Technological advancements have improved security measures in various sectors, allowing growth in terms of customer support and data security. Although the digital sphere seems quite safe, the instances of identity theft and other related scams indicate a different situation.
Identity frauds are often part of the news for being the source of problems for businesses operating through digital spaces. To counter this, face recognition technology has fast become the definitive security solution. From unlocking smartphones to the security checks in business transactions and office entrances, face verification is the most preferred security measure.
Biometrics is clearly the popular choice for security, as research indicates over 80% of people choose it in place of passwords for securing their payments and transactions. Face recognition technology makes use of AI to detect and verify unique facial characteristics to identify a person. This type of verification boasts security because faces cannot be hacked, at least not as easily as passwords.
Face verification solutions are created using a number of AI technologies and machine learning models that make it capable of detecting and matching the different parts of an individual’s face. Fraudsters that attempt to fake their identity while interacting with business representatives through online platforms often use fake IDs and even use software like deep fake and photoshop. This is done by fraudsters to fool the person interacting through video conference and pretend to be someone else in order to manipulate systems.
The common motive behind stealing identities is to benefit from another person’s position or gain money illegally. However, the ways of committing identity fraud have changed over the past few decades. This being the reason because the advancements in technology have not only benefited industries throughout the world but also empowered criminals with sophisticated tools to overcome security barriers.
Faking identity involves criminals creating their own identity documents that are used to surpass manual verification procedures in order to gain unauthorized access. Once a fraudster enters an organization’s system, they cause harm to the company in various ways and also launder money.
There are also those instances where fraudsters steal some of the personally identifiable information from others in order to stay undetected when they commit crimes. Synthetic identity is the name given to this hybrid of stolen and fake information. Banks, insurance companies, and investment firms usually become victims of fraud where synthetic identities are used by fraudsters to fool the verification agents.
Financial institutions often become victims of these identity frauds and face losses due to money laundering and compliance penalties. This is the reason why due diligence processes have become a must in financial institutions, where customers are screened to check their background transactions.
Nowadays, digital onboarding of clients in businesses has become the norm, where there is a certain amount of vulnerability due to the lack of identity verification measures. Here, face recognition technology provides foolproof security as the service can simply be integrated within the platform through which online customer onboarding is carried out.
To reduce crimes originating from stolen identities, online Face Verification is implemented by organizations handling sensitive information. This is because customers lose trust in the companies that fail to provide them with the basic level of security. Several enhancements in biometric technology and the use of AI to extensively analyze data have accounted for an extremely accurate face verification solution.
Once the service is implemented by installing particular APIs, the identification of potential customers begins with matching their face with their ID card photo. Without facial verification, fake identity documents and deep fakes would be undetected and fraudsters would easily access business systems. Using AI-based biometric face recognition technology, these attempts are caught with even the slightest doubts in originality.
Liveness detection is one of the integrated technologies in the face verification solution, which determines whether an actual person is appearing in front of the camera or a photoshopped image is being presented. It detects gestures like blinking, smiling, and other movements in the face to verify the individual’s identity.
In addition to liveness detection, 3D depth analysis is also used as part of a face verification solution to identify individuals through online platforms. The distance between different facial features and the depth at different areas is analyzed by AI-driven technology. Face recognition technology leaves little to chance while verifying identities and determines the slightest fake characteristics.
To sum it up, facial recognition technology is a much-needed technological solution to automate the identity verification process in businesses and financial institutions. This solution not only provides the necessary protection from identity fraud but also provides convenience to customers while getting access to online business platforms.