Can you distinguish between what’s real and what’s not in audio and video? With the rapid rise of deepfake attacks, this challenge is no longer theoretical—it’s a growing threat to businesses worldwide.

Fueled by advancements in artificial intelligence (AI), machine learning, and other emerging technologies, deepfakes have become increasingly accessible and cost-effective, amplifying their potential for misuse.

Voice-enabled AI agents, powered by widely accessible AI tools, can now perform common scams at scale. Meanwhile, worldwide adoption of voice-enabled AI agents is projected to reach USD 31.9 billion from 2024 to 2033.

The cost of deepfake attacks goes beyond immediate financial losses. These attacks can lead to brand erosion, compliance penalties, and recovery expenses.

Unsurprisingly, 90% of consumers have raised concerns about deepfake attacks, as revealed in our 2023 Deepfake and Voice Clone Consumer Report. Without proactive defenses, organizations are left vulnerable to these sophisticated fraud tactics.

In this article, we’ll explore:

• The various types of deepfake attacks and why they’re rising
• The direct and indirect financial consequences for organizations
• Corporate vulnerabilities and practical strategies to mitigate risks
• How Pindrop^® Pulse™ Tech offers advanced solutions to combat these threats

Types of deepfake attacks

Deepfake technology generates hyper-realistic synthetic media that mimics individuals and fabricates misleading situations. These attacks manifest in multiple forms, targeting specific organizational vulnerabilities. The main types include:

Audio deepfakes

Scammers use AI-generated audio to replicate a person’s voice, often impersonating executives, public figures, and others convincingly.

These deepfakes can manipulate phone-based authentication systems, posing significant risks to contact centers in industries like insurance or financial institutions.

Video deepfakes

AI-generated videos manipulate or alter facial expressions, actions, and more to mimic individuals and create fabricated scenarios.

In insurance and financial institutions, these videos can deceive stakeholders or employees by portraying false statements or actions, which can lead to reputational damage and a breakdown of organizational trust.

Synthetic identity creation

Combining AI-generated visuals and voices, attackers create entirely fabricated identities to bypass traditional security checks. This method is increasingly used in financial scams and other fraudulent activities, making detection more challenging.

Rising concerns about deepfake attacks

As mentioned, the proliferation of AI systems and open-source tools has made deepfakes easier and cheaper. Fraudsters can now generate convincing synthetic media quickly.

This growing accessibility raises significant concerns about AI safety and the preparedness of organizations to handle these evolving threats.

Notable deepfake incidents involving organizations in 2024:

• The $25 million deepfake scam at Arup. Cybercriminals used AI-generated deepfakes to impersonate Arup’s CFO and other employees during a video conference, convincing a staff member to transfer $25 million to Hong Kong bank accounts.
• The WPP CEO impersonation attempt. Fraudsters targeted WPP, the world’s largest advertising group, by creating a deepfake voice clone and fake WhatsApp account to impersonate CEO Mark Read. The attack involved using YouTube footage to deceive employees during a virtual meeting.
• The YouTube cryptocurrency scams. Scammers orchestrated “Double Your Crypto” frauds using AI-generated deepfakes of public figures like Elon Musk, Ripple’s CEO Brad Garlinghouse, and Michael J. Saylo. They hijacked YouTube accounts to promote fake Bitcoin giveaways, stealing over $600,000 from victims.

Recent findings highlight the rise in deepfake scams:

• Research revealed that deepfake-powered scams targeted 53% of businesses, and 43% of those fell victim to the attacks. 
• In this survey of 1,533 U.S. and U.K. finance professionals, 85% viewed deepfake scams as an existential threat to their organization’s financial security. However, only 40% of professionals surveyed said protecting the business from deepfakes is a top priority.
• Additionally, an early study showed that we are only 53.7% accurate in identifying deepfake audio, and this accuracy is expected to decline as AI technology advances.

Direct financial losses from deepfake attacks

The financial repercussions of deepfake attacks can be devastating. In a single orchestrated attack, businesses can lose millions of dollars.

Fraudulent transactions

Deepfake scams often manipulate financial processes, enabling attackers to complete unauthorized payments or withdrawals. For example, synthetic audio may impersonate a company executive, instructing finance teams to transfer funds to fraudulent accounts.

The scale of potential losses is alarming. A recent Deloitte Center for Financial Services report estimates that fraud losses enabled by generative AI could reach $40 billion in the U.S. by 2027, highlighting the critical need for enhanced fraud detection measures.

Identity theft

Deepfakes also facilitate identity theft by enabling fraudsters to mimic trusted voices, granting them access to confidential accounts and sensitive information. These attacks often target financial institutions, where stolen identities can lead to:

• Access to restricted accounts: Fraudsters use deepfake technology to bypass security checks, posing as customers or employees to exploit banking systems.
• Siphoning of financial assets: Once access is granted, attackers can withdraw funds, compromise assets, or initiate fraudulent transactions.

Indirect financial losses from deepfake attacks

Brand and reputation damage

The aftermath of a deepfake attack can erode public trust in an organization. Companies that fail to prevent or address these attacks risk losing consumer confidence and long-term profitability.

Legal and compliance costs

If deepfake fraud leads to data breaches or financial losses, organizations may face regulatory scrutiny or lawsuits. Non-compliance with evolving security standards can result in significant penalties.

Mitigation and recovery expenses

Post-attack recovery often involves forensic analysis, rebuilding security protocols, and investing in employee training—costly endeavors that strain resources.

Corporate and organizational impacts of a deepfake attack

Internal security breaches

Deepfake attacks often exploit vulnerabilities in an organization’s internal systems, bypassing traditional security measures like password-based authentication. For example:

• A deepfake-generated audio clip of a CEO might direct an employee to transfer funds, bypassing internal verification protocols.
• Impersonation of employees through synthetic voices can facilitate unauthorized access to sensitive systems, disrupting operations and compromising data integrity.

Once trust within internal communications is undermined, organizations may face a cascading effect of security breaches, requiring significant time and resources to restore confidence and operational normalcy.

Employee training and preparedness

Employees are often the first line of defense against deepfake fraud, but most are unprepared to recognize the sophisticated tactics used in these attacks. Without adequate training, employees may:

• Fall victim to deepfake-generated impersonations during phone or video interactions.
• Share sensitive information or grant unauthorized access based on fabricated directives.

Organizations must invest in ongoing training programs to:

• Educate staff on identifying red flags in voice and video communications.
• Enhance awareness of the potential risks posed by deepfakes and other AI-enabled threats.

This proactive approach minimizes vulnerabilities and fosters a culture of vigilance.

Loss of intellectual property

Deepfake technology is also being used to target intellectual property (IP). Fraudsters may exploit synthetic media to:

• Coerce employees into revealing proprietary data or trade secrets.
• Fabricate internal communications to gain access to sensitive R&D projects.

The theft or misuse of IP can have long-term consequences, including the loss of competitive advantages, decreased market share, and reputational harm.

How to protect against deepfake attacks

Technological solutions

Adopting advanced tools and technologies is critical to effectively detecting and mitigating deepfake threats. Key solutions include:

• Liveness detection: This technology analyzes subtle human characteristics in voice or video interactions to identify synthetic content. Pindrop^® deepfake detection technology, for instance, verifies that a voice is human, not machine, helping to ensure reliable customer interactions.
  
• Voice biometrics analysis: By analyzing vocal features, such as pitch, tone, and rhythm, voice biometrics analysis can identify anomalies indicative of a deepfake. With tools like Deep Voice^Ⓡ tech, you can enhance caller authentication with a neural network-based biometric analysis engine.
  
• Deepfake fraud detection software: AI-powered tools analyze audio and video for signs of manipulation, flagging potential deepfake threats in real-time. Pindrop® Pulse™ Tech enhances fraud detection and authentication with cutting-edge audio deepfake detection, offering industry-leading accuracy and seamless integration for real-time detection in contact center environments.
  
• Multifactor Authentication (MFA): Combining voice authentication with additional factors like PINs, one-time passwords, or facial recognition adds an extra layer of security. MFA helps ensure that even if one security layer is compromised, others remain intact. Pindrop® multifactor authentication solution helps contact centers authenticate legitimate callers quickly and accurately.

Deepfake compliance measures

Organizations must establish internal regulatory processes to manage the risks associated with deepfakes while adhering to emerging external regulations. Internally, companies should develop clear guidelines for creating, disseminating, and detecting AI-generated content. This includes:

• Internal auditing processes: Regular reviews of AI tools and systems to ensure compliance with ethical standards and industry best practices.
  
• Awareness training: Involves educating employees on identifying and managing deepfake risks, particularly for teams handling sensitive communications or transactions.

Externally, organizations should stay informed about evolving laws and proposed regulations.

Defend against deepfake attacks with Pindrop^® Pulse™ Tech

With Pindrop® Pulse™ Tech and Pindrop® Pulse™ Inspect technology, your organization can leverage innovative solutions to tackle the increasing issue of deepfakes in real time.

With features like liveness detection, real-time monitoring, and many more innovative solutions, you can help safeguard your organization against synthetic fraud.

These tools can assist you in preserving trust and operational integrity while reducing the financial impact of deepfake attacks. Request a complimentary deepfake demo today.