Federated Evidence Packs for Privacy-Safe Operational Forecasting

Operational forecasts for regulated enterprise systems require evidence distributed across grid telemetry, maintenance observations, financial risk records, cloud-resource signals, policy repositories, and privacy-scoped analytics stores. Centralizing these records creates unnecessary disclosure risk and weakens control over source authority. This paper proposes FEP-OF, a Federated Evidence Pack architecture for Privacy-Safe Operational Forecasting. Each governed domain constructs a local pack containing relational predicates, retrieval evidence, forecast features, calibration state, privacy transformation metadata, risk summaries, and a contract-bound audit record. A federation coordinator composes only admissible pack summaries and emits forecasts with traceable uncertainty and tail-risk controls. In a simulated benchmark over grid stress, calibration maintenance, financial-risk escalation, and hybrid-cloud capacity forecasting, FEP-OF increases evidence-supported forecast decisions from 0.74 to 0.93, reduces simulated sensitive-field exposure alerts from 7.8% to 0.9%, reduces adverse-event CVaR by 34.6%, and preserves zero simulated contract-invalid evidence transfers.