Spread financial intelligence

Hummingbird, a US RegTech startup and operator of an anti-money laundering (AML) platform, announced that it has raised $3 million in a funding round led by San Francisco-based Seed Capital Venture firm Homebrew. Hummingbird’s mission is to fight financial crime by helping financial institutions investigate suspicious behavior and report on it to law enforcement.

Estimated $2 trillion is laundered every year and less than 1% is caught. According to the United Nations that illegal activities fuel 2–5 percent of the global GDP in money laundering every year. Profits from political corruption, bribery, organized crime, human trafficking, and illegal trading all end up being laundered through the financial system. Financial institutions invest billions in AML programs, but tech-savvy criminals are tough to catch.

Hummingbird brings agility, intelligence, and breadth to the AML practice for financial institutions. Many of these institutions struggle to keep up with increasing complexity in AML. Hummingbird claims to use machine learning in combination with deep investigative capabilities, enabling investigators to focus on fighting financial crime.

US institutions are spending an estimated $25 billion per year on AML, but they’re battling dated technology stacks and manually coordinating detailed workflows,” said Joe Robinson, co-CEO and co-founder of Hummingbird. “Hummingbird’s technology and algorithms can assist AML experts with complex investigations and help these institutions stay on top of new money laundering methods.”

FinTelegram much appreciates the activities of companies such as Hummingbird. Money laundering actually is a huge challenge for the global crypto-scene for example and one of the main obstacles for development of a sustainable crypto-economy (read our article on crypto and money laundering here). Hence, we are happy to see that technology investors provide funds to startups fighting money laundering and cybercrime. Our congratulations to the Hummingbird team. Well done!

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