PwC’s latest Family Office Deals Study shows that the size of family offices’ cheques to start-up founders declined by almost 45% in 2022. The number of deals also fell by more than 22%, the first such decline in 11 years. According to our proprietary database of 6,530 family offices worldwide, they invested US$161.7bn in start-ups in 2022, down from the previous year’s high of US$295.1bn, while the number of investments also fell from 6,092 in 2021 to 4,736 in 2022.
Despite the decrease, family offices have become a vital investor group for start-ups. In 2022, they accounted for almost one-third of the total capital invested in start-ups worldwide and for more than 10% of all investments. Until 2018, family offices invested mainly in early-stage start-ups. But from 2018, they shifted their focus to primarily late-stage start-ups. This suggests they have become more risk-averse, preferring more reliable and established business models.
The key findings from the study include:
- Club deals, where family offices invest together with other investors, made up 92% of investments in 2021. However, this figure dropped to 89% in 2022.
- The gap between the number of medium-sized deals and mega-deals has been narrowing. But in 2022, the differential widened again, signalling higher risk aversion as the focus shifted away from mega-deals and back towards smaller-size investments.
- Family offices’ top target markets for investments by deal count are the US, India, the UK, Germany, and France. Meanwhile, investors overall target the US, China, the UK, India, and Canada.
- The Americas and the Caribbean are the most attractive target markets for family offices’ start-up investments, whereas the number of deals in the Asia Pacific region fell slightly faster than in other regions.
- Software as a Service (SaaS) is the most important target industry for family offices and start-up investors. Family offices rank financial technology (FinTech) as the second most important target industry, while investors as a whole rank artificial intelligence and machine learning in second place.
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