The Thesis: Off-the-shelf APIs and generic AI models create “signal leakage.” To maintain an edge, enterprises require bespoke predictive modeling that integrates unique sector-specific data.
Predictive modeling has become a buzzword, but for the $100M+ allocator, the distinction between “generic” and “bespoke” is the difference between profit and noise. Most available models suffer from signal leakage—the same data being sold to thousands of retail traders simultaneously.
Numin’s edge is built on institutional-only delivery. We utilize alternative data—from satellite imagery for mining exploration to sentiment streams for tech sectors—to build probabilistic forecasts. Our models aren’t “black boxes”; they are mathematical frameworks designed to support effective, data-driven decision-making in real-time.
Whether it is for commodity collateralized lending or hedge fund strategy, predictive modeling must be iterative. Static models are dead. By iterating daily, we capture the “convexity” of the market, allowing our clients to see shifts in the landscape days or weeks before they manifest in public API feeds.