IDC European Woman in Venture Capital

EUROPEAN WOMEN IN VC IDC #EUR148997722 © IDC 2022 95 LITHUANIA *Lithuania only lists 2 VCs with AuM >€25M. Work — 4 stars Money — 1 star Knowledge — 2 stars Time — 1.5 stars Power — 2 stars The current position of women across all areas is low, except for work, where opportunities are relatively strong. Financial rewards do not match up and conditions related to time and power are also rather poor for women in Lithuania. GP Balance — Lithuania Lithuania Firepower Male 83% Female 17% 86% 14% Diversity from a Funding Perspective • Though the starting position of women in Lithuania is low, there are signs of change. The 2020 parliamentary elections marked a turning point in Lithuania’s political parity. Today, 27% of seats are held by women, and the government’s cabinet is now the most gender-balanced as well as the youngest in Central and Eastern Europe.  • Lithuania leads the Baltics with the highest percentage of general female partners (16%). One  of the largest funds (Livonia Partners) was set up by a female GP.  At the same time, it needs to be noted that there are not many VCs with funds of >€25M in Lithuania. There are several initiatives to spur growth in  Lithuania for women in business, tech and finance.  • The LTVCA (Lithuanian Venture Capital Association) is a strong advocate of diversity that publishes its own research on women in VC in the Baltics as well. Startup Perspective • There is a growing interest in tech from women, as stated by Women Go Tech. This is a Lithuanian mentorship scheme focusing on females retraining towards tech, and it has seen the number of applications to its scheme grown five times, showing a growing interest in tech.  • Unicorn Vinted completed a funding round in the second quarter of 2021. The  €250M investment influences investments into (co)female led startups quite significantly.  • Other (co) female led startups include: Interactio, Brolis Sensors, DappRadar #of startups from >=2010 that that received funding Source: Dealroom Startup Data Male Female Mix 94 % 77 % 2017 2018 2019 2020 2021 71 % 0 % 29 % 91 % 79 % 8 % 2 % 6 % 10 % 11 % 15 % 7 % 0 %