by Angela Guess
A new paper by Algorithmics “sets out the case for an integrated data-oriented approach to risk management, and outlines the practical steps risk IT professionals can take to achieve this… The paper provides insight into risk-specific data issues, such as the use of shared architectural foundations for marshalling data into risk analytics systems for end-to-end risk management.”
Entitled “Data management for risk management: the importance of data-oriented systems,” the paper “outlines how centralizing risk data collection facilitates the most efficient validation and normalization, enabling risk managers to do more with the data that already exists across the organization. Only such an approach makes it feasible for calculation results and stress tests to accurately reflect the interdependence between different risk types.”
Neil Bartlett, Chief Technology Officer of Algorithmics noted, “Continuing to manage data in a siloed risk environment is simply not a feasible option; using an integrated, data-oriented system is fundamental to enterprise risk management and tackles financial institutions other important business needs, including the minimization of operational risk. In such a system, all calculations are driven from a centralized data source, providing consistency, timeliness, minimization of workloads, and elimination of the errors that manual processes typically produce. The benefit is less time spent on data management, and more time spent on adding value to the business across all aspects of enterprise risk management.”
The paper is available for download here.
