FTI Consulting, Inc (FCN) Fair Value & Analysis
Industrials · US · Market cap $4.7B
Analysis
FTI Consulting, Inc (FCN) currently trades at $143.65, while our model-based Fair Value estimate is $188.70 — implying the stock looks roughly 31.4% undervalued today. We read business quality at 95/100 (high quality), in the Industrials 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
FTI Consulting, Inc. provides business advisory services to manage change, mitigate risk, and resolve disputes worldwide. The company operates through Corporate Finance; Forensic and Litigation Consulting; Economic Consulting; and Technology, and Strategic Communications segments. The Corporate Finance segment provides transactions, transformation and turnaround, and restructuring services. The Forensic and Litigation Consulting segment offers construction, projects and assets and environmental solutions, data and analytics, dispute advisory services, healthcare risk management and advisory, and risk and investigations, which include cybersecurity and financial services-related offerings. The Economic Consulting segment provides antitrust and competition economics, financial economics, and international arbitration services. The Technology segment offers blockchain and digital assets, information governance, privacy and security, investigations, litigation, M&A, and antitrust and co…
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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.