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Deepfakes and Financial Fraud Prevention: Dispatches from the AI-Powered Frontline

It’s forecast that the AI cybersecurity market will grow from $22 billion in 2023 to $60 billion by 2028. In 2023, fraud scams and schemes totaled $485.6B in projected losses globally, while an estimated $3.1T in illicit funds worked its way through the global financial system.

From transforming biometric data analysis to dissecting document authenticity and monitoring subtle behavioral cues, AI is on the frontline of weapons used in financial fraud prevention and to ensure secure transactions. The need for those solutions has never been greater.

In this article, we’ll explore AI’s pivotal role in boosting regulatory compliance and customer trust in financial services, including how it not only enhances existing know your customer (KYC) security protocols, but actively shapes them, introducing dynamic and real-time solutions to combat identity theft, document forgery, and financial fraud.

Biometric Breakthroughs in ID Verification

The global biometric technology market size is estimated to reach $150 billion by 2030. In the digital age, ID verification has matured from simple password protection to the complexities of biometric analysis. AI algorithms are increasingly used to analyze biometric data such as facial recognition, fingerprints, and voice recognition.

By cross-verifying physical biometrics with digital identity documents, AI-augmented systems can ensure the person behind the screen is exactly who they claim to be. These systems can detect subtle anomalies in biometric data that may indicate the use of deepfakes or manipulated images/videos.

Outsmarting ID Spoofs

In the high-stakes world of banking security, AI-driven liveness detection techniques are setting new standards in the fight against identity spoofing. As the software increases in complexity and power, so does its ability to manipulate photographs, videos and masks, and its prevalence. It’s not enough for financial institutions to simply keep up—they need to stay ahead.

This means AI systems are on the frontline, requiring users to perform live actions like blinking, smiling, making head movements, or sayins specific words. It’s not just about seeing a face; it’s about seeing it move. Analyzed in real-time, these actions confirm the presence of a live person, not just a manipulated image or “mask.” This method transforms the KYC process from a static check into a dynamic verification process, where AI can ensure the authenticity of each interaction.

AI’s Overhaul of Document Verification

AI can also cross-verify the physical biometric data with digital identity documents to ensure consistency and authenticity. AI technology can scrutinize the authenticity of various documents submitted during the KYC process. This includes checking for forged or altered documents like passports, driver’s licenses, and utility bills. AI systems can detect inconsistencies in fonts, layout, and other document features that are typically invisible to the human eye, ensuring that every submission is as legitimate as it appears.

It’s also creating more frictionless onboarding. For example, in the UK, HSBC is using “selfie” biometrics for identity verification within its mobile banking app. Customers can open new accounts by uploading a photo ID and a selfie: securing the identity verification and speeding up the onboarding process.

Behavioral Analysis: AI, the Ultimate Watchdog

AI-powered systems act like a watchdog in financial fraud prevention, monitoring the nuances of human interaction during KYC processes and shining a spotlight on suspicious behaviors. It’s not just about what users do, but how they do it—mouse movements, keystroke dynamics, and navigation patterns are all under relentless scrutiny. These aren’t just random data points; they’re behavioral biometrics, finely tuned to distinguish the genuine user from the bot or identity thief hiding behind a synthetic persona.

With AI on the lookout, typical human interactions have a benchmark, and anything deviating from this norm triggers alarms. This high-tech scrutiny ensures that behind every transaction and login lies a real person, not a programmed imposter. In the battle against digital deception, AI can be the gatekeeper.

Flagging Anomalies

AI models trained on vast transactional data are the new guardians in financial fraud prevention. These models are trained to discern the subtle nuances of transaction patterns, honing in on anomalies that might imply fraud. But it doesn’t end there. The true power of these AI models lies in their adaptability, which is key in an era of real-time transactions.

As fraudsters evolve, so too do these systems, learning and adapting in real-time to counter new tactics with laser-guided precision. This dynamic approach means that with each transaction, AI models grow smarter, making them formidable foes.

To dive deeper into how AI-powered compliance is helping thwart financial crime, download our whitepaper, “Financial Crime Prevention: Step Up Compliance Efficiency with AI.”

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Guillaume Casterman

Director of International Projects & Knowledge, Financial Crime & Compliance

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