The number of investable assets has grown 10x in 20 years

We all know we’re in an era of data growth -few industries feel its impact as profoundly as financial services. At the forefront of this data revolution stands Morningstar, a company that has become synonymous with investment research, data, and analysis. Lee Davidson, Morningstar’s Chief Data and Analytics Officer recently shared insights into the company's evolution, challenges, and vision for the future of financial data.

The Expanding Universe of Investment Products

The financial landscape has undergone a seismic shift in recent years, with the number of investment products exploding at an unprecedented rate. Davidson notes, "In the asset management industry, we have seen approximately 9% CAGR over the last 20 years in growth of products available for sale globally. There's more than a million products available for sale now – that is a tenfold increase from 20 years ago."

This proliferation of investment options has created both opportunities and challenges. While investors now have access to a wider array of products tailored to their specific needs, the sheer volume of choices can be overwhelming. Morningstar's role in this ecosystem has become increasingly crucial, as Davidson explains: "The role of data and analytics in helping to make sense of options in this ecosystem is growing in importance."

The company's approach to tackling this challenge involves a multi-pronged strategy. First, they focus on gathering and organizing the performance, portfolio, and operational data required for investors to make informed decisions. Second, they categorize products to facilitate meaningful comparisons. Finally, they provide their own insights through portfolio analytics, asset allocation, and their well-known rating systems such as the Star Rating and the Medalist Rating.

The Power of Persistence: Long-Term Vision in a Fast-Paced World

One of the most striking aspects of Morningstar's approach to innovation is its willingness to invest in long-term projects. In an age where startups often prioritize quick wins and rapid pivots, Morningstar's commitment to seeing through multi-year transformations sets it apart.

Davidson shared a compelling example of this approach with the development of their Medalist Rating system. "We knew that investment products were proliferating faster than we could reasonably scale our qualitative research team. So we knew we needed a machine learning approach to help us scale our insights. We tested this approach internally for five years before we got comfortable to deploy it initially," he recounts. "We launched it as an independent product, allowing us to focus on iterative development. And during that time, we kept that team separate and focused. Over the next five years, we incrementally expanded coverage of this machine-learning approach from one country to another, from one vehicle type to another."

This patience and persistence paid off. The project, which began in 2011, culminated in 2022 with the merger of these two rating systems under the banner of Medalist Ratings, effectively increasing their analyst throughput tenfold. Davidson emphasizes the importance of this approach: "Large transformations can sometimes take more than five years. Patience is important. In this case,. success took 10 years before we really saw it through to fruition."

The Data-Savvy Consumer: Evolving Demands and API Integration

As financial data becomes more complex and ubiquitous, consumers' data literacy has been steadily increasing. Lee Davidson notes this shift in client expectations, particularly in how they want to access and interact with Morningstar's data.

"15 years ago you didn't have too many requests for an API endpoint," Davidson observes. This evolution in client demands reflects a broader trend in the financial services industry, where data accessibility and integration have become paramount.

The transition from traditional "binder world" deliverables to API-based data access presents both opportunities and challenges. On one hand, API access points offer "more scale and frictionless experience on both sides," potentially streamlining data delivery and integration for clients. However, this shift also requires careful management of the transition period, as some customers may not be ready to move away from legacy data delivery methods.

Another part of maturity in the financial services industry comes in the form of enhanced data governance. Davidson highlights a significant trend among Morningstar's clients, particularly on the asset management side: "the creation of data functions, where previously there were not." He cites T. Rowe Price as an example, noting their recent addition of roles like Chief Data Officer and head of data governance. Vanguard and Morgan Stanley are other notable examples. This trend provides evidence that asset management and wealth management firms are maturing beyond just how they consume data to how they can actively manage it within their organizations in a state-of-the-art way. 

Davidson recounts from a recent Financial Times conference called the Future of Asset Management stating that "every single panel, whether it was leadership from sales, strategy, compliance, legal, emphasized the importance of data to the future success of their businesses.," This widespread recognition of data's importance is driving increased data budgets and sophistication among asset manager across the board. 

The growing data literacy is also leading to more nuanced and technical requests from clients. Davidson mentions that clients are now asking for more detailed data lineage, a level of detail that wasn't typically requested in the past. This shift underscores the increasing sophistication of data consumers and their desire for transparency in data sourcing and processing.

Unstructured Data: The Final Frontier

While Morningstar has made significant strides in many areas of data processing and analysis, one challenge continues to loom large: unstructured data. The company ingests an enormous volume of unstructured data. For example, Morningstar ingested more than 150 million PDFs in the last year alone. These documents, ranging from prospectuses to regulatory filings, come in dozens of languages and various formats.

"We have automation rates right now for unstructured documents in the single digits compared to price and portfolio data ingestion sitting in the high nineties," Davidson reveals. This disparity highlights the complexity of extracting structured information from unstructured sources.

However, Morningstar is not backing down from this challenge. The company is in the midst of a multi-year transformation project leveraging generative AI to tackle this problem. "We've deployed it in five or six cases in production, but there are probably hundreds more that we need to deploy to a follow a saturation approach," Davidson explains.

The goal is not to replace human analysts but to create a more efficient workflow where AI assists in the initial processing, with humans providing oversight and quality control. This approach aims to reduce the marginal cost of production while maintaining the high standards of accuracy that Morningstar's clients expect.

As the financial industry continues to evolve, with the lines between public and private markets blurring and the demand for comprehensive data analysis growing, Morningstar's commitment to innovation and long-term thinking positions it well for the future. Davidson's insights reveal a company that is not just reacting to changes in the financial landscape but actively shaping its future.

In an industry where data is king, Morningstar's ability to navigate the complexities of unstructured information, coupled with its willingness to invest in long-term projects, sets it apart. As Davidson puts it, "We see a lot of firms deploying chatbots to drive a more frictionless experience for customer interaction. The most important thing to keep in mind in these contexts is to build experiences that maximize customer trust.”

As Morningstar continues to push the boundaries of what's possible in financial data analysis, it's clear that the company's journey is far from over. With challenges like the integration of private market data and the ongoing quest to master unstructured information, Morningstar's story is one of constant innovation and adaptation. In a world where data is increasingly driving investment decisions, Morningstar's role as a trusted guide through the complexities of financial information has never been more critical.