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Collecting as much data as possible: Is that a key differentiator for private market investments?
Private markets are considered by investors as the new El Dorado for delivering much-needed performance and diversification. However, private market asset classes raise new challenges as they require a different operational approach. This paper focuses on the data requirements for private market investing and questions the idea that getting ‘as much data as possible’ is truly best when considering the output in relation to the effort and cost spent on operational tasks.
The full article is available to subscribers to the journal.
Catherine Le Caranta joined SimCorp in 2016, and is an Offer Manager. In her role, Catherine works on the alternative investments solution roadmap and future developments. She develops offers through partnerships with FinTech providers, such as Domos FS and Alkymi, leveraging technology to increase operational efficiency. Prior to that, Catherine spent several years working for a software company specialising in private equity, which became a leader in this market. She was Head of Business Analysis, in charge of implementing private equity software for various general partners and limited partners across Europe and Africa, working on their data and STP, and creating proof of concepts and data audits for many financial institutions. Catherine graduated from the Institut Commercial de Nancy (ICN) and holds an MBA from Bloomsburg University.