The Role of Entity Linking and Matching Service in Streamlining Private Market Data

Introduction

In recent years, private markets have experienced a remarkable surge in popularity among investment managers. As firms seek to diversify their portfolios and capture higher returns, exposure to private equity, private debt, and other alternative investments has become increasingly common. According to recent reports, total global assets under management (AUM) in private markets reached approximately $11.87 trillion in 2023 and are projected to grow to $15 trillion by 2025 and more than $18 trillion by 2027. However, with this growth comes a host of challenges related to data management, particularly when it comes to mastering private market data.

Source: S&P Global, "Private Markets – A Growing, Alternative Asset Class” (July 2024)

The Challenge of Aggregating and Validating Private Market Data

Investment management firms aspire to treat private market data with the same rigor and standardization as public market data. However, the reality is that private market data often lacks a consistent schema or standardized identifiers, which creates significant confusion for firms trying to aggregate, master, and validate multiple sets of data from various vendors.

This lack of standardization leads to several challenges:

• Data Fragmentation: Firms often find themselves managing data across numerous systems and platforms, making it difficult to create a unified view of their investments.
• Quality Control: The absence of standard identifiers complicates the process of reconciling data from different sources, resulting in discrepancies and inconsistencies that can affect decision-making.
• Investor Demands for Transparency: As investors increasingly demand transparency in reporting, firms must ensure that their data is accurate, comprehensive, and easily accessible. This is particularly critical in private markets, where data is often opaque and less readily available than public market data.

How S&P Global Market Intelligence’s Entity Linking and Matching Service Can Help

To address these challenges, S&P Global Market Intelligence offers an innovative Entity Linking and Matching service designed to help investment managers make sense of private market data. By leveraging advanced technology and best-in-class software, S&P Global's service enables firms to effectively link and match entities across disparate datasets, providing a clearer picture of their investments.

1. Standardization of Data: S&P Global's Entity Linking and Matching service helps create a consistent framework for identifying and linking entities, making it easier for firms to reconcile data from multiple sources. This standardization is crucial for accurately assessing the performance and risk associated with private market investments.
2. Leveraging AI for Enhanced Matching: The service employs sophisticated AI algorithms that analyze various attributes of entities, such as names, addresses, and other identifying information, to identify connections and similarities. This AI-driven approach not only improves the accuracy of matches but also significantly reduces the time spent by data teams in manual reconciliation. By automating the linking process, firms can focus on higher-value tasks, such as analysis and strategy development.
3. Cross-Reference Data as a Service: S&P Global's offering includes cross-reference data that enhances the matching process by providing additional context and relationships between entities. This service allows investment managers to link private asset data with public market identifiers, thus treating private market data with the same rigor as public data. This capability is essential for comprehensive analysis and reporting.
4. Leveraging Continuous Monitoring via Web scraping: S&P Global’s continuous monitoring of company webpages, market news, press releases, social media mentions, and other external sources help to enrich existing datasets with relevant and accurate information. These dynamic updates help our entity linking and matching service stay current with the most up to date data. Organizations can define specific rules and parameters which allow more focused data collection ensuring that we meet specific business needs.
5. Enhanced Data Quality: By utilizing advanced algorithms and machine learning techniques, S&P Global's service improves data quality by identifying duplicates, resolving discrepancies, and establishing relationships between entities. This not only reduces the burden on data teams but also enhances the overall reliability of the data being used for decision-making.
6. Streamlined Reporting: With accurate and standardized data, investment managers can more easily generate reports that meet investor demands for transparency. This capability is essential for maintaining trust and credibility with stakeholders in a landscape where scrutiny of private market investments is increasing.

Case Study: A Leading Global Investment Manager

To illustrate the effectiveness of S&P Global's Entity Linking and Matching service, consider the experience of a leading global investment manager facing significant challenges in managing private market data. This firm struggled with data fragmentation and the lack of standardized identifiers, complicating their ability to aggregate and analyze investments across various private market assets.

The Problem: The investment manager needed a solution to reconcile multiple sets of private market data from different vendors while ensuring high data quality and transparency in reporting. They sought to augment their newer data management staff and effectively combine over 50 disparate datasets to create a cohesive view of their investments.

The Solution: By implementing S&P Global's Entity Linking and Matching service, the firm was able to standardize their data processes. The AI-driven algorithms facilitated the linking and matching of entities, allowing them to create a unified view of their private market investments. The cross-reference data provided additional context, enabling the firm to integrate private asset data with public market identifiers seamlessly.

The Benefits: As a result of this implementation, the investment manager experienced enhanced data accuracy and quality, which significantly reduced the time spent reconciling data. They were able to generate more transparent and reliable reports for their portfolio managers in the decision making process and for investors, thereby strengthening their credibility and trust. The streamlined processes also allowed their data teams to focus on higher-value analytical tasks, ultimately driving better investment decisions.

Conclusion

As private markets continue to grow in prominence within investment portfolios, the need for robust data management solutions becomes increasingly critical. S&P Global's Entity Linking and Matching service provides investment managers with the tools necessary to navigate the complexities of private market data, ensuring that they can treat this data with the same level of rigor as public market data.