Explainable decisions
Each agent step records its inputs, the policy it applied and its output, so a reviewer, auditor or model-risk team can reconstruct why a case moved forward.
BANKING & FINANCIAL SERVICES
AI agents for banking,
with every decision on record.
Banks run on high-volume, rules-heavy work where every decision may need to be explained later. Agents can gather evidence, apply policy and prepare the case, while your analysts approve what carries risk.
Workflows worth
handing to agents.
Each workflow names the agents involved, the point where a person decides, and what a pilot would measure.
KYC and customer onboarding
Today. Analysts collect documents, re-key data, check watchlists and chase missing information across several systems.
- An intake agent extracts and validates identity and company documents.
- A screening agent checks sanctions, PEP and adverse-media sources and records each match it considered.
- A risk agent scores the case against your policy and drafts the rationale.
Human checkpoint. An analyst approves or rejects every case the policy marks as medium or high risk, with the evidence already assembled.
A pilot would measure: Time from application to decision · Share of cases needing manual rework · Screening matches correctly cleared or escalated
Fraud and transaction monitoring
Today. Rules engines raise many alerts, and investigators spend most of their time gathering context before they can judge one.
- A triage agent enriches each alert with account history, counterparties and related alerts.
- An investigation agent drafts a narrative of what happened and why it may or may not be suspicious.
Human checkpoint. Investigators decide every alert disposition and any report to regulators; agents never close a case on their own.
A pilot would measure: Investigation time per alert · Alerts escalated that investigators confirm · Consistency of case narratives in quality review
Reconciliation and month-end close
Today. Finance teams match records across ledgers, bank statements and payment systems, then investigate breaks by hand.
- A matching agent pairs transactions and explains each break it cannot resolve.
- A follow-up agent drafts the queries to counterparties or internal teams.
Human checkpoint. Controllers approve adjustments and sign off the close; agents propose, people post.
A pilot would measure: Unmatched items at day one of close · Hours spent on break investigation · Adjustments reversed after review
Designed for how
this industry works.
Data stays in your boundary
Systems can run in your own cloud accounts and use your identity provider, with access limited to the data each step needs.
Your obligations, designed in
KYC, AML and data-protection requirements are mapped during discovery and reviewed with your compliance team; we design to them, and your team remains the authority on them.
Latest for
banking & financial services.
Updated daily by our research workflow. Papers are recent preprints; their claims are the authors’ and need evaluation.
- arXiv preprint · 28 Sept 2026Certified Multi-Source Integrity for Structured Agent Actions
Common
questions.
Can agents make credit or fraud decisions on their own?
We don't design them to. Agents assemble evidence and recommend; people decide anything with financial, legal or customer impact, and the system records who decided and why.
Will this work with our core banking and case-management systems?
Integration is scoped in discovery from your actual systems and APIs. Where direct access isn't possible, a pilot can start from exports and add integrations once the workflow proves itself.
How do you handle model risk review?
We document the workflow, data, prompts, evaluation results and known limits so your model-risk or governance team can review the system like any other model.
Other industries: Insurance · Healthcare · Retail & e-commerce · Logistics, supply chain & procurement · Any other field
A GOOD PLACE TO START
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