feat(governance): Implement automated risk evaluation engine

[adwiteeymauriya]

Description

Implement real-time risk scoring engine that evaluates sensitivity, impact, and probability of misalignment. Supports continuous assurance.

Risk Dimensions

Data Sensitivity

• Classification level (public, internal, confidential, restricted)
• PII presence detection
• Regulatory scope (GDPR, HIPAA, PCI-DSS applicability)

Decision Impact

• Reversibility (can decision be undone?)
• Affected parties (who is impacted?)
• Financial exposure (potential monetary impact)
• Reputational risk (brand/trust implications)

Operational Context

• Time pressure (urgency of decision)
• Human oversight (is human review available?)
• System confidence (model certainty scores)

Scoring Model

def compute_risk_score(context: Context) -> RiskScore:
    sensitivity = score_sensitivity(context.data)
    impact = score_impact(context.decision_type)
    operational = score_operational(context.environment)
    
    # Weighted combination with context-specific weights
    weights = get_domain_weights(context.domain)
    
    raw_score = (
        sensitivity * weights.sensitivity +
        impact * weights.impact +
        operational * weights.operational
    )
    
    # Apply risk modifiers from context
    modifiers = get_risk_modifiers(context)
    final_score = apply_modifiers(raw_score, modifiers)
    
    return RiskScore(
        value=final_score,
        level=categorize(final_score),
        factors=explain_score(sensitivity, impact, operational),
        recommended_controls=suggest_controls(final_score)
    )

API Design

POST /api/v1/governance/risk/evaluate
GET /api/v1/governance/risk/score/{entity_id}
GET /api/v1/governance/risk/trends

Acceptance Criteria

• Multi-dimensional risk scoring implemented
• Configurable weight profiles per domain
• Real-time scoring with <100ms latency
• Risk score history and trending
• Integration with guardrails (auto-adjust based on risk)
• Explainable risk factors