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Pitney Bowes Inc (PBI) Fair Value & Analysis

Industrials · US · Market cap $2.3B

Price$17.05
Fair Value$11.20
Upside-34.3%
Quality95/100
Evidence: High Range $7.53 – $20.03

Analysis

Pitney Bowes Inc (PBI) currently trades at $17.05, while our model-based Fair Value estimate is $11.20 — implying the stock looks roughly 34.3% overvalued today. We read business quality at 95/100 (high quality), in the Industrials 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: high).

About the company

Pitney Bowes Inc. provides digital shipping solutions, mailing innovation, and financial services worldwide. It operates through SendTech Solutions and Presort Services segments. The SendTech Solutions segment offers physical and digital shipping and mailing technology solutions and other applications for sending, tracking, and receiving of letters, parcels and flats, as well as supplies and maintenance services. This segment also provides financing alternatives to finance other manufacturers' equipment and product purchases. The Presort Services segment operates as a workshare partner of the United States Postal Service; and offers mail sortation services. It markets its products, solutions, and services through direct and inside sales force, partner channels, direct mailings, and digital channels. The company was formerly known as Pitney Bowes Postage Meter Company. Pitney Bowes Inc. was incorporated in 1920 and is headquartered in Shelton, Connecticut.

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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.