
Chief Executive Officer
Published: November 18, 2025

AI deepfakes can impersonate executives so convincingly they bypass controls and authorize catastrophic transactions, deepfake fraud is now a board-level financial, regulatory, and reputational risk.
Acting now means cross-channel detection (email, phone, video), out-of-band verification for high-stakes requests, employee training, and AI-incident-ready compliance.
Deepfake fraud is the use of AI-generated synthetic audio or video to convincingly impersonate executives, colleagues, or partners and trick people into authorizing fraudulent transactions or handing over sensitive data. Because the forgeries can fool even discerning leaders, deepfake fraud is now a board-level financial, regulatory, and reputational risk.
The catch: these forgeries bypass traditional security controls by targeting human trust across email, phone, and video, so single-channel defenses miss them, and a “wait-and-see” approach leaves the organization exposed.
In This Article
The sophistication of artificial intelligence has given rise to a significant business risk: AI-generated deepfakes. These synthetic audio and video forgeries have become so realistic they can deceive even discerning executives, creating direct threats to your organization's financial stability, regulatory standing, and brand reputation. What was once a technical curiosity is now a strategic imperative that requires board-level attention.
This briefing outlines the financial and operational impact of deepfake threats, clarifies new regulatory obligations, and presents a strategic framework for mitigating these advanced risks.
Deepfake technology enables attackers to execute highly convincing impersonations of key personnel, bypassing traditional security controls to authorize fraudulent transactions and access sensitive data. The financial ramifications are substantial and immediate.
High-Value Financial Fraud:
A well-documented incident involved a finance employee transferring $25 million to criminals after being deceived by a deepfake video conference that convincingly replicated the company's CFO and other executives. This case demonstrates the potential for catastrophic, single-event losses.
Systemic Operational Risk:
The 2024 ransomware attack on Ascension, a major healthcare provider, resulted in an estimated
$1.5 billion loss. While not a direct deepfake attack, it highlights the financial devastation that can follow from sophisticated cyber intrusions, a category where deepfakes are increasingly prevalent.
Compromised Talent Acquisition:
Gartner projects that by 2028, one in four job candidate profiles will be synthetic. This trend poses a direct threat to organizational security by facilitating the placement of malicious insiders who can exfiltrate intellectual property or enable further attacks.
State-Sponsored Corporate Espionage:
The infiltration of 320 companies by North Korean IT workers in the past year alone underscores the scale of advanced deception tactics being deployed against corporations. These operations often aim to steal funds or proprietary information, posing a direct threat to competitive advantage and financial health.
Global regulatory bodies are moving swiftly to address the risks associated with AI, establishing compliance frameworks that carry significant financial penalties for non-adherence.
The European Union's AI Act is a landmark regulation that classifies AI systems based on risk. Deepfakes fall under specific transparency mandates, requiring organizations to disclose when media is artificially generated. This act sets a global precedent, signaling a broader regulatory expectation for robust AI governance and risk management.
For executives, this means that proactive compliance is essential. Regulators and auditors will expect to see evidence of due diligence, including:
Quantified Risk Assessments: Formal evaluation of potential AI-driven threats.
Technical and Organizational Controls: Implementation of appropriate security measures.
Tailored Incident Response Plans: Protocols designed specifically for AI-generated incidents.
Failure to meet these standards not only exposes the organization to direct attack but also creates significant compliance and financial risk.
A robust defense strategy against deepfake threats requires a holistic approach that integrates advanced technology, stringent processes, and comprehensive training.
Adopt Advanced Detection Technologies:
Deploy security solutions capable of detecting threats across diverse communication channels, including email, phone, and video. The most effective tools apply shared awareness by aggregating and analyzing multiple metadata elements—such as sender identity, device details, network patterns, and file properties—to identify suspicious activity that may be missed when monitoring a single vector.
Implement AI-powered systems that evaluate media for subtle artifacts, behavioral inconsistencies, and metadata anomalies, enhancing detection accuracy.
Integrate real-time detection tools into communication platforms and security workflows to provide automated, cross-channel defense against synthetic media and deepfake threats.
Implement Robust Verification Protocols:
Mandate multi-channel, out-of-band verification for all high-stakes requests, such as fund transfers or changes to sensitive system credentials.
Establish a system of secure challenge questions or passphrases for identity verification during verbal or video interactions.
Foster a Culture of Security Through Employee Training:
Conduct regular, targeted training programs to educate employees on the mechanics and indicators of deepfake attacks.
Utilize social engineering simulations with deepfake elements (e.g., AI-generated voice notes) to test and reinforce employee vigilance.
Strengthen Data Protection and Governance:
Enforce data minimization policies to limit the public availability of audio, video, and image data of key personnel.
Update incident response plans with specific protocols for containing, investigating, and reporting deepfake-related security events.
The threat from deepfake technology represents a quantifiable risk to your organization's financial health, regulatory compliance, and brand reputation. A "wait-and-see" approach is no longer a viable option.
By making a strategic investment in cross-channel threat detection, reinforcing business processes with robust verification protocols, and cultivating a security-aware culture, you can build a resilient defense. This proactive framework will safeguard corporate assets, ensure regulatory alignment, and protect the integrity of your executive leadership. The time for decisive action is now.
SOURCES & REFERENCES
Criminals Use Generative Artificial Intelligence to Facilitate Financial Fraud, FBI Internet Crime Complaint Center (IC3), Public Service Announcement (December 3, 2024). Warns that criminals use AI-generated media and voice cloning to scale fraud, and recommends out-of-band verification.
Alert on Fraud Schemes Involving Deepfake Media Targeting Financial Institutions (FIN-2024-Alert004), U.S. Treasury Financial Crimes Enforcement Network (FinCEN) (November 13, 2024). Reports rising deepfake media used to bypass identity verification.
Justice Department Disrupts North Korean Remote IT Worker Fraud Schemes, U.S. Department of Justice (August 8, 2024). Charges in schemes where overseas workers used stolen identities to obtain remote jobs at U.S. companies.
Science & Tech Spotlight: Combating Deepfakes (GAO-24-107292), U.S. Government Accountability Office (March 11, 2024). Finds that existing detection methods may not accurately identify deepfakes in real-world conditions.
Artificial Intelligence Risk Management Framework: Generative AI Profile (NIST AI 600-1), NIST (July 26, 2024). Maps generative-AI risks to concrete governance, assessment, and incident-response actions.
Reducing Risks Posed by Synthetic Content (NIST AI 100-4), NIST / U.S. AI Safety Institute (November 2024). Reviews the technical limits of synthetic-content detection and authentication.

Chief Executive Officer
CEO/Founder of Netarx LLC, Real-time detection of deepfake and social engineering threats via enterprise video, voice and email. Managing Partner of Koach Capital, a Private Equity firm managing a multitude of commercial real estate (CRE) funds whose focus is retail sale-leasebacks. Sandy's entrepreneurial success began by founding a network integration and services provider that served large enterprises. We focused on advanced technologies including Business Intelligence (BI), Network & Information Security, Virtualization, Storage Area Networks, Unified Communications and Data Center Services. In 2009, Netarx acquired the VAR business of Analysts International (including Sequoia and Entree Systems). In 2011 Netarx was acquired by Logicalis (a division of Datatec - Symbol LSE: DTC) and stayed on as its Chief Technology Officer. He continued to build by founding Verge.io (Formerly Yottabyte) and Service.com. Also, Sandy served as a General Partner of Ludlow Ventures, a venture capital fund focusing on investments in early-stage tech companies. Sandy contributes to the community via lectures, publications and developing new technologies - he currently holds 8 Patents.
It’s the use of AI-generated synthetic audio or video to impersonate executives, colleagues, or partners and deceive people into authorizing fraudulent transactions or sharing sensitive data, bypassing traditional security controls by exploiting human trust.