Risks exist in every aspect of our lives and risk management has always been a vital topic. Most computational techniques and tools have been used for optimizing risk management and the risk management tools benefit from computational approaches. Computational intelligence models such as neural networks and support vector machine have been widely used for early warning of company bankruptcy and credit risk rating, operational research approaches such as VaR (value at risk) optimization has been standardized in managing markets and credit risk, agent-based theories are employed in supply chain risk management and various simulation techniques are employed by researchers working on problems of environmental risk management and disaster risk management. Investigation of computational tools in risk management is beneficial to both practitioners and researchers. The Computational Risk Management series is a high-quality research book series with an emphasis on computational aspects of risk management and analysis. In this series research monographs, conference proceedings are published.

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Papers should be submitted via online submission system ( click here   http://risklab.utoronto.ca/springer )

All questions can go to Christine: huixia.guo@utoronto.ca or dexter@mie.utoronto.ca