Bureau Veritas SA (BVRDF) Fair Value & Analysis
Industrials · US · Market cap $13.7B
Analysis
Bureau Veritas SA (BVRDF) currently trades at $29.43, while our model-based Fair Value estimate is $31.57 — implying the stock looks roughly 7.3% undervalued today. We read business quality at 94/100 (high quality), in the Industrials sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.
About the company
Bureau Veritas SA provides laboratory testing, inspection, and certification services. It operates through six segments: Marine & Offshore; Agri-Food & Commodities; Industry; Buildings & Infrastructure; Certification; and Consumer Products services. The company engages in inspecting, analyzing, auditing, and certifying the products, assets, and management systems of its clients in relation to regulatory or self-imposed standards, as well as issues compliance reports. It also provides technical services, including asset integrity management for marine and offshore; post accident expertise, risk assessment for the offshore industry, marine accident investigations, pre- and post salvage advice, and refloating of vessels; inspection, audit, certification, and testing services for oil and petrochemicals, metals and minerals, and agri commodities; technical control, code compliance, independent technical assistance, quality assurance/quality control, construction management, and project m…
Open the full interactive analysis →
Similar stocks
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.