How managers can rework data models to close the private/public visibility gap

This article first appeared in Ignites.

Asset managers are rapidly expanding into private markets, creating new opportunities for alpha generation — and new oversight challenges for monitoring portfolio-wide risk.

Managers cannot count on privates to regularly share information in a consistent format that would allow them to see underlying holdings and assess risk as they do for public companies. To maintain risk visibility and well-informed decision-making, asset managers can modernize their data infrastructure to organize and examine the data they have.

“When managers have an operating model that’s built around public [companies] — their systems, their people, their processes are built around the public — and then they introduce private assets, that then surfaces where the gaps are,” said Sam Showah, Head of Product Strategy, Asset Management, Broadridge.

Since public and private assets are structured differently and have different reporting requirements, firms are working with disparate data, struggling to compare exposure across blended portfolios and analyze risk across markets. The consequences of untimely, inaccurate or ungoverned data can reverberate beyond risk teams, impacting, for example, deal teams evaluating credit worthiness or compliance teams reporting to investors.

Unified data is essential to making high-quality decisions, Showah said. As such, firms are reassessing their data operating models to bring together fragmented systems, standardize information and make risk insights more readily available.

Build, buy or blend?

Showah said the first step for firms reevaluating their data operating models is to align goals and pinpoint their differentiator. This will allow firms to decide what to keep in-house and what might be better off outsourced to a partner with subject-matter expertise.

Firms that opt to build a new system will have more control but will lack the expertise an outside vendor can bring. For smaller asset managers in particular, this can be costly. For this reason, many firms are opting for a hybrid approach, Showah said.

“Managers are combining external data and platforms and internal models and controls,” he said. “They're using vendors as the foundation, but they're really retaining ownership of the logic and the decisions.”

For newer firms, this hybrid approach may entail collaborating with a partner to build an operating model that is cloud-native from the ground up. Asset managers unraveling legacy systems, on the other hand, may look for vendor platforms and data warehouse solutions to help organize, centralize and supplement siloed data. The end goal is a foundation of standardized investment data that is easily accessible in real-time to various teams and seamlessly integrated into tools and interfaces.

Leveraging AI

A manual and fragmented operating model not only introduces risk but stifles opportunities. AI tools can support data standardization but require a uniform data foundation as well.

“If you control your data, you’re able to leverage the AI tools that are available,” Showah said. AI can scrape, ingest and organize unstructured data, such as PDFs of financial statements or data in an Excel spreadsheet, to help monitor governance, support compliance or meet portfolio goals. 

While some managers are at the beginning of their data transformation journey and still recognizing the need to modernize, other managers began this transformation years ago and are already taking advantage of AI tools alongside cloud technology.

Cloud-based data models can unlock accessibility for firms, helping to digitize workflows, streamline operations and unify various systems. This can enable firms to layer in different analytics platforms and AI applications as well.

Looking ahead

As public and private markets evolve, flexibility is key, said Showah. Instead of trying to force private markets into a public framework, adapting and modernizing will allow firms to meet the moment and capture the nuances of both markets.

This transformation is not a one-time fix but a continuous journey. The push for privates, alongside AI innovation, has created a perfect storm that will continue to test data operating models while offering the potential for significant upside. Partnership can help ensure asset managers don’t overlook hidden risks or emerging opportunities.