Inversiones La Construcción S.A (ILC) Fair Value & Analysis
Financial Services · CL · Market cap 2.2T CLP
Analysis
Inversiones La Construcción S.A (ILC) currently trades at 21,900 CLP, while our model-based Fair Value estimate is 36,793 CLP — implying the stock looks roughly 68.0% undervalued today. We read business quality at 94/100 (high quality), in the Financial Services 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
Inversiones La Construcción S.A. operates in the financial and health sectors in Chile, Peru, and Colombia. It operates through six segments: AFP, Ispare, Insurance, Health, Banking, and Other segments. The company is involved in the management of products related to savings and retirement, including mandatory individual retirement savings; individual and group voluntary retirement savings; voluntary individual savings; management and payment of pensions under scheduled or temporary withdrawal programs through a network of branches and digital platforms, such as websites, call centers, and mobile applications; and provision of health insurance solutions, plans, and supplementary products and collective credit life insurance for mortgages, as well as educational and information technology services. It also provides savings and retirement products, such as annuities, individual life insurance, consumer loans for pensioners, and credit life insurance; and corporate and retail banking p…
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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.