The mathematical foundation for how the world's largest banks calculate their safety buffers is wrong by 41 percent.
Standard Gaussian risk models used for global bank capital requirements systematically understate the frequency of a total market collapse. These models assume that market movements follow a normal bell curve, but reality follows a much more volatile fractal dynamic. This error means the safety buffers designed to prevent the next financial crisis are 41 percent thinner than they should be. Most people believe that the math behind bank regulation is a solid foundation for the global economy. This research reveals that the largest financial institutions are operating on a dangerously optimistic set of equations.
Risk Intelligence — A New Era for Institutional Finance
SSRN · 6615841
This paper presents a unified institutional risk intelligence framework combining Mandelbrot's Multifractal Model of Asset Returns (MMAR), LLM orchestration via Model Context Protocol (MCP), and a federated three-tier sovereign architecture for deployment at CCPs, custodians, SIFIs, pension funds, and regulators. The framework rests on three claims. First, Fractal Precision: Gaussian risk models systematically understate institutional tail risk — the ten-day VaR multiplier under empirically cali