FinTech is one of the fastest-growing sectors today, with FinTech companies having dominated the lists of fastest-growing companies at least in the past couple of years. That being said, the accelerated growth of this sector does not come without challenges, particularly in navigating the different regulatory frameworks across global and regional markets.

A winner in the Startup Awards – FinTech & RegTech at the 2021 ORIGIN Innovation Awards, Tookitaki Holding Pte Ltd is an enterprise software solutions provider that creates sustainable compliance programs for the financial services industry. We are innovating the regulatory compliance space by developing software solutions to maximize the efficiency and effectiveness of compliance processes.

In this interview with Tookitaki’s Founder and Chief Executive Officer, Abhishek Chatterjee, we learn how the award-winning brand is changing the face of anti-money-laundering (AML) RegTech by harnessing AI, breaking down silos, and working with a network of AML experts around the world to tackle criminal activity.

Abhishek Chatterjee, Founder & CEO, Tookitaki
Abhishek Chatterjee, Founder & CEO, Tookitaki

What are the trends driving innovation in the Asia Pacific region today, particularly relevant to FinTech and RegTech?

We found the following trends in the Regtech space:

Increasing complexity of regulations

Regulators around the world continue to issue new regulations at a rate of 200 per day, putting increased pressure on financial institutions to interpret those notices and adapt their AML systems to keep up.

Firms are also plagued by constant updates on existing regulations, which consumes additional time and resources to monitor for any changes. New players, such as crypto exchanges, are being added to regulatory frameworks, broadening the available market for RegTech while increasing the complexity for traditional financial institutions to monitor new types of accounts and currencies.

Increasing demand for compliance solutions from neobanks and FinTechs

New-age financial services are gradually being scrutinized by regulators, with increased oversight and, in some cases, intervention. Many RegTech players use cloud and SaaS models, allowing them to implement compliance solutions in a more timely, effective, and scalable manner.

The emerging need for industry-wide collaboration

There are initiatives led by regulators that promote information sharing across institutions and regions in order to improve compliance. In the AML space, for example, the FATF recently published a paper stating that emerging technologies can facilitate advanced AML/CFT analytics and allow collaborative analytics between financial institutions while adhering to national and international data privacy requirements.

What are three key challenges that you are trying to address, and how are you addressing these through tech solutions?

Every year, approximately $800 billion to $2 trillion is laundered through the financial system, equating to approximately 25 percent of global GDP. Despite the fact that financial institutions and banks worldwide (including fund managers, insurers, and others) will spend more than $213.9 billion on AML and sanctions compliance in 2021, there are a number of reasons why this investment will not have the desired impact:

A lack of transparency: Investigators frequently struggle to identify the genuine, “beneficial,” because money launderers have learned how to bypass rules engines in order to avoid detection.

A lack of collaboration: Individual institutions are designing their anti-money laundering (AML) programs around their own products, customer types, and locations, with little knowledge of suspicious patterns of behavior observed among their peers.

A lack of resources: Financial institutions struggle to keep pace with implementing new rules. They are plagued with high false-positive volumes and file too many low-quality or unnecessary reports because they are incentivized to cover their backs rather than to apply sensible risk criteria.

Current AML compliance solutions are fragmented, relying primarily on rules or being supplemented by traditional machine learning approaches that are insufficient to keep up with changing customer behavior as a result of increased digitization. At the same time, current solutions produce extremely high false positives, rendering AML programs ineffective and inefficient while increasing costs.

Tookitaki’s AML compliance platform harnesses artificial intelligence (AI) to support a family of intelligent specialist compliance applications that set new standards in accuracy, speed, and resilience. Since our launch in 2014, we have built different compliance offerings including the Tookitaki Anti Money-Laundering (AML) Suite which is the industry’s first operating system for AML that combines processes across transaction monitoring, name & transaction screening, and customer risk scoring.

It reduces the time it takes to create, configure and test new rules by 50 percent. At the center of this is our library of over 100 pre-configured typologies and over 5,000 risk indicators which reflect real-life patterns of criminal behavior and built with specialist input from regulators, AML experts, and financial institutions around the world.

By focusing on patterns of behavior, we have made it easier for banks and financial institutions to work together to capture and adapt to continually changing criminal behavior. This is without needing to share commercially sensitive, personally identifiable information (PII), rules, or thresholds.

Tookitaki’s Anti-Money Laundering Suite (AMLS) assists financial institutions in improving risk coverage through democratized AML insights and precise detection via hyper configurable machine learning.

How important are regulations in the success of technology solutions, for instance, DeFi or FinTech platforms?

Regulations add a layer of security to technology solutions and technology becomes more trustworthy when it is regulated.

Blockchain-based decentralized finance is both recreating traditional financial instruments and inventing new ones. Because blockchain networks are decentralized and global, DeFI activities are outside of the purview of existing regulatory regimes. As a result, there is a high risk of DeFi being abused for crimes such as fraud and money laundering. We’ve already seen instances of cryptocurrencies and initial coin offerings being used to facilitate money laundering.

Given the risks, regulators must modify the current regulatory framework to accommodate DeFi services. It will not happen overnight. Regulators should improve their knowledge of new technology, collaborate productively with new technology players, create sandboxes, and aim to create informal guidelines rather than strict regulations at first.

What are your bold predictions for the FinTech sector in the medium term? How about the long-term?

  • The rising cost of compliance, frequent changes in regulations, and low entry barriers for SaaS-based solutions will drive demand for RegTech solutions in the medium and long term.
  • RegTech is no longer restricted to the financial sector. RegTech will expand to include more areas, such as embedded finance and decentralized finance, as time goes on, and the total addressable market will grow.
  • Consumers would be more interested in flexible Regtech with a global focus. Next-generation RegTech solutions would be driven by challenges rather than specific regulations. In the medium to long term, the rapid growth of applications based on artificial intelligence (AI), machine learning, and blockchain will provide new opportunities for RegTech companies.

Can you share some interesting data or case studies from your portfolio or partners that are a good example of how technology can bring about impactful change amid today’s business environment?

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) in the last quarter of 2020. 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).

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 handles 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.

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.

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.

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

  • Name Screening: 70 percent reduction in false positives for individual names and 60 percent reduction in false positives for corporate names.
  • Transaction Monitoring: 50 percent reduction in false positives with less than 1 percent misclassification, 5 percent increase in true positives (file-able SARs), and an overall true positive prediction rate of 96 percent 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 customization of data features to target specific risks accurately;
  • Ability to enable longer look-back periods to detect complex scenarios.

Tookitaki was also a winner at the inaugural ORIGIN Innovation Awards held in 2020, during which TechNode Global interviewed Tookitaki’s Abhishek Chaterjee on the impact of inclusive regulatory compliance.

Anti-Money Laundering guidance for FinTech