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eLEND Solutions — Paired quote-to-decision panel: for the same consumer credit application, the initial finance terms quoted by the dealer (payment, rate, down payment, term) joined to the actual decision returned by 100+ auto lenders, plus the re-penilization/withdrawal outcome. This is a matched quote-vs-fundable-terms dataset, not just approvals — it captures where lender terms diverge from what was sold.. Small but unusually deep: 28 people, ~$8.4M revenue. Published slice is a survey-based market-size report; the underlying asset is a matched dealer-quote / lender-decision panel spanning…
Paired quote-to-decision panel: for the same consumer credit application, the initial finance terms quoted by the dealer (payment, rate, down payment, term) joined to the actual decision returned by 100+ auto lenders, plus the re-penilization/withdrawal outcome. This is a matched quote-vs-fundable-terms dataset, not just approvals — it captures where lender terms diverge from what was sold.
From 5 yearsFormat TabularCoverage Information Technology · Financials
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eLEND Solutions — Paired quote-to-decision panel: for the same consumer credit application, the initial finance terms quoted by the dealer (payment, rate, down payment, term) joined to the actual decision returned by 100+ auto lenders, plus the re-penilization/withdrawal outcome. This is a matched quote-vs-fundable-terms dataset, not just approvals — it captures where lender terms diverge from what was sold.. Small but unusually deep: 28 people, ~$8.4M revenue. Published slice is a survey-based market-size report; the underlying asset is a matched dealer-quote / lender-decision panel spanning…
eLEND Solutions offers (Alternative, Fundamental) — est. 10^4-10^5 paired quote/decision applications to date (report analyzes 'thousands' for a single study), growing at the rate of connected-dealer application flow — likely 10^5-10^6 per year at full network scale. Each record carries 4+ paired numeric terms plus a decision label from 100+ distinct lenders..
Training and calibrating pre-desking / credit-decisioning models that predict fundable terms before the F&I office; lender-level quote-accuracy and counteroffer-behaviour benchmarking; dealer F&I penetration and gross-profit optimization; quantifying the cost of rate-sheet withdrawal for lender network design; synthetic labeled (quoted terms -> fundable terms) pairs for ML, which is the exact supervision signal a credit-prediction vendor needs.
The data is with 5 years of history.
Coverage spans US; Application Software, Consumer Finance; alternative, fundamental; equities, fixed_income.
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