How Biometrics has Transformed the Digital Identity Space

Biometrics technology is growing in popularity as a way of identifying individuals online. And the technology is changing rapidly. Methods being used today were unavailable a few short years ago. And the future will look different from today.

To appreciate what the future of online biometrics looks like, first understand how far we’ve come.

  • The first systematic use of biometrics for identification purposes dates back to 1858 when William Herschel used workers’ handprints on the backs of their contracts to distinguish workers from imposters when payday arrived. 
  • The year 1852 saw Francis Galton creating a classification system for fingerprints (known as the Galton Details) that is still in use today.
  • Ophthalmologist Frank Burch in 1936 proposed using the iris pattern for identification.
  • During the 1960s, Woodrow Bledsoe developed the first semi-automatic, face recognition system. 
  • 1960 saw Gunnar Fant create the first model that describes the biological components of speech, a concept crucial to speaker recognition.
  • In 1998, the FBI launched the Combined DNA Index System to digitally store, search, and retrieve DNA markers for forensic law enforcement purposes. 
  • And in 2013, Apple introduced the first fingerprint scanner in a consumer smartphone.

Today, biometrics is considered to be a quick and reliable way of identifying and authenticating individuals. Biometric methods of identification are divided into two broad categories: physiological and behavioral. Physiological methods include identifying unique characteristics of a person’s face, fingerprints, hand, iris, and DNA. Behavioral methods analyze such things as a person’s keyboard keystrokes, signature, and voice.

Risks of Verifying Identity Without Biometrics

Traditional means for identity verification are becoming obsolete as technology continues to evolve. This poses a major security risk for companies who haven’t migrated to a more advanced biometric technology solution. Why should you be concerned about outdated security software? As technology becomes more advanced and AI capabilities are becoming smarter, fraudsters are finding more and more new ways to hack internal systems and wreak havoc. Security hacks on internal systems that compromise the personal identification of your customers is detrimental to your business. Why take the risk by using an outdated solution for identification?

What is Digital Identity?

Biometrics are growing in popularity as a way of identifying individuals offline and online. Online, biometrics involves a person’s Digital Identity. Digital Identity is the online equivalent of physical ID documents, such as drivers’ licenses and passports. The goal of Digital Identity is to verify the identities of individuals online in a secure way that prevents spoofing and counterfeiting while safeguarding privacy and personal information.

The three most common biometric identification methods being used today to identify and verify individuals are facial recognition, voice recognition, and fingerprint scans.

The Future of Biometrics in the Online ID Verification Realm

Technology and processes change quickly in the area of biometric identification. In the area of online ID verification, you can anticipate seeing the following three trends develop in the coming months and years.

Trend 1: Customer and Employee Onboarding

When banks, credit unions, and other financial institutions open an account for an individual, they use a process called onboarding. Onboarding requires new customers to provide a set of documents to verify their identity and confirm their home address. This process is how financial institutions, retail stores, and other enterprises comply with regulations to prevent corruption, money laundering, and funding of illegal activities, such as terrorism.

Typically, the new customer onboarding process involves obtaining a copy of the applicant’s driver’s license, a utility bill or filed tax return as well as a selfie from the customer to perform the necessary identity verification checks. This information is then sent to back-office operations for verification. Today’s onboarding process is time-consuming and frustrating for many customers and makes the experience less than ideal for all concerned.

In the near future, much of this manual process will be replaced by biometrics. Biometrics transforms the virtual onboarding process for employees and customers alike. Customers require just a mobile device and an app to scan their biometric information to prove to the system that they are who they say they are. 

IDmission’s Artificial Intelligence Character Recognition platform, for example, uses a complex artificial intelligence engine to read an ID document and determine not only what it says, but what the field definitions/names are for a particular document type. It then compares the photo on the ID document with the selfie taken with the customer’s mobile device and sends the completed identity check data to the onboarding application.

With biometrics, organizations will easily capture the data required to complete a thorough identity check in one fluid process that eliminates today’s manual back-office processes. This will speed up onboarding while improving security.

Trend 2: Machine Learning and Recognizing Patterns

The future of biometrics in online ID verification involves machine learning and artificial intelligence. Future solutions will use machine learning and artificial intelligence to learn from data, identify patterns, and make decisions with minimal human intervention.

We are seeing this future taking shape today. Machine learning, for example, is being used to augment machine vision. Think of it as adding a brain to a camera. Organizations are taking images captured with machine vision and using machine learning to train the machine to recognize patterns in human faces.

Organizations are also using machine learning to detect patterns in large data sets. Machine learning algorithms convert data to information, convert information to knowledge, and finally convert knowledge to wisdom. Machines are being trained to detect patterns in data, helping businesses draw vital conclusions about customer behavior and intent.

There are three main benefits of combing machine learning with biometrics:

  1. Machine learning eliminates human error and the need for human intervention
  2. Machine learning expedites the identification and verification process, improving the customer experience
  3. Machine learning simplifies data sets, making biometrics systems smarter and more accurate

Trend 3: Multi-Factor Fraud Defense

Multi-factor authentication is quickly becoming the norm in the online space. The most common method is two-factor authentication, in which individuals confirm their identities using an additional method beyond their username and password. This second method is most commonly a security question or a code sent to their mobile phone by text.

The future of biometrics in online ID verification will involve machine learning platforms that examine multiple factors before authenticating an individual’s identity. One of these factors will be a biometric identifier. For example, organizations will scan the individual’s face or fingerprint using an app on the person’s mobile phone, plus require the individual to type their PIN into an app on their phone.

Adopting Biometric ID Technology in Your Business

Biometric technology is going to revolutionize the way individuals verify their identities online in the future. Juniper Research predicts that more than 18 billion transactions will involve biometric identity verification by 2021.

Biometric technology for online ID verification is exploding largely because of the increased security and speed offered by biometric authentication technologies.

Biometrics promises to simplify customer and employee onboarding, create robust and enjoyable digital experiences for customers, deter identity theft, eliminate impersonation, and deter fraud and theft.

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