Mimiro raises $30mn for ML platform analyzing counterparty risk profile

London-based Mimiro has raised $30 million from investors to accelerate the global expansion of its machine learning platform for analyzing the risk of financial crime by verifying parties and transactions. Index Ventures, the London and San Francisco-based venture capital firm, led the Series B round, and were joined in the round by existing investor Balderton Capital.

As the global economy becomes increasingly complex and interconnected, it’s now more vital – but also more difficult – than ever to get a clear picture of the entity on the other side of the table during a transaction or business relationship. Geopolitical instability, lengthening supply chains, increased migration and the growth of emerging markets all put pressure on companies to improve their standards for verifying the risk and legitimacy of counterparties and payments.

While financial crime and KYC rules are Mimiro’s near-term focus, the company is building a global repository that provides a risk profile for every commercial entity and individual in the world. Mimiro has a growing list of 350 clients in 45 countries across the US, Europe and Asia, including Santander and other major global banks.

Mimiro’s CEO and founder Charles Delingpole said in statement that many businesses can be hyper-cautious and conservative to offset concerns about counterparty risk, losing out on commercial opportunities and in some cases abandoning entire countries or industries.

In the post-9/11 environment, companies have been spending hundreds of billions of dollars each year to understand who they’re doing business with. But businesses are typically reliant on ineffective solutions that generate large amounts of manual work, plus silos of data that have patchy coverage and can’t easily be combined.

The system is beset with false positives which divert attention from following up on genuine red flags. Multiple scandals, where banks have been fined billions of dollars for facilitating illegal activity, point to the ongoing reputational and commercial dangers of getting things wrong.1

Mimiro solves the problem by using deep learning and machine intelligence. The company’s self-improving algorithms absorb 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.

As a result, Mimiro builds a “holistic” snapshot of an entity’s risk in real-time, and spots nuanced patterns across users and transactions that would elude a human assessor. The company also lets clients tailor the product to focus on parameters that are particularly relevant to them. On average, Mimiro reduces the rate of false positives by 70%.

Jan Hammer, Index Ventures partner, said in a statement: “Historically, financial crime tends to run ahead of the means of catching it; remedies have been reactive. Today, the problems are getting bigger, the risks and the penalties are more severe, and the old system can’t cope. Mimiro has a completely new approach, giving companies the power to get a fast, sophisticated understanding of where their risks lie.”

Read the full release

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