FUIP Governance Roadmap

PG table fuip.activation_gates (11 cols, UNIQUE tenant_id+gate_key), PostgreSQLActivationGateRepository wired in DI

Activate/suspend/list/check operations via ActivationGateService (5 methods) + AdminGovernanceGateAction endpoint

Prerequisites checked before gate activation, RuntimeException thrown on unmet prerequisites

Gate status cached at fuip:gate:{t}:{gk} with 300s TTL, RedisGovernanceCache integration

Gate state changes produce audit events via FuipAuditIntegrationService with high severity for activate/suspend

PG table fuip.subject_consent_states (10 cols, UNIQUE tenant_id+subject_id), PostgreSQLConsentRepository with jsonb @> operator

isConsentedFor() with Redis-first lookup + PG fallback, recordConsent/revokeAll lifecycle methods

Redis key fuip:consent:{t}:{s} (600s TTL) invalidated on recordConsent and revokeAll operations

Consent changes audited via FuipAuditIntegrationService + Kafka produce to fuip.governance.audit topic (#29)

All 7 ConsentPurpose enum cases handled: ANALYTICS, PERSONALIZATION, EXPERIMENTATION, COGNITIVE_PROCESSING, CROSS_DEVICE_TRACKING, ADVERTISING, SAFETY

PG table fuip.retention_classes (10 cols, UNIQUE tenant_id+data_category) + 6 RetentionTier enum levels: EPHEMERAL through PERMANENT

PG table fuip.telemetry_field_policies (9 cols) with allowlist/denylist support, GovernancePolicyRepository (6 methods)

Submit/execute/status/inventory lifecycle via PurgeOrchestrationService, PG table fuip.purge_requests (11 cols)

Per-store execution log tracking purge across PG, ClickHouse, Redis, and Kafka stores

Purge lifecycle events produced to fuip.governance.purge Kafka topic (#28) for downstream consumers

FuipAuditIntegrationService with nullable AuditWriter injection, 3 public methods: auditRegistryMutation, auditGovernanceOperation, auditPrivilegedAccess

36 auditable resource types registered across all FUIP layers, event type format: FUIP_{RESOURCE_TYPE}_{ACTION}

Dynamic severity assignment: high for delete/purge/block/rollback/merge, medium for create/activate/deactivate, low for others

Consistent FUIP_{RESOURCE_TYPE}_{ACTION} naming convention for all audit events across the platform

Governance audit events produced to fuip.governance.audit Kafka topic (#29) from ConsentEvaluationService and PurgeOrchestrationService

25 resource domains defined in FuipIamResourceDefinition covering telemetry, behavior, experiments, decisions, features, algorithms, safety, governance

11 action patterns defined: read, list, create, update, delete, activate, deactivate, execute, export, configure, purge

4 predefined roles with layered inheritance: viewer -> analyst -> operator -> admin, permissions computed dynamically

10 privileged operations identified and tracked via isPrivileged(domain, action) method for elevated audit

Full PERMISSION_MATRIX covering all 25 resource domains with action-level granularity per role

Initiate/status/list operations via AdminReplayAction, PG table fuip.replay_control (16 cols), PostgreSQLReplayControlRepository (6 methods)

PG table fuip.processing_checkpoints (11 cols, UNIQUE tenant_id+processor_key+partition_id) for consumer offset tracking

3 admin POST endpoints registered: /admin/governance/gate, /admin/replay, /admin/purge with action-based routing

Governance routes wired in FUIP route group at routes/api/fuip.php, 8th phase require after safety

Non-blocking consent check in DecisionContextAssemblyService via logConsentStatus(), nullable ConsentEvaluationServiceInterface injection

Track payment outcomes (success, failure, decline) per user over time with payment_behavior_rollup read model aggregation

Measure payment retry patterns and their success rates after initial failure, feeding into transaction_outcome_rollup

Track order lifecycle completion rates and cancellation patterns per user, feeding into transaction_outcome_rollup

Monitor refund frequency, chargeback disputes, and dispute resolution outcomes feeding into payment_behavior_rollup

Track subscription billing timeliness, late payment patterns, and billing regularity feeding into billing_stability_rollup

Track spending patterns and order value distribution stability over time, detect anomalous shifts in financial_stability_profile

Analyze frequency vs value stability over rolling windows, detect spending velocity changes (not income, only behavioral patterns)

Monitor subscription continuity, churn patterns, and plan upgrade/downgrade behavior feeding into commitment_consistency_profile

Track delivery completion, attendance, usage fulfillment across order types in fulfillment_reliability_profile read model

Aggregate commitment behavior signals (delivery + attendance + usage) into commitment_consistency_profile with rolling window computation

Derive LOW/MEDIUM/HIGH financial band from payment success rate, retry patterns, refund ratio. Always accompanied by reason codes (e.g., HIGH_PAYMENT_SUCCESS, LOW_REFUND_RATIO). Financial domain only

Derive LOW/MEDIUM/HIGH financial band from fulfillment success rates, delivery completion, commitment consistency with explainable reason codes. Financial domain only

Derive LOW/MEDIUM/HIGH financial band from spending patterns, order value consistency, billing punctuality with explainable reason codes. Financial domain only

Derive LOW/MEDIUM/HIGH behavioral risk band from combined platform behavioral signals. Explicitly non-credit, non-income, non-financial-judgment — based only on observable platform behavior patterns. Financial domain only

Read-only API assembling financial domain bands with reason codes into financial_intelligence_snapshot. Covers financial bands only (payment reliability, fulfillment capacity, financial stability, behavioral risk). Trust/compliance bands are served separately from F19. Example: {payment_reliability: HIGH, reasons: ["95% success rate", "low refund ratio"]}

Detect and record abuse patterns, fraud indicators, and system misuse signals into trust_behavior_profile read model. Trust/compliance domain — separate from financial signals (F16-F18)

Track complaint frequency, dispute patterns, resolution outcomes, and escalation rates per user over time. Trust/compliance domain

Monitor policy violations, ToS breaches, refund abuse, and compliance infractions feeding into compliance_signal_snapshot. Trust/compliance domain

Derive HIGH/MEDIUM/LOW trust band from abuse, complaint, and violation signals. Separate from financial bands (F18). Example: trust_band=LOW, reasons=[HIGH_REFUND_ABUSE, MULTIPLE_DISPUTES]. Trust/compliance domain

Derive compliance band from policy adherence, dispute resolution patterns, and refund abuse indicators with reason codes. Trust/compliance domain — separate from financial bands (F18)

Compose financial bands (F18) + trust bands (F19) into sponsor suitability indicators for sponsor/lender eligibility assessment (NOT approval/denial). Composition layer — does not merge domain ownership

Behavioral-only payment affordability indicator derived from platform behavioral/payment history signals. Does NOT use income data, does NOT use external credit bureau data, does NOT infer formal credit score. Based solely on observable platform behavior (spending patterns, billing punctuality, financial stability band)

Signal-based subscription tier suitability (prepaid/standard/premium) composed from financial stability band + billing punctuality signals + trust band. Composition layer — does not merge domain ownership

Forward-looking risk indicators composed from commitment history, financial stability bands (F18), and trust/compliance bands (F19) for long-term commitment assessment. Composition layer

Read-only APIs: sponsorship_support_snapshot + subscription_eligibility_snapshot. Composes financial bands (F18) + trust bands (F19) but does not merge domain ownership. FUIP provides signals only — consuming systems make decisions

Structured registry of all reason codes (HIGH_PAYMENT_SUCCESS, LOW_DISPUTE_RATE, CONSISTENT_ACTIVITY, HIGH_REFUND_ABUSE, etc.) with categories and human-readable descriptions

API endpoint returning band values + human-readable reason codes for any financial/trust intelligence query. Example: {"reason_codes": ["HIGH_PAYMENT_SUCCESS", "LOW_DISPUTE_RATE"]}

Audit log capturing every downstream system that consumes financial/trust intelligence signals — who queried, what bands, for what purpose, at what time

Purpose-based filtering of financial/trust intelligence outputs via FUIP F2 consent governance integration. Internal operational and governance-safe signals may be processed under approved internal purpose and policy controls. External-facing, sponsor-facing, advertiser-facing, and third-party-facing outputs require appropriate consent, lawful basis, and purpose control. Every read path must be purpose-tagged. External exposure must be filtered by consent/purpose rules

Tag every intelligence query/response with purpose (eligibility, risk_assessment, sponsorship, subscription, internal_governance) for compliance tracking and audit

Governance-level signal drift monitoring (not ML model drift). Detects drift in band distributions over time, signal instability across rolling windows, and degradation in reliability of derived indicators. Feeds Quality Center and governance review for investigation. Non-blocking initially — observe mode only

Define policy rules mapping band values (HIGH/MEDIUM/LOW) to allowed/restricted actions per use case. Configurable via governance dashboard, not hardcoded

HIGH trust/reliability -> allow premium features. LOW trust -> restrict risky operations. Always with explanation via F21 explainability layer

HIGH reliability -> allow subscription/credit plans. LOW reliability -> require prepaid. Policy-driven, not hardcoded, always with user-facing explanation

MANDATORY: every restriction must produce a user-facing explanation. No silent punishment. TransparencyGuard validates every action policy execution includes reason codes

Audit log of every action policy execution: band values used, reason codes generated, action taken, user notified. Integrates with F4 Audit + F21 governance layer