By: Tim Prugar
Yes. Yes they will. But Payments will also change the way that Biometrics are leveraged for security.
Technology has widened the chasm between small businesses and behemoth competitors like Amazon and Alibaba. This becomes most clear in the payments space, where smaller merchants struggle to process the volume and speed of transactions with the technological innovation that larger firms can afford. Small Business Trends took a look at the role biometrics plays in payments, and had an interesting takeaway:
Biometrics is not a Binary
Well, shouldn't be a binary anyway. Biometric identifiers don't get scored as "Correct" or "Incorrect" like knowledge-based identifiers do (Either "Appetite for Destruction" is your favorite album or it isn't!). Instead, authentication solutions look for the probability of a match based on a number of traits or signifiers - once that probability crosses a certain threshold, it's deemed a "match."
The most effective biometric systems increase the probability that a biometric identifier is deemed a match by marrying that fingerprint or iris or what-have-you to other data signals. As the article points out, fingerprint biometrics can have their efficacy increased when paired with data signals like geolocation or Device ID. Similarly, Jack Ma made Alipay more secure by marrying the "Selfiepay" concept with smiling or nodding as a movement captcha.
But what about Voice Biometrics?
Voice biometrics are an effective solution for authenticating callers and detecting fraud. Without additional data points, however, Voice Biometrics fails to meet its full potential.
Here's what Voice Bio can leverage to get even smarter:
Dynamic Blacklists - If a call is coming from a known fraudulent number, a suspicious international number range, or a compromised account- why treat it as a basic customer call? Leverage this information, much of which can be accessed via API in near-real-time, to flag calls before they even reach you Biometric Authentication.
Spoof - According to Next Caller's research, 94% of all fraudulent attacks on the call center leverage ANI spoofing as one of the methods to gain access. Smart call centers use information about whether a call is spoofed to "green light" a call for an agent or flag that call for further scrutiny.
Geolocation - Where should your caller be? If they're somewhere else - that's a solid indicator to at least take a second look at a call.
Again, all of the above information is available in near-real-time, much faster than a Voice Biometric Authenticator can perform an analysis.
The next major wave of Biometric Security won't be the implementation of the solutions, but the marrying of data that makes those solutions smarter.
Tim Prugar is the Director of Customer Success at Next Caller. He can be reached at email@example.com