Tookitaki Holding takes home AI Award for banking at SBR's inaugural Technology Excellence Awards
The company bagged the award with its end-to-end transaction monitoring and names screening solution.
Tookitaki's Anti-Money Laundering Suite (AMLS) is a reputable, end-to-end transaction monitoring and names screening solution powered by machine learning, which helps financial institutions transform AML compliance by providing cost reduction, improved productivity of compliance personnel, and enhanced regulatory compliance.
For this remarkable innovation, the company bagged the AI Award for the banking category at Singapore Business Review’s recently concluded Technology Excellence Awards.
A product of Tookitaki’s matchless R&D effort, AMLS is created with the vision to enable sustainable compliance programmes at financial institutions. Existing rules-based systems focus on static transactional behaviour which fails to detect sophisticated threats and generates a whopping number of false alerts. This results in high risks for banks in terms of huge alert backlogs and high investigator churn. Banks could also miss true suspicious cases, which leads to reputational and financial perils.
Tookitaki AMLS is a paradigm shift from such legacy systems as it was created with a design philosophy of providing maximum detection coverage and low false alerts whilst being fully scalable and transparent. The proven platform reduces false positive alerts by 40-60% and increases the detection of new suspicious cases by 5%.
AMLS is based on three new concepts that are intended to revolutionise the AML compliance industry. The product has an unmatched capability to detect unknown “true” cases to mitigate risk and make the AML programme more effective.
It also features a smart typology repository to update detection scenarios automatically and intelligently groups alerts for speedy and efficient alert disposition.
Other distinctive features of AMLS include:
- Self-learning capabilities allowing models to continuously and automatically learn with incremental data
- Explaining machine learning models, bringing a glass box approach to understand model decisions
- Seamless integration to existing systems for faster time-to-market
The solution uses Tookitaki’s proprietary semi-supervised algorithms which combine the best of supervised and unsupervised machine learning techniques to handle cases that are typically skipped by rules and unsupervised specific learnings. Its pre-built champion-challenger framework helps the solution learn new patterns automatically and continuously, keeping the engine efficacy intact and maintaining high detection coverage with changing times.
In a pilot project, AMLS delivered astounding results with a 60% and 50% reduction in false positives for individual names and corporate names, respectively, for names screening alerts. At the same time, transaction monitoring saw a 40% decrease in false positives and a 5% increase in true positives.
Tookitaki’s clients are immensely satisfied with the operational efficiency improvements in AML programmes they have reaped by implementing AMLS. Among them include United Overseas Bank (UOB) who partnered with Tookitaki to enhance its money-laundering surveillance.
“The area of AML requires constant vigilance and continual enhancement to ensure that we stay on top of preventive, detective and enforcement measures,” said Victor Ngo, UOB’s head of group compliance.
“The use of RegTech (regulatory technology) such as Tookitaki’s AMLS enables us to augment our ability to identify actionable alerts and to minimise false positives. These sharpen the accuracy and effectiveness of our AML risk management,” he added.
Tookitaki means “hide-and-seek” in Bengali, an Indo-Aryan language primarily spoken by the Bengalis in South Asia. Through its solutions, namely AMLS and Reconciliation Suite (RS), the AI company enables machines to seek hidden patterns in data. Headquartered in Singapore with offices in the US and India, Tookitaki derives strength to face mounting competition from its core team with cumulative 150 years’ experience in finance, AI, big data analytics and financial crime.
Recognising Singapore’s leading companies in technology innovation, the Technology Excellence Awards lauds outstanding companies that have pioneered groundbreaking IT products and solutions and implemented avant-garde technology initiatives that have made an impact on their business.
The Technology Excellence Awards, presented by Singapore Business Review, was held on 30 May 2019 at the Conrad Centennial Singapore.
This year’s nominations were judged by a panel consisting of Cheang Wai Keat, Head of Advisory, Ernst & Young LLP; Darwin Thio, Director, Cybersecurity & Technology Services, Nexia TS; Daryl Pereira, Head of Cybersecurity, KPMG; Evelyn Lim, Executive Director, Tax Advisory, BDO LLP; and Jonathan Kok, Co-Head of Technology, Media & Communications Industry Group, RHTLaw Taylor Wessing LLP.
Check out the event photos during the awards night here.
If you would like to join the 2020 awards and be acclaimed for your company’s exceptional technology innovations, please email Julie Anne Nuñez at email@example.com