Hansol Inticube Co (070590) Fair Value & Analysis
Technology · KR · Market cap 22.1B KRW
Fair value as of: Jun 24, 2026
Analysis
Hansol Inticube Co (070590) currently trades at 1,612 KRW, while our model-based Fair Value estimate is 1,148 KRW — implying the stock looks roughly 28.8% overvalued today. We read business quality at 93/100 (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
Hansol Inticube Co., Ltd. engages in setting up contact center infrastructure, and developing contact center solutions and wireless Internet solutions in South Korea. It offers digital contact center solutions, such as integrated routing, omnichannel, customer experience, outbound, self service, work force optimization, service control, and system control; AI communication solutions, including cloud type AI communication, robotic process automation, service orchestration engine, and voice gateway; and cloud-based communication service comprising contact center as a service and unified communication as a service. It also provides mobile solutions consisting of Internet protocol location server, MMSC, short message service center, cell broadcasting message service center, short message service gateway, media gateway control function, short message spam filtering system, push notification system, Internet protocol short message gateway, message sensing system, mobile signature service …
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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.