For decades, investors have sought to combine the flexibility of stochastic scenario modeling with the efficiency of closed-form optimizers, especially for complex objectives like PVDE.

Ortec Finance’s new Scenario-Based Machine Learning (SBML) approach addresses this, using AI to optimize nearly any risk-return objective within a stochastic framework. By training an “AI investment agent” on thousands of simulated scenarios, SBML identifies high-performing portfolios that traditional methods might miss.

This whitepaper dives into how AI is revolutionizing scenario analysis techniques, transforming the stochastic scenario approach—a backbone of investment decision-making for decades—and enabling smarter, faster, and more strategic decisions across industries like pensions, private wealth, and insurance.

Download the whitepaper ‘How AI can help manage insurance portfolios’

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