Challenges Drive Data Innovation
The Business Challenges that are Shaping Innovation in Data Management
Colin Pope, Lead Solution Architect EMEA and APAC, Eagle Investment Systems
Investment managers are becoming quicker to embrace new technological developments as they look to achieve greater efficiency and focus on core competencies. The data management challenges themselves—ensuring data quality, consistency, availability and accessibility—have remained broadly the same as they always have been. However, it is the newer business challenges that are really driving innovation and shaping technological advances in the world of data management.
From the dynamic regulatory environment to the growing adoption of data-as-a-service, asset managers are seeking more agility to meet business demands, which often underpins the evolving data management solution set. The following are among the most prominent business challenges today’s asset managers are facing:
The regulatory environment continues to evolve with MiFID, FRTB and GDPR all driving new data management demands in Europe, while regulations like SEC Modernisation are affecting US firms. In each instance, there are significant data management requirements as firms must deliver data or reports to regulators, with growing penalties being applied for incorrect or late delivery. As a result, firms are focused on the business processes and technologies they need to put in place to satisfy these regulatory obligations.
As part of this increase in regulation, data lineage is becoming far more important. To put it in the context of a traditional classroom, it is as much about demonstrating how you “worked out” an answer as it is about actually being correct. Firms are increasingly being asked about their data sources and then expected to prove that the data itself is correct and consistent. This, of course, requires a different technology toolset—rather than being able to provide a snapshot of data, firms are required to be able to pinpoint data at a given point in time and answer questions around which data was selected and why.
Controlling costs is another traditional challenge that firms face in managing their data, but this too is taking on a new dimension. Firms have been focused on tracking and rationalising their expenditure on the acquisition of market data, increasingly many are also now looking at the operational costs of processing and managing this data. For example, in calculating the daily NAV, firms are scrutinising the cost, in terms of the organisational effort that is required to generate the NAV or to resolve associated issues as they emerge. This is leading to the development of solutions that enable firms to track workflows, determine where the most effort is dedicated and identify areas to improve efficiencies.
Having accurate and consistent data available for decision-making purposes has long been a goal of data management. Increasingly, though, as firms diversify and expand globally, the requirement is for that single data source to serve different parts of the business and their own distinct needs. For example, it might be that an area of the business requires different pricing mechanisms to be applied. It is no longer about providing instant access to a single set of data—organisations may need to deliver several useful and meaningful datasets that meet each user’s specific needs. This adds another dimension of complexity to the data management process.
Firms are increasing their focus on data-as-a-service. Data delivery is not a one-way street and discrete teams often require specific or bespoke data sets. With greater frequency, data-as-a-service is being developed as a cross-charge service in many organisations. As costs are attached to these data services, firms are also looking to third parties to provide not just a software solution but also a managed data service. The expectation is that this can not only free up internal resources but also, bring expertise and insight to improve the function at the same time.
In addition to service providers helping to manage data, there is far greater integration of third-party solutions today as firms look to do more with the data they have available. For example, a client may have the data they need for MiFID reporting but chose to engage a separate third party to build the reports needed and also service those requirements. As a result, at Eagle we are building out our network of strategic alliances and developing APIs to ease the integration with alliance organisations, in order to help meet reporting or analytic needs that clients may have.
Finally, there has been a long line of disruptive technologies that continue to shape and impact data management. The most recent of these is social media, which in many respects is about changing the way information is sourced and managed. This is fueling conversation within the industry around several important topics:
- What type of data management platform is required
- How is data delivered and are there opportunities for standardised data exchange formats
- The role of big data and data lakes
- The value of relational databases versus NoSQL databases
The data management industry is evolving. In the past, the innovation often occurred in isolation and was then applied to existing problems. Given the agility and pace of technology advancements today, new innovations can be quickly introduced to address distinct business challenges or needs. This also explains the evolving role of the vendor to balance the issues that businesses are facing from a data management perspective with the technology, software, and services to help them meet those challenges.
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