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Solving the reference data disconnect: Capital markets survey

We surveyed buy- and sell-side professionals globally to better understand the reference data disconnect.

Overview

Firms are spending millions of dollars on reference data from multiple sources in disparate formats, which requires continuous cleansing and reconciliation. Despite significant effort and expense, these problems have not been resolved, and in fact, seem to be getting worse.

Accenture undertook a study in partnership with Greenwich Associates to better understand this problem. We interviewed 133 buy- and sell-side professionals globally to determine where the reference data disconnect lies and what can be done to set firms on the right path.

We reveal the findings in this report.

Key Findings

Our study uncovered challenges across four key themes that were consistently identified throughout all survey demographics:

Quality
Despite significant investments in time and money, quality issues continue to plague the industry.

Costs
Shrinking margins require increasingly creative approaches to managing costs.

Control
Regulatory requirements are driving ever-increasing burdens for proving effective control processes.

Change
Firms continually struggle with balancing streamlining business operations while responding to continual industry change.

Of these four themes, costs and quality were by far the dominant issues across the enterprise. In fact, 70 percent of respondents cite data quality as one of their most pressing issues and a concern that clearly affects costs. When it comes to costs, respondents highlighted three categories of costs that were of concerns: internal, external, and infrastructure and platform costs.

Paul Obrocki
Senior Principal,
Accenture Global Data Management Lead
The haphazard approach to data management is clearly highlighted by quality and cost challenges.

Recommendations

What can and should be done?

Define the data vision

  • Establish a strategic vision for what data is required to support the company strategy, how data will be managed by the business and how it will be enabled by technology

  • Champion and encourage awareness of the true cost and effective use of data across the company

  • Identify data which could be acquired to create value

Establish data policy and governance

  • Set a policy which will allow the company to comply with data-related regulation (ensuring legal/compliance responsibilities are clear)

  • Embed and enforce the data policy through processes

Deliver data fixes and a delivery program

  • Deliver data architecture components

  • Deliver large data-related programs

  • Deliver value added data remediation

Establish data services for the business

  • Provide data quality management services

  • Facilitate data exploitation

  • Improve enterprise knowledge about data assets available