Deepfake fraud in the financial industry is rapidly increasing, as malicious actors utilize AI-generated media and text to impersonate executives, workers, and customers. These sophisticated scams facilitate unauthorized transactions and data breaches, posing significant security and reputational risks for financial institutions. Experts found that the number of deepfake incidents in fintech increased by 700% in 2023 and predicted that generative AI could enable fraud losses in the US to surpass $40 billion by 2027.
To protect their infrastructure, customers, and reputation, financial institutions increasingly look to adopt AI-generated fraud detection solutions to identify deepfake attacks before they lead to expensive cybersecurity breaches.
Although cybercriminals are only beginning to explore the full potential of AI-generated fraud, deepfake attacks have already become diversified. High-profile impersonations of executives have cost companies tens of millions, but less-publicized cases of fraudsters impersonating IT workers via AI-generated media have also led to massive financial losses for customers. Fraudsters utilize social engineering tactics and phishing, leverage deepfake videos, images, and voice clones to overcome biometric verification, and harness the democratized power of AI to create fake documents to open fraudulent accounts, easily overcoming KYC and AML verification measures.
AI-Generated Fraud Detection in the Real World
Audio deepfakes are a particularly challenging fraud method for the financial industry, as banks relying on voice verification find their call centers inundated with synthesized phone calls where fraudsters utilize voice clones of customers and workers to hijack accounts.
Recently, Reality Defender partnered with a major bank providing financial services to hundreds of millions of customers in tens of billions of transactions per day. As the bank’s agents routinely encountered thousands of fraudulent claims over the phone, the client approached Reality Defender to incorporate our AI-generated fraud detection software into their call center workflow. The client seamlessly incorporated our state-of-the-art deepfake detection API into their call center workflow for real-time results, with our detection models scanning both inbound and outbound calls, flagging any conversations that might feature synthetic audio.
Evolving Threats Call for Scalable Solutions
The capabilities of AI-generated fraud detection models extend far beyond voice clone analysis. Reality Defender’s deepfake detection API is designed to be platform-agnostic, meaning it can be integrated into any preexisting workflow or product. Clients can add detection capabilities to their biometric verification processes to catch fraudsters’ attempts at utilizing AI-generated likeness to break into accounts. Workers can immediately verify whether messages and calls from executives are authentic before processing large transactions.
Reality Defender’s AI-generated fraud detection tools are built, maintained, and updated by a team of industry experts who constantly research and integrate improved models to respond to the newest developments in generative AI. Our API allows for file submission matched to the client’s scale, allowing for mass submission of firehose of content — a crucial feature for institutions that face a ceaseless onslaught of potential deepfake attacks.
In 2023, fraud accounted for more than $8.8 billion in losses in the US alone. Considering the risks of financial and reputational damage, and the current and future impact of deepfakes on finance and the economy at large, AI-generated fraud detection has become a necessary cybersecurity tool to protect our institutions from malicious actors. Adoption of these tools into multi-pronged security measures and continuous innovation will greatly reduce the impact of deepfake attacks, ensuring that the current predictions of devastating financial impact on the industry won’t come to pass.
