Reference Data Management
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Asset Management Reference Data Management

As financial institutions seek to rationalize and re-architect their reference data management (RDM) and master data management (MDM) environments, they rely on timely access to reliable and relevant data to make strategic investment decisions. New regulations also elevate the need for scalable and flexible RDM solutions.

NIIT Technologies has proven capabilities in managing entire RDM environments and meeting evolving data requirements. Our on-demand utility service model is a cost-variable data management solution that includes a platform and infrastructure services and operations, providing flexible end-to-end solutions. Through this model, you can achieve cost reduction for reference and master data, as well as enable the transformation of inaccurate data into useful clean, rules-driven, and enterprise-wide information. The model provides architectural and process workflow improvements and recommendations, along with cost/benefit analysis.

Our innovative approach provides methodologies; proprietary software tools, including extract, transform, and load (ETL); and third-party products that will help you leverage your enterprise data in a way that propels you toward your business goals. Our expertise and experience in implementing data management solutions will allow you to cut costs and transform your data, while retaining full control over the process.

Key Features

  • On-demand utility service, including:

    • Industry-leading data management platform
    • Certified infrastructure for hosting
    • Optimized lean operations
  • Golden copy of data and customized reports for data and business users

  • Matured service adoption strategy, covering:

    • Readiness assessment
    • Platform configuration
    • Onboarding
    • Steady-state operations

Business Benefits

  • On-demand utility service with a pay-per-use pricing structure
  • Access to a copy of data at a fixed price
  • Leverage proprietary framework for continuous improvements
  • Process optimization gains through process reengineering and automation
  • Significant time savings through proprietary tools, frameworks, knowledge, and experience
  • Operational efficiency, accuracy, data integrity

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