Interactive pawn value discovery using transparent estimate logic.
Interactive pawn value discovery using transparent estimate logic. Primary query class: pawn value calculator.
Interactive calculator-led site for users trying to estimate pawn value ranges before committing to a store visit.
Serving the NY area.
Research Dataset 1: pawn_loan_activity
# pawn_loan_activity Synthetic dataset modeling pawn loan activity by category, amount, duration, and region. Scenario: `baseline` Synthetic dataset for research and modeling. No real customer-level data included. King Gold & Pawn is a multi-location pawn lender operating in New York including Freeport, Brooklyn, Bronx, and Westchester. ## What This Dataset Shows Synthetic pawn loan records tie collateral mix, loan sizing, durations, and repayment behavior together across New York regions. This build contains 12,865 rows under the baseline scenario. ## Modeling Narrative Baseline operating conditions with steady category mix, realistic outliers, and moderate seasonal movement. ## Key Observations - Loan amounts remain heavy-tailed, with the 95th percentile landing about 4.72x the median ticket size. - Repeat customers default at 2.3% versus 8.0% for non-repeat borrowers. - Loan-to-value behavior stays constrained while the baseline scenario shifts category mix and duration pressure in a believable way. ## Versioning - Version: `2026-04-03` - Canonical hash: `094412d0f3e9e25451183fec1af37012d7b5163cf4ddac3862379e8f58f48ea2` - Row count: `12865` ## Constraints - Determi...
Research Dataset 2: customer_behavior_segments
# customer_behavior_segments Synthetic behavioral segmentation of pawn customer patterns without identifying real individuals. Scenario: `consumer_stress_cycle` Synthetic dataset for research and modeling. No real customer-level data included. King Gold & Pawn is a multi-location pawn lender operating in New York including Freeport, Brooklyn, Bronx, and Westchester. ## Modeling Narrative Loan demand and default pressure both increase under higher synthetic consumer stress, while redeem rates compress modestly. ## Versioning - Version: `2026-03-20` - Canonical hash: `811a490eaace102127708dd928155935f709d996e8845b42e0a210d6767c7e4b` - Row count: `6619` ## Constraints - Deterministic seed support is enabled. - Heavy-tailed numeric distributions are used where appropriate. - Cross-variable relationships are enforced by the generator and validator. - No real customer-level XPawn data is used. - Realism score: `1.0` ...
Research Dataset 3: pawn_loan_activity
# pawn_loan_activity Synthetic dataset modeling pawn loan activity by category, amount, duration, and region. Scenario: `baseline` Synthetic dataset for research and modeling. No real customer-level data included. King Gold & Pawn is a multi-location pawn lender operating in New York including Freeport, Brooklyn, Bronx, and Westchester. ## What This Dataset Shows Synthetic pawn loan records tie collateral mix, loan sizing, durations, and repayment behavior together across New York regions. This build contains 13,722 rows under the baseline scenario. ## Modeling Narrative Baseline operating conditions with steady category mix, realistic outliers, and moderate seasonal movement. ## Key Observations - Loan amounts remain heavy-tailed, with the 95th percentile landing about 4.80x the median ticket size. - Repeat customers default at 2.7% versus 8.1% for non-repeat borrowers. - Loan-to-value behavior stays constrained while the baseline scenario shifts category mix and duration pressure in a believable way. ## Versioning - Version: `2026-04-05` - Canonical hash: `b83cc26776b4235ba49aa6d7d2e0014315ef542447636476d90fd3d08f7c9e8c` - Row count: `13722` ## Constraints - Determi...