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Transaction Monitoring in Fintech: Challenges and Solutions

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Tookitaki
16 June 2021
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6 min

While the COVID-19 pandemic has affected the global economy with long-lasting implications for companies and consumers, the Fintech sector has largely been resilient with notable growth across most geographies. A joint study of the sector by the World Bank, the Cambridge Centre for Alternative Finance at the University of Cambridge’s Judge Business School, and World Economic Forum identified Fintech firms have continued to help expand access to financial services during the COVID-19 pandemic—particularly in emerging markets.

“Fintech has shown its potential to close gaps in the delivery of financial services to households and firms in emerging markets and developing economies,” said Caroline Freund, World Bank Global Director for Finance, Competitiveness and Innovation.

She added that the fintech industry is “adapting to the pandemic and offers insights for regulators and policymakers seeking to promote innovation and reap the benefits of fintech while managing risks to consumers, investors, financial stability, and integrity”.

Operational Challenges

Meanwhile, according to the study, fintech companies are also facing operational challenges due to the pandemic. Forty per cent of firms surveyed noted that they have either introduced or are in the process of introducing better fraud or security measures as a response to business conditions under the pandemic. In fact, regulators have also started worrying about compliance within fintech firms, given their increased popularity and growth. They are concerned that neobanks’ compliance processes are not up to the mark, leaving them vulnerable to criminal abuse.

Recently, German regulator BaFin ordered neobank N26 Bank to “rectify deficiencies both in IT monitoring and in customer due diligence”. The order stated that the neobank should hire more personnel, improve the documentation of compliance processes, redo due diligence checks on some existing customers and close backlogs in transaction monitoring. BaFin also appointed a “special commissioner” to update the regulator on the bank’s progress.

N26, which has 7 million customers in 25 markets, clarified that fraudsters misused its platform by pushing third parties to open accounts, which were then used for criminal purposes. “Since the start of the COVID pandemic, criminal activity in connection with online trade has increased dramatically around the world,” the neobank said. “The demands of BaFin aim to prevent the opening of such accounts, to identify illegal financial transactions as quickly as possible, and to block them.”

The Need for Transaction Monitoring

Transaction monitoring refers to monitoring customer transactions such as deposits, withdrawals and transfers for potential illegal behaviour while considering customers’ historical and current information and transactional relationships. Today, financial institutions use various software solutions to analyse transactions as it is not practical for them to have dedicated staff to review each and every one from millions of transactions.

These transaction monitoring systems have various rules and threshold settings to identify potential illegal behaviours and flag those transactions. When a transaction is flagged, a human investigator goes into its details, decides whether it is suspicious or not and reports to relevant authorities if it is suspicious. Transaction monitoring is important for any regulated financial institution as the process acts as a key line of defence against all forms of financial crimes.

Issues with financial crime detection

Criminals worldwide continue to innovate their strategies to launder money despite increased scrutiny by regulators and higher compliance spending by financial institutions. They know how transaction monitoring systems work within financial institutions and have ways to bypass rules and thresholds easily.

Financial institutions need to create new rules and update thresholds to counter new and emerging money laundering and fraud strategies. Financial institutions need several weeks to create, test and implement new rules into their transaction monitoring systems, and rules upgrade may not be a sustainable option given the frequent changes in the regulatory landscape and continuous changes in criminal behaviour.

Operational efficiency is impacted.

On the operational side, financial institutions have the problem of false alerts. While lenient transaction thresholds in monitoring systems would help financial institutions avert risk, they result in a large number of false alerts. While each and every alert needs to be investigated, the pile of false alerts leads to wastage work hours and huge alert backlogs for many institutions. The inability to determine the relative risk of individual alerts adds tremendous operational pressure to AML teams.

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AI for superior AML compliance programs

AI has brought in disruption in many industries with its ability to mine, structure and analyse huge volumes of data and provide actionable insights. AI can take up repetitive tasks, saving valuable time, effort and resources that can be redirected perform higher-value functions. From an AML compliance perspective, AI can extract risk-relevant information from large volumes of data and present that information in a better coherent manner, making the process of identifying high-risk transactions even easier in the fight against financial crime.

Machine learning enables superior data analytics, which can accurately flag anomalous behaviour. The process inefficiencies in AML alert management can be reduced significantly as AI can effectively automate repetitive tasks, saving a lot of man-hours for financial institutions and eliminating alert backlogs. With advanced machine learning, alerts can be grouped based on risk levels to dedicate more time and talent to those that matter. While AI cannot replace human judgment in the AML compliance process, it can assist humans with predictions, recommendations and powerful analytics, enabling faster and more accurate decision-making.

Comprehensive risk coverage with Tookitaki

Tookitaki is a pioneer in the fight against financial crime, leveraging a unique and innovative approach that transcends traditional solutions. The company's two distinct platforms: the 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 our 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 compliance programs remain cutting-edge.

Tookitaki AMLS and AFC Ecosystem

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.

Our solution has been proven to be highly accurate in identifying high-risk transactions. For more details of our AMLS solution and its ability to identify various money laundering techniques, please contact us.

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18 Dec 2025
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Beyond the Ratings: What FATF’s December 2025 Review Means for Malaysia’s AML Playbook

When the Financial Action Task Force publishes a Mutual Evaluation Report, it is not simply assessing the existence of laws and controls. It is examining whether those measures are producing real, demonstrable outcomes across the financial system.

The FATF Mutual Evaluation Report on Malaysia, published in December 2025, sends a clear signal in this regard. Beyond the headline ratings, the evaluation focuses on how effectively money laundering and terrorist financing risks are understood, prioritised, and mitigated in practice.

For banks, fintechs, and compliance teams operating in Malaysia, the real value of the report lies in these signals. They indicate where supervisory scrutiny is likely to intensify and where institutions are expected to demonstrate stronger alignment between risk understanding and operational controls.

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What a FATF Mutual Evaluation Is Really Testing

A FATF Mutual Evaluation assesses two interconnected dimensions.

The first is technical compliance, which looks at whether the legal and institutional framework aligns with FATF Recommendations.

The second, and increasingly decisive, dimension is effectiveness. This examines whether authorities and reporting entities are achieving intended outcomes, including timely detection, meaningful disruption of illicit financial activity, and effective use of financial intelligence.

In recent evaluation cycles, FATF has made it clear that strong frameworks alone are insufficient. Supervisors are looking for evidence that risks are properly understood and that controls are proportionate, targeted, and working as intended. Malaysia’s December 2025 evaluation reflects this emphasis throughout.

Why Malaysia’s Evaluation Carries Regional Significance

Malaysia plays a central role in Southeast Asia’s financial system. It supports significant volumes of cross-border trade, remittance flows, and correspondent banking activity, alongside a rapidly growing digital payments and fintech ecosystem.

This positioning increases exposure to complex and evolving money laundering risks. FATF’s evaluation recognises Malaysia’s progress in strengthening its framework, while also highlighting the need for continued focus on risk-based implementation as financial crime becomes more cross-border, more technology-driven, and more fragmented.

For financial institutions, this reinforces the expectation that controls must evolve alongside the risk landscape, not lag behind it.

Key Signals Emerging from the December 2025 Evaluation

Effectiveness Takes Precedence Over Formal Compliance

One of the strongest signals from the evaluation is the emphasis on demonstrable effectiveness.

Institutions are expected to show that:

  • Higher-risk activities are identified and prioritised
  • Detection mechanisms are capable of identifying complex and layered activity
  • Alerts, investigations, and reporting are aligned with real risk exposure
  • Financial intelligence leads to meaningful outcomes

Controls that exist but do not clearly contribute to these outcomes are unlikely to meet supervisory expectations.

Risk Understanding Must Drive Control Design

The evaluation reinforces that a risk-based approach must extend beyond documentation and enterprise risk assessments.

Financial institutions are expected to:

  • Clearly articulate their understanding of inherent and residual risks
  • Translate that understanding into targeted monitoring scenarios
  • Adjust controls as new products, delivery channels, and typologies emerge

Generic or static monitoring frameworks risk being viewed as insufficiently aligned with actual exposure.

Ongoing Focus on Cross-Border and Predicate Offence Risks

Consistent with Malaysia’s role as a regional financial hub, the evaluation places continued emphasis on cross-border risks.

These include exposure to:

  • Trade-based money laundering
  • Proceeds linked to organised crime and corruption
  • Cross-border remittances and correspondent banking relationships

FATF’s focus here signals that institutions must demonstrate not just transaction monitoring coverage, but the ability to interpret cross-border activity in context and identify suspicious patterns that span multiple channels.

Expanding Attention on Non-Bank and Digital Channels

While banks remain central to Malaysia’s AML framework, the evaluation highlights increasing supervisory attention on:

  • Payment institutions
  • Digital platforms
  • Designated non-financial businesses and professions

As risks shift across the financial ecosystem, regulators expect banks and fintechs to understand how their exposures interact with activity outside traditional banking channels.

Practical Implications for Malaysian Financial Institutions

For compliance teams, the December 2025 evaluation translates into several operational realities.

Supervisory Engagement Will Be More Outcome-Focused

Regulators are likely to probe:

  • Whether monitoring scenarios reflect current risk assessments
  • How detection logic has evolved over time
  • What evidence demonstrates that controls are effective

Institutions that cannot clearly explain how their controls address specific risks may face increased scrutiny.

Alert Volumes Will Be Scrutinised for Quality

High alert volumes are no longer viewed as evidence of strong controls.

Supervisors are increasingly focused on:

  • The relevance of alerts generated
  • The quality of investigations
  • The timeliness and usefulness of suspicious transaction reporting

This places pressure on institutions to improve signal quality while managing operational efficiency.

Static Monitoring Frameworks Will Be Challenged

The pace at which money laundering typologies evolve continues to accelerate.

Institutions that rely on:

  • Infrequent scenario reviews
  • Manual rule tuning
  • Disconnected monitoring systems

may struggle to demonstrate timely adaptation to emerging risks highlighted through national risk assessments or supervisory feedback.

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Common Execution Gaps Highlighted Through FATF Evaluations

Across jurisdictions, FATF evaluations frequently expose similar challenges.

Fragmented Monitoring Approaches

Siloed AML and fraud systems limit the ability to see end-to-end money flows and behavioural patterns.

Slow Adaptation to Emerging Typologies

Scenario libraries can lag behind real-world risk evolution, particularly without access to shared intelligence.

Operational Strain from False Positives

Excessive alert volumes reduce investigator effectiveness and dilute regulatory reporting quality.

Explainability and Governance Limitations

Institutions must be able to explain why controls behave as they do. Opaque or poorly governed models raise supervisory concerns.

What FATF Is Signalling About the Next Phase

While not always stated explicitly, the evaluation reflects expectations that institutions will continue to mature their AML capabilities.

Supervisors are looking for evidence of:

  • Continuous improvement
  • Learning over time
  • Strong governance over model changes
  • Clear auditability and explainability

This represents a shift from compliance as a static obligation to compliance as an evolving capability.

Translating Supervisory Expectations into Practice

To meet these expectations, many institutions are adopting modern AML approaches built around scenario-led detection, continuous refinement, and strong governance.

Such approaches enable compliance teams to:

  • Respond more quickly to emerging risks
  • Improve detection quality while managing noise
  • Maintain transparency and regulatory confidence

Platforms that combine shared intelligence, explainable analytics, and unified monitoring across AML and fraud domains align closely with the direction signalled by recent FATF evaluations. Solutions such as Tookitaki’s FinCense illustrate how technology can support these outcomes while maintaining auditability and supervisory trust.

From Compliance to Confidence

The FATF Mutual Evaluation of Malaysia should be viewed as more than a formal assessment. It is a forward-looking signal.

Institutions that treat it purely as a compliance exercise may meet minimum standards. Those that use it as a reference point for strengthening risk understanding and control effectiveness are better positioned for sustained supervisory confidence.

Final Reflection

FATF evaluations increasingly focus on whether systems work in practice, not just whether they exist.

For Malaysian banks and fintechs, the December 2025 review reinforces a clear message. The institutions best prepared for the next supervisory cycle will be those that can demonstrate strong risk understanding, effective controls, and the ability to adapt as threats evolve.

Beyond the Ratings: What FATF’s December 2025 Review Means for Malaysia’s AML Playbook
Blogs
16 Dec 2025
6 min
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RBNZ vs ASB: Why New Zealand’s AML Expectations Just Changed

In December 2025, the Reserve Bank of New Zealand sent one of its clearest signals yet to the financial sector. By filing civil proceedings against ASB Bank for breaches of the AML/CFT Act, the regulator made it clear that compliance in name alone is no longer sufficient. What matters now is whether anti-money laundering controls actually work in practice.

This was not a case about proven money laundering or terrorism financing. It was about operational effectiveness, timeliness, and accountability. For banks and financial institutions across New Zealand, that distinction is significant.

The action marks a turning point in how AML compliance will be assessed going forward. It reflects a shift from reviewing policies and frameworks to testing whether institutions can demonstrate real-world outcomes under scrutiny.

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What Happened and Why It Matters

The Reserve Bank’s filing outlines multiple failures by ASB to meet core obligations under the AML/CFT Act. These included shortcomings in maintaining an effective AML programme, carrying out ongoing customer due diligence, applying enhanced due diligence when required, and reporting suspicious activity within mandated timeframes.

ASB admitted liability across all causes of action and cooperated with the regulator. The Reserve Bank also clarified that it was not alleging ASB knowingly facilitated money laundering or terrorism financing.

This clarification is important. The case is not about intent or criminal involvement. It is about whether an institution’s AML framework operated effectively and consistently over time.

For the wider market, this is a regulatory signal rather than an isolated enforcement action.

What the Reserve Bank Is Really Signalling

Read carefully, the Reserve Bank’s message goes beyond one bank. It reflects a broader recalibration of supervisory expectations.

First, AML effectiveness is now central. Regulators are no longer satisfied with documented programmes alone. Institutions must show that controls detect risk, escalate appropriately, and lead to timely action.

Second, speed matters. Delays in suspicious transaction reporting, extended remediation timelines, and slow responses to emerging risks are viewed as material failures, not operational inconveniences.

Third, governance and accountability are under the spotlight. AML effectiveness is not just a technology issue. It reflects resourcing decisions, prioritisation, escalation pathways, and senior oversight.

This mirrors developments in other comparable jurisdictions, including Australia, Singapore, and the United Kingdom, where regulators are increasingly outcome-focused.

Why This Is a Critical Moment for New Zealand’s Financial System

New Zealand’s AML regime has matured significantly over the past decade. Financial institutions have invested heavily in frameworks, teams, and tools. Yet the RBNZ action highlights a persistent gap between programme design and day-to-day execution.

This matters for several reasons.

Public confidence in the financial system depends not only on preventing crime, but on the belief that institutions can detect and respond to risk quickly and effectively.

From an international perspective, New Zealand’s reputation as a well-regulated financial centre supports correspondent banking relationships and cross-border trust. Supervisory actions like this are closely observed beyond domestic borders.

For compliance teams, the message is clear. Supervisory reviews will increasingly test how AML frameworks perform under real-world conditions, not how well they are documented.

Common AML Gaps Brought to Light

While the specifics of each institution differ, the issues raised by the Reserve Bank are widely recognised across the industry.

One common challenge is fragmented visibility. Customer risk data, transaction monitoring outputs, and historical alerts often sit in separate systems. This makes it difficult to build a unified view of risk or spot patterns over time.

Another challenge is static monitoring logic. Rule-based thresholds that are rarely reviewed struggle to keep pace with evolving typologies, particularly in an environment shaped by real-time payments and digital channels.

Ongoing customer due diligence also remains difficult to operationalise at scale. While onboarding checks are often robust, keeping customer risk profiles current requires continuous recalibration based on behaviour, exposure, and external intelligence.

Finally, reporting delays are frequently driven by workflow inefficiencies. Manual reviews, alert backlogs, and inconsistent escalation criteria can all slow the path from detection to reporting.

Individually, these issues may appear manageable. Together, they undermine AML effectiveness.

Why Traditional AML Models Are Under Strain

Many of these gaps stem from legacy AML operating models.

Traditional architectures rely heavily on static rules, manual investigations, and institution-specific intelligence. This approach struggles in an environment where financial crime is increasingly fast-moving, cross-border, and digitally enabled.

Compliance teams face persistent pressure. Alert volumes remain high, false positives consume investigator capacity, and regulatory expectations continue to rise. When resources are stretched, timeliness becomes harder to maintain.

Explainability is another challenge. Regulators expect institutions to articulate why decisions were made, not just that actions occurred. Systems that operate as black boxes make this difficult.

The result is a growing disconnect between regulatory expectations and operational reality.

The Shift Toward Effectiveness-Led AML

The RBNZ action reflects a broader move toward effectiveness-led AML supervision.

Under this approach, success is measured by outcomes rather than intent. Regulators are asking:

  • Are risks identified early or only after escalation?
  • Are enhanced due diligence triggers applied consistently?
  • Are suspicious activities reported promptly and with sufficient context?
  • Can institutions clearly explain and evidence their decisions?

Answering these questions requires more than incremental improvements. It requires a rethinking of how AML intelligence is sourced, applied, and validated.

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Rethinking AML for the New Zealand Context

Modernising AML does not mean abandoning regulatory principles. It means strengthening how those principles are executed.

One important shift is toward scenario-driven detection. Instead of relying solely on generic thresholds, institutions increasingly use typologies grounded in real-world crime patterns. This aligns monitoring logic more closely with how financial crime actually occurs.

Another shift is toward continuous risk recalibration. Customer risk is not static. Systems that update risk profiles dynamically support more effective ongoing due diligence and reduce downstream escalation issues.

Collaboration also plays a growing role. Financial crime does not respect institutional boundaries. Access to shared intelligence helps institutions stay ahead of emerging threats rather than reacting in isolation.

Finally, transparency matters. Regulators expect clear, auditable logic that explains how risks are assessed and decisions are made.

Where Technology Can Support Better Outcomes

Technology alone does not solve AML challenges, but the right architecture can materially improve effectiveness.

Modern AML platforms increasingly support end-to-end workflows, covering onboarding, screening, transaction monitoring, risk scoring, investigation, and reporting within a connected environment.

Advanced analytics and machine learning can help reduce false positives while improving detection quality, when applied carefully and transparently.

Equally important is the ability to incorporate new intelligence quickly. Systems that can ingest updated typologies without lengthy redevelopment cycles are better suited to evolving risk landscapes.

How Tookitaki Supports This Evolution

Within this shifting environment, Tookitaki supports institutions as they move toward more effective AML outcomes.

FinCense, Tookitaki’s end-to-end compliance platform, is designed to support the full AML lifecycle, from real-time onboarding and screening to transaction monitoring, dynamic risk scoring, investigation, and reporting.

A distinguishing element is its connection to the AFC Ecosystem. This is a collaborative intelligence network where compliance professionals contribute, validate, and refine real-world scenarios based on emerging risks. These scenarios are continuously updated, allowing institutions to benefit from collective insights rather than relying solely on internal discovery.

For New Zealand institutions, this approach supports regulatory priorities around effectiveness, timeliness, and explainability. It strengthens detection quality while maintaining transparency and governance.

Importantly, technology is positioned as an enabler of better outcomes, not a substitute for oversight or accountability.

What Compliance Leaders in New Zealand Should Be Asking Now

In light of the RBNZ action, there are several questions worth asking internally.

  • Can we evidence the effectiveness of our AML controls, not just their existence?
  • How quickly do alerts move from detection to suspicious transaction reporting?
  • Are enhanced due diligence triggers dynamic or static?
  • Do we regularly test monitoring logic against emerging typologies?
  • Could we confidently explain our AML decisions to the regulator tomorrow?

These questions are not about fault-finding. They are about readiness.

Looking Ahead

The Reserve Bank’s action against ASB marks a clear shift in New Zealand’s AML supervisory landscape. Effectiveness, timeliness, and accountability are now firmly in focus.

For financial institutions, this is both a challenge and an opportunity. Those that proactively strengthen their AML operating models will be better positioned to meet regulatory expectations and build long-term trust.

Ultimately, the lesson extends beyond one case. AML compliance in New Zealand is entering a new phase, one where outcomes matter as much as intent. Institutions that adapt early will define the next standard for financial crime prevention in the market.

RBNZ vs ASB: Why New Zealand’s AML Expectations Just Changed
Blogs
12 Dec 2025
7 min
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AFASA Explained: What the Philippines’ New Anti-Scam Law Really Means for Banks, Fintechs, and Consumers

If there is one thing everyone in the financial industry felt in the last few years, it was the speed at which scams evolved. Fraudsters became smarter, attacks became faster, and stolen funds moved through dozens of accounts in seconds. Consumers were losing life savings. Banks and fintechs were overwhelmed. And regulators had to act.

This is the backdrop behind the Anti-Financial Account Scamming Act (AFASA), Republic Act No. 12010 — the Philippines’ most robust anti-scam law to date. AFASA reshapes how financial institutions detect fraud, protect accounts, coordinate with one another, and respond to disputes.

But while many have written about the law, most explanations feel overly legalistic or too high-level. What institutions really need is a practical, human-friendly breakdown of what AFASA truly means in day-to-day operations.

This blog does exactly that.

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What Is AFASA? A Simple Explanation

AFASA exists for a clear purpose: to protect consumers from rapidly evolving digital fraud. The law recognises that as more Filipinos use e-wallets, online banking, and instant payments, scammers have gained more opportunities to exploit vulnerabilities.

Under AFASA, the term financial account is broad. It includes:

  • Bank deposit accounts
  • Credit card and investment accounts
  • E-wallets
  • Any account used to access financial products and services

The law focuses on three main categories of offences:

1. Money Muling

This covers the buying, selling, renting, lending, recruiting, or using of financial accounts to receive or move illicit funds. Many young people and jobseekers were unknowingly lured into mule networks — something AFASA squarely targets.

2. Social Engineering Schemes

From phishing to impersonation, scammers have mastered psychological manipulation. AFASA penalises the use of deception to obtain sensitive information or access accounts.

3. Digital Fraud and Account Tampering

This includes unauthorised transfers, synthetic identities, hacking incidents, and scams executed through electronic communication channels.

In short: AFASA criminalises both the scammer and the infrastructure used for the scam — the accounts, the networks, and the people recruited into them.

Why AFASA Became Necessary

Scams in the Philippines reached a point where traditional fraud rules, old operational processes, and siloed detection systems were not enough.

Scam Trend 1: Social engineering became hyper-personal

Fraudsters learned to sound like bank agents, government officers, delivery riders, HR recruiters — even loved ones. OTP harvesting and remote access scams became common.

Scam Trend 2: Real-time payments made fraud instant

InstaPay and other instant channels made moving money convenient — but also made stolen funds disappear before anyone could react.

Scam Trend 3: Mule networks became organised

Criminal groups built structured pipelines of mule accounts, often recruiting vulnerable populations such as students, OFWs, and low-income households.

Scam Trend 4: E-wallet adoption outpaced awareness

A fast-growing digital economy meant millions of first-time digital users were exposed to sophisticated scams they were not prepared for.

AFASA was designed to break this cycle and create a safer digital financial environment.

New Responsibilities for Banks and Fintechs Under AFASA

AFASA introduces significant changes to how institutions must protect accounts. It is not just a compliance exercise — it demands real operational transformation.

These responsibilities are further detailed in new BSP circulars that accompany the law.

1. Stronger IT Risk Controls

Financial institutions must now implement advanced fraud and cybersecurity controls such as:

  • Device fingerprinting
  • Geolocation monitoring
  • Bot detection
  • Blacklist screening for devices, merchants, and IPs

These measures allow institutions to understand who is accessing accounts, how, and from where — giving them the tools to detect anomalies before fraud occurs.

2. Mandatory Fraud Management Systems (FMS)

Both financial institutions and clearing switch operators (including InstaPay and PESONet) must operate real-time systems that:

  • Flag suspicious activity
  • Block disputed or high-risk transactions
  • Detect behavioural anomalies

This ensures that fraud monitoring is consistent across the payment ecosystem — not just within individual institutions.

3. Prohibition on unsolicited clickable links

Institutions can no longer send clickable links or QR codes to customers unless explicitly initiated by the customer. This directly tackles phishing attacks that relied on spoofed messages.

4. Continuous customer awareness

Banks and fintechs must actively educate customers about:

  • Cyber hygiene
  • Secure account practices
  • Fraud patterns and red flags
  • How to report incidents quickly

Customer education is no longer optional — it is a formally recognised part of fraud prevention.

5. Shared accountability framework

AFASA moves away from the old “blame the victim” mentality. Fraud prevention is now a shared responsibility across:

  • Financial institutions
  • Account owners
  • Third-party service providers

This model recognises that no single party can combat fraud alone.

The Heart of AFASA: Temporary Holding of Funds & Coordinated Verification

Among all the changes introduced by AFASA, this is the one that represents a true paradigm shift.

Previously, once stolen funds were transferred out, recovery was almost impossible. Banks had little authority to stop or hold the movement of funds.

AFASA changes that.

Temporary Holding of Funds

Financial institutions now have the authority — and obligation — to temporarily hold disputed funds for up to 30 days. This includes both the initial hold and any permitted extension. The purpose is simple:
freeze the money before it disappears.

Triggers for Temporary Holding

A hold can be initiated through:

  • A victim’s complaint
  • A suspicious transaction flagged by the institution’s FMS
  • A request from another financial institution

This ensures that action can be taken proactively or reactively depending on the scenario.

Coordinated Verification Process

Once funds are held, institutions must immediately begin a coordinated process that involves:

  • The originating institution
  • Receiving institutions
  • Clearing entities
  • The account owners involved

This process validates whether the transaction was legitimate or fraudulent. It creates a formal, structured, and time-bound mechanism for investigation.

Detailed Transaction Logs Are Now Mandatory

Institutions must maintain comprehensive transaction logs — including device information, authentication events, IP addresses, timestamps, password changes, and more. Logs must be retained for at least five years.

This gives investigators the ability to reconstruct transactions and understand the full context of a disputed transfer.

An Industry-Wide Protocol Must Be Built

AFASA requires the entire industry to co-develop a unified protocol for handling disputed funds and verification. This ensures consistency, promotes collaboration, and reduces delays during investigations.

This is one of the most forward-thinking aspects of the law — and one that will significantly raise the standard of scam response in the country.

BSP’s Expanded Powers Through CAPO

AFASA also strengthens regulatory oversight.

BSP’s Consumer Account Protection Office (CAPO) now has the authority to:

  • Conduct inquiries into financial accounts suspected of involvement in fraud
  • Access financial account information required to investigate prohibited acts
  • Coordinate with law enforcement agencies

Crucially, during these inquiries, bank secrecy laws and the Data Privacy Act do not apply.

This is a major shift that reflects the urgency of combating digital fraud.

Crucially, during these inquiries, bank secrecy laws and the Data Privacy Act do not apply.

This is a major shift that reflects the urgency of combating digital fraud.

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Penalties Under AFASA

AFASA imposes serious penalties to deter both scammers and enablers:

1. Criminal penalties for money muling

Anyone who knowingly participates in using, recruiting, or providing accounts for illicit transfers is liable to face imprisonment and fines.

2. Liability for failing to protect funds

Institutions may be held accountable if they fail to properly execute a temporary hold when a dispute is raised.

3. Penalties for improper holding

Institutions that hold funds without valid reason may also face sanctions.

4. Penalties for malicious reporting

Consumers or individuals who intentionally file false reports may also be punished.

5. Administrative sanctions

Financial institutions that fail to comply with AFASA requirements may be penalised by BSP.

The penalties underscore the seriousness with which the government views scam prevention.

What AFASA Means for Banks and Fintechs: The Practical Reality

Here’s what changes on the ground:

1. Fraud detection becomes real-time — not after-the-fact

Institutions need modern systems that can flag abnormal behaviour within seconds.

2. Dispute response becomes faster

Timeframes are tight, and institutions need streamlined internal workflows.

3. Collaboration is no longer optional

Banks, e-wallets, payment operators, and regulators must work as one system.

4. Operational pressure increases

Fraud teams must handle verification, logging, documentation, and communication under strict timelines.

5. Liability is higher

Institutions may be held responsible for lapses in protection, detection, or response.

6. Technology uplift becomes non-negotiable

Legacy systems will struggle to meet AFASA’s requirements — particularly around logging, behavioural analytics, and real-time detection.

How Tookitaki Helps Institutions Align With AFASA

AFASA sets a higher bar for fraud prevention. Tookitaki’s role as the Trust Layer to Fight Financial Crime helps institutions strengthen their AFASA readiness with intelligent, real-time, and collaborative capabilities.

1. Early detection of money mule networks

Through the AFC Ecosystem’s collective intelligence, institutions can detect mule-like patterns sooner and prevent illicit transactions before they spread across the system.

2. Real-time monitoring aligned with AFASA needs

FinCense’s advanced transaction monitoring engine flags suspicious activity instantly — helping institutions support temporary holding procedures and respond within required timelines.

3. Deep behavioural intelligence and comprehensive logs

Tookitaki provides the contextual understanding needed to trace disputed transfers, reconstruct transaction paths, and support investigative workflows.

4. Agentic AI to accelerate investigations

FinMate, the AI investigation copilot, streamlines case analysis, surfaces insights quickly, and reduces investigation workload — especially crucial when time-sensitive AFASA processes are triggered.

5. Federated learning for privacy-preserving model improvement

Institutions can enhance detection models without sharing raw data, aligning with AFASA’s broader emphasis on secure and responsible handling of financial information.

Together, these capabilities enable banks and fintechs to strengthen fraud defences, modernise their operations, and protect financial accounts with confidence.

Looking Ahead: AFASA’s Long-Term Impact

AFASA is not a one-time regulatory update — it is a structural shift in how the Philippine financial ecosystem handles scams.

Expect to see:

  • More real-time fraud rules and guidance
  • Industry-wide technical standards for dispute management
  • Higher expectations for digital onboarding and authentication
  • Increased coordination between banks, fintechs, and regulators
  • Greater focus on intelligence-sharing and network-level detection

Most importantly, AFASA lays the foundation for a safer, more trusted digital economy — one where consumers have confidence that institutions and regulators can protect them from fast-evolving threats.

Conclusion

AFASA represents a turning point in the Philippines’ fight against financial scams. It transforms how institutions detect fraud, protect accounts, collaborate with others, and support customers. For banks and fintechs, the message is clear: the era of passive fraud response is over.

The institutions that will thrive under AFASA are those that embrace real-time intelligence, strengthen operational resilience, and adopt technology that enables them to stay ahead of criminal innovation.

The Philippines has taken a bold step toward a safer financial system — and now, it’s time for the industry to match that ambition.

AFASA Explained: What the Philippines’ New Anti-Scam Law Really Means for Banks, Fintechs, and Consumers