Liquidity P&C - Data Reconciliation

Purpose

Liquidity P&C - Data Reconciliation is designed to integrate and reconcile liquidity-related data across ERP, treasury, accounting, and risk systems for Insurance P&C use cases. Its purpose is to detect mismatches and automatically fill missing data based on the information provided.

Primary users

The primary user is not specified in the provided information. The agent is associated with the AQS team or BU, and the listed owner is Ronan Davit.

Where it fits (process/stage/trigger)

This agent fits into liquidity data reconciliation processes involving ERP, treasury, accounting, and risk system data. The specific process stage, trigger, maturity stage, or operational timing is not specified in the provided information.

Key capabilities / workflow

The agent integrates liquidity-related data from multiple systems, reconciles records, detects mismatches, and fills missing data automatically. The workflow centers on extracting relevant liquidity data, comparing records across systems, validating whether mismatches or missing values exist, looping back when the data is incomplete, and delivering reconciled data once validation is complete.

Inputs

Typical inputs are liquidity-related data from ERP, treasury, accounting, and risk systems, as explicitly described in the use case. No additional input format, dataset name, file type, or source specification is provided.

Outputs / Deliverables

Outputs include reconciled liquidity-related data, detected mismatches, and missing data filled automatically. No additional output format, report structure, dashboard, dataset, or delivery channel is specified.

Value

The agent supports Insurance P&C liquidity data quality by helping reconcile data across key financial and risk systems. Its value lies in identifying inconsistencies and reducing missing data within liquidity-related datasets, based on the provided use case description.