Machine Learning Facial Recognition: Expediency of KYC in the Insurance Industry

KYC is a swiftly growing expansive procedure with diverse applications in various industries. KYC procedures include a range of verification tools through which industries verify their clients and abstain from dubious activities. Face recognition is a vital component of the verification process and is extending its range promptly. 

From unlocking mobile phones and protecting social media accounts to surveillance and security, face recognition is revolutionizing the insurance industry with automation advancements. However, it is a simple method that uses the distinctive features of an individual’s face to verify their identities. Machine learning facial recognition operates by comparing and identifying the input with the existing database. 

Let’s delve into the article and learn more about machine learning and AI’s evolving technology.

Salient Features of the Article

  • Understand what a facial recognition scanner is
  • Comprehend the functioning of biometric face recognition 
  • The role of AI face recognition in the insurance industry 
  • How face recognition solutions are optimizing the efficiency of the insurance industry 
  • How face recognition services use machine learning

What is a Facial Recognition Scanner?

As technology evolves, the demand for verification also increases. The primary feature of technology was to make human tasks efficient, accurate, and fast, and it is still doing that. A face recognition scanner is a great innovation when it comes to verifying identity through a camera lens. The scanner works the same as the human eye. It captures the features of the face, sends them to the backend, and identifies them. The scanner needs the information in the system to compare the output with the available dataset. 

How does the Biometric Face Recognition Model Work?

Biometrics is defined as the biological dimensions and physical features of humans. These distinctive features differentiate them from one another. Biometrics include face mapping, eye retina, fingerprints, and others. The biometric face recognition model works simply by detecting the face from the picture or video, and the scanners read the facial features, including the eyes, eyebrows, forehead, ears, lips, and skin color. They also read the distance between the facial features, such as the nose bridge and forehead, and other things like the contour of the faces. Then, the biometric face recognition sends these notions to the system that formulates algorithms by converting the analog image into digital code and identifying the face. 

The Use of Machine Learning by Face Recognition Services 

Facial recognition technology was developed with the assistance of deep learning, which is part of machine learning technology. It involves training artificial intelligence and neural networks to recognize data. The deep learning model is trained by inserting a large dataset of images of faces. The model then learns to differentiate between these faces by recognizing and identifying the patterns based on these differences after getting trained by the immense dataset. 

Convolutional neural networks (CNNs) are one of the most used algorithms for face recognition. Face recognition services, on the other hand, develop this technical service and provide it to the user conveniently. These face recognition services use deep learning to modify the technology according to the user’s needs.

AI Face Recognition In the KYC Insurance Industry

The insurance industry is part of the financial sector and involves exchanging money from business to business and business to consumer. It has traditionally been considered a relatively enduring component of the economic system. Nevertheless, over $308.6 billion in insurance fraud costs America alone each year.

Therefore, high-risk components need insurance to secure their financial health from tribulations. Insurance covers most benefits, from health to accidents and job security, so some countries only proceed with insurance. However, where insurance compensates most of the requirements, it encounters fraudsters who use these services erroneously and demand the benefits. 

Hence, insurance industries opt for KYC regulations to prevent these casualties from financial loss. And here comes the use of AI face recognition. The facial recognition technology verifies the users and indicates early if it detects any distrustful faces with criminal records. 

Powerful Face Recognition Solution Optimized Insurance Industry

The robust face recognition solution allows insurance companies to accommodate their clients securely by providing enhanced security. Insurance companies use face recognition in their login systems to identify their clients. Furthermore, the companies also use facial recognition solutions to verify the identity of the person claiming and benefiting from the insurance. There are several other advantages of facial recognition solutions have been provided for the insurance companies, such as: 

  • Secure the identities of the users
  • Authenticate and verify the users
  • Prevents financial loss by determining the false claims
  • Detects the suspicious activities

Final words

Machine learning facial recognition has optimized the services of the insurance industry. This advancement in technology has transformed the dynamics of verifying the identities of the users. The critical feature of facial recognition is reducing the rate of fraud.  The revolutionized technology has optimized the efficiency of the insurance industry and saved it from fraudulent activities. In countries where insurance is necessary, people disguise their identities and claim insurance on behalf of the insured.

About Safikul Islam

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