Does it support geographic-specific data?

Yes, it can analyze price variances at the state and zip code level to calibrate settlements based on the claimant's specific geographic market.

How does it assist insurance underwriters?

It ranks brands and vehicle segments by residual value, allowing underwriters to identify high-risk categories that may require premium or reserve adjustments.

Can it distinguish between new and used vehicle trends?

Yes, it includes specialized workflows for used vehicle depreciation curves and new vehicle MSRP parity tracking to handle both types of insurance claims.

How does this skill help with total-loss claims?

It calculates the Fair Market Value (FMV) trajectory and provides local market comparisons to ensure settlement offers are accurate, defensible, and reflective of actual replacement costs.

Depreciation Tracker for Insurance

Name: Depreciation Tracker for Insurance
Author: MarketcheckHub

byMarketcheckHub

•

データサイエンスとML

Analyzes vehicle depreciation trends and replacement costs to optimize insurance claim settlements and reserve accuracy.

The Depreciation Tracker skill is designed specifically for insurance professionals to automate the analysis of vehicle value trajectories. It provides data-driven insights for claims adjusters and underwriters by generating detailed depreciation curves, tracking brand-level residual values, and identifying regional price variances. By leveraging real-world transaction data, the skill helps ensure that total-loss settlements are accurate, claim reserves are properly adjusted for market shifts, and portfolio risks—such as the rapid depreciation of EVs—are proactively identified.

主な機能

01Brand-level residual ranking and insurance risk tier classification

02Automated multi-interval depreciation curve generation for specific makes and models

03MSRP parity tracking to estimate replacement costs for vehicles less than one year old

042 GitHub stars

05Geographic variance analysis to calibrate settlement offers based on local market data

06Segment-level trend monitoring for portfolio-wide total-loss exposure

ユースケース

01Adjusting claim reserves based on real-time market depreciation or appreciation trends

02Calculating fair market value for total-loss settlements using localized transaction data

03Assessing underwriting risk by ranking vehicle brands by their value retention scores

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add marketcheckhub/marketcheck-cowork-plugin depreciation-tracker

For use in Claude.ai and ChatGPT

主な機能

01Brand-level residual ranking and insurance risk tier classification

02Automated multi-interval depreciation curve generation for specific makes and models

03MSRP parity tracking to estimate replacement costs for vehicles less than one year old

042 GitHub stars

05Geographic variance analysis to calibrate settlement offers based on local market data

06Segment-level trend monitoring for portfolio-wide total-loss exposure

ユースケース

01Adjusting claim reserves based on real-time market depreciation or appreciation trends

02Calculating fair market value for total-loss settlements using localized transaction data

03Assessing underwriting risk by ranking vehicle brands by their value retention scores

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add marketcheckhub/marketcheck-cowork-plugin depreciation-tracker

For use in Claude.ai and ChatGPT