Scale your business, not your operational overhead

Much has been said and written about the efficiency benefits to be reaped from Artificial Intelligence and Machine Learning. Yet many firms in the financial sector, particularly the private market space, are still in the early stages of adoption.

There are understandable reasons for this reluctance, starting with timing and cost. There’s the issue of choice (‘which technology is right for me?’). And there’s the risk of talent mismatch if investment managers lack the right people to use these new tools correctly to systematize processes and improve outcomes.

Fortunately, you can leverage the benefits of AI/ML without installing and maintaining costly technology platforms or hiring a new team of data scientists.

Services providers such as Linedata can provide managed as-a-Service access to AI/ML platforms – or a fully-fledged AI/ML solution, complete with trained quants and financial analysts who function as extended members of your team.

The benefits of this approach are multiple. You can streamline and automate front office risk and research functions, scale your business, and achieve better outcomes without the need to invest in expensive platforms or hire, train, and retain your specialist staff.

And, by outsourcing and automating non-investment activities such as research and risk, you can empower your front-office teams to be even better in their roles.

The light bulb moment

Of course, some fund managers might initially argue against outsourcing anything to do with the front office. This can be seen as the inner sanctum, the place where a manager’s ‘secret sauce’ is fiercely protected.

Others, however, have already experienced that ‘light bulb’ moment. Partnering with an outsourced AI/ML provider is speeding such firms’ ability to complete more high-quality deals and steal a march on their competitors – while achieving significant cost savings, and without surrendering any trade secrets.

In short, far from watering down one’s secret sauce, AI/ML automation offers a way to add more spice, more pep. Rather than your teams being distracted by time-intensive manual tasks, automation frees up more hours for senior analysts to focus on deals.

Command and control

For some investment managers, taking the necessary steps to introduce automation in their risk and research processes might sound like a difficult proposition: one that requires a collective leap of faith.

However, rather than worrying about outsourcing leading to a loss of control, firms should view this as a way to achieve a “command and control” operating framework. Such a model will enable them to scale their business, leverage highly skilled expertise, and use AI/ML to empower, rather than undermine, the best of their analysts and portfolio managers.

As the opportunity set continues to grow, the best-run firms will evolve beyond the old-fashioned linear model of building everything in-house, from systems to headcount. AI/ML provides a geometric path to achieving scale and greater automation, giving managers the right expertise exactly where it is needed to augment their front-office activities.

In so doing, they can build sustainable, long-term business models that can absorb future market shocks and turn uncertainty into opportunity.

About the author, Rama Krishna

Rama Krishna is the Executive Director, Center of Excellence India at Linedata.