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Addressing Complexities of Data Management in the Private Credit Ecosystem

Following the pandemic and market volatility that ensued in its earlier days, private debt assets had reached a total AUM reaching $887 billion in mid 2020 [1]. While the market uncertainty remains in 2023 [2], the deals market has increased substantially over the years. To address this immense growth, however, deal/fund structures – along with operations and technology – have become far more complex, especially for those creative deals that have been designed to align with higher risk tolerance.

As deal structures become more innovative and deal volume continues to rise, operating models will need to evolve to mitigate the reference data management issues that can form as a byproduct of the complexities in the private credit data management ecosystem, including:

  • Lack of a Standardized Data Model: Each asset management firm dealing in private credit data needs to maintain various forms of information on each individual asset class. But, there are variations in data attributes being maintained by different firms and it being ingested in different formats, volumes and quality, leads to a lack of standardization and low data integrity in reference data management.
  • Data Sourcing & Normalization: Sourcing data from external parties in private credit markets is a massive hurdle faced by asset managers due to a lack of data sharing between institutions and corresponding privacy concerns. Also, with the use of multiple non-standard data sources, it becomes increasingly difficult for firms to organize and normalize their data for storage and consumption.
  • Data Quality: Due to non-standard data sourcing and multiple manual touchpoints on ingested data, there is a strong need for firms to run data quality checks to prevent issues and inaccuracy within their deal pipeline. With a potential to hinder day-to-day operations and deal valuation, firms must have workflow management, exception management and data validation rules in place.
  • Data Volume: Unlike liquid assets where data is more accessible, deal information in the private credit data management space is only available from specific sources at certain stages of the deal pipeline. With this increased risk of the unknown, the volume of data collected by deal teams is greater and it must be processed promptly and distributed for accurate reporting, analytics and decision making.
  • ESG Data: While ESG is neither new nor limited to the private credit data space, it is becoming increasingly accepted for investment decisions, defining investment strategy and compliance. The COVID-19 pandemic has spurred more interest in ESG investing. With this, a growing requirement to comply with and use ESG data has resulted in a formidable task for managers due to a lack of standardization when it comes to its collection and distribution.

Data Management Solution

IVP Security & Reference Master which is part of IVP’s award-winning suite, possesses a configurable data model that allows asset managers to maintain and customize assets based on their requirements while eliminating reliance on the external IT team. IVP Security & Reference Master also has native capabilities to integrate with multiple data sources, including ESG data, to produce a blended golden copy of data, store data at both the issuer and at the country level, and distribute the copy of data to multiple applications for their consumption. This helps to maintain consistency across applications and allows asset managers to scale with ease, thus solving a multitude of issues related to a lack of standardization and redundant data retrievals.

To learn more about IVP can help in your journey of achieving alpha, contact us.

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Security & Reference Master

A reference data management solution with a highly configurable core and intuitive data modeling that combine to create an accurate reference master more efficiently.

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