Agentic Policy Servicing Automation

Policy updates are slowed by manual intake, inconsistent documentation, and repeated verification. Errors, fraud risk, and poor audit trails increase operational cost and compliance exposure.

Policy servicing teams handle high volumes of customer updates such as address changes and beneficiary modifications across web, scans, and voice channels. Requests often arrive with incomplete or inconsistent information, requiring manual extraction, re-keying, and repeated follow-ups. Verification is typically performed through fragmented checks, which increases the likelihood of incorrect updates, exceptions, and potential fraud. Updates must also be synchronized across SCV and downstream systems, where failures create mismatches and customer dissatisfaction. Finally, audit evidence and authorization trails are often inconsistent, making it harder to meet regulatory expectations for traceability and oversight.

Unify intake, extraction, verification, decisioning, and SCV updates into one controlled workflow. Auto-approve high-confidence changes and route exceptions to human review with full auditability.

The solution automates policy servicing updates end-to-end by capturing requests from digital and assisted channels, detecting intent, and retrieving the latest SCV record. It extracts and normalizes change fields from forms and documents, then verifies identity and validates updates using policy rules and compliance checks. A decisioning layer determines whether to auto-update via APIs (high confidence) or route to human review (low confidence or flagged changes). Updates are synchronized across SCV and downstream systems, and customers receive real-time confirmation. Every step is logged to maintain traceability, authorization evidence, and audit readiness.

Enables faster, safer policy updates by automating verification and synchronization while maintaining strong compliance and audit trails.

Reduces incorrect or incomplete updates through automated extraction, normalization, and validation against existing SCV records.

Cuts end-to-end processing time by auto-approving high-confidence changes and minimizing manual back-office effort.

Maintains traceable decision logs, authorization evidence, and consistent controls aligned to regulatory requirements for policy changes.

Brillio streamlines policy servicing updates on AWS by automating request intake, document extraction, verification, decisioning, and compliant synchronization with Single Customer View (SCV) and downstream systems. The solution supports multi-channel servicing (web, scan, assisted) while enforcing validation rules, authorization checks, and confidence-based routing. High-confidence changes are auto-updated via APIs; exceptions are routed to human review with a complete audit trail. Using AWS-managed services for orchestration, storage, and security, the approach improves data accuracy, reduces operational effort, and strengthens compliance and audit readiness for policy changes.

AWS Native Services Utilized: Amazon Bedrock and Amazon SageMaker.

Extracts update fields from documents and payloads, normalizes them into canonical formats, and assigns confidence scores to support downstream decisioning. The workflow reduces manual re-keying and prevents incomplete updates by standardizing address and beneficiary structures before validation and synchronization.

Validates changes against policy rules and compliance requirements, then routes outcomes based on confidence: auto-update via API for high-confidence cases and human review for exceptions. Ensures SCV and downstream systems remain synchronized, while capturing authorization evidence and complete audit logs for regulatory readiness.

A large national insurer struggled with slow and error-prone policy updates such as address changes and beneficiary modifications. Requests arrived in inconsistent formats, required manual extraction and repeated verification, and often resulted in SCV mismatches, customer complaints, and weak audit trails.

Brillio deployed an AWS-based servicing workflow that captured intent, extracted and normalized change fields, verified identity and policy rules, and used confidence-based decisioning to auto-update SCV via APIs or route exceptions to human review with traceability.

The insurer reduced processing time for routine servicing requests, improved consistency of updates across systems, and strengthened compliance through standardized controls and decision logs. Customer confirmations became faster and more reliable, lowering rework and operational overhead.