Risk Management Using B ayesian Networks
Martin Neil, Norman Fenton · Wiley StatsRef: Statistics Reference Online · 2017
Abstract Bayesian networks (BNs) can be used to model risk in situations where data is scarce but where casual knowledge and expert estimation is available. The graphical part of a BN is used to model the causes and consequences of risk, hence enabling better management and intervention, while subjective probabilities are exploited, along with BN computation algorithms, to calculate risk. Risk measurement is therefore more meaningful in the decision context and the results easier to check and verify in practice by decision makers.