Securemetric Berhad (0203) Fair Value & Analysis
Technology · MY · Market cap 63.5M MYR
Fair value as of: Jun 26, 2026
Analysis
Securemetric Berhad (0203) currently trades at 0.1000 MYR, while our model-based Fair Value estimate is 0.0700 MYR — implying the stock looks roughly 30.0% overvalued today. We read business quality at 95/100 (high quality), in the Technology 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
Securemetric Berhad provides digital security solutions in Malaysia, Vietnam, the Philippines, Indonesia, the United States, Singapore, and internationally. The company operates through Digital Security Solutions, Electronic Identification Products, Maintenance Services, and Others segments. Its products include software licensing protection dongles for the prevention of unauthorized access, copy, imitation, and distribution of software; two-factor authentication that enhances access security by enforcing a second authentication factor through a randomly generated one-time password; public key infrastructure tokens; and CENTAGATE, a software that manages user authentication and supports multi-factor and multichannel authentication, and digital signing solution. The company also trades in electronic identification products and offers other related services. In addition, it sells smart cards, smart card readers, fingerprint readers, barcode scanners, and barcode printers; and provides…
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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.