In-depth analysis showing the identification and quantification of exposure to financial risk has become more accessible...

Value at risk analysis, which has become available through increased computing power, is now easier to implement and can cater for extreme market conditions.

Monte Carlo analysis is a modelling technique which can be applied to financial analysis, allowing thousands of variables to be integrated together to show standard behaviours and outlier abnormalities requiring detailed understanding in a 'what if?' environment.

Sensitivity analysis involves checking the performance of a financial risk model against the various interrelationships between the different input variables in the model.

Simulation, which is becoming available through standard computing packages, is complex to implement but dynamic and adaptable to cater for different assumptions.

Regression analysis is easy to understand and implement, and based on future expectations.