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Synthetic Identity Fraud and COVID-19

Published: August 19, 2020 by Guest Contributor

In 2015, U.S. card issuers raced to start issuing EMV (Europay, Mastercard, and Visa) payment cards to take advantage of the new fraud prevention technology. Counterfeit credit card fraud rose by nearly 40% from 2014 to 2016, (Aite Group, 2017) fueled by bad actors trying to maximize their return on compromised payment card data. Today, we anticipate a similar tsunami of fraud ahead of the Social Security Administration (SSA) rollout of electronic Consent Based Social Security Number Verification (eCBSV).

Synthetic identities, defined as fictitious identities existing only on paper, have been a continual challenge for financial institutions. These identities slip past traditional account opening identity checks and can sit silently in portfolios performing exceptionally well, maximizing credit exposure over time. As synthetic identities mature, they may be used to farm new synthetics through authorized user additions, increasing the overall exposure and potential for financial gain. This cycle continues until the bad actor decides to cash out, often aggressively using entire credit lines and overdrawing deposit accounts, before disappearing without a trace.

The ongoing challenges faced by financial institutions have been recognized and the SSA has created an electronic Consent Based Social Security Number Verification process to protect vulnerable populations. This process allows financial institutions to verify that the Social Security number (SSN) being used by an applicant or customer matches the name. This emerging capability to verify SSN issuance will drastically improve the ability to detect synthetic identities. In response, it is expected that bad actors who have spent months, if not years, creating and maturing synthetic identities will look to monetize these efforts in the upcoming months, before eCBSV is more widely adopted.

Compounding the anticipated synthetic identity fraud spike resulting from eCBSV, financial institutions’ consumer-friendly responses to COVID-19 may prove to be a lucrative incentive for bad actors to cash out on their existing synthetic identities. A combination of expanded allowances for exceeding credit limits, more generous overdraft policies, loosened payment strategies, and relaxed collection efforts provide the opportunity for more financial gain. Deteriorating performance may be disguised by the anticipation of increased credit risk, allowing these accounts to remain undetected on their path to bust out.

While responding to consumers’ requests for assistance and implementing new, consumer-friendly policies and practices to aid in impacts from COVID-19, financial institutions should not overlook opportunities to layer in fraud risk detection and mitigation efforts. Practicing synthetic identity detection and risk mitigation begins in account opening. But it doesn’t stop there. A strong synthetic identity protection plan continues throughout the account life cycle. Portfolio management efforts that include synthetic identity risk evaluation at key control points are critical for detecting accounts that are on the verge of going bad.

Financial institutions can protect themselves by incorporating a balance of detection efforts with appropriate risk actions and authentication measures. Understanding their portfolio is a critical first step, allowing them to find patterns of identity evolution, usage, and connections to other consumers that can indicate potential risk of fraud. Once risk tiers are established within the portfolio, existing controls can help catch bad accounts and minimize the resulting losses. For example, including scores designed to determine the risk of synthetic identity, and bust out scores, can identify seemingly good customers who are beginning to display risky tendencies or attempting to farm new synthetic identities.

While we continue to see financial institutions focus on customer experience, especially in times of uncertainty, it is paramount that these efforts are not undermined by bad actors looking to exploit assistance programs. Layering in contextual risk assessments throughout the lifecycle of financial accounts will allow organizations to continue to provide excellent service to good customers while reducing the increasing risk of synthetic identity fraud loss.

Prevent SID

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Fake IDs have been around for decades, but today’s fraudsters aren’t just printing counterfeit driver’s licenses — they’re using artificial intelligence (AI) to create synthetic identities. These AI fake IDs bypass traditional security checks, making it harder for businesses to distinguish real customers from fraudsters. To stay ahead, organizations need to rethink their fraud prevention solutions and invest in advanced tools to stop bad actors before they gain access. The growing threat of AI Fake IDs   AI-generated IDs aren’t just a problem for bars and nightclubs; they’re a serious risk across industries. Fraudsters use AI to generate high-quality fake government-issued IDs, complete with real-looking holograms and barcodes. These fake IDs can be used to commit financial fraud, apply for loans or even launder money. Emerging services like OnlyFake are making AI-generated fake IDs accessible. For $15, users can generate realistic government-issued IDs that can bypass identity verification checks, including Know Your Customer (KYC) processes on major cryptocurrency exchanges.1 Who’s at risk? AI-driven identity fraud is a growing problem for: Financial services – Fraudsters use AI-generated IDs to open bank accounts, apply for loans and commit credit card fraud. Without strong identity verification and fraud detection, banks may unknowingly approve fraudulent applications. E-commerce and retail – Fake accounts enable fraudsters to make unauthorized purchases, exploit return policies and commit chargeback fraud. Businesses relying on outdated identity verification methods are especially vulnerable. Healthcare and insurance – Fraudsters use fake identities to access medical services, prescription drugs or insurance benefits, creating both financial and compliance risks. The rise of synthetic ID fraud Fraudsters don’t just stop at creating fake IDs — they take it a step further by combining real and fake information to create entirely new identities. This is known as synthetic ID fraud, a rapidly growing threat in the digital economy. Unlike traditional identity theft, where a criminal steals an existing person’s information, synthetic identity fraud involves fabricating an identity that has no real-world counterpart. This makes detection more difficult, as there’s no individual to report fraudulent activity. Without strong synthetic fraud detection measures in place, businesses may unknowingly approve loans, credit cards or accounts for these fake identities. The deepfake threat AI-powered fraud isn’t limited to generating fake physical IDs. Fraudsters are also using deepfake technology to impersonate real people. With advanced AI, they can create hyper-realistic photos, videos and voice recordings to bypass facial recognition and biometric verification. For businesses relying on ID document scans and video verification, this can be a serious problem. Fraudsters can: Use AI-generated faces to create entirely fake identities that appear legitimate Manipulate real customer videos to pass live identity checks Clone voices to trick call centers and voice authentication systems As deepfake technology improves, businesses need fraud prevention solutions that go beyond traditional ID verification. AI-powered synthetic fraud detection can analyze biometric inconsistencies, detect signs of image manipulation and flag suspicious behavior. How businesses can combat AI fake ID fraud Stopping AI-powered fraud requires more than just traditional ID checks. Businesses need to upgrade their fraud defenses with identity solutions that use multidimensional data, advanced analytics and machine learning to verify identities in real time. Here’s how: Leverage AI-powered fraud detection – The same AI capabilities that fraudsters use can also be used against them. Identity verification systems powered by machine learning can detect anomalies in ID documents, biometrics and user behavior. Implement robust KYC solutions – KYC protocols help businesses verify customer identities more accurately. Enhanced KYC solutions use multi-layered authentication methods to detect fraudulent applications before they’re approved. Adopt real-time fraud prevention solutions – Businesses should invest in fraud prevention solutions that analyze transaction patterns and device intelligence to flag suspicious activity. Strengthen synthetic identity fraud detection – Detecting synthetic identities requires a combination of behavioral analytics, document verification and cross-industry data matching. Advanced synthetic fraud detection tools can help businesses identify and block synthetic identities. Stay ahead of AI fraudsters AI-generated fake IDs and synthetic identities are evolving, but businesses don’t have to be caught off guard. By investing in identity solutions that leverage AI-driven fraud detection, businesses can protect themselves from costly fraud schemes while ensuring a seamless experience for legitimate customers. At Experian, we combine cutting-edge fraud prevention, KYC and authentication solutions to help businesses detect and prevent AI-generated fake ID and synthetic ID fraud before they cause damage. Our advanced analytics, machine learning models and real-time data insights provide the intelligence businesses need to outsmart fraudsters. Learn more *This article includes content created by an AI language model and is intended to provide general information. 1 https://www.404media.co/inside-the-underground-site-where-ai-neural-networks-churns-out-fake-ids-onlyfake/

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