Harnessing Uncertainty: The Future of Risk Analytics

The increasingly complex and global nature of enterprises and of their activities, i.e. global supply chains, cross-border financial activity, services outsourcing etc., is accompanied by increasing levels of economic uncertainty, greater regulatory controls, and higher dependence on information technologies to conduct business. The combined effect of these factors is an increased exposure to events having the potential to severely impact operations of an enterprise, as well as the operations of enterprises with which they interact. At the same time, greater visibility to such factors can provide opportunity to use the uncertainty for strategic gain. This potential for both risk exposure and risk opportunity highlights the importance of a systematic and integrated approach to risk management. While myriad risk modeling methods and tools exist today, current methods do not fully address the challenges arising in developing end-to-end, integrated risk management systems which span risk data collection and management, development of flexible, scaleable risk models that can capture dependencies across multiple systems, and risk information presentation and interaction for ongoing, dynamic decision support. The purpose of this paper is to outline IBM Research’s point of view on integrated risk management, delineating existing risk analytics capabilities and presenting strategic initiatives to address outstanding scientific challenges.

By: Bonnie Ray; Chid Apte; Kevin McAuliffe, Lea Deleris; Eric Cope

Published in: RC24534 in 2008


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