Risk Severity and Frequency Modeling

Purpose

Risk Severity and Frequency Modeling supports insurance risk analysis by using supervised machine learning models, including GBMs and neural nets, to predict claim frequency and claim severity per policy segment.

Primary users

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

Where it fits (process/stage/trigger)

This agent fits within insurance risk modeling activities where policy-level exposure, historical claims, risk attributes, and external socio-economic data are used to assess expected claim behavior by policy segment.

Key capabilities / workflow

The agent analyzes available policy and claims datasets, prepares relevant risk attributes, trains supervised machine learning models, validates whether predictions are suitable, and generates claim frequency and severity predictions for policy segments.

Inputs

Inputs are not specified. The provided dataset includes policy-level exposure, historical claims, risk attributes, and external socio-economic data.

Outputs / Deliverables

Outputs are not specified. Based on the stated use case, the agent produces predictions of claim frequency and claim severity per policy segment.

Value

The agent helps insurance teams model risk at the policy-segment level, supporting more data-driven analysis of expected claim frequency and severity using historical, exposure, risk, and socio-economic data.