A Ticket to the Future: Top Trends, the Latest Tech, Marketing Mavens and More

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 Businesses relying on outdated identity verification methods are especially vulnerable.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/

By implementing effective identity risk management, financial institutions can protect themselves and their consumers from identity fraud.

At Experian, we believe in fostering innovation and collaboration to solve complex challenges. Recently, Ivan Ahmed, one of our talented product management leaders at Experian Housing, had the opportunity to participate in the FHFA 2024 TechSprint, where his team won the award for the best Risk Management and Compliance idea. In this article, we share Ivan's experience as he reflects on the TechSprint, the inspiration behind his team's project, and the valuable lessons learned. Can you share your experience participating in the FHFA 2024 TechSprint? What was the atmosphere like, and how did it feel to be recognized for the best Risk Management and Compliance idea? Let me start by explaining what a TechSprint is. It is a fast-paced, high-energy collaborative workshop where diverse experts and stakeholders come together to design technological solutions to complex problems. Each team is given a high-level problem and use case. From there, stakeholders and domain experts must develop a proof of concept within 3 days to best address the problem. On the last and final day, called the “Demo Day,” teams must showcase their solution in front of a panel of judges. It’s a fun, high-energy, challenging, and rewarding experience. A TechSprint is a convergence of everything I love – technology, business, and design and I think FHFA did a wonderful job orchestrating the event. Each team consisted of representatives from different functions in the housing ecosystem, including lenders, technologists, product managers, and regulators. We were given access to a room, whiteboards, and, most importantly, delicious snacks. We were also given access to industry subject matter experts outside our teams, including representatives from Fannie Mae and Freddie Mac, FHFA, and leaders from top companies. What I found the most impactful was the ability to pressure test our ideas and solutions against these industry subject matter experts. Ideating in a vacuum can be challenging, so being able to stress test things rapidly with these experts allowed us to change course quickly as new information was introduced. Winning the best Risk Management and Compliance idea award was rewarding, especially as we were able to ideate a solution to such a critical accessibility issue. Ultimately, our goal was to help create a fairer, more equitable, and inclusive housing finance system. A big shoutout to my teammates, Wemimo Abbey, Joseph Karbowski, Will Regenauer, and Eddy Atkins. What inspired Team Arsenal to focus on identifying potential gaps in ADA compliance within multifamily buildings, and what were some of the key challenges your team faced during the process? My mother has suffered from several disabilities most of her life. With age, she has become more wheelchair-dependent, and traveling has become a major challenge. On a recent family trip, the entry to our hotel building wasn’t ADA-compliant, and I had to carry her up a flight of stairs. It was frustrating to deal with. I later went down a rabbit hole around ADA compliance and, much to my surprise, learned that only 0.15% of all homes in the U.S. are wheelchair accessible! As we explored the problem space further as a team, we learned how difficult it is to ensure that new and existing rental homes are ADA-compliant. We hypothesized that a solution is needed to establish incentives for borrowers, lenders, and GSEs to meet compliance. A technological solution could more easily enable multi-family lenders and builders to identify rental units that are non-ADA compliant and could provide ways to address the gaps. We noticed two primary challenges: an enforcement gap and an incentive gap. We learned that agency loans (Fannie Mae and Freddie Mac) account for most multi-family home loan originations. If we could tackle the enforcement challenge at the GSE level, we could set up the proper incentives for all players in the multi-family lending process. By providing tools to both the borrower and the GSE’s, we could help foster a more inclusive and accessible rental housing market. How do you envision your AI-driven solution impacting the rental housing market and improving ADA compliance for multifamily buildings? We wanted to ensure that we leveraged the true power of Generative AI, which meant that our solution could take multimodal inputs and produce multimodal outputs. For example, we could train the Generative AI model on photos of interior multi-family rental units and structured or unstructured text like building sketches, site layouts, and local building codes. We could then incorporate ADA design requirements and analyze discrepancies. The result would be a compliance report or tool outlining the adherence level to ADA design requirements and providing tips and recommendations on remediation. The solution could be delivered as a free tool by the GSEs, who could incentivize its usage by offering price concessions to borrowers. Developers could also use the tool to evaluate whether new or existing builds were ADA-compliant. How did your background and experience with Experian contribute to developing your team's winning idea at the FHFA TechSprint? Much of my role at Experian has involved exploring ways to leverage proprietary and public record property data for marketing, account review, and analytical use cases. I work very closely with property data at Experian, so I was very familiar with the types of input fields of property data that would be the most relevant to improving a generative AI model output. Specifically, in our use case, we wanted to train the model to better identify homes and features that were non-compliant with ADA and provide clear remediation steps. We knew that public record property information was available from various sources and could be leveraged as additional third-party input data to improve our model accuracy. What advice would you give to other teams or individuals looking to participate in future TechSprint events, especially those aiming to tackle complex issues like risk management and compliance? It’s important to remember that an ideal solution is both impactful and practical. Practicality is achieved when the solution has both business and technical viability. Therefore, it’s crucial to carefully vet problems and solutions by understanding their viability. Working as a team to solve the problem means leveraging the expertise of subject matter experts around you. Each team member should draw on their strengths, making the collective effort stronger than individual contribution. Most importantly, fairness, inclusivity, and accessibility matter. An effective solution should strive to have a positive social impact in addition to other considerations. Winning with purpose Ivan’s journey through the FHFA 2024 TechSprint exemplifies the innovative and collaborative spirit that drives our team at Experian. His reflections highlight the impact of well-designed technological solutions on critical issues like ADA-compliance in multifamily housing. We hope Ivan’s experience inspires others to explore their potential in solving complex problems and to participate in future TechSprints, where innovative thinking and a commitment to social good can lead to meaningful change.