How AI Identity Verification Works: A Comprehensive Overview

How AI Identity Verification Works

Artificial intelligence continues to revolutionize our everyday lives. And nowhere is that evident more than in identity verification.

Until now, manual ID verification – e.g. checking ID cards and manual document scanning – was the preferred choice for many companies. Knowledge-based authentication, performed by users, was another popular choice.

However, the security of these systems isn’t 100% secure, and they leave open the door for identity theft, with fake IDs, phishing scams to steal knowledge-based data, and other types of identity fraud risks.

Enter AI verification.

AI identity verification solutions are continuously being implemented to improve security measures, streamline processes, and mitigate fraud. Interested in how AI ID verification works? We’ll touch on that, as well as types of AI verification technologies that are now being used.

How Is AI Used in Identity Verification?

How Is AI Used in Identity Verification?

AI identity verification uses data to make decisions about the authenticity of an ID document. Essentially, AI technology relies on machine learning and algorithms to perform a variety of tasks, from estimating the next word in a sentence (like ChatGPT), to performing sophisticated ID verification.

In identity verification, AI systems decide if the person performing a transaction is who they claim to be. These systems, therefore, cross-reference ID data, like a driver’s license number, with governmental databases and user-provided data like a selfie photo.

Additionally, AI systems like OCR (optical character recognition) recognize and parse text data from ID documents, which allows the system to then process and verify this data against a database. Other types of AI methods used in verification include:

  • Facial recognition to verify IDs
  • Voice recognition
  • Behavioral biometrics that analyze user behavior
  • Anomaly detection for identity potential fraud
  • Natural processing language models to analyze and authenticate text data
  • Risk scoring systems to generate comprehensive risk scores

A key thing to remember: AI-based verification systems are always learning. They get smarter with the more data they collect and analyze. Therefore, over time, these systems increase their precision in ID verification, and often, they outperform humans with lower error rates.

What Is AI Identity Verification?

AI ID verification is a digital system that authenticates and verifies ID cards and identity documents in real-time. These systems typically require users to:

  • Scan their ID card or driver’s license
  • Data is parsed from the card with AI-based OCR
  • A user-provides data to cross-reference the scanned data (e.g. a selfie)
  • AI-based liveness detection determines if the user is present in the selfie
  • Using facial recognition, this selfie is then cross-referenced with the scanned ID document

Ultimately, based on the cross-check, an AI system will decide to verify or reject an ID.

What Is AI ID Verification?

The Benefits of AI Identity Verification

AI verification systems offer several advantages, from improving customer experiences (e.g. faster checkouts and onboarding), to reducing human error risk. Some of the key benefits include:

  1. Accuracy of Data – During onboarding, new customers must provide an assortment of documents as part of KYC compliance checks, such as passports with MRZ codes, government IDs, and proofs of residency. Humans must review these documents, a process which uses a lot of resources and could result in mistakes.By automating the verification process, technology can upload and review documents in a matter of seconds. This not only makes errors less likely, but it also makes it possible to onboard customers much more quickly.
  2. Convenience – ID verification and KYC compliance procedures demand time, effort, and resources. Throughout this procedure, numerous customers can lose interest or grow irritated. By developing a seamless workflow that moves users from one stage to the next in a matter of seconds without sacrificing the necessary due diligence procedures, AI will accelerate and simplify the onboarding process for consumers.
  3. Risk Profile – Many businesses use a risk-based strategy for onboarding. Following onboarding, customers’ behaviors and risk status are assessed to see if they pose a risk for fraud, money laundering, or other criminal activities. Throughout the lifetime of the customer, this risk profile is periodically evaluated. Because of its complexity, it cannot be completed manually.However, AI has the capacity to handle massive amounts of unstructured data over time and may swiftly identify anomalies that raise red flags. For this very reason, AI technology is frequently used for PEP and sanctions screening. To manually access and evaluate the data in sanctions or PEP lists, or in government and business registries, would take a lot of time and effort.By using technology to carry out these searches and gather the required data, compliance terms will be freed from the stress of studying these lists while still completely complying with compliance regulations.
  4. Saving Money – The cost of manually doing ID verification checks is very high. To examine and review documents, several staff members must be hired, and delays could even cause customers to give up midway through.Additionally, if mistakes are made with that personal information, the company is vulnerable to regulatory penalties or reputational harm. AI lessens the demand for those resources and the wages necessary to keep them employed for identity verification.
  5. Verification Done in Real-Time – Platforms for AI identity verification provide real-time authentication, enabling businesses and organizations to instantly verify identities. This is especially useful in sectors like financial services and customer onboarding procedures where time-sensitive transactions are involved.
  6. User-Friendly Experience – It might be inconvenient and time-consuming to submit physical documents when using traditional identity verification procedures. AI-driven solutions enable people to digitally authenticate their identities using their smartphones or cameras, providing a seamless and user-friendly experience. By doing so, the requirement for physical document submission is removed, the verification process is sped up, and customer satisfaction is increased.

How Are AI Identity Verification Models Trained?

Any machine learning algorithm, such as recommenders or facial recognition, needs clean data to be designed, tested, modeled, and put into practice. Next, essential threshold parameters must be defined at the outset by a data professional who is familiar with the sector and understands what is required for approval.

Training is necessary for machine learning models to improve their capacity for making decisions. Automated authentication tests may occasionally be unsuccessful for several reasons, such as poor lighting or wear and tear on ID documents.

In order to overcome those concerns, human ID validation experts will be needed, especially in the early training stages. Manual checking will also be necessary. This will fix the system’s main issues as well as identify any new ones.

Biometrics and AI Identity Verification

Biometrics and AI Identity Verification

To comply with KYC and KYB regulations, biometric ID verification is used. With the help of distinctive biological characteristics like fingerprints, voices, retinas, and facial features, biometric authentication is a cybersecurity procedure that confirms a user’s identity. It can also be used to authenticate an employee’s identity at work.

The use of passwords, PIN codes, and other antiquated forms of authentication has long since been replaced by biometric authentication. Biometrics can develop data-driven security protocols with the use of AI. The biometric verification procedure has been enhanced by AI.

AI and biometric authentication work together to create a verification solution that fraudsters cannot manipulate. AI can be used with a biometrics identity verification system like:

  • Facial Recognition: An image or video of the owner can be used to easily mislead facial recognition systems. Technology for 3D biometric facial recognition is used in AI. AI can recognize a person’s face and can learn from a variety of images. A person employing a face mask, a photocopy of a photo, a photocopy of the screen, or a manipulated paper containing a phony photo can all be identified by AI. This is why AI and biometrics together provide the ideal biometric authentication solution.
  • Voice Recognition: Numerous applications, including ordering, answering, playing music, home automation systems, smartphones, etc., use voice recognition. These systems can struggle to understand the voice due to noise. In these biometric systems, voices can be recognized using AI. It is also possible to evaluate various vocal patterns, including accent, tone, and speed. A person’s voice can be evaluated by AI for biometric verification.
  • Keystroke Dynamics: A person’s typing pattern can be used by AI to identify them and confirm their identity. It makes use of fight time, dwell time, and speed. The amount of time spent pressing a key is known as dwell time, while the amount of time spent releasing a key and pressing another key is known as fight time. The commonly used keys of a person can also be used by this system to identify them.

Wrapping Up

Artificial intelligence has the capacity to streamline the verification process from start to finish by expediting, simplifying, and enhancing its accuracy. However, to achieve the desired results, the algorithm must be adequately trained with real-world experience.

If you are seeking a business that possesses the essential expertise, technology, and breadth of knowledge required for your business, we invite you to schedule a consultation and demo with FTx Identity today.

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  • AI identity verification
  • Biometric authentication
  • Facial Recognition