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How Automation Eases the Pain of Commercial Bank Customer Onboarding

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

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We’ve written before about how intelligent process automation is a boon for banks and other financial institutions. We’re taking a deeper dive into how intelligent process automation helps with a particularly complex and expensive process for commercial banks: customer onboarding

For commercial banks, the customer onboarding process involves no fewer than eight steps, according to Deloitte white paper 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 involves numerous additional steps. The account owner data includes business licenses, partnership agreements, and credit histories from various sources. Once collected, someone manually extracts relevant data and uploads it into internal bank systems for analysis. The same goes for the other seven steps.

Deloitte states the onboarding process can take up to 16 weeks to complete, at a cost of $20,000 or more. 

 The adoption of robotic process automation (RPA) for banking helps automate some steps in the onboarding process. Now banks look 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,” Deloitte states. 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.  Deloitte describes that the same bank would see another $100 million in savings from the automation of ongoing monitoring processes every three years. 

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


IPA complements RPA for customer onboarding 

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 Deloitte describes.

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

The Deloitte report notes that cognitive technologies 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 simultaneously, thus improving customer satisfaction with the process while also reducing the risk of human error.

Customer onboarding is just one example of intelligent automation in banking. Many more examples exist in other areas of financial services, healthcare, insurance, and more. Learn more –download the Everest Group white paper, Unstructured Data Process Automation.


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