1. Startups

Regtech Startup Tookitaki Enters Indonesia, Presents Anti-Money Laundering Solutions for Fintech

Marks the second expansion of the year, after entering the Philippines in August 2022

Startups regtech Singaporean "Tookitaki" announced its presence in Indonesia to help financial institutions tackle money laundering risks. In the ASEAN region, it is claimed by several banks and companies fintech rely on his solution in implementing an anti-money laundering platform (anti-money laundering - AML).

In an official statement delivered today (20/9), Founder & CEO of Tookitaki Abhishek Chatterjee said, Indonesia is a market with great potential and the most influential in Southeast Asia. He hopes that his presence in Indonesia will not only fight the problem of money laundering, but can contribute more in building a secure financial ecosystem in various sectors.

“[..] We are happy to be a part of the financial ecosystem in Indonesia, as well as to help accelerate efforts to become members of the FATF,” said Chatterjee.

The momentum for Tookitaki's entry coincided with the Indonesian government's efforts to become a full member of the Financial Action Task Force (FATF). This is in order to combat the Crime of Money Laundering (TPPU) and the Financing of Terrorism (TPPT). Indonesia is the only G20 country that has not yet become a full member of the FATF.

Being a member of the FATF is considered to be able to make Indonesia easier to accept in international trade, as well as get assistance in combating money laundering and preventing the financing of terrorism. Indonesia will also have the opportunity to set global standards in its context as a developing country and gain the trust of foreign investors.

Based on data from PPATK (Center for Financial Transaction Reports and Analysis), there were 73 thousand suspicious transactions in Indonesia last year. This figure increased from the previous year of 68.057 transactions.

Tookitaki Solution

Tookitaki's vision is to eradicate financial crime by promoting an open rather than closed collective approach. It is supported by AML Ecosystem or called The Hub and Anti Money Laundering Suite (AMLS) or called "The Spoke".

The Hub is an intelligence service that studies money laundering patterns. While The Spoke is a simulated setup that allows local companies to download and test relevant patterns from The Hub, detect traces of illegal money and stay protected. The Spoke is installed in a financial institution environment without allowing test data to leave the network, thus providing maximum security.

AMLS has four main modules: Transaction Monitoring, Smart Screening, Customer Risk Scoring, and Case Manager. AMLS can also be used in various platforms, including Public Cloud, Private Cloud, and central data storage.

Tookitaki's expansion to two countries this year was supported by a new investor, namely Thunes, a Singapore-based global payments company, in April 2022. Tookitaki's investment in the deal amounted to $20 million (over 299 billion Rupiah).

According to estimates by the United Nations Office on Drugs and Crime (UNODC), between 2%-5% of global GDP, or $800 billion to $2 trillion, is laundered every year. This criminal activity threatens the functioning and integrity of the banking and financial services market. As cross-border payments increase, the risk of money laundering increases significantly, as do compliance costs.

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Additionally, a recent report by JP Morgan shows the total annual transaction fees for global cross-border payments have risen to $120 billion. Regulatory compliance makes up a significant percentage of this amount, and any reduction will provide important savings for Thunes customers.

Singapore-based Tookitaki was founded in November 2014, and employs more than 100 people across Asia, Europe and the US. It provides AML and compliance solutions to some of the world's leading banks and financial institutions, using Big Data and Machine Learning technologies.

“Our approach to AML monitoring is highly adaptable to changing market needs and customer behavior and fundamentally changes the way machine learning is applied to detect financial crimes,” Abhishek added.

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