The Impact of Generative AI on Identity Fraud

According to AU10TIX’s recent Q2 2023 Global Identity Fraud Report, organized identity fraud has surged by 44% in the U.S., compared to previous quarters. This increasing trend of fraud is largely attributed to the rise of generative AI, which has both positive and negative implications.

The Rise of Organized Attacks

AU10TIX’s AI-powered fraud detection tools, particularly the Serial Fraud Monitor, have identified a significant increase in professional organized attacks globally. These attacks are not limited to a single account or a small sum of money; they are major swarm attacks that can last for weeks or even months, causing significant damage to organizations. The vulnerability of the crypto trading and payments verticals has made them prime targets for fraudsters.

“These are major swarm attacks that can last weeks, even months, and their impact is much bigger. Organizations are enduring harder blows, and the general response we see is helplessness.” – Ofer Friedman, Chief Business Development Officer at AU10TIX

The Challenge of Differentiating Between Forgeries and Reality

The advancements in large language models and generative AI have given fraudsters the ability to mimic valid identities convincingly. This has made it increasingly difficult to differentiate between forgeries and real identities, posing a significant challenge for fraud detection.

“Large language models and generative AI give professional fraudsters the ability to mimic valid identities in convincing ways, so differentiating between forgeries and the real thing has become a major challenge.” – Dan Yerushalmi, CEO at AU10TIX

Furthermore, generative AI has made it easier for fraudsters to access a vast amount of data and iterate their attacks to overcome detection or cause even more damage.

“Generative AI puts all the data in the world at the fingertips of fraudsters, and can infinitely iterate to overcome thwarted attacks or simply cause more damage.” – Dan Yerushalmi, CEO at AU10TIX

The Impact on Fraud Techniques

Generative AI has revolutionized fraud techniques in multiple ways. Deepfake technology, which involves manipulating images, voice recordings, and videos, is used in advanced social engineering and phishing attacks. Fraudsters can create fraudulent accounts with fake identities or bypass ID verification systems using deepfakes. Biometric ID validation systems can also be defeated using presentation attacks and injection attacks.

“Deepfakes can also be used to create fraudulent accounts with fake identities or bypass ID verification to break into existing accounts.” – AU10TIX’s Q2 2023 Global Identity Fraud Report

Generative AI is also used to manufacture entire identities, making it harder to detect fraud. Synthetic IDs, which blend stolen SSNs, names, and addresses with false information, can now pass almost any verification check and develop digital personas by mimicking real human behavior.

“Synthetic IDs that blend stolen Social Security numbers, names and addresses with false information and new digital alter egos can now pass almost any verification check. Over time, they develop digital personas by mimicking real human behavior, which makes them even more difficult to detect.” – AU10TIX’s Q2 2023 Global Identity Fraud Report

Combating Undetectable Fraud

To fight against undetectable fraud, organizations need to add a layer of generative AI detection capabilities on top of their existing security measures. This means implementing multilayer fraud detection systems that analyze fraud from different angles.

“Instead of the usual single-layer case-based fraud prevention, we are moving into multilayer detection, which looks at fraud and the behavior of fraudsters from different angles.” – Ofer Friedman, Chief Business Development Officer at AU10TIX

AI deepfake detection algorithms can analyze facial transformations, voice patterns, and behavioral signals to determine if content has been manipulated. Additionally, organizations should implement automated AI and ML identity verification systems at the case level and have a second layer of defense that detects coordinated attacks at the network traffic level.

The Importance of Collaboration and Trust

Given the evolving nature of gen AI and fraud techniques, organizations must work together to combat widespread sophisticated fraud and retain consumer trust. Collaboration and sharing anonymized data can help identify hidden patterns and anomalies that point to sophisticated fraud.

“Organizations must work together to reduce fraud globally, and AU10TIX brings a long history of relationship and trust building to that effort.” – Dan Yerushalmi, CEO at AU10TIX

While generative AI presents new challenges in the fight against fraud, it should be used in conjunction with traditional software algorithms and machine learning. An intelligent combination of these technologies is key to optimizing results and providing both security and a seamless user experience.

“An intelligent combination of machine learning, AI, and basic algorithms is the key to optimizing results.” – Dan Yerushalmi, CEO at AU10TIX

By adding generative AI detection capabilities and adopting a collaborative approach, organizations can protect their customers from fraud, maintain customer trust and loyalty, and ensure their long-term survival in an increasingly digital landscape.

“Customers will abandon any business process they are not happy with and move on to any of a thousand other options at their fingertips.” – Dan Yerushalmi, CEO at AU10TIX

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