The first wave of nCino’s AI credits wasn’t just tested. It was fully consumed. Now, over 230 banks are paying for more.
That's the core takeaway from nCino CEO Sean Desmond's latest earnings call, according to PYMNTS. Desmond revealed that early adopters have "used up their first bundles of credits and have come back for more," confirming a transition from cautious pilot to operational necessity. For legacy banking software, this is a rare signal: a new product with a usage-based pricing model is gaining traction not in slide decks, but in actual budgets.
This pattern of consumption isn't happening at the fringe. Twenty of nCino's largest U.S. enterprise customers, representing over $900 billion in assets, renewed their contracts ahead of schedule. They did so with an average annual contract value (ACV) increase of more than 10% explicitly to lock in access to nCino's expanding AI tools. As Desmond framed it, "They’re proactively doubling down on nCino because we’ve spent nearly 15 years building the trusted global system of record for critical banking processes."
From Experimental Credits to a Core Operations Budget
The shift is stark. Just months prior, in a December 2025 earnings call, the company reported 110 customers had purchased its Intelligence Units, the credit bundle used to pay for AI agent tasks. That figure has now more than doubled to over 230. This isn't a story of spreading trial licenses. It's a story of consumption.
The implications are concrete. A free sample or a proof-of-concept credit is easy to ignore. A paid, recurring line item for additional units means the tool is delivering measurable, repeatable work that banks are unwilling to stop. When Desmond stated, "We have recently begun monetizing the sale of additional Intelligence Units... a strong signal of engagement," he was understating the case. It's a signal of dependence.
XOOMAR Analysis: nCino has successfully executed a classic "land and expand" SaaS playbook, but with an AI twist. They used their entrenched position as a cloud banking system of record to land the initial AI credits. The rapid consumption proves those credits unlocked workflows banks didn't want to give back, triggering the expansion phase. This upgrades AI from an R&D cost center to a variable operational expense tied directly to productivity.
What Were Those Credits Actually Buying?
The source material provides one powerful, quantified example. Desmond cited a single U.S. enterprise customer that reported saving 160,000 hours per year using the "locate and file" function within nCino's Banking Advisor. Based on median loan officer compensation, that translates to over $5.5 million in annual savings.
“Proof points like this are motivating customers to transition to our platform pricing model to gain access to nCino’s agentic solutions and other AI initiatives,” Desmond said.
This points directly to the type of work consuming those initial credits: high-volume, repetitive, document-intensive back-office tasks. The AI agents, or Digital Partners as nCino brands them, are likely handling:
- Processing loan documentation
- Extracting data from forms
- Routing files and triggering compliance checks
- Assembling customer profiles from disparate data sources
The "agentic" label suggests these aren't simple macros. They likely involve multi-step reasoning: find document X, verify its completeness against checklist Y, extract key fields Z, and file it in workflow A. This is the grunt work that bogs down lending and onboarding, and it appears banks found the AI efficiency too valuable to dial back. For more on how AI agents are reshaping financial infrastructure, see our coverage of the AI Agents Swarm Financial APIs in Architecture Invasion.
The Hidden Threshold: From Utility to Strategic Renewal
The most revealing data point isn't the credit consumption. It's the renewal behavior of the largest customers. These are institutions with the "financial and technical resources to build internally if they choose to," as Desmond noted. Their decision to renew early and pay more is a strategic vote against in-house development for this generation of AI tools.
What this signals:
- Speed to Value: Buying proven, integrated agents from nCino is faster and more reliable than a multi-year internal build.
- Integration Depth: The AI tools are woven into nCino's core banking platform, making them more valuable than standalone point solutions.
- Risk Mitigation: These banks are effectively outsourcing the initial model risk and operational complexity to a vendor.
The 10%+ ACV bump is the price of securing what they now view as a competitive necessity. This dynamic puts immense pressure on other core banking vendors. If they cannot demonstrate similar AI consumption and renewal momentum, they risk being viewed as legacy anchors.
What Comes After the Credit Binge?
The path forward involves three critical watch items, all extrapolated from the source's facts.
Watch the credit velocity. The next earnings call should reveal not just how many customers are buying credits, but how quickly they are burning through them. Accelerating consumption would indicate AI agents are taking on more complex, higher-volume tasks. Stagnant usage might suggest a ceiling on current automation opportunities.
Monitor for the "explainability" pivot. As these AI agents move from filing documents to potentially assisting with risk assessments or compliance flags, regulatory scrutiny will follow. nCino's next challenge is baking audit trails and model transparency directly into its agentic workflows to satisfy examiners. Success here will separate scalable adoption from stalled pilots.
Observe the competitive response. nCino has a first-mover advantage within its installed base. The real test is whether its AI capabilities become a reason for banks outside its core customer base to switch platforms. If nCino starts landing new enterprise deals primarily on the strength of its AI roadmap, it will confirm a wider industry shift.
For financial institutions, the lesson is operational. AI adoption is no longer about running a pilot. It's about identifying the highest-friction, highest-cost manual processes and instrumenting them to measure an AI agent's hourly savings. The bank that saved 160,000 hours didn't start with a grand AI strategy. It started with a frustrating, time-consuming problem and found a tool that solved it. The credits were just the meter running.
Disclaimer: This XOOMAR analysis is for informational and educational purposes only. It is not financial, investment, legal, tax, or professional advice. It does not provide buy, sell, hold, price-target, portfolio, or personalized recommendations. Verify information independently and consult qualified professionals before making decisions.
The Bottom Line
- It signals AI is moving from banking pilot projects to core operational tools, changing how financial institutions invest in technology.
- The shift to usage-based pricing with paying customers indicates real, measurable value is being delivered, not just promised.
- This trend could accelerate digital transformation across the banking sector, forcing competitors to adapt or risk losing efficiency.
Originally published on XOOMAR. For more news and analysis, visit XOOMAR.
