Cloud-Powered Healthcare & Insurance Transformation with CRM and Advanced Analytics

Abstract

Healthcare and insurance agencies are experiencing disjointed experiences, an increase in service demands, and stringent regulations that hinder cost, quality, and expertise. The paper presents a proposal of a cloud-native blueprint that will merge Salesforce Health Cloud, Service Cloud Voice, and Einstein Copilot with a controlled analytics stack to modernize engagement, care coordination, and claims. Data is extracted through FHIR/HL7 and APIs into a lakehouse and feature store and operated to serve risk, service, and fraud models and operationalized within a CRM component based on retrieval-augmented guardrails. They are entity resolution to a Member/Patient 360, PHI tokenization, and experiment-ready instrumentation. With expected results of 10-20% decrease in Average Handle Time, a 6-10 percentage point increase in First-Contact Resolution, a 15 percent reduction in claims cycle time, readmission AUROC >0.82, precision of SIU logged at 1k ≥0.60, and ≥99.9% logged with ≤0.1% policy exceptions, steps A/B were hired, the randomized-encouragement and threshold A/B designs are applied. Observability focuses on P95 API latency of <300 ms and ASR WER under 12% and the cost per member per month is regulated and taxed to be between $0.08–$0.25 per month. The donation will include a Remote deployable compliant reference architecture, measurement plan, connecting the model measures to business KPIs, and guardrails on fairness, safety, and reliability. The solution can be applied to federated learning, multimodal analytics, and streaming interoperability through FHIR Subscriptions and payer-to-payer APIs. Research is applicable across both payers and providers and contributes to a gradual rollout and clear governance, financial, and well-defined performance WM.