46+ financial services skills with validation
10+ jurisdictions: US, Canada, EU, UK, Australia, Singapore, Brazil
Zero training on your data
Isolated per-project workspaces

Regulatory Coverage

Choose your regulatory domain. Start drafting in minutes.

Each category groups domain-specific skills with reference material and validation tools for production-ready financial compliance documents.

Canadian Securities (CSA)

6 skills 20+ validation checks

NI 51-102 continuous disclosure: MD&A, Annual Information Form, Business Acquisition Report, Material Change Report, Information Circular, and NI 41-101 prospectus for offerings.

  • SEDAR+ filing structure
  • NI 51-102 and NI 41-101 compliance
  • Cross-reference validation

Banking Regulation

12 skills 35+ validation checks

Prudential frameworks across jurisdictions: Canadian OSFI B-10 third-party risk (4 skills) and E-13 regulatory compliance (5 skills), Brazilian BACEN/CMN prudential reporting and VASP compliance, Singapore MAS TRM.

  • OSFI, BACEN, MAS coverage
  • Third-party risk lifecycle (B-10)
  • Basel III capital adequacy reporting

Insurance & Consumer Protection

5 skills 20+ validation checks

EU Solvency II SFCR (Pillar 3) reporting, UK FCA Consumer Duty fair value assessments, Australian Statement of Advice, and insurance policy analysis tools.

  • Solvency II QRT consistency checks
  • FCA PRIN 2A fair value alignment
  • Policy coverage gap analysis

Payment Security & Controls

4 skills 20+ validation checks

PCI DSS v4.0 Report on Compliance and SAQ scope documentation, SOX Section 404 ICFR control narratives (COSO/PCAOB), and CFPB UDAAP consumer complaint compliance.

  • PCI DSS v4.0 ROC structure
  • COSO 2013 / PCAOB AS 2201 alignment
  • UDAAP fair lending checks

How it compares

Why financial services teams choose Rakenne over generic AI

Regulatory documents demand precision, jurisdiction awareness, and traceable structure. Generic AI gives you none of that.

Traditional Tools
Generic AI (ChatGPT)
Regulatory citation accuracy
Traditional Tools Manual lookup of statutes and rules
Generic AI (ChatGPT) Hallucinated or outdated references
Multi-jurisdiction coverage
Traditional Tools One tool per jurisdiction or market
Generic AI (ChatGPT) No jurisdiction awareness
Filing structure compliance
Traditional Tools Rigid forms — hard to adapt
Generic AI (ChatGPT) No format or section enforcement
Cross-reference integrity
Traditional Tools Manual spreadsheet tracking
Generic AI (ChatGPT) No cross-reference linking
Audit trail
Traditional Tools External documentation required
Generic AI (ChatGPT) No history — ephemeral chat
Regulatory update cadence
Traditional Tools Vendor-dependent release cycles
Generic AI (ChatGPT) Frozen at training cutoff

See it in action

The agent drafts, validates, and self-corrects

Skills include automated checks that run against the output. When something fails, the agent fixes it — no manual back-and-forth.

AML transaction monitoring with red-flag validation

In this AML/BSA example, the agent uses industry-specific red-flag libraries and validates sanctions screening frequencies against the declared risk appetite — all within the same conversation.

Rakenne Agent
You
Medium risk appetite. Our bank has retail and crypto custody business lines.
Agent
Documented. Let me pull industry-specific transaction monitoring indicators for both business lines.
Agent
Running red_flag_library with banking and crypto parameters…
Agent
Got 16 indicators across both industries (BK-01 through BK-10 for banking, CR-01 through CR-06 for crypto). I’ve organized them by category in the monitoring chapter.
Agent
Running sanctions_list_frequency_check with risk appetite medium…
Agent
All checks passed. Sanctions screening: real-time ✓ | PEP rescreening: semi-annual ✓ | Adverse media: quarterly ✓ — all meet or exceed expectations for medium risk appetite.

Specialized skills

Beyond the main categories — tax, advisory, and market-specific compliance

The financial services skill library includes specialized tools for niche regulatory domains and jurisdictions.

Transfer Pricing

  • OECD Local File
  • OECD Master File

Market-Specific

  • WpHG Suitability (Germany)
  • CNMV Prospectus Validator (Spain)
  • BCB VASP Compliance (Brazil)

Analysis & Advisory

  • Financial Data Analysis
  • Fintech PRD
  • Australian SoA (Wealth)

Go deeper

Related resources and best practices

Guides and articles relevant to financial services compliance workflows.

FAQ

Common questions from financial services teams

Yes. Each skill references version-pinned regulatory material — for example Reg S-K, GAAP codification topics (ASC 260, 820, 850, 855), NI 51-102, and NI 41-101. Reference files are bundled with each skill, so the agent works against a known regulatory baseline rather than general training data.

Both. Individual skills cover specific sections — MD&A, Risk Factors (Item 1A), footnotes, proxy statements — so you can draft them independently or chain them together in a single workspace. Earlier sections inform later ones: the agent reads prior artifacts for cross-reference consistency.

The skill library includes separate AML skills per jurisdiction: AML/BSA for US FinCEN-regulated entities, AML/CTF for AUSTRAC-regulated entities in Australia, Nordic AML/CFT per Joint ESA Guidelines and AMLD6, and GwG for German non-financial sector. Each skill carries jurisdiction-specific references, red-flag libraries, and filing requirements.

Skills produce structured documents that follow the expected section layout for each filing type (e.g., Reg S-K items for SEC, NI 51-102 parts for CSA, five BSA pillars for AML). You’ll still format for your specific submission channel, but the structure and content requirements are validated before you get the draft.

Absolutely. A single workspace can use skills from multiple domains — for example, combine SOX ICFR with ISO 27001 for IT controls, or pair AML/BSA with GDPR for privacy-sensitive customer due diligence. Skills read each other’s outputs, so cross-framework references stay consistent.

No. Your prompts, documents, and outputs are processed only to deliver the service and are never used to train foundation models. Each project gets an isolated workspace — no cross-tenant or cross-project access. Data handling and subprocessors are described in our Privacy Policy.

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