AI Agents for finance operations
Purpose-built AI agents that own specific finance tasks — AP, reconciliation, procurement, compliance, cash-flow — grounded in your data, governed by four-eyes controls, and deployed in weeks, not quarters.
Why generic chatbots fail in finance
- They hallucinate on numbers and account codes.
- They can't call your ERP or bank safely.
- They leave no audit trail.
- They bypass approval controls.
Grounded agents with typed tools
BancoOS agents run on a runtime purpose-built for finance: typed tools that call your ERP, ledger and bank; memory scoped to the workflow; guardrails enforced at the platform layer; every action logged for audit.
Agents that ship out of the box
- AP Agent — captures, validates, matches and prepares invoices for approval.
- Reconciliation Agent — reconciles bank statements against the ledger and surfaces breaks.
- Procurement Agent — matches quotes, POs and supplier terms.
- Compliance Agent — validates GDT, MST and internal policy.
- Cash-Flow Agent — maintains a live 13-week forecast.
- Copilot — natural-language interface across every dataset.
Business benefits
- 10× throughput per finance FTE.
- Exceptions surfaced in minutes, not days.
- Full audit trail for every agent action.
- Governance and controls preserved.
Use cases
- Auto-processing 90%+ of vendor invoices without human touch.
- Overnight bank reconciliation across every account.
- Continuous compliance monitoring against GDT and internal policy.
- Real-time cash-flow answers to executive questions.
Architecture & workflow
Integrations
Agents call MISA, SAP Business Central, NetSuite, GDT, Vietnamese banks and your data warehouse through typed tools — never through screen scraping.
Security, governance & controls
Tenant isolation, per-tool authorization, four-eyes controls, prompt and output logging, evaluation harness, and no customer data used for model training.
ROI metrics
- Touchless invoice rate above 90%.
- Payback within 6 months.
- 10× throughput per FTE on automated workflows.
Frequently asked questions
›What is an AI agent in BancoOS?
An AI agent is a purpose-built worker that owns a specific finance task — for example, matching invoices to POs, reconciling bank statements or answering GDT compliance questions — with tools, memory and guardrails scoped to that task.
›How are BancoOS agents different from generic LLM chatbots?
They are grounded in your ledger, ERP and document store; they call typed tools rather than free-form web APIs; every action is logged; and they operate inside human approval workflows.
›Which agents ship out of the box?
The AP Agent, Reconciliation Agent, Procurement Agent, Compliance Agent and Cash-Flow Agent. Custom agents can be built for your specific workflows.
›Do agents make autonomous payments?
No, unless explicitly authorized. By default agents prepare work and route it for human approval; four-eyes controls are enforced at the platform layer.
›How are agents evaluated for accuracy?
Every agent action is logged with its inputs, tool calls, outputs and confidence. Continuous evaluation runs against golden datasets, and drift triggers alerts to the platform team.
›Which LLMs do agents use?
BancoOS orchestrates multiple foundation models per task, choosing based on latency, cost and accuracy — customers do not need to pick or manage models.
›Is customer data used to train models?
No. Customer data is never used to train foundation models. It stays in your tenant and is used only to serve your workflows.
›Can we build our own agents on BancoOS?
Yes. The Agent SDK exposes typed tools, workflow steps and evaluation hooks so your team can build domain-specific agents on the same runtime.
›How do agents handle exceptions?
Anything below a confidence threshold, or outside policy, is routed to a human workqueue with full context and the agent's reasoning attached.
›Are agents deployed per-tenant?
Yes. Each customer gets isolated agent runtimes, memory and tools — nothing is shared across tenants.