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Synthetic identity fraud, otherwise known as SID fraud, is reportedly the fastest-growing type of financial crime. One reason for its rapid growth is the fact that it’s so hard to detect, and thus prevent. This allows the SIDs to embed within business portfolios, building up lines of credit to run up charges or take large loans before “busting out” or disappearing with the funds. In Experian’s recent perspective paper, Preventing synthetic identity fraud, we explore how SID differs from other types of fraud, and the unique steps required to prevent it. The paper also examines the financial risks of SID, including: $15,000 is the average charge-off balance per SID attack Up to 15% of credit card losses are due to SID 18% – the increase in global card losses every year since 2013 SID is unlike any other type of fraud and standard fraud protection isn’t sufficient. Download the paper to learn more about Experian’s new toolset in the fight against SID. Download the paper

The CU Times recently reported on a nationwide synthetic identity fraud ring impacting several major credit unions and banks. Investigators for the Federal and New York governments charged 13 people and three businesses in connection to the nationwide scheme. The members of the crime ring were able to fraudulently obtain more than $1 million in loans and credit cards from 10 credit unions and nine banks. Synthetic Identity Fraud Can’t Be Ignored Fraud was on an upward trend before the pandemic and does not show signs of slowing. Opportunistic criminals have taken advantage of the shift to digital interactions, loosening of some controls in online transactions, and the desire of financial institutions to maintain their portfolios – seeking new ways to perpetrate fraud. At the onset of the COVID-19 pandemic, many financial institutions shifted their attention from existing plans for the year. In some cases they deprioritized plans to review and revise their fraud prevention strategy. Over the last several months, the focus swung to moving processes online, maintaining portfolios, easing customer friction, and dealing with IT resource constraints. While these shifts made sense due to rapidly changing conditions, they may have created a more enticing environment for fraudsters. This recent synthetic identity fraud ring was in place long before COVID-19. That said, it still highlights the need to have a prevention and detection plan in place. Financial institutions want to maintain their portfolios and their customer or member experience. However, they can’t afford to table fraud plans in the meantime. “72% of FI executives surveyed believe synthetic identity fraud to be more challenging than identity theft. This is due to the fact that it is harder to detect—either crime rings nurture accounts for months or years before busting out with six-figure losses, or they are misconstrued as credit losses, and valuable agent time is spent trying to collect from someone who doesn’t exist,” says Julie Conroy, Research Director at Aite Group. Prevention and Detection Putting the fraud strategy discussion on hold—even in the short term—could open up a financial institution to potential risk at time when cost control and portfolio maintenance are watch words. Canny fraudsters are on the lookout for financial institutions with fewer protections. Waiting to implement or update a fraud strategy could open a business up to increased fraud losses. Now is the time to review your synthetic identity fraud prevention and detection strategies, and Experian can help. Our innovative new tool in the fight against synthetic identity fraud helps financial institutions stop fraudsters at the door. Learn more

As industry experts are still unsure when the economy will fully recover, re-entry into marketing preapproved credit offers seems like a far-off proposal. However, several of the top credit card issuers are already mailing prescreen offers, with many other lenders following suit. When the time comes for organizations to resume, or even expand this type of targeting, odds are that the marketing budget will be tighter than in the past. To make the most of the limited available marketing spend, lenders will need to be more prescriptive with their selection process to increase response rates on fewer delivered offers. Choosing the best candidates to receive these offers, from a credit risk perspective, will be critical. With delinquencies being suppressed due to CARES Act reporting guidelines, identifying consumers with the ability to repay will require additional assessment of recent credit behavior metrics, such as actual payment amounts and balance migration. Along with the presence of explicit indicators of accommodated trades (trades affected by natural disaster, trades with a balance but no scheduled payment amount) on a prospect’s credit file, their recent trends in payments and balance shifts can be integral in determining whether a prospect has been adversely impacted by today’s economic environment. Once risk criteria have been developed using a mix of bureau scores (like the VantageScore® credit score), traditional credit attributes and trended attributes measuring recent activity, additional targeting will be critical for selecting a population that’s most likely to open the relevant trade type. For credit cards and personal installment loans, response performance can be greatly improved by aligning product offers with prospects based on their propensity to revolve, pay in full each month or consolidate balances. Additionally, the process to select final prospects should integrate a propensity to open/respond assessment for the specific offering. While many lenders have custom models developed on previous internal response performance, off-the-shelf propensity to open models are also available to provide an assessment of a prospect’s likelihood to open a particular type of trade in the coming months. These models can act as a fast-start for lenders that intend to develop internal custom models, but don’t have the response performance within a particular product/geography/risk profile. They are also commonly used as a long-term solution for lenders without an internal model development team or budget for an outsourced model. Prescreen selection best practices Identify geography and traditional credit risk assessment of the prospect universe. Overlay attributes measuring accommodated trades and recent payment/balance trends to identify prospects with indications of ability to pay. Segment the prospect universe by recent credit usage to determine products that would resonate. Make final selections using propensity to open model scores to increase response rates by only making offers to consumers who are likely looking for new credit offers. While the best practices listed above don’t represent a risk-free approach in these uncertain times, they do provide a framework for identifying prospects with mitigated repayment risk and insights into the appropriate credit offer to make and when to make it. Learn about in the market models Learn about trended attributes VantageScore® is a registered trademark of VantageScore Solutions, LLC.


