Does FICO’s minimum scoring criteria limit consumers’ access to credit?
Simply put, the answer is no. Over the last 30 years, FICO has continued to analyze the minimum amount of credit bureau data that is necessary to deliver a reliable, predictive FICO® Score to the market - which benefits both consumers and lenders alike.
As a reminder, we have found that at least 6 months of credit history, as well as data reported within the past 6 months, is required in order to best ensure that the consumer’s current financial position is sufficiently reflected. Our research has consistently found that models that rely solely on sparse and/or outdated credit information are less reliable at forecasting future performance.
Diving in a bit deeper, this means that, unlike with other scores in the market, consumers that just opened their first trade line, such as a credit card, would not be eligible for a FICO® Score before they have ever made a single payment. A payment history of at least 6 months is necessary to derive a consistently predictive and reliable credit score. At any time, there are approximately 2.5M consumers that have recently opened a credit account, but don’t yet have the necessary 6 months of repayment experience in order to obtain a FICO Score based solely on traditional credit bureau data. Allowing consumers to build their credit repayment history over six months before assigning them a FICO Score will result in a consistently more accurate assessment of their credit risk, and with it, confidence by lenders to extend credit to these consumers at more favorable terms.
There is a larger population of roughly 16.2M consumers that do not have sufficiently current credit bureau data to generate a score. These consumer files are often referred to as “stale” or “dormant” files. Within this consumer population there are two distinct groups that have very different credit profiles.
The first group of approximately 7.4M consumers are often referred to as the “credit retired” population. In examining the credit files of the credit retired population, we find that they tend to have overwhelmingly positive repayment history, but simply stopped using credit. As you might suspect, the general appetite for additional credit among this population is quite low, making up 1-4% of the total applicant pool. The median age of the credit retired population is 73 and time since the last update to their credit files is 4.5 years.
The second group of approximately 8.8M consumers are those that lost access to credit and generally appear to have encountered economic difficulty as they often have significant amounts of negative information reported in their credit files. With no new, positive data flowing into their files to offset the negative data present, these consumers would likely score too low to obtain credit. In fact, we estimate that some 94% of these “lost access to credit” consumers would be assigned a benchmark score[1] of 620 or below, perpetuating their lack of access to affordable credit.
The median age of this group is 43, considerably lower than the “credit retired” population, and still very much in a stage of life where credit access is important. This population can best be helped back onto the credit ladder by the use of alternative data that resides outside of the traditional credit bureau file, where a return to financial health can be observed and incorporated into a FICO Score calculation.
Delivering less predictive and often low scores to the market using only sparse and/or stale credit bureau data is not a recipe for helping consumers gain access to credit. FICO has found the answer to supporting lenders in identifying credit ready consumers is to augment traditional credit bureau data with FCRA compliant alternative data such as telecom, utilities, public record, and checking account data to provide a predictive and reliable score that lenders can use to responsibly expand access to credit.
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[1] For comparison purposes, we created a benchmark score that was built using only credit bureau data but that scored people by loosening the FICO minimum scoring criteria (which results in scores being calculated even when the only data available is very sparse or stale).
