Improve the activation rates of genuine customers and prevent fraudsters from gaining access to your services.
Udentify Digital Onboarding
How it works
1. Scan ID
2. Take a Selfie
3. Result
Features
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Fast and accurate.


Mostly everything.
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Automation.
Fraud.com’s autopilot precisely identifies customers’ ID documents to minimise errors.

Smart guidance.
Fraud prevention.
cutting-edge AI fraud detection technologies to differentiate between trustworthy customers and fraudulent ones.
Protecting the customer, your brand and reputation.
Meet regulatory compliance mandates.


Tailored for
your business.

Gain a complete picture of your customers onboarding and biometric authentications with the Udentify identity hub.
Resources
Keep up to date with the latest onboarding insights.


Case Study
FAQ
Digital customer onboarding refers to enrolling a new customer to a company or subscribing a new user to a service using their mobile device. The key objective of digital customer onboarding is to authenticate the identity of the enrolled person to ensure that they are who they claim to be.
To achieve this, facial biometrics and liveness detection technology, along with identity document processing, are employed to verify the user’s identity digitally and remotely.
Passports, Driving licenses and government-issued ID cards. Udentify supports 12,000 document templates currently and we are constantly adding new templates as required.
An artificial intelligence-assisted verification method that detects whether the presented person is a live person and not a spoof (i.e. video, image or mask). Udentify passive liveness detection works in the background to speed up the onboarding, age verification and authentication process. It also; does not present the technology to fraudsters to leave doubt in their mind, as no fraudster likes to show their face.
Udentify passive liveness detection is iBeta ISO 30107-3 Level 1 & Level 2 certified, delivering the confidence that only your onboarded live customers can access your services.
To complete the digital customer onboarding process, the individual’s identity must be entered into the system.This can be done in two ways using NFC or OCR technologies.
NFC technology is used for documents that adhere to ICAO-9303 standards, such as chip ID cards, passports, and driver’s licenses.
OCR technology is used for non-chip documents like driver’s licenses or government-issued IDs.
NFC technology is a wireless communication system that enables data exchange between devices with one touch. Udentify’s NFC technology quickly reads identity information from chips and saves it to the Udentify server without additional documents.
OCR technology is an AI-based technology that processes text from scanned documents or image files.
Udentify uses OCR to quickly process and save identity information from chipless identity documents without additional data entry.
Recently, biometric-based digital onboarding has gained significant popularity, particularly in banking, due to the pandemic. Digital or client onboarding in the banking sector refers to the process of signing up for banking services, including opening a bank account entirely online, usually through a mobile device.
Banks and other financial institutions are legally bound to know their customers and perform Know-Your-Customer (KYC) checks or procedures. When onboarding clients remotely, a secure and reliable way of verifying a client’s identity digitally is vital. This process is called eKYC or electronic Know Your Customer, as it is entirely digitised.
Within the eKYC process, banks or financial institutions must ensure that the client is genuinely who they claim to be. This can be challenging to verify remotely, primarily due to the rise of online identity fraud and deep fakes. That’s why fully remote digital onboarding steps in.
During the digital customer onboarding process, the client’s identity is verified by 1. validating their identity document and 2. matching their presented face using AI face verification to the validated identity document to check they are the right person, simultaneously checking that they are a real live person using passive liveness detection.
There are two types of liveness today, passive and active. Passive liveness does not require any action from the user, while active liveness does. Active liveness may be more beneficial for frequent logins but can also cause friction and lead to high abandonment rates for new customers. It is essential to consider the differences between the two approaches when deciding which one to use.
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Active | Passive | Hybrid | |
User experience | Users are required to respond to “challenges” (i.e. look left, look right etc) that may increase the time and effort needed for the process. | This process does not require any action from the user, which reduces any difficulties and decreases the likelihood of users abandoning the process, especially in cases of remote digital customer onboarding. | Hybrid liveness detection is a new form combining active and passive liveness detection. However, unlike the typical active detection on its one, when combined with passive liveness detection, any customer actions (challenges) are coupled, thus validating the presented user is the right person. |
Image Analysis | Requires analysis of multiple images or frames of video to detect movement. | The analysis can be carried out using a single image and processed almost instantly. | |
Speed | Active liveness always increases user effort, resulting in a more extended liveness check. | Near real-time. | |
Bandwidth requirements | It may be necessary to exchange more data between the user’s device and a server-based solution. | Passive liveness detection uses the same selfie used for facial recognition, resulting in no incremental traffic to the server. | |
Robustness of spoofing | Fraudsters can use active systems to figure out how to bypass the liveness check. They can easily reverse-engineer the instructions provided to them. Some standard methods they use to break through include using a 2D mask with holes for the eyes or animation software to imitate head movements, smiling, and blinking. | There is an advantage to using passive methods for security, which is known as “security through obscurity.” These methods are less susceptible to spoofing attacks, as the perpetrator does not have any clues as to how to bypass the liveness check. In fact, they may not even be aware that the check is taking place. |

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