For much of the financial services industry, the conversation around AI has focused on creating efficiencies by automating processes, reducing costs, and replacing manual work. But banks may be overlooking AI’s biggest opportunity. Rather than focusing on what AI can eliminate, financial institutions may find greater value in using the technology to better understand their customers, anticipate their financial needs, and deliver personalized experiences that drive revenue.
In this conversation from FinovateFall 2026 in New York, we speak with Oban MacTavish, Co-Founder and CEO of Spade, about why the industry’s enthusiasm for AI agents may be misplaced and how better transaction data can help banks unlock AI’s potential. MacTavish explains why traditional payment data isn’t built for modern intelligence tools and how financial institutions can use AI to recreate the personalized relationships customers once had with their local bankers, but at scale.
“I think most of their customers are looking for a better experience, and it’s one of the ways that we actually see the biggest opportunity for AI in financial services is helping them turn their data into revenue,” said MacTavish.
MacTavish is Co-Founder and CEO of Spade, a New York-based financial data and AI company he co-founded in 2021. Under his leadership, Spade has expanded its platform to help financial institutions make better use of payments data for fraud prevention, customer engagement, analytics, and AI-powered applications. MacTavish also participated in a fireside chat at FinovateFall 2026 on how AI is changing offers, cross-sell, and personalization.
Founded in 2021, Spade transforms raw transaction data into structured, actionable merchant intelligence. Its platform helps banks, fintechs, and other financial services companies identify merchants, enrich transaction records, and build more personalized financial products and experiences. Spade raised $40 million in Series B funding in March 2026, led by Oak HC/FT, to expand its data and AI capabilities.
Photo by RDNE Stock project
