AI-Powered Data Reconciliation

Purpose

AI-Powered Data Reconciliation is designed to reconcile datasets between actuarial systems, such as policy administration systems and data warehouse environments, using record-linkage and anomaly detection techniques.

Primary users

The primary user is not specified. The agent is associated with the AQS team and is intended for users involved in insurance data reconciliation activities.

Where it fits (process/stage/trigger)

This agent fits into reconciliation processes where datasets from actuarial systems need to be compared, linked, and checked for anomalies, particularly between policy administration data, claim data, data warehouse extracts, and system reconciliation tables.

Key capabilities / workflow

The agent supports dataset reconciliation by linking records across systems, checking match quality, analyzing anomalies, and producing reconciliation-related outputs based on the provided policy and claim datasets, data warehouse extracts, and reconciliation tables.

Inputs

Inputs are not specified. Available source datasets include policy and claim datasets, data warehouse extracts, and system reconciliation tables.

Outputs / Deliverables

Outputs are not specified. Please refer to documentation or implementation details for the exact reconciliation deliverables produced by the agent.

Value

The agent provides value by supporting reconciliation between insurance actuarial systems and helping identify potential anomalies in policy, claim, warehouse, or reconciliation datasets.