Intrum AB (INJJF) Fair Value & Analysis
Financial Services · US · Market cap $347M
Fair value as of: Jun 26, 2026
Analysis
Intrum AB (INJJF) currently trades at $0.5147, while our model-based Fair Value estimate is $0.4686 — implying the stock looks roughly 9.0% overvalued today. We read business quality at 91/100 (high quality), in the Financial Services 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
Intrum AB (publ), together with its subsidiaries, provides payment solutions, and credit and collection services in Europe and internationally. It operates in two segments, Servicing and Investing. The company offers invoicing and payment services, including reminder, invoice, and accounts receivable management services; debt recovery and purchase services; credit optimization comprising credit monitoring, decisioning, and information services; debt collection; e-commerce; financial; and collateral services. It also provides Ophelos, a platform for AI debt collection and machine learning technologies, smart communications, and vulnerability detection. The company operates in Norway, Sweden, Denmark, Finland, Austria, Germany, Belgium, Netherlands, Switzerland, France, the United Kingdom, Ireland, Portugal, Spain, Italy, Greece, Czech Republic, Slovakia, Hungary, and Poland. Intrum AB (publ) was founded in 1923 and is based in Stockholm, Sweden.
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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.