Converging predictive streams: A dual-domain AI framework for integrated HR and financial risk intelligence in enterprise environments

Enterprise organizations consistently manage human capital analytics and financial risk governance through disconnected architectural pipelines, despite their profound operational interdependence. This paper proposes the Dual-Domain Predictive Intelligence (DDPI) Framework — a unified enterprise architecture integrating predictive HR analytics and financial risk intelligence into a single coherent decision support system. The DDPI Framework introduces five integrated components: a Dual-Domain Data Ingestion Layer, a Unified Feature Engineering Pipeline, a Cross-Domain Predictive Model Suite, a Convergence Signal Engine, and an Executive Intelligence Dashboard. Evaluation across three enterprise financial services scenarios demonstrated a 47% reduction in cross-domain decision latency, cross-domain alert precision of 0.81, recall of 0.76, and an 82% improvement in regulatory audit preparedness compared to siloed baseline architectures. The framework enables simultaneous detection of attrition risk, compensation anomalies, credit exposure, and regulatory compliance gaps from a unified predictive pipeline — a capability not previously formalized in the peer-reviewed literature. These results establish the DDPI Framework as a validated architectural model for enterprise Chief Human Resources Officers, Chief Financial Officers, and Chief Data Officers seeking to align people strategy with financial risk governance.