Open source models allow for flexibility and efficiency, enabling organizations to tailor development tools to their unique needs and make them more accurate by incorporating a financial institution’s proprietary data. As a result, 83% percent of respondents said open source is important to their organization’s AI strategy, with 43% saying it is very to extremely important.
“Open source models can help banks close the gap with early movers, unlock cost efficiencies and safeguard against vendor lock-in, but they’re not without their limitations — proprietary approaches can unlock superior performance for domain-specific tasks,” said Alexandra Mousavizadeh, cofounder and co-CEO of Evident Insights. “Leading banks need to demonstrate proficiency in both approaches — applying the right kind of model to the right problem, in the right context.”
Financial institutions have moved from piloting AI projects to deploying solutions that create business impact and scaling them across the organization. In turn, companies have begun to see significant return on investment from AI on the top and bottom lines.
As stated above, 89% of survey respondents said AI has helped increase annual revenue and decrease annual costs. For many organizations, the impact has been significant, with 64% of respondents saying AI has helped increase annual revenue by more than 5% — including 29% who said revenue increased more than 10%.
Similarly, 61% said AI had helped decrease annual costs by more than 5%, with 25% saying costs decreased more than 10%.
Respondents cited a long list of AI use cases that have provided return on investment, including document processing and management, customer experience and engagement, algorithmic trading and risk management.
Creating operational efficiencies is the largest improvement AI has made in financial services, according to 52% of respondents. And 48% said employee productivity was among the biggest improvements.
“The most tangible ROI I’m seeing is in payment operations, specifically authorization optimization and intelligent routing,” said Dwayne Gefferie, payments strategist at Gefferie Group. “Agentic AI systems can now autonomously route transactions to the most optimized payment networks, dynamically adjust retry logic based on real-time issuer signals and make routing decisions under 200-millisecond routing that traditional rule-based systems simply can’t match. What makes this compelling is that every basis point improvement in authorization rates translates directly to revenue — there’s no ambiguity in measurement.”
Given the shift from running proof of concepts to deploying AI-enabled applications into production, the financial services industry is looking to significantly expand AI budgets. Nearly 100% of respondents said their AI budgets would increase or stay the same in the coming year.
About 41% of respondents said investment would go toward optimizing AI workflows and production, reinvesting in and improving the AI solutions that are already working.
More than a third (34%) said they had an eye toward AI expansion in their organizations, with spending focused on identifying additional use cases. And 30% said that investment would focus on building or providing more access to AI infrastructure, such as on-premises installations or in the cloud.
Investment will also flow to deployment and expansion of AI agents, which are advanced AI systems designed to autonomously reason, plan and execute complex tasks based on high-level goals. About 21% of respondents said AI agents have already been deployed, with another 22% saying AI agents will be deployed within the next year and beyond.
“The institutions winning in AI are treating their proprietary data as a strategic asset for building differentiated AI products,” said Yu.
Download the “ State of AI in Financial Services: 2026 Trends ” report for in-depth results and insights.
Explore NVIDIA’s AI solutions and enterprise-level AI platforms for financial services .
Everything Will Be Represented in a Virtual Twin, NVIDIA CEO Jensen Huang Says at 3DEXPERIENCE World
Key considerations
- Investor positioning can change fast
- Volatility remains possible near catalysts
- Macro rates and liquidity can dominate flows
Reference reading
- https://blogs.nvidia.com/blog/ai-in-financial-services-survey-2026/#content
- https://www.nvidia.com/en-us/
- https://blogs.nvidia.com/?s=
- I stuck with the same PC controller brand for four years – here's what to look for in your next gamepad
- Retro Apple Mac mod implements thermal printer floppy swap — machine also benefits from a Mac Mini brain transplant
- Asus ProArt PA32KCX 32-inch 8K professional monitor review: A reference for color, pixel density, and brightness
- Nvidia says it didn't use pirated books to train its AI models — company asking for Anna's Archive suit to be dismissed
- How to Get Started With Visual Generative AI on NVIDIA RTX PCs
Informational only. No financial advice. Do your own research.