Tools for Risk Prediction

There are various tools for risk prediction, ranging from complex mathematical models to a less complicated Event Tree Analysis. The following section provides a description of two types of risk prediction tools Data Mining and Failure Mode Effect Analysis (FMEA)  

Risk in general is a term attributable to future loss, and risk management is attributed to the process and resources utilised in order to control the loss (Haimowitz and Key 2002). Hence, the more relevant issue is to ascertain whether the future predictable losses are controllable. In order to predict the losses and reduce the uncertainty it is necessary to be able to look into the future based upon 

The role of data mining is to analyse historical data, to improve prediction capability. Some of the common analytic approaches used by data miners are  

Estimation of the parameters of past performance Means, Standard deviations, Correlations, and Associations for hypothesis testing 

Classification Segmentation, or Clustering of data units to facihtate the modelling process 

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