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Just in Time: Current Trends in Risk Management Data Supply

By Marc Alvarez, senior director, Reference Data Infrastructure, Interactive Data

The global upheaval of the capital markets over the past few years has resulted in a wholesale, industry-wide effort to improve the risk management function. When looked at from the perspective of the data supply chain that services the risk management role, a major shift towards a near-time, event driven operating model is making itself visible. Risk managers are increasingly looking to operate on a ‘just in time’ basis in order to provide the most up to date measurement and analysis possible to their firms and their customers.

This article breaks down these emerging trends to the level of the data supply chain and its impact on both data subscribers and providers. When taken together, these trends point to a major shift that can be expected in the direction of improving service levels not only across the industry, but also in the execution of the risk management function on a day to day basis.

It likely comes as little surprise, but with the extraordinary events in the capital markets over the past couple of years, there is a fundamental restructuring underway in the domain of risk management. More than once over this period has this vital function within financial firms been severely stressed, leading to what some have described as ‘once in a generation’ changes to the scope and activities of risk managers.

When viewed at the business level, this shift makes perfect sense and is readily recognised as a direct result of changes in the broader economy. While it may cause some pretty significant disruption in the short term, the emerging consensus is that, ultimately, this is a positive development that will benefit investors globally. When looked at from the perspective of supplying data content to service today’s risk management functions though, it highlights some pretty big challenges coming over the horizon.

First, risk monitoring and reporting at the enterprise level have become more of a team sport than ever before. More and more, the traditional distinction between market, credit, operational and other risks is blurring. Risk management is becoming a function of the combination of all these factors and servicing this new environment requires data providers to raise the level of service across a broad front in order to meet the needs of today’s powerful risk management applications.

That one phrase – ‘level of service’ – captures a very broad and challenging range of issues in the data supply chain, including:
• Timeliness – reporting and analysis are moving rapidly to an intraday, on demand basis. The need to deliver the latest information to risk managers is now seen as a real-time function, to be executed pre-trade and as part of developing new investment models. Scheduled batch delivery of data content is coming under pressure from more frequent delivery and on an event driven basis so that the risk view is as up to date and complete as possible

• Completeness – risk analysis and assessment can be expected to drill down to a more detailed level in evaluating both existing as well as prospective investment positions. This translates into the need for a growing array of database fields and entirely new sources. And as portfolios re-balance and diversify globally, the universe of instruments – along with their related derivatives – risks growing faster than processing and storage capacity. Achieving complete coverage and maintaining it in a timely manner becomes a multi-dimensional effort, requiring the integration of both real-time and reference data services

• Integration – at the functional level, measuring risk involves combining content from multiple sources into a single, coherent framework and marrying it with internal data. In order to streamline this process, the more content that can be produced upstream the better, thereby reducing the integration complexity that the risk application needs to support. For data providers this extends the need to support and deliver a growing library of derived and calculated values

• Availability – having content accessible and ready for use in response to the development of new investment strategies and in acquiring new positions is clearly more important than ever before. Given the need for timeliness, this content has to be staged and ready for use. Batch delivery provides a good starting point for transferring what can be quite a large universe of content. However, the need to take a ‘just in time’ approach is clearly on the horizon. For the data supply chain, that means having all the content in production and maintaining it on an intraday basis, so that it is readily accessible for use when needed

• Accuracy – developments in operational risk over recent years highlight that additional effort and transparency from data providers are expected and must be accounted for in day to day business operations. But the need for accuracy goes even deeper, to the lifecycle of the content and transparency to support necessary audit trails.

Taken together, these trends highlight an ongoing shift to raise the bar when it comes to servicing risk management applications. Above all, they reflect the global, enterprise-wide nature of the risk management function and its importance to today’s business.

For the data supply chain, these trends lay the groundwork of guiding principles that need to be taken into account in servicing the risk management function. Above all, they point clearly to the need to integrate data content, technology and service levels into more of a coherent package tailored expressly to meet these needs. All in all, they highlight an increase in the convergence of content with technology at an enterprise and global scale.

What’s interesting about this integration is that it cuts across both the data supplier and the data consumer landscape in some new ways. While not unfamiliar, the underlying shift to a ‘just in time’ enterprise level approach lays out challenges for the supply chain end to end. For subscribers, new capabilities, functionality and capacity are needed – there’s no point in improving the supply of data if it can’t be made operational to the enterprise. But these benefits do come at a cost – legacy systems and operations need to be revisited and tuned to support the broader enterprise, including regulatory reporting.

For data providers this underscores need to invest in the technologies and interfaces to streamline this process for customers. After all, having a high performance data consumption capability should be met with higher performance data delivery and broader content. Interestingly, there could well be much in common with the efforts that subscribers and consumers of this content undertake over the short term. Clearly, there is an opportunity to open a two-way, functional dialogue aimed at improving levels of service by leveraging new technologies and capabilities across the industry.

It’s all too easy to think of these changes to the risk management landscape as major difficulties. Meeting the demands of the risk management function will require significant effort and investment over the short to medium term. But for investors, such a move is going to result in better transparency and more active management of risks, which will benefit everyone.

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