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How Ontologies Help Asset Managers post-MiFID II

MiFID II is in the process of revolutionising information flows for asset managers globally, with important implications for returns and competitive positioning.

Active managers, who are under increasing pressure to articulate their value proposition, are exploring new ways of maximising Return on Investment (ROI) on external research. Customisable Ontologies, multi-dimensional data-maps designed specifically for asset managers, may be the key to improving productivity and leveraging key information across complex, siloed, multi-asset-class investment enterprises.

MiFID II is creating an unprecedented “information asymmetry” between asset managers depending upon their ability and/or willingness to pay for research. It is now illegal for European managers to receive research services they have not specifically paid for and it is illegal for research producers to provide it.

This means, that for the first time ever, research producers (primarily banks) have to cut off managers that can’t or won’t pay. This will create a new information hierarchy, with research producers moving capacity away from Europe and P&L managers toward those managers that can or are paying (that is, US hedge funds).

Most large asset managers in Europe have opted to pay for research via P&L. A major investment bank has estimated that the average P&L manager in Europe will cut research budgets by 50%. These managers will have to make the remaining research work harder.

Regardless of funding mechanism, asset managers now have to demonstrate that their research spending is supporting the investment objectives of their clients.

New approaches to semantic search and technology facilitated collaboration across complex, multi-asset-class investment management organisations can drive unprecedented research efficiencies, even in a constrained supply environment.

Millions of press column inches have been devoted to the notion of integrating “Big Data” into the investment process. But before managers attempt to conquer the external “Big Data” universe, they should leverage what they already have within the enterprise.

Complex global managers have significant internal “Big Data” as their investment professionals receive and generate hundreds of thousands of internal and external documents every year which aren’t stored centrally or searched effectively. Investment professionals conduct countless conversations and generate enormous amounts of useful data in their day-to-day processes.

If this data could be captured and seamlessly leveraged across the enterprise, it would lead to significant gains in productivity and allow the identification of “thematic communities” across asset classes within the manager – generating a new source of alpha.

Ontologies can be used to organise and data-mine the interiors of the millions of documents that asset managers may hold internally. Moreover, if managers had the ability to reflect their unique investment process (DNA) in the “search” mechanism, they would have a very effective way to demonstrate that they were deriving maximum value from research by systematically data-mining the vast corpuses of documents or interactions that they had purchased.

For active managers that have been struggling to convince investors that they were adding value, MiFID II may yet have a silver lining. It may serve as the catalyst to finally re-invent decades-old search processes that have not kept up with changes in technology. Using ontologies is the first step on the roadmap to Artificial Intelligence-enabled knowledge graphs which could push the boundaries of identifying new investment themes to unprecedented levels. Adopting the use of ontology, specifically “Cognitive Ontology”, may be one of the measures that separates winners from losers in active investment management going forward.

The Ontology Project is an industry-wide asset management initiative to better understand and utilise these techniques, launched with support from Dane Rook and Ashby Monk of the Global Projects Center (GPC), at Stanford University in Palo Alto, which works with large asset owners on investment governance issues. Edison Research is also early in lending its full support to the project.

Stanford’s GPC faculty has written extensively on Knowledge Management (KM) issues for asset managers/owners, within the wider remit of helping investment organisations use technology more effectively to drive returns. We’ll work together to publish new papers suggesting ontology-based solutions to the KM issues raised in previous Stanford papers.

Asset owners and asset managers share a common goal of maximising investment returns and by being a part of the Ontology Project they will work together to create a new collaborative ecosystem to improve research processes.

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