Fraud and risk agents
Real-time transaction screening and case investigation agents that cut false positives without missing threats.
Industry
AI for Banking & Financial Services
Modernize banking operations with AI that respects risk frameworks, regulatory expectations, and customer trust.
- 60%faster compliance reviews
- <1sfraud decisions at transaction time
- 100%of AI decisions audit-traceable
Capabilities
AI built for regulated banking
Risk, compliance, fraud detection and operations agents for banks and financial institutions.
Ops and knowledge copilots
Relationship managers and ops teams get instant, cited answers from policy, product and customer context.
Compliance automation
KYC refresh, screening, evidence collection and regulatory reporting automated with full audit trails.
Secure RAG for policy and product
Permission-aware retrieval across policies, procedures and product sheets — grounded, cited, current.
How we deliver in banking
Production AI inside your risk appetite
Model risk management, data residency, auditability — we build for the constraints first, so systems actually reach production.
Risk and fraud
Investigation agents that work cases like analysts
Agents gather account history, screen counterparties, check sanctions and draft SAR narratives — with every step logged and every conclusion linked to evidence.
- Case triage and enrichment across core systems
- Draft narratives with linked supporting evidence
- Human sign-off gates on every filing
Summarize open claims above $50k and draft escalation emails.
query_claims_db
draft_email
✓ policy_check
Found 12 claims. 3 need escalation — drafts are ready for your review.
Human approval requiredReview →
Knowledge operations
Every policy answer cited and permission-checked
Front-office and ops teams stop hunting through PDFs. Retrieval respects entitlements, answers cite the exact clause, and stale documents are flagged before they mislead.
- ACL-aware retrieval across policy and product corpora
- Clause-level citations on every answer
- Freshness monitoring on regulated content
DocsCRMWiki
↓
↓
Answer with citationsscoped to the user's permissions [1] [2]
Governance
Model risk management, engineered in
Eval evidence, challenger comparisons, decision logs and reproducibility — the artifacts your MRM and audit teams require, generated by the platform rather than assembled by hand.
- Documented eval gates for every model change
- Immutable decision and data-access logs
- Deployment inside your VPC with your IAM
Groundedness
96%
Safety
100%
Task success
93%
Tone & format
91%
CI gate passedrelease promoted to production
Use cases
Where banks deploy AI with us
Transaction fraud triage
Real-time scoring plus agent-led case investigation and SAR drafting.
KYC and onboarding
Document intake, verification and periodic refresh automated end-to-end.
Credit memo drafting
Financial spreading and first-draft memos grounded in borrower data.
Contact-center copilots
Agent assist with policy answers, account context and next-best actions.
Regulatory reporting
Evidence collection and report assembly with reviewable lineage.
Collections optimization
Outreach prioritization and compliant conversation support.
Delivery
Industry-first delivery
Every engagement is grounded in your domain — regulations, operating models, and the use cases that actually move the needle.
- Domain-ready use cases
- Compliance-aware design
- Ops & CX impact
- Reusable industry playbooks
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1
Map the domain
Identify high-ROI workflows and risk boundaries.
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2
Prioritize use cases
Score impact, feasibility and data readiness.
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3
Pilot with guardrails
Ship a controlled production pilot fast.
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4
Scale across ops
Expand to adjacent processes with shared platforms.
Three AI vendors failed our model-risk review before this. This build passed first time — the eval evidence and decision logs were exactly what our second line needed.
Works with your stack
Fits your banking stack
Core banking, payments, CRM and compliance platforms — integrated through hardened, audited connectors in your VPC.
- Temenos
- Finacle
- FIS
- Salesforce FSC
- Actimize
- Fenergo
- AWS
- Azure
- Snowflake
- Anthropic Claude
- OpenAI
- MCP
FAQ
Common questions
Can this pass our model risk management review?
That's the design goal. Every model and prompt change carries eval evidence, decisions are logged immutably, and behavior is reproducible — the documentation MRM expects is generated automatically, not written after the fact.
Where does our data go?
Nowhere outside your control. Deployments run in your VPC or on-prem, with zero-retention model endpoints or self-hosted models for sensitive flows, and data residency enforced per jurisdiction.
Which use case should a bank start with?
Usually an internal, human-in-the-loop workflow — ops copilots, KYC document processing, case investigation assist. High value, controllable risk, and it builds the governance muscle before customer-facing AI.
Do you work with our existing fraud and compliance vendors?
Yes. We integrate with and augment platforms like Actimize and Fenergo rather than replacing them — AI agents work the queues those systems create.
Next step
Ship AI your regulators can live with
Tell us the workflow and the constraint — we'll design the system that satisfies both.