Source: Ness Technologies
Ness Technologies (NASDAQ: NSTC), a global provider of IT services and solutions, today announced that it will launch a new enhanced version of Financial Data Enterprise (FDE) at FIMA 2006 (Europe).
FDE is an enterprise reference data management platform developed by Ness Innovative Business Services (Ness IBS) to efficiently address the reference data needs of global financial institutions.
A cost-effective, flexible solution, FDE allows financial institutions to take complete control of their enterprise data by automating end-to-end acquisition, management and distribution of reference data. FDE acts as a transformation and enrichment hub that consolidates all disparate data sources leveraging its intelligent and dynamic metadata layer and delivers data to end users, systems and value-chain participants. FDE ensures that the data that drives performance attributions, risk analysis, pricing, research, fund accounting and customer servicing and other mission-critical applications is clean, complete and consistent.
The new version, FDE 3.0, includes new features such as enhanced data acquisition interface allowing users to dynamically map, cleanse and transform incoming data from various formats to the user's underlying database model. In addition, FDE 3.0 includes improved exceptions and workflow management interface as well as a new extraction rules engine providing rules-driven golden copy generation and distribution.
"The new version enhances data acquisition, management and distribution, leading to increased productivity and improved performance," said Rajkumar Velagapudi, President of Ness IBS. "It reduces data sourcing costs and eliminates downstream needs for validation and exception management, thus saving time and administration costs, meeting the critical needs of financial institutions. The combination of FDE 3.0 with Ness' EnVue Analytical Platform 2.5 enables financial institutions, especially wealth managers, financial advisors and fund managers, to review and distribute detailed performance data near-real-time."