Data Management Strategy – a requirement for longevity in today’s global market

Recent credit crisis won’t be the last event leaving firms exposed

Few could have predicted what the state of the financial markets would be like by mid 2008. Even fewer can make credible claims as to where it will be in the future. We’ve all heard various CEOs state with conviction that their company has not been adversely affected by the spreading credit crisis, only to announce later that they were incorrect. So why are so many firms struggling to understand the impact of market events on their business? We believe it is primarily due to the inability of financial organisations to have true transparency and visibility into their businesses as the result of the lack of a cohesive data management strategy.

The evolving credit crisis is yet the latest event to raise awareness around the challenges that today’s organisations have when it comes to assessing exposure to critical market events. Despite the continued focus on both risk and performance measurement systems, organisations appear to have made minimal progress in gaining deeper visibility into their business. At the core of this issue is investment data and the proper management of this data. Imagine for a moment that a firm announces a liquidly crisis and within minutes you are able to traverse your organisation’s systems, determine exposure to that specific security, and take action to minimise your risk – that’s what a cohesive data management strategy can help you achieve.

In the absence of a cohesive data management strategy, many organisations rely on a matrix of off-line spreadsheets and manual processes to cobble together data from disparate systems to support decision-making. An example of this practice that is playing out in real-time is the way firms are scrambling to process complex security types. Given the lower fees associated with derivatives (futures, options, swaps, OTC), and the ability to hedge risk with them, it’s not surprising that this asset class continues to gain more and more traction in uncertain economic times. I n the face of technological deficiencies in existing systems and processes, many firms have fallen back on building critical infrastructure around legacy accounting systems in the form of supplemental spreadsheets or transient database applications leaving managers overwhelmed with manual processes.

This practice is problematic on several levels: how do you oversee the governance, risk and compliance of your business when key investment data is being managed outside core processes? As human intervention increases, so does the risk of bad decisions and rogue practices, not to mention the cost of running the business. Furthermore, as these pockets of information and analysis spread, the organisation becomes ill-equipped to conduct new types of analyses as the market evolves, which may very well result in a loss of competitive edge. Technology solutions must be able to adapt to accommodate these new instruments within existing processes and provide multiple, appropriate points of integration with other enterprise applications to be operationally efficient within a firm’s technology infrastructure.

From an operational perspective, the benefits technology brings are largely around increased automation of key processes which remove human intervention, resulting in increased throughput, minimised errors and ultimately lowered costs. Key to this concept is the use of consistently applied business rules that evaluate, validate and transform data, allowing a firm’s business experts to focus on anomalies and make sound business decisions. With a solid data management strategy in place, firms will experience an increased ability to conduct deep analysis, spot trends and answer the questions the market is asking today- not last month.

Data management challenges can be categorised at a high level into three key areas: data quality, data integration and data delivery. From a quality perspective, firms continue to be plagued by the difficulties inherent in providing consistently accurate reference and investment data to the business. Quality is measured in terms of accuracy, consistency, completeness and timeliness across all key systems. All these measures of quality, and the ability to execute and monitor the service levels built around them, are more rationally supported from a well designed and executed data management platform. Data integration, the ability to combine data from current accounting solutions with reference and other investment system data, is extremely difficult without a centralised data management solution in place, yet this complex process is absolutely fundamental to a firm’s ability to react to market shifts. Finally, the delivery of high quality investment data to risk, compliance, performance measurement, reporting and analysis applications results from sound business processes and a solid systems infrastructure built on a sound data management foundation. At the end of the day, the market measures a firm on its ability to accurately communicate its strategy, demonstrate the results of sticking to it, and explain how the strategy is transformed into its investment performance. However, many firms that continue to rely on legacy systems are challenged to provide high quality, business-focused reports to portfolio managers and senior management in a timely manner. Systems deployed 10 years ago are ill equipped to generate and distribute critical investment information from disparate systems, let alone send it securely over the Web or through wireless devices.

For many firms the struggle begins with the concepts around what it means to employ a data management strategy. What does our firm mean by data management, what’s involved, what systems are included, and how does one go about developing, deploying and measuring the success of such an undertaking? Eagle Investment Systems has had the opportunity to work with many of the world’s most prominent financial organisations, assisting them in various aspects of delivering a data management program. In our decades of experience, successful data management is the result of a strong partnership between business, IT and technology vendors to build a system infrastructure that supports business processes and strategies as defined by each client we work with.

A data management solution often begins with a reference data project, but does not end until an organisation is successfully solving its most pressing business problems, often focused on risk, compliance, and performance measurement. By definition, data management is the policies and procedures that properly manage the full data lifecycle needs of an enterprise. We believe that the role of technology in data management is to underlie and enable these business policies and procedures by providing solutions as part of a flexible and extensible system architecture.

The business value of consolidated, high-quality security reference data is well recognised in the asset management and financial services industries as core to the ability to deliver consistency across all key investment systems from trading to performance measurement. A reference data solution that allows maximum automation and exception-only processing to maximise data throughput and accelerate business is a crucial step in establishing a data management solution. Since the policies and procedures of every business vary, the technology solutions that serve them must be customisable via rules-based tools understandable to business users.

The ability to combine consistently reliable security reference data with daily accounting data is the first step to transforming market weights into daily asset allocation reporting based on a firm’s investment strategy. The ideal state is to produce this transformation daily across all trading and accounting systems for all managers and instrument types – globally. This transformation must be able to accommodate complex fund hierarchies and provide drill-down through N levels.

To ensure a firm’s strategies are not adrift, market index data must be aligned and tracked so it can be studied side-by-side with a firm’s daily activity. The complex mandates and outperformance strategies employed by many portfolio managers require the creation of custom indices for compliance and performance measurement. From a data management standpoint, custom indices require reference and analytic information, both historic and current, and the ability to model and aggregate the requisite custom structures.

Managers and firms are measured and compensated on their investment performance. For this reason, they must be able to accurately generate single- and multi-period returns, present them in a compelling manner that illustrates their contribution to their clients’ portfolios, and provide the information and measures required by industry regulatory groups. The accurate generation of returns requires holdings and transactions over time be mapped to the type of return calculation required. The ability to look at portfolios from any angle, for example, sectors or issuer, relies on the existence of an accurate reference data repository. Depending on the time period and calculation, thousands of data points can be required to generate the returns. Add to this the requirement that many of the analytic measures, like attribution, relative and absolute risk, are calculated relative to a specified index and the access to accurate underlying data quickly becomes the overarching business problem for performance.

Finally, a crucial aspect of a data management solution is how well it supports the data governance of the organisation. At a high level, this support is measured by how well a data management infrastructure can provide for the data and associated processes as defined by an internal governing body. For example, a data management solution needs to deliver to a business mandate that the firm operate from a single security reference source in order to support the firm’s data governance strategy. Providing data to risk and compliance systems to ensure adherence to internal and external regulations is another example of the support required for a good data management solution. From a technology and systems standpoint, the security of investment and client data is paramount, as is the permission and monitoring of user access to data. Going forward, however, the data governance bar is being raised as business units take interest in how the firm’s data affects their daily operations and bottom lines. Focus is increasing on how the data moves through the firm, its workflows, derivations and dependant service levels. Firm-wide data dictionaries complete with business definitions, activity levels for specific data sources, and the ability to track every piece of data from its source out to publishing systems, and every step in between, are quickly becoming the norm.

The recent market events surrounding the credit crisis are demonstrating the critical business need for sound data management. Many firms are obligated to take significant action to leverage key resources and technologies towards the goal of implementing a data management strategy that provides them proper visibility into their business so that they can take true measure of their business, understand its position relative to acceptable risks, and steer through future market conditions to maintain their competitive advantage. Increasingly financial organisations view data as a business asset and not an IT headache. Industry activity is humming around data governance practices and implementations, along with increased focus and business participation in data standardisations initiatives. At Eagle we are seeing not just a shift in the market, but in the industry mindset that will result in a better understanding of the key data management holds to unlocking better business practices – no matter the market.

Serving the world’s leading financial institutions, Eagle Investment Systems LLC is a global provider of financial services technology. Eagle is committed to providing leading-edge products and professional services for enterprise-wide investment accounting, data management, performance measurement, and information delivery solutions. Eagle’s Web-based systems support the complex requirements of firms of any size including institutional investment managers, mutual funds, hedge funds, brokers, public funds, plan sponsors and insurance companies. Eagle’s product suite is offered as an installed application or can be hosted via Eagle ACCESS, Eagle’s application service provider. To learn more about Eagle’s solutions, contact sales@eagleinvsys.com or visit www.eagleinvsys.com .