As pension funds act more like asset managers, with internal investment responsibilities, they should focus on the competitive advantages to be gained from data and analytics.
The healthcare industry has seen a 20 per cent decrease in patient mortality by analysing streaming patient data. The Telco industry has seen a 92 per cent increase in processing time by analysing network and call data. These are two powerful examples used by IBM to demonstrate the return on equity of investing in big data technology.
For many investment managers and asset owners, data remains an untapped resource.
According to Virginia Rometty, chief executive of IBM in an article in The Economist, data constitutes a vast new natural resource, which promises to be for the 21st century what steam power was for the 18th, electricity for the 19th and hydrocarbons for the 20th.
She says that in 2014 a new model of firm will emerge, called the “smarter enterprise”.
“These firms will do the things that organisations have always done: make decisions, create value and deliver value. But they will do them in new ways. Smarter enterprises will make decisions by capturing data and applying predictive analytics, rather than just relying on past experience.”
This new way of thinking of data, as a resource, is very relevant to the investment management industry which not only has a high volume of data but relies on data for decision making. But according to a survey by State Street there is a real divide in the industry between the data leaders and the data laggards.
The study conducted by the Economist Intelligence Unit, and commissioned by State Street, “Leader or Laggard? – How Data Drives Competitive Advantage in the Investment Community”, surveyed 400 firms and looked at the strategies leading asset managers and asset owners are using to gain a competitive advantage from data.
The survey found that the vast majority of respondents saw data and analytics as a strategic priority (91 per cent), and yet only a small proportion (29 per cent) strongly agreed that they are already gaining a competitive advantage from their data now.
For those that are not, they are missing out. There is a lot for room for investors to use the analytics and interpretation of data, to identify investment opportunities and risks. The State Street report says data analytics can help with managing risk across multi-asset portfolios, enabling smarter and faster investment decisions and learning how to master regulatory complexity.
The importance of data analytics is highlighted by head of State Street Global Exchange Research and Advisory, Jessica Donohue, who says insight into portfolio data allows investors to leverage the “high ticket items” like asset allocation.
“Insight into the portfolio allows you to do things like tilt the portfolio for better return but less exposure, and it allows you to do factor analysis, manager assessment and look at things like manager strategy overlap,” she says.
“The theme of the last four years is it is all about risk, risk, risk, where previously it was all about alpha, alpha, alpha. But they are two sides of the same coin.”
This theme has also played out in the functions of investment firms, where risk was seen as middle to back office function but now it has front office implications.
The State Street report highlights one of the challenges of data, is its sheer volume (the others being velocity and variety), reporting that global IP traffic is projected to reach 554 billion gigabytes per month by the end of 2016. This is more than 110 times all of the information estimated to have been created by human beings from the dawn of civilisation until 2003.
Similarly IBM’s Rometty quotes that by 2020 there will be 5,200 gigabytes of data for every human on the planet by 2020. (To put this into perspective, one gigabyte is the equivalent of about 20,000 reasonably-sized word documents.)
For this industry its worth noting that financial data mirrors the general growth in data, and further, that the infrastructure investors use has not kept up with that growth.
A recent report from experts at the US Treasury’s Office of Financial Research says: “Financial market data volumes are growing exponentially. One should thus expect traditional data management technologies to fail, and they have.”
In particular back offices have not kept up with developments in either their own front offices or other industries.
The good news is the survey shows that investors are addressing this issue, and Donohue says that 86 per cent of respondents have increased their investment in data and analytics infrastructure in the past three years.
“We are in a cost cutting mode across the industry, but it is one of the areas people are spending money,” she says.
In addition to investment in technology, Donohue also highlights the interpretative skills as a barrier in the industry to embracing data as an advantage.
Particularly she says there needs to be continued innovation and specialisation in data analytics and then the visualisation of that data and analysis.
“This will be a powerful tool when it can be put in the hands of the C-suite, and it helps the chief investment officer, or chief risk offer see things in the portfolio and drill down,” she says.
“Having accurate data, and your own portfolio data at hand, is a big deal. “Big data” is a buzz word but there is a sense that your own data is your asset, it’s a tool you want to use. The next step is asking how you can do that and the realisation you should be able to do that.”
State Street Global Exchange is a new division of State Street and Donohue says it is a statement of how important data and analytics play in the role of our clients. It combines capabilities in research and advisory, portfolio performance and risk analytics, electronic trading and clearing, information and data management, along with new innovations to help asset owners and managers gain new insights and execute investment decisions efficiently.
The State Street report highlights five steps necessary to becoming a data leader
1. Improving risk tools with multi-asset class capabilities
2. Developing better tools to manage regulation in multiple jurisdictions
3. Improving the ability to manage and extract insight from multiple data sources
4. Optimising electronic trading platforms
5. Developing a scalable data architecture that will grow with your business
Source: “Leader or Laggard? – How Data Drives Competitive Advantage in the Investment Community”,
