“Data really powers everything that we do,” is a quote that has been attributed to Jeff Weiner, former chief executive officer and current executive chairman of LinkedIn. Today, the same sentiment coming from a private debt fund manager would be a surprise, but there’s little doubt the market is increasingly embracing technology as time goes by.
One driver is the growing thirst for data around ESG, with our affiliate title, PERE, reporting this week on German asset manager Patrizia’s finding that client demand for such information has increased 18 percent in response to new European Union targets.
But ESG is only part of the data story. As market conditions become more challenging – for reasons our readers will by now be very familiar with – the minds of fund managers have become focused on any possibility of competitive advantage, including improving operational efficiency. And that’s where data comes in.
This week, Private Debt Investor caught up with Altin Kadareja, chief executive officer of Cardo AI, a Milan-based firm launched in 2018 to provide private debt-related data solutions to institutional investors, banks and credit servicers. The data is used in all sorts of ways – from analysing non-performing loan portfolios, to helping banks with capital efficiency, to assisting GPs and investment committees with their decision making.
Referring specifically to fund managers, Kadareja pondered some of the opportunities and challenges. The smaller managers with often younger management teams tend to be more comfortable with technology and inclined to be data-driven in what they do – they have, in other words, the right kind of culture to be open-minded about what data firms have to offer. But, operating on tight budgets, they may not have deep enough pockets to take advantage.
PDI also recently caught up with Legalist, a US-based firm investing in several niche private debt strategies. Co-founder Eva Shang was just 20 years old when she dropped out of Harvard University to launch the firm. It was arguably a classic example of the type of manager Kadareja is referring to, with an investment approach that Shang describes as ‘top down’ – ie, deciding what the firm wants to invest in and then creating the technology that allows the investment opportunities to be identified. In its case, the firm – cash-strapped in its early years – built its own technology.
When it comes to larger managers, things may be the other way round – as they scale up, says Kadareja, they have the money to spend and have probably become more aware of the competitive advantages that data could potentially give them. But they may remain marooned in a world of old school practices and legacy systems that are difficult to unravel.
Whether large or small, managers are now operating in a changed environment where recession may be around the corner and where the demand from investors for high quality and reliable information seems bound to increase. As one market source told us: “Recession will make people question the things they trusted before.”
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