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16 July 2024

From Theory to Practice | AI in Investment Management

You can hardly read an article or discuss tech without mentioning artificial intelligence (AI). The talk surrounding AI is omnipresent, influencing sectors far and wide, including investment management. Yet, a pertinent question arises: How are firms harnessing AI to their advantage, particularly in your industry?

Are wealth managers leveraging Artificial Intelligence?

Our episode of Tech it Up cuts through the noise and dives into practical use cases for AI. Hosts Trent and Jasmin sat down with a couple of experts on the topic: Jaci Stanton, Managing Director of F2 Strategies, a wealth management technology consulting firm, and Prakash Kanchinadam, Vice President of Engineering for SS&C Intralinks. The good news is that if you’re on the fence about AI, you’re not alone – and you’re not behind.

Recently, F2 Strategies conducted a survey to determine whether wealth managers are using AI and, if so, how. Jaci reports that about half the respondents said they were actively using or testing AI in three key areas: workflow automation, predictive analytics, and generative AI to create content for communications with clients. While there is still some discomfort and uncertainty, these firms are forging ahead.

SS&C Intralinks is a business unit of SS&C that specializes in technology to support merger and acquisition activity, in particular, a virtual “deal room” for sharing information among the various parties in a transaction. Due diligence in M&A entails the exchange of thousands of documents and highly sensitive, confidential information. Prakash says the group has been using AI for about five years, developing models to help organize, streamline, and speed up the due diligence process.

We’re still talking about data quality.  

In addition to practical use cases for AI, Jaci and Prakash discuss some issues it raises. The main one is data quality – an AI model is only as good as the data used to train it, so firms need to ensure they have quality, clean data before attempting any AI initiative.

Regulatory issues also come into play. For example, if firms rely on AI models for personalized client recommendations, the methodology behind the model must be traceable and explainable. Firms should be able to attest that there is no inherent bias in the model’s training and that any recommendations are truly in the client’s best interest.

What should investment managers expect?

While AI isn’t likely to be a marketing differentiator for investment managers, Jaci says it presents opportunities to optimize the time managers spend with clients. At a time when organic growth is challenging, AI-powered solutions can help drive operating efficiencies that benefit the bottom line. She suggests that firms focus first on small wins that help make their lives easier, such as automating client communication. “Slow and steady wins the race,” she says.

The evolution of investment management into the AI-powered future is ongoing, bringing challenges and opportunities for those willing to navigate the dynamic landscape. If you're seeking insights into how firms leverage AI in investment management, check out our podcast episode, Adapting to Change: The Future of AI in Investment Management.

Also available on Apple and Spotify.