Unchecked Deepfakes Pose a Serious Risk to Commercial Enterprises. What Measures Can Be Implemented to Combat Them?
Rising Deepfake Fraud Pose Global Threat and Challenges
Deepfake fraud, a type of identity fraud that uses machine learning to generate fake personas or impersonate existing individuals, is becoming an increasingly significant issue worldwide. In the first four months of 2025 alone, deepfake fraud resulted in over $200 million in losses, with 179 incidents documented, surpassing all of 2024 by 19%.
The industries most affected by deepfake fraud are fintech, payments, crypto, and gambling platforms. These sectors are vulnerable due to the majority of customers being onboarded online without face-to-face communication. The U.S. is particularly affected, with projections estimating deepfake fraud losses could reach $40 billion by 2027.
Deepfake attacks employ AI-generated audio and video to mimic voices and appearances with about 85% accuracy, often used to manipulate victims into urgent money transfers or divulging sensitive information. These scams include financial fraud (23%), explicit content manipulation (32%), and political disinformation, affecting public trust and causing emotional or reputational harm.
Notable incidents include a $25 million loss suffered by the UK engineering firm Arup due to a deepfake CEO scam, while a similar attempt on Ferrari was thwarted. Public figures like politicians and celebrities are heavily targeted due to the availability of extensive media material to train AI models.
Despite emerging deepfake detection technologies, they are locked in an ongoing arms race with deepfake generation methods. Consequently, procedural safeguards like mandatory verification for financial transactions remain critical defense measures. Additionally, legislation such as Denmark’s recent deepfake laws aims to address some enforcement challenges, though cross-border regulatory cooperation is still a major hurdle.
Statistically, over 105,000 deepfake attacks were reported last year globally, though the actual figure could be higher due to underreporting from reputational concerns. Deepfake fraud exposure per contact center averages $343,000, evidencing the large-scale risk to businesses.
In response to these challenges, companies like Sumsub are developing AI technology to detect deepfakes. Sumsub's solution is incorporated into their in-house liveness, a proprietary technology that detects spoofing attempts while authenticating real users in seconds. Sumsub's liveness is an integral part of the KYC flow for many businesses, and in addition to detecting deepfakes, it is widely used for authentication purposes, confirming user actions, detecting duplicate accounts, and more.
Sumsub has a dedicated team of AI/ML experts who constantly work to improve their deepfake detection. The liveness works by analyzing certain artifacts of provided images using the latest AI technologies. With these advancements, businesses can stay ahead of criminals and keep digital platforms, people, and communities safe from advancing threats.
Key Statistics
| Trend/Statistic | Details | |------------------------------------|---------------------------------------------------------------------------------------------------------| | Total reported Q1 2025 loss | >$200 million | | Incident increase Q1 2025 vs 2024 | +19% (179 vs fewer in 2024) | | Victim distribution | 41% public figures, 34% everyday individuals, 18% organizations | | Types of fraud | Financial fraud (23%), explicit content (32%), political manipulation | | Notable incidents | $25M Arup scam (UK), foiled Ferrari CEO voice scam | | U.S. projected losses by 2027 | $40 billion | | Global reported attacks in 2024 | 105,000+ deepfake attacks | | Average loss per contact center | $343,000 | | Current defense | Emerging detection tech, employee training, procedural verification, legislative measures (e.g., Denmark) |
In light of the increasing deepfake fraud, it's essential for the finance industry to enhance cybersecurity measures, given that they are one of the most vulnerable sectors to such fraud. With financial fraud constituting 23% of all deepfake scams, the integration of advanced technology like that offered by companies such as Sumsub, which can detect deepfakes, is critical for safeguarding business interests and customer data.
Technological advancements in deepfake generation methods and detection have taken center stage in the battle against deepfake fraud. Businesses must keep evolving their technology and procedures to proactively combat such threats and maintain consumer trust, as cyberattacks can inflict substantial damage, with each contact center averaging a $343,000 loss due to deepfake fraud exposure.
