Risiki

Risiki is a term used in risk theory to denote an integrative measure of risk exposure in complex systems. It refers to the combined effect of multiple interacting risk factors, where the joint probability of adverse outcomes cannot be inferred from marginal risks alone. In explanatory use, risiki emphasizes systemic and cascading risks arising from interdependencies among components of a network, such as financial markets, supply chains, or critical infrastructure.

The concept has been described as a framework rather than a single metric. Proponents propose calculating risiki with a multi-step process: identify risk factors, model their marginal distributions, and characterize dependencies using copulas or network-based connections. Simulation methods, including Monte Carlo, are commonly employed to estimate distributions of aggregate loss or impact. The resulting risiki score can be decomposed into a base risk level plus interaction terms that reflect synergies and amplification effects.

Applications span finance, manufacturing, climate and disaster planning, cybersecurity, and public health. In practice, risiki supports stress testing, contingency planning, and resilience assessment by highlighting potential tipping points and vulnerable links in a system.

Critics argue that the approach can be data-intensive and sensitive to model specification. They caution against over-interpretation of interaction terms without robust validation. Nevertheless, risiki remains a topic of interest in discussions of systemic risk and resilience.