Approval-gated AI agents for the workflows banks are most exposed to losing. Cross-border payments, FX, liquidity, collections, cashflow forecasting. Deployed under your brand. Inside your data perimeter. Governed by your policies.
Banks face two pressures at the same time. Direct-to-company fintechs and ERP platforms are taking the daily business banking workflow away. General-purpose AI assistants are starting to take the channel that used to belong to the bank. Both pressures call for the same response: agentic capability inside the bank’s own perimeter, in 2026.
Building business banking technology with banks since 2016 · Global Finance Innovator Award 2024
The threat to banks is workflow-shaped. It rarely arrives as a wholesale switch of bank accounts. It arrives one workflow at a time. Payments, foreign exchange, cash visibility, collections. Small and mid-sized companies have been quietly switching parts of that workflow away from their bank for several years. Each workflow that leaves is a daily relationship the bank no longer owns.
Independent research from Capgemini’s World Payments Report 2026 puts the numbers next to the pattern. Only 15 percent of small merchants and 22 percent of mid-sized merchants are satisfied with their bank’s merchant services. Forty percent of small and mid-sized merchants are considering a shift to specialist payment technology providers. Sixty-six percent still prefer their traditional bank for financial services. The opening is closing fast, but not yet closed.
A second pressure has arrived more recently. Small and mid-sized company owners are starting to use general-purpose AI assistants to plan, decide, and act on their financial life. If a third-party AI assistant becomes the company owner’s first interface for money decisions, the bank moves one click further from the relationship. Surveys put the willingness to use a third-party AI financial agent at around 57 percent of customers if their own bank does not offer one.
Book a 45-minute working session with us. Bring one workflow your bank is currently losing to a fintech, or worried about losing to an external AI assistant. We will walk through what the agentic layer would look like for that workflow inside your brand, your data, your governance.
Independent research finds that banks deploying agentic AI in the frontline report between three and 15 percent higher revenue per relationship manager and 20 to 40 percent lower cost to serve. In many banks, relationship managers spend only 25 to 30 percent of their time in client dialogue. Agentic AI returns 10 to 12 hours per week to each banker.
Bring one workflow you are losing, or worried about losing. We will walk through what the agentic layer would look like for that workflow inside your brand, your data, your governance.
Agentic Business Banking is TreasurUp’s model for delivering AI agents inside a bank’s own business banking channels. It combines a composable banking platform, an Intelligence Engine grounded in domain AI, and approval-gated agents for the daily workflows of small and mid-sized company clients.
Every agent action with financial, regulatory, or accounting impact passes through an explicit human approval before anything happens. The agent prepares the work – it gathers the data, applies domain rules, and presents a recommended action alongside the alternatives it considered – but the company user or bank user makes the final call. The platform does not expose autonomous-execution APIs for material actions, so this is structural, not a setting you can switch off. Every approval is logged end-to-end with the agent’s full reasoning chain, the input data, the ranked alternatives, the approver’s identity, and a post-action check.
The roster covers the workflows where banks are most exposed to fintech and AI-assistant competition, split between company-side and bank-side agents. Company-side: Cross-border Payments, Collections & Receivables, Liquidity Management, FX Risk Management, Cashflow Forecaster, and the Copilot for Business Banking (a natural-language interface). Bank-side: Sales Intelligence Radar, Client Reporting & Sales Analytics, and the Trade Anomaly Detector. The lead modules ready to deploy first are the FX Risk Management agent and the Cashflow Forecaster.
Banks choose the deployment shape that fits their estate. Managed SaaS is fully hosted by TreasurUp and fastest to deploy. Single-tenant runs the full platform inside the bank’s own cloud, in the bank’s region of choice, so bank data never leaves the bank’s perimeter. Hybrid splits the stack – orchestration stays TreasurUp-hosted while sensitive data and inference stay inside the bank’s boundary. Across all three, Bring-your-own-LLM lets the bank pick its own foundation model, whether a leading commercial model, a bank-private model, or a multi-vendor mix.
Compliance is designed in from the ground up, not bolted on. Components are classified against the EU AI Act’s risk tiers and ship with the documentation banks need for high-risk system obligations. For DORA, components are catalogued and classified by criticality, support TLPT-style resilience testing, and stream incidents to the bank’s existing SIEM through standard interfaces. Every agent carries a registered specification covering model, version, inputs, outputs, decision rights, and fallbacks, and banks can run independent validation, monitor for drift, and disable, override, or roll back any agent without TreasurUp involvement.
It depends on your starting point. For banks already running TreasurUp modules, the agentic layer is a configuration and rollout exercise rather than a new procurement, with live agent deployments targeting the second half of 2026. For banks new to TreasurUp, procurement, security review, and model risk validation run in parallel from week one, putting end-to-end time from contract to the first company-user-facing agent at around six months for the lead modules.
Four deliberate non-goals, and they are permanent. No autonomous trade execution – agents propose, humans approve, and the trade ticket flows to the bank’s own execution venue. No autonomous limit changes – counterparty, product, and policy thresholds stay with bank governance. No agent-to-agent transactions across institutions – cross-institution agentic flows are a 2027 question, not a 2026 one. And no autonomous credit decisions – agent insights inform the bank’s credit and risk teams, but the decisions stay inside the bank’s frameworks.
A 12-month roadmap for banks serving small and mid-sized companies.
A 12-month roadmap for banks serving small and mid-sized companies. The three-layer platform, the agent roster, deployment choices, governance posture, and how banks engage. Seventeen pages, with all source data attributed.
A 12-month roadmap with attributed source data, written for banks serving SMEs. Everything you need to move from “we should look into this” to a defensible plan.
