How AI is Taking the Headache Out of the New Customer Onboarding Process

Perhaps no aspect of the financial services workflow is more frustrating than new client onboarding – both for the clients and the companies that want to service them. It should not be that way. This is the moment of truth when both parties have already agreed to work together, terms have been set, and enthusiasm for what comes next – whether it’s a new auto or home loan, a new banking relationship, or a new investment account opening – is at its highest. Yet, when it comes to this final step in consummating that relationship, the process is often beset by cumbersome records transfer, redundant information requests, and slow processing times.

In fact, the average mortgage closing cycle time on a new home loan is 42 days, according to Freddie Mac and in the retail banking space, onboarding can take anywhere from 20-90 days or more. Then, as if to add insult to injury, just over half (56%) of those new bank accounts end up converting to active banking relationships. Similar trends exist in insurance, where the onboarding cycle for a life insurance policy can be upwards of six weeks, and countless other business relationships where regulatory pressures and clunky workflows have made it difficult to get new clients up and running.

Also Read: AiThority Interview with Thyaga Vasudevan, EVP of Product at Skyhigh Security

Streamlining a Broken Workflow

Set against the backdrop of huge advertising spends and staggering new account acquisition costs, these stats are almost hard to believe. After all the time and money that goes into wooing a new customer, their first experience with the brand is a multi-week waiting period during which they are asked to scan and email – sometimes even fax – forms, submit to background and credit checks, and repeat information, often in triplicate, to an assortment of different representatives and digital platforms. Sometimes, the process takes so long that customers need to resubmit newer versions of the same documentation they already submitted just to keep everything up-to-date.

It does not have to be that way. New advances in generative artificial intelligence (GenAI) are making it possible to dramatically streamline all aspects of the new account onboarding process while also reducing errors and improving risk management. Based on my team’s work with some of the world’s largest financial services and insurance firms, following are some of the most exciting applications of GenAI to improve the onboarding experience:

• Automated Records Aggregation: One of the biggest customer pain points in the onboarding process is digging up and sending all of the documents required to prove identity and asset ownership. Even basic tasks like scanning photos of the front and back-sides of a driver’s license or – in the case of a life insurance claim – going through the pain and hassle of securing death certificates and sending them electronically. With GenAI, financial firms and insurers are now able to access much of that information automatically by scouring public records, connecting directly to funeral home records management systems, and process that information straight-through to satisfy new client onboarding requirements – without the client having to do anything.
• Real-Time Feedback: GenAI is also extraordinarily proficient at scouring through vast amounts of structured and unstructured data to quickly identify anomalies and critical pieces of information that are missing. So, for example, in a new account opening scenario, if a reference document provided is out-of-date or some other form of evidence is required, that feedback can be provided in real-time, rather than making the client wait several weeks only to learn that they need to resubmit paperwork. The introduction of this real-time checklist throughout the onboarding process has been shown to dramatically reduce cycle times.
• Computer Vision: Photographic evidence has become increasingly popular in insurance and lending for assessing the value of things like vehicles, homes, and other forms of property. However, relying on photos taken by consumers on their phones can sometimes lead to some degree of uncertainty. With GenAI-powered photo analysis tools, it is now possible to analyze those photos to ensure that all angles are represented and the piece of collateral is indeed what it purports to be. Additionally, in the property and casualty insurance space, aerial images from satellites and drones, coupled with AI-powered computer vision technologies are making it possible for insurers to conduct virtual site visits without ever sending a representative out to the property.
• KYC and KYP Screening from Public Records: One of the big reasons for the lengthy new client review process that exist in regulated industries like financial services and insurance are the strict know your customer (KYC) and know your patient (KYP) regulations that exist to root out fraud and money laundering. With its power to instantly scour millions of records across public databases and other sources, GenAI is making it possible to satisfy KYC and KYP requirements in minutes, without putting clients through a gauntlet of exercises designed to prove that they are who they say they are.
• Business Document Processing: These streamlined processes also apply in a business-to-business context in situations like vendor screening and new supplier on-boarding, whereby a prospective partner is typically asked to provide financial statements, invoices, and other documents as part of the screening process. GenAI is making that process seamless by integrating directly with vendor management portals to synchronize all aspects of the onboarding journey.

Also Read: The State of Gen AI in Customer Service

Delighting the Customer – From Day One

The irony should be obvious to anyone with even a basic sense of customer experience or brand advocacy that greeting a new customer with an arm-long list of homework items and a litany of questions designed to prove that they aren’t lying isn’t exactly the warm fuzzy way to start a relationship. In fact, data has shown that with certain onboarding-intensive purchases like life insurance and annuity products, for example, customer satisfaction starts declining immediately after purchase.

Deployed properly, GenAI has the power to reverse that trend while giving financial firms and insurers even more reliable intelligence on their customers. While the mainstream discourse around GenAI in finance and insurance has largely centered on chatbots and large language models (LLMs), the back-end workflow processing gains made possible by the technology may be the biggest breakthrough we see in this field.

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