Taking out multiple loans to get more funding than would be approved for any one loan is something that both real consumers do, and fraudsters do when trying to get as much as they can out of a stolen identity. The challenge for online lenders is not just recognizing loan stacking, but recognizing which type of applicant it is. Recent data from a credit bureau shows that higher credit score consumers have higher charge-off rates with loan stacking, likely resulting from the fact that these are the identities fraudsters target to steal and monetize.
Loan stacking refers to a single consumer or identity taking out multiple loans or lines of credit in a short period of time. This can be in the form of identity fraud and repeat fraud attacks, where multiple loans are taken out in a victim’s name, or from consumers using their real identity information to take out more than one loan. This second group of loan stackers, real consumers, includes those who intend to pay back all loans and those who intended to default on them and are not concerned with credit rating repercussions.
With cases of identity theft or the use of “clean” identities, it is difficult to distinguish third party fraud from legitimate consumers. Organizations can track loan or application velocity, but typically can’t see the intent of the applicant, and not all loan stacking is bad. According to data from credit bureau TransUnion comparing consumer loans rated prime, loans that were stacked with others were 3.2 percent more likely to end up in default compared to non-stacked loans. It is expected that the default rate would be higher, as consumers who are loan stacking may over extend, but the default rate isn’t significantly higher compared to single or non-stacked loans.
By comparison, TransUnion also reports that stacked loans in the superprime segment are 10.5 percent more likely to default relative to non-stacked superprime loans. While superprime consumers are lower credit risk, in the case of loan stacking it is more likely that these are stolen or compromised identities. From a fraudster’s perspective, these superprime consumers are higher value targets, where they can get approved for greater loan amounts using the stolen identity.
This presents a difficult challenge in the online lending market: The lowest credit risk applicants, superprime loans, are also likely to include the most stolen identities and third party fraud.
Another challenge in detecting risk with loan stacking is that when using shared velocities and services that track an identity or device across multiple lenders, there can be velocity data on loan application activity, but this may be legitimate consumers shopping rates. That is, they can apply and be approved but not accept the loan, to see if they can find lower interest rates or fees elsewhere. According to data from ID Analytics, there is increased risk when velocity of loan applications rises, but primarily when all of the applications are submitted within a short period of time. They found that loans where applicants submitted just one application in the last hour had a default rate of 2.8 percent, compared to 6.3 percent of loans that submitted two applications in the past hour and 18.2 percent of loans that were the third application submitted in the past hour.
Online lenders, loan origination platforms and others that manage risk related to loan stacking can consider these data trends regarding superprime and high velocity applicants in fraud and credit risk management decisions. Additional resources related to online applications and loan stacking include The Fraud Practice’s white paper titled “Using Confidence Indicator Services to Enhance Qualification Capabilities in Online Applications” and Confidence Indicator Technique Page in our Fraud Library.
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