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Dentsu Soken Inc (IFMNF) Fair Value & Analysis

Technology · US · Market cap $2.6B

Price$13.11
Fair Value$14.10
Upside+7.6%
Quality95/100
Evidence: High Range $8.34 – $18.19

Analysis

Dentsu Soken Inc (IFMNF) currently trades at $13.11, while our model-based Fair Value estimate is $14.10 — implying the stock looks roughly 7.6% undervalued today. We read business quality at 95/100 (high quality), in the Technology 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

Dentsu Soken Inc. provides information technology solutions. It operates through four segments: Financial Solutions, Business Solutions, Manufacturing Solutions, and Communication IT. The Financial Solutions segment offers IT solutions that support various financial operation at financial institution and other companies. The Business Solutions segment provides human capital management and accounting management solutions. The Manufacturing Solutions segment develops performance evaluation methods for air mobility, researches and develops solutions in product lifecycle management. The Communication IT segment provides software services. Dentsu Soken Inc. was formerly known as Information Services International-Dentsu, Ltd. and changed its name to Dentsu Soken Inc. in January 2024. The company was incorporated in 1975 and is headquartered in Tokyo, Japan. Dentsu Soken Inc. operates as a subsidiary Dentsu Group Inc.

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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.