AI and RPA in asset management

After a whirlwind of conferences this fall, I had a chance to flip through my notes and quickly identified one of the most-mentioned buzz words at CRM Forum, 2017 MMI Annual Conference, and MFEA Marketing Council: Artificial Intelligence (AI). I thought it would be worth exploring and sharing the common themes and highlights that resonated across these conferences.

Below is a sample of some memorable statements, from mainstage speakers to audience members, on machine learning, AI, and Robotic Process Automation (RPA). (Note: these are not exact quotes, but will help give a sense of industry sentiment on these topics):

  • Machine learning helps you look at every-day data in a new way.
  • AI is merely a buzz word. Find one or two use cases that are truly value-add and run with those. The results may end up being more predictive than true AI.
  • Robotics (RPA) has been one of the most important technology investments in asset management. Successful application of RPA can be seen in: trade reconciliation, compliance, data entry from Excel spreadsheets and paper forms, yield calculation, and more.

During many of these sessions, the lines between AI and RPA appeared to blur as there were different interpretations depending on the firm and use case. However, panelists appeared to unanimously agree on the importance of having a robust amount of the right data going into the effort; a mature data management strategy; and monitoring and testing to ensure you get the right results. My sense was that, while AI could have potential as interest grows, RPA currently has more practical application in the asset management industry, but what does SalesPage think?

I asked some folks at SalesPage for their takes on AI and RPA, and how it may impact our industry and product development. Here’s what I learned:

  • The perception of AI and machine learning is that it’s easy, but in reality it’s a rigorous process. You need more than a working knowledge of statistics to get results that are questionable at best. There are roughly only a few hundred thousand reps in the asset management industry, while Google has tons of data to draw on examples. Better data will give you better results.
  • The current forms of AI are heavily based on real-time access to pertinent data. Most asset managers have a long way before they can effectively handle this. SalesPage engages with all of our clients to update their data architecture and to continuously enhance their data management strategy to support AI in the future.
  • Several of SalesPage’s clients leverage our native functionality to enable basic RPA principles that enhance workflow and accelerate data standardization, enrichment, and usability across their organizations.

Based on both thoughts from the industry and SalesPage, I’m going to say that some principles of RPA are further ahead with our clients, but we’ll have to see where AI goes in the coming years! As always, if you’d like to continue this conversation, contact us. We’d be happy to share some examples of work we did for our clients with technologies like these that innovate alongside the industry.