ScalePoint Research
Independent analysis of AI for payments and finance operations
ScalePoint Research evaluates AI models on payments and finance workflows, scoring them on the financial mistakes they make and the total token cost to run them. See the research agenda →
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- 51payments and finance processes mapped across six types of firm
- 34AI models tested via OpenRouter, each with its hosting route and data retention terms
What the tests show so far
Every chart below comes from the live leaderboards and updates when a test does. Enter research for every result.
The research agenda
AI agents are showing up in payments and finance operations, both in vendor products and in tools firms build themselves. Either way, an AI model underneath does the work. The research asks two questions about those models.
How well does each model do a given payments task, and what do its mistakes cost?
Each test has a leaderboard that ranks models on the money they get wrong, kept up to date as new models come out.
What does each model cost to run at a firm's own volume, and where can it run with zero data retention?
The cost per task sits next to every score, and the hosting page shows which routes keep no copy of the data.
Each test takes one task from a map of 51 payments and finance processes. Read the full research agenda →
Articles on AI in payments and finance operations
What Changes When an AI Agent Works the Queue
The roles, controls and numbers that change once an agent does the first pass on every case.Read → AI agents · OutlookWill AI Agents Be Standard in Finance Operations by 2031?
How far agents have come in five years, what the forecasts say, and why adoption won't be even across processes or firms.Read → AI agents · Worked exampleHow an AI Agent Works a Reconciliation Break
One £1,240 settlement shortfall, followed step by step: who does what, and what drives the cost.Read → AI agents · GuideAI Models, Copilots and Agents: What's the Difference
A plain guide for CFOs being pitched AI agents in finance and payments operations.Read →About
Martin Koderisch is the founder and lead analyst of ScalePoint Research. He focuses on testing how well AI models handle payments and finance operations tasks, and what they cost to run, so that payments and finance teams can make better build or buy decisions.
He spent ten years in operating roles at Citi, Mastercard and the start-up Luup, then nine years at Edgar, Dunn & Company, latterly as a Principal, on more than 75 engagements for banks, fintechs, card networks, private equity firms and merchants. Since 2024 he has worked independently with payments and fintech businesses on strategic finance and value creation. He splits his time between London and Barcelona.
Martin on LinkedIn →Custom work
ScalePoint Research also takes on custom work for payments and finance teams, from testing models on a firm's own files to the business case behind the decision.
- Private evaluations. Testing AI models, or a vendor's AI product, on your own cases, with accuracy and cost per task at your volume.
- Unit economics and strategic finance. What a process costs to run today and with AI at your volumes, whether the savings in a business case will land and when, and how that feeds a budget, a value creation plan or a deal.
- Build or buy. Whether to build, buy or combine for a given process, and what good looks like before an RFP.
Email Martin Koderisch to talk it through. Every piece of work is agreed in a fixed-price statement of work.
martin@scalepointpartners.com