Classifying & Managing Risk: The RATIFI Project

Abstract

There are major benefits to be exploited in Safety Science by advances in information processing under uncertainty, particularly in cost/benefit optimisation scenarios. Information processing under uncertainty is not a problem which must draw upon mathematics alone for solutions — an interdisciplinary approach which reviews the philosophies behind the mathematical paradigms traditionally applied, and borrows techniques from Physics, Computing and Social Science, has much to offer. This paper aims to review the more traditional processing and modelling methods used, and then moves on to outline a modified approach. There is a legacy problem in that the different disciplines which need improved techniques for this task are grouped along a qualitative/quantitative divide, and seldom take advantage of the considerable benefits of pooling their approaches to gain a broader understanding of their problems. For example, insurers are steeped in statistics which prove highly effective in predicting fixture claims in stable times, but can lead to substantial losses when trends change abruptly. An understanding of the underlying factors influencing insurance markets is required for a rapid reassessment.