Our UOB Success Tale: Setting a New Benchmark for AI-based AML Compliance

Tookitaki achieved a rare and historic milestone as our Anti-Money Laundering Suite (AMLS) solution went live within the premises of United Overseas Bank (UOB), one of the top 3 banks in Singapore. We became the first in the APAC region to deploy a complete AI-powered anti-money laundering (AML) solution in production concurrently to two AML risk dimensions, namely transaction monitoring (TM) and name screening (NS). By deploying Tookitaki’s AI-enabled AMLS, UOB could effectively create workflows for prioritizing TM and NS alerts based on their risk levels to help the compliance team focus on those alerts that matter the most. Vindicating the efficacy, robustness and sustainability of the machine learning models involved, AMLS underwent multiple rounds of rigorous testing, validation and evaluation, involving third-party consultants, before going live in full scale.

Compliance Challenges That Prompted us to be Innovators

Combating money laundering has become an enormous task for financial institutions, and it comes with substantial costs and risks, including but not limited to regulatory, reputational and financial crime risks. During the first half of 2020, APAC regulators imposed almost USD 4 billion in fines for AML violations, according to a report. Ineffective risk-based frameworks, deficient monitoring systems, inadequate review of suspicious activity, and unoptimized resources allocation are some of the widely cited AML compliance problems for financial institutions.

A leading bank in Southeast Asia with a global network of more than 500 offices in 19 countries and territories in Asia Pacific, Europe and North America, UOB wanted to have a holistic view of money laundering risks and the threat-scape across various banking segments such as corporate, retail and private. Existing static and granular rules-based approaches, which are oblivious of the holistic trend with a narrow and uni-dimensional focus, were not capable of doing the same. For UOB, which is handling about 30 million transactions and more than 5,700 TM alerts per month, existing rules-based systems produced a significant volume of false positives. The situation was not different in the case of the NS process, where the bank screened about 60,000 account names on a monthly basis. These false leads are a drain on productivity as they take significant time and resources to be disposed of. In the AML compliance space, banks are wasting more USD 3.5 billion per year chasing false leads because of outdated AML systems that rely on stale rules and scenarios and generate millions of false positives, according to research.

Undoubtedly, using limited resources to close off non-material and unimportant alerts is manual and onerous, resulting in huge backlogs for both processes and missed/delayed Suspicious Activity Report (SAR) filings. Furthermore, the ballooning costs of AML compliance coupled with the high volume of backlog alerts swamp compliance teams and potentially distract them from ‘true’ high-risk events and customer circumstances. Alert investigation was a time-consuming and labour-intensive affair as the compliance team spent significant time in gathering data and analysing it to differentiate illegitimate activities from legitimate ones. Disparate data sources and highly complex business processes added to the difficulty of the investigation team in analysing the links between parties and transactions.

These issues prompted the bank to leverage innovation and next-generation technology to enhance existing AML compliance processes, surveillance systems, and alert handling practices. In specific, UOB wanted a next-gen solution that can do the following:

  • Identification of non-material false positives for both TM and NS using data from disparate sources.
  • Accurate grouping of high-risk alerts for increased focus by compliance personnel.
  • Advanced analytics combining data from existing financial crime systems and numerous disparate data sources.
  • Faster investigation and resolution of all alerts by connecting the dots within the data, and constructing a more holistic global view of accounts, counterparties and transactions, effectively reducing the high volume of alert backlogs.

AMLS: An Innovation Proven for Robustness, Agility and Sustainability

As part of its ‘AML/CFT Technology Roadmap’ to harness next-generation AI and machine learning-driven technologies to combat money laundering, UOB teamed up with Tookitaki. The bank’s aspiration was to shift beyond rules-based systems to achieve higher performance with machine learning models and other disciplines of AI. Tookitaki’s ability to seamlessly connect with existing AML systems at UOB for data ingestion hastened the bank’s decision to onboard us.

As such, Tookitaki developed AMLS, an end-to-end AML compliance solution that combines supervised and unsupervised machine learning techniques to detect suspicious activities and identify high-risk clients quicker and more accurately. We use a combination of machine learning algorithms to build highly accurate and stable models and techniques such as dynamic clustering which does behavioural segmentation based on composite features. AMLS TM module can prioritise known alerts based on their risk scores and detect new, unknown suspicious patterns. The NS module has three core components – enhanced name matching through a wider range of complex name permutations, reduction of undetermined hits through inference features and accurate alert detection through primary and secondary information. These capabilities help accurately distinguish between false hits and true hits. The major innovative features of the solution are:

  • Smart Alert Triage: The solution offers a smart way to triage TM and NS alerts by segregating them into three risk buckets – L1, L2 and L3 – where L3 is the highest-risk bucket. The highly accurate alert classification helps UOB’s compliance team to allocate time and experience judiciously and effectively address alert backlogs. Compliance analysts can now focus on those high-risk cases (L3 and L2) that require more time to investigate and close. Meanwhile, they can close low-risk alerts (L1) with minimal investigation. AMLS generates a probability score for all alerts, along with an explanation to guide the investigator make the right decision faster.
  • Champion–Challenger Approach: A core component of our data science platform, this approach enables machine learning models to continuously learn from data shifts and data additions. It helps ensure that the model remains effective and unbiased amid incremental changes in data.
  • Explainable AI (XAI) Framework: Our patent-pending XAI framework provides transparent machine learning models, and explainable and documentable predictions to ensure thorough understanding and to conduct quality investigations along with aligning users with the compliance model transparency requirements of regulators.
  • Scalability: AMLS uses a combination of distributed data-parallel architecture and machine learning to ensure scalability across the bank’s multiple business lines and complex layers of existing technologies and systems.

Unique Implementation Approach Resulting in Sustained Model Performance

UOB had tested the effectiveness of AMLS in terms of alert prioritization in a six-month pilot started in early 2018. After receiving successful results, which were validated by Deloitte, the bank tested the solution again with a unique data set and performed another round of model validation. The subsequent machine learning models outperformed the results we achieved during the pilot. The successful results gave UOB the confidence to move the machine learning models to production and build a tailored solution. Based on the bank’s feedback, Tookitaki introduced various enhancements and additional features into its solution.

While deploying AMLS on UOB premises, we took a unique approach of augmenting existing systems with AI-based smart alert management where our solution would sit on top of existing TM and NS solutions and accurately group alerts for faster closure. In the model training phase, our solution’s powerful integration layer extracted data from existing product systems and primary TM and NS systems, transformed them and then loaded them to our platform. This used to be a process that requires considerable effort and time, however, Tookitaki solution’s pre-packed connectors made it easier for us to adapt to the bank’s various enterprise architectures and up-stream systems.

For TM execution, we integrated historical data for three years (customer, accounts, transactions, primary system alerts, etc.) in the learning phase. In NS, which is used to identify individuals and entities that are involved in AML activities, our advanced name matching algorithms compared individual names and business names with the bank’s internal and external watch lists. Our solution could effectively handle multiple attributes such as typos, transliteration limitations, cultural differences for accurate hits detection.

After validating the accuracy and stability of the training models, we moved to the execution mode where we integrated additional data from source systems. The final models used in TM and NS processes helped execute alert prioritization accurately and investigate alerts in a faster manner. AMLS consolidated all source data to provide a holistic view of customers, accounts and transactions and brought in enhanced network analysis and intelligent cluster analysis to aid investigative functions across various business units within the bank.

The business interface of AMLS provides easy-to-use and highly customizable dashboards for both TM and NS processes, enabling efficient work allocation, exploratory analysis, link analysis, prediction interpretation and management reporting.

The following are the quantitative business benefits we received from the project.

  • Name Screening: 70% reduction in false positives for individual names and 60% reduction in false positives for corporate names.
  • Transaction Monitoring: 50% reduction in false positives with less than 1% misclassification, 5% increase in true positives (file-able SARs) and an overall true positive prediction rate of 96% in the high-priority category.

Other benefits we achieved are:

  • Increased effectiveness in identifying suspicious activities
  • A sharper focus on data anomalies rather than depending on threshold triggering
  • Easier customisation of data features to target specific risks accurately
  • Ability to enable longer look-back periods to detect complex scenarios

Protecting against model biases, our platform’s Champion-Challenger module automatically and continuously incorporates data shifts and data additions and informs users of the availability of any ‘Challenger’ model. Users may validate the vitals of the newly created ‘Challenger’ and replace it with the existing ‘Champion’ effortlessly. This unique feature helps financial institutions avoid time-consuming and costly model upgrades, ensuring faster ROI realization and sustained and effective performance of AML compliance programs.

The deployment of AMLS at UOB with stellar results marks the end of the AI experimentation phase in AML compliance. It is another example of how Tookitaki, as a fast-growing AI startup, sets new standards for the regulatory compliance industry’s fight against money laundering. Our success is noteworthy given that many enterprise AI projects are dying within laboratories. AMLS went through multiple rounds of testing and validation and our machine learning models have been proven to provide stable results and remain agile to the cause in dynamic situations. At the same time, it could effectively explain the decision-making process of machine learning models in a comprehensive yet simple manner through our patent-pending Explainable AI framework. Through this project, we also validated that our AI processes are effective, efficient and set to be applied in a responsible and ethical manner.

A complete revamp of existing AML compliance processes is imperative for financial institutions given that money laundering strategies become more and more sophisticated. It is time to embrace modern-era intelligent technology to enhance efficiency and effectiveness in AML compliance programs, establish next-gen financial crime surveillance and ensure robust risk management practices.

For more details into our partnerships with UOB and many other big banks across the globe, please contact us.

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Fraud targeting governments’ pandemic-related welfare programs have seen criminals exploiting these schemes ever since countries started helping their citizens and businesses. If reports are correct...

Crowdfunding: Yet Another Unconventional Means to Launder Money

Having transformed many ideas into profitable businesses, crowdfunding, a new-gen investment trend enabled by the internet, has become the first resort for many entrepreneurs and small businesses. The...

The Crackdown on Shell Companies and the Role of Technology

The Anti-Money Laundering Act (AMLA) 2020, enacted as part of the National Defense Authorization Act (NDAA) 2021 of the US in January this year, had many key provisions to take the Anti-Money Launderi...

Tookitaki Powers AI-Driven Anti-Money Laundering Solution Using HPE GreenLake

Hewlett Packard Enterprise (HPE) announced a key collaboration with Tookitaki to provide a new offering designed for banks and financial institutions across Asia-Pacific. The new offering delivers T...

AMLA 2020: 8 Key Provisions that Financial Institutions Required to Know

The US Congress passed the National Defense Authorization Act (NDAA) 2021 on January 1, 2021, addressing a variety of pressing concerns related to the nation’s security. The act included a number of...

The Rising Case for RegTech to Address AML Risks Amid COVID-19

Emerged as a subset of FinTech, the Regulatory Technology (RegTech) industry has now gone more mainstream, thanks to regulators and industry practitioners. Recently, there have been many pro-RegTech c...

Hakrinbank Selects Tookitaki to Ensure Sustainable Financial Compliance Monitoring

Tookitaki announced a partnership with Hakrinbank, a leading South American bank based in Suriname, to fortify its Anti-Money Laundering (AML) detection and alerts management capabilities. To improve...

Breaking Barriers: 5 Key Insights on RegTech Adoption

HKMA in a report shared comprehensive hands-on experience and insights from respondents to better understand the factors and dependencies affecting AML/CFT Regtech adoption. The regulator collaborated...

How to Address Present-day Sanctions Screening Pain Points with AI

Sanctions risk of financial institutions is evolving in line with the global social, economic and political changes. As seen in recent news, governments across the globe are increasingly relying on sa...

Tookitaki Got Selected for FinTech Program: Asia meets Tokyo

Tookitaki has been listed among 8 Fintech startups in Asia for FinTech Program: Asia meets Tokyo, an accelerator launched by the Tokyo Metropolitan Government (TMG). We have been selected for our anti...

AML Alert Management: How AI can Augment Your Compliance Efficiency

The financial sector is facing one monster of a problem at the moment. As today’s financial institutions deal with millions of daily transactions, several thousands of routine financial transactions...

Tookitaki Recognised for Innovative Use of AI & Machine Learning

Tookitaki has won the Regtech Award for AI & Machine Learning and was highly commended in the solutions category for AML/CTF Compliance, in the 3rd Regulation Asia Awards for Excellence 2020 ...

Our UOB Success Tale: Setting a New Benchmark for AI-based AML Compliance

Tookitaki achieved a rare and historic milestone as our Anti-Money Laundering Suite (AMLS) solution went live within the premises of United Overseas Bank (UOB), one of the top 3 banks in Singapore.

Tookitaki Wins 2020 WITSA Digital Innovation Award

Tookitaki has won the 2020 Digital Innovation Award from the World Information Technology and Services Alliance (WITSA) as part of the industry body’s Global ICT Excellence Awards. Nominated by...

Money Laundering via Cryptocurrencies: All You Need to Know

Technological advancements have given criminals faster and safer options to wash their ill-gotten money. There is no doubt that cryptocurrencies are very useful technology innovation that helps indivi...

CNA 938 radio interviews Tookitaki Co-founder Jeeta Badopadhyay

Tookitaki Co-founder and COO Jeeta Bandopadhyay was named among the Singapore 100 Women in Tech (SG100WIT) List in September 2020. A collaboration between the Singapore Computer Society (SCS), IMDA, S...

Need for New Customer Risk Rating Models: Not All Customers Are Created Equal

Being estimated at between US$800 billion to US$2 trillion every year, money laundering is a serious problem for the global economy. While regulators and financial institutions are working hard to pre...

Is AML Compliance Heading for a New Normal in the Age of Digital Payments?

Increased digitization has influenced various businesses and brought in a paradigm shift in the way they create business models and approach growth opportunities. Moving away from conventional transac...

Excel to AI: How Reconciliation Tools Evolve for Better

In the world of finance, reconciliation is the process of comparing two related sets of records or two accounts at the end of a specific accounting period to find out if account balances are matching ...

Lessons Not Well Learned: 2020 AML Fines Cross 2019 Total

If research is to be believed, institutions across the globe have not done enough in the anti-money laundering (AML) compliance area. Data from consultancy Duff & Phelps revealed that AML fines in...

Exploring AML Risks in COVID-Era and the Ways to Address Them

The world continues to battle the COVID-19 pandemic and the crisis it brought in is unprecedented in the history of humankind. While there are a number of pandemic-related factors contributing to the ...

AML Amid COVID-19: Watch out for These FBI-listed Fraud Schemes

There has been a rise in the number of cybercrimes and fraud schemes across the globe ever since the proliferation of the COVID-19 pandemic. Criminals, in general, are taking advantage of people’s s...

OCC Spring Risk Perspective: 5 Takeaways on Compliance Risk

Despite its general strength, the US federal banking system is apparently susceptible to the ongoing economic weakness caused by the rampant spread of coronavirus. Earlier this month, The US Office of...

How Criminals Used COVID-19 Sales Pitch to Defraud, Launder Money

As the world is working hard to contain the spread of the COVID-19, criminals continue to take advantage of the pandemic. They are devising sophisticated methods to defraud people and launder the crim...

5 Top Myths and Facts about AI Implementation in AML Programs

We are more confirmed about the power of Artificial Intelligence (AI) to transform lives and businesses now. There are countless possible applications of AI and machine learning at present, and we see...

Typology Repository Management: Solving AML Problems Via Collective Intelligence and Continuous Learning

Despite its general strength, the US federal banking system is apparently susceptible to the ongoing economic weakness caused by the rampant spread of coronavirus. Earlier this month, The US Office of...

Money Laundering Amid COVID-19: What Regulators Across Globe Say

As the world continues to fight against the COVID-19 pandemic, there are reports that criminals are taking advantage of the difficult situation. They are seizing the moment to proliferate their crimin...

How will Art Cease to Be a Preferred Money Laundering Vehicle?

Money laundering via high-end art and antiquities is not new yet it is difficult to detect. Art-related money laundering amounts to about US$3 billion per year, according to this blog, quoting the Uni...

Beware! Money Mules in Demand amid COVID-19. Here’s an Effective Cure

If reports are to be believed, cybercrooks are taking advantage of the COVID-19 situation. They are targeting people who were laid off or working from home due to the pandemic to work for them as mone...

How do we weather a tornado of change?

“Great works are performed not by strength but by perseverance” – Samuel Johnson All of us are in challenging times. However, we cannot afford to be lethargic to life, work, and busi...

Roundtable Rewind: Embracing Next-gen Tech & Collaboration Key to Sustainability

As a regtech player with a vision to enable sustainable compliance programs in financial institutions, Tookitaki organized a first-of-its-kind industry roundtable in Charlotte, NC, USA to discuss oppo...

Tookitaki Appoints Industry Veteran Joe Friscia as Advisor

Tookitaki Holding Pte. Ltd. appointed industry veteran Joe Friscia, former President of NICE Actimize and BAE Systems as Advisor to the Company’s Advisory Board. Joe brings over 25 years’ extensi...

Should Modern Machines Be Ethical?

There are mounting concerns across the globe about the reliability and safety of artificial intelligence (AI) based systems and its enabling technologies such as machine learning (ML). On the air are ...

Tookitaki Raises Another US$11.7 million in Series A; Closes Round at US$19.2 million

– by Abhishek Chatterjee, Founder & CEO The Tookitaki team and I are excited to announce that we have raised an additional US$11.7 million in Series A funding, taking the total investment in...

30 Years of FATF: Notable Facts About Global AML Watchdog

The Financial Action Task Force (FATF), the intergovernmental body formed in 1989 to combating money laundering, is celebrating its 30th anniversary this year. Since its inception, the global agency p...

Tookitaki Joins Aite Financial Crime Forum as Sponsor

Technological advances have fundamentally changed the operational landscape of financial institutions. However, there are also new risks emerging in forms of sophisticated financial frauds and complex...

Will Machine Learning Replace Compliance Professionals?

The impact of modern technologies such as artificial intelligence (AI) and machine learning on job security has been a widely discussed topic today. Of course, AI has advanced very quickly in the last...

6 Most Prevalent Cyber-Laundering Methods in APAC

Despite being a medium to exchange information in real-time and with scale, the Internet is being misused in several ways. Among the slew of financial crimes facilitated by the Internet, money launder...

What Made Us Earn the WEF Technology Pioneer Title

Tookitaki has bagged another global acknowledgement for its outstanding works in the regulatory compliance field. Our company was selected among hundreds of candidates as one of the World Economic Fo...

We Stay as a Team, We Win as a Team and We Flourish as a Team

“Teamwork is the ability to work together toward a common vision. The ability to direct individual accomplishments toward organizational objectives. It is the fuel that allows common people to a...

ABA Regulatory Compliance Conference: 10 Sessions You Can’t Miss

The 2019 edition of the American Bankers Association (ABA) Regulatory Compliance Conference is a few more days away. Organized by the Washington, D.C.-based trade association, the conference is touted...

Tookitaki AMLS Wins SBR Technology Excellence Award 2019

Tookitaki’s Anti-Money Laundering Suite (AMLS), an end-to-end machine learning-powered transaction monitoring and names screening solution, has bagged the inaugural Singapore Business Review Tec...

Watchdogs Grow Optimistic about AI Prospects at Banks

Proper regulation of banking operations is important as any failure in the banking system would affect the wider economy. Therefore, banking is one of the most regulated industries across the globe. F...

Pitfall of Black Box AI at Banks: Explaining Your Models to Regulators

The use cases of artificial intelligence (AI) and machine learning in front-office, middle-office and back-office activities at banks are growing slowly but steadily. The major areas of AI play includ...

AI for Regulatory Compliance at Banks: 4 Assessments Before You Okay the Solution Proposal

Banking is one of the industries where artificial intelligence and machine learning find their applications at a rapid pace. Regulatory compliance within banking is an area which has become a costly a...

We Believe in Innovation, the Key to Survival and Growth

“Innovation distinguishes between a leader and a follower.” -Steve Jobs What comes on the top of your screen when you google the meaning of the word innovation is – the introduction of somet...

Compliance Functions in Need of a Technological Overhaul. Can Machine Learning be the Game-Changer?

McKinsey in its latest compliance benchmarking survey found that compliance function at financial institutions has reached “an inflection point” and current compliance standards are in an “incho...

Tookitaki Raises US$7.5 mn Series A from Global VCs to Transform Regulatory Compliance

Tookitaki, a regulatory technology company that aims to enable financial institutions to develop sustainable compliance programs, has raised US$7.5 million in Series A round. The round was co-led by L...

From Wachovia to Danske Bank: Biggest Money Laundering Cases in Recent Times

Money laundering – the criminal activity of processing criminal proceeds to disguise their origin – is one of the gravest problems faced by the global economy, and its size is growing rapidly. It ...

A Modern Approach to Address the Reconciliation Challenges of Financial Services

Reconciliation of transactions is deemed critical for the smooth running of every financial institution. The speed and accuracy of data reconciliation can distinguish a successful institution from its...

Busting a Myth: Compliance Officer’s Job is All About Risk

Regulatory compliance has become a dreadful task for banks after regulators across the globe set stricter norms in the aftermath of the 2008 financial crisis in an effort to prevent financial crimes s...

SocGen Goes Next-Gen with Tookitaki Reconciliation Suite

Société Générale leveraged Tookitaki’s Reconciliation Suite to automate the bank’s existing break reconciliation system. Key Challenges Addressed The bank’s finance department was unable to ...

Attending ACAMS Conference in Singapore? Tookitaki Awaits You with Its Disruptive AML Solution

“In today’s era of volatility, there is no other way but to re-invent. The only sustainable advantage you can have over others is agility, that’s it.”- Jeff Bezos Singapore is hosting ACAMS’...

MAS’ Stress on Transaction Monitoring for Effective AML/CFT Compliance and Machine Learning is the Answer

Singapore is known for its top-notch AML/CFT regime created through up-to-date legislation, stringent policy and uncompromising supervision to safeguard against the abuse of the city state’s financi...

Mifid II and the Pressing Need for a New Reconciliation Approach

The financial services industry in the EU has been confused with the introduction of a revamped version of the Markets in Financial Instruments Directive (Mifid II). The ambitious regulatory reforms t...

Is Automated Reconciliation Next to Impossible in Today’s Complex Financial World?

The 2008 global financial crisis and fairly new regulatory requirements like Basel III asked financial institutions (FIs) to cut operating costs and adopt a lean operations structure, pushing FIs to r...

Modern Tech to Reshape US AML Compliance with Regulators’ Recent Handshake

George Bernard Shaw once said: “Those who cannot change their minds cannot change anything.” The past week has seen a significant change of mind from financial regulators in the US in their ardent...

Skills Development: We Have Talents and We Strive to Multiply Them

“Mastery lies on an infinite continuum, and as a result, we will never reach the end. We can, however, see to it that we are as far along that continuum as our circumstance allows.” ― Chris Mat...

It’s Our Fourth Founding Day; Taking a Pause to Cherish Our Simple but Awesome Journey

Today, as we step into our 4th year of foundation, I feel proud and honored to be leading Tookitaki that has been successful in creating added value to all its stakeholders. I was never a CEO and Took...

Tookitaki Expands into the US with New Office in Charlotte

SINGAPORE, Sept. 24, 2018: Tookitaki Holding Pte Ltd, a leading regulatory technology company, is pleased to announce the official opening of its North American office in Charlotte, NC, in the Unite...

We Tame Machines but We Unleash Human Spirits

We are well aware of the fact that our progress as an organization is in the hands of our employees. The more energy, time and attention we invest in them, the more yield we receive. So, we always mak...

5 Methods That Modern Money Launderers Use To Beat Detection

Society prepares the crime, the criminal commits it. DID YOU KNOW? Every year, an estimated amount in the range of US$800 billion-US$2 trillion (2-5% of global GDP) is being laundered globally Regulat...

Risk Management Conference: Positive Vibes from All Corners

The Risk Management Association’s (RMA) premier annual event, the Risk Management Conference, came to an end on 6 November, and Tookitaki had the privilege to attend the event which we believe was ...

Singapore Fintech Festival: Tookitaki to showcase advanced machine learning solutions in financial services

Singapore is assured of the Fintech world’s unwavering attention next week, as the city state, is hosting this year’s Fintech Festival during 12-16 November. Touted as the world’s largest platfo...

The RMA Clarion Call to Address Risks and the Tookitaki Way

Risk officers, doing your best today is good while preparing hard for tomorrow is extraordinary. Risk management at banks has become difficult due to operational and regulatory changes. The Risk Manag...