Babylon Pump & Power Ltd (BPP) Fair Value & Analysis
Industrials · AU · Market cap A$9.8M
Fair value as of: Jun 24, 2026
Analysis
Babylon Pump & Power Ltd (BPP) currently trades at A$0.0775, while our model-based Fair Value estimate is A$0.1300 — implying the stock looks roughly 67.7% 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
Babylon Pump & Power Ltd provides specialty mining services to the resources sector in Australia. It operates through two segments: Rental and Maintenance. The company offers high-pressure pumping, dewatering and project water management with supplying and maintaining equipment in remote and offshore locations. It also provides a full range of speciality power generation solutions, including system design, installation, commissioning, operations and maintenance services; and full maintenance and asset management services for high-horsepower mobile equipment, including engines, power train assemblies and components. In addition, the company offers dewatering; bore test pumping; vacuum loading, blast, and paint; and mobile and ancillary plant equipment. Further, the company provides rebuilding and maintenance services for diesel-driven equipment; field services work; and water blasting and ancillary services to the resources sectors. The company was formerly known as IM Medical Limite…
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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.