{"id":3327,"date":"2026-05-20T12:33:00","date_gmt":"2026-05-20T12:33:00","guid":{"rendered":"https:\/\/blog.bioaffix.com\/?p=3327"},"modified":"2026-05-21T08:34:53","modified_gmt":"2026-05-21T08:34:53","slug":"use-of-artificial-intelligence-in-biometric-systems","status":"publish","type":"post","link":"https:\/\/blog.bioaffix.com\/en\/biometric-technologies\/use-of-artificial-intelligence-in-biometric-systems\/","title":{"rendered":"Use of Artificial Intelligence in Biometric Systems"},"content":{"rendered":"\n

What Is Biometric Identity Verification?<\/h2>\n\n\n\n

Biometric data is among the most sensitive types of data used to verify a person\u2019s identity. Information such as fingerprints, facial structure, iris patterns, or voice characteristics represents unique and unchangeable features of an individual. Common biometric verification methods include fingerprint recognition, facial recognition, retinal scanning, and voice recognition. Biometric verification systems are generally considered more secure than traditional passwords or PIN codes. However, these systems also have certain vulnerabilities. For example, some fingerprint-based systems may be deceived using a fingerprint mold or image. Ones Technology has taken a significant step toward addressing this issue by using sensors that also monitor the device\u2019s power status. Companies may use facial recognition to uniquely identify users who create a new account on an online platform, or to verify the real identity of an account holder when risky or suspicious account activity is detected. One way to strengthen this process is through two-factor authentication. Two-factor authentication, or 2FA, is an authentication method that may include biometric factor checks. In this approach, a biometric factor is used together with a possession factor. For example, a user first enters a password and then verifies their identity by touching a fingerprint scanner. Since two different factors must be validated, this method provides a higher level of security.<\/p>\n\n\n\n

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When these systems are integrated with artificial intelligence technologies, the security layer expands significantly. However, this also introduces new risks. Since 2008, Ones Technology has been developing biometric identity verification solutions. Initially launched to help prevent unauthorized insurance usage in the Turkish Social Security Institution, the Biometric Identity Verification-Based Access Control System represents one of the first integrated biometric identity verification and access control system infrastructures developed in T\u00fcrkiye, including both software and hardware.<\/p>\n\n\n\n

Where Are Biometric Systems Evolving?<\/h2>\n\n\n\n

Biometric systems are no longer used only for identity verification. Today, they play an active role in many areas of life, from security and healthcare to finance and education. Different biometric data types such as fingerprints, facial recognition, vein patterns, iris recognition, and even gait recognition become more accurate, agile, and flexible when combined with artificial intelligence. Traditional biometric systems are mostly based on fixed algorithms. For example, in a fingerprint system, the finger may need to be placed at a specific angle. However, the real world does not always work that way. Fingers may be wet, a person may be wearing a mask, or lighting conditions may be poor. In some professions, fingerprints may even be temporarily or permanently deformed. In such cases, artificial intelligence can provide a way forward by increasing the system\u2019s ability to learn, adapt, and tolerate errors. Compared to traditional methods such as passwords or PIN codes, biometrics can offer a much stronger identity verification model. Through common methods such as fingerprint recognition, facial recognition, retinal scanning, and voice recognition, users can be verified not only by \u201cwhat they know,\u201d but by \u201cwho they are.\u201d<\/p>\n\n\n\n

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At this point, Ones Technology’s access control philosophy becomes highly relevant: \u201cPeople have cards; cards do not have people.\u201d In other words, whether a person is verified by card, biometric data, or password, the system recognizes the individual as the primary identity. Even in cases where a security vulnerability occurs, or where a person must be blocked from the system, or where verification methods must be temporarily or permanently changed, the verification process can continue seamlessly because the user remains the central reference point. The integration of artificial intelligence into these areas can help verification processes adapt to changing conditions over time and potentially deliver identity verification with error rates approaching zero.<\/p>\n\n\n\n

Every System Has a Vulnerability<\/h2>\n\n\n\n

The widespread use of AI-based biometric systems naturally raises certain questions. As the title suggests, every system has advantages and disadvantages, benefits and risks, strengths and limitations. One of the most significant vulnerabilities in AI-based verification systems may be long-term information manipulation.<\/p>\n\n\n\n

So, what does this mean exactly?<\/h2>\n\n\n\n

Let us imagine that a user\u2019s biometric characteristics physically change over time. For example, their skin tone may become noticeably lighter or darker, a temporary infection may cause swelling or bruising on the face, or a fingerprint may be affected by cuts, burns, or other temporary deformities. To tolerate such changes, artificial intelligence may try to update the acceptance threshold during each new verification attempt. However, over time, this process may cause the biometric data to drift away from its original reference state. This drift can reduce verification accuracy or even lead to false matches. Therefore, biometric data may need to be updated at certain intervals, which creates additional technical workload and cost.<\/p>\n\n\n\n

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AI algorithms may also produce inaccurate results when trained on insufficient or unbalanced datasets. For instance, if an AI system is trained mainly on datasets based on T\u00fcrkiye or Europe, it may perform poorly in other regions of the world where there are significant differences in skin tone or facial characteristics. This may result in false matches or failed verifications.<\/p>\n\n\n\n

In addition, as AI improves biometric verification capabilities, some projects may evolve into live tracking systems. This can create ethically controversial issues such as privacy violations or unauthorized monitoring. In regions where such systems are deployed, this may lead to self-censorship, a culture of fear, and targeted discrimination, such as the special monitoring and tracking of selected individuals. Therefore, the level of AI usage must be carefully determined. AI should be used to improve the system, not to create new ethical or social risks. Otherwise, it may contribute to a concept that can be described as digital enslavement.<\/p>\n\n\n\n

As a result, biometric verification systems do become more secure and intelligent when combined with artificial intelligence. However, while using these systems, it is necessary to pay attention not only to technology, but also to ethical principles and user rights. Within Ones Technology\u2019s NG, or Next Generation, vision, the goal is to establish this balance and use AI at the most optimal level without compromising the stability and certainty of the existing system, and without creating additional cost or security vulnerabilities.<\/p>\n\n\n\n

Customer Service and Continuous Support<\/h2>\n\n\n\n

Artificial intelligence can be used not only in biometric verification systems, but also in another critical area: customer support and after-sales processes. As is well known, customer service is one of the most important elements for all companies, from SMEs to large enterprise groups. Customer diversity, multinational customer profiles, and localization efforts play a critical role in acquiring new potential customers and retaining existing ones. After all, every company is only as valuable as the quality of the service it provides. AI-powered chatbots can play a vital role at this point. Imagine employing as many shift-based and multilingual support agents as possible. It would still be extremely difficult to respond instantly at the start of every conversation, understand the customer\u2019s product, adapt to the customer\u2019s native language and cultural background, and provide fast and accurate answers to even the simplest or most complex questions with the same speed and consistency as an AI system that already knows the entire infrastructure.<\/p>\n\n\n\n

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Sources<\/h1>\n\n\n\n
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  1. https:\/\/www.microsoft.com\/en-ie\/security\/business\/security-101\/what-is-two-factor-authentication-2fa<\/a><\/li>\n\n\n\n
  2. https:\/\/tr.wikipedia.org\/wiki\/BioAffix<\/a><\/li>\n\n\n\n
  3. https:\/\/arxiv.org\/abs\/1503.03832<\/a><\/li>\n\n\n\n
  4. https:\/\/www.nice.com\/glossary\/what-is-ai-customer-service<\/a><\/li>\n\n\n\n
  5. https:\/\/www.gartner.com\/en\/newsroom\/press-releases\/2024-04-11-gartner-says-75-percent-of-enterprise-software-engineers-will-use-ai-code-assistants-by-2028<\/a><\/li>\n<\/ol>\n\n\n\n
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