Reinsurance P&C - Loss Reserve Forecasting

Purpose

Reinsurance P&C - Loss Reserve Forecasting is designed to apply time series forecasting and regression models to predict reserves more accurately across lines of business for property and casualty reinsurance.

Primary users

The primary user is not specified in the provided information. The agent is associated with the AQS team and owned by Ronan Davit.

Where it fits (process/stage/trigger)

This agent fits into the loss reserve forecasting process for P&C reinsurance, where reserve predictions are needed across lines of business using available claims and loss-related datasets.

Key capabilities / workflow

The agent analyzes claims triangles, paid and incurred losses, exposure measures, and IBNR estimates, then applies time series forecasting and regression models to produce reserve predictions. If data availability or forecast acceptability is not met, the workflow loops back to review the data or refine the forecasting step.

Inputs

Inputs are not specified beyond the available dataset, which includes claims triangles, paid and incurred losses, exposure measures, and IBNR estimates.

Outputs / Deliverables

Outputs are not specified beyond predicted reserves or reserve forecasting results across lines of business.

Value

The agent supports more accurate reserve prediction for P&C reinsurance by applying forecasting and regression methods to relevant claims and loss datasets.