While it's no secret that the key to operational efficiency is streamlined data management, investment management companies continue to struggle with maintaining consistent and accurate data. There are a number of approaches for improving data quality, however centralizing data and establishing one common database has proven to be the most effective model.
It's not uncommon for financial institutions to manage numerous data sources in various databases throughout their enterprise. In many cases, companies maintain best-of-breed systems, which offer little or no control over maintaining and auditing the data, which ultimately results in poor quality. As business groups lose faith in their company's ability to effectively manage and distribute accurate data, they begin to build their own databases and maintain the data needed to support their business decisions.
In this scenario, organizations treat systems and databases as "islands of technology" (non-streamlined systems) " following the standard accounting-centric model. This is problematic on several levels. With no overall information architecture, a duplication of effort results by data being maintained in multiple application-specific databases and systems. This creates a costly overhead, as resources are devoted to maintaining and managing information in an often manual process. This silo-management of data dramatically increases the probability of data inconsistency across databases resulting in reporting discrepancies between business groups. Additionally, inadequate quality controls and limited auditing capabilities may not uncover a problem in a timely manner, resulting in significant cost implications. Data-centric Approach
Various departments within a financial institution, from trading in the front office all the way through to settlement and accounting in the back office, manage and share security reference data. Since security reference data impacts all areas of the investment management process, the most logical data management approach is to centralize data within an organization's architecture. In doing this, an organization achieves several benefits:
- Cost Savings " By eliminating silo-management of security reference data, a single point of entry is introduced for data feeds. This allows changes from data vendors to be implemented once, rather than in multiple instances. Additionally, with data management centralized, costs attributed to vendor relationships are better controlled, minimizing any redundancy in market data contracts and their associated costs.
- Decreased Risk " With centralized data management, all edits and manipulations to core data are housed and stored centrally. This model allows for staunch controls, detailed audit trails, and enables business users to access consistent data.
- Data Consistency " When data feeds are managed in a central repository, an organization can achieve consistent data management and distribution throughout its global offices and internal systems. Once data is brought into the data repository, the data can then be scrubbed, validated, and readied for distribution throughout an enterprise.
- Data Quality " A data-centric approach enables the establishment of a data standard across an enterprise, allowing organizations to make better business assessments.
- Operational Efficiency " When one business unit controls an organization's data centrally, the resources previously devoted to data management can be redirected back to core business needs. Additionally, organizations can eliminate manual processing of data, which in turn reduces the risks of making poor business decisions.
Gain Control of Your Data
Eagle has approached the management of data from a data-centric approach. Eagle Reference Manager is a powerful Web-based data consolidation, validation, and dissemination solution that enables organizations to streamline the management of security reference data throughout its global offices. By centralizing the management of security reference data, organizations can provide clean, consistent data that can improve decision-making, reduce data processing timeframes, and manage data errors through exception-based management tools. Eagle Reference Manager enables an organization to lower the total cost of ownership associated with the management of security reference data and further support its efforts to achieve improved operational efficiencies.
About Eagle Investment Systems Corp.
Eagle, a Mellon Financial CompanySM, is a global provider of financial services technology. Eagle's Web-based systems automate internal systems to support STP requirements of money managers, mutual funds, hedge funds, brokers, plan sponsors, banks, corporate trusts, and insurance companies. Eagle provides solutions for portfolio management, investment accounting, performance measurement, attribution, AIMR/GIPS compliance, reporting, messaging, reference data management, and outsourcing. To learn more about Eagle's solutions, contact us at 1.800.810.3819 or firstname.lastname@example.org or visit www.eagleinvsys.com.
Five steps to improved data
- Security master files are loaded into the data repository history tables.
- Once in the repository history, a composite source record is built by applying user-defined rules that define the source hierarchy.
- Data is then scrubbed and validated on three user-defined levels in a separate staging area.
- Appropriate data is released into the production data repository and disseminated to downstream systems.
- Erroneous data is sent to a workflow queue for correction and resubmission and dissemination.
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