Someday soon, you may be able to unlock your car or even log in to your favorite streaming app on a hotel TV simply with the sound of your voice.

Pindrop, an Atlanta company that now primarily offers sound-based fraud detection tools for call centers, plans to release a service later this year that will let connected devices verify who they’re talking to, turning the human voice into a combination of a username and password.

“Everybody has a unique voice, and everybody has a unique behavior in the way they say things,” says Pindrop cofounder and CEO Vijay A. Balasubramaniyan.

Secure voice recognition login could make it safer to conduct complex transactions through digital assistants like Apple’s Siri and Amazon’s Alexa—and it could prevent scenarios in which loud TV advertisements or children playing with devices accidentally give commands (and buy products) via such devices. And if different devices adopted Pindrop or another common voiceprint provider, users wouldn’t have to separately program each device to recognize their individual speech patterns and could log in to new devices simply by speaking, says Balasubramaniyan.

The technology should also be able to detect when people are distorting their voices or playing recordings of other people speaking—fraud techniques he says they already encounter in the call center market, where Pindrop reports it works with eight of the top ten U.S. banks and two of the top five insurers to detect phone scams. Call center customers pay based on call volume, and Pindrop will likely roll out similar cost structures for IoT device makers he says.

For phone fraud detection, Pindrop’s systems don’t just listen to the sound of callers’ voices as they dial in to place orders or transfer funds—it also uses other audio data to determine where people are calling from and the type of phones and networks they’re using. Different models of phones introduce their own acoustic signatures into conversations, Balasubramaniyan says. And phone networks in different parts of the world transmit different sound frequency ranges based on different requirements for balancing bandwidth consumption and voice quality. Even internet calling tools, like Skype and Google Voice, break conversations into different-sized audio packets, making it possible for Pindrop’s algorithms to tell them apart.

“Every time you drop a packet, you’re having a break of 30 milliseconds as opposed to 20 milliseconds or whatever else,” Balasubramaniyan says.