![]() There are several approaches to making optimal decisions in Bayes Server.įor example, they allow us to determine the optimal strategy (set of policies) for managing risk. How to make optimal risk-based decisions? ![]() Sensitivity analysis (parameters or evidence input).Support advanced analysis and diagnostics.Optionally allow us to optimize decisions based on costs/rewards (utilities) or using Evidence optimization.Can be built from Expert opinion and/or data.Designed specifically to natively handle uncertainty.Causal models - Naturally model cause and effect.Bayesian networks are a natural framework for managing uncertainty. ISO 31000 defines risk as the effect of uncertainty on objectives. Essentially they maintain a list, which is not much more sophisticated than a shopping list.Įach item in the list typically contains the following information: Many companies still take a simplistic approach to risk management. Quantitative - a model is used, allowing for more sophisticated analyses.Even though they may have a priority, the risks are not combined in any sophisticated way. Qualitative - methods which do not use a model.There are many different approaches to risk management. Controls that are put in place before events occur are called 'Proactive' or 'Preventative' whereas those that limit the loss (or protect the reward) are called 'Reactive' controls. Prevention and cure Ĭontrols (mediation) can limit the negative impact (or protect the upside) of risks. However both types of risk can potentially be mitigated. Risks typically fall into one of two categories those that are fully or partially under our control and those that aren't. Market Risk (also known as systematic risk).Credit Risk (also known as Default Risk).We will not cover the full range of risks that companies model, however it is interesting to note that it is not uncommon for sophisticated financial institutions to model between 50-100 different types of risks. As well as avoiding loss, risk models are also used to maximize the chance of realizing opportunities.
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