Technology Awards 2019 – Best AML/CTF Solution

2019 Winners

Best AML/CTF Solution

Tookitaki

Who are you?
Tookitaki is a Singapore-headquartered global regtech startup that is innovating regulatory compliance by moving beyond rules-based applications and introducing software solutions to maximise efficiency and reduce risks in compliance processes. In regulatory compliance, the company’s award-winning offerings include an Anti-Money Laundering Suite (AMLS) and a Reconciliation Suite (RS).

Tookitaki has successfully teamed up with Broadridge Financial Solutions, Inc. (NYSE:BR) in utilising their award-winning AI and ML technology to deliver a next-generation platform addressing industry-wide reconciliation, matching and exception processing inefficiencies.

Incorporated in November 2014, the company is led by a core team with a cumulative 150 years of experience in finance, AI, Big Data Analytics and financial crime. In 2019, Tookitaki won UBS Future of Fintech Challenge and the SG:D Techblazer Awards, along with the Technology Pioneer recognition by the World Economic Forum.

Tookitaki has raised a total of US$19.2 million in Series A funding, co-led by Viola Fintech and SIG, followed by Nomura Holdings through its venture capital arm Nomura Incubation Investment Limited Partnership, along with existing investors Illuminate Financial, Jungle Ventures and SEEDs Capital, an investment arm of the Singapore government.

Describe your solution (I.e. that which is applicable to your award)
Tookitaki’s Anti-Money Laundering Suite (AMLS) uses powerful machine learning and the latest distributed computing framework to deliver high-performance and scalable transaction monitoring and names screening solutions. The solution has two modules:

  • Transaction Monitoring Module: Processes billions of data points across source systems to perform improved customer segmentation and network mapping to detect net new suspicious cases and triage alerts in high, medium and low-risk buckets.
  • Names & Sanctions Screening Module: Screens new and existing individual and corporate customers against sanctions lists, PEPs, adverse media, etc. to identify suspicious cases.

Across banks in multiple geographies, AMLS has been able to reduce 40% of false alerts for transaction monitoring and 50% of false alerts for names screening. In addition, it has detected new suspicious cases and helped banks increase their SAR filing rate by up to 5%, thanks to our comprehensive, proprietary AML Typology Repository and novel machine learning approach.

What makes it stand out/apart from other similar solutions in the marketplace?
Tookitaki’s Anti-Money Laundering Suite (AMLS) is one of the few enterprise AML software offerings to be deployed in production with proof points in better alerts triaging and new suspicious case detection.

Our unique features are:

Multi-dimensional models: Our machine learning models learn from multiple customer interactions and apply ensemble learning techniques to predict customer behaviour with accuracy. This unique feature provides banks incremental actionable insights into anomalous behaviour and helps detect criminal activities in a faster and auditable manner.

Explainable outcomes: Our patent-pending explainability framework includes model transparency and interpretability at its core. Our transparency module explains the details of the underlying core model while our interpretability module explains the rationale for every prediction made through the AMLS engine.

Explain how it adds value to the business of PBS/WMs
Tookitaki’s solution enables continuous and automatic learning with incremental data, capitalising on a champion-challenger framework and providing easy integration options with a bank’s complex underlying upstream and downstream systems, which make the operationalisation of AI much faster and allows PBs and WMs to spend less of their time on routine tasks and being able to better manage case detection due to lower rates of false alerts.

As our solution comes with an explainability framework that comes along with an interpretability module, which explains the rationale for every prediction made through the AMLS engine. The results produced by the solution are wrapped by relevant customer content, so that the explanations can be used in a business-friendly fashion for PBs and WMs to make better informed decisions in creating a culture of compliance throughout the industry and improve the operational efficiency of the compliance team.

Contact details
Tookitaki: www.tookitaki.ai
KeKommunikation for Tookitaki: tookitaki@kekommunikation.com