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In the past decades, risk management in the financial community has been dominated by data-intensive statistical methods which rely on short historical time series to estimate future risk. Many observers consider this approach as a contributor to the current financial crisis, as a long period of low volatility gave rise to an illusion of control from the perspectives of both regulators and the regulated. The crucial question is whether there is an alternative. There are voices which claim that there is no reliable way to detect bubbles, and that crashes can be modeled as exogenous "black swans". Others claim that "dragon kings", or crashes which result from endogenous dynamics, can be understood and therefore be predicted, at least in principle. The authors suggest that the concept of "Bayesian risk management" may efficiently mobilize the knowledge, comprehension, and experience of experts in order to understand what happens in financial markets.
Increasing resource efficiency can potentially deliver important economic and environmental benefits. Many of these benefits are regularly foregone because the financial sector's capacity to adequately take the opportunities and risks arising from resource utilization and related climate change aspects into account has so far remained relatively undeveloped. Focusing on the case of Germany, a number of barriers to the inclusion of resource efficiency and climate change aspects into financial services' considerations are presented. Corresponding measures for improving the capacity of the financial sector to better integrate resource efficiency considerations and climate change related risks into its operating procedures are introduced. The measures encompass the areas of risk controlling, company reporting, institutional reporting requirements, as well as additional supporting measures.