Driver’s License as a fraud prevention tool

Adding Driver’s License (DL) validation into your fraud prevention strategy can help you detect fraudulent applications. One of the reasons is that DL number is not easy to steal. Typically, when an identity is being stolen, victim’s information may include name, address, DOB, phone number but DL number is usually not included. That leads to the fraudster having to make up a DL number for this stolen identity.

At Clarity, we examined our data to detect invalid or fraudulent DLs. Here is what we found:

Over 92% of all applications that Clarity had seen in the first quarter of this year had the valid format for the state that was entered. What this tells us is that legitimate consumers are taking the time to enter in the information correctly. Compare that to the 40% of identified fraudulent applications that used a valid format. When further comparing the DL to actual state DMV records, only 29% of identified fraud applications pass verification compared to over 90% of all applications.

As an example, the majority of the applications from two of the fraud rings highlighted in this fraud bulletin have used incorrect DL Number format. In the first three months of this year, Excel Vision has 79% incorrect DLformat on the  applications. The Texas Yahoos has 81% incorrect DL format on the applications. Identifying an incorrect DL format can help us spot fraud as well as help link fraudulent applications together, particularly when it is a key part of an identified fraud ring’s MO. But, unfortunately, the data also tells us that this single data element is usually not accurate enough to decline an applicant. What needs to be explored is how accuracy can be increased by combining an incorrect DL format with other application inconsistencies such as when the home telephone area code is inconsistent with the address, an address is high risk or non-residential, or when there are a lot of phone number or email address changes in the past

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Steps you can take to decrease fraud

Accuracy can also be increased with cleaner data and higher collection rates. We have identified some issues to address around the DL that we feel will help all of us tremendously in our fight against fraud.

  • Collect DL.  Make the fraudsters work a little harder. Every reasonable piece of PII that you require will tend to drive the fraud to venues that require less.
  • If you notice that a certain source of application data is consistently giving you incorrect DL information find out if the information is coming from them or the consumer. For instance, we have seen a rash of Soundex DLs sent to us from non-Soundex states that are not fraud. Bad data makes legitimate applications look like fraud and limits your ability to use DL to identify fraud.
  • Examine the DL carefully. Use at least a basic DL validation tool. Although coverage is low, also use a DL verification tool, when available. A match or mismatch is very valuable information.