The road from idea to market can be winding for a product, but tech provider nCino’s strategy is in high gear. 

“It’s not just about what we’re hearing from our customers, but where do we think the market is headed and what is trending that the technology enables,” Sean Desmond, chief product officer at nCino, told Bank Automation News. 

With industry trends and consumer demand in mind, nCino works to innovate around identified business challenges facing its clients, Desmond said. 

To develop timely products, Wilmington, N.C.-based nCino follows these steps: 

Market momentum drives development

The tech provider’s Banking Advisor tool, launched in June, was inspired by momentum from the market and consumer demand around AI, Desmond said. 

Seventy percent of nCino’s clients said they want a focus on efficiency and expect to gain 20% to 30% in efficiency from AI, Desmond said. 

AI-driven Banking Advisor delivers on those efficiency demands, he said of the tool that helps modernize portfolio management, streamline repetitive tasks and simplify complex processes. 

Developing Banking Advisor 

To create Banking Advisor, nCino followed its product development steps: 

• Market research: There continues to be interest in the market around AI and its ability to bring efficiency to financial services, Desmond said.  “We think about efficiency as a key driver,” he said. Once demand for an AI-driven solution was identified, Banking Advisor was born out of nCino’s annual hackathon event, in which employees from across the bank could pitch ideas that solve the issue, Desmond said.  
• Consumer survey: After Banking Advisor was pitched based on client need, nCino began creating a solution to automate search-and-retrieve processes for structured and unstructured documents, he said. 
• Software development lifecycle: To build upon the hackathon idea, nCino leaned on its existing data lake, which reduced the build time, Desmond said. The tech provider had the data lake and the modeling, so it only had to train large language models and send data to those models. That’s where the team came in. 
• Allocating resources: For Banking Advisor, “we’re taking a handful of data scientists, a handful of engineers and a project manager,” Desmond said, noting that some of the data scientists were brought in from outside but the product manager and engineering team were already nCino employees. 
• Go-to-market: When the first iteration of Banking Advisor was ready, nCino offered the solution to existing clients as part of an early adopter program, which offers fast feedback on how it’s operating, Desmond said. The tool was then launched, but the innovation is never done.
  
• Iteration: Once Banking Advisor could solve problems for commercial clients, nCino realized the tool could be extended across consumer, small business, mortgage business and other areas, Desmond said. The company sees opportunities for Banking Advisor use in unstructured data with documentation and automating data extraction and other functions, Desmond said. “We’re constantly managing, prioritizing and iterating in our roadmaps across the platform by solution,” Desmond said. 

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