Claims Valuation

---
name: claims-valuation
description: >
  Total-loss determination and settlement pricing. Triggers: "total loss valuation",
  "claims value", "settlement offer", "salvage estimate", "insurance claim pricing",
  "total loss threshold", "what's the claim worth", "settlement range",
  "pre-loss value", "diminished value", "total loss determination",
  insurance claim vehicle valuation, total-loss determination,
  settlement pricing, or salvage value estimation.
version: 0.1.0
---

# Claims Valuation — Insurance Total-Loss & Settlement Pricing

## Insurer Profile (Load First)

1. Read the `marketcheck-profile.md` project memory file.
2. If exists, extract: location (zip/state), preferences (total_loss_threshold_pct, default_comp_radius).
3. If not found: ask for ZIP code to proceed. Suggest running `/onboarding` first.
4. **Country check:** US-only. UK not supported (requires predict_price and sold data).
5. Confirm: "Using profile: **[user.name]**, [ZIP], [State]"

## User Context

The primary user is an **insurance adjuster** or **total-loss specialist** who needs a defensible, comparable-backed fair market value (FMV) to determine if a vehicle is a total loss and, if so, what the settlement offer should be. The valuation must be supportable in dispute resolution.

## Workflow: Total-Loss Determination & Settlement

### Step 1 — Vehicle identification

Collect from user:
- VIN (required)
- Current odometer reading (required)
- Pre-loss condition: Clean, Average, Rough (required)
- Date of loss (optional, defaults to today)
- Any pre-existing damage or modifications

Call `mcp__marketcheck__decode_vin_neovin` with the VIN to get exact specs: year, make, model, trim, body type, drivetrain, engine, transmission, original MSRP.
→ **Extract only**: year, make, model, trim, body_type, drivetrain, engine, transmission, MSRP. Discard full response.

### Step 2 — Fair Market Value (FMV) determination

Make THREE pricing calls:
1. `mcp__marketcheck__predict_price_with_comparables` with VIN, miles, ZIP, `dealer_type=franchise` → Franchise retail FMV
2. `mcp__marketcheck__predict_price_with_comparables` with VIN, miles, ZIP, `dealer_type=independent` → Independent retail FMV
3. If vehicle was CPO (`is_certified` in history or user states): additional call with `is_certified=true`
→ **Extract only**: predicted_price, comp count per call. Discard full response.

**Pre-loss FMV** = average of franchise and independent predicted prices, adjusted by condition:
- Clean: use the higher of the two predictions
- Average: use the average
- Rough: use the lower, minus 5%

### Step 3 — Comparable evidence (wide radius)

Pull active retail comparables:
- `mcp__marketcheck__search_active_cars` with YMMT, ZIP, `radius=100`, `miles_range=<odo-15000>-<odo+15000>`, `car_type=used`, `sort_by=price`, `sort_order=asc`, `rows=20`
→ **Extract only**: VIN, price, miles, dealer_name, distance, dom per listing. Discard full response.

Pull sold transaction evidence (strongest for disputes):
- `mcp__marketcheck__search_past_90_days` with same YMMT filters, `sold=true`
→ **Extract only**: VIN, sold_price, miles, dealer_name, sale_date per listing. Discard full response.

### Step 4 — Total-loss determination

Calculate:
- **Repair cost threshold** = FMV x total_loss_threshold_pct (default 75%)
- If estimated repair cost > threshold → **TOTAL LOSS**
- If not provided, just present the threshold: "This vehicle is a total loss if repair costs exceed $XX,XXX (75% of FMV)"

### Step 5 — Settlement range

Calculate three tiers:
- **Low settlement** = 25th percentile of sold transaction prices (condition-adjusted)
- **Mid settlement** = Pre-loss FMV from Step 2
- **High settlement** = 75th percentile of sold transaction prices

### Step 6 — Salvage value estimate

Salvage value is typically 15-25% of pre-loss FMV depending on damage severity:
- Minor (cosmetic): 25% of FMV
- Moderate (mechanical): 20% of FMV
- Severe (structural/flood): 15% of FMV
- If user provides actual salvage bid, use that instead

**Net claim cost** = Settlement offer - Salvage value

## Output

Present: vehicle ID summary, pre-loss FMV table (franchise/independent/condition-adjusted), total-loss threshold and determination, settlement range (low/mid/high), salvage estimate and net claim cost, comparable evidence tables (active + sold with VIN/price/miles/dealer), methodology notes and caveats.

## Workflow: Batch Claims Processing

For multiple VINs (e.g., hail damage event, flood):

1. Accept list of VINs with miles and condition
2. Use the `insurer:portfolio-scanner` agent to process each VIN
3. Present summary: total claim exposure, average FMV, total-loss count, salvage estimate
4. Ranked table of all vehicles with FMV and settlement recommendation

## Workflow: Diminished Value

For vehicles that were repaired (not total-loss) and the claimant wants diminished value:

1. Get pre-loss FMV (same as Steps 1-2 above)
2. Estimate post-repair diminished value: typically 10-25% of FMV depending on repair severity
3. Show: "Pre-loss FMV: $XX,XXX → Post-repair diminished value: $X,XXX-$X,XXX"

## Important Notes

- **US-only:** Requires `predict_price_with_comparables` and `search_past_90_days`.
- Always cite specific comparable VINs — adjusters need to defend valuations.
- Sold transaction data is the strongest evidence in settlement disputes.
- The 75% total-loss threshold is a common default — actual thresholds vary by state and insurer. Use profile value if available.
- For disputed settlements, recommend expanding the search radius to 150-200 miles and including older sold data.