As the digital economy expands, artificial intelligence (AI) is reshaping fraud prevention and payments, offering both opportunities and challenges. At the recent MRC Virtual Summit on Generative AI, industry leaders explored AI’s dual role as an enabler of innovation and a weapon for fraudsters.
The discussions emphasized the urgent need for businesses to stay ahead of AI-driven fraud tactics by adopting proactive, trust-focused strategies. Leveraging AI’s strengths can empower companies to build intelligent, adaptive fraud prevention systems that protect customers and secure the digital ecosystem. Read on for key insights from the summit and practical strategies to combat evolving threats.
The Threat of Generative AI
Armen Najarian, Chief Marketing Officer at Sift, opened the summit with a stark warning about the alarming ease with which generative AI can be exploited by fraudsters. Demonstrating this point, he highlighted how even a novice can create convincing deepfakes with minimal effort. “With just a few clicks and at zero cost, even the most inexperienced fraud actor can generate a deepfake of me or anyone else you know and trust,” Najarian emphasized.
To illustrate the accessibility of these tools, Najarian shared his own experience creating a deepfake video. The exercise revealed not only the rapid advancements in generative AI technology, but also the widespread availability and free nature of these tools. As this technology becomes increasingly sophisticated, it poses a growing risk to businesses and consumers alike.
Building Trust in a Digital World
Fraudsters have learned to exploit the trust that businesses build with their customers. By mimicking the tone and voice of merchants in official communications, fraudsters can deceive consumers into believing they are interacting with legitimate companies. This makes it crucial for businesses to develop AI-driven methods to verify the authenticity of digital interactions.
Raviv Levi, Sift Chief Product and Technology Officer, argued that combating GenAI fraud requires more than just matching AI capabilities. It involves leveraging AI to establish trust with legitimate consumers. “The way to fight GenAI is not with AI that’s trying to do the exact same thing, but rather leveraging AI, machine learning, and GenAI to build trust through other means about that entity that you interact with,” Raviv explained.
The Role of Identity and Behavioral Analysis
Many tried and true fraud tactics still persist, even in the age of AI, such as using stolen or synthetic identities and launching social engineering attacks. It’s important for merchants to not lose sight of these ever-present fraud threats while also preparing for new GenAI applications.
Jacob Sanchez, Director of Fraud Operations at FanDuel, noted, “We’ll still see fraudsters continue to change their tactics quickly. I think it’s always going to be a cat and mouse game. It’s just going to continue at a higher rate and the changes are going to be quicker and the technology is going to evolve faster.”
While AI can enhance these tactics, it also offers new ways to detect and prevent fraud. Traditional fraud detection methods based on static signals are becoming less effective on their own. Incorporating dynamic behavioral signals and identity intelligence can provide better protection. Oxana Korzun, Fraud Intelligence at Upwork, noted “Traditional models cannot predict that well, like AI can do. It can recognize if there is a change in the pattern, if a person changed the time zone or they use language in a different way.”
Oxana also mentioned the rise of anti-detection tools like anti-browsers, VPNs, and proxies, which make it more challenging to rely on static signals for fraud detection. The use of these tools necessitates a greater emphasis on analyzing user behavior and patterns over time to identify suspicious activities.
The Hype Cycle of AI
During a session on the current state of AI-driven fraud, Sift Senior Trust and Safety Architect Brittany Allen discussed the Gartner hype cycle, illustrating the stages that technology goes through from conception to widespread adoption. She emphasized the importance of separating hype from reality and focusing on real-world uses for AI.
While generative AI is currently riding a wave of inflated expectations, it’s essential for businesses to look beyond the hype and invest in AI solutions that address their specific challenges. Allen emphasized the importance of working with AI-powered solution providers that help businesses focus on revenue and the consumer experience. For example, Sift helps transform fraud prevention into a competitive advantage by offering reliable, user-level insights that enable businesses to increase acceptance rates for trusted customers while proactively detecting risks and evolving fraud patterns.
Fighting Fire with Fire
Fraud fighters can—and should—harness the power of AI in their defense strategies. By leveraging AI and machine learning, businesses can stay ahead of fraudsters and protect their customers. As Najarian stated, “GenAI-based fraud attacks are increasing in velocity, sophistication, and volume. But there’s hope. We can flip the script, fight fire with fire, and leverage generative AI ourselves. Many solution providers are already integrating GenAI and machine learning-based AI into their platforms, equipping fraud fighters with the tools they need to win.”
Kevin Lee, SVP of Customer Experience Trust and Safety at Sift, echoed this sentiment, emphasizing the need for businesses to adopt AI tools to enhance their fraud detection capabilities. Lee stated, “AI is going to evolve to better recognize and adapt to new fraud patterns in real time. This is something that rules and more static solutions cannot achieve.”
The summit also explored practical applications of AI in fraud prevention. Speakers discussed the use of AI to analyze user behavior, detect anomalies, and identify patterns that indicate fraudulent activities. By integrating AI into their fraud detection systems, businesses can improve their ability to detect and respond to fraud in real-time.
For more insights on AI-driven fraud and AI-powered solutions, check out our Digital Trust Index on managing risk in the age of AI-driven fraud.
