Obliterating Deception With Digital Identity Verification

Digital Identity Verification
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Digital identity should be unique to individuals in a technological environment. People should establish their existence and describe their characteristics through it. Verifying a person’s name, identity, and presence has long been a prerequisite in complex human societies.

Today, various identity verification methods are used to authenticate and prove identification. They help blur the borders between identity as a tool for verification and as a means to scam people. They help guarantee that the person confirming their identity is genuine and not a fraud.

What Is the problem?

Many businesses continue to rely on physical identity verification. For example, face-to-face identity verification is still required when opening a bank account, applying for a mortgage, a loan, etc. Such operations limit access and do not scale in today’s online world.

Traditional identity verification methods used in the past are no longer appropriate. The global digital revolution demands robust identity verification solutions.

In the pre-technology era, verifying the authenticity of individuals was a challenging milestone. But, it became the bare minimum necessity with digitalization that eliminated location barriers. Even so, the need for identification security prevails in offline operations as well.

Every industry is transitioning to digital models nowadays. Companies exploit digital infrastructure to connect customers with what they want and need right now, ranging from banking, shopping, travel, and so on.

The problem is, the fraudsters are still using flaws in identity verification solutions due to the shift to digital. Businesses are grappling with the issue of online identity verification.

What Is the solution?

The world faces an utmost necessity for a consolidated security system. It should be capable of detecting and decrypting deception in a matter of a few seconds.

The ambition is to eradicate human dependence and security protocols based on mere guesses and assumptions. The solutions should adopt resilient, customizable, and nearly invisible identification moments through SAAS models. It should be like the technology stack we found at AU10TIX.

AU10TIX’s stack comprises ten layers of omnichannel authentication. Each stack helps tackle a unique approach to identity fraud. With such robust technology, the solution can detect identity thefts within a few seconds.

The new-age solutions to an unbreachable identification system comprise services revolving around privacy and security interwoven with designed solutions.

Identification Document Verification

Unifying the identification credibility to centralized documentation with an electronic database is an excellent incline towards digitized security which now aids each industry for authentication of individuals.

Extracting, screening, and validating Identification documents automatically in any customer-facing workflow or identity management situation with Artificial Intelligence (AI)-led mechanisms for a convenient interaction throughout.

Biometric Authentication

An individual’s most unique and distinctive features are the natural elements of their physical attributes. Duplicating such specific features is arduous, making it essential to add one of a person’s most distinguishing characteristics. You can use the user’s physical attributes by capturing biometrics like fingerprints and iris scans, and match them to your verification flow to boost customer trust and eliminate forgery.

Electronic Data Verification

Every business collects data from customers while registering for the KYC process. How would a company know that the data is correct by all means? Hence, an identity detection solution should have near-instant data access detection capabilities.

The solution can ask the users to fill in the details and scan through millions of sources to verify the data with such abilities. For instance, it should do adverse media and finance probity screening.

Machine Learning Automation

The Machine Learning (ML) algorithms can aid in the tracking of fraudulent transactions, reducing fraud risks, and improving operational efficiency. These algorithms can learn from historical data to improve efficiency with time.

Hence, with the help of ML algorithms, security teams can automate synthetic identity and content detection. For instance, if the ML algorithms find any inconsistencies in documents, the systems will auto-detect them and alert the teams to take necessary actions.

Dynamic keystrokes

The typing pattern of each individual varies, just as it does with writing. AI can recognize a person’s typing pattern and verify their identification. Dwell time, speed, and combat time are all factors.

Dwell time refers to how long a user spends pressing a key, whereas fight time refers to how long it takes the user to release a key and press another. This system can also recognize a person based on their most frequently used keys.

Final Thoughts

It’s essential to establish the processes needed to maintain data accuracy and improve identity identification models with the information available. One of the secrets to selecting the ideal blend of security, speed, and convenience for your business is to do so, especially in a world where the introduction of metaverse has already begun the digital revolution.

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