Autonomous Research have analysed investments in Initial Coin Offerings (ICOs) since their inception. The left-hand side graph depicts funding by category for ICOs from 2014 to 2017. Initial funding in 2014 began at US$26 million, breaking down to $19 million being spent on core tech and $7.5 million going towards cloud innovations. 2015 saw a dip in funding, dropping to a total of $14 million but it was spread out across a wider range of applications, with $5 million being dedicated to financial markets and $2 million being invested in cryptocurrencies. There onwards the ICO market has grown immensely, largely due to The DAO raising $150 million in investments, causing total ICO funding to rise to $222 million in 2016. The first half of 2017 has shown the greatest amount of funding, rising to over $1.2 billion, with over $500 million going towards cryptocurrencies and financial market services in second raising nearly $200 million.
The right-hand side depicts the firms with the most funds raised in the 2017 period so far. Topping the list is Tezos with $208 million followed shortly by EOS at $200 million, both of whom deliver core tech services. BANCOR received the third highest amount of investments at $150 million, dominating the financial market services, with only two other financial market firms with large investments: (1) Gnosis, raising $12 million, and (2) OpenANX, raising $19 million. Media and social services grew hugely in 2017, with Status raising $95 million, Basic Attention Tokens raising $35 million and the DAO.Casino raising $12 million. Other notable service funding include cloud and payments, with TenX topping payment services at $80 million and SONM leading the way for cloud at $42 million.
* Updated numbers through December 10th, 2017 are below:
** A note on methodology. We primarily look at ICOs that have raised or are raising over $1mm USD, which filters for more reputable projects but may miss the longer tail of seed-stage token investing. To collect the data, we leverage and cross-check multiple primary and secondary data sources, and then categorize projects based on use-case into industries. The starting and ending dates of ICOs are also a moving target, therefore we use the earliest of the dates where possible. Our goal with this data is highlight the direction of travel, which appears to be from the protocol level to the application level.