ID Analytics talks identity fraud and recession trends

by ID Analytics

ID Analytics

ID Analytics recently hosted a webcast on identity fraud trends in 2020.  Since identity fraud is a pervasive problem that is constantly evolving, we wanted to share the most-asked questions during the live presentation with our broader readership.

Q: What are the data sources used by ID Analytics to identify first-party fraud?

A: ID Analytics’ first-party fraud score is designed to identify consumers who are using their own identity to open credit or service accounts they don’t intend to repay. The solution uses the same core data assets as our third-party and synthetic fraud scores. This data is housed in our ID Network®.

The ID Network is our data consortium that is built from the data contributions of our clients. Enterprises that use our solutions allow us to take the application data being evaluated and place it into the network. They also agree to report the outcome of that application – whether the application was approved, the account turned out to be fraudulent, the consumer is still paying, etc. For first-party fraud, we use that application and performance insight to identify high- risk behaviors paired with the limited changes in personally identifiable information (PII) that are often typical for someone attempting to commit such fraud.

The result is an ever-growing system of knowledge – clients request insights from the ID Network, and in doing so, they contribute data which makes the network an even stronger resource for the next evaluation. Its unique visibility across a multitude of lending and service industries form the foundation of our insights and assessments.

Q: How does ID Analytics distinguish between first-party fraud and identity theft?

A: While it is not always easy to distinguish between first-party fraud and identity theft, we see different behavior patterns between the two. The most notable being (1) the use of PII and (2) the velocity of credit seeking. In first-party fraud (meaning someone is using their own identity to commit fraud), we typically see the applicant use their true contact information (e.g., address, phone number, email, etc.) to attempt to open accounts over a series of days or weeks. With identity theft, we look at the behavior the victim reports as fraud (committed by someone else) and typically see some variance in at least one of the contact elements and a high velocity of credit applications. For example, use of a phone number that does not belong to the victim accompanied by a burst of credit seeking activity where the applications are submitted within 24 to 72 hours of one another.

Q: What are some examples of recession-era fraud trends?

A: We recently addressed this question on our blog where we wrote about fraud trends that potentially indicate an upcoming recession. The relevance of this topic has grown, as many economists now say that growth is likely to slow considerably this year, if not contract altogether.¹

Over the past 18 months, ID Analytics has seen an increase in first-party fraud and have heard consistent anecdotal reports from many of our customers that family fraud (when one family member steals another family member’s identity) is on the rise. These forms of fraud tend to increase when the economy is on a downswing and individuals find themselves more in need of short-term financial assistance. In these cases, opportunistic fraudsters seek immediate monetary gain in exchange for some type of consequence, such as a drop in their credit score or damage to a personal relationship. To learn more read, Is identity fraud becoming a leading economic indicator?


ID Analytics’ solutions help combat both identity fraud and credit risk. To learn more about how alternative data can help support your credit risk management strategies tune in to our recent web seminar hosted by American Banker, 2020 vision: Taking action on the latest trends in alternative data.


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1., (accessed March 10, 2020).