Scenario-Driven Modeling Supports Complex PE Carve-Out
QuantFi partnered with a PE sponsor on a carve-out from a global financial institution, delivering scenario-driven modeling to optimize structure, quantify risk, and drive investment conviction.
🧩 The Problem
QuantFi built and maintained a dynamic deal model that incorporated:
- Multiple operating scenarios (Base, Upside, Downside) to evaluate sensitivities in topline recovery, margin expansion, and synergies.
- Flexible capital structure modules to toggle between debt sizing options, interest rates, and repayment profiles.
- Return waterfalls modeling gross and net IRR/MOIC across sponsor, management, and co-investor tranches.
- A standalone cost model to isolate stranded overhead and estimate true go-forward economics.
QuantFi worked directly with deal leads, bankers, and operating partners to update the model in real time during exclusivity.
💡 QuantFi's Solution
QuantFi built and maintained a dynamic deal model that incorporated:
- Multiple operating scenarios (Base, Upside, Downside) to evaluate sensitivities in topline recovery, margin expansion, and synergies.
- Flexible capital structure modules to toggle between debt sizing options, interest rates, and repayment profiles.
- Return waterfalls modeling gross and net IRR/MOIC across sponsor, management, and co-investor tranches.
- A standalone cost model to isolate stranded overhead and estimate true go-forward economics.
QuantFi worked directly with deal leads, bankers, and operating partners to update the model in real time during exclusivity.
🚀 The Results
The sponsor was able to confidently underwrite the transaction with a balanced capital structure and a clear view of both downside protection and upside optionality. The model became the central source of truth for IC presentations, lender discussions, and management alignment.
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Scenario-Driven Modeling Supports Complex PE Carve-Out
QuantFi partnered with a PE sponsor on a carve-out from a global financial institution, delivering scenario-driven modeling to optimize structure, quantify risk, and drive investment conviction.
