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An Explosion of Data: forging partnerships to manage growing volumes of essential information

David Pagliaro, Head of State Street Global Exchange at EMEA for The Fintech Times.

Institutional investors are making use of more data than ever as they seek increasingly sophisticated analysis to enhance functions like investment performance and risk management analytics.

As data sources proliferate and volume multiplies, it creates new challenges for the investment industry. Professional investors must seek a balance between maintaining the essential knowledge bestowed by access to the same range of data as their peers (as well as potentially harnessing technology to give them unique, actionable insights), but also as cutting out ‘noise’ – information they do not truly need to do their jobs, and which can act as a distraction.

Our own research bears this out, showing that the ability to analyse increasing volumes of genuinely valuable data, while filtering that which is less relevant, is a growing concern for investors.

Key data management challenges

According to a survey we conducted this year with 86 asset managers, pension funds and other institutional investors worldwide, the biggest challenges faced by the data and technology functions in their businesses relate to the scale of their data operations.

The biggest perceived challenge, for 42 percent of respondents, was a lack of integration between different data sources and types, followed by increased volume of data (39 percent).

Just five years ago, when we last conducted this survey, data accuracy was the top concern for these investor types. Timeliness of data followed in second place, tied with integrating multiple data sources (34 percent each).

Escalating investments in technology

The challenge of managing this explosion of data is driving significant increases in technology investment by investment organisations, along with a focus on seeking support from trusted partners.

In our 2013 research, nearly half (49 percent) of the institutions surveyed were reliant entirely or mostly on in-house solutions for data analytics, whereas in 2018, 54 percent relied entirely or mostly on external providers.

All of this shows that the industry has matured to the point where most institutions have clear data management strategies in place and have tailored their relationships with outside providers to their specific strengths and requirements. This offers clear benefits. For example, 46 percent say their data and technology investments have improved alignment between data and risk teams.

The impact of regulation

This focus on data management and analytics is set to continue. Much of it has been driven by regulation, as firms implement technological solutions to meet requirements for new sets of rules like MiFID II and AIFMD. Third-party providers create risk and performance analysis and reporting systems for managers, and these are enhanced over time to meet wider requirements from the industry.

More than half (55 percent) of respondents to our latest survey cited regulation as a key driver of their technology investment. And a similar proportion (56 percent) say regulation will have the biggest influence on its data strategy over the next five years. Nearly one third (31 percent) also expect client demand for better data and analytics processes to be a major driver of their strategies.

Looking to the future

Most firms acknowledge this is a fast moving industry and that there is much work to be done to keep pace with developments. In 2013, 91 percent of respondents said they had all or most of the right talent in place to advance their investment data and analytics strategy.

Five years on, this figure had fallen to 60 percent, with nearly a quarter (23 percent, compared to eight percent in 2013) claiming to have significant knowledge and/or training gaps, and five percent (compared to none in 2013) saying they simply do not have the right talent in place.

These numbers show how difficult the future can be to predict in the sphere of technological development. Relatively nascent advances, like distributed ledger (blockchain) and artificial intelligence or machine learning, have the power to create significant disruption to established methods and operating models.

The investment industry needs to understand this and organisations should make a forward looking, collaborative approach to data management an integral part of their strategies and culture.


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