How to spot deepfakes in finance and accountancy

In recent years, deepfakes—hyper-realistic images, videos, and audio recordings generated using artificial intelligence (AI)—have emerged as one of the most concerning cybersecurity risks for a variety of industries, including finance and accountancy.

While deepfakes were initially used to create viral videos for entertainment, they now pose a serious threat to financial integrity and compliance, potentially undermining trust in business transactions, audits, and client communications.

The financial sector, particularly accountancy, relies heavily on trust, transparency, and documentation.

As deepfake technology evolves and becomes more accessible, businesses and professionals need to be vigilant in detecting and preventing the use of falsified materials that could cause reputational, financial, and legal damage.

Understanding Deepfakes and Their Risks

A deepfake is created using AI and machine learning algorithms to manipulate media (video, audio, or images) to create realistic but fraudulent representations of real people.

These forgeries can be used for a wide range of malicious activities, such as impersonating executives, altering financial documents, or creating fake invoices.

In the context of finance and accountancy, the risks associated with deepfakes are vast.

Financial fraud could be carried out by faking communications between financial officers, altering documents to misrepresent transactions, or using fake video or audio recordings in regulatory audits.

As cybercriminals exploit this technology, accountancy firms, banks, and financial institutions must take proactive steps to ensure their operations and communications are secure.

The Financial and Reputational Risks of Deepfakes

The financial consequences of deepfakes can be severe. If fraudulent financial transactions are processed using manipulated documents, it could lead to financial losses, legal disputes, and regulatory sanctions.

Additionally, if a deepfake is used to impersonate a senior executive, it could lead to miscommunication, wrong decisions, and even market manipulation.

Furthermore, deepfakes can be used to fake signatures or manipulate official correspondence, making it harder to trace fraudulent activities.

Reputational damage can also be significant. A company found to be a victim of deepfake fraud might suffer a loss of trust among clients, investors, and regulators.

This could result in financial instability, legal consequences, and challenges in retaining customers. The damage to an organisation’s credibility may take years to rebuild.

Spotting Deepfakes in Finance and Accountancy

While deepfake technology is advancing rapidly, there are still ways to detect fraud and minimise the associated risks.

The key lies in identifying the telltale signs of tampered media and building robust systems to safeguard against potential deepfake use.

1. Examine Video and Audio Quality for Anomalies

Although deepfakes have improved in quality, they often still display subtle signs of manipulation. These signs include:

• Inconsistent facial movements: Look for unnatural blinking or lip movements that don’t match speech patterns.
• Unusual lighting or shadows: Deepfake technology struggles with recreating natural lighting and shadows on a face, so inconsistencies may appear in the video.
• Unnatural skin tones or textures: Deepfakes often have artificial-looking skin textures or colours, particularly around the eyes or mouth.
• Inconsistent audio: Audio might be slightly off from the person’s natural voice, such as mismatched lip movements or odd pauses in speech.

2. Cross-Reference and Verify Documents

One of the easiest ways to detect a deepfake is to check the authenticity of financial documents, emails, and communications.

Given the crucial role of documentation in finance, ensuring that all documents are verified can help prevent fraudulent activity:

• Verify signatures: Use electronic signature verification tools to confirm authenticity.
• Audit document metadata: Every document has metadata that records who created, edited, or accessed it. Cross-reference these details for inconsistencies.
• Check document version history: Ensure there’s a clear history of document edits and approvals. Manipulated documents often lack a transparent version history.

3. Utilise Advanced Detection Tools

To counter the growing threat of deepfakes, several AI-based tools and software are now available that can detect manipulated media.

These tools use machine learning to identify patterns and inconsistencies in video and audio files.

• Deepware Scanner: This tool is designed to detect deepfake videos by analysing the subtle facial anomalies that are difficult to spot with the human eye.
• Amber Video: This platform uses AI to flag potential deepfakes and provide evidence of manipulation, making it particularly useful in verifying corporate video content.
• Microsoft Video Authenticator: Developed by Microsoft, this tool analyses videos to detect any manipulation and provides a percentage score of authenticity.

These tools, combined with human oversight, can help finance professionals spot deepfakes early in the process, reducing risks associated with misrepresentation.

4. Establish a Strong Cybersecurity Framework

Preventing deepfake-related fraud in finance also requires businesses to put a strong cybersecurity framework in place.

Protecting sensitive financial data and communications is essential to safeguarding against manipulation:

• End-to-end encryption: Ensure that all communications, whether by email or video conferencing, are encrypted to prevent interception or manipulation.
• Multi-factor authentication (MFA): Use MFA to secure logins and sensitive information, particularly for systems used by executives or auditors.
• Employee training: Regular training on cybersecurity best practices can help employees recognise phishing attacks or social engineering tactics often used alongside deepfakes.

5. Be Cautious with External Communications

Financial services and accountancy firms are particularly vulnerable to deepfakes used to impersonate senior executives.

Firms should take extra care in communication with external stakeholders and clients:

• Verify external requests for financial transfers: Fraudsters may use deepfakes to impersonate a senior executive requesting a payment. Always verify such requests through multiple channels.
• Consider using video verification for sensitive transactions: High-value transactions should be verified using video calls or secure messaging services to confirm the identity of the requestor.

Conclusion

As deepfake technology continues to evolve, the finance and accountancy sectors must remain vigilant.

The potential for deepfake-based fraud is a significant risk, but with the right tools, processes, and training, companies can protect themselves.

By adopting proactive strategies to detect and prevent deepfake fraud—whether through enhanced document verification, AI tools, or solid cybersecurity practices—businesses can minimise the damage of deepfake attacks and maintain the trust of their stakeholders.

As the technology advances, the cost of staying ahead will be far less than the price of recovering from a deepfake-related incident.