Intercorp Financial Services Inc (IFS) Fair Value & Analysis
Financial Services · US · Market cap $5.6B
Analysis
Intercorp Financial Services Inc (IFS) currently trades at $54.76, while our model-based Fair Value estimate is $109.52 — implying the stock looks roughly 100.0% undervalued today. We read business quality at 95/100 (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
Intercorp Financial Services Inc., together with its subsidiaries, provides banking, insurance, wealth management, and payment services for retail and commercial clients in Peru. The company offers loans, credit facilities, deposits, and current accounts; life annuity products with single payment and life insurance products, as well as other retail insurance products; and brokerage and investment management services. It also engages in the development, management, operation, and processing of credit and debit cards; facilitation of payments and services through commercial stores; and installation and maintenance of infrastructure for transactions through electronic commerce modality and networks of payment methods processors. In addition, the company manages mutual funds and investment funds; and provides investment consultancy and related services. The company was incorporated in 1897 and is headquartered in Lima, Peru. Intercorp Financial Services Inc. operates as a subsidiary of …
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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.