Scicom (MSC) Berhad (0099) Fair Value & Analysis
Industrials · MY · Market cap 597M MYR
Fair value as of: Jun 24, 2026
Analysis
Scicom (MSC) Berhad (0099) currently trades at 1.82 MYR, while our model-based Fair Value estimate is 1.38 MYR — implying the stock looks roughly 24.2% overvalued today. We read business quality at 94/100 (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
Scicom (MSC) Berhad is an investment holding company that provides customer contact center outsourcing services in Malaysia, the Philippines, Singapore, Hong Kong, Sri Lanka, Thailand, Germany, and internationally. The company operates through two segments: Outsourcing Services and Education. The company offers business process outsourcing services, which include multilingual and multichannel customer care, technical support help desk, consultative sales, and associated fulfilment, as well as electronic solutions and applications for online processing, border security services, digital platforms, and software solutions. It also provides educational and industrial training services that focus on customer care in the service industry. In addition, the company offers digital strategy, digital marketing, e-commerce platforms, blockchain applications, advanced data insights and analytics, customer experience design, website and mobile app development, cloud computing, cybersecurity, data…
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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.