Using a combination of existing and innovative new software components, 'Right Time' offers financial institutions the ability to measure and manage risk 'on-demand' and in a continuous simulation setting, both at the enterprise and at the desk level.

The breadth and capability of the 'Right Time' approach enables banks to use the most appropriate technology for their business objectives. Complementing a proven architecture that enables strategic decision-making at the enterprise level, the 'Right Time' continuous simulation framework now allows financial institutions to better support considered risk-taking, financial product development and effective control in dynamic and evolving financial markets.

Dr. Michael Zerbs, President & COO of Algorithmics, said "Turbulent markets have demonstrated that it is essential for financial institutions to proactively measure and manage risk quickly and accurately. The 'Right Time' approach enables evaluation of market and credit risk 'on-demand', at a transaction, counterparty or portfolio level. As the trend to transform credit risk into tradable market risk grows, the ability to accurately price and comprehensively understand the risk and return at the time of the transaction becomes paramount."

Dr. Andrew Aziz, Executive Vice President, Risk Solutions at Algorithmics added, "Clients increasingly want access to greater analytic flexibility at the individual desk level and to be able to make trading decisions based on full knowledge of the risk profile of the transaction and counterparty. Through event-driven simulation, combined with a dramatic increase in the speed of calculation, we are able to deliver a radical advance that is especially relevant for counterparty credit risk in the trading book. This is what we call 'Right Time' risk management."

The 'Right Time' approach builds on Algorithmics' successful Mark-to-Future framework and on other significant innovations recently introduced as discrete products. Together they offer a truly interactive risk management solution, ultimately leading to a comprehensive financial engineering workbench. Already available are:

• A powerful user application which supports the analysis of portfolios and a variety of what-if capabilities including proposed transactions and changes, real or hypothetical in market conditions,
• An Accelerated Analytics programme and 'on-demand' continuous simulation, which revolutionises the calculation time for a variety of financial instruments, massively reducing hardware requirements for large counterparty credit simulations and reducing processing to a fraction of the time otherwise required,
• A high volume, real-time trading, counterparty exposure simulation solution with full netting and collateral, and excess management for e-commerce platforms,
• A collection of excess, limit management and business process tools which prompt end users when events occur that impact credit controls, allowing them to take timely and appropriate action.

The 'Right Time' approach has been developed with interoperability as a major architectural consideration. It can be deployed alone or together with third party application components, proprietary client systems and other Algorithmics products to provide customers with a comprehensive solution to their specific requirements.

The 'Right Time' approach offers the ability for end users to take control, delivering access to the most up to date information on which to base decisions. By incorporating a 'Choose As You Go' dynamic configuration, users can decide how, what and when they calculate; each user can trigger 'on-demand' simulations using user-defined Monte Carlo simulations, stress tests, and what-if scenarios for their own book, at the portfolio, or even at the enterprise level. The full power of Algorithmics' analytical and simulation engines is being brought to the desks of end users in new ways. The 'Right Time' architecture will provide risk managers and analysts with interactive tools to be able to model products, construct scenarios, and perform wide-ranging what-if tests.