Infrastructure for Independence & Conflict Checking

Independence and conflict checking requires formally codified regulatory rules — SEC, PCAOB, AICPA independence standards — mapped to specific relationship types (financial interest, family member employment, prior service). These cannot be narrative policy documents interpreted by humans; the AI must apply explicit logical rules: IF Consultant.FinancialInterest EXISTS IN Client.SecuritiesIssuers AND EngagementType = Audit THEN IndependenceViolation = TRUE. Regulatory specificity demands formal rule codification (L4) rather than documented guidance that leaves AI interpretation open.

Conflict checking requires systematic capture of consultant financial interests (investment disclosures), client relationship databases, engagement histories, and staffing assignments. Professional services firms require annual independence disclosure forms as regulatory obligations — these template-driven submissions create systematic records of financial interests and family relationships. Engagement acceptance questionnaires capture new client relationships systematically. This required annual capture cycle provides the AI with current relationship data against which to check new engagements.

Independence checking requires consistent schema linking consultants to their financial interests, the client entities they're related to, and engagement records. Risk frameworks define relationship categories (financial interest, employment, family) and engagement types (audit, advisory, tax) with consistent fields across records. The AI can query 'all consultants assigned to Engagement X who have disclosed financial interests in Client X's subsidiaries' because the schema has defined entity types and linkage fields. L3 consistent schema supports this cross-entity querying without requiring full formal ontology.

Automated independence checking requires API access to the independence disclosure database, CRM client entity hierarchy, engagement staffing system, and regulatory rules repository. Risk management systems in professional services have web interfaces and search capabilities, and CRM integrations with risk databases provide client entity data. The AI must query 'who is staffed on this engagement' and 'what financial interests has each person disclosed' simultaneously — requiring API access to staffing and independence systems at L3.

Independence rules and conflict databases must update when regulatory standards change and when new relationship disclosures are filed. Event-triggered maintenance ensures that when a consultant updates their financial interest disclosure, the conflict checking system immediately re-evaluates their current engagements. Regulatory independence rule changes — new SEC guidance, updated PCAOB standards — must propagate to the checking engine as they are issued, not at the next quarterly review cycle, to avoid ongoing violations.

Independence and conflict checking requires integration across independence disclosure systems, CRM client hierarchy databases, engagement staffing platforms, and regulatory reference libraries. These systems must share context: when a new engagement is created in PSA, the conflict checker must query CRM for the client's corporate family tree and cross-reference all staffed consultants' disclosures simultaneously. API-based connections across these systems (L3) enable automated screening at engagement creation, replacing manual cross-system lookups by risk staff.