Here’s How AI Technology Has Enhanced Identity Verification

Artificial Intelligence (AI) refers to the capability of a smart machine to perform tasks that generally require human intelligence. These smart machines use algorithms and large amounts of data to learn to identify patterns in order to make predictions. AI technology not only drives down the time needed for completing tasks, but also facilitates decision-making and risk management by making the process smarter and faster.

AI can be found in various technologies today, ranging from autopilot mode in cars to facial recognition applications. One AI-powered technology this blog will be taking a closer look at is identity verification software, and how it assists in fraud prevention.

Artificial Intelligence and Identity Verification

With more and more data being stored online, identity theft has been on the rise. Particularly after the onset of the global pandemic, identity theft reports more than doubled in the U.S. compared to the previous year, with the amount reaching approximately USD 1.4 million in 2020.

AI technology uses ML (Machine Learning) and DL (Deep Learning) to automate the process of identity verification. For AI technology to work, historical data has to be provided to enable it to make human-like decisions that are then used for making predictions. This way, AI makes authentication and verification of individuals more credible and accurate.

Biometric Verification

Biometrics are being increasingly used for identity verification and access control for one basic reason — the data is difficult to forge. Biometric Verification relies on distinct biological features to verify individuals, while also staying in compliance with KYC and AML regulations. Unlike traditional methods of authentication that use PIN codes and passwords, biometric authentication makes use of physical traits, such as fingerprints and facial patterns, to verify identities. As biological characteristics cannot be faked, fraudsters within a business can be easily weeded out before they are able to infiltrate the system.

AI and Biometric Verification

AI combined with biometric technology makes a verification solution that is difficult to be manipulated by criminals. Listed below are some ways in which AI has enabled biometric verification for fraud prevention:

1.     Keystroke Dynamics

Keystroke dynamics is a form of biometric authentication in which users are verified through the analysis of their typing patterns. The process involves monitoring an individual’s typing speed, dwell time, flight time, use of space and capitalization of letters, frequently made mistakes, typing rhythms etc. AI-enabled keystroke recognition is a convenient biometric approach as it validates the legitimate identity of individuals in a cost-effective and transparent manner. With multimodal biometric systems gaining ground across an array of industries, the adoption of keystroke dynamics is also on the rise with the market forecasted to reach a value of USD 754.86 million by 2025.

2.     Facial Recognition

Biometric facial authentication uses an individual’s facial patterns as passwords instead of a typed-in passcode or a fingerprint. The tech giant Apple, for instance, switched from fingerprint scanning to “Face ID” as a form of user verification, that leverages AI-based face recognition technology to assist in lowering the chances of unauthorized users accessing a mobile device. Another way this form of biometric authentication helps in preventing fraud is by accurately detecting imposters using face masks, fake pictures or tampered documents with false pictures to disguise themselves as someone else.

3.     Voice Recognition

Voice recognition, alternatively known as speech recognition, helps identify legitimate individuals by analyzing speech patterns. A voice sample has to be captured and integrated into the biometric database to form a reference template that enables future comparison for identity authentication. Voice recognition technology is being used by numerous industries today, from e-commerce platforms and financial institutions to call center operations and educational institutions, due to its ability to accurately identify individuals during the natural course of a conversation.

Key Takeaways

• AI technology leverages machine learning and deep learning to automate the process of identity verification, making the results more credible and accurate
• AI combined with biometric technology makes a verification solution that is difficult for criminals to manipulate
• Examples of AI-enabled biometric authentication systems include keystroke dynamics, voice recognition and facial recognition