Unipr AI Agents

THE PROBLEM:

You're defending a $300M portfolio allocation with wildly different risk profiles—early discovery programs, late-stage pivots, platform investments, acquisitions. The board wants to know: What's the probability we hit $500M revenue? What if the Phase 3 fails? How correlated are these investments? Finance wants NPV projections. Investors want Monte Carlo simulations showing downside scenarios. Your spreadsheets show static point estimates that ignore technical risk, market uncertainty, and correlation effects. Leadership needs credible financial intelligence to make billion-dollar decisions, not back-of-envelope calculations.

WHAT FINANCIER DELIVERS:

• Risk-Adjusted NPV Modeling – Calculates rNPV with stage-gate probabilities across technical, regulatory, and commercial milestones—not blind NPV optimism.
• Monte Carlo Simulation – Quantifies uncertainty with probability distributions showing best-case, worst-case, and most-likely scenarios across thousands of iterations.
• Portfolio Correlation Analysis – Identifies which projects move together and which provide true diversification—optimizing risk-adjusted returns.
• Competitive Benchmarking – Grounds valuations in recent deal comparables, market multiples, and acquisition precedents from your therapeutic areas.

THE OUTCOME:

Board meetings shift from defending assumptions to discussing strategy. Your investment committee sees the 20% probability scenario alongside the 80% scenario—making decisions with eyes open. Portfolio allocation is optimized for risk-adjusted returns, not gut feel. When acquisitions are proposed, you evaluate them with the same rigor as internal programs. Capital flows to opportunities with the best risk-return profiles.

WHO FINANCIER HELPS:

Portfolio VPs and CFOs allocating capital across uncertain investments who need financial models that quantify risk with market intelligence—not hide it with static assumptions.