How Automation Eases the Pain of Commercial Bank Customer Onboarding

July 30, 2020 / Commercial Banking, Intelligent Process Automation, Use Case

customer onboarding

We’ve written before about how intelligent process automation can be a boon for banks and other financial institutions, but in this post we’re going to take a deeper dive into how it helps in an area that can be particularly complex and expensive for commercial banks: customer onboarding. 

For commercial banks, the process of customer onboarding involves no fewer than eight steps, according to a white paper by Deloitte titled, “Automation in Onboarding and Ongoing Servicing of Commercial Bank Clients.” They include:  

  • Soliciting and confirming new clients
  • Collecting account owner data
  • Validating client data
  • Setting up credit lines and limits
  • Completing legal due diligence (including term negotiations)
  • Setting up accounts
  • Tracking and archiving data
  • Completing ongoing reporting and analytics for compliance and cross-selling purposes

Each one of those steps, in turn, involves numerous additional steps. The account owner data to be collected, for example, may include business licenses, partnership agreements and credit histories from various sources. Once collected, someone then has to manually extract relevant data and upload it into internal bank systems for analysis. The same goes for the other seven steps. 

The Deloitte paper says the onboarding process can take as long as 16 weeks to complete, at a cost of $20,000 or more. 

That’s why we’ve seen adoption of technology such as robotic process automation (RPA) in banking, to help automate at least some steps in the onboarding process. Now banks are looking to go further by adopting cognitive technologies including intelligent process automation, natural language processing and machine learning to automate parts of the onboarding process that RPA can’t handle by itself. 

“The rise of RPA and cognitive technologies has enabled many processes to be automated, resulting in up to 50% reduction in on-boarding costs,” the Deloitte paper says. A typical commercial bank with 125,000 customers that onboards around 3% of that number in new customers per year, and expands services for another 6% to 7%, would see around $100 million in one-time savings from automating on-boarding tasks. The same bank would see another $100 million in savings every three years from automation of ongoing monitoring processes, Deloitte says. 

Related Article: How AI is Ushering in New Era of Automation in Financial Services

IPA complements RPA in onboarding processes 

Cognitive technologies help banks pick up where RPA leaves off. “RPA can automate the straightforward, rules-based steps of an activity, whereas cognitive technologies can automate the judgment-based and predictive steps,” as the Deloitte paper puts it.

For example, RPA can be used to help sort documents collected online, extract some data and run a credit check. Cognitive tools including IPA can then be used to “read” and extract data from any documents containing unstructured data, which RPA tools generally can’t handle effectively. Cognitive tools could also be used to analyze the results of the credit check and assign the client a corresponding credit limit. 

The Deloitte white paper notes cognitive technologies also help banks analyze data to “perform sophisticated analysis and offers an opportunity to provide valuable insights,” leading to a more targeted sales approach and operational efficiencies. 

What’s more, automating the onboarding process will likely help streamline it at the same time, thus improving customer satisfaction with the process while also reducing the risk of human error. 

Customer onboarding is just one example of a process that IPA tools can help commercial banks automate. Many more examples exist in other areas of financial services, healthcare, insurance and more. To learn more, download our own white paper, written by experts at the Everest Group. 


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