Technology based on behavioral traits and biological characteristics is making digital user authentication processes faster and more secure
Codes and passwords have long been the most common forms of authentication in the banking industry, but increasingly they are recognized as less than secure, and their reliability is in question.
Many consumers in the USA – 61% – reuse passwords for different accounts, for example, according to a Visa study. Additionally, more than 80% of those surveyed said they were interested in using biometrics to verify identity and make payments, while 70% said this method would be easier to use than passwords.
In fact, the payment processor itself foresees that passwords are on their way out, since they generate friction in transaction processes, and are easily forgotten. And forgetting is just one of the problems.
Typically, users use weak and repetitive passwords or pins. That is, they use the same password for different applications, banking or otherwise. Considering this, hackers look for username-password pairs from one site, and then try to reuse them on more lucrative ones.
Even strong passwords that incorporate letters, numbers and symbols should be abandoned because frequently users repeat the same code for multiple logins, according to the U.S. Department of Commerce's National Institute of Standards and Technology (NIST)
Based on this, financial institutions are turning to biometrics and machine learning as a safer, simpler and faster authentication method for their users.
Unlike other security systems, biometric authentication can be used with a range of factors or identifiers, such as physiological and behavioral characteristics.
Biological biometrics include physical characteristics of an individual such as fingerprints, hand shape, vein pattern, and eyes, among others. These offers many advantages, both for users and for the adopting institution.
For clients, biological biometrics are a highly secure mechanism as they are unique to each person. Additionally, they are easy: customers do not need to remember any passwords (or run the risk of forgetting them), and they make it very convenient to complete a transaction in just seconds.
As for the advantages for a financial institution, biometric authentication is a technology that minimizes friction in transaction processes (logging in, making payments and transfers, etc.), and does not require extra systems or terminals that can make the tool more expensive.
With the advances in technology, it is now possible to apply biometrics in conjunction with Artificial Intelligence (AI) to enhance the security of a system. In fact, the introduction of AI marks a turning point in the use of new authentication methods.
Basic facial biometrics use reference points on a geometrically represented face to approve or deny authentication requests. With the addition of AI, modern verification systems not only store the information, but also learn from and enhance physical or behavioral data and patterns.
This not only improves automatic identification, but also provides a more comprehensive level of security.
Combined with facial biometrics, AI can create more accurate authentication models with the help of millions of pieces of facial data. In addition, as biological traits - especially those related to the face - change, AI can also use predictive models to anticipate the effects of aging, keeping up with the passage of time.
When it comes to security, biometrics in conjunction with AI provide a more reliable digital shield by working with irreplaceable and unrepeated digital data: physical and behavioral identities that cannot be hacked or stolen.
With these technologies, we can forget our passwords forever.
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