About a-team Marketing Services

A-Team Insight Blogs

Strategy and Tools for Tracking Licensed Data

Subscribe to our newsletter

By Neil Sandle, Chief Product Officer, Alveo.

Indices are tools used to track how asset classes, industry sectors, market segments, and a host of other physical and virtual sets of data perform over time. Leading examples can be found in the realm of financial services, in particular with stock markets where the FTSE 100, NASDAQ Composite and Hang Seng Index are primary examples. Other asset classes can also be indices, such as returns from fixed income portfolios.

These indices serve as a solid foundation for product development, asset allocation and performance benchmarking. Exchange-traded funds (ETFs), such as iShares by BlackRock, are instruments that directly follow price movements in indices, either directly or inversely. Demand for indices is growing and the index provider market is quite concentrated with a few large players dominating the market. The FCA has initiated a Wholesale Data Market Study, that is investigating the market data space including index data.

Tracking the price of index data

A report by AFME published recently, shows that fixed income data spend for sell-side institutions has increased by half in the past five years. This represents a trend across the financial services industry. Spend on data from exchanges has also risen by 42% since 2017, with information services becoming an increasingly central business model for exchanges.

In particular, the license fees for indices have risen sharply. If investment products rely on this data to function, then this is an essential cost that the financial services provider has to bear, especially if they are contractually required to report performance against a specific index as part of their mandate. This stipulation is often made to allow performance comparisons between asset managers and their different products.

Therefore, tracking data consumption is critical in order to generate maximum value from a scarce resource. This implies being able to track who uses the data within an organisation, its downstream applications, and which internal or external reports it appears in. It should also be clear whether new derivations from the data are created such as internal, custom benchmarks.

Fundamental to understanding how the data is used involves ensuring that it is correctly permissioned within the organisation and that license restrictions are followed. As is the case with all licensed products, when additional products are created on top of it, royalties may be due to the originator.

The question naturally arises of how can an organisation track its usage of data? The answer is the introduction, or utilisation, of comprehensive data lineage and data usage tracking tools. Firms should be clear about how they buy the data, where it enters the organisation, and its subsequent journey within the enterprise. This means understanding who uses the data, in which databases or business applications it is stored, and whether it is used for external reporting. Due to granular content licensing, index data is a scarce resource and it should be managed, or perhaps sometimes even rationed, accordingly.

Firms with low data management maturity will struggle to collect and aggregate data or integrate it into their workflows. Maintaining the integrity and quality of the data will also be challenging when examining how the data is used in interactions with third parties, not only internally. Siloed working practices and a lack of detailed knowledge of license rights may present further complexities if the data is allowed to subsequently leave the organisation via email or in reports without express rights.

Data management to the rescue

The key to solving these issues and ensuring that index data is being managed correctly, is to understand whether the data is being used to derive proprietary blended indices or benchmarks, as this typically has its own licensing implications.

Staying compliant with license agreements requires being able to track the data. Tracking also brings other benefits, such as being able to exercise greater control over what the organisation is buying, how much data it is using, and whether it needs to be paid for. Data tracking allows an enterprise to answer queries, undertake root cause analysis, and respond to customers, investors and regulators, allowing firms to justify and explain their decision making.

A sound data management solution will help this strategy by acting as a central pathway, tracking permissions and mapping data as it travels from system to system and department to department. A centralised solution such as this will track lineage and flows end-to-end, providing a single clear view of data usage and distribution. Opting for a Data-as-a-Service (DaaS) solution from a managed data services provider gives financial institutions the ability to effectively manage their data, increase agility and flexibility, and remove unnecessary expenditure on data processing and platform maintenance.

This strategy marks a major advance in overcoming the complexity of managing index data, and ensures peace of mind in terms of compliance, and a comprehensive view of data flows. Having this in place allows firms to be in control and able to properly cope with often opaque pricing models. Worst case scenario is if facts on usage, direct or indirect via derivated data, are only unearthed during a data vendor audit. Firms need to know how they use data products to stay ahead of that curve. DaaS solutions built on robust and proven technology are indispensable here

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: Augmented data quality: Leveraging AI, machine learning and automation to build trust in your data

Date: 19 September 2024 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes Artificial intelligence and machine learning are empowering financial institutions to get more from their data. By augmenting traditional data processes with these new technologies, organisations can automate the detection and mitigation of data issues and errors before they become...

BLOG

Citigroup Fine Shows Importance of Having Robust Data Setup

The US$136 million fine meted out to Citigroup for data irregularities dating back to 2020 should serve as a warning to all financial institutions that robust data management is essential to avoid sanctions amid tougher regulatory regimes. The Federal Reserve and Office of the Comptroller of the Currency (OCC) jointly imposed the penalty on the...

EVENT

Data Management Summit New York City

Now in its 14th year the Data Management Summit NYC brings together the North American data management community to explore how data strategy is evolving to drive business outcomes and speed to market in changing times.

GUIDE

ESG Handbook 2021

A-Team Group’s ESG Handbook 2021 is a ‘must read’ for all capital markets participants, data vendors and solutions providers involved in Environmental, Social and Governance (ESG) investing and product development. It includes extensive coverage of all elements of ESG, from an initial definition and why ESG is important, to existing and emerging regulations, data challenges...