AI in investment management is revolutionizing the entire industry. With a proper understanding and a plan in place, wealth and asset managers can get the most out of machine learning.
The adoption of artificial intelligence is picking up steam, and investment organizations that want to stay competitive will be wise to leverage the technology.
After all, financial institutions that leverage AI in the investment process can grow AUM by 8% and raise productivity by 14%, according to Deloitte.
And investment firms aren’t waiting around to start implementing the new tech. Consider these stats:
With all this in mind, there is a lot to consider when implementing machine learning.
For so long, the talk of AI often felt like a “tomorrow” thing, something that could be beneficial or otherwise, depending on your perspective.
The reality is that it’s here now.
Whether it's investment research, risk management, compliance, or other relevant functions, we are only at the start of a monumental shift in how the technology will be used. Every investment firm should develop an AI strategy.
For all the AI use cases in investment management, it’s impressive what machine learning can do, but it can’t do everything.
The technology has come a long way, but it still has a long way to go.
Maybe the tech will get you 60% or 70% the way there, and that’s ok. If it frees up time in some way, that’s still a win.
And over time, the AI will be just that: more intelligent.
But know its limitations, and allow for human oversight.
Machine learning presents a lot of opportunities for improvement in investment research, risk management, generating alpha, and the client experience, among other area
As the technology performs increasingly higher-level tasks, many people fear AI could put them out of a job.
While AI will be better at doing certain tasks, the technology still isn’t perfect.
Using ChatGPT as an example, it’s a powerful tool, but it’s not going to replace financial advisors.
On a related note, don’t view yourself in competition with AI, but embrace AI.
Use where appropriate with data analytics, research, trading, compliance, sales, marketing, and other areas you find it potentially helpful.
Ultimately, you’ll be able to make decisions faster, get more done, and communicate with more clients and more frequently.
In short, the human element is still necessary. However, as the technology gets smarter, it will require upskilling. Humans cannot stay static in their skill sets as AI improves.
As artificial intelligence gains ground, you’ll see 2 types of investments:
There’s good reason to invest in AI for sure, but the enthusiasm can lead to emotional investment decisions.
Investments in AI-related startups hit $5.9 billion in 2022, and with all that money thrown around, there’s no guarantee every firm’s AI solution will come to fruition, be it in terms of portfolio returns or performing desired functions for internal use.
Samir Kaul, founding partner at Khosla Ventures, shared his view about the phenomenon:
"Now you are getting this herd mentality (among venture capitalists). (Lackluster investments) will get funded, but fail and give the entire sector, which is very promising, a black eye."
In short, investment managers must do their due diligence in AI investing, be it for internal use or portfolio returns.
AI is best used for the more complex of processes that require the thought process of humans, except faster and with fewer human mistakes.
And for more straightforward tasks, those manual and routine, investment managers can leverage automation.
Bots can be deployed into their systems to perform various tasks, including private equity statement downloads and processing, from start to finish.
For workflows that still require human input but are not the organization’s core competencies, wealth and asset managers can outsource various functions, including back-office operations.
Especially if you’re a small- or medium-sized organization, you either don’t have the time or expertise to implement the AI or automation capabilities in house.
Besides, it’s not the best use of time doing that work.
Firms should focus fully on revenue-generating activities.]That’s why we recommend investment firms to partner with third parties who have expertise in their respective fields.
These vendors have the internal resources to do the job better and faster, and at a lower cost than it would be doing those jobs internally.
At Empaxis, we are all about leveraging technology to the max. If we can speed up reporting and data management processes using bots, better integrated data, and any technology our clients use, we will build that solution.
Indeed, AI gives investment firms all the benefits when properly used and understood.]
Machine learning is here, but it’s not a perfect solution. The tech will improve, but to the extent one upskills, AI will complement their skill sets rather than compete against them.
Similarly, with all the talk about AI investing, wealth and asset managers must be careful about the AI applications they invest in for internal use, as well as those they invest in for portfolio returns.
And by partnering with AI service providers, as well as automation and outsourcing solutions providers like Empaxis, investment firms will enjoy a fully modernized operation that is built to last for years to come.
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