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Target operating model

Revamping the target operating model – Why hedge funds need to start at security master

Firms are looking to get more from their ever-growing pool of information, from analytics and reporting to strategy and forecasting, and as such are looking at new tools and solutions to help. In so doing, they are also finding where and how their current data management systems are lacking. As a result, over the past year the industry has begun a substantial transformation of their data management systems. One group we’ve seen embarking on this journey is hedge funds.

In our conversations with hedge funds recently, the phrase “revamping the target operating model” has come up a few times. They are reaching a point in their lifecycle where they are getting too big for their infrastructure and are looking to solve their operational growing pains – both now and in the future. In each of these discussions, the topic starts with upgrading their security master.

Why security master?

It’s not hard to figure out why, despite all the advancements in data management systems, tools, and solutions, security master is the focus: Security master data is foundational to firms’ architectures, and this holds true for hedge funds. Unlike other buy side firms, however, hedge funds tend to use this data to a much larger extent for analytics as well as operational purposes.

Much of the analytics being run are dependent on information at the security data level. There are some circumstances where firms will look at portfolio level data, like risk and performance for example, but for activities like investment research and trading strategy formulation and testing core security master information linked to time series data become critical.  Having a goldencopy of identifier information for example is critical to link pricing and other analytical data together from different sources.  Also having historical corporate actions properly reflected in the reference data (e.g. mergers and acquisitions) is critical to doing accurate time series analysis.  Finally accurate issuer to issue linkage is required for fundamental analysis for equities as well as risk analysis for credit instruments.

The challenges

The way that hedge funds engage with securities is an interesting case. Their number of securities held is typically small, but how much they take into their system is very, very large – not dissimilar to investment banks. Hedge funds do this because they need this data at the ready for when they do make trades or to use it for analytics. This means that performance becomes very important because this massive trove of security data needs to be pulled in and ready to be interacted with quickly. A legacy security master cannot handle that kind of volume.

Historically it wasn’t terribly challenging to build a security master in-house. With a low number of inbound data sources, (sometimes just one) firms could simply bring data into the database and map the fields they wanted. With just one source of data, they didn’t need the degree of scrubbing anywhere close to what is required now, so teams just built them. Now, however, with a need for better data quality, pulling in more instruments and a broader set of data than they had previously, just revamping the systems they built in the past isn’t sufficient. It also isn’t practical or efficient to just build another one.

Security master and the cloud

As many companies are, hedge funds are looking at bringing their data management infrastructure into the cloud. The lifecycle of a legacy system won’t be extended by adding a cloud element, in fact, quite the opposite: it will shorten the lifecycle of that system because it highlights all its shortcomings more quickly. Consumers of the data will want additional information, different fields, and better data quality as they utilize the analytics power of the cloud, and they simply cannot do those things on the legacy systems because they weren’t built for that degree of scale.

The increased use of cloud platforms, and the analytics platforms in the cloud, is accelerating the need for clean, robust operational data, including security master information. The current infrastructure typically isn’t flexible enough to accommodate that.

How do hedge funds solve for this?

Hedge funds can solve these problems by getting to a more modern data architecture that takes into account both security master and operational data, as well as analytics data, providing a platform and infrastructure that won’t need to be revamped every 5-7 years. Firms can bring in new data sources and even put more systems in place around the platform, without the concern for scalability.

This starts with a cloud-ready security master, with a robust data model, that can handle large data volumes. This will improve performance, make getting data in and out of the system much easier, greatly increase data quality, and provide an optimal experience for data consumers. They can then take this database of complete and trusted information and create a frictionless passthrough to the cloud for trustworthy and actionable analytics and reports – both now and in the future.

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