By Vera Huang, Head of Data Solutions, Asset Owner Solutions
Whether you’re C-suite in a private markets management firm or a fund administrator servicing private markets investors, we can all agree that the private markets infrastructure needs a long-overdue makeover. Specifically, the technology and data infrastructure supporting businesses in this space.
In recent years, it’s become increasingly apparent from our conversations with private markets managers that they’re looking for more from us as their fund administrator. It is expected and taken for granted that we’ll get the fund admin and accounting right, but what else can we do for them? How else can we add value?
As a fund administrator, we process a lot of data for our clients, and it’s in this space where we believe the real opportunity for value creation lies.
To process client data effectively and efficiently, we use a lot of technology and tools. We’re technology agnostic and don’t believe there’s one tool that can solve it all. That said, all the technologies we’ve adopted (and will continue to adopt in the future) must fit into a unified platform strategy. For us, that strategy is focused on giving our clients transparency, at scale, with flexibility. It may sound like an oxymoron – scale and flexibility – but that’s exactly the balance we need to strike every day, especially for private markets investors.
Data rich, insight poor: moving away from this dilemma
The private markets have their quirks, one of which is the amount of unstructured data that needs dealt with. We’ve developed a love/hate relationship with PDFs as a result. We love sending a PDF but hate receiving one. We love it when we manage to pull data together into an insightful and nicely formatted report; we hate it when we need to digitise and extract data from a PDF before we can do anything with it.
Structuring unstructured data
When it comes to turning unstructured PDF-based data into structured data (which then allows it to be translated into actionable insights), there are different ways and tools through which this can be achieved:
1. Digitisation tool
This type of tool usually comes with optical character recognition (OCR) and/or machine learning capabilities, allowing KPIs to be extracted and put in a query-able format
2. Natural language conversational interface
In recent years, driven by the rise of generative AI, tools such as Microsoft’s Copilot have gained traction, allowing end users to query in a natural language and get information directly from such platforms. There are many vendors in this space and they usually partner with large language model (LLM) providers (such as OpenAI or Anthropic) to develop their platform. Beyond the strength of the underlying model, it’s important that end users input logically strong prompts for the right information to be retrieved.
Turning structured data into insights
Once we’ve turned unstructured data into structured data, how do we then turn it into actionable insights? With the rise of natural language querying, does this mean the death of dashboarding and business intelligence (BI) tools?
Absolutely not.
Dashboarding, BI tools, or what I would call pre-built analytics – they have served and will continue to serve a specific purpose, which is reporting in a pre-agreed format, delivered at an agreed frequency. For example, quarterly investor reports and board packs.
Natural language query, on the other hand, supports on-the-fly queries, providing busy executives with quick answers to specific questions. This feature can be built into a reporting tool or upon a data warehouse, requiring underlying data to be structured into a business glossary so that end users can query using business terminology they are familiar with, without learning how to code.
For clients of ours who’ve implemented their own technology platform, we facilitate downstream integration with their system via our data warehouse and its adjacent tools, giving back their data that we’ve processed on their behalf.
Setting the right foundation
While fund administration has become table stakes for private markets managers looking to outsource their back-office functions, we’re now at the point that effective data management needs to be considered similarly foundational in order for these managers to ride the next AI-driven wave of evolution, using data-led insights to guide investment decision-making and stay competitive.
To this end, it’s critical that private markets investment data is captured and structured in a logical, consistent and standardised manner.
We are familiar with the saying that execution eats strategy for breakfast; I’d say that data quality eats the best technology for breakfast. Without good quality data, even the best technology developed upon the most advanced LLM will not give us the insights we’re looking for.
A key question for private markets managers to ask themselves is this: how are you working with your partners to ensure investment data is captured correctly, so that the right tools can be deployed to give you the insights you need – not just for now but well into the future?
Get in touch
At IQ-EQ, our holistic approach to data management includes data collection, aggregation and exchange, in addition to central fund administration. We utilise our Snowflake-based data platform to curate and transform data on behalf of our clients, bringing together disparate data sources and delivering actionable insights.
Click here to find out more or contact our expert team today to discuss how IQ-EQ’s comprehensive data services could add value for your firm.
