January 31, 2024

How Voice Impersonation Scams Exploit Generative AI

How Voice Impersonation Scams Exploit Generative AI

Generative AI has gained massive popularity in the past year and continues to be employed for a variety of uses in business. However, scammers have taken note and are exploiting this new technology to defraud consumers more efficiently.

What Is Generative AI?

Generative AI is a type of artificial intelligence that can create text, images, music, and other media. For example, you could ask a generative AI tool like ChatGPT to write a story that includes a few specific plot points. ChatGPT could use its algorithm and the information you provide to create a story that closely matches your expectations.

In most cases, generative AI produces useful content that helps people do their jobs more efficiently. Unfortunately, scammers can also harness the power of generative AI. Voice impersonation scams are some of the most recent ways criminals take advantage of unsuspecting consumers.

Voice Impersonation Scams Are on the Rise

The Federal Trade Commission (FTC) reports that impersonation scams stole $2.6 billion in 2022. Generative AI likely played a stronger role than in previous years as more criminals gained access to the technology.

How Scammers Are Using Generative AI

Scammers use generative AI in several ways, such as removing accents from their voices, generating scam scripts, and unleashing AI-powered bots that can operate independently.

Vocal cloning, however, stands out as the biggest threat.

At Hiya’s 2023 State of the Call Summit, the company’s Chief Product Officer, James Lau, demonstrated how criminals are using generative AI to make their voice impersonation scams more effective. Lau took simple steps to clone the voice of Hiya’s CEO, Alex Algard, and asked an employee in the finance department to wire $20,000 to an account.

Lau used a YouTube clip to clone Algard’s voice with a generative AI tool used in voice impersonation scams. He then downloaded number spoofing software to make the call appear as though it was coming from Algard’s number. The result was a recording that sounded like Algard and looked like it came from his number. It would fool practically any employee unaware of how effectively voice impersonation scams work.

Some AI tools can even generate content in real time. If the employee had asked “AI Algard” a question, the clone would have created a reasonable response. In many cases, conversing with an AI voice generator feels as seamless as talking to a real person.

How AEs Identify Spam Calls

Analytics engines (AEs) play a critical role in stopping voice impersonation scams before they reach consumers and damage a phone number’s reputation. AEs look at all aspects of a call to determine its validity. Some of the details AEs consider include the call’s origin, the phone number’s history, whether the caller and recipient have interacted before, and STIR/SHAKEN information. Some of the most sophisticated AEs can even use “audio fingerprints” to identify scam calls.

When AEs detect anything suspicious, they can add a warning label or flag to help consumers decide whether they want to answer calls.

AEs Use Adaptive AI to Identify Spam

Analytics engines need to evolve so they can stay ahead of the technologies used by scammers. Over time, adaptive AI gathers more information and improves its approach to combating spam. It learns what works well and applies those methods to future calls. Even when criminals pivot to avoid detection, adaptive AI learns from their behaviors to stay one step ahead.

EU Enacts The AI Act

Governments also have a role to play in fighting voice impersonation scams using generative AI. The European Union’s AI Act shows how some of the world’s most influential governments want to regulate AI. Ideally, regulations encourage companies to take advantage of AI’s benefits while curbing negative outcomes.

The EU’s AI Act bolsters government authority to pursue criminals using AI nefariously. How the regulations are interpreted and enforced will likely change over the years, but the AI Act establishes a foundation for monitoring high-risk AI projects and stopping criminal enterprises, potentially including those using AI for voice impersonation scams.

Impact on Businesses From Call Blocking and Labels

Governments have serious reasons to worry about how individuals and organizations use artificial intelligence technology. Businesses also have good reasons to take scams seriously.

Phone calls remain a critical way for businesses to reach leads and customers. As more carriers and third-party apps try to protect consumers, they have taken a more aggressive stance against potential spam. The effects of call blocking and negative labels could devastate some businesses. According to a report from TransUnion and Omdia, 70% of businesses say that call blocking and labels have cost them 10% or more in revenue within the last six months.

Protecting people from voice impersonation scams is an important part of improving consumer trust. Unfortunately, those protections can damage legitimate businesses trying to reach their customers.

Identify, Remediate, and Redress Caller ID Flags

Analytics engines will play an increasingly important role in protecting consumers from scammers using generative AI. Unfortunately, emerging AEs will make mistakes similar to the ones already used to stop spam. That means they could erroneously flag your numbers.

If your numbers get flagged, you will need to take several steps to restore its reputation.

1. Identify Flags

First, you must identify carrier and AE flags attached to your number. That often requires monitoring caller IDs vigilantly. Caller ID flags can come from consumer flagging, calling behavior, or call spoofing attempts.

2. Remediate Problematic Dialing Practices

Second, you need to remediate the reasons a carrier or AE has flagged your number. For example, you might need to adopt more ethical dialing practices to align with industry standards.

3. Redress Flags and Labels

Finally, you have to contact the carriers and AEs to have flags removed from your number.

These steps can take a lot of time and effort, especially when your business uses multiple phone numbers.

Managing Your Caller ID

Caller ID Reputation streamlines the whole process by monitoring phone numbers for flags and negative labels. Device Cloud gives you screenshots from real mobile devices connected to real carriers, so you see exactly what your customers see on their screens.

Caller ID Reputation also has a team of remediation professionals to help you address any issues that attract flags. The team can also contact carriers and AEs to dispute erroneous flags from your phone numbers.

Schedule a demo to learn more about Caller ID Reputation’s innovative approach to helping businesses reach their contacts.