Nowadays, hacking and fraudulent activities are on the rise, and the need to avoid them and remain safe from those activities is essential to perform within organizations. With the increase in technology, different verification systems have been introduced to help identify an individual; one of the most unique and authentic factors is biometric face recognition.
A streamlined face recognition process can be regarded as using facial recognition software successfully during AML and KYC onboarding processes. To increase the strength of your biometric identity verification processing, you must remember to use identification verification platforms. Facial recognition kyc considered a double-edged sword as it not only helps identify an individual’s real identity but also lets us know that the person’s verification confirmations were submitted physically in the system.
Facial Recognition KYC has many advanced applications to implement within an organization that not only helps authentically an individual but is also cost-effective. Whether a company hires someone to do these facial recognition solution or buys software for conducting biometric verification, if a company does not have complete knowledge to perform facial recognition even after purchasing the software, then it will be a waste of time and cost for that company.
Choosing an appropriate system is compulsory and essential to perform the successful Facial recognition KYC. The software must be secure and safe enough that it can not only secure an individual’s information but also ensure that it cannot be hacked easily and cannot be utilized in any criminal or fraudulent activity in the future.
What is Biometric Facial Recognition
This is a technology that identifies an individual’s identity through its biological characteristics. Iris technology scanning always needs advanced systems to identify them, as this can be utilized in criminal investigations, including DNA scanners and fingerprint scanning using high-tech security systems. People’s facial features are scanned in this facial recognition kyc, which helps in understanding their identities biologically and ensures their authenticity as well.
An individual’s face is recognized by having them physically, by conducting a video call meeting, or by having their photo; these steps can be considered for the successful completion of the biometric verification process. A visual pattern recognition method scans the patterns through facial expressions to find a match with the authorized person in facial recognition KYC.
This technology works in three-dimensional ways as it reconstructs the image information with two-dimensional images to get the match of that specified person. Between the three and two-dimensional images, poses and expressions are observed using appropriate lighting during biometric facial recognition kyc.
There are five modules upon which this facial recognition kyc technology works: matching, extracting features, normalizing, detecting, and processing. Without the involvement of other physiological identification approaches, biometric facial recognition is considered authentic and reliable because it provides high accuracy in identifying accurate information about an individual. Facial recognition kyc technology shows accuracy and other solutions as they scan through a certain distance compared to Iris scans without imposing on a person’s body.
Working Criteria of the Biometric Verification Process
Pattern matching software is utilized in the complex biometric verification process. The human body has intricate biometric modalities, ingrained patterns in our features that are different for every individual, such as ear shapes, fingerprints, hand geometry, and so on. Facial recognition KYC, a sophisticated process, compares or matches these biometric modalities with their images or scans them physically within the system. The five steps, each requiring a high level of technical expertise, are mentioned below, which successfully complete the biometric verification process:
- Detection: It includes scanning the image by separating it from the background image and locating the exact features of the human face.
- Normalization: Facial canonical coordinates are aligned geometrically using an AI face recognition online tool that picks facial features and their positions from the eyes, ears, mouth, and outline of the face.
- Face Processing: This step is a compulsory in deep learning technologies called face recognition deep learning identification process but is usually not expected in the regular identification process. It relies on transforming two-dimensional images into three-dimensional images. This tool’s processing takes place and helps in dealing with lighting and posing.
- Extraction: This process, to find out the difference between facial features and images provided using facial recognition kyc, pulls out information from facial features. This process forms a vector representation through an image by using photometric and 32 geometric points; these features are modified in the extraction process.
- Comparison: This is the final stage as it finally matches patterns from the database’s data with an image of an individual and finds a match in both. AFR automated facial recognition software, a specific type of facial recognition software, is usually identified and utilized to complete facial recognition KYC.
Final Thought
Facial recognition KYC is the most reliable and trusted way, used in organizations to identify the true information of their employees. This verification also makes sure that the person is actually the one who they show. This process helps in saving the system of that organization from fraudulent activities and also making sure that the data remains safe of every individual in that organization.
