Subprime Opportunity Finder — Dealers in the Subprime Lending Sweet Spot

Lender sales rep from a subprime/non-prime lending company looking for independent dealers that specialize in older, higher-mileage, budget-priced vehicles. These are the natural partners for subprime lending programs.

Gotchas

1. Independent dealer bias. Subprime inventory concentrates at independent dealers, but some franchise dealers have separate "value lot" operations. If user asks, run a second scan without dealer_type=independent to catch franchise dealers with subprime-profile inventory.
2. Price floor matters. Vehicles under $3,000 are often parts cars, salvage, or non-retail inventory. The default floor of $3,000 exists for a reason — do not lower it unless the user explicitly asks. These units are not lendable.
3. BHPH dealers may not appear. Buy-Here-Pay-Here dealers often do not list on major aggregators. The scan will find dealers who LIST subprime-profile vehicles online, which skews toward dealers seeking retail financing partners (exactly the right audience), but the total addressable market is larger.
4. Mileage range is critical for risk. Vehicles over 150,000 miles are typically outside even subprime lending guidelines. The default ceiling of 150,000 miles is a hard stop for most lenders — confirm with the user if they want to go higher.
5. Dealer facet cap of 50. The dealer_id facet returns at most 50 dealers. In large metro areas, this undercounts. If the scan returns exactly 50 dealers, note "50+ dealers found — results may be truncated. Consider narrowing by ZIP+radius."

Workflow: Find Subprime-Profile Dealers

1. Search for subprime-segment inventory — Call mcp__marketcheck__search_active_cars with state=[ST] (or zip=[ZIP]+radius=[R]), price_range=3000-18000 (or profile's subprime range), year=2012-2020, miles_range=60000-150000, car_type=used, dealer_type=independent, seller_type=dealer, facets=dealer_id|0|50|2, stats=price,miles, rows=0. → Extract only: dealer_ids from facets with unit counts, total matching units (num_found), avg_price, avg_miles from stats. Discard full response.

   • If exactly 50 dealers returned in facet, note truncation warning.

2. Profile top subprime dealers — For the top 15 dealers by matching unit count (minimum 10 units in range), call mcp__marketcheck__search_active_cars with dealer_id=[id], car_type=used, stats=price,miles,dom, facets=make|0|15|1,year|0|10|1, rows=0. → Extract only per dealer: seller_name, city, total_count (num_found for all inventory), avg_price, avg_miles, avg_dom from stats, make distribution and year distribution from facets. Discard full response.

3. Calculate subprime metrics per dealer:

   • Subprime Concentration = subprime_matching_units / total_units × 100. Over 50% = dedicated subprime dealer.
   • Avg Price in subprime range — confirms lending sweet spot alignment
   • Avg Year — older = more subprime oriented
   • Avg Mileage — higher = more subprime oriented
   • Turn Estimate = based on avg_dom. Lower DOM = they move cars = more originations.
   • Monthly Origination Est = subprime_units × (30 / avg_dom) × penetration (30% for subprime — higher since limited financing options)
   • Subprime Score = (concentration × 40) + (volume × 30) + (turn_rate × 30)

4. Classify:

   • Score 70+: CORE SUBPRIME — Dedicated BHPH/subprime dealer, high volume, strong fit
   • Score 50-69: PARTIAL SUBPRIME — Mixed lot with significant subprime inventory
   • Score 30-49: FRINGE — Some qualifying units but not primary business

Output Template

── Subprime Opportunity Finder: [State/ZIP] ── [Date] ──────

MARKET SUMMARY
Total subprime-profile units found: [X]
Dealers with 10+ qualifying units:  [Y]
Avg price in range: $XX,XXX | Avg miles: XX,XXX | Avg year: XXXX

SUBPRIME DEALER PROSPECTS
Rank | Dealer Name      | City   | Total | Sub Units | Conc% | Avg $  | Avg Mi  | DOM | Est Mo Orig | Score | Class
-----|------------------|--------|-------|-----------|-------|--------|---------|-----|-------------|-------|------
1    | [Name]           | [City] |  XX   |    XX     |  XX%  | $X,XXX | XX,XXX  | XX  |    X.X      |  XX   | CORE
2    | [Name]           | [City] |  XX   |    XX     |  XX%  | $X,XXX | XX,XXX  | XX  |    X.X      |  XX   | CORE
...

CLASSIFICATIONS
CORE SUBPRIME (70+):    [X] dealers — dedicated BHPH/subprime, high volume
PARTIAL SUBPRIME (50-69): [X] dealers — mixed lot, significant subprime
FRINGE (30-49):         [X] dealers — some qualifying units

SUMMARY
[X] core subprime dealers with [Y] total lendable units.
Estimated monthly origination opportunity: [Z] loans.

TOP 5 OUTREACH RECOMMENDATIONS
1. [Dealer] in [City] — [specific reason, e.g., "XX units in sweet spot, XX% concentration, fast turn"]
2. ...

Source: MarketCheck inventory data, [Date].

Output

Subprime dealer prospect table: Rank, Dealer Name, City, Total Units, Subprime Units, Concentration %, Avg Price, Avg Miles, Avg Year, Avg DOM, Est Monthly Originations, Subprime Score, Classification. Summary: "[X] core subprime dealers with [Y] total lendable units. Estimated monthly origination opportunity: [Z] loans." Top 5 outreach recommendations.

Self-Check (before presenting to user)

1. All dealers have minimum 10 qualifying units? Do not include dealers below the threshold — they are not worth the sales call for subprime.
2. Subprime Score components add to 100? Concentration (40) + Volume (30) + Turn Rate (30) = 100 max. Verify each dealer's score is the sum of its components.
3. Concentration % is subprime units / total units, not the reverse? A dealer with 50 subprime units out of 80 total is 62.5% concentration. Verify direction.
4. Monthly origination estimate uses 30% penetration? Subprime penetration is higher than prime (30% vs 20%) because these dealers have fewer financing options. Confirm the right rate was used.
5. Price range aligns with lending guidelines? Verify that the search price_range matches the profile or the $3K-$18K default. Units outside the lender's actual guidelines should not be counted.
6. No franchise dealers in results (unless explicitly requested)? Default is dealer_type=independent. Confirm the filter was applied.