Icelandic anti-money laundering startup Lucinity receives USD6.1 million in funding
Karma Ventures and byFounders have led a USD6.1 million funding round in Icelandic anti-money laundering startup Lucinity.
Existing investors Nordic based Crowberry Capital and US based early stage investor Preceptor Capital also participated in the founding round.
The software startup Lucinity is an Anti-Money-Laundering app that “uses human AI to ‘make money good’ by augmenting financial crime fighters in financial firms with AI technology,” according to the company.
Margus Uudam, founding partner at Karma Ventures, led the deal. “The huge problem Lucinity tackles, the team’s excellent background in financial services and AML solutions industry and the revolutionary approach that the team brings to the market are all components that make us firm believers that there is a great success story in the making,” he commented on the investment.
Lucinity founder and CEO Gudmundur Kristjansson reportedly had minimal face time with the investors while finalising the deal.
“Partners like byFounders and Karma Ventures are invaluable,” commented Kristjansson, who was a senior Citigroup compliance tech expert before going on to founding Lucinity.
“Their willingness to break their comfort zone to invest in such extraordinary circumstances is a testament to their belief in what we are building. We can not wait to work closely with them moving forward,” he said.
In June 2019 Lucinity raised a seed funding round from Crowberry Capital. The startup was launched in November 2018, with the goal of solving the current gap in the Anti-Money Laundering (AML) transaction monitoring market.
The initial funding was used to expand the company’s data science, engineering and go-to-market efforts of its Lucinity ClearLens platform.
Lucinity adopted a new approach called Augmented Intelligence, which combines the power of AI and human intelligence through feedback loops, according to the founder. Using this approach, the aim of ClearLens is to enable clients to improve detection of suspicious behaviour patterns and increase review efficiency.