Complete AI Training
Sign inGet my AI kit

Your job's AI kit

Get your AI kit

Tell us who you are and what you do. We show you your kit right away and email you the link: skills, prompts, AI agents, MCP servers and courses for your job.

500+ jobs ready, and we make a kit for any other job. No payment needed to look.

Share

AI agent for insurance data analysts

Policy Renewal Retention Forecast Agent

Accurate renewal forecasts and at-risk lists

Policy Renewal Retention Forecast Agent: what goes in, what the agent does and what you get

What it does

Retention teams need to know which valuable policies are likely to lapse before renewal, while there is still time to act. Each month this agent forecasts renewals using the renewal model, with inputs such as rate change, tenure, claims and payment history. A rate increase over 10 percent counts as a high-risk input. It first compares last month's forecast with actual renewals and checks accuracy by segment. If any segment falls below 90 percent, it looks for the cause, such as a new competitor price or a changed input, adjusts or retrains, and reruns before trusting the new forecast. It then lists at-risk policies with premium above the set amount. The analyst approves the forecast and every list shared with retention teams. Edge case: a state rate increase just took effect, so the agent adds it as an input before forecasting.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedNo 1 STARTS WHEN Monthly forecast 2 USES A TOOL Load renewal policies and inputs 3 USES A TOOL Compare last forecast to actual 4 CHECKS THE RESULT Is accuracy within target by segment? If not: find the cause, adjust or retrain, and reload.Back to step 2. 5 DOES Score upcoming renewals 6 DOES List high-value at-risk policies 7 YOU APPROVE Analyst approves forecast and list 8 RESULT Forecast and at-risk list shared
Read the steps as a list
  1. Monthly forecast
  2. Load renewal policies and inputs
  3. Compare last forecast to actual
  4. Is accuracy within target by segment?If not: find the cause, adjust or retrain, and reload. Back to step 2.
  5. Score upcoming renewals
  6. List high-value at-risk policies
  7. Analyst approves forecast and listThe agent waits here for your OK.
  8. Forecast and at-risk list shared

How it decides

It scores each policy's renewal chance and checks the model against actual outcomes by segment.

  • Accuracy below 90% in a segment: investigate
  • Rate change over 10%: high risk input
  • Premium over set amount and low score: add to list

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Accuracy target
  • Segments
  • List size
  • Model refresh rules

What keeps you in control

It always asks you first

  • Sharing lists with retention teams

Hard limits

  • Never changes prices
  • Never contacts customers

It stops when

  • Done: forecast shared
  • Stop: data late

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensIn the June run, last month's forecast missed homeowners renewals by 6 points in one state, below the 90% accuracy target. The agent found a 12% rate rise that took effect May 1 was not loaded as an input. It added the rate change, re-ran the back-test and reached 93%. It then scored 4,800 upcoming renewals and listed 220 high-value at-risk policies. The analyst approved the list for agents.

More agents for insurance data analysts