5 Key Insights from nCino's APAC Summit: How AI Is Reshaping Banking's Future

But here's what really stood out: successful digital transformation isn't just about the latest tech. It's about having the right strategy, quality data, and an unwavering commitment to keeping humans at the center of banking.

Here are five key insights from the Summit.

1. Putting Humans Back Where They Belong

Mark Bernhardi, APAC General Manager, opened the Summit with a challenge to the industry. Banking has become too focused on internal processes, he said-we've turned financial institutions into "data factories" instead of customer-focused enterprises. "I truly believe that AI, embraced well, will allow more of our people to get back to the front line and provide customer outcomes where AI and the systems begin to generate insights."

This theme resonated throughout the Summit. AI's purpose isn't to replace bankers-it's to amplify what they do best. When technology handles routine tasks, relationship managers can focus on what really matters: providing personalized guidance and strengthening the human connections that remain central to banking.

2. The $8 Million Problem Hiding in Commercial Onboarding

Ashleigh Breaden shared research that should grab every financial institution's attention: poor commercial onboarding costs banks approximately $8 million annually per 1,000 applications. Drawing on surveys of over 1,100 banking professionals and SMEs, Breaden revealed that the average commercial onboarding process costs $14,700 per customer and takes 49 days to complete. Even worse? One in 13 customers abandons the process entirely because of frustrating experiences.

The research shows that 80% of customer dropouts happen during document collection, KYC verification, and validation-precisely where automation and AI can deliver immediate impact. Here's the irony: 90% of banking professionals know that better onboarding leads to higher customer lifetime revenue, yet only half believe their institution provides a good experience.

"Onboarding isn't the problem," Breaden explained. "It's how we're thinking about onboarding. That's the problem." Bankers believe they could cut onboarding time in half with the right technology-a change that would reduce costs, rework, and time to decision while accelerating revenue.

Breaden showcased how nCino has rebuilt its digital account opening platform to provide segmented customer journeys: automated self-serve for small businesses, streamlined experiences for mid-market clients, and high-touch service for complex commercial relationships. The platform now offers always-on KYC monitoring with automated alerts for business changes and ownership shifts-moving from point-in-time verification to continuous monitoring that reduces friction at every lending event.

3. Banking Is a Data Business-AI Makes That Data Work

Anthony Morris, nCino's Chief Industry Innovation Officer, delivered what might've been the Summit's most fundamental insight. "We are a data business, at the end of the day. Banking-there's no physical product. It's all data," Morris emphasized. "So a technology that finally recognizes that and allows that to be actionable in a lot more than just lip service is absolutely, fundamentally important."

Morris outlined nCino's investment strategy built on four pillars: accelerating data ingestion, enabling intelligent automation while maintaining human control, leveraging generative AI for administrative tasks, and deploying multifactorial predictive analytics across all aspects of risk and opportunity. He presented a maturity model with three stages-explore, evolve, and embrace-to help institutions strategically implement AI based on their readiness, risk tolerance, and data infrastructure.

4. Why 95% of AI Pilots Fail (And How to Be in the 5% That Succeed)

Will Jung, nCino's Chief Technology Officer, addressed the uncomfortable truth hanging over the industry: despite massive investment and excitement, most AI initiatives fail to deliver meaningful outcomes. Jung cited MIT research showing that 95% of AI pilots fail, and industry data revealing that while AI use cases in banking have doubled in the past year, less than 30% are producing actual results.

Strategy matters more than ever in the AI age. Using Netflix, Nike, and nCino as examples, Jung illustrated how successful companies focus their technology on solving specific domain problems. "It's not the model you use that matters. It's the use cases and the metrics you're going to move that matters."

On data, Jung introduced the concept of context engineering. Without proper context, AI agents are like workers who "come into work, forget who they are, forget their role, forget what they're good at, forget what industry they're in." He reminded attendees that fundamentals matter even more in the AI era: "Your strategy determines what data you need as an organization, the context you provide, the people, the process, the tech your organization runs on."

5. Operational Analytics: The Customer Experience Differentiator

Navin Benoy focused on how operational analytics can transform home lending to meet dramatically evolved customer expectations. Customers now expect the same real-time, seamless experiences they get from other industries-instant feedback, same-day deliveries-to extend to mortgage transactions.

"Customer expectations have completely changed," Benoy explained. "They're getting real-time payments. They're getting instant feedback. They're getting same-day deliveries, and they're bringing some of those expectations into their banking world as well."

He identified the product origination phase as critical-the moment where customer decisions are made and lender options are evaluated. This is where process inefficiencies compound throughout the customer journey, and where "a name put forward at the settlement table really differentiates" one lender from another.

Home lending customers fundamentally seek three qualities: trust, ease, and speed. They want complete transparency about processes, clarity on roles and responsibilities, and above all, rapid execution. "This is a highly stressful area for customers, so they're heavily scrutinizing how quickly and efficiently you can get what they need," Benoy observed. Operational analytics enable lenders to demonstrate their capability to handle complex customer issues effectively.

The message was clear: financial institutions that successfully navigate AI transformation will be those that use technology to put humans back in banking-not those that simply automate for efficiency's sake. As the industry stands at this inflection point, the winners will be institutions that combine AI's analytical power with human judgment, empathy, and relationship-building skills to deliver exceptional customer outcomes.