Still at the end of 2021 here in Namirial we predicted that in the near future 75% of remote onboarding transactions would be handled in a fully automated way through Artificial Intelligence or Digital Identity Systems.
Indeed, AI is a game changer in remote identification processes, but to understand its role in onboarding we must first understand what onboarding is.
What is customer onboarding?
In general, customer onboarding is the process of collecting and verifying all necessary customer information to provide access to a service or product. This data can range from legal name, physical address, email address, banking details etc.
Digital Customer Onboarding is the process of customer onboarding where AI-based solutions are used to automate the verification and authentication of customer data. Indeed, AI algorithms are able to review customer data, verify their identity and authenticate it against reliable sources such as databases or records. This allows customers to complete their onboards more quickly and securely than traditional methods.
What are the benefits of AI in customer onboarding?
The first main benefit of AI-based digital onboarding solutions is the possibility to automate identity and data verification and the ability to quickly process large amounts of data in a secure manner, making them more cost-effective and efficient.
But AI algorithms can also identify fraudulent activity and prevent potential data leakage or other security threats.
Moreover, AI in customer on boarding can analyze users behavior, streamline the customer journey, and provide personalized services, thus improving the overall customer experience.
Challenges of AI in customer onboarding
AI in customer onboarding is not without its challenges and drawbacks. AI algorithms can be biased, leading to unreliable results, or they may not be secure enough to protect customer data. AI also requires a large amount of data to train the algorithms with, which can make implementation more costly. Additionally, AI-based systems require regular maintenance and updating in order to remain competitive and secure.
Compliance or user experience?
One of the weaknesses of digital onboarding is what we call the “tyranny of the cursor,” or the need in remote identification processes to choose between compliance or user experience. Basically, any company implementing a digital onboarding system has to choose between paying more attention to data protection but making the processes more time-consuming and cumbersome for the customer; or, facilitating and speeding up these processes while neglecting compliance. Apparently, a company will have to choose one of the two options, forgoing the other.
Artificial intelligence solves this issue, bringing security and user experience together. In fact, AI makes it possible to have multiple “cursors”, that is, to adjust compliance levels according to the cases or national regulations without affecting the user experience.
But how does a company figure out the right levels without testing and correcting? Well, Namirial‘s application of Ai in customer onboarding has led to the creation of preset systems that allow to avoid having to make adjustments on the fly.
The Digital Onboarding according to Namirial
Namirial makes extensive use of AI in customer Onboarding, in each of the 6 phases that compose it:
- IDVerification – To make sure that the Identity Document presented by the customer is real and valid.
- DocumentCheck – To analyze and verify supporting documents such as payroll or energy bills.
- IdentityCheck – To ensure that the user really exists and is the owner of the ID document.
- Signature – To digitally sign any contract using legally binding electronic signatures.
- Archiving – To securely store onboarding documents for as long as required by law.
- ContractDelivery – To deliver the onboarding contract to the customer by certifying both the delivery process and its contents.
The impact of AI in customer onboarding and on customer experience is particularly found in the first 3 steps:
- During ID Verification, the user takes a front/back photo of their ID. Then, Machine Learning algorithms verify the authenticity of the document by checking several elements. In the case of Namirial’s systems, as of 2015, more than 93 percent of transactions do not require any human verification, and even when local regulations may require a human operator to confirm identity verification, the use of Machine Learning will greatly improve efficiency and take care of tedious systematic checks.
- In the Document Check, the AI can analyze the additional documents. For example, Machine Learning can check if a payroll is recent, identify the employer and verify its existence, check if the pdf has been tampered with.
-
In Identity Check, Remote Identity Proofing usually takes place through a video chat with a human operator. Thanks to AI, specifically deep learning, it is possible to make the process faster and safer. In fact, AI’s accuracy is over 99% compared to an average human accuracy of 97%.
Depending on local regulations, the process can be fully automated or confirmed by a human operator.
