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The Actuary The magazine of the Institute & Faculty of Actuaries

Complexity the key to simplifying risk

Applying the science of complexity and complex adaptive systems can provide a greater understanding of risk appetite and emerging risk, according to research from the Actuarial Profession.

The findings of the study, carried out by Neil Cantle of Milliman and Neil Allan of the University of Bath, were presented at the Profession’s Risk and Investment Conference in Gateshead yesterday.

The research focuses on two key problems in risk management: the setting of risk appetite with a consistent set of risk limits, and the timely identification and understanding of emerging risk.

Mr Cantle described risk as an evolutionary process and claimed that, by applying insights from other sciences, such as biology, it is possible to study more clearly how risks emerge and how they may develop in future.

"Complex adaptive systems are diverse and made up of multiple, interconnected elements yet are adaptive in that they have the capacity to respond and evolve as they interact with their surroundings," he said.

"They can exist in the natural world - ant colonies, cells or ecosystems, for example, and in the man-made world, especially in terms of what we might term joint human endeavour, such as a business.

"If we treat companies as complex adaptive systems and their risks as their unintended emergent properties, it is possible to apply a range of tools developed for studying emergent phenomena which arise through the complex interactions of multiple factors. These can help us to spot the early signatures of trouble before they become apparent in headline observations."

Mr Cantle went on to explain that, by using a systems approach to risk appetite, it is possible to understand how risk dynamics behave and build a structural model of the risk using a Bayesian Network.

"This not only permits the setting of limits but the same tool can be used to monitor compliance with overall risk appetite," he said. "It has the capability of learning from new data which means that the monitoring adapts naturally as the risk dynamics change.

"The solutions proposed can be applied to any industry and size of company and play to actuaries’ strengths in making sense of uncertain future developments."