Synthetic identity fraud grew in the fourth quarter on a year over year basis, but artificial intelligence is helping to slow the pace of growth, according to a report from TransUnion.
Synthetic fraud balances rose 5.2% in the fourth quarter compared with the same period the year prior, according to the report. Such balances rose 68.5% between Q4 2015 and Q4 2016.
“Despite the slowing of fraud balance growth in the credit card space, TransUnion found that the incidence of such fraud on credit applications remains similar to last year, moving from 0.59% at the end of 2016 to 0.60% in 2017,” the press release reads.
Some of these results were present in a case study TransUnion conducted with an undisclosed credit card lender. The company’s analysis revealed that hundreds of loan applications were connected to the same address and multiple consumers utilized the same name and date of birth but had different Social Security Numbers.
Service provider Point Predictive uses a form of artificial intelligence called machine learning to analyze fraud for its auto lender clients. The technology identifies the synthetic identities during the origination process so lenders can take actionable steps to prevent the fraud.
“Auto lenders participating in our consortium meetings have identified that one of their top three issues this year is solving synthetic identity fraud,” Eric Werab, vice president of fraud and product strategy at PointPredictive, said in a press release. “Our analysis shows that synthetic identity fraud accounts for 15-20% of fraud and misrepresentation losses across the industry. This equates to more than $1 billion in synthetic identity originations this year.”
In these cases where the technology identifies fraudsters, TransUnion recommends asking for “proof of life” statements such as multiple utility bills or a Social Security card.