The enhancement enables risk managers to implement more robust oversight of the underlying risk factors driving their risk models.

The quality and completeness of the input data used in risk management is of increasing interest to regulators, auditors, senior management and clients. The market is now much more conscious of the fact that risk reports and analytics are only as good as the quality of the data they are based upon. Risk management needs a firm data foundation to build models upon, and desktop-based approaches to data management for risk are not robust enough to deal with ever-increasing reporting demands. Risk managers need tools that can automate the validation process and allow them to understand the data being used more quickly.

The new Risk Factor Management module in TimeScape allows easy definition of individual risk factors from formulas combining raw market data series, assignment of risk factor to groups, viewing of a factor's participation in collections and categorization of factors by dimensions such as industry, currency, rating, region or tenor. Risk factors can then be passed through automated validation processes and data exceptions investigated and corrected, before feeding downstream risk management and modelling systems. Risk factors can also be viewed and analysed in a variety of charts, reports and heatmaps to get both a high level and granular view of the data being used.

"Using consistent and high quality risk factor data provides a solid foundation for building robust auditable risk modelling and reporting," says Brian Sentance, CEO, Xenomorph. "The principles of consistency, quality and auditability found within data management need to be extended further through the business workflow. This new release is a great illustration of how this philosophy is benefiting our clients."