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Software Service, Inc (SFSVF) Fair Value & Analysis

Healthcare · US · Market cap $423M

Price$85.59
Fair Value$153.33
Upside+79.1%
Quality95/100
Evidence: High Range $91.09 – $192.73

Fair value as of: Jun 24, 2026

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Analysis

Software Service, Inc (SFSVF) currently trades at $85.59, while our model-based Fair Value estimate is $153.33 — implying the stock looks roughly 79.1% undervalued today. We read business quality at 95/100 (high quality), in the Healthcare 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

Software Service, Inc. engages in providing electric medical record, hospital total ordering, and other systems. It offers its products under the e-medical records and NEWTONS. The company was incorporated in 1969 and is headquartered in Osaka, Japan.

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Frequently asked questions

Is Software Service, Inc (SFSVF) undervalued?
As of Jun 24, 2026, our model estimates a fair value of $153.33 versus a price of $85.59 — about +79% (undervalued). Model-based estimate, not financial advice.
What is the fair value of SFSVF?
Our 21-model fair value for Software Service, Inc is $153.33 (as of Jun 24, 2026), built from audited fundamentals. The current price is $85.59.
What is the quality score of SFSVF?
Software Service, Inc 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.