9 New AI-Based Identity Verification Methods for Better Security

identity verification methods

New technologies introduce new security risks for businesses.

However, new identity verification methods are constantly being developed. This allows businesses to respond to new issues – like deep fake identity fraud, for example – while improving their security processes.

Traditional methods of ID authentication are quickly becoming outdated. This includes ID verification methods like password authentication and manual ID checks. Not only are these processes inefficient, but they also leave the door open for human error.

AI-based and biometrics-enhanced ID verification platforms offer a solution. These tools use technologies like facial recognition and biometrics for an added layer of security. As a result, they better protect customer’s identities and keep businesses safe.

Interested in learning more about modern ID checking technologies? Here’s a look at how AI and biometrics are changing how businesses verify identification.

Existing vs. AI-Based Identity Verification Methods: Key Differences

Traditional forms of identity verification such as passwords and SMS-based two-factor authentication typically involve manual or semi-automated processes.

These include tools and technologies like:

  • Password Authentication: This is the most common form of identity verification. Users create a unique password that they must enter to access their accounts.
  • Two-Factor Authentication (2FA): This method adds an extra layer of security to the standard password method by requiring users to provide two forms of identification. The first factor is something the user knows (like a password), and the second factor is something the user has (like a mobile device to receive a one-time password) or something the user is (like a fingerprint or other biometric data).
  • Security Questions: This method involves users answering pre-set questions that only they should know the answers to.
  • Physical ID Verification: This involves checking a physical ID document like a passport or driver’s license. This could be done in person or by sending a scanned copy of the document.

Pitfalls of Traditional ID Verification Methods

Traditional identity verification methods are vulnerable to fraud, can be inconvenient which causes systems to fail to verify identity, and offer limited ID proofing.

They often rely on user memory, which can lead to account lockouts, and they don’t provide continuous authentication, leaving sessions open to hijacking.

Manual checks, on the other hand, are time-consuming, prone to human error, and difficult to scale. This requires a person to spot fake IDs, whereas scanning and AI can do this more thoroughly.

Storing sensitive information also presents data security risks. These shortcomings have spurred the development of advanced identity verification methods like biometrics and AI-based solutions. Ultimately, businesses are investing in other types of technologies, while relying on these existing, outdated ID verification methods.

This is leading to what some experts call “cyber debt.”

>> Learn More. See our guide What Is AI Identity Verification?

Modern Identity Verification Technology: AI and Biometrics

Age and identity verification technology is more advanced than ever. New technologies like facial recognition, biometrics, and OCR document scanning are enabling faster, more accurate and less biased verification checks.

The result is a better customer experience, helping businesses improve their processes and maximize compliance.

Some of the latest identity verification methods include:

  1. Facial Recognition: This technology uses AI and machine learning to compare digital images to stored faces in database. This is a core functionality of face ID verification. Facial recognition allows for a selfie to be compared to a scanned driver’s license photo.
  2. Biometric Verification: This requires a unique biological identifier to prove a customer or users’ identity. Common examples include fingerprint scans, iris scanning, and voice recognition.
  3. OCR Document Verification: OCR – or optical character recognition – uses AI and machine learning to read and verify documents. This technology also enables data extraction tools to capture ID information and build identity profiles. It can be used for passports, driver’s licenses and ID cards.
  4. Behavioral Biometrics: This technology uses algorithms to determine if a web user is a human. Examples would include analyzing keystroke dynamics or mouse movement patterns. Ultimately, this data can be cross-referenced against an existing user’s web use data.
  5. Liveness Detection: Another core feature of FTx Identity’s ID scans, this feature using facial recognition and biometrics to ensure that a person is physically present, and not a video, photo, or mask. Selfie checks with liveness detection ensure a user actually took a photo.
  6. Age Estimation Technology: This type of tool uses AI to estimate a person’s age based on facial features. This is often used in online platforms that have age restrictions, and may trigger an ID scan requirement.
  7. Blockchain Technology: Blockchain identity verification tools create decentralized and secure digital identity profiles. These profiles are tamper-proof and more secure.
  8. AI-based KYC Solutions: These solutions use AI to automate the KYC compliance process, which involves verifying the identity of clients and assessing potential risks of illegal intentions towards the business relationship.

Pitfalls of AI Identity Technology

These emerging identity verification methods are very new, and as a result, the security risks aren’t fully known. However, a few risks include customer privacy concerns, as well as misidentification and false positives.

Benefits of AI and Biometrics-based ID Verification

When compared to traditional ID verification methods like two-factor authentication, biometrics and AI-based solutions improve accuracy, reduce risk, and enable businesses to move faster without sacrificing security.

Some of the key benefits of modern ID verification methods include:

  • Enhanced Security: These methods provide a higher level of security than traditional methods, as they use unique biological characteristics or advanced AI algorithms that are difficult to fake or steal.
  • Convenience: Biometrics and AI-based methods can provide a seamless user experience. For example, facial recognition or fingerprint scanning can be quicker and easier than remembering and typing in a password.
  • Continuous Authentication: Some of these technologies can continuously monitor and authenticate users throughout a session, enhancing security.
  • Scalability: AI-based methods can handle large volumes of verifications quickly and accurately, making them scalable for large user bases.
  • Reduced Dependence on User Memory: Unlike passwords and security questions, biometric and AI-based methods don’t require users to remember specific information.
  • Fraud Prevention: Advanced technologies like liveness detection can help prevent fraud by ensuring that the person is physically present and not a photo, video, or mask.
  • Automation: AI-based methods can automate the verification process, reducing the need for manual checks and improving efficiency.


AI-based identity authentication methods are the modern answer to securing and protecting business systems from hackers and uninvited users.

With AI and cloud technology, businesses can react quickly to changes in security standards and meet their requirements for authentication in real time. This allows them to remain agile and confidently protect their data, financial assets, employees, and customers. Not to mention, AI improves the ROI of investing in an ID checking platform.

By leveraging robust identity verification solutions, companies can enjoy a higher level of control and take proactive steps to beat online fraudsters at their own game.

Want to learn more? See our guide to Authentication vs Verification for more advanced security processes.

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