Executive Chairman, Neuravest
It’s no secret that recent years have seen a rapid proliferation of data, especially alternative data. Between 2010 and 2020, the amount of data created, copied, captured and consumed increased by 5,000% (according to Forbes). In the investment management space, this means firms have an unprecedented amount of information to leverage when making critical trading and portfolio management decisions. In theory, this is a good thing, but the reality is that the vanishing scarcity of data has led to stagnation for many asset managers.
This trend has coincided with the continued rise of passive investment management and, accordingly, the decline of active investment management. These approaches have roughly equal representation in the marketplace but are trending in opposite directions. Active management is a failed approach – these funds simply don’t have a track record of beating their benchmarks. Meanwhile, passive management is a road to institutional parity, as there’s no way to meaningfully differentiate between funds that follow the same index – yet investors are flocking to them for their low cost, yet still forced to compromise on slow and steady lackluster returns. All of this is occurring amid a background of margin compression, making it harder than ever to stand out.
In this environment, an approach that offers the upside of active management and the safety of passive management is the holy grail. Investment managers can achieve this by embracing a third investment approach: adaptive investment management, a cutting-edge strategy that combines human-driven investment strategies, AI-driven analysis and data-driven execution.
We know that the clearest path to success as an active asset manager is having better data – but how is this possible in a world where everyone has an internet connection and a Bloomberg Terminal? The answer is that while data may be widely available, determining which and when datasets are most predictive remains a significant challenge. To solve it, active managers can’t take a page from their passive counterparts, but rather they should leverage AI and machine learning to integrate a wide variety of technical, fundamental and alternative factors into their investment research process.
This approach is made more difficult by the fact that many asset managers are already struggling to keep pace with standard day-to-day business challenges, such as compliance, traditional research, client management and trade execution, that have come to define our industry. That’s not a knock on these firms – it’s just that querying massive quantities of data to find the predictive needle in an information haystack generally doesn’t fall under their core competencies. This is an ideal use case for another approach that asset managers must leverage to keep pace in today’s markets: outsourcing.
The New Face of Outsourcing
There are some big egos in our industry (present company included!), but even the most successful asset managers will acknowledge the impossibility of being the best in the world at everything they do. By keeping their core competencies in house and outsourcing other functions, these firms can offer comprehensive, differentiated solutions without being pulled in too many directions.
Outsourcing is not a new concept, but the need for innovative strategies like adaptive investment management means it must now be applied in a new way. This isn’t about hiring a third-party vendor to deliver cost savings to some back-office process. This is about identifying strategic partners that can bring to bear a core competency for asset managers to exploit that can drive revenue and improve performance.
Those who are skeptical need look no further than Vanguard, one of the largest and best-known asset managers in the world, for an outsourcing success story. Vanguard made its name pursuing passive strategies, but it knew customers were looking for actively managed products as well. Instead of pouring resources into an area that fell outside of its wheelhouse, the firm outsourced its active management to some of the foremost active managers in the world: PrimeCap, Wellington and Baillie Gifford.
This has resulted in a model through which Vanguard can rapidly offer new products while retaining the distribution, service and support that made them a market leader in the first place. It’s a case of a manager pursuing outsourcing not to make existing functions less expensive, but to unlock new revenue streams while retaining its key differentiators.
Adaptive investment management requires active managers to take the same approach. The level of analysis needed to reliably beat the competition is unattainable for many firms, but by focusing on their core competencies and outsourcing the rest, they can offer best-in-breed solutions far beyond anything they could have achieved by going it alone. That means that while bread-and-butter functions like investment strategy creation and management, distribution, marketing and logistics may stay in house, more technical functions like data selection and validation, fund allocation optimization, hedging and execution are performed by third-party experts.
This isn’t mere handwringing. The numbers are clear: If active managers do not act, they will continue to miss their benchmarks and lose market share. These firms have a choice: ride a fundamentally flawed approach into the ground, or adapt with the times and live to invest another day.
While the explosion of data may appear to have leveled the playing field, the reality is that it has only changed what is needed to gain an edge. While the key to strong active returns was once simply access to data, now it is the ability to identify the most predictive signals within widely accessible data. This new paradigm requires that asset managers take new approaches, with alternative data validation and AI investment, outsourcing and honest self-assessments of core competencies at the forefront.