Why Data Quality Management Is Business-Critical in Private Markets
Summary
Private markets firms face costly risks when data quality breaks down across accuracy, completeness, uniqueness, validity, consistency, and timeliness. Errors distort NAVs, misstate risk, and erode trust with LPs and regulators. Strong data management and automation not only mitigate reputational and financial harm but also unlock operational efficiencies.
Ankit Jain
Ankit has 14 years of experience building technology-driven products for the investment management industry, focusing on turning complex operational challenges into scalable, user-centric solutions. His work intersects across product management and solutions architecture, where he combines strategic thinking with hands-on execution. Ankit has led the end-to-end development of platforms supporting the full investment lifecycle, from trade processing to reporting and analytics. He partners with stakeholders across business and technology teams to define product vision, prioritize roadmaps, and deliver robust and adaptable solutions.
Bibliography:
[i] The Accounting Review (2018) 93 (1): 317–333. The Credibility of Financial Reporting: A Reputation-Based Approach, https://publications.aaahq.org/accounting-review/article-abstract/93/1/317/3940/The-Credibility-of-Financial-Reporting-A?redirectedFrom=fulltext
[ii] Investment Advisers Association. https://www.investmentadviser.org/events/access-to-private-market-investments-for-retail-investors/
[iii] EY, The lender’s edge: data strategies for private credit, December 19, 2024. https://www.ey.com/en_us/insights/wealth-asset-management/data-strategy-in-private-credit
