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Trade Based Money Laundering Explained

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Tookitaki
9 min
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Trade Based Money Laundering (TBML) is a sophisticated method used by criminals to disguise illicit funds by manipulating international trade transactions. This article provides a comprehensive understanding of the basics, techniques, red flags, global impact, and prevention measures associated with TBML. Additionally, it highlights the role of financial institutions and the use of technology in detecting TBML, along with future trends and challenges in combating this form of money laundering.

Understanding the Basics of Trade Based Money Laundering

Trade Based Money Laundering involves exploiting the complexities of international trade to hide the origins of illicit funds and integrate them into the global financial system. Criminals use legitimate trade transactions to move money across borders disguised as legitimate businesses, making it difficult for authorities to trace the illicit funds.

One common method in TBML involves over-invoicing or under-invoicing goods, where the value of the goods in a trade transaction is manipulated to facilitate the movement of funds. For example, criminals may overstate the value of imported goods to transfer excess funds, or they may understate the value of exported goods to repatriate funds. By manipulating the prices of goods, criminals can launder money without raising suspicion.

Another technique used in TBML is the use of false documentation and multiple layers of trade intermediaries. This creates a complex network of transactions that further obscures the origins of illicit funds. Criminals may establish front companies, shell companies, or use collusive traders to create fictitious transactions and invoices.

Moreover, in the realm of Trade Based Money Laundering, criminals often exploit the time lag between the shipment of goods and the payment for those goods. This time gap provides an opportunity for illicit actors to manipulate documents and transfer funds discreetly. By delaying the payment or receipt of payment for goods, criminals can obscure the true nature of their financial activities, complicating the tracking process for law enforcement agencies.

Additionally, the use of trade finance instruments, such as letters of credit and trade loans, can be abused in TBML schemes. Criminals may misuse these financial tools to facilitate the movement of illicit funds under the guise of legitimate trade transactions. By leveraging the complexity of trade finance mechanisms, perpetrators of TBML can further obfuscate the money trail and evade detection.

Common Techniques Used in Trade Based Money Laundering

In addition to over-invoicing and under-invoicing, criminals employ various other techniques in TBML. These include:

  1. Phantom Shipments: Criminals create fake shipments that do not involve the actual movement of goods. In this scheme, invoices, bills of lading, and other shipping documents are falsified to create the appearance of a legitimate trade transaction.
  2. Multiple Invoicing: Criminals generate multiple invoices for the same transaction, making it difficult to track the movement of funds. This technique involves creating several invoices with varying values for the same goods.
  3. Black Market Currency Exchange: Criminals exploit the differences in foreign exchange rates to launder money. They manipulate the exchange of currencies in unofficial or unregulated markets, enabling them to convert illicit funds into legitimate currencies.
  4. Bulk Cash Smuggling: Criminals physically transport large sums of cash across borders, bypassing detection by authorities. This method is commonly used in conjunction with trade transactions to legitimize the illicit funds.

Another technique frequently used in Trade Based Money Laundering is Trade Mispricing. This method involves deliberately misrepresenting the price, quantity, or quality of goods on trade documents. By manipulating these details, criminals can disguise the true value of the goods being traded, allowing them to move illicit funds across borders without raising suspicion.

Shell Company Transactions are also a common tactic employed in TBML. Criminals set up shell companies with no legitimate business activities to facilitate money laundering. These companies engage in fake trade transactions, issuing false invoices and receipts to create the illusion of legitimate commerce. The complexity of the corporate structure and the use of multiple jurisdictions make it challenging for authorities to trace the illicit funds back to their source.

Red Flags of Trade Based Money Laundering

Identifying potential instances of TBML involves recognizing certain red flags. Some indicators of TBML include:

  • Unusual Trade Patterns: Frequent changes in trading partners, sudden shifts in product lines, or high-value transactions without a justified business purpose can be signs of TBML.
  • Overlapping Trade Routes: Suspicion arises when trade transactions involve countries known for money laundering activities or if trade routes deviate from usual patterns.
  • Unrelated Financial Flows: When the financial flows associated with a trade transaction do not correspond to the actual goods traded, it suggests potential TBML.
  • High-Risk Products: Certain industries, such as the precious metals and gemstones trade, have higher risks of TBML due to their high value and lack of standardized pricing.

Furthermore, it is essential for financial institutions and regulatory bodies to stay vigilant and updated on the evolving tactics used in TBML. One emerging trend is the utilization of shell companies in trade transactions to obscure the true origins and beneficiaries of funds. These shell companies often have complex ownership structures, making it challenging to trace the ultimate beneficial owners.

Another red flag to watch out for is the use of trade invoices with vague or incomplete descriptions of goods being traded. This lack of transparency can be a tactic used to disguise illicit activities within legitimate trade flows. Additionally, discrepancies between the stated value of goods on trade documents and their market prices can indicate potential TBML schemes, especially in industries where prices are volatile or difficult to determine accurately.

Global Impact of Trade Based Money Laundering on Economies

TBML poses significant risks to both developed and emerging economies. The extensive use of TBML not only facilitates money laundering but also undermines legitimate trade and distorts economic data. The infusion of illicit funds into the global financial system can damage economic stability, promote corruption, and hinder sustainable development.

Additionally, TBML creates unfair competition by enabling criminals to offer lower prices, undercutting legitimate businesses. This can lead to job losses, reduced tax revenues, and imbalances in trade balances.

Furthermore, the complex nature of TBML schemes makes them difficult to detect and investigate, allowing criminal organizations to exploit loopholes in regulatory systems. This not only weakens the integrity of financial institutions but also erodes public trust in the global financial system.

Moreover, the interconnected nature of international trade means that the repercussions of TBML extend beyond individual economies, affecting global supply chains and market dynamics. The increased use of TBML techniques poses a systemic risk to the international financial system, requiring coordinated efforts from governments, financial institutions, and regulatory bodies to combat effectively.

The Role of Financial Institutions in Preventing Trade Based Money Laundering

Financial institutions play a crucial role in identifying and preventing TBML. They are responsible for conducting enhanced due diligence on their customers, monitoring trade transactions, and reporting suspicious activities to the appropriate authorities.

To effectively combat TBML, financial institutions should establish robust Know Your Customer (KYC) procedures to ensure the legitimacy of their clients' trade activities. They should also implement transaction monitoring systems to detect unusual patterns, conduct periodic risk assessments, and provide comprehensive training to their employees.

Furthermore, financial institutions need to stay abreast of the latest trends and techniques used by money launderers to exploit trade transactions. This includes understanding the complexities of international trade finance, such as the use of shell companies, trade mispricing, and the manipulation of invoices to disguise illicit funds.

Collaboration between financial institutions, regulatory bodies, and law enforcement agencies is essential in the fight against TBML. Information sharing and coordination can help in identifying and disrupting money laundering activities effectively. Financial institutions should actively participate in public-private partnerships and industry forums to exchange best practices and strengthen their anti-money laundering efforts.

How to Prevent Trade Based Money Laundering?

Preventing TBML requires a comprehensive approach involving collaboration between governments, financial institutions, and other stakeholders. Some key measures to prevent TBML include:

  1. Enhanced Regulatory Frameworks: Governments should enact and enforce stringent legislation targeting TBML, imposing penalties for non-compliance and providing adequate resources for law enforcement agencies.
  2. International Cooperation: Countries must collaborate by sharing information and intelligence to track illicit flows and disrupt TBML networks that operate across borders.
  3. Technological Solutions: Utilizing advanced analytics, artificial intelligence, and machine learning can enhance the detection and prevention capabilities of financial institutions in identifying TBML.
  4. Public Awareness: Creating awareness campaigns and educating businesses about the risks and indicators of TBML can empower them to identify and report suspicious activities.

Moreover, it is essential for financial institutions to conduct thorough due diligence on their customers and counterparties to ensure they are not unwittingly facilitating TBML. This includes verifying the legitimacy of transactions, understanding the underlying economic substance of trade deals, and monitoring for any unusual patterns or red flags that may indicate potential money laundering activities.

Additionally, regulatory authorities can play a crucial role in combating TBML by conducting regular audits and assessments of financial institutions to evaluate their compliance with anti-money laundering regulations. By imposing strict reporting requirements and conducting on-site inspections, regulators can deter illicit activities and hold institutions accountable for any lapses in their anti-money laundering controls.

Technology and Innovation in Detecting Trade Based Money Laundering

Technological advancements play a pivotal role in enhancing the detection and prevention of TBML. Anti-money laundering (AML) software and data analysis tools can help financial institutions identify suspicious trade activities, analyze vast amounts of data, and detect patterns that would be difficult to identify manually.

Moreover, the use of blockchain technology, with its transparent and tamper-proof nature, holds potential in making trade transactions more secure and traceable, reducing the opportunities for TBML. Adopting these innovative solutions can significantly strengthen the efforts against TBML.

One of the key challenges in combating TBML is the constantly evolving nature of money laundering techniques. Criminals are adept at finding new ways to exploit vulnerabilities in the financial system, making it crucial for authorities to stay ahead of these tactics. This is where cutting-edge technologies such as artificial intelligence (AI) and machine learning come into play. By leveraging these tools, financial institutions can continuously adapt their detection methods to keep up with the changing landscape of financial crime.

Furthermore, collaboration between public and private sectors is essential in the fight against TBML. Information sharing and cooperation between financial institutions, regulatory bodies, and law enforcement agencies can lead to more effective detection and prosecution of money laundering activities. Technology serves as a catalyst for this collaboration, providing the necessary infrastructure for secure data exchange and communication.

Future Trends and Challenges in Trade Based Money Laundering

The fight against Trade Based Money Laundering (TBML) continues to evolve as criminals adapt their techniques to exploit vulnerabilities in the global trade system. Addressing the challenges associated with TBML requires constant vigilance and ongoing collaboration.

Future trends in combating TBML are likely to focus on the development of advanced technologies and data-sharing platforms that facilitate real-time information exchange among governments, financial institutions, and other stakeholders. These technologies will enable more efficient and effective detection of suspicious trade transactions, allowing authorities to take swift action to prevent money laundering.

One such technology that holds promise in the fight against TBML is artificial intelligence (AI). AI algorithms can analyze large volumes of trade data, including invoices, shipping documents, and financial records, to identify patterns and anomalies that may indicate illicit activity. By automating the analysis process, AI can significantly enhance the speed and accuracy of TBML detection, freeing up investigators to focus on more complex cases.

Another emerging technology that is expected to shape the future landscape of TBML prevention is blockchain. Blockchain is a decentralized and transparent ledger that records transactions in a secure and immutable manner. By leveraging blockchain technology, trade transactions can be recorded and verified in real-time, making it more difficult for criminals to manipulate trade documents and disguise illicit funds.

Moreover, regulatory bodies are expected to place a greater emphasis on enforcing strict compliance measures and holding financial institutions accountable for their anti-money laundering efforts. This includes conducting thorough due diligence on customers, implementing robust transaction monitoring systems, and reporting suspicious activities to the relevant authorities. By imposing stronger regulatory frameworks, governments can create a deterrent effect and ensure that financial institutions prioritize their anti-money laundering obligations.

Furthermore, international cooperation will play a crucial role in combating TBML. As money laundering knows no borders, sharing information and intelligence among countries is essential to identify and disrupt global money laundering networks. Inter-governmental organizations, such as the Financial Action Task Force (FATF), are working to enhance international cooperation and coordination in the fight against TBML.

Final Thoughts

In conclusion, TBML presents a significant challenge to the global financial system, posing threats to economic stability, fair trade, and the integrity of the financial sector. Understanding the basics, techniques, red flags, and prevention measures associated with TBML is vital in combating this complex form of money laundering. By leveraging technology, fostering international cooperation, and implementing robust regulatory frameworks, governments and financial institutions can make significant strides in preventing TBML and safeguarding the global economy.

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Blogs
23 Apr 2026
5 min
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Understanding the Source of Funds in Financial Transactions

In today's financial landscape, understanding the source of funds (SOF) is crucial for ensuring compliance and preventing financial crimes. Financial institutions must verify the origin of funds to comply with regulations and mitigate risks. This blog post delves into the meaning, importance, best practices, and challenges of verifying the source of funds.

Source of Funds in AML: What It Is and How Banks Verify It

Source of Funds Meaning

The term "source of funds" refers to the origin of the money used in a transaction. This can include earnings from employment, business revenue, investments, or other legitimate income sources.

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Source of Funds Example

For instance, if someone deposits a large sum of money into their bank account, the bank needs to verify whether this money came from a legitimate source, such as a property sale, inheritance, or salary.

Here are some common sources of funds:

  • Salary: Imagine you've been saving up from your job to buy a new gaming console. When you finally get it, your salary is the Source of Funds for that purchase. In the grown-up world, this could mean someone buying a house with the money they've saved from their job.
  • Inheritance: Now, let's say your grandma left you some money when she passed away (may she rest in peace), and you use it to start a college fund. The inheritance is your Source of Funds for that college account.
  • Business Profits: If you have a lemonade stand and make some serious cash, and then you use that money to buy a new bike, the profits from your business are your Source of Funds for the bike.
  • Selling Assets: Let's say your family decides to sell your old car to buy a new one. The money you get from selling the old car becomes the Source of Funds for the new car purchase.
  • Investments and Dividends: Suppose you've invested in some stocks, and you make a nice profit. If you use that money to, say, go on vacation, then the money you made from your investments is the Source of Funds for your trip.

Difference Between Source of Funds and Source of Wealth

Source of Funds (SOF) refers to the origin of the specific money involved in a transaction, such as income from employment, sales, or loans. It is focused on the immediate funds used in a particular financial activity.

Source of Wealth (SOW), on the other hand, pertains to the overall origin of an individual’s total assets, including accumulated wealth over time from various sources like investments, inheritances, or business ownership. It provides a broader view of the person's financial background.

Importance of Source of Funds Verification

Regulatory Requirements and Compliance

Verifying the source of funds is essential for financial institutions to comply with regulations such as anti-money laundering (AML) laws. Regulatory bodies like the Financial Action Task Force (FATF) mandate stringent checks to ensure that funds do not originate from illegal activities.

Financial and Reputational Risks

Failure to verify the source of funds can result in significant financial penalties and damage to an institution's reputation. Banks and other financial entities must implement robust verification processes to avoid involvement in financial crimes and maintain public trust.

Best Practices for Source of Funds Verification

Risk-Based Approach

Implementing a risk-based approach means assessing the risk level of each transaction and customer. Higher-risk transactions require more rigorous verification, ensuring that resources are allocated efficiently and effectively.

Advanced Technology Utilization

Utilizing advanced technologies such as artificial intelligence and machine learning can enhance the efficiency and accuracy of source of funds verification. These technologies can analyze large datasets quickly, identifying potential red flags.

Regular Updates and Audits

Maintaining updated records and conducting regular audits are crucial for an effective source of funds verification. This ensures that the verification processes remain robust and compliant with the latest regulations.

Source of Funds Requirements Across APAC

FATF Recommendation 13 requires financial institutions to apply enhanced due diligence, including source of funds verification for high-risk customers and transactions. In practice, each APAC regulator has translated this into specific obligations.

Australia (AUSTRAC)

Under the AML/CTF Rules Part 7, AUSTRAC requires ongoing customer due diligence that includes verifying source of funds when a transaction or customer profile is inconsistent with prior behaviour or stated purpose. Enhanced customer due diligence — triggered by high-risk customer classification, PEP status, or unusual transaction patterns — requires documented source of funds evidence before the transaction proceeds or the relationship continues.

Acceptable documentation under AUSTRAC guidance includes: recent pay slips (last 3 months), business financial statements, tax returns, property sale contracts, or investment account statements. For inheritance-sourced funds, a grant of probate or solicitor letter is required.

Singapore (MAS)

MAS Notice 626 requires Singapore-licensed FIs to verify source of funds as part of enhanced due diligence for high-risk customers and any customer whose funds originate from high-risk jurisdictions. MAS examination findings have consistently cited inadequate SOF documentation as a gap — specifically, accepting verbal declarations without supporting evidence.

Malaysia (BNM)

BNM's AML/CFT Policy Document requires source of funds verification for EDD-triggered customers, high-value transactions above MYR 50,000 in cash-equivalent form, and corporate accounts where beneficial ownership is complex. BNM specifically requires that SOF evidence be independently verifiable — a customer's own declaration is not sufficient for high-risk accounts.

Philippines (BSP)

BSP Circular 706 and its amendments require source of funds verification for customers classified as high-risk under the institution's risk assessment, and for any transaction that appears inconsistent with the customer's known financial profile. AMLC's guidance notes that source of funds documentation must be retained for a minimum of 5 years.

Common Sources of Funds

Legitimate Sources

Legitimate sources of funds include earnings from employment, business income, investment returns, loans, and inheritances. These sources are generally verifiable through official documentation such as pay slips, tax returns, and bank statements.

Illegitimate Sources

Illegitimate sources of funds might include money from illegal activities such as drug trafficking, fraud, corruption, or money laundering. These sources often lack proper documentation and can pose significant risks to financial institutions if not properly identified and reported.

Challenges in Verifying Source of Funds

Complex Transactions

Complex transactions, involving multiple parties and jurisdictions, pose significant challenges in verifying the source of funds. Tracing the origin of such funds requires comprehensive analysis and robust systems to track and verify all related transactions.

Privacy and Data Protection Concerns

Verifying the source of funds often involves handling sensitive personal data. Financial institutions must balance the need for thorough verification with strict adherence to privacy and data protection regulations, ensuring that customer information is secure.

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What Good Source of Funds Verification Looks Like in Practice

The institutions that handle SOF verification most effectively treat it as a tiered process, not a one-size-all checklist.

For standard-risk customers, verification at onboarding is enough — pay slips, a bank statement, or a tax return. For high-risk customers, EDD-triggered accounts, or transactions that don't fit the pattern, that standard is higher: independently verifiable documentation, a paper trail that shows the funds' journey from origin to arrival, and a compliance officer's written sign-off.

The documentation requirement is not the hard part. The hard part is knowing when to apply it — and that is a transaction monitoring question as much as a KYC question. A source of funds issue that doesn't get flagged at monitoring never reaches the verification stage.

For more on building the monitoring programme that surfaces these cases, see our Transaction Monitoring Software Buyer's Guide and our complete guide to KYC and customer due diligence.

Talk to Tookitaki's team about how FinCense handles source of funds flags as part of an integrated AML and transaction monitoring programme.

Frequently Asked Questions

1. What is source of funds in AML?
Source of funds refers to where the money used in a specific transaction or business relationship comes from. In AML compliance, financial institutions review source of funds to understand whether the money is legitimate and whether it matches the customer’s profile and declared activity.

2. Why is source of funds important in AML compliance?
Source of funds is important because it helps financial institutions assess whether the money involved in a transaction is consistent with what they know about the customer. It supports due diligence, helps identify unusual activity, and reduces the risk of money laundering or other financial crime.

3. What is the difference between source of funds and source of wealth?
Source of funds refers to the origin of the money used in a particular transaction or account activity. Source of wealth refers to how a customer built their overall wealth over time. In simple terms, source of funds looks at where this money came from, while source of wealth looks at how the person became wealthy in general.

4. How do financial institutions verify source of funds?
Financial institutions may verify source of funds using documents such as bank statements, salary slips, business income records, property sale agreements, inheritance papers, dividend records, or other documents that explain where the money originated. The exact documents required depend on the customer, the transaction, and the level of risk involved.

5. When is source of funds verification required?
Source of funds verification is commonly required during customer onboarding, enhanced due diligence, high-risk transactions, or periodic reviews. It may also be requested when a transaction appears unusual or does not match the customer’s known financial behaviour.

6. Is source of funds verification required for every customer?
Not always. The depth of source of funds verification usually depends on the customer’s risk level, the nature of the transaction, and applicable AML regulations. Higher-risk customers and more complex transactions generally require closer scrutiny.

7. What source of funds documentation does AUSTRAC accept?
AUSTRAC's AML/CTF guidance accepts: recent pay slips (last 3 months), business financial statements or tax returns, property sale contracts with settlement documentation, investment account statements, and for inherited funds, a grant of probate or solicitor's letter. Verbal declarations are not sufficient for high-risk customers or transactions triggering enhanced due diligence.

8. Is source of funds verification required for every transaction?No. Source of funds verification is triggered by risk level, not transaction volume. Standard-risk retail customers verified at onboarding do not require SOF documentation for routine transactions. The trigger points are: EDD classification, PEP status, transactions inconsistent with the customer's stated financial profile, high-value cash transactions above reporting thresholds, and periodic review of high-risk accounts. See your regulator's specific guidance — AUSTRAC's Part 7, MAS Notice 626, or BNM's AML/CFT Policy Document — for the applicable triggers in your jurisdiction.

Understanding the Source of Funds in Financial Transactions
Blogs
22 Apr 2026
6 min
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eKYC in Malaysia: Bank Negara Guidelines for Digital Banks and E-Wallets

In 2022, Bank Negara Malaysia awarded digital bank licences to five applicants: GXBank, Boost Bank, AEON Bank (backed by RHB), KAF Digital, and Zicht. None of these institutions have a branch network. None of them can sit a customer across a desk and photocopy a MyKad. For them, remote identity verification is not a product feature — it is the only way they can onboard a customer at all.

That is why BNM's eKYC framework matters. The question for compliance officers and product teams at these institutions — and at the e-money issuers, remittance operators, and licensed payment service providers that operate under the same rules is not whether to implement eKYC. It is whether the implementation will satisfy BNM when examiners review session logs during an AML/CFT examination.

This guide covers what BNM's eKYC framework requires, where institutions most commonly fall short, and what the rules mean in practice for tiered account access.

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The Regulatory Scope of BNM's eKYC Framework

BNM's eKYC Policy Document was first issued in June 2020 and updated in February 2023. It applies to a wide range of supervised institutions:

  • Licensed banks and Islamic banks
  • Development financial institutions
  • E-money issuers operating under the Financial Services Act 2013 — including large operators such as Touch 'n Go eWallet, GrabPay, and Boost
  • Money service businesses
  • Payment Services Operators (PSOs) licensed under the Payment Systems Act 2003

The policy document sets one overriding standard: eKYC must achieve the same level of identity assurance as face-to-face verification. That standard is not aspirational. It is the benchmark against which BNM examiners assess whether a remote onboarding programme is compliant.

For a deeper grounding in what KYC requires before getting into the eKYC-specific rules, the KYC compliance framework guide covers the foundational requirements.

The Four BNM-Accepted eKYC Methods

BNM's eKYC Policy Document specifies four accepted verification methods. Institutions must implement at least one; many implement two or more to accommodate different customer segments and device capabilities.

Method 1 — Biometric Facial Matching with Document Verification

The customer submits a selfie and an image of their MyKad or passport. The institution's system runs facial recognition to match the selfie against the document photo. Liveness detection is mandatory — passive or active — to prevent spoofing via static photographs, recorded video, or 3D masks.

This is the most widely deployed method among Malaysian digital banks and e-money issuers. It works on any smartphone with a front-facing camera and does not require the customer to be on a live call or to own a device with NFC capability.

Method 2 — Live Video Call Verification

A trained officer conducts a live video interaction with the customer and verifies the customer's face against their identity document in real time. The officer must be trained to BNM's specified standards, and the session must be recorded and retained.

This method provides strong identity assurance but introduces operational cost and throughput constraints. Some institutions use it as a fallback for customers whose biometric verification does not clear automated thresholds.

Method 3 — MyKad NFC Chip Reading

The customer uses their smartphone's NFC reader to read the chip embedded in their MyKad directly. The chip contains the holder's biometric data and personal information, and the read is cryptographically authenticated. BNM considers this the highest assurance eKYC method available under Malaysian national infrastructure.

The constraint is device compatibility: not all smartphones have NFC readers, and the feature must be enabled. Adoption among mass-market customers remains lower than biometric methods as a result.

Method 4 — Government Database Verification

The institution cross-checks customer-provided information against government databases — specifically, JPJ (Jabatan Pengangkutan Jalan, road transport) and JPN (Jabatan Pendaftaran Negara, national registration). If the data matches, the identity is considered verified.

BNM treats this as the lowest-assurance method. Critically, it does not involve any biometric confirmation that the person submitting the data is the same person as the registered identity. BNM restricts Method 4 to lower-risk product tiers, and institutions that apply it to accounts exceeding those tier limits will face examination findings.

Liveness Detection: What BNM Expects

BNM's requirement for liveness detection in biometric methods is explicit in the February 2023 update to the eKYC Policy Document. The requirement exists because static facial matching alone — matching a selfie against a document photo — can be defeated by holding a photograph in front of the camera.

BNM expects institutions to document the accuracy performance of their liveness detection system. The specific thresholds the policy document references are:

  • False Acceptance Rate (FAR): below 0.1% — meaning the system incorrectly accepts a spoof attempt in fewer than 1 in 1,000 cases
  • False Rejection Rate (FRR): below 10% — meaning genuine customers are incorrectly rejected in fewer than 10 in 100 cases

These are not defaults — they are floors. Institutions must document their actual FAR and FRR in their eKYC programme documentation and must periodically validate those figures, particularly after model updates or changes to the verification vendor.

Third-party eKYC vendors must be on BNM's approved list. An institution using a vendor not on that list — even a globally recognised biometric vendor — does not have a compliant eKYC programme regardless of the vendor's technical capabilities.

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Account Tiers and Transaction Limits

BNM applies a risk-based framework that links account access limits to the assurance level of the eKYC method used to open the account. This is not optional configuration — these are regulatory caps.

Tier 1 — Method 4 (Database Verification Only)

  • Maximum account balance: MYR 5,000
  • Maximum daily transfer limit: MYR 1,000

Tier 2 — Methods 1, 2, or 3 (Biometric Verification)

  • E-money accounts: maximum balance of MYR 50,000
  • Licensed bank accounts: no regulatory cap on balance (subject to the institution's own risk limits)

If a customer whose account was opened via Method 4 wants to move into Tier 2, they must complete an additional verification step using a biometric method. That upgrade process must be documented and the records retained — the same as any primary onboarding session.

This tiering structure means product decisions about account limits are also compliance decisions. A digital bank that launches a savings product with a MYR 10,000 minimum deposit and relies on Method 4 for onboarding has a compliance problem, not just a product design problem.

Record-Keeping: What Must Be Retained and for How Long

BNM requires that all eKYC sessions be recorded and retained for a minimum of 6 years. The records must include:

  • Raw images or video from the verification session
  • Facial match confidence scores
  • Liveness detection scores
  • Verification timestamps
  • The outcome of the verification (approved, rejected, referred for manual review)

During AML/CFT examinations, BNM examiners review eKYC session logs. An institution that can demonstrate a successful biometric match but cannot produce the underlying scores and timestamps for that session does not have compliant records. This is a documentation failure, not a technical one and it is one of the more common findings in Malaysian eKYC examinations.

eKYC Within the Broader AML/CFT Programme

A compliant eKYC onboarding process does not discharge an institution's AML/CFT obligations for the full customer lifecycle. BNM's AML/CFT Policy Document — separate from the eKYC Policy Document — requires institutions to apply risk-based customer due diligence (CDD) continuously.

Two areas where this creates friction in eKYC-based operations:

High-risk customers require Enhanced Due Diligence (EDD) that eKYC cannot complete. A customer who is a Politically Exposed Person (PEP), operates in a high-risk jurisdiction, or presents unusual transaction patterns requires EDD. Source of funds verification for these customers cannot be completed through biometric verification alone. Institutions must have documented rules specifying when an eKYC-onboarded customer triggers the EDD workflow — and those rules must be reviewed and enforced in practice, not just documented.

Dormant account reactivation is a re-verification trigger. BNM expects institutions to treat the reactivation of an account dormant for 12 months or more as an event requiring re-verification. This is a common gap: many institutions have onboarding eKYC workflows but no corresponding re-verification process for dormant accounts coming back to active status.

For institutions that have deployed transaction monitoring alongside their eKYC programme, integrating eKYC assurance levels into monitoring rule calibration is good practice — a Tier 1 account that begins transacting at Tier 2 volumes is exactly the kind of pattern that should generate an alert. The transaction monitoring software buyer's guide covers what to look for in a system capable of handling this kind of integrated logic.

Common Implementation Gaps

Based on BNM examination findings and the February 2023 policy document guidance, four gaps appear most frequently in Malaysian eKYC programmes:

1. Using Method 4 for accounts that exceed Tier 1 limits. This is the most consequential gap. If an account opened via database verification reaches a balance above MYR 5,000 or a daily transfer above MYR 1,000, the institution is operating outside the regulatory framework. The fix requires either enforcing hard caps at the product level or requiring biometric re-verification before account limits expand.

2. No liveness detection documentation. An institution that has deployed biometric eKYC but cannot demonstrate to BNM that it tested for spoofing — with documented FAR/FRR figures — does not have a defensible eKYC programme. The technology alone is not enough; the validation and documentation must exist.

3. Third-party eKYC vendor not on BNM's approved list. BNM maintains an approved vendor list for a reason. An institution that integrated a non-listed vendor, even one with strong global credentials, needs to remediate — either by migrating to an approved vendor or by engaging BNM directly on the approval process before continuing to use that vendor for compliant onboarding.

4. No re-verification trigger for dormant account reactivation. Institutions that built their eKYC programme around the onboarding workflow and never implemented re-verification logic for dormant accounts have a gap that BNM examiners will find. This requires both a policy update and a system-level trigger.

What Good eKYC Compliance Looks Like

A compliant eKYC programme in Malaysia has five elements that work together:

  1. At least one BNM-accepted verification method, implemented with a BNM-approved vendor and validated to the required FAR/FRR thresholds
  2. Hard account tier limits enforced at the product level, with a documented upgrade path that triggers biometric re-verification for Tier 1 accounts requesting higher access
  3. Complete session records — images, scores, timestamps, and outcomes — retained for the full 6-year period
  4. EDD triggers documented and enforced for high-risk customer categories, including PEPs and high-risk jurisdiction connections
  5. Re-verification workflows for dormant accounts reactivating after 12 months of inactivity

Meeting all five is not a one-time project. BNM expects periodic validation of vendor performance, regular review of threshold calibration, and documented sign-off from a named senior officer on the state of the eKYC programme.

For Malaysian institutions building or reviewing their eKYC programme, Tookitaki's AML compliance platform combines eKYC verification with transaction monitoring and ongoing risk assessment in a single integrated environment — designed for the requirements BNM examiners actually check. Book a demo to see how it works in a Malaysian digital bank or e-money context, or read our KYC framework overview for a broader view of where eKYC sits within the full compliance programme.

eKYC in Malaysia: Bank Negara Guidelines for Digital Banks and E-Wallets
Blogs
21 Apr 2026
5 min
read

The App That Made Millions Overnight: Inside Taiwan’s Fake Investment Scam

The profits looked real. The numbers kept climbing. And that was exactly the trap.

The Scam That Looked Legit — Until It Wasn’t

She watched her investment grow to NT$250 million.

The numbers were right there on the screen.

So she did what most people would do, she invested more.

The victim, a retired teacher in Taipei, wasn’t chasing speculation. She was responding to what looked like proof.

According to a report by Taipei Times, this was part of a broader scam uncovered by authorities in Taiwan — one that used a fake investment app to simulate profits and systematically extract funds from victims.

The platform showed consistent gains.
At one point, balances appeared to reach NT$250 million.

It felt credible.
It felt earned.

So the investments continued — through bank transfers, and in some cases, through cash and even gold payments.

By the time the illusion broke, the numbers had disappeared.

Because they were never real.

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Inside the Illusion: How the Fake Investment App Worked

What makes this case stand out is not just the deception, but the way it was engineered.

This was not a simple scam.
It was a controlled financial experience designed to build belief over time.

1. Entry Through Trust

Victims were introduced through intermediaries, referrals, or online channels. The opportunity appeared exclusive, structured, and credible.

2. A Convincing Interface

The app mirrored legitimate investment platforms — dashboards, performance charts, transaction histories. Everything a real investor would expect.

3. Fabricated Gains

After initial deposits, the app began showing steady returns. Not unrealistic at first — just enough to build confidence.

Then the numbers accelerated.

At its peak, some victims saw balances of NT$250 million.

4. The Reinforcement Loop

Each increase in displayed profit triggered the same response:

“This is working.”

And that belief led to more capital.

5. Expanding Payment Channels

To sustain the operation and reduce traceability, victims were asked to invest through:

  • Bank transfers
  • Cash payments
  • Gold and other physical assets

This fragmented the financial trail and pushed parts of it outside the system.

6. Exit Denied

When withdrawals were attempted, friction appeared — delays, additional charges, or silence.

The platform remained convincing.
But it was never connected to real markets.

Why This Scam Is a Step Ahead

This is where the model shifts.

Fraud is no longer just about convincing someone to invest.
It is about showing them that they already made money.

That changes the psychology completely.

  • Victims are not acting on promises
  • They are reacting to perceived success

The app becomes the source of truth.This is not just deception. It is engineered belief, reinforced through design.

For financial institutions, this creates a deeper challenge.

Because the transaction itself may appear completely rational —
even prudent — when viewed in isolation.

Following the Money: A Fragmented Financial Trail

From an AML perspective, scams like this are designed to leave behind incomplete visibility.

Likely patterns include:

  • Repeated deposits into accounts linked to the network
  • Gradual increase in transaction size as confidence builds
  • Use of multiple beneficiary accounts to distribute funds
  • Rapid movement of funds across accounts
  • Partial diversion into cash and gold, breaking traceability
  • Behaviour inconsistent with customer financial profiles

What makes detection difficult is not just the layering.

It is the fact that part of the activity is deliberately moved outside the financial system.

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Red Flags Financial Institutions Should Watch

Transaction-Level Indicators

  • Incremental increase in investment amounts over short periods
  • Transfers to newly introduced or previously unseen beneficiaries
  • High-value transactions inconsistent with past behaviour
  • Rapid outbound movement of funds after receipt
  • Fragmented transfers across multiple accounts

Behavioural Indicators

  • Customers referencing unusually high or guaranteed returns
  • Strong conviction in an investment without verifiable backing
  • Repeated fund transfers driven by urgency or perceived gains
  • Resistance to questioning or intervention

Channel & Activity Indicators

  • Use of unregulated or unfamiliar investment applications
  • Transactions initiated based on external instructions
  • Movement between digital transfers and physical asset payments
  • Indicators of coordinated activity across unrelated accounts

The Real Challenge: When the Illusion Lives Outside the System

This is where traditional detection models begin to struggle.

Financial institutions can analyse:

  • Transactions
  • Account behaviour
  • Historical patterns

But in this case, the most important factor, the fake app displaying fabricated gains — exists entirely outside their field of view.

By the time a transaction is processed:

  • The customer is already convinced
  • The action appears legitimate
  • The risk signal is delayed

And detection becomes reactive.

Where Technology Must Evolve

To address scams like this, financial institutions need to move beyond static rules.

Detection must focus on:

  • Behavioural context, not just transaction data
  • Progressive signals, not one-off alerts
  • Network-level intelligence, not isolated accounts
  • Real-time monitoring, not post-event analysis

This is where platforms like Tookitaki’s FinCense make a difference.

By combining:

  • Scenario-driven detection built from real-world scams
  • AI-powered behavioural analytics
  • Cross-entity monitoring to uncover hidden connections
  • Real-time alerting and intervention

…institutions can begin to detect early-stage risk, not just final outcomes.

From Fabricated Gains to Real Losses

For the retired teacher in Taipei, the app told a simple story.

It showed growth.
It showed profit.
It showed certainty.

But none of it was real.

Because in scams like this, the system does not fail first.

Belief does.

And by the time the transaction looks suspicious,
it is already too late.

The App That Made Millions Overnight: Inside Taiwan’s Fake Investment Scam