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Banco Mercantil do Brasil S.A (BMEB3) Fair Value & Analysis

Financial Services · BR · Market cap R$7.5B

PriceR$49.70
Fair ValueR$95.80
Upside+92.8%
Quality95/100
Evidence: High Range R$71.85 – R$119.75

Analysis

Banco Mercantil do Brasil S.A (BMEB3) currently trades at R$49.70, while our model-based Fair Value estimate is R$95.80 — implying the stock looks roughly 92.8% undervalued today. We read business quality at 95/100 (high quality), in the Financial Services 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

Banco Mercantil do Brasil S.A., together with its subsidiaries, provides financial services to individuals and corporate clients in Brazil. It operates through Financial, Insurance and Business Intermediation, Marketplace, and Other segments. The company offers Current Account, Loans, Cards, Investments, Card receivables, Overdraft, private pension, benefit transfer, special limit, and capital market products. It also provides internet, WhatsApp, Mercantile app, and self-service banking services. In addition, the company engages in real estate, securitization, and technology activities. The company was formerly known as Banco Industrial de Minas Gerais and changed its name to Banco Mercantil do Brasil S.A. in 1974. Banco Mercantil do Brasil S.A. was founded in 1940 and is headquartered in Belo Horizonte, Brazil.

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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.