Biometric Authentication: The New Trend in Mobile Security

Melissa López
April 16, 2021

Biometric authentication is a technology that identifies the physical and unique characteristics of an individual, at the FinTech level this has allowed the automation of financial processes in a more secure way.

Likewise, biometric security works as part of a multi-factor approach through a mobile device for unlocking, rather than password, login and even purchases.

Facial recognition allows verifying that the user is the one authorized to log in , preventing unauthorized access in case of loss or theft of the device.

By including biometric authentication capability in your applications, rather than relying on a specific device feature, it allows application vendors to differentiate and customize the security features and performance of their applications.

In the case of Antit, our applications use biometric security to automate processes and provide greater security to our users based on the latest technology for this.

Likewise, when we combine facial recognition with voice biometrics we achieve greater precision and performance, making the counterfeiting attempt even more difficult.

By implementing this security, FinTechs reduce identity substitution, fraud and average transaction duration, systematization, and improve the customer experience.

Among its benefits is greater comfort and security because biological measurements are much more complicated to 'hack' than alphanumeric combinations.

Within the biometric verification we can mention some types that have stood out above the rest such as:

Biometric behavioral identifiers : this allows you to identify behavior patterns of your customers during banking activity, such as hand and eye coordination, pulse, precision of movements, pressure on keys, among others that prevent it from being supplanted by a robot.

Iris recognition: in countries like Spain, the iris scanner of mobile devices is used so that users access their accounts in a simpler and more secure way.

Facial recognition: in this process small facial movements are detected, such as smiles, expressions, blinks in order to avoid that printed images are used to try to impersonate the identity.

In the case of facial recognition, it compares the source image with an image store looking for its match, making use of advanced algorithms to extract biometric data from a facial image, distilling characteristics such as the position and size of a person's eyes in relation to with the other in a standardized data set.

However, facial comparison makes use of the same technology but assumes that two images of the same person are being compared.

Face comparison is generally used when a trusted source image such as a user's identity document is available to compare an image in real time.

The system requests the taking of a photograph that compares with the document looking for matches.

FinTechs have made use of this technology to make it easier for financial institutions to verify the identity of a new user when they request to open an account and are not physically present.

The facial comparison technology compares the selfie image with the image of the verified identification document, to prove that the person is actually present during the account opening process.

Life Detection: The most common method of life detection is to ask the user to perform a series of head movements to test life and prevent spoofing.

More advanced techniques such as 3D recognition and thermal imaging require specialized hardware and are not suitable for everyday business applications.