The 2007-9 crisis has exposed the issue of reliability in mathematical risk quantification and highlighted the importance of taking measurement uncertainty into account when measuring and reporting risk and the subsequent decision-making process. It is essential that risk managers rethink the way they measure and control risk in order to avoid another industry shattering crisis. Uncertainty of risk figures needs to be better understood and expert judgement needs to be absorbed into the fabric of risk management. Rethinking Risk Measurement and Reporting contains the leading techniques and tools that the risk management industry will need to make the step towards a more effective risk management framework.

Both volumes of Rethinking Risk Measurement and Reporting provide critical reviews of standard risk models used in practice, useful techniques to assess model uncertainty such as expert judgement and tools that allow you to analyze the impact of this uncertainty on the final result; typically a risk figure that is used in risk control, risk management or decision making. Emphasis is given to Bayesian methods, by which it is possible to analyze model uncertainty in a statistically sound and efficient way.

The two volumes present practical examples relating to risk types and, in addition, you the reader will gain an overall picture of a ‘complete’, improved risk management framework:

- An Introduction to Bayesian Analysis
- Expert Judgement
- Credit Risk
- Operational Risk
- Market Risk and Time Series Analysis
- Stress Testing and Risk Aggregation
- Asset Allocation
- Reporting, Decision Making and Regulation