New York, June 4, 2018

Dear Friends and Colleagues,

I was recently invited to speak at a conference in New York, on the use of advanced data and analytics in the investment management industry. An abridged version of the presentation is here, but a brief summary is below.

We are in a period of significant transition and change in our industry. As with all such periods, there will likely be winners and losers. The key question is why (and how) some firms are handling this transition better than others and are able to use data analysis as a source of competitive advantage.

Using more data and analytics in the investment process is increasingly intuitive, but deceptively hard. How to best shape the organization to utilize it is a question I have thought long and hard about, both in my time on the buy side as well at Exante. At Exante, we have also seen this in action among our clients, who are generally handling these transitions successfully. While each situation is different, there are some general best-practices that seem to apply quite broadly.

The overall answer is accepting the new multi-faceted reality and adapting to it.

For example, the regulatory environment and inertia has created a world with dis-economies of scale, in terms of incumbent organizations’ ability to build data and expertise. This is exacerbated by the advent of cloud computing, and easy access to capital, giving small, nimble companies a level playing field to access to crucial technological infrastructure. The best incumbent firms have adjusted to this by building specific core competencies in-house and working with reliable external providers to outsource the rest.

Another key reality to adapt to is the simultaneous acknowledgement of the powers and limitations of data analysis in finance. In difficult times, the instinctive reaction for industry veterans can be to move to one extreme or the other, i.e. either shun new data analytics altogether and return to what worked for them historically, or radically overhaul their entire process and teams.

We believe that the right choice is more subtle. High quality data and analytics, as they exist today, are best equipped to supplement (not supplant) existing investment processes.

Looking through the hype, it is clear that current algorithms are unable to truly solve the complex, unbounded and dynamic puzzle that is the financial markets. Indeed, it seems possible (likely) that this is not a truly solvable puzzle at all. The reality to accept here is that the combined skills of man and machine are what is likely to come closest.

In our experience, the most successful firms use advanced analytics to improve the quality of data provided to human decision makers – i.e. combine the relative strengths of man and machine. For example, a machine’s ability to scan large sets of disparate data dispassionately, and flag outliers, is almost without parallel. But the human ability to view these outliers in the right context is where true insight is generated. To us, such combinations of humans and algorithms are the best source of alpha, and the way forward (at least for now).

At Exante, we are focused on building tools within this hybrid framework, using and learning from developments in the machine learning and AI worlds, and combining them with human input. We intend to continue down this path and remain keen to connect with those who are thinking about the same issues.

Ankit Sahni
Head of Research
Exante Data LLC