Traditional risk systems fail when markets shift. They rely on fixed thresholds calibrated to historical data, leaving funds exposed when volatility spikes or regimes change. Most systems use simple VaR models with hardcoded stop-loss percentages that do not adapt to real-time conditions. The result is capital destruction during bear markets, missed opportunities during favorable conditions, and overfitting that breaks when market structure changes. Funds need risk management that thinks ahead, adapts continuously, and preserves capital when it matters most, without relying on machine learning models that overfit to past data. Traditional risk systems fail to adapt when market structure changes. Funds require forward-looking risk intelligence that preserves capital during stress without relying on execution or discretionary intervention.