Artificial intelligence is being used by forward-thinking enterprises to overcome real-world digital identification concerns.
Users are essentially self-registered and in most cases, self-registration is a type of identity verification that captures the phone number and email address.
This is insufficient because it exposes only minute facts about the user. This is why it’s critical to move beyond self-registration and utilize automatic and intelligent identity proofing to identify people who require access to your system and network.
What is identity verification, then? It is the process of confirming a user’s identification. Don’t confuse this with standard verification, which relies on a username and password pairing.
The moment users protect their credentials to sign in to an app, as well as the standard authentication method, comes before identity.
The two terms offered by the National Institute of Standards and Technology (NIST) are sufficient to better describe identity proofing. According to the Digital Identity Framework of the National Institute of Standards and Technology (NIST),
Assumed identity: Information about a user’s defined identity when they register with an Identity and access management (IAM) system. To put it another way, they are whom they profess to be.
Real identity: Information that verifies the user’s identification. This is who they are at their core.
It is noteworthy to know that identity proofing, in particular, has one key goal. Its purpose is to guarantee that users’ stated identities match their actual identities.
This is why it acts as the first line of protection against identity perimeter infiltration.
Manual method of identification
This method of verification comes with its own setbacks:
Employees that aren’t well-informed pose a threat of compromise
There have been multiple instances of compliance personnel tasked with checking ID credentials getting their hands dirty in identity theft.
The manual method has flaws as customers will never trust your brand’s reputation if they find their personal information is being utilized for nefarious purposes.
Workforce costs are high
It will take too much money to establish a human team than it will automate. You’ll need to pay staff, buy computers, pay rent, and other expenditures for a human workforce.
Compensation for the compliance team, for example, can cost up to $45 per hour. For a 1000-person team, this equates to around $225,000 each year, let’s not even talk about renting a space.
All of these expenditures can be reduced by 70% if you use an automated process.
Processing at a slower pace
A manual procedure will take a long time to adequately enroll the compliance team.
You risk losing potential consumers who require your services right away or having your brand tarnished owing to inexperienced employees.
Manual Know Your Costumers (KYC) is still used by some financial firms, which can take lots of time. If your customers have to wait days for a response, they might as well go somewhere where the process is automated.
Errors made by humans
Humans become fatigued, and this exhaustion might result in mistakes. When implementing manual ID verification, is a significant challenge.
Machines, however, do not become weary, and they do not lose concentration. Not just that, but if a company lacks a qualified and effective compliance team, errors can occur.
Expanding is hard
When entering new markets, manual ID checks become harder to expand because you’ll need to hire a new crew that’s familiar with local rules.
Automated checks, on the other hand, allow firms to onboard new clients instantaneously.
Automated identity verification
Automated identity proofing streamlines the onboarding process and helps companies increase client retention.
You may verify the identification of users in a matter of minutes using a digital solution.
You don’t need to hire or outsource a huge compliance team to scale. Automation makes it simple to enter new markets.
Users’ sensitive data is stored in a secure manner. Innovative and enhanced technologies such as Optical Character Recognition (OCR), machine learning, and Machine Readable Zone (MRZ) are used to check documents.
How businesses automate identity verification
If you have taken a decision to automate your identity verification process, here’s what you need to know:
Capture of identity documents
Businesses may incorporate automatic file capture into their apps with the proper solution. Users will be guided through the verification procedure via the right tool.
Biometric data collection
Users can take selfies with biometric methods. It can also ask for a face recognition video to authenticate the validity of the document owners.
Hybrid and automated evaluation
Thoughtful analysis examines data sets and conducts a real-time analysis of submitted information as well as biometric collection. If the ID cannot be verified, a fraud expert will carefully check the information.
Results in real-time
After the analysis is completed, the user will receive a real-time result on the validity, legitimacy, and uniformity of the documents examined.
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