Biometric consent verification is a modern approach to online fraud prevention. With the increasing number of identity thefts, data breaches, account takeover frauds, and financial crimes, there is a need for revision in identity verification methods.
The reason is that fraudsters are getting advanced and use the same innovative tricks against online security systems due to which they exploit the vulnerabilities and perform malicious activities.
Biometric Identification helps businesses stay one step ahead of fraudsters. It incorporates a detailed process of identity verification in which consent and biometric verification take place simultaneously. Hence with multiple verification approaches, an identity can be verified with a high accuracy rate.
Biometric consent identification corresponds to two identity verification methods that some industries adopt to conduct online KYC. Biometrics verification online includes face verification. In real-time, facial features are captured along with the consent paper.
Using underlying Artificial intelligent and Machine learning algorithms, the information is extracted and mapped in the machine. It is stored in a database and verified. Consent could be in the form of some hand-written note that the user needs to hold and capture the face, as well as consent, live in the form of a picture or a video.
A combination of verification helps in the better authenticity of an individual. A customized document and face recognition serves the purpose of the online security of businesses and websites. Traditional passwords are no more secure, and many online users do not meet the minimum requirements of having secure passwords strategies. Hence all this has been covered by biometric consent verification.
Consent verification is performed by capturing the document and extracting written information from it. In real-time, to extract the information, OCR technology is used. Optical Recognition Technology (OCR) identifies the pattern in which text is written. In the process of consent verification, the online website would suggest a sentence or content that an online user is supposed to write on a note and show it in a selfie along with the face.
API integrated with the system will use OCR technology to recognize the text. The information is extracted and verified against the content provided by websites. If both match, identity is verified.
For Face Recognition online, facial recognition technology is used whose underlying algorithms extract the facial features of an individual in real-time. These featured are captured and mapped into the database in the form of some mathematical formula.
Every time the user tries to verify the features are captured and matched with the data stored previously in the database. If both match, identity is verified. In this process, spoofing facial elements are also detected to make sure that the picture involves no photoshopped or forging factors.
A large number of online attacks take place as a result of unauthorized access to user accounts. Or another reason could be the tricks of fraudsters that steal the identity information through credentials stuffing or running malicious executables.
To prevent these frauds, dynamic security measures should be taken in place. Every time the online user tries to log in to the account, consent biometric verification should be performed in real-time to authenticate the user and provide services. In this way, several online frauds can be prevented.
To sum up, with the combination of two verification methods, biometric identification and consent verification, the purpose of online account security can be achieved. This deters the risks of fraudulent activities committed by fraudsters online.
Instead of traditional passwords and 2-factor authentication methods, biometric consent verification provides a modern way of identity verification to mitigate high-risk customers into legitimate online systems.
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