Posted on 13 Jan 2009
Willis Re Inc., the U.S. reinsurance arm of global broker Willis Group Holdings (NYSE: WSH), today announced the launch of Willis conNextTM – a web-based portfolio management and risk analysis platform that empowers analysts, risk managers and corporate executives to quantify exposure, evaluate underwriting effectiveness, and plan for catastrophic events.
With Willis conNext, companies no longer need numerous distinct products or solutions to provide mapping, reporting, analysis, and performance monitoring. With a scalable architecture and a consolidated data source for exposure and modeled loss, users can navigate seamlessly from dashboards to scorecards, and to detailed reports and analysis, without being forced to access multiple tools or systems or manage integration of dissimilar systems. Willis conNext connects people, technology, strategic planning and risk management in one integrated system.
“By harnessing the power of our proprietary analytical tools as well as the latest technology and modeling science, Willis conNext provides our clients with new capabilities to evaluate, set and monitor portfolio strategies over varying time spans, while managing to the objectives of their Enterprise Risk Management programs,” said Peter Hearn, CEO, Willis Re. “Willis conNext is a dynamic, next-generation solution that meets our clients’ increasingly complex requirements for data management and related analytics and helps our clients make sound, fact-based risk-management decisions.”
Willis Analytics has long been known for providing its clients with advanced and innovative capabilities for Catastrophe Risk Management. Willis conNext represents the next stage in Willis Analytics’ continuing evolution. Key capabilities of Willis conNext include:
* Enterprise Data Mining and Reporting – Willis conNext offers outstanding drill- anywhere data capabilities, and both pre-compiled and user-defined ad hoc reports.
1. Reporting capabilities designed to enhance clients’ ability to proactively establish optimal strategies, evaluate and compare exposure to risk and measure profitability across a myriad of user-defined categories, including geographic territory, line / class of business, and profit-center / underwriter;
2. Detail on Demand™, a user-friendly, interactive tool that enables clients to pinpoint the lowest level of policy and location data to identify relationships between key risk drivers;
3. Standard-setting data mining capabilities, including QuickQuery™, a dynamic tool that allows clients to create customized views based on user-defined criteria of their online data without the need to re-query the database or request a new report.
* Visual Communication – Integrated data mining, rich charting and robust mapping capabilities provide for a dynamic risk intelligence platform.
1. Sophisticated integration of Geographic Information Systems (GIS) provides an intuitive platform to view concentrations of exposure and correlated loss distribution on a map. Interactive web capabilities allow the user to drill into the map and data to retrieve aggregate or policy-level detail;
2. Charting and profiling tools provide a library of enhanced visualizations of high- resolution data and metrics. User-specified metrics display in charts and maps to provide a multi-dimensional point of view for risk assessment;
3. Collaboration tools promote clients’ ability to easily create and customize on-line reports and share them across all levels of their organization – from the Corporate Executive to the Underwriter – as well as with their Willis Re partners.
Julie Serakos, Executive Vice President and head of Catastrophe Modeling Services for Willis Re, said, “Willis conNext dramatically improves the ability of Willis Re’s clients to manage risk prudently. Sophisticated data profiles generated by this application become the principal method of communication between Willis Re and its business partners for property and casualty risk management. With its advanced data mining and analysis capabilities, Willis conNext helps our clients save time, act faster and make more profitable decisions by assessing the correlations between exposure and modeled loss results.”