For asset managers, the processes and resources devoted to data management have evolved in the last decade. Thanks go to: better technology, increased budgets and executive level support. That said, today, effective data management is a must for the asset management industry. Consider the following:

  • Dodd-Frank and other wide-reaching regulations mandate investment firms to provide more detail than ever about their holdings and risk exposures.
  • Institutional clients have sophisticated requirements in areas of risk management that call for transparency and access to data.
  • Expansion of outsourcing investment and back-office functions requires seamless sharing of data within daily trading sessions.
  • The use of analytics and proprietary algorithms to make big bets are based on accurate and timely data.

Portfolio managers rely on accurate information delivered to their screens each morning and precision and timeliness are critical for all data used at firms. For analysis and other processes to be reliable, data management requires fine tuning with minimal human intervention. Asset managers need recommended data practices, controls and technology. These tools enable them to support investment professionals, clients and regulators. They can also help firms realize maximum return of investment from their data sets.

Data management has grown into its own discipline over the last 10 years

The amount of data created, obtained and used by investment firms on a daily basis is overwhelming. What’s more, it is growing at an exponential pace. We see firms organize and manage data by establishing three high-level data classes, identifying their key attributes and methodically laying out an approach to make it usable. Client data is highly confidential and, as such, needs a high level of security. Product data, aggregated across holdings to compute performance and valuations, requires consistent formats and fields. Reference data is the essence of the investment cycle.

Key ‘Enabling Behaviors’ for Data Management

At Accenture, we think of data management as a way to integrate strategy, business and technology. To achieve an effective approach, asset management firms should adhere to several guiding principles.

First, since data management requires alignment with multiple stakeholders and across the enterprise as well as common data for the business and IT, the firm should establish a data governance structure or even a Chief Data Officer (CDO). The CDO sets policies for how data is acquired, managed and used.

Second, the firm should develop a unified data model, which promotes the use of centralized sources. This approach embraces the concept of “Golden Copy.” It refers to the source data that governs issues covering definitions and how data is used.

Third, the firm and team should embrace data management as a business process. It is not a one-and-done technology project. True, technology supports data management. However, business users must take ownership of their data and understand how it supports their key processes.

Effective Data Management Start: Data Mapping

An initial step to achieve effective data management is to assess data consumption relative to critical processes of the firm. This is where data mapping comes in. It looks at the end result of major processes to understand how data is used, then traces it back to the source. This exercise enables the firm to address how it can better acquire, manage and secure data.

With data map in hand, a firm can address foundational questions, such as:

  • Are there opportunities to leverage purchased data?
  • How should data be stored and with what resiliency measures?
  • Which control processes assure timeliness and accuracy?
  • What level of access and transparency is appropriate and to whom?
  • What Key Risk Indicators (KRIs) assure compliance with data management policies?

Yesterday, Today and Tomorrow

Data management has blossomed into its own discipline over the last 10 years. Today, it is a standard practice within a mindful approach that integrates strategy, business and technology. To be effective, firms must establish a focused data management capability that provides stewardship over the acquisition, maintenance and access to data within the firm. They also must integrate data management into a formal IT business plan.

In the coming years, as the investment industry evolves and big data enhances analysis, data management will become a core competency. As such, asset managers must have effective data management strategies in place. In this way, they will help address the growing needs of their businesses and generate operational alpha.

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