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How to Address Present-day Sanctions Screening Pain Points with AI

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Tookitaki
25 March 2021
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8 min

Sanctions risk of financial institutions is evolving in line with the global social, economic and political changes. As seen in recent news, governments across the globe are increasingly relying on sanctions as an important measure for political foreign policy. They, as well as international organizations, implement preventive and corrective measures to prohibit illicit activity and control undesirable actions by certain high-risk countries, persons or groups.

For financial institutions, adhering to multiple sanction lists from various issuing countries and agencies is becoming a troublesome AML/CFT compliance task with process inefficiencies abound and risk heightened. What many of them lack are a sustainable screening framework and new-age screening tools. In this article, we would discuss the present-day challenges related to sanctions screening and a modern approach to address these challenges and build sustainable and scalable screening programs.

Why Sanctions Screening is Important for Financial Institutions

While all businesses in all sectors are mandated to comply with sanctions screening requirements, financial institutions, who work as channels of financial transactions, historically face increased scrutiny from regulators and enforcement actions have been more prominent on them. Therefore, financial institutions should have adequate controls in place to screen individuals and entities on a regular basis. They need to create a database of sanctioned individuals and entities and update them very frequently. In addition, they need to have tools in place to match their clients (both individuals and entities) with sanction lists, identify and stop unlawful activities, and report the same to relevant authorities. Failure in having adequate sanction controls and violation of sanctions would lead to enforcement actions including hefty fines. Penalties by the US Office of Foreign Assets Control (OFAC) reached a record US$1.3 billion in 2019.

What Makes Sanctions Screening Painful

The way how sanctions work is not uniform across the globe. It differs from country to country. There are sanction lists produced by countries as well as international bodies such as the United Nations and European Union. However, in a sanctions screening program, financial institutions need to compile information from various sanction lists and periodically update them. Further, they need to be watchful of the changes in sanctions programs to avoid risks. For example, OFAC updated 22 and 7 sanctions programs in 2020 and 2021, respectively, according to present official data.

The following are some of the key challenges of financial institutions with respect to sanctions screening.

  • Multiple sanctioning bodies: Financial institutions may have to refer to lists produced by multiple sanctioning bodies depending on the territory of operation, currencies involved, the nature of business and international agreements.
  • Daily updates: Financial institutions need to be watchful of any updates to their following watchlists on a daily basis. New entities are added to and removed from sanctions lists very frequently.
  • Understanding sanctions: In line with global political and economic developments, the definition and scope of sanctions is broadening, and they are interpreted in different ways. Lack of clarity on sanctions is making it very difficult for financial institutions to effectively identify and manage risk. For example, customers who are not on a sanctions list but have some connection with a sanctioned individual or entity can also pose significant risk.
  • Extended screening: At present, it’s not just customers that a financial institution should screen. They should have adequate controls in place to screen associates of clients, beneficial owners, and extended supply chains especially in geographies that have known links to sanctioned countries.

Technological Challenges in Sanctions Screening

Organizations are required to screen both their new and existing against multiple sanctions lists. Financial institutions either maintain in-house watchlists or subscribe to those provided by third parties. Subsequently, they check and match their customer and third-party databases in real-time or periodically with the help of certain tools for possible sanctions alerts. Possible matches are investigated and confirmed customers or third parties are blacklisted and reported. The objective of a sanctions screening program is not just detecting sanctioned customers and preventing them from doing transactions but it is also to avoid bad experiences to legitimate customers.

Recent changes in the sanctions space and the high volume of entries to be screened prompted financial institutions to move from rudimentary name matching models to rules-based screening tools. However, the volume of alerts generated for screening matches remained high with a false positive rate of more than 95%. These false positives are a drain on productivity as they take a lot of time and resources to remediate. This can lead to huge alert backlogs, high operational costs, poor customer experience and loss of business. With ineffective tools, there are also dangers of false negatives where designated entities slip through the compliance net, resulting in hefty fines.

The Way Machine Learning Augments Sanctions Screening Efficiency 

The primary reasons why existing screening tools remain inefficient and produce large false positives are:

  • Inability to merge relevant data from multiple systems into a standardised structure
  • limited consideration for secondary information such as date of birth, occupation, address and bank identification codes.
  • Inadequate support for data in non-Latin characters
  • Ineffective handling of name ordering, mis-spelling qualifiers, titles, prefix and suffix
  • Lack of evidence-based alert review mechanism

In order to be effective, the technology used for sanctions screening should be easy to use and offer configurable risk-based settings, so that financial institutions can avoid over-screening and adjust screening criteria to match their risk appetite. By using machine learning, financial institutions will be capable of doing precision tuning their screening program to reflect the company’s risk exposure dealing with imprecise or inaccurate data to eliminate false positives.

As part of its award-winning Anti-Money Laundering Suite (AMLS), Tookitaki developed a Smart Screening solution leveraging advanced machine learning and Natural Language Processing (NLP) techniques. While addressing the above issues, the solution helps accurately score and distinguish a true match from a false match across names and transactions in real-time and in batch mode. In addition to screening against sanctions lists, the solution covers politically exposed persons (PEPs), adverse media and local/internal blacklist databases. The transaction screening feature triages and scores funds, goods or assets, between parties or accounts within a financial institution.

Tookitaki Smart Screening solution offers the following benefits to the customers:

1. More focus on alerts that matter

The solution offers a smart way to triage screening alerts by segregating them into three risk buckets – L1, L2 and L3 – where L3 is the highest-risk bucket. The highly accurate alert classification helps clients allocate time and experience judiciously and effectively address alert backlogs. Compliance analysts can focus on those high-risk cases (L3 and L2) that require more time to investigate and close. Meanwhile, they can close low-risk alerts (L1) with minimal investigation.

2. Better risk mitigation with reduced undetermined hits

Tookitaki solution uses NLP to process free texts and infers entity attributes like age, nationality, work-place title, alongside adverse media information, payment reference information or the stated purpose of the payment in a SWIFT message to derive vivid connection and accurately score all hits.

3. Superior screening accuracy with improved name matching

Tookitaki Smart Screening can handle typos, misspelling, nicknames, titles, prefix, suffix, qualifiers, concatenations, transliteration limitations and cultural differences for accurate hits detection.

4. Time/cost savings with faster implementation

Enabling faster go-live, the Screening solution comes with ‘out-of-box’ risk indicators across primary and secondary information of a customer for screening to accurately detect a true hit from several watchlist hits.

5. Low model maintenance costs

Too many lists with frequent updates have made screening more complex, prompting banks to introduce new rules and change thresholds. Tookitaki’s Smart Screening solution can self learn from incremental data and feedback to provide consistent performance over time.

6. Easy integration and flexible deployment

The solution has connectors to seamlessly ingest varied data points from multiple internal and external source systems and convert into a standardised format. Further, it provides API-based integration with primary screening systems, making the integration process easy, seamless and cost-effective. In addition, it offers on-premise and cloud deployment options.

7. Faster decisions with explainable outcomes

Tookitaki solution is equipped with an advanced investigation unit that provides thorough explanations for each alert and facilitates faster decision-making, reducing alerts backlog. Its actionable analytics dashboard for senior management helps monitor a bank’s sanctions risk across business segments, jurisdictions, etc. over a time period.

Recently, our AMLS solution went live within the premises of United Overseas Bank (UOB), one of the top 3 banks in Singapore, making us the first company in the APAC region to deploy a complete AI-powered AML solution in production concurrently to transaction monitoring and name/sanctions screening. By deploying AMLS, UOB could effectively create workflows for prioritizing alerts based on their risk levels to help the compliance team focus on those alerts that matter.

A complete revamp of existing sanctions compliance processes is imperative for financial institutions given that the international sanctions space is becoming more complex. It is time to embrace modern-era intelligent technology to enhance efficiency and effectiveness in AML compliance programs, establish next-gen financial crime surveillance and ensure robust risk management practices.

For more details into our Smart Screening solution, please contact us.

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Blogs
23 Dec 2025
6 min
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AML Failures Are Now Capital Risks: The Bendigo Case Proves It

When Australian regulators translate AML failures into capital penalties, it signals more than enforcement. It signals a fundamental shift in how financial crime risk is priced, governed, and punished.

The recent action against Bendigo and Adelaide Bank marks a decisive turning point in Australia’s regulatory posture. Weak anti-money laundering controls are no longer viewed as back-office compliance shortcomings. They are now being treated as prudential risks with direct balance-sheet consequences.

This is not just another enforcement headline. It is a clear warning to the entire financial sector.

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What happened at Bendigo Bank

Following an independent review, regulators identified significant and persistent deficiencies in Bendigo Bank’s financial crime control framework. What stood out was not only the severity of the gaps, but their duration.

Key weaknesses remained unresolved for more than six years, spanning from 2019 to 2025. These were not confined to a single branch, product, or customer segment. They were assessed as systemic, affecting governance, oversight, and the effectiveness of AML controls across the institution.

In response, regulators acted in coordination:

The framing matters. This was not positioned as punishment for an isolated incident. Regulators explicitly pointed to long-standing control failures and prolonged exposure to financial crime risk.

Why this is not just another AML penalty

This case stands apart from past enforcement actions for one critical reason.

Capital was used as the lever.

A capital add-on is fundamentally different from a fine or enforceable undertaking. By requiring additional capital to be held, APRA is signalling that deficiencies in financial crime controls materially increase an institution’s operational risk profile.

Until those risks are demonstrably addressed, they must be absorbed on the balance sheet.

The consequences are tangible:

  • Reduced capital flexibility
  • Pressure on return on equity
  • Constraints on growth and strategic initiatives
  • Prolonged supervisory scrutiny

The underlying message is unambiguous.
AML weaknesses now come with a measurable capital cost.

AML failures are now viewed as prudential risk

This case also signals a shift in how regulators define the problem.

The findings were not limited to missed alerts or procedural non-compliance. Regulators highlighted broader, structural weaknesses, including:

  • Ineffective transaction monitoring
  • Inadequate customer risk assessment and limited beneficial ownership visibility
  • Weak escalation from branch-level operations
  • Fragmented oversight between frontline teams and central compliance
  • Governance gaps that allowed weaknesses to persist undetected

These are not execution errors.
They are risk management failures.

This explains the joint involvement of APRA and AUSTRAC. Financial crime controls are now firmly embedded within expectations around enterprise risk management, institutional resilience, and safety and soundness.

Six years of exposure is a governance failure

Perhaps the most troubling aspect of the Bendigo case is duration.

When material AML weaknesses persist across multiple years, audit cycles, and regulatory engagements, the issue is no longer technology alone. It becomes a question of:

  • Risk culture
  • Accountability
  • Board oversight
  • Management prioritisation

Australian regulators have made it increasingly clear that financial crime risk cannot be fully delegated to second-line functions. Boards and senior executives are expected to understand AML risk in operational and strategic terms, not just policy language.

This reflects a broader global trend. Prolonged AML failures are now widely treated as indicators of governance weakness, not just compliance gaps.

Why joint APRA–AUSTRAC action matters

The coordinated response itself is a signal.

APRA’s mandate centres on institutional stability and resilience. AUSTRAC’s mandate focuses on financial intelligence and the disruption of serious and organised crime. When both regulators act together, it reflects a shared conclusion: financial crime control failures have crossed into systemic risk territory.

This convergence is becoming increasingly common internationally. Regulators are no longer willing to separate AML compliance from prudential supervision when weaknesses are persistent, enterprise-wide, and inadequately addressed.

For Australian institutions, this means AML maturity is now inseparable from broader risk and capital considerations.

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The hidden cost of delayed remediation

The Bendigo case also exposes an uncomfortable truth.

Delayed remediation is expensive.

When control weaknesses are allowed to persist, institutions often face:

  • Large-scale, multi-year transformation programs
  • Significant technology modernisation costs
  • Extensive retraining and cultural change initiatives
  • Capital locked up until regulators are satisfied
  • Sustained supervisory and reputational pressure

What could have been incremental improvements years earlier can escalate into a full institutional overhaul when left unresolved.

In this context, capital add-ons act not just as penalties, but as forcing mechanisms to ensure sustained executive and board-level focus.

What this means for Australian banks and fintechs

This case should prompt serious reflection across the sector.

Several lessons are already clear:

  • Static, rules-based monitoring struggles to keep pace with evolving typologies
  • Siloed fraud and AML functions miss cross-channel risk patterns
  • Documented controls are insufficient if they are not effective in practice
  • Regulators are increasingly focused on outcomes, not frameworks

Importantly, this applies beyond major banks. Regional institutions, mutuals, and digitally expanding fintechs are firmly within scope. Scale is no longer a mitigating factor.

Where technology must step in before capital is at risk

Cases like Bendigo expose a widening gap between regulatory expectations and how financial crime controls are still implemented in many institutions. Legacy systems, fragmented monitoring, and periodic reviews are increasingly misaligned with the realities of modern financial crime.

At Tookitaki, financial crime prevention is approached as a continuous intelligence challenge, rather than a static compliance obligation. The emphasis is on adaptability, explainability, and real-time risk visibility, enabling institutions to surface emerging threats before they escalate into supervisory or capital issues.

By combining real-time transaction monitoring with collaborative, scenario-driven intelligence, institutions can reduce blind spots and demonstrate sustained control effectiveness. In an environment where regulators are increasingly focused on whether controls actually work, this ability is becoming central to maintaining regulatory confidence.

Many of the weaknesses highlighted in this case mirror patterns seen across recent regulatory reviews. Institutions that address them early are far better positioned to avoid capital shocks later.

From compliance posture to risk ownership

The clearest takeaway from the Bendigo case is the need for a mindset shift.

Financial crime risk can no longer be treated as a downstream compliance concern. It must be owned as a core institutional risk, alongside credit, liquidity, and operational resilience.

Institutions that proactively modernise their AML capabilities and strengthen governance will be better placed to avoid prolonged remediation, capital constraints, and reputational damage.

A turning point for trust and resilience

The action against Bendigo Bank is not about one institution. It reflects a broader regulatory recalibration.

AML failures are now capital risks.

In Australia’s evolving regulatory landscape, AML is no longer a cost of doing business.
It is a measure of institutional resilience, governance strength, and trustworthiness.

Those that adapt early will navigate this shift with confidence. Those that do not may find that the cost of getting AML wrong is far higher than expected.

AML Failures Are Now Capital Risks: The Bendigo Case Proves It
Blogs
18 Dec 2025
6 min
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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
read

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