The age of AI-driven fraud Technology is evolving at an unprecedented pace, offering remarkable benefits while simultaneously introducing sophisticated risks. Among the most concerning advancements is deepfake technology. Fraudsters are now leveraging real-time deepfakes—AI-generated video and audio that mimic a person’s voice, appearance, and movements in real time—to execute various fraudulent schemes. As fraudsters leverage this technology to manipulate trust, deceive financial institutions, and bypass traditional security measures, the financial sector must recognize and respond to this new frontier in fraud prevention.

The implications are profound. Fraudsters can use deepfake technology to execute highly sophisticated scams that easily bypass traditional security checks. Imagine a CEO’s voice cloned with near-perfect accuracy to authorize a fraudulent wire transfer, leading to massive financial losses before anyone realizes what’s happened. Or a deepfake video of an employee tricking authentication systems into approving a high-value transaction. Attackers can take social engineering to the next level, manipulating executives, clients, and financial institutions into trusting fake identities, approvals, or even policy changes. As fraud methods evolve, so must our defenses—businesses need AI-driven detection, stronger authentication layers, and continuous vigilance to stay ahead. These are no longer hypothetical scenarios—they are occurring today, posing severe threats to financial stability and consumer confidence.

Real-world incidents highlighting the threat 

Recent high-profile cases worldwide underscore the growing danger of deepfake fraud:

  • Hong Kong: A finance executive was deceived into transferring $25 million after receiving a deepfake video call impersonating the company’s CFO.
  • United Kingdom: British universities reported applicants using deepfake technology to falsify online interviews and secure fraudulent admissions.
  • United States: A U.S.Senator was targeted in a deepfake operation where fraudsters, posing as a Ukrainian official, attempted to extract sensitive political information.

The Canadian banking sector is not immune to these threats. The Canadian Bankers Association and Financial Consumer Agency of Canada have issued warnings about AI-driven fraud, with fraud cases nearly doubling over the past decade—from 79,000 in 2012 to 150,000 in 20221 as per Statistics Canada. The Financial Consumer Agency of Canada reports that 15% of Canadians experienced financial fraud in the last two years, up from 12% in 20232. While multiple factors contribute to this rise, AI-driven fraud techniques—such as deepfake scams and automated social engineering—are making attacks more scalable, personalized, and difficult to detect.

A recent Gartner report predicts that by 2026, 30% of enterprises will no longer consider identity verification and authentication solutions reliable in isolation due to deepfakes3. This highlights the growing sophistication of AI-powered fraud and its impact on financial security. As fraudsters continue to refine their use of AI, the ability to distinguish between legitimate and synthetic identities is becoming a pressing challenge for banks and regulators alike.

The shift in fraud prevention strategies

Traditional fraud prevention mechanisms, such as passwords, PINs, and knowledge-based authentication, are proving inadequate in the face of AI-generated fraud. Financial institutions must transition from reactive fraud detection to proactive threat mitigation, that can help organizations stay one step ahead of cybercriminals, focusing on leveraging advanced technologies like AI-driven detection, deepfake detection tools, and multi-factor authentication to identify and prevent fraudulent activities before they occur. It also involves establishing secure communication channels, implementing continuous monitoring systems, conducting regular fraud risk audits, and providing ongoing employee training and user education to effectively detect, mitigate, and respond to emerging fraud risks in real time.

In addition to leveraging advanced detection technologies, financial institutions should incorporate Security Red Teams into their fraud prevention strategies. These specialized teams simulate cyberattacks and fraud attempts in an organization's defences, to identify vulnerabilities. Red Teams conduct adversarial testing by creating and deploying deepfake scams, social engineering attacks and AI-driven fraud attempts, to assess the institution’s readiness. Their insights help identify weak spots, refine detection algorithms, and enhance employee training by identifying where organizations need to focus. By continuously stress-testing systems, Red Teams proactively mitigate AI-based fraud risks.

The key challenge: How can banks verify identity in a world where seeing—and hearing—is no longer believing?

  • Defensive AI vs. offensive AI: As fraudsters leverage AI to execute highly sophisticated attacks, financial institutions are responding with equally advanced defensive solutions to safeguard their operations and customers. The evolving threat landscape highlights the urgent need for cutting-edge technologies to stay one step ahead.
  • Behavioral biometrics: AI-powered behavioral analysis is increasingly crucial in fraud prevention, with institutions leveraging it to monitor typing speed, mouse movements, and navigation patterns to identify anomalies. For example, a leading LATAM bank successfully reduced social engineering fraud targeting mobile users by 67%, using behavioral biometrics. The system continuously adapts to users' normal behaviors, improving detection accuracy and reducing false positives, which ultimately strengthens security measures.
  • Voice & facial recognition analysis: As deepfakes and voice manipulation rise, AI models are identifying discrepancies in speech and facial features to detect fraud. Voice biometrics in banking can flag mismatched voiceprints during calls, preventing fraudulent withdrawals worth millions. AI systems trained to recognize deepfake manipulation are improving fraud detection. Studies from MIT and Google show just one minute of voice data can create convincing deepfake audio, raising concerns about the effectiveness of voice biometrics. This issue is so significant that regulators and major financial institutions are being questioned about their strategies to address deepfake voice fraud.
  • Real-time transaction monitoring: Machine learning algorithms are routinely employed to detect suspicious activity in real-time, analyzing vast quantities of transaction data to identify patterns that deviate from the norm. Recent case studies at leading North American and European banks showcase how real-time monitoring detects fraud attempt involving compromised accounts, halting the transaction before any financial loss occurred. Such systems can adapt and refine their detection capabilities based on newly identified patterns of fraud.
  • Blockchain & digital identity verification: Blockchain technology is increasingly used to secure digital identities in an immutable system, providing greater transparency and reducing fraud. Financial institutions are adopting blockchain-based identity verification, allowing customers to prove their identity quickly and securely across multiple services. Using distributed ledger technology reduces the risk of fraudulent account creation and manipulation, while providing a consolidated view of clients and significantly lowering both the costs and time involved in identity verification, making the financial ecosystem safer for all.

Global and national measures against deepfake fraud 

Recognizing the escalating threat, governments and private sectors worldwide are implementing measures to combat deepfake fraud:

  • Regulatory actions: China mandates that AI-generated content carry clear disclosures to inform viewers of its synthetic nature.4
  • Technological solutions: Companies like Reality Defender are developing AI-powered tools capable of detecting real-time deepfake videos.
  • Legal frameworks: Australia imposes substantial fines on social media companies failing to remove scam content involving deepfakes.5
  • Canadian response: While Canada lacks specific deepfake regulations, the Competition Bureau Canada urges vigilance against AI-generated scams, emphasizing the importance of recognizing red flags such as unrealistic videos, speech inconsistencies, and urgent messages.

The ethical and regulatory dilemma 

As financial institutions adopt AI-powered fraud detection, they face a growing debate: security versus privacy. Regulatory bodies are attempting to strike a balance, yet the pace of AI innovation often outstrips compliance efforts. Financial leaders must collaborate with regulators, cybersecurity experts, and policymakers to ensure that fraud prevention measures enhance security without infringing on privacy rights.

Preparing for the inevitable 

The financial industry stands at a critical juncture. The question is not if deepfake frauds and AI driven threats will become a widespread problem, but when it will impact an institution.

  • Are financial institutions equipped to detect and mitigate deepfake threats?
  • How can banks build customer trust when digital identities can be easily manipulated?
  • What steps can organizations take today to avoid becoming the next victims of AI-powered fraud?

A call to action 

Deepfake fraud is no longer a future concern—it is a present-day reality. Financial institutions must act now by implementing AI-powered fraud prevention strategies, collaborating with regulators, and fostering industry-wide innovation.

Fraud Prevention Month serves as a timely reminder that staying ahead of fraud requires anticipation, innovation, and collaboration. The financial sector must rethink security, redefine trust, and reshape how we protect digital assets.

How is your institution preparing for the rise of deepfake fraud and AI-driven threats? Let’s start the conversation.

1: Canada.ca, The rise of AI: Fraud in the digital age, March 1,2024

https://www.canada.ca/en/competition-bureau/news/2024/03/the-rise-of-ai-fraud-in-the-digital-age.html

2: The Financial Consumer Agency of Canada

https://x.com/FCACan/status/1897360012244128029/photo/1

3: Gartner, Gartner Predicts 30% of Enterprises Will Consider Identity Verification and Authentication Solutions Unreliable in Isolation Due to AI-Generated Deepfakes by 2026 February 1, 2024

Gartner Predicts 30% of Enterprises Will Consider Identity Verification and Authentication Solutions Unreliable in Isolation Due to AI-Generated Deepfakes by 2026

4 : Wired, China’s Plan to make AI watermarks Happen, By Zeyi Yang, Sep 27, 2024

China’s Plan to Make AI Watermarks Happen | WIRED

5 : Reuters, Australia threatens fines for social media giants enabling misinformation, By Byron Kaye, Sep 12, 2024

https://www.reuters.com/technology/australia-threatens-fines-social-media-giants-enabling-misinformation-2024-09-12/