Unlocking the Future of Private Investments

I have teamed up again with Dynamo Software to talk about a hot topic:? Today’s trends on the use of AI.? ?

Join me, Hank Boughner (Dynamo’s CEO) and Jason Warner, CFA (Head of Data Science at Francisco Partners) on December 4th for a free webinar to discuss the survey findings.

Webinar Link:

https://attendee.gotowebinar.com/register/8364594524778997335?source=CapitalAllocators

A copy of the report can be found here:

https://www.dynamosoftware.com/alternative-investments-research-series-2024-ai-survey/?utm_source=CapitalAllocators&utm_medium=Email&utm_campaign=2024-AI-Frontline-Insight-Report

The technological advances in structured data, enhanced workflows, AI and edge computing is changing how we work.?The slow burn of progress in AI and software development over the last 30 years has made this year a tipping point into a new era. ?

From improving the way we diligence managers to the digitization of private markets we are seeing immediate adoption.

“This is only a foretaste of what is to come and only the shadow of what is going to be.? We have to have some experience with the machine before we really know its capabilities.”         

This is what Alan Turing said in 1950 about the computer or what he described as “the mechanical mind”.? Turing was a British mathematician and WW2 code breaker. He is most famous for developing the benchmark when humans cannot distinguish if an interaction is with a human or a computer. ? ?

We now know this as the “Turing Test”. ? ? ? ? ?

The topic of AI is pervasive in our industry and the Dynamo AI survey uncovers several things but one overarching headline is obvious:

AI is here to stay and we are in early innings.

While some quants and leading hedge funds have been using LLMs for years, the door has swung open and AI is no longer optional for alpha generation in this era of efficient markets.? ?

There are many AI aspirations for investment firms.? Many are lofty, forward thinking ideas that will require real tech budgets, tools and new human capital skillsets.

The good news is there are several things that are being used today and are available to most organizations. There are also some things on the horizon we should keep an eye on.?

Here are some thoughts:

Harvest the low hanging fruit

If you talk to investment teams today, there are some immediate use cases for the repeatable but crucial parts of the investment process.? When something new rolls out, people by nature will apply it to work that has the most friction.? Let’s name a few:

• The war on unstructured data continues for LPs. Allocators are extracting more data from our pdf-heavy world to consume and prosume data to gain new insights with faster data ingestion across disparate systems.
• The adoption of AI note takers is playing an increasing role in our workday. Reducing the friction of writing manager meeting notes and investment committee memos is in motion.? Analysts can now merely edit notes and upload it to an RMS resulting in a faster and more consistent knowledge sharing experience.
• AI is also playing a critical role in RFPs, DDQs and other documents that are content rich and repeatable, easing the burden for IR and client service professionals. ? ?

AI Fluency is not just for CTOs

If you look at the survey, AI initiatives are about direct investment process integration yet almost all of the efforts are run by the CTO.? This will have to change.

Investment teams are going to need to be adept at incorporating AI into investment research and process for alpha generation. This is analogous to when quants came onto the scene years ago.

There are also downstream effects on all stakeholders.? Importantly, legal and compliance teams will need to understand these integrations. IR teams will need to be able to discuss AI use in a way that is transparent, discernible and repeatable.

Creating New Knowledge Sets with Data Science

As the report highlights:? “GPs are focused most heavily on data analysis and predictive modeling (52%), indicating a trend toward leveraging AI for improved decision-making.? Real-time decision-making is also a priority, showcasing a belief that AI can increase agility and responsiveness.”

There is no better time to leverage the data we have available to us. Data quality in AI is a continued focus as third party market data is enriched with unique data sets to become the new sources of alpha.? Firms are quickly adding AI to their models for enhanced forecasting, capital market assumptions and other toy models on their desktop.

The question is will investors be able to see concentrated bets, trends and risks with a better and faster “MRI” on their portfolio?? We will see, but the good news is that data extraction is the fuel for improvement in processes and workflows.

The Risks of AI and Knowing Your Portolio

With the implementation of any new tool there are downsides.? One senior private markets investor told me they are taking the slow approach to using AI.? Why?? She fundamentally believes that AI can make us lazy.

If I can write a manager research report with a few prompts how well am I underwriting? While AI can help ease some of the grunt work in the investment office, we still need to own and deeply understand our portfolio.

If you go back in time this had played out before.? In 1982, digital clocks became mainstream. While most people were excited there was some concern. Some worried that we would longer be able to tell time.? One thing for sure is that managing change can be a troublesome endeavor.

Embracing AI creates new weaknesses as well as strengths. Understanding these risks and creating a new set of standards will be imperative.

Creating the Data Loop

Workflow automation is going to power the AI revolution. With 35% of survey respondents focused on portfolio monitoring this number will likely increase as data flows more easily into portfolio management systems.

We are seeing great progress with data integration and analysis into what I will call a “data loop” moving away from template uploads. This data loop will seamlessly extract information from pdfs into a firm’s OMS/PMS for immediate analysis by investment and ops teams.

While the industry is making progress on this holy grail of data extraction and workflow, LPs must take the long view.? There is often an imbalance of what LPs need to do their jobs effectively with the data/information GPs are willing to provide.? GPs need to protect (some) of their data as markets become increasingly efficient.? ?

The next wave of innovation will require: 1) CIOs to understand and own the role of AI at their companies 2) fluency across IR, legal, compliance and operations to integrate improved processes in a compliant manner and 3) allocators and ODD practitioners to have a firm understanding on commonly used AI frameworks and market-leading service providers that power investment firms.

We have come a long way since Turing saw the potential of the mechanical mind, but I am excited about what is next in AI for our industry.