AFC Thoughts

Fighting Money Mules with Tookitaki’s Community-Based Approach

Site Logo
Tookitaki
05 Apr 2023
6 min
read

Money laundering is a global problem that affects all countries and industries, including financial institutions. One of the methods used to launder money is through the use of money mules. Money mules are individuals who are recruited by fraudsters to move stolen money between bank accounts, often across international borders. These individuals, often unwittingly, enable the transfer of money from victims of fraud to the perpetrators. The use of money mules is a growing problem, with the number of cases reported to authorities increasing year on year.

According to a media report, 1,239 scammers and money mules below 30 were arrested in Singapore between 2019 and 2021.

The impact of money mule activities on financial institutions can be severe, including reputational damage, financial losses, and even regulatory fines. Thus, it is crucial for financial institutions to have robust anti-money laundering (AML) compliance programmes in place to prevent and detect money mule activities. Tookitaki's community-based approach to AML compliance provides an innovative and effective solution to combat money mules.

Understanding Money Mules

Money mules are individuals who criminal organisations recruit to move money obtained through illegal means. They are often unaware that they are participating in a money laundering scheme, believing that they are simply receiving and transferring funds for someone else. Common methods used by money mules to launder money include:

  • Depositing funds into personal bank accounts and then transferring them to other accounts
  • Using online payment services to transfer funds to different accounts
  • Transporting cash across borders
  • Using digital currencies to transfer funds
Money mules can be anyone, including college students, senior citizens, and even professionals. However, they are often recruited from vulnerable populations, such as those with financial difficulties or those seeking employment opportunities.

The impact of money mule activities on financial institutions and the economy can be severe. Money mules can be used to facilitate a wide range of criminal activities, including drug trafficking, terrorism financing, and human trafficking. The use of money mules can make it difficult for law enforcement agencies to track the origins of illicit funds, making it challenging to hold criminals accountable.

To effectively combat money mule activities, financial institutions must have robust AML compliance programmes in place. Traditional AML compliance methods, such as transaction monitoring and Know Your Customer (KYC) checks, can be useful in detecting money mule activities. However, these methods alone may not be enough.

{{cta-afc}}

Traditional Approaches to Combating Money Mules

Financial institutions have traditionally relied on manual methods to detect and prevent money mule activities. These methods include:

  • Transaction Monitoring: Banks and financial institutions monitor transactions for any unusual patterns or amounts that may indicate money laundering or money mule activities. However, these systems are rule-based and often rely on pre-defined scenarios, making them vulnerable to false positives or negatives.
  • Know Your Customer (KYC): KYC is a method that involves verifying the identity of customers and assessing their risk profile. However, KYC checks can be incomplete or inaccurate, allowing money mules to go undetected.
  • Employee Training: Financial institutions provide training to employees to identify and report suspicious activities. However, employees may not always have the necessary knowledge or resources to identify and report money mule activities.

The Importance of a Community-Based Approach

A community-based approach to fighting financial crimes involves sharing information and intelligence between financial institutions, regulators, law enforcement agencies and other relevant stakeholders. This enables financial institutions to detect and prevent money mule activities more effectively.

The community-based approach involves the following key elements:

  • Education and awareness: Educating the public about the risks associated with money mules is critical to reducing their use. Financial institutions can work with law enforcement agencies and other stakeholders to raise awareness of the dangers of becoming involved in money mule activity.
  • Collaboration: Collaboration between financial institutions, law enforcement agencies, and other stakeholders is essential to the success of any AML compliance programme. These organisations can identify and disrupt money mule activity by sharing information and working together.
  • Technology: Technology plays a critical role in AML compliance. By leveraging advanced analytics on top of insights derived from the community, financial institutions can identify patterns of suspicious activity and detect potential money mule activity.

Tookitaki's AFC Ecosystem

Tookitaki is a pioneer in the fight against financial crime, leveraging a unique and innovative approach that transcends traditional solutions. The company's Anti-Money Laundering Suite (AMLS) and Anti-Financial Crime (AFC) Ecosystem work in tandem to address the limitations of siloed systems in combating money laundering.

The AFC Ecosystem is a community-based platform that facilitates sharing of information and best practices in the battle against financial crime. Powering this ecosystem is a Typology Repository, a living database of money laundering techniques and schemes. This repository is enriched by the collective experiences and knowledge of financial institutions, regulatory bodies, and risk consultants worldwide, encompassing a broad range of typologies from traditional methods to emerging trends.

The AMLS is a software solution deployed at financial institutions. It is an end-to-end operating system that modernises compliance processes for banks and fintechs. AMLS collaborates with the AFC Ecosystem through federated machine learning. This integration allows the AMLS to extract new typologies from the AFC Ecosystem, executing them at the clients' end to ensure that their AML programs remain cutting-edge.
Tookitaki AFC Ecosystem and AMLS

Additionally, Tookitaki leverages federated machine learning to bridge the gap between the AFC Ecosystem and the AMLS deployed at financial institutions. Instead of sharing sensitive data, federated learning allows the AMLS to access the latest typologies from the AFC Ecosystem and execute them locally at the client's end. This unique integration enables financial institutions to stay ahead of the curve and maintain cutting-edge AML programs while preserving data privacy and security.

In summary, Tookitaki's AMLS and AFC Ecosystem stand out from traditional AML solutions by fostering a collaborative community approach and harnessing the power of federated machine learning, ensuring that financial institutions have access to the most advanced tools and knowledge to effectively detect, prevent, and combat money laundering and related criminal activities.

The Benefits of Tookitaki’s Community-Based Approach

Tookitaki's community-based approach significantly enhances the overall effectiveness and efficiency of a financial institution's AML program in several ways:

  • Comprehensive Typology Repository: By fostering collaboration between financial institutions, regulatory bodies, and risk consultants, Tookitaki's AFC Ecosystem creates a collective knowledge base through a Typology Repository. This living database contains up-to-date money laundering techniques and schemes, which enables financial institutions to stay informed about emerging trends and threats.
  • Enhanced Detection Accuracy: Financial institutions can better identify suspicious activities and potential money laundering risks with access to the latest typologies and schemes. This leads to improved detection accuracy and a more robust AML program.
  • Reduction in False Alerts: Tookitaki's innovative technology, combined with the insights from the AFC Ecosystem, helps to minimize false positives. By accurately identifying suspicious activities, financial institutions can focus their resources on high-risk cases and reduce the operational burden of false alerts.
  • Adaptive Learning: Federated machine learning enables Tookitaki's AMLS to continuously learn from the AFC Ecosystem, ensuring that the AML program remains adaptive and up-to-date with the latest trends and regulatory changes.
  • Streamlined Compliance Processes: Tookitaki's AMLS modernizes compliance processes, making them more efficient and effective. This results in faster response times and allows financial institutions to maintain compliance with evolving regulations.
  • Improved Collaboration: The community-based approach encourages knowledge sharing and best practices among financial institutions, regulatory bodies, and risk consultants, fostering a cooperative environment in the fight against financial crime.

Protect Your Financial Institution from Money Mule Activities

Money mules are a significant threat to financial institutions and the economy as a whole. Traditional AML compliance methods have fallen short in detecting and preventing money-mule activities, but technology is changing the game. Tookitaki's AFC Ecosystem provides a community-based approach to AML compliance that is highly effective in combating money mules and other financial crime techniques.

Financial institutions must take proactive measures to prevent money mule activities and join Tookitaki's AFC Ecosystem to protect themselves and their customers. Learn more about Tookitaki's community-based approach to AML compliance and join the fight against money mules today.

By submitting the form, you agree that your personal data will be processed to provide the requested content (and for the purposes you agreed to above) in accordance with the Privacy Notice

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.

Ready to Streamline Your Anti-Financial Crime Compliance?

Our Thought Leadership Guides

AFC Thoughts
18 Jul 2024
4 min
read

Typology Tales July 2024: Account Takeover Surveillance

We are pleased to share the latest edition of "Typology Tales" for July 2024. This edition highlights the new typologies that our Anti-Financial Crime (AFC) community has carefully analysed and selected. Our community's collective efforts are crucial in staying ahead of evolving financial crime threats, and we are grateful for your continued participation and contributions.

AFC Community’s Role

Each month, our dedicated AFC community comes together to analyze and evaluate newly created typologies, selecting those that can significantly enhance the ecosystem's ability to prevent and combat financial crime. The typologies chosen for publication are those that offer the most promise in terms of effectiveness and applicability across various scenarios.

Key Highlights from July 2024 

These typologies have been meticulously curated to ensure they provide robust and actionable insights, ultimately helping to safeguard the financial ecosystem.

Theme of the Month: Account Takeover Fraud (ATO)

Theme of the month

Account takeover fraud (ATO) is a type of cybercrime where unauthorised people access a user's account and use it for harmful purposes. This dangerous activity has increased significantly in recent times, posing a growing threat to both individuals and organisations. 

In this edition...

In this edition of Typology Tales, we delve into two typologies that compliance professionals can incorporate into their transaction fraud monitoring systems to proactively prevent account takeover in real time.

Typology 1: Surge in Multi-Party Transactions in Sizeable Values

Typology-multiple counterparty

A pattern of multiple parties making high-value transactions with one entity in a short period of  time suggests possible account takeover fraud. This requires a strategic review of transaction behaviours.

How It Works

  • The typology monitors transactions involving a single customer who receives or transfers funds with multiple parties within a short time span.
  • To identify potential account takeover risks, the typology groups transactions by the unique identifiers of senders and receivers within a specified time frame. By tracking these identifiers over a defined period, it can determine how many different parties have transacted with a particular entity.

  • Simultaneously, the typology aggregates the transaction amounts linked to unique senders and receivers.

  • It flags any entity that engages in transactions with a large number of different parties and exceeds a cumulative transaction threshold. This signals potential account takeover risks due to unauthorised access and high-value transactions.

Typology 2: Monitoring High-Value Transactions Across Multiple Payment Modes

15 - 2024 July Edition TT Typology tales-1-1-1-1

Financial institutions may implement advanced monitoring to detect high-value transactions between senders and receivers through various modes, aiming to uncover potential account takeover fraud.

How It Works

  • To effectively oversee the flow of funds, the typology tracks and aggregates transaction amounts based on the mode of transfer.
  • Transaction amounts, including those made through cash or alternative payments, are further aggregated by the unique identifiers of the sender and receiver over a specific period.
  • Entities showing high-value transactions across multiple payment modes over specified time frames are potentially flagged as suspicious. This increased activity may indicate that an account has been compromised and is being used to funnel funds illegally.

From the Media: Account Takeover Attacks Overtake Ransomware as Leading Security Concern

Research by cybersecurity firm Abnormal Security highlights that account takeover (ATO) attacks have become a top concern for security leaders. The 2024 State of Cloud Account Takeover Attacks report reveals that 83% of organisations experienced at least one ATO incident in the past year. 

Over 75% of security leaders rank ATOs among the top four global cyber threats, with nearly 50% facing more than five incidents annually and around 20% encountering over ten incidents. ATOs are now considered more significant than other threats such as spear phishing and ransomware.

Read More

Unite in the Fight Against Financial Crime

Financial crime is a pervasive issue that requires a collective, centralised approach to intelligence gathering. That's why we have created the Anti-Financial Crime (AFC) Ecosystem, a network of experts who work together to share knowledge and develop strategies for combating financial crime.

If you are an AFC expert, we invite you to join our efforts and help us grow the AFC Ecosystem. And if you know any other AFC experts, please refer them to us so we can continue to expand and strengthen our network. Together, we can make a real difference in the fight against financial crime.

Typology Tales July 2024: Account Takeover Surveillance
AFC Thoughts
01 Jul 2024
3 min
read

Account Takeover Fraud: Monitoring Entities Incorporated Long Back

In the evolving landscape of financial crime, financial institutions need to intensify their scrutiny of transactions from entities with a long history of incorporation but sporadic or recent activity. This increased vigilance aims to detect and thwart potential account takeover fraud within savings accounts, ensuring the safety and integrity of financial systems.

Given below is a typology from Tookitaki's AFC Ecosystem. It details how to ensure your monitoring system triggers alerts transactions from entities with a long history of incorporation

Understanding the Typology

Setting Up Entity Historical Profiles

Financial institutions employ a function known as the "Incorporation Date of the Entity" to track and record the incorporation dates and transaction activities of entities. This function helps identify entities that have been established long ago but have shown recent or sudden transaction activities, which could be indicative of fraud.

Function Configuration and Data Aggregation

  • Aggregate Fields: The system aggregates data on 'sender incorporation date' and 'receiver incorporation date.'
  • Aggregate Function: Using the collect_set function, the system compiles a unique set of incorporation dates for each sender and receiver, providing a comprehensive historical perspective of each entity's transaction timeline.
  • Group By: Transactions are grouped by unique identifiers like 'sender_hashcode' and 'receiver_hashcode,' linking each entity’s transaction history to specific account profiles.

Monitoring and Anomaly Detection

The system continuously monitors the transaction activities of these entities, comparing current transactions against historical data. Entities that have shown no or minimal transaction activities for a significant period since their incorporation are closely watched. A sudden spike in transactions, especially those of significant volume or frequency, triggers an alert. This scrutiny is particularly heightened if the entity's previous activity has been minimal or non-existent for years.

Group 16190-1

Flagging and Review Process

Transactions involving long-dormant entities resuming activity are flagged as high-risk. These flagged transactions undergo a detailed review to ascertain the legitimacy of the activity and to rule out any potential account takeover or other fraudulent intentions.

Investigative Measures

For flagged transactions, financial institutions conduct thorough investigations involving:

  • Background Checks: Verifying the entity's background.
  • Transaction Legitimacy: Confirming the legitimacy of the transaction.
  • Entity Ownership: Ensuring the entity's ownership and operational status.

Preventative Actions and Customer Interaction

If fraudulent activity is confirmed, financial institutions take immediate steps to:

  • Block further transactions.
  • Secure the affected accounts.
  • Possibly reverse fraudulent transactions.
  • Contact entity representatives for further clarification and to ensure all parties are informed of the situation.

Compliance and Reporting Obligations

All suspicious activities are documented and reported in compliance with regulatory requirements. This ensures that the institution remains compliant with anti-fraud regulations and aids in broader efforts to combat financial crime.

{{cta-ebook}}

Enhancement of Monitoring Systems

Based on findings and trends observed from monitoring these entities, financial institutions continually refine their detection algorithms and update their monitoring systems to better identify and prevent potential fraud.

By closely monitoring the activities of entities incorporated long ago but recently active, banks can effectively spot unusual patterns that may indicate fraudulent activities, such as account takeovers. This proactive approach helps safeguard customer assets and maintain the integrity of the financial system.

Final Thoughts

Financial institutions must remain vigilant and proactive in monitoring and analyzing transaction activities, especially those involving historically dormant entities. This typology, sourced from Tookitaki's AFC Ecosystem, highlights the importance of advanced monitoring techniques in detecting potential fraud.

We encourage anti-financial crime professionals to join the AFC Ecosystem to access unique typologies and leverage community-driven insights for enhanced fraud detection and prevention. Together, we can strengthen our defenses against financial crime and protect the integrity of our financial systems.

Account Takeover Fraud: Monitoring Entities Incorporated Long Back
AFC Thoughts
22 May 2024
3 min
read

The Globalization of Fraud: The Rise of Transnational Scams

In an increasingly interconnected world, the borders that once confined criminal activities are rapidly dissolving, aided by the rise of digitalisation and the pervasive reach of online platforms. The stark reality we face today is a landscape where fraudsters exploit digital payment systems to target individuals across the globe, particularly in the Asia-Pacific region. Organised fraud syndicates are not just local threats; they operate on an international scale, executing sophisticated scams that often outpace current preventative measures.

Case Study: A Transnational Crackdown on Job Scams

On 20 March 2024, a significant breakthrough came when the Commercial Affairs Department (CAD) of the Singapore Police Force and the Bukit Aman Commercial Crime Investigation Department of the Royal Malaysia Police joined forces in Kuala Lumpur. This joint operation was the culmination of extensive cross-border investigative efforts aimed at dismantling a formidable job scam syndicate.

Between October 2023 and January 2024, this syndicate deceived over 3,000 individuals, accumulating illicit gains of approximately $45.7 million. These scams primarily targeted Singaporeans, promising lucrative job opportunities that required victims to make upfront payments or divulge sensitive information under the guise of securing employment. The rapid escalation of these scams prompted an intensive collaborative investigation, which eventually led to the arrest of five Malaysians involved in laundering the proceeds from these fraudulent activities.

This operation not only highlights the severity and reach of transnational scams but also underscores the urgent need for global cooperation and shared strategies to combat these crimes effectively.

Job Scam

The Imperative of a Collaborative Approach

As we witness a surge in transnational fraud, the isolation of financial institutions in their silos makes them particularly vulnerable. The complexity and rapid adaptation of fraud strategies require that defences be equally dynamic and interconnected.

Collective Intelligence and Shared Responsibility

To counteract the evolving menace of cross-border fraud effectively, a collaborative approach is indispensable. The AFC Ecosystem initiative represents a commitment to fostering industry-wide cooperation and information sharing. Through this collective intelligence, we aim to establish a robust defence mechanism that not only identifies but also anticipates fraudulent activities, ensuring safe and secure societies. This shared responsibility is vital in creating an impenetrable barrier against the sophisticated mechanisms of modern financial criminals.

Considering the Typology of the AFC Ecosystem

Drawing from the AFC Ecosystem's insights, let's delve into the typology of transnational job scams. This framework is instrumental in understanding how these frauds operate and what measures can be employed to thwart their attempts.

Detailed Analysis of the Typology

Transnational job scams represent a highly organized and rapidly proliferating threat that exploits the aspirations of job seekers worldwide. These scams are not just about deceit regarding employment opportunities but involve intricate financial manipulations that siphon funds across international borders.

Operational Mechanics

  • Initial Recruitment: The scam begins with contact through social media or other digital platforms, where victims are lured with high-return, low-effort job offers.
  • Deceptive Promises: The roles are advertised as lucrative yet simple enough to attract a wide demographic, from students to the unemployed.
  • Financial Prerequisites: Victims are persuaded to make upfront payments or provide personal information as a part of the onboarding process.
  • Expeditious Expansion: To maximize profits before any potential crackdown, these operations quickly scale and replicate across various regions.

{{cta-ebook}}

Granular Red Flags and Risk Indicators

To effectively monitor and prevent these scams, it is crucial to recognise the following detailed risk indicators:

  • Value: Transactions often involve small amounts that are usually perceived as low-risk by victims, making them less likely to raise immediate alarms.
  • Volume: A high frequency of transactions complicates tracking and analysis, as the sheer number of transactions can overwhelm standard monitoring systems.
  • Velocity: The rapid succession of payments, coupled with potential chargebacks or cancellations, creates a chaotic financial trail that is difficult to follow.
  • Channels: Scammers predominantly use digital payment platforms, online banking, and occasionally cryptocurrencies to maintain anonymity and complicate tracing.
  • Anonymity: There is often a mismatch between beneficiary details and the purported employer, signalling a red flag for transactions.
  • Recurrence: Victims are frequently solicited for multiple payments under various pretexts, each justified as necessary for job commencement or continuation.
  • High-risk Geos: Payments are directed to accounts in high-risk jurisdictions or to those that are otherwise unrelated or suspicious, lacking any logical connection to the job or employer.
  • Geographical Inconsistencies: The involved countries often have no direct connection to the alleged job or employer, exploiting the complexities of international law and jurisdictional boundaries.

Harnessing Collective Efforts for Enhanced Security

The fight against transnational fraud is not a battle that can be won in isolation. It requires the concerted efforts of financial institutions, regulatory bodies, law enforcement, and the public. By adopting the typology provided by the AFC Ecosystem and vigilantly monitoring the detailed risk indicators, we can forge a path towards a more secure and resilient financial environment. This collective approach is our best defense against the sophisticated and ever-evolving landscape of global fraud.

The Globalization of Fraud: The Rise of Transnational Scams