Uncloaking Synthetic Identities – Revealing the Ring

by Guest Contributor 4 min read April 23, 2013

As we prepare to attend next week’s FS-ISAC & BITS Summitwe know that the financial services industry is abuzz about massive losses from the ever-evolving attack vectors including DDoS, Malware, Data Breaches, Synthetic Identities, etc. Specifically, the recent $200 million (and counting) in losses tied to a sophisticated card fraud scheme involving thousands of fraudulent applications submitted over several years using synthetic identities. While the massive scale and effectiveness of the attack seems to suggest a novel approach or gap in existing fraud prevention controls, the fact of the matter is that many of the perpetrators could have been detected at account opening, long before they had an opportunity to cause financial losses. Synthetic identities have been a headache for financial institutions for years, but only recently have criminal rings begun to exploit this attack vector at such a large scale.

The greatest challenge with synthetic identities is that traditional account opening processes focus on identity verification compliance around the USA PATRIOT Act and FACT Act Red Flags guidance, risk management using credit bureau scores, and fraud detection using known fraudulent data points. A synthetic identity ring simply sidesteps those controls by using new false identities created with data that could be legitimate, have no established credit history, or slightly manipulate elements of data from individuals with excellent credit scores. The goal is to avoid detection by “blending in” with the thousands of credit card, bank account, and loan applications submitted each day where individuals do not have a credit history, where minor typos cause identity verification false positives, or where addresses and other personal data does not align with credit reports. Small business accounts are an even easier target, as third-party data sources to verify their authenticity are sparse even though the financial stakes are higher with large lines of credit, multiple signors, and complex (sometimes international) transactions. Detecting these tactics is nearly impossible in a channel where anonymity is king — and many rings have become experts on gaming the system, especially as institutions continue to migrate the bulk of their originations to the online channel and the account opening process becomes increasingly faceless.

While the solutions described above play a critical role in meeting compliance and risk management objectives, they unfortunately often fall short when it comes to detecting synthetic identities. Identity verification vendors were quick to point the finger at lapses in financial institutions’ internal and third-party behavioral and transactional monitoring solutions when the recent $200 million attack hit the headlines, but these same providers’ failure to deploy device intelligence alongside traditional controls likely led to the fraudulent accounts being opened in the first place.

With synthetic identities, elements of legitimate creditworthy consumers are often paired with other invalid or fictitious applicant dataso fraud investigators cannot rely on simply verifying data against a credit report or public data source. In many cases, the device used to submit an application may be the only common element used to link and identify other seemingly unrelated applications. Several financial institutions have already demonstrated success at leveraging device intelligence along with a powerful risk engine and integrated link analysis tools to pinpoint these complex attacks. In fact, one example alone spanned hundreds of applications and represented millions of dollars in fraud saves at a top bank.

The recent synthetic ring comprising over 7,000 false identities and 25,000 fraudulent cards may be an extreme example of the potential scope of this problem; however, the attack vector will only continue to grow until device intelligence becomes an integrated component of all online account opening decisions across the industry. Even though most institutions are satisfying Red Flags guidance, organizations failing to institute advancedaccount opening controls such as complex device intelligence can expect to see more attacks and will likely struggle with higher monetary losses from accounts that never should have been booked.Traditional-Controls

Related Posts

From Hybrids to Refinancing: Consumers are Finding New Roads to Vehicle Affordability

For today’s automotive consumers, considering a vehicle purchase isn’t just about the price they see on the window, it’s about finding the right combination of their vehicle preference and monthly payment. In fact, data from Experian Automotive’s State of the Automotive Finance Market Report: Q2 2026 highlighted how affordability continues to shape the automotive finance market. For instance, hybrids offered the lowest average new vehicle loan payment across all fuel types, coming in at $646 in Q2 2026, compared to electric vehicles (EVs) at $692, and gasoline-powered vehicles at $721. This led to considerable growth in new vehicle market share for hybrids this quarter, accounting for 16.80%, from 12.99% last year. While the automotive market continues to offer consumers an expanding mix of fuel types, the combination of growing hybrid share and comparatively lower monthly payments is something worth watching. Affordability isn’t just about what consumers drive, it’s how they finance it While hybrid vehicles are continuing to pave their way in the vehicle market, consumers who already have an auto loan are finding greater savings through refinancing. In the second quarter of 2026, automotive refinancing reached approximately 140,000 loans. More notably, the financial benefit associated with refinancing has grown. Consumers who refinanced this quarter reduced their average interest rate by more than 2.4%, with the average rate moving from 10.40% on the original loan to 7.97% on the refinanced loan. Those rate reductions translated into meaningful monthly savings, especially when refinancing through particular lenders. In Q2 2026, refinancing saved consumers an average of $83 per month, compared to an average monthly savings of $64 this time last year. However, credit unions delivered the largest average payment difference among lender types at $102 this quarter, followed by banks ($65), and finance companies ($38). It’s important for automotive professionals to acknowledge that affordability is not a single moment in the vehicle journey. It can influence the vehicle a consumer chooses, the financing they opt for during that transaction, and the decisions they make years after driving off the lot. Understanding and leveraging those different moments can help professionals identify opportunities to better serve consumers throughout the vehicle ownership lifecycle. To learn more about automotive finance trends, view the full State of the Automotive Finance Market Report: Q2 2026 presentation on demand.

August 27, 2026 by Melinda Zabritski
AI Agent Identity Verification: How to Verify AI Agents in Digital Transactions

AI agents are changing the way consumers interact with businesses online. Learn how you can establish greater confidence in AI transactions.

August 26, 2026 by Laura Burrows
Ask the Expert: Turning Insight into Advantage with Michelle Goeppner and David Elmore

What if some of your best potential borrowers are the ones your traditional credit strategy can't fully see? A credit score can tell lenders a lot about a consumer, but it doesn't always capture the full picture of how someone is managing their financial life. For consumers with nontraditional income patterns or limited credit histories, that incomplete view can mean missed opportunities. In this Ask the Expert session, David Elmore of Experian talks with Michelle Goeppner, Chief Lending Officer at Vantage West Credit Union, about how alternative data can provide additional context around consumer risk, uncover opportunities traditional data alone might miss and help lenders expand their reach without disrupting strategies that already work. Who could lenders be missing? That question is especially important when a consumer’s financial life doesn’t fit neatly into a traditional credit profile. Take gig workers. Someone driving for Uber or delivering for DoorDash likely has a different income pattern than a salaried employee — irregular, seasonal, spread across platforms. That doesn't mean they aren't reliably managing bills, rent and other obligations. It just means a traditional file may not show it. Goeppner has a name for the risk of overlooking that context: FOMM — Fear of Missing Members. You've heard of FOMO — Fear of Missing Out. I think about it as FOMM — Fear of Missing Members. Who are we leaving behind if we're not using it?Michelle Goeppner, Chief Lending Officer For credit unions especially, that's not just a data question — it's a mission question. A partial view of a member's finances can mean missing a member the institution exists to serve. The credit score alone doesn't tell you where someone's headed Traditional credit data is still  foundational to lending decisions. But alternative data — income, cash flow, payment behavior — adds a layer that a credit score alone can't provide. Goeppner illustrates the distinction with two consumers who have exactly the same credit score: I don't know if you're a 640 score on your way to 720 — or are you a 640 headed southwards to 580? It doesn't show me how you're managing your day-to-day financial lifeMichelle Goeppner, Chief Lending Officer Two borrowers can share the same score and be moving in opposite directions. Alternative data helps lenders tell the difference — and put that score in context rather than treating it as the whole story. Start small and layer it in Adopting alternative data doesn't mean overhauling an existing strategy. As Goeppner puts it, it's additive, not a replacement: It's not a rip and replace. You don't have to let go of your existing playbook. It's additive — you layer it in.Michelle Goeppner, Chief Lending Officer Her advice for getting started: Define the problem first. Are you trying to increase approvals, reach more underserved borrowers, or improve decisioning for a specific product? Test before you scale. Revisit loans you've already booked and ask whether alternative data would have changed the outcome — or pilot it on a single product before rolling it out further. Build in governance from day one. Document what changed, where the new data was used, and what results followed. As Goeppner puts it: “Crawl, walk, run. Slow and grow.” More loans without changing the risk profile For Vantage West, the value of that approach has shown up in its lending results. It has been an absolute game changer for us at Vantage West. We have been able to make more loans to our target members, our target segments, without changes to our risk profile.Michelle Goeppner, Chief Lending Officer That distinction matters. The goal isn't approving more loans for its own sake — it's having enough information to recognize good borrowers that traditional data alone would have missed. The result is a fuller picture of the people behind the credit file, and more confidence in deciding who a lender can serve. Explore alternative data with us Alternative data can help lenders add context to traditional credit information for a more complete view of consumers. Experian works with institutions of all sizes to incorporate additional consumer signals into existing lending strategies — strengthening decisioning, managing risk and identifying new opportunities for growth. Learn more Contact us About our experts Michelle Goeppner Chief Lending Officer, Vantage West Credit Union Michelle Goeppner is a dynamic financial services executive with over two decades of experience driving strategic growth, product innovation, and operational excellence across leading credit unions and financial institutions. Currently serving as the Chief Lending Officer at Vantage West Credit Union, Michelle leads the strategic vision for multi-billion-dollar consumer loan and deposit portfolios, as a member of the Executive Coalition. Her expertise spans consumer lending, product management, integrated marketing, and talent development, with a proven track record of leveraging fintech partnerships, automation, and data-driven strategies to optimize portfolio performance and member engagement. Throughout her career, Michelle has held pivotal leadership roles in organizations such as Alliant Credit Union and Discover Financial Services. She is recognized for her collaborative approach, detail-oriented execution, and commitment to developing future female leaders. Michelle’s contributions include founding Alliant’s Women’s Resource Group, serving on advisory councils and boards, and earning multiple industry awards for excellence and innovation. She holds an Executive Certification in Product Management from UC Berkeley, a Master of Science in Integrated Marketing Communications from Roosevelt University, and a Bachelor of Science in Marketing from Northern Illinois University. David Elmore Vice President of Fintech Sales, Experian David Elmore leads a team of fintech sales professionals at Experian focused on helping fintech organizations drive responsible, scalable growth through data-driven analytics and decisioning. With more than 20 years in financial services — a decade of it focused on fintech — he brings deep expertise in applying traditional and alternative data across the customer lifecycle. David and his team partner with fintech leaders to navigate opportunities across acquisition, underwriting, portfolio management, and collections, balancing innovation, risk, and trust.

August 26, 2026 by Julie Lee

Subscribe to our Newsletter

Enter your name and email for the latest updates.

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Subscribe to our Newsletter

Don't miss out on the latest industry trends and insights!
Subscribe