From Chatbots to Ambient AI.

Cloud-based AI and Machine Learning technology is readily available. Large technology platform companies such as Amazon (Alexa), Google and Microsoft (Azure), encourage third-party developers to build applications and services on top of their core AI and Machine Learning platforms. This enables developers to focus resources on building value through the user experience and decision support systems, not having to concern themselves with core AI investment.

Chat bots are a good example of simple AI technology that has enjoyed broad adoption across industries.

The next AI iteration will be voice-enabled applications powered by decision support systems seamlessly integrated with cloud-based core AI and ML offerings (the latter primarily from Amazon, Google and Microsoft). Some refer to these integrated systems as “Ambient AI”. The user experience will look similar to Google Assistant (see end of article for video), but rather than booking hair salon appointments, the conversation may go something like this:

• Me: “HAL, I’m concerned with Mark Zuckerberg’s recent post regarding changes to Facebook’s business model. Show me our exposure to Facebook across all funds.”

• HAL: “Sure Jonathan. Total Facebook exposure across all funds is $2.153 billion. A precedent does not exist for a social media company of Facebook’s size as it relates to changes in business model. Would you like to reduce the firm’s position in Facebook?”

• Me: “Yes HAL. Please reduce our Facebook market value exposure by 10% through a series of market orders over the next 30 days.”

HAL will execute the order (so long as it doesn’t go rogue), in a manner so as to minimize the impact to portfolios that own the stock.

The underlying technology in the example above isn’t so different from today’s Quant funds with one exception – that being the human-machine voice interaction – including the machine’s ability to anticipate potential questions and instructions (“..precedent does not exist…” and “would you like to…?”).

New Fintech Players?

My imagined interaction with HAL requires seamless integration of three critical technologies:

• Core AI & Machine Learning: dominated by Google, Amazon and Microsoft.
• Decision Support: Which companies will fill the void?
• Voice: dominated by Google and Amazon.

Who will step-up and fill the Decision Support void? We have some thoughts. In our investment front-office example – which would theoretically extend to related front-office investment functions such as Product Management – there are a number of technology company candidates that may make HAL a reality:

• Tech Startups and Tech Giants: historically market disruption and innovation comes from new companies and new market entrants. Players in the former category are largely unknown. Players in the latter category include the previously mentioned technology platform companies: Amazon (tkr: AMZN), Google (tkr: GOOG) and Microsoft (tkr: MSFT).
• Fintech Front-Office Incumbents:
  • Bloomberg (Pvt.): The $60,000 question is what is Bloomberg’s endgame? IPO or Sale? I expect the status quo from Bloomberg and the firm becomes less relevant with each passing day. In the future investment decisions will increasingly be made by analyzing alternative data sources, not by running EPS regressions.
  • FactSet (tkr: FDS): FactSet is at least making an effort to leverage alternative data sources via partnerships. I would like to see the firm become more aggressive on the alternative data front. FDS operates conservatively in a highly fluid end market. Ambient AI is an opportunity that I fear FactSet will miss.
  • IHS Markit (tkr: INFO): Historically a highly ambitious firm with a risk-taking founder CEO. The question here is will IHS Markit allocate more capital and resources to the Financial Services side of the business or to the legacy IHS side of the business?
  • Morningstar (tkr: MORN): Steady as she goes under Kunal Kapoor. MORN may not have the scale to drive innovation as it relates to Ambient AI.
  • Thomson Reuters (tkr: TRI): Muddled strategy, significant opportunity cost. What could have been!
• Established Fintech Players: These companies (some Fintech pure-plays, some not), aren’t new to the scene but historically have not played exclusively in the investment front-office.
  • IBM (tkr: IBM): I typically push back on IBM, particularly as it relates to the company’s M&A strategy. Here I believe IBM is uniquely qualified to deliver on the Ambient AI vision. IBM combines AI and Machine Learning knowledge (via Watson) with systems integration capability and the familiarity of working with large financial services firms.
  • Oracle (tkr: ORCL): Oracle needs to do something dramatic as their mission has become muddled. This is what happens when you have a distracted founder who remains entrenched in the business. I don’t envy Safra Catz or Mark Hurd.
  • Pegasystems (tkr: PEGA): Unlike Oracle founder Larry Ellison Pegasystems founder & CEO Alan Trefler is anything but disengaged. Pegasystems is well versed in the Financial Services domain, understands AI, ML and RPA and has expertise around making complex systems work with one another.
  • SAP (tkr: SAP): SAP has done much to acquire horizontal expertise (advanced analytics for example). Now the firm needs to build out its industry vertical expertise outside of Auto and Aerospace. Investment Management is an obvious vertical to pursue particularly as the investment decision-making process is increasingly data driven. SAP’s real-time analytics offerings would be complemented nicely by acquisitions of FactSet and/or Morningstar on the structured data side and Quandl on the alternative data side.
  • SS&C Technologies (tkr: SSNC): SS&C’s new middle office, back office platform – Singularity – combines AI, machine learning and RPA architected from the ground up. We would love to see SS&C acquire Capital Markets data capability to more fully build out the front-middle-back office stack. That said, the opportunity on the Pharmacy Administration side (via the DST acquisition) is a much larger revenue opportunity. The player that people don’t often mention on the Pharmacy side is Amazon. The firm recently acquired PillPack, not to mention the firm’s JV with JP Morgan and Berkshire – which now has a name and a website: Haven.
  • Tibco (Pvt): Vista-owned Tibco is well-versed in advanced analytics and visualization. Some of the smartest visualization applications I’ve ever seen were developed by Spotfire (now Tibco) in Somerville MA in the early-to-mid 2000s and were deployed at large institutional investment firms such as Fidelity Investments.
  • Verisk Analytics (tkr: VRSK): Verisk plays primarily on the risk management side and has plenty of room to grow within Asset Management/ Financial Services. The firm is no stranger to large, complex enterprise deals.
  • One could make a case for the large technology consulting firms such as previously mentioned IBM, Accenture (tkr: ACN), Cognizant (tkr: CTSH), Infosys (tkr: INFY) and others.

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