Ensuring regulatory compliance can be expensive for financial services companies. In fact, the average cost nearly doubled from $16 million to $30.9 million between 2011 and 2017, according to one survey. And it’s tough for most to keep up — in 2017, over 900 agencies together issued over 200 regulatory updates each day, on average.

Companies like Tookitaki aim to ease the regulatory burden through AI-imbued software. The Singapore-based startup, which was cofounded by J.P. Morgan veteran Abhishek Chatterjee and Jeeta Bandopadhyay, taps machine learning and distributed systems to tackle compliance for anti-money laundering, reconciliation, and more.

Following seed rounds totaling $8.8 million, Tookitaki today announced that it has extended its series A to $19.2 million, thanks to a fresh injection of $11.7 million led by Viola Fintech, with participation from SIG Asia Investment and Nomura Holdings. This brings the company’s total raised to over $20 million, which CEO Chatterjee said will be used to enhance Tookitaki’s product offerings and “drive technological innovation.”

“Our vision has always been to revolutionize regulatory compliance and ensure sustainable compliance programs for every financial institution in the world,” said Chatterjee, who added that Tookitaki’s year-over-year revenue growth exceeded 300% over the last two years. “Backed by our strategic global investors, we are better placed to deliver on this vision by growing our presence significantly across the U.S. and the Asia-Pacific region.”

Tookitaki claims its anti-money laundering suite (AMLS), which uses machine learning to spot sophisticated schemes, reduces false alerts by 40-60% while spotting 5% more cases, on average. A semi-supervised transaction-monitoring algorithm fed network data provides secondary scoring, as does a screening mechanism that makes use of sophisticated matching techniques. Helpfully, the suite prioritizes alerts and integrates with existing upstream and downstream systems via built-in connectors and APIs, and it accounts for changing regulations through a process of continuous learning.

As for Tookitaki’s reconciliation product, it leverages separate modules for matching and substantiation, bolstered by algorithms that learn from historic patterns. The company claims it generates roughly 90% match rates for general matching cases and up to 70% reduction in exception investigation and resolution time, thanks to the automatic generation of rules for complex cases and the detection of exception cases that would be difficult to investigate manually.

“With almost 20 years’ experience that Viola has in the AML sector, we found Tookitaki’s approach to be … unique. Its pragmatic way of creating an overlay on top of legacy AML systems helps increase accuracy and significantly lower operating costs for financial institutions,” said Viola Fintech general partner Tomer Michaeli. “Moreover, its regulator-ready ‘glass box’ solution shows an innovative approach and a deep understanding of the challenges in the modern AML solutions market.”

Michaeli will join Tookitaki’s board of directors as part of the round, and former LinkedIn director Subhas Samanta will head up product development. With offices in the U.S., Singapore, and India, Tookitaki plans to expand in the U.S. and Europe and “aggressively” grow its R&D team in Singapore and Bangalore.

Sign up for Funding Daily: Get the latest news in your inbox every weekday.