November 2017: AI: Turning Buy-Side Donkeys Into Thoroughbreds?


Asset managers exist for one reason and one reason only: to manage assets. Those buy-side firms that do it well attract more assets than those that do not. And those that are particularly poor at it tend not to last for very long at all in an increasingly competitive marketplace. Key to managing those assets successfully—success in this context is measured by a manager’s capacity to consistently outperform one or more benchmarks, and by so doing produce positive returns commensurate with its clients’ expectations—is the ability to make the best possible investment decisions. The premise is a piece of cake, but like many things in life, it’s the execution part that is inordinately challenging.

Of course, compliance is crucial and so too is risk management and the efficiency with which a buy-side firm manages its various back-office functions, but as important as they are, they pale into insignificance when compared to performance. Essentially, those activities need to be managed effectively in order to guarantee entry to the game—they are contingent on the rules of the game and constitute something of a protocol in terms of how it is played, but whether the outcome of the game is successful or not depends on how well the asset manager performs. 

I’ve said it before but it’s worth reiterating that buy-side firms have never been better served in terms of the tools they have at their disposal to help in this regard. And, over the course of the last 12 months, one new class of technology has risen to prominence above all others: artificial intelligence (AI). But scratch a little under AI’s surface and you won’t find a lot of new, whizz-bang technology—its specialness is predicated largely on its ability to carry out staggeringly large numbers of calculations in literally the blink of an eye, and not its innate “intelligence.”

It is no secret that the Brits are obsessed with the weather, which means they fixate on forecasts. In order to improve the accuracy of its predictions, the country’s Met Office embarked on a lengthy implementation of a Cray XC40 supercomputer, the final phase of which went live in December last year, allowing its meteorologists to run 14,000 trillion calculations per second thanks to its 460,000 compute cores. And while asset managers currently don’t have access to that kind of firepower, AI does hold the key to providing them with the ability to make far more accurate calculations based on a sea of variables within their four walls that just a few years ago was unimaginable. But will AI be able to turn a buy-side donkey into a thoroughbred? No, almost certainly not at this point, but it will provide them with the means to systematize and enhance their decision-making, which is the next best thing. 

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