Today New City Initiative is comprised of 43 leading independent asset management firms from the UK and the Continent, managing approximately £500 billion and employing several thousand people.
Published by Charles Gubert
Depleting returns interlaced with excessively crowded trading conditions have forced asset managers to contemplate alternative approaches towards generating better performance for clients. By systematically integrating bottom-up, in-depth data – often supplied by external technology providers or bank counterparties – and then leveraging AI to conduct deeper analysis of securities, sectors or markets is one way fund managers could suppress the post-crisis downward return spiral, and revert to profitability. Or at least that is theory.
The reality is more ambiguous. Not only are genuine doubts being flagged about the actual reliability of data (i.e. its authenticity in the context of unchecked fake news and the superfluity of online misinformation) being used to furnish investment research, but firms are also being warned they risk inviting regulatory scrutiny if data is acquired improperly or used inappropriately. If managers are found to have inadequate controls or weak data governance, the consequences could be severe. A prudent data strategy is therefore key.
Know where the data comes from
Service provider (e.g. fund administrator, custodian,) selection requires asset managers to conduct intense vendor due diligence beforehand. A similar approach needs to be adopted by managers when engaging big data providers so as to validate that their service offering is robust and the information being supplied is accurate. Equally important is that managers corroborate that these providers are obtaining data responsibly through legitimate channels, and that they have full oversight over where the information is sourced from.
Aside from the obvious risk of nursing steep losses by incorporating imprecise or inexact data into the investment decision-making process, firms could also find themselves in trouble for breaching GDPR (General Data Protection Regulation) rules if they acquire or use information illicitly. Regulators including the Financial Conduct Authority (FCA) have put the financial services industry on notice warning them that misuse of consumer data will not be accepted. As the regulatory tide turns against big data, caution must be exerted by firms.
Big data and a possible regulatory onslaught
Regulation is perhaps the biggest threat to the big data industry. With the increasing repudiation of technology companies unconstrained use of consumer data, the financial services industry needs to tread carefully. More alternative data firms are moving into the market offering fund managers everything from anonymised, aggregated reports on consumer credit card spending habits right through to cellular phone location information – all of which are designed to give investors additional insights into underlying market trends.
Firstly, it is crucial that data used by managers does not contain any personally identifiable information on the end consumer, although this is something institutions appear to be reasonably vigilant about. In addition to privacy protection, it is entirely possible regulators may start deliberating on whether some of the alternative data providers are bestowing investors with an unfair competitive advantage. While the US Securities and Exchange Commission (SEC) has not yet issued any enforcement action against users of alternative data, it is reportedly monitoring developments carefully. Given the SEC’s takedown of expert networks in the early 2010s following a series of hedge fund insider trading scandals, alternative data providers could be a potential target for future regulatory investigations.
Big data as an operational enabler
On the investment side, firms need to be careful about where they source information from, and how they use it. Increasingly, however, fund managers are making more use of data as it applies to their operations. For instance, a number of custodians are scouring through clients’ trade settlement data to see whether they can prevent trade fails using predictive analytic tools thereby netting investors’ cost and risk benefits. Elsewhere, big data from multiple sources and counterparties is being mapped with AI technology and used to help firms with their regulatory compliance requirements. This can expedite and improve the quality of regulatory filings, to the benefit of both managers and their market supervisors.