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White Paper

Cloud Solutions for Centralized Reference Data Management

 

Due to the repercussions of the global financial crisis, most banking and financial institutions are seeking innovative ways to improve efficiencies and contain costs. Reference data management (RDM) currently revolves around data quality, integration between data elements and flexibility to meet regulatory demands. The concept of a single or centralized reference data platform was triggered by the need to reduce manual intervention, speed up the on-boarding process, simplify risk analysis, expedite regulatory reporting and improve automation.

Today, managing reference and master data offers no differentiation and there is no competitive cost advantage in maintaining systems separately and liaising with multiple entities such as data vendors, technology vendors, internal IT teams and client teams. Despite use of improper reference data resulting in fixes on trade data, many capital market firms consider the cost of maintaining reference data within the firm as an unnecessary overhead. As a result, capital market firms are adopting a platform based approach for RDM that has resulted in increased process efficiencies though no measures have been initiated to improve the data quality.

Despite having failed to address data quality issues, many data vendors and technology solution providers are offering a flexible approach to RDM, as the demand for a centralized utility for data management grows. In the interim, firms need to explore options to adopt next generation technology services such as RDM as a service (managed service model) and cloud or data virtualization techniques. One option is to adopt a cloud-based centralized enterprise data management solution that ensures improved risk management, regulatory compliance and maximizes operational efficiency across the enterprise.

In this white paper, we talk about how financial institutions are evaluating the option of cloud-based hosting, maintenance, monitoring, and support of reference data systems in an attempt to understand if it can result in improved cost and operational efficiencies. The objective is to explore the options of promoting on-demand data sharing between trading, sales, reference data, market data and financial control systems.