Companies mentioned: Adobe (tkr: ADBE), Alteryx (tkr: AYX), Amazon (tkr: AMZN), Automation Anywhere (private), BNY Mellon (tkr: BK), DataRobot (private), Google (tkr: GOOG), Microsoft (tkr: MSFT), Pegasystems (tkr: PEGA), Salesforce (tkr: CRM), SAS (private), SS&C Technologies (tkr: SSNC), Tableau (tkr: CRM, acquisition closed August 1st 2019), Tibco (private). Word count: 1,111.
Two major trends have dramatically changed the Asset Management industry over the past number of years: 1.) a massive rotation of assets from actively managed products to passive products and 2.) fee compression. To a degree the latter is the result of the former. As alpha generation is de-emphasized, asset managers must look elsewhere for sources of competitive advantage and financial performance. Artificial Intelligence (“AI”) and related technologies can be that strategic lever.
For purposes of this article we won’t focus on active managers that leverage AI and Machine Learning (“ML”) to power their investment decision-making process. We will instead focus on other functional areas that may leverage AI, ML, Deep Learning (“DL”), Robotic Process Automation (“RPA”) and Predictive Analytics, collectively known as Intelligent Process Automation (“IPA”) when they work together in a cohesive system.
Sales & Marketing
Sales & Marketing is one area where asset managers may leverage Advanced Analytics (including Predictive Analytics) and AI to grow Assets Under Management (“AUM”). The Asset Management industry is just scratching the surface as it relates to online marketing efforts including targeted advertising, SEO, social media marketing and online campaigns with video as the common underpinning.
Business Intelligence, Reporting & Analytics have been central to Asset Manager marketing efforts for years. Now, Advanced Analytics and AI are increasingly playing a role across Sales & Marketing operations. For example, Microsoft has incorporated AI capability into its Office 365 product suite. Similarly, Microsoft’s social network/ business development platform – LinkedIn – centrally manages its machine learning models with a homegrown “AI Automation” platform named “Pro-ML”. Adobe’s Creative Cloud leverages Adobe’s “Sensei” AI capability to automate various elements of the creative process. Salesforce will accelerate its AI/ML/data effort with its recent acquisition of Tableau Software. Alteryx, DataRobot and Tibco are examples of companies that leverage advanced analytics, machine learning and visualization tools (Tibco Spotfire) to parse, analyze and visually represent data which may be used to develop go-to-market strategies, model future sales activity and shape marketing campaigns.
Investment Operations & Intelligent Process Automation
Investment Operations (middle and back office), represents another significant opportunity for Asset Managers to leverage IPA in the pursuit of operating efficiency gains (30-40%) and developing a sustainable competitive advantage.
IPA can provide a sustainable competitive advantage assuming a long-term commitment to people and technology. We can’t imagine a fully autonomous investment operation within the next 10-15 years. Over the near-to-intermediate-term IPA will be less about entirely removing the human element and more about automating low value-added tasks, therefore enabling people to pursue high value-added activities. For example – automating regulatory reporting and creating time for people to support the Sales & Marketing functions in a “middle office” capacity – resulting in better utilization of internal resources and reducing the demand for additional outside resources.
There are a number of approaches and delivery models available to Investment Operations in terms of applying advanced technologies to their day-to-day operations:
1.) Partnering with an investment operations platform provider: Companies such as SS&C Technologies incorporate IPA elements including AI, ML, RPA, NLP, predictive analytics and more into their technology-enabled services. SS&C Technologies has infused its comprehensive new “intelligent investment operations” platform – Singularity – with these cutting edge technologies. The primary benefit of partnering with a market leader such as SS&C is that you the Investment Manager can focus on your core competency – gathering and managing assets. Further, delivering on the Intelligent Process Automation vision requires scale. Lots of people (data scientists, engineers, neuroscientists) are required to build and refine the various data models that power these complex technologies and systems. SS&C is uniquely positioned as it has both the scale and domain expertise to deliver on the IPA vision.
2.) Point solution vendors: Asset Managers may work with technology vendors that specialize in a particular area – for example – RPA provider Automation Anywhere. In addition, the large platform players such as Google (Google Assistant), Amazon (Alexa) and Microsoft (Cortana) have invested heavily in Natural Language Processing (not all of the press has been positive) and various deep learning models which power the conversational AI/ voice-based services commonly found in customer support areas.
3.) Full Outsourcing: Offered by the large service providers ranging from the traditional, people-heavy service providers such as Bank of New York Mellon and the other custodian banks to technology-first providers such as SS&C (SS&C offers a variety of delivery models including private cloud hosting, multi-tenant environments, co-sourcing of specific workflows to full operational outsourcing).
Certain Asset Managers may prefer to build their own IPA processes using a combination of FinTech point solutions and AI-powered cloud services offered by Google Cloud Platform (“GCP”), Microsoft Azure and AWS. Our advice is to start small in terms of project scope. Second, use “off-the-shelf” products and services wherever possible.
- First: Define the business problem or use case.
- Second: Understand the data you may leverage both in terms of its availability and readiness (by “readiness” we are referring to the fact that data typically must be cleansed and prepared before it may be utilized. Otherwise, “garbage in, garbage out”). Certain data sets may connect via APIs, others may require a more formal integration such as made possible by SS&C Salentica Data Broker – a data integration product that enables wealth advisors to automate workflows by porting data from one application to another. This second phase also includes understanding what data experts you may have on staff that may be utilized for an AI/ IPA project. These professionals – “data scientists” – will have advanced degrees in mathematics and/or statistics.
- Third: Our recommendation is to work with commercialized AI and Advanced Analytics products, tools and services such as those offered by SS&C Technologies, Pegasystems, SAS and DataRobot rather than build your own. These technologies require significant investment at scale to consistently drive innovation. We’ve previously seen the movie where financial institutions built homegrown technology solutions in the 1980s, 1990s and early 2000’s. Today many of those legacy technologies offer little to zero value as they were one-off solutions.
For more information see our note “No Time Like Now to Leverage AI”. You may reach us at email@example.com. Join us on Tuesday September 17th in Orlando for the “Practical Applications for AI in Investment Operations & Accounting” panel at SS&C Deliver. Learn more here.
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