InsurTech weekly - The dual nature of data

_{Is data an opportunity or a threat for insurers?}

I recently came across three articles which detail different perspectives around that same question. In the first one, insurers shared their fears around the need they might have to share their data. On the other hand, the second article details a request from insurers to access adjacent data sets. And the last one is a regulatory perspective. It wonders how incumbents plan to leverage data they could get from tech giants.

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_{Opportunities & challenges in (embedded) private credit}

The private credit market is expected to grow from $1.6 trillion in 2023 to $2.8 trillion by 2028. It’s created, sold, and managed by hedge funds, private equity, venture capital, or fintech firms. The industry is dominated by firms like Apollo, Blackstone, and KKR, lending to mid-sized companies with below-investment-grade ratings (typically for a higher price than a bank would lend). US regulators manage finance via the banks. Capital requirements came in after the financial crisis to make them safer, restricting how much they could profitably lend. Private credit now has a much bigger role in the wider economy.

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_{AI firms might exhaust internet’s data}

In 2006 fei-fei li, then at the University of Illinois, now at Stanford University, saw how mining the internet might help to transform ai research. Linguistic research had identified 80,000 “noun synonym sets”, or synsets: groups of synonyms that described the same sort of thing. The billions of images on the internet, Dr Li reckoned, must offer hundreds of examples of each synset. Assemble enough of them and you would have an ai training resource far beyond anything the field had ever seen. “A lot of people are paying attention to models,” she said. “Let’s pay attention to data.” The result was ImageNet.

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