June 14, 2023

How Analytics Engines Use Audio Fingerprinting To Identify Scam Calls

The Federal Trade Commission received more than 230,000 reports about phone call fraud in 2022. That’s just the number of calls that got reported — thousands of people probably don’t report scam calls because they don’t know how or don’t want to be bothered with filing complaints.

The increase in scam calls has eroded public trust, making it harder than ever for legitimate businesses to reach consumers. Analytics engines and audio fingerprinting offer a high-tech way to catch scammers before they cause too much financial damage.

What Is Audio Fingerprinting?

Audio fingerprinting uses algorithms to analyze sound files and create digital summaries that describe their content. It can then use those summaries to compare files quickly and find similarities.

You might have used technology like this when you wanted to know the name of a song. Music-recognition apps like Shazam, SoundHound, and Musixmatch compare a song with millions of files. When the algorithms find a match, they can tell you the name of a song you hear.

Audio fingerprinting has diverse uses. For example, copyright owners can use it to ensure they get paid when someone uses their music. The copyright owner doesn’t have to listen to endless hours of recordings. Instead, algorithms can browse albums, individual tracks, movies, television shows, commercials, and other digital recordings to find unlicensed use. The copyright owner can then pursue compensation.

At some point, companies realized they could adjust their algorithms to do more than discover unlicensed use of copyrighted material. They could protect consumers by identifying and stopping scam calls.

What Are Carrier Analytics Engines?

Audio fingerprinting can’t identify scam calls efficiently without carrier analytics engines.

Carrier analytics engines collect information about calls made on a network. Once they collect enough data, they can discover variables common among scam calls. For example, a carrier analytics engine might find that scam calls frequently come from numbers that place more than 50 outbound calls per hour. The next time the algorithms see an excessive number of calls coming from a number, the analytics engine can add a label to that number (e.g., “spam likely”).

Carrier analytics engines provide essential information that helps audio fingerprinting find scam calls. When an analytics engine applies a label to a number, audio fingerprinting algorithms can start looking for calls from other numbers that contain similar content.

How Does Audio Fingerprinting Identify Scam Calls?

Analytics engines typically focus on number behavior to identify likely scam calls. Audio fingerprinting can use those labels to find and block scam calls from other numbers. Importantly, it doesn’t need to know the phone number’s history to determine whether it behaves like a scam caller.

Audio fingerprinting looks at the content of a call, not the behavior of a number. When the software finds the same content coming from different numbers, it infers that those numbers use recorded scripts to reach as many consumers as possible.

Audio Fingerprinting Protects Consumers

Imagine that someone wants to trick people into joining an auto insurance scam. The person wants to automate as much of the process as possible, so they record a script that encourages consumers to stay on the line for more information. Audio fingerprinting would recognize that many of the calls play the same message. That looks suspicious, so the software could apply a “scam likely” label to other calls that play the message.

The software doesn’t need to know what number the calls come from. It just needs to know what content to look for. Then, it can warn consumers not to answer suspicious calls. This number-neutral approach also means audio fingerprinting can identify spam messages when scammers use caller ID spoofing to trick consumers.

Protect Your Business Reputation From Scam Calls

Analytics engines and audio fingerprinting algorithms exist to protect consumers from potential scams. Unfortunately, that goal can come at the expense of companies placing legitimate calls.

If your dialing behavior and call content have traits similar to those of other scam calls, analytics engines might flag your numbers. Suddenly, you’ll find that people don’t answer your calls because their caller ID screens display warning messages.

You can protect your business reputation and continue reaching customers by:

Registering your CNAM data so carriers, analytics engines, and consumers have accurate information about your organization.
Scanning the numbers you purchase to make sure none of them already have negative labels connected to them.
Monitoring your caller ID information across carriers.
Redressing erroneous flags and blocks so you can keep using all of the numbers you own.

Solutions to Protect Your Dialing Reputation

Caller ID Reputation has several solutions that make it easier to protect your business reputation from scam calls.

Device Cloud – This branded call monitoring tool shows you what appears on customer caller ID screens, so you don’t have to wonder what your contacts see. You get screenshots from actual devices, so you know what gets displayed on their screens when you call them.
Phone Number Scoring – This technology uses data aggregation to determine when analytics engines might have applied labels or blocks to your numbers. You’ll also get real-time notifications when it finds a flag.
Number Redress Remediation – Our managed team simplifies the redress process to get your numbers back into rotation as soon as possible whenever you find your numbers have inaccurate labels.

Would you like to see how Caller ID Reputation’s suite of products can protect your brand and number reputation? Start a five-day trial!