Venture Capital Firms are using Algorithms to Find Start-Ups

Maija Palmer indicated yesterday at The Financial Times Online that, “One of the biggest challenges for venture capital companies is finding interesting investment targets before anyone else. It is often a laborious, travel-intensive job. But machine learning and predictive analytics are starting to transform how an investor puts a portfolio together.

“‘My job used to be about getting on a plane once a week and going to a different European city to try to find people who were doing interesting things,’ says Roberto Bonanzinga, co-founder of InReach Ventures and previously a partner at Balderton Capital, a UK-based VC firm which invests primarily in early-stage European technology companies.”

The FT article explained that, “Mr Bonanzinga thought he could combine internet data and machine learning to do a better job of ferreting out prospects. It took two years and £5m in investment for InReach Ventures to create the software, which has so far trawled through 95,000 European start-ups, picking out 2,000 that Mr Bonanzinga might be interested in.

The software determines this based on the people they are hiring, the products they are developing and the traffic on their website, among other things. For example, InReach identified Oberlo, a Lithuanian start-up, as an investment target because it was advertising for engineers to solve a particular type of ecommerce problem. ‘We did a deal before any other VC firm in Europe even knew they existed,’ Mr Bonanzinga says.”

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