Identity theft is no longer a big problem online; things have gone beyond this. There have been cases that depict fraudulent and dishonest insurance claims more often caused by identity theft and deepfake detection. Research conducted by the Coalition Against Insurance Fraud (CAIF) indicates that insurance fraud takes at least $308.6 billion annually from American consumers.
This massive number highlights the dire need for something that can immediately identify the insured person before their claims have been made to the insurance companies. Thus, biometric face recognition is crucial for identifying and verifying the person who is claiming the insurance. Cases have been seen that show people swapping their identities or stealing in order to get benefits from insurance companies.
This article will explore fraud prevention with face recognition technology and how it benefits insurance companies to deter identity theft optimally.
What is Face Recognition, and Why is it Important?
Face recognition is the wonder of the 20th and 21st centuries. It is optimal for identifying the human face and recognizing human features in a way that cannot be fooled. This technology has the ability to recognize the human face from a still image, video, or any source that depicts the facial characteristics of the individual.
Biometric face recognition is developed in Python using machine learning (ML), and with its subsequent that is deep learning. The AI-driven advanced technology also uses the CNN framework, which is also known as a conventional neural network. It is sufficient to extract human features and analyze hierarchies from images to verify facial characteristics.
How Does Biometric Face Recognition System Work?
Biometric face recognition system primarily works with a scanner to identify the insured person. The process can be performed at physical locations with scanners or digitally with the help of smartphone cameras. However, the process remains the same for programming and functionality. The face recognition scanner works in the following way:
- Image Capture: The process of biometric face recognition starts with capturing an image or video frame of the face using a camera lens or a scanner. This step can be achieved in real-time or can be obtained from stored digital images.
- Face Detection: Then, the system identifies the presence of a face in the image by locating the human facial features using advanced algorithms. It basically differentiates the face from the background and other objects to identify it.
- Face Alignment: Then, the located face is aligned to match the required biometric template format for the facial analysis. This involves adjusting the face’s orientation to a standard position and also the lighting.
- Feature Extraction: Further, the system extracts unique human facial characteristics to identify the insured.For example, the spacing of the eyes, the form of the jaw, lips, ears, forehead, and the outline of the face.
- Face Comparison: These extracted features are then corresponded against a stored facial feature database. Advanced algorithms and machine learning techniques are used to find a perfect match.
- Identification/Verification: Lastly, the system identifies the insured and the claimant by providing the final results based on the comparison.
Face Recognition Biometrics to Deter Fraudulent Insurance Claims
Fraudulent and dishonest insurance claims have been in practice for decades. Thus, there is a stringent need for biometric face recognition as it is optimal in deterring fraud. This technology can identify the insured and claimant and verify that they are the same person. Insurance providers must comply with KYC standards for individual registration.
Deterring fraudulent insurance activities is crucial in today’s digital space, as companies are losing millions to these scammers. Media highlighted that in the United Kingdom, a couple faked the death of their husband to get insurance money. Eventually, it came to light that the husband was actually alive and was benefiting from the insurance payout. Thus, biometric face recognition services are essential in finding the difference between a dead and alive person by verifying them with official databases.
Advantages of Face Detection in Insurance Industries
Biometric face recognition gives insurance companies several critical advantages in verifying the insured and the claimant. The benefits include:
- Enhanced Security: Biometric face recognition adds an extra layer of security by accurately verifying the identity of customers, reducing the chances of fraud.
- Faster Claims Processing: Automating identity verification speeds up the claims process, providing quicker service to clients.
- Fraud Detection: This technology helps prevent identity theft and fraudulent claims by cross-referencing real-time facial data with existing records.
- Convenience: Individuals with insurance can conveniently confirm their identity from a distance, removing the requirement for physical documents and face-to-face validation.
- Cost-Effective: Insurance firms cut down on operational expenses by minimizing the necessity for manual verification.
- Compliance: Facial recognition complies with regulatory standards, including KYC (Know Your Customer) and AML (Anti-Money Laundering) guidelines.
What Does The Future Hold For Biometric Face Recognition?
Biometric face recognition has already changed the insurance companies’ matrix. This technology has already made the verification process more accessible so that the insured can be registered and identified efficiently. As for the future, the technology will further embed with Artificial Intelligence and other advanced methods to identify people accurately. The accuracy of this technology right now is optimal, but it can be further improved in the future with more advancement.
