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Open Lending Corporation (LPRO) Fair Value & Analysis

Financial Services · US · Market cap $368M

Price$3.12
Fair Value$1.41
Upside-54.8%
Quality95/100
Evidence: Low Range $1.21 – $1.60

Fair value as of: Jun 26, 2026

Analysis

Open Lending Corporation (LPRO) currently trades at $3.12, while our model-based Fair Value estimate is $1.41 — implying the stock looks roughly 54.8% overvalued today. We read business quality at 95/100 (high quality), in the Financial Services sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: low).

About the company

Open Lending Corporation provides lending enablement and risk analytics solutions to credit unions, regional banks, finance companies, and captive finance companies of automakers in the United States. The company offers lenders protection platform (LPP), which is a cloud-based automotive lending enablement platform that provides loan analytics solutions and automated issuance of credit default insurance with third-party insurance providers. Its LPP products include loan analytics, risk-based loan pricing, risk modeling, and automated decision technology for automotive lenders. The company was founded in 2000 and is headquartered in Austin, Texas.

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Frequently asked questions

Is Open Lending Corporation (LPRO) undervalued?
As of Jun 26, 2026, our model estimates a fair value of $1.41 versus a price of $3.12 — about −55% (overvalued). Model-based estimate, not financial advice.
What is the fair value of LPRO?
Our 21-model fair value for Open Lending Corporation is $1.41 (as of Jun 26, 2026), built from audited fundamentals. The current price is $3.12.
What is the quality score of LPRO?
Open Lending Corporation has a Quality Score of 95/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

How we calculate Fair Value

Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.

Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.