were designed to include payment information from thousands of consumers and were calculated based on a complex mathematical algorithm that generates a credit score the moment a report is ordered. There are literally trillions of score combinations used in the calculations. When combined with computer applications, scoring models have made the process of granting credit extremely efficient and much more objective. Although far from perfect, these models help facilitate commerce by expediting consumers’ ability to get the credit they need in a far more efficient and effective manner than the systems previously used.
As for your answers above, if you selected all, you were right!
Jeff Mandel is president and Marlin Brandt is COO of ApprovalGUARD.