As data science, machine learning, and artificial intelligence continue to influence nearly every industry, automation could open up new opportunities for alternative asset managers

As data science, machine learning, and artificial intelligence continue to influence nearly every industry, automation could open up new opportunities for alternative asset managers

 

 

Opportunities in alternative assets continue to grow. However, to operate at scale and service the largest asset managers, processes need to be automated to efficiently manage the volume of written documentation and data.  

Process automation can create efficiencies, but as internal skillsets and operating models change over time, the living process must be constantly monitored through metrics and KPIs to retrain and adapt models. This approach requires a short-term view where you can quickly iterate to see what works and what doesn’t.  

We found that it’s crucial to accept that things might not work out in the first use case – but the second or third could be the one. Going through use cases quickly helps to maintain a competitive advantage and to roll out new services. This concept may be inherent for technology firms, but we needed to build that within our culture. Basically: try stuff out, fail fast, keep going.  

One of the methods we have worked with to bring scale is natural language processing (NLP), a form of artificial intelligence (AI). This was the obvious place for us to start, given the amount of documentation we process, and so we looked at specific use cases to review internal processes. While we were able to find some viable methods, our short-term mantra rang true in other cases. With NLP, you may never get a particular piece of information in a machine-readable format. And that was OK: we saw a place NLP didn’t apply and moved on.  

In some cases, you’ll find that NLP, or any AI, isn’t the answer at all. From here, you take a step back, rethink, and adjust the process logically. You confer with your technology experts, data managers, and operations teams on what they need automated and focus on that. That’s when you see fundamental change and enhancements, because these people know how the processes will work and support clients day to day.

Efforts to more efficiently manage our data led to the development of our common data platform (CDP). We built new products like our Forex and ESG offerings that feed data into the CDP while also migrating all legacy data. We built a way to take data, centralize it, and standardize it, making it more accessible. This infrastructure also allows us to offer data as a service, adding technology and analytics to our broader professional and banking services.  

Right now, the industry is primarily file based and not entirely on board with using these new technologies. Storing data on our CDP allows larger managers to start integrating with APIs and real-time notifications; even though the smaller managers might not be there, we can still provide them with the same access if they can manage the integration. We believe the industry is heading this way and expect more managers to utilize new ways of consuming data.

 

This article originally appeared in the Preqin Special Report: Service Providers in Alternative Assets 2021. The opinions and facts included within the above do not constitute investment advice. Professional advice should be sought before making any investment or other decisions. Preqin and MUFG Investor Services providing the information in this content accept no liability for any decisions taken in relation to the above.