Using AI to better visualise complex data
The amount of data is exponentially growing. A paper by IDC, Data Age 2025, said that 16.3 zettabytes of information was generated in 2017 (one zettabyte is 1 billion terabytes), and forecasted this amount would rise to as much as 163 zettabytes in 2025.
Making sense of all this data has become the next arms race, with artificial intelligence playing a pivotal role in pattern recognition and generating new insights for managers.
This is certainly true when one considers the new generation of hedge funds that are using autonomous learning and neural networks to run their portfolios. These funds ingest massive data sets. For SS&C Technologies, this is a trend that plays very much to the company's strengths.
As analytics tools sharpen, investment firms are getting smarter about how they utilise data to make investments and operational decisions. This is a great opportunity for the global hedge fund industry; each month improvements are made both in automation and analysis.
“As a tech-focused firm and a global fund administrator, we plug in to that trend really well,” says Mike Megaw (pictured), Managing Director at SS&C GlobeOp. “A big part of what we do is provide sound data to help managers understand what they’ve done, know where they are going, and to assist them in their investment strategy activities. The basis for that is having clean data.”
To that end, SS&C Technologies allows clients to leverage a dual platform that handles data aggregation and management, known as CORE, on top of which lies a data analytics platform, SightLine, a leading edge solution for visualising and presenting data.
CORE creates data sets and feeds them in a formatted way either to the manager’s internal systems or to external systems with which they interact. SS&C Technologies has made a significant investment into the organisation of unstructured data sets to give clients better information.
“We are applying artificial intelligence to take unstructured data sets and organise them in a way such that the interpretation is as accurate as possible; that’s what feeds other decision-making engines, such as neural networks.”
“SightLine, on the other hand, allows the manager to create different visualisations of that data. Different personnel within a hedge fund need to look at the data in different ways, and create their own visualisations of a particular data set. We also support the ability to marry data with existing data sets that the manager might have. We empower CIOs to get a better handle on the investment process,” says Megaw.
The two platforms combined give hedge fund managers an effective way of aggregating, managing, and making sense of huge data sets, leading to new insights both at the portfolio level and across the business as a whole. “A big part of what SightLine does is organise data in a meaningful way for the manager, and allows them to improve the way they communicate with investors,” adds Megaw.
Taking raw data and applying analytics has huge potential for fund managers. One example relates to transaction cost analysis. Using SightLine, the CIO/CFO can look at how the portfolio manager is allocating trades, perform trend analysis over a period of time, and determine whether those costs are in line with expectations or are rising too high. Previously, arriving at such an answer would have required a lot of engineering. Now it is available almost instantaneously.
“That’s a big reason why we put this platform together: to quickly get clean, validated data to managers and allow them to turn that data into information to aid the decision-making process,” concludes Megaw.