AI-Based Duplication and Record-Linking Detection

Purpose

AI-Based Duplication and Record-Linking Detection is designed to detect duplicate or mismatched records across datasets using fuzzy matching and clustering, with a focus on insurance data such as policy and claims databases.

Primary users

The primary user is not specified. Based on the provided ownership and context, this agent is associated with the AQS team and owned by Ronan Davit.

Where it fits (process/stage/trigger)

This agent fits into data quality, reconciliation, and record-linking activities involving insurance policy and claims databases, especially when customer-level identifiers need to be compared across datasets.

Key capabilities / workflow

The agent analyzes policy and claims data, extracts customer-level identifiers, applies fuzzy matching, groups potentially related records through clustering, validates the reliability of detected clusters, and produces duplicate or mismatch findings for review.

Inputs

Typical inputs are policy and claims databases and customer-level identifiers. No additional input formats or required fields were specified.

Outputs / Deliverables

Outputs were not specified. The expected deliverable is a set of detected duplicate or mismatched records, but any formal output format should be confirmed in documentation.

Value

The agent helps improve insurance data quality by identifying duplicate and mismatched records across datasets, supporting cleaner customer, policy, and claims information for downstream processes.