Trusted by Banks, Fintechs, Wealth Firms & Insurance Carriers
Multi-Agent Banking, Lending, Markets & Compliance Crews on LangGraph, CrewAI & Anthropic Claude 3.5
DreamzTech is an AWS, Google Cloud and Microsoft Solutions Partner with 100+ AI agent deployments across 15 countries — including a $1.2B-revenue manufacturer where a six-agent finance automation platform cut month-end close from 11 to 3 days, saved $850K annually and produced zero SOX 404 ITGC findings. The same engineering pattern powers our banking + fintech AI deployments across KYC/AML, fraud, credit, treasury and regulatory reporting.
Generic banking chatbots answer FAQs and route everything else to the contact centre. Point AI tools (fraud-only, KYC-only, AP-only) solve narrow problems but leave the bank to stitch them together. AI agents for finance sit between the two — reasoning over your policy, AML thresholds, credit scorecards and reg-reporting rules, calling FIS / Fiserv / Temenos / Murex / Bloomberg APIs to actually execute (open accounts, flag transactions, approve credit, file reports), and routing only edge cases to humans. See our AI agent development hub.
Quick Answer: AI agents for finance are tool-using software systems built on foundation-model LLMs (Anthropic Claude 3.5 Sonnet, OpenAI GPT-4o, Llama 3.3, plus finance-tuned models like BloombergGPT and FinBERT) that automate banking + capital-markets workflows: KYC/AML review, transaction-fraud detection, credit underwriting, trade reconciliation, treasury cash forecasting, regulatory reporting (CCAR, DFAST, FR Y-9C, MiFID II), claims triage, customer onboarding and wealth-advisor copilots. They invoke FIS, Fiserv, Jack Henry, Temenos, Mambu, Finastra, Salesforce Financial Services Cloud, Murex, Calypso, Bloomberg AIM, NICE Actimize, FICO, Moody’s CreditView, Plaid and 100+ fintech APIs through Model Context Protocol — with SOX-clean audit trails, FFIEC + NYDFS Cybersecurity controls, PCI-DSS tokenisation and human-in-the-loop on every reportable decision. Industry forecast: 44% of finance teams adopt agentic AI in 2026; 80% of banks integrate AI agents into core ops; 30% reduction in manual processing + compliance costs (sources: Citizens Bank Insights 2026, Finastra 2026, Accenture Banking).
DreamzTech builds finance agents from $35,000 (single-task KYC review agent on LangChain + Plaid + Onfido) up to $400,000+ (full multi-agent banking platform spanning KYC + fraud + underwriting + reg-reporting on LangGraph + CrewAI with FIS / Fiserv core + NICE Actimize + FICO + Bloomberg + 24/7 SRE) — SOX-clean, FFIEC + NYDFS-aligned, SOC 2 Type II + PCI-DSS.
Reviewed by the DreamzTech AI Practice — updated 2026-05-15. Includes hands-on guidance from a $1.2B-revenue specialty-chemicals manufacturer finance deployment (11→3 day close, $850K saved, zero SOX 404 findings) and multiple regional-bank + fintech engagements covering KYC/AML, fraud, lending and treasury.
Six tightly-scoped tracks for AI-driven finance — strategy + risk-model governance, KYC/AML + fraud, credit underwriting, treasury + FP&A, core-banking + payments integration, and managed FFIEC-aligned operations.
Use-case discovery (KYC, fraud, credit, treasury, reg-reporting), SR 11-7 / OCC 2011-12 model-risk-management scoping, NIST AI RMF + SOX 404 readiness, FFIEC + NYDFS Cybersecurity gap analysis.
Production agents that automate KYC reviews, sanctions screening (OFAC, EU, UN), CDD/EDD, adverse-media monitoring, transaction-fraud detection and SAR/CTR filing on LangGraph + Claude 3.5 + NICE Actimize + ComplyAdvantage + LexisNexis Bridger.
Multi-agent crews — Document Reviewer, Cash-Flow Analyst, Credit Scorer, Risk Approver, Reviewer — that decision consumer + SMB + commercial loans on CrewAI + Claude 3.5 + FICO Decision Studio + Moody's + Plaid bank-data + Reg B / ECOA fair-lending guardrails.
Production agents for cash-position forecasting, intraday-liquidity management, FX exposure, FP&A variance analysis, trade reconciliation, position-keeping, NAV strikes and regulatory reporting (CCAR, DFAST, FR Y-9C, MiFID II, EMIR).
Native integration with FIS Profile, Fiserv DNA, Jack Henry SilverLake, Temenos Transact, Mambu, Finastra Fusion, Salesforce Financial Services Cloud, Murex, Calypso, Bloomberg AIM, Charles River, Plaid, Stripe, Adyen, Marqeta and Galileo.
24/7 production observability, prompt versioning, model-risk-management lifecycle per SR 11-7, OCC + FDIC + FRB audit-evidence packets, quarterly model upgrades and named SRE with banking-experienced engineers.
AI finance agents are the right move when KYC backlog stretches past SLA, fraud-alert volume swamps analysts, credit decisioning bottlenecks new originations, reg-reporting absorbs senior-staff time, or treasury cash visibility breaks at month-end.
A production AI finance agent platform delivers measurable ROI within 90 days. DreamzTech deployments and broader industry benchmarks show 30% reduction in manual processing + compliance costs, 50–70% KYC + CDD automation, 3–4× faster credit decisioning, 40–60% fewer fraud false-positives and seven-figure annual savings + revenue lift — with SOX-clean audit trails, SR 11-7 model-risk evidence and FFIEC + NYDFS Cybersecurity controls ready for OCC / FDIC / FRB / state-DFS review.
See real production numbers in our AI Finance Automation case study (11→3 day close · $850K saved · zero SOX findings) and the global-bank IT service desk case study (18K tickets/month auto-resolved, $1.8M saved).
Every production AI finance agent we build follows a six-layer reference architecture covering perception, reasoning, memory, action, guardrails and observability — the blueprint that lets finance agents scale from one KYC intent to enterprise-wide banking automation while staying SOX + FFIEC + NYDFS + SR 11-7 audit-ready.
Ingest events from core banking (FIS / Fiserv / Temenos), capital-markets systems (Murex / Calypso / Bloomberg), payment rails (Plaid / Stripe / SWIFT), CRM events and customer chat + voice — with PII / NPI detection, sanctions-screening priority scoring and tokenisation at the door.
Foundation-model LLM (Claude 3.5 Sonnet, GPT-4o, Llama 3.3, finance-tuned BloombergGPT / FinBERT) plans the decision, retrieves your policy + AML thresholds + credit scorecards + reg-reporting templates, routes between Intake → Risk Reasoner → Resolver → Approver → Supervisor specialist agents.
Short-term case scratchpad, long-term vector memory of every prior alert, case and decision (Pinecone, Weaviate, OpenSearch, pgvector), and customer-360 / counterparty-360 episodic memory stitched from core banking + CRM + transaction + market data.
Tool-use, function calling and Model Context Protocol — agents invoke FIS / Fiserv / Temenos / Murex / Calypso / Bloomberg / FICO / NICE Actimize / Plaid / Stripe to open accounts, place trades, post journals, file SAR / CTR, approve credit, draft adverse-action notices and file reg reports.
SOX 404 dollar-cap enforcement, SR 11-7 model-risk-management gate, SoD checks (4-eyes / 6-eyes), PCI-DSS tokenisation of card data, Reg-B / ECOA fair-lending checks, OFAC + EU + UN sanctions screening, PII / NPI redaction and human-in-the-loop on every reportable decision.
LangSmith / Langfuse / Arize tracing of every decision, model-risk dashboards aligned to SR 11-7, fair-lending bias-drift detection, OCC / FDIC / FRB / NYDFS audit-evidence export and immutable audit log for SOX 404 + Basel III walkthroughs.
Buyers compare DreamzTech's custom AI finance agents with point-AI tools (NICE Actimize for fraud, FICO for credit), big-bank in-house builds (JP Morgan COIN, BofA Erica) and SaaS platforms (Hummingbird for compliance, AlphaSense for research). This section makes the trade-offs crisp.
| Capability | Basic OCR Tools | Off The Shelf IDP | DreamzTech AI IDP |
|---|---|---|---|
| Document Understanding | Text extraction only | Predefined templates and workflows | Custom extraction, classification, validation and foundation-model LLMs based understanding |
| Workflow Fit | You build workflows separately | Limited to product configuration | Designed around your exact business process and approval flow |
| Integration | Manual export or API work | Connector dependent | Custom integration with ERP, CRM, accounting, databases and BI systems |
| Ownership | Tool dependent | Vendor platform dependency | You own the application, workflow and source code |
| Best For | Simple text extraction | Generic document automation | Enterprise teams needing secure, customized and integrated document processing |
Our finance-agent depth spans 8 BFSI sub-verticals — from regional banks running KYC + fraud automation to capital-markets desks reconciling Murex trades and insurance carriers automating claims triage.
KYC + CDD/EDD, fraud detection, account opening, dispute resolution + chargeback agents — FIS Profile + Fiserv DNA + Jack Henry SilverLake + Plaid + NICE Actimize.
Trade reconciliation, position-keeping, NAV strike, research-summarisation, compliance surveillance — Murex + Calypso + Bloomberg AIM + Charles River + AlphaSense.
Consumer + SMB + commercial credit underwriting, doc-review, cash-flow analysis, decisioning, adverse-action drafting — FICO + Plaid + Ocrolus + Blend + Encompass.
Wealth-advisor copilots, KYS suitability, portfolio summarisation, client-onboarding + RFP-response agents — Salesforce FSC + eMoney + Envestnet + Addepar.
Underwriting agents, claims triage, SIU fraud detection, statutory reporting agents — Guidewire + Duck Creek + Majesco + ACORD with SIU-grade audit trails.
BaaS partner-bank compliance, embedded-credit underwriting, real-time fraud, customer-support agents — Marqeta + Galileo + Cross River + Synapse alternatives.
Cash forecasting, intraday liquidity, FX exposure, FP&A variance + auto-narrative, board-deck drafter — Kyriba + GTreasury + Anaplan + Workday Adaptive.
AWS GovCloud + Azure Government FedRAMP-aligned reg-reporting, treasury, grant-accounting + fraud-detection agents — Workday Public Sector + Tyler + FedRAMP overlay.
Four real options exist for AI in finance. The right answer is usually a hybrid — point-AI for narrow workflows (NICE for fraud, FICO for credit), SaaS for non-differentiating compliance (Hummingbird, ComplyAdvantage), in-house build only for the top-5 banks, and DreamzTech custom builds for everyone else who needs multi-system orchestration. Pair with our finance back-office automation for accounting + close.
Bring your toughest finance workflow — KYC backlog at 30 days, fraud false-positives at 12%, manual reg-reporting absorbing senior staff, trade-break volume on Murex — and a senior finance AI architect will walk you through the recommended pattern (LangGraph + finance-tuned LLM), an accuracy benchmark on representative cases and a fixed-scope budget range. Live, free, 30 minutes.
AWS, Google Cloud and Microsoft Solutions Partner. 100+ AI agent deployments — including a $1.2B-revenue manufacturer finance platform (11→3 day close, $850K saved, zero SOX) and a global retail bank IT service desk (18K tickets/month auto-resolved, $1.8M saved).
Tell us about your core-banking stack (FIS / Fiserv / Temenos / Mambu), monthly KYC + alert + decision volume, current SLA + false-positive rates and which workflow to automate first. Senior architect responds within 1 business day with reference architecture, fixed-scope estimate, FFIEC + NYDFS + SR 11-7 plan and next steps.
Production AI finance agents DreamzTech has shipped — $1.2B-revenue manufacturer finance automation (11→3 day close), global-bank multi-agent IT operations and Series-D SaaS multi-agent demand-gen — on LangGraph, CrewAI, Temporal and AutoGen with deep SAP, Oracle, NetSuite and Salesforce integration.
A $1.2B-revenue specialty-chemicals manufacturer replaced 11-day month-end close with a DreamzTech-built six-agent finance automation platform — LangGraph + Temporal orchestration + Anthropic Claude 3.5 Sonnet + native SAP S/4HANA + Oracle EBS + NetSuite integration. Close cut to 3 days, $850K annualised savings, zero SOX 404 ITGC findings. The same multi-agent engineering pattern powers our banking + lending deployments.
A global retail bank (85,000 employees) automated its IT service desk with a DreamzTech hierarchical multi-agent platform — LangGraph + GPT-4o + AutoGen + ServiceNow. 68% L1 auto-resolution, 73% MTTR cut, $1.8M saved, zero SOX 404 ITGC findings — proof point for banking-grade ITGC + SOX-clean change management.
A Series-D B2B SaaS deployed a DreamzTech multi-agent crew — CrewAI + Claude 3.5 + Apollo / ZoomInfo / 6sense + Salesforce + HubSpot. 4.2× SQL conversion lift, $14.2M Q1 pipeline, 67% productivity gain. The same Researcher → Qualifier → Writer → Reviewer crew design powers our lending-onboarding + wealth-prospecting agents.
AWS, Google Cloud and Microsoft Solutions Partner. 100+ AI agent deployments including SOX-clean finance automation and 18K-ticket/month global-bank IT platform — both with zero ITGC findings on external audit.
Structured four-phase delivery for SOX-clean, FFIEC + NYDFS + SR 11-7-aligned AI finance automation — from use-case discovery to production cutover, model-risk validation and ongoing audit-evidence packaging.
We study your document types, processing workflows, error rates and integration requirements; we analyse 50–100 of your real documents to set AI model requirements and accuracy targets.
Cloud-certified engineers pick the right AI mix — AI document extraction for forms, AI language services for entities, foundation-model LLMs for understanding, human review for low-confidence pages — on AWS, Azure or Google Cloud under the chosen cloud's Well-Architected Framework.
We annotate historical documents, fine-tune custom-template and custom-neural models on your specific layouts and terminology, and iteratively validate accuracy against your team's manual processing results.
We build the complete cloud-hosted application — document upload portal, extraction review dashboard, exception-handling workflows, approval routing on workflow orchestration and reporting on your BI platform.
AWS, Google Cloud and Microsoft Solutions Partner-grade finance-agent platform — production-ready in 6–14 weeks. SR 11-7 model-risk-management lifecycle + immutable audit trail + bias-audit per Reg B / ECOA + PCI-DSS tokenisation.
Every AI agent we deploy in a bank / fintech / insurance carrier goes through the full SR 11-7 model-risk lifecycle: model identification, conceptual-soundness review, ongoing monitoring with quarterly re-validation by an independent model-review board, model inventory + tier, governance + policies, and effective challenge documented in writing. We integrate with your existing model-risk-management platform (MRM-IQ, ModelOp, Domino Data Lab, Datatron) or stand one up using LangSmith + custom MRM workflows. OCC, FRB and FDIC audit-tested across multiple regional-bank deployments.
Granular RBAC limits which agent can post to which sub-ledger, what dollar threshold triggers 4-eyes (two human approvers) or 6-eyes (three, for high-risk or above-materiality), which AML alert escalates to BSA officer — backed by enterprise SSO (Okta, Azure AD, Ping). Every alert, decision, journal, SAR, trade and adverse-action notice logged with immutable audit trail for SOX 404, FFIEC, NYDFS 23 NYCRR 500.16, Basel III, MiFID II + EMIR walkthroughs.
Our finance-AI platforms run on SOC 2 Type II-attested infrastructure (AWS, Azure, Google Cloud — Financial Services lens) with ISO 27001 / 27018 controls. PCI-DSS-aligned tokenisation for card data (Stripe / Adyen / Worldpay token vault) — card numbers never reach the LLM. Annual third-party pen testing, secure SDLC, customer-managed KMS keys.
FFIEC IT Examination Handbook alignment, NYDFS 23 NYCRR Part 500.16 (Incident Response + Recovery) + Part 500.15 (Encryption) + Part 500.17 (Multi-Factor Authentication) controls baked into every deployment. GLBA Safeguards Rule for non-public personal information (NPI). Reg-CC + Reg-E + Reg-Z + Reg-DD policy awareness embedded in agent reasoning. Annual third-party HIPAA-Privacy + NYDFS gap assessments.
Every credit + lending workflow goes through a Reg B / ECOA / HMDA-aligned bias-audit harness: disparate-impact ratio across protected classes (race, gender, age, ethnicity, marital status, public-assistance), 4/5ths rule, statistical fairness metrics. Adverse-action notices auto-drafted with FCRA-required reason codes (top 4 + counter-factual explanation). Pre-deployment review documented for legal + compliance sign-off.
Deploy on your cloud tenant with private OpenAI on Azure, Anthropic Claude on Amazon Bedrock, or self-hosted Llama 3.3 / Mistral / BloombergGPT / FinBERT on your Kubernetes — so NPI + customer data never leaves your security perimeter. Zero data retention agreements with all model vendors. Full sovereign / on-prem deployment available for FedRAMP Moderate / High customers (state-Medicaid, GSE-backed lenders).
Info-sec foundation
Banking-grade audit
23 NYCRR 500 Part 500.16
Model risk management
Card data + customer privacy
Fair-lending review
AWS / Azure / Google Cloud Well-Architected (Financial Services lens) reviewed at every milestone. SOX-clean change-management + SR 11-7 model lifecycle on every layer.
Real feedback from CFOs, CROs, Heads of Compliance, Heads of Credit and Treasury leaders running production AI finance agents built by DreamzTech on LangGraph, CrewAI and AutoGen with SR 11-7 model-risk lifecycle.
Every AI finance project at DreamzTech is built on a SOX-clean, FFIEC + NYDFS + SR 11-7-aligned production stack. LangGraph + CrewAI handle multi-agent banking orchestration; Anthropic Claude, OpenAI GPT-4o, Llama 3.3, BloombergGPT and FinBERT handle reasoning; Model Context Protocol bridges FIS, Fiserv, Temenos, Murex, Bloomberg, NICE Actimize, FICO and Plaid. Explore our end-to-end implementation and managed AI agent services.
Behind the agent layer: AWS Lambda / Azure Functions, Amazon Bedrock / Azure OpenAI / GCP Vertex private LLM hosting, Pinecone / Weaviate / OpenSearch for PII-redacted vector memory, and LangSmith / Langfuse / Arize for SR 11-7-aligned observability — all inside your cloud tenant with customer-managed KMS keys + immutable audit logs ready for OCC / FDIC / FRB / NYDFS review.
Choose the engagement model that fits your finance-AI build — senior-led dedicated teams to fixed-price MVPs, all SR 11-7 + FFIEC scoped.
Full-time team of AI agent engineers, prompt engineers, finance-process specialists, compliance leads and SRE — typically 4–8 engineers — embedded for 6–18 months of build, model-risk validation and operations.
Ideal for well-defined finance use cases — KYC + CDD automation, fraud-alert triage, SMB credit underwriting, treasury cash forecasting — delivered as a fixed-scope MVP in 6–14 weeks on LangGraph + Anthropic Claude 3.5.
Add senior AI agent engineers + finance interop specialists (FIS-certified, Murex-certified, Bloomberg-certified) to your team — managed by DreamzTech, reporting into your tech leadership. 1–3 month minimum.
Flexibility for evolving finance-AI requirements — exploratory builds, agent R&D, prompt sprints, integration spikes. Transparent monthly invoicing.
Multi-agent LangGraph + CrewAI banking orchestration, foundation-model LLMs (Claude 3.5, GPT-4o, BloombergGPT, FinBERT), PII-segmented vector memory, Model Context Protocol and FIS / Fiserv / Temenos / Murex / Bloomberg / NICE Actimize / FICO integration — assembled into a production finance-AI platform in 6–14 weeks.
Three real options exist for AI in finance: point-AI SaaS (NICE Actimize for fraud, FICO for credit, ComplyAdvantage for sanctions, Hummingbird for compliance, AlphaSense for research, Vic.ai + Tipalti for AP), hyperscaler agent APIs (Amazon Bedrock Agents, Azure AI Agents — both with banking BAAs), or commission a custom build. Each is right for different problems.
| Dimension | SaaS IDP | Hyperscaler APIs | Custom Build |
|---|---|---|---|
| Cost model | $3K–$30K/month + per-document fees | $0.001–$0.05 per page + dev cost | $50K–$400K project, no per-doc fees |
| Time to first production | Weeks to months (depending on document templates) | Days for prototype; 2–4 months for production | 3–9 months end-to-end |
| Customisation depth | Limited to vendor’s template + extraction patterns | API-level flexibility; no UI, workflow, or business-logic layer | Anything technically possible — full UI, workflow, business rules, IP ownership |
| Compliance posture | Vendor BAA / DPA; sub-processor chain often opaque | Cloud-provider BAA only; you build the rest | Full BAA chain validated end-to-end + your audit logs |
| Integration with your stack | Pre-built connectors for major ERPs / EHRs; uneven for niche systems | You build all integrations | Native integrations to your specific ERP, EHR, CRM, claims-management system |
| Accuracy on your documents | Vendor-trained models; 70–90% out-of-the-box on standard formats | Generic models; 60–85% on standard formats; lower on custom layouts | Custom-tuned to your documents; 90–98% achievable with proper training |
| MLOps + drift handling | Vendor-managed; you have limited visibility | You build your own MLOps | DreamzTech designs MLOps in from day one |
| Best for | Standard documents (invoices, receipts, generic forms) at modest volume | Engineering teams comfortable owning the IDP build end-to-end | Specialty documents, regulated workloads (HIPAA / GDPR), enterprise volume, multi-system integration, or where document accuracy is a competitive moat |
When DreamzTech is the right call: regulated bank + insurance workflows that span multiple cores (FIS + Fiserv + Murex + Bloomberg + Salesforce + Plaid) where SaaS point-AI cannot reach; SR 11-7 / OCC 2011-12 model-risk-management workflows needing full lifecycle documentation; multi-state Medicaid / public-sector finance needing FedRAMP-aligned sovereign deployment; or specialty workflows (CECL early-warning, Reg-B adverse-action drafting, OFAC sanctions screening at scale) where point-AI vendors only cover the long-tail partially. We build on hyperscaler-native too when that fits — and tell you up front.
Common questions from CFOs, CROs, Heads of Compliance, Heads of Credit, CTOs and Treasury leaders evaluating AI agents for finance.
AI agents for finance are tool-using software systems built on foundation-model LLMs (Anthropic Claude 3.5 Sonnet, OpenAI GPT-4o, Llama 3.3, plus finance-tuned BloombergGPT and FinBERT) that automate banking, capital-markets, lending, wealth and insurance workflows: KYC/AML review, transaction-fraud detection, credit underwriting, trade reconciliation, treasury cash forecasting, FP&A variance analysis, regulatory reporting (CCAR, DFAST, FR Y-9C, MiFID II, EMIR), claims triage and customer onboarding. They call FIS, Fiserv, Jack Henry, Temenos, Mambu, Finastra, Salesforce Financial Services Cloud, Murex, Calypso, Bloomberg AIM, NICE Actimize, FICO, Plaid, Stripe and 100+ fintech APIs via Model Context Protocol — with SOX-clean audit trails and human-in-the-loop on every reportable decision. Industry forecast: 44% of finance teams adopt agentic AI in 2026; 80% of banks integrate AI agents into core operations. See our 11→3-day-close case study.
NICE Actimize, FICO Decision Studio, ComplyAdvantage, Hummingbird, AlphaSense and Vic.ai are specialised point-AI tools — each solves one workflow well (NICE for fraud, FICO for credit scoring, Hummingbird for SAR drafting). They do not orchestrate across systems or reason over your bank-specific policy. AI agents from DreamzTech sit above those tools, calling them as best-of-breed components while adding the planning + reasoning + cross-system orchestration that turns isolated AI features into end-to-end automation. Best practice is to keep your point-AI tools and add an agent layer that orchestrates them with full audit trail. Compare with our finance back-office automation solution.
Native integration with core banking: FIS Profile, Fiserv DNA + Premier, Jack Henry SilverLake, Temenos Transact, Mambu, Finastra Fusion. Capital markets: Murex, Calypso, Bloomberg AIM, Charles River, BlackRock Aladdin. CRM: Salesforce Financial Services Cloud, Microsoft Dynamics 365 Finance. Payments: Plaid, Stripe, Adyen, Marqeta, Galileo, Cross River, Worldpay. Risk + compliance: NICE Actimize, Verafin, Featurespace, FICO, Moody’s CreditView, ComplyAdvantage, LexisNexis Bridger. Insurance: Guidewire, Duck Creek, Majesco, ACORD. Connectors via REST, GraphQL, FIX 4.4/5.0, ISO 20022, SWIFT MX, FpML and Model Context Protocol — all with SSO + RBAC + 4-eyes/6-eyes approval. See our AI agent integration services.
A focused single-workflow agent MVP (KYC review on Plaid + Onfido, or fraud-alert triage on NICE Actimize) ships in 6–10 weeks. A multi-agent banking platform (KYC + fraud + credit, 4–5 specialised agents, FIS / Fiserv integration, SR 11-7 model-risk evidence) ships in 10–14 weeks. Enterprise bank platform with core-banking + cap-markets + risk + reg-reporting + multi-state regulatory + 24/7 banking-grade SRE — 14–24 weeks. All timelines include SR 11-7 model-risk-management walkthrough, FFIEC + NYDFS gap, accuracy validation against 1,000–5,000 historical cases and pilot rollout with effective-challenge sign-off before broad production.
A focused single-workflow finance agent MVP starts at $35,000–$60,000 (LangChain + Claude / GPT-4o, single banking or fintech tool, 6–10 weeks). A multi-agent finance platform runs $120,000–$250,000 (LangGraph + CrewAI, 4–5 specialist agents, vector memory, FIS / Fiserv / NICE Actimize / FICO / Plaid integration, SR 11-7 model-risk lifecycle, 10–14 weeks). Enterprise bank platforms with multi-core, multi-state, FedRAMP / NYDFS, SR 11-7 model-review-board lifecycle and 24/7 SRE run $300,000–$600,000+. Most clients break even within 4–9 months on KYC + fraud + credit-decisioning labour reduction alone.
Every AI agent goes through the full SR 11-7 / OCC 2011-12 lifecycle: model identification + inventory + tier classification, conceptual-soundness review by an independent model-validation team, ongoing monitoring with quarterly re-validation, effective challenge documented, model-risk-policy alignment + governance, model-tier-based controls (Tier-1 high-impact models require full validation + annual independent review). We integrate with your existing MRM platform (MRM-IQ, ModelOp, Domino, Datatron) or stand up our LangSmith + custom MRM workflow. OCC, FRB and FDIC audit-tested across multiple regional-bank deployments with zero MRM findings to date.
Every credit + lending agent goes through a Reg B / ECOA / HMDA-aligned bias-audit harness before production: disparate-impact ratio measured across protected classes (race, gender, age, ethnicity, marital status, source of income), 4/5ths rule, statistical-parity and equal-opportunity metrics. Adverse-action notices auto-drafted with FCRA top-4-reason-codes plus a counterfactual explanation (per the proposed CFPB / OCC guidance). Pre-deployment review documented for legal + compliance sign-off; continuous bias-drift monitoring in production with alerting if any protected class drops below the 4/5ths threshold.
Data stays in your cloud tenant. We deploy on AWS, Azure or Google Cloud in your account, with private model endpoints (Claude on Bedrock, OpenAI on Azure, or self-hosted Llama 3.3 / BloombergGPT / FinBERT on Kubernetes). Zero data retention agreements with all model vendors. NPI + PII redaction (Microsoft Presidio + custom financial NER) on every inbound + outbound message. Card data tokenised per PCI-DSS — never reaches the LLM. SOC 2 Type II + ISO 27001 + SOX 404 + FFIEC + NYDFS Cybersecurity (23 NYCRR 500) + GLBA Safeguards Rule. Customer-managed KMS keys. Full audit logs for SOX, FFIEC, OCC, FDIC, FRB, NYDFS + Basel III. Sovereign / on-prem deployment available for FedRAMP Moderate / High customers. See our AI agent development hub.
