Mimiro, a machine learning platform to detect financial crime, has secured $30m in financing led by Index Ventures along with existing investor Balderton Capital.
As part of the Series B round, Index Ventures partner Jan Hammer has joined the Mimiro board. The financing will help the company to strengthen its machine-learning platform for analysing the risk of financial crime.
By verifying parties and transaction, Mimiro can help change the way how companies assess who they are doing business with and build confidence of companies in their own operations, attacking financial crime and reducing laborious manual checks. Mimiro has 350 clients across 45 countries including the US, Europe and Asia and major global banks.
As per the company, with the global economy becoming increasingly complex and interconnected, it is now vital and also very difficult, in getting a clear picture of an entity on the other side of the table during a transaction or business relationship.
Geopolitical instability, lengthening supply chains, increased migration and growing emerging markets are all putting pressure on companies to improve their standards for verifying the risk and legitimacy of counterparties and payments.
While in the short term, the company’s focus is on financial crime and ‘know your customer’ rules, it is also building a comprehensive global repository that provides an instant, accurate risk profile for commercial entities and individuals across the world.
Mimiro CEO and founder Charles Delingpole said: “We exist because globalisation is intensifying the business problems of trust. To offset concerns, many businesses can be hyper-cautious and conservative, losing out on commercial opportunities – in some cases abandoning entire countries or industries.”
In the post-9/11 environment, companies have spent hundreds of billions of dollars each year to under who they’re doing business with. And, the businesses are claimed to be reliant on ineffective solutions that generate large amounts of manual work and silos of data with patchy coverage, that can’t easily be combined. Such a system generates several false positives which divert attention from following genuine red flags.
To counter these challenges, Mimiro uses a deep learning, machine intelligence. Its algorithms can take in and scour millions of structured and unstructured data sources daily, including registers of high-level national and international sanctions, individuals who should be treated with caution, and adverse media coverage.
This result has result in the company building a holistic snapshot of its risk in real-time and can spot patterns across users and transactions, which could otherwise elude from a human assessor.
The company also lets clients tailor the product to focus on parameters that are particularly relevant to them. On average, Mimiro claims to reduce false positives by up to 70%.