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AML Detection: Securing Malaysia's Financial Ecosystem with Tookitaki

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Tookitaki
01 June 2023
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7 min

In an increasingly interconnected financial landscape, the spectre of money laundering looms large, casting a menacing shadow over economies worldwide. Malaysia, a thriving financial hub in Southeast Asia, is no exception to this pressing concern. Money laundering, a deceptively intricate process where illicitly obtained funds are masked to appear legitimate, poses an immense threat to the integrity of Malaysia's financial ecosystem. The implications of this illicit activity extend beyond pure financial loss, eroding public trust and destabilizing the nation's economic fabric.

Being at the crossroads of major trading routes, Malaysia is particularly susceptible to such financial crimes. The clandestine nature of money laundering disrupts economic stability and undermines the nation's efforts to maintain a transparent and robust financial system. It indirectly promotes crime by facilitating corrupt practices, smuggling, and even terrorist financing.

Against this backdrop, it becomes abundantly clear that effective detection and prevention mechanisms are crucial to combat money laundering. That's where Anti-Money Laundering (AML) detection technology comes into play. AML detection technology serves as a bulwark against these nefarious activities, systematically identifying suspicious transactions and alerting relevant authorities to possible money laundering attempts.

Harnessing the power of artificial intelligence, machine learning, and other cutting-edge technologies, AML detection systems equip financial institutions with the tools necessary to identify, track, and report suspicious activities. These technologies play a vital role in safeguarding the financial ecosystem, bolstering risk management strategies, and ensuring regulatory compliance.

As the battle against money laundering intensifies, the importance of advanced, efficient, and robust AML detection systems becomes undeniably paramount. One such transformative solution emerging in this arena is offered by Tookitaki, a pioneer in the space, revolutionizing how financial institutions approach AML compliance and detection. Stay tuned as we delve deeper into how Tookitaki's AML technology is redefining AML detection and bolstering Malaysia's defence against financial crime.

The Current State of AML Detection

Traditional Methods of AML Detection

Traditionally, AML detection has revolved around a set of prescribed rules and manual processes. These rule-based systems are where transactional and non-transactional activities are monitored based on predefined rules or patterns. For example, any single transaction over a certain amount, say $10,000, could trigger an alert for further investigation. AML processes typically include:

  • Know Your Customer (KYC) Checks: KYC processes are aimed at verifying the identity of clients, understanding their financial activities, and assessing potential risks of illegal intentions.
  • Customer Due Diligence (CDD) and Enhanced Due Diligence (EDD): CDD is a basic level of fact-checking that involves confirming the customer’s identity and assessing their risk levels. EDD is an additional layer of scrutiny applied to higher-risk customers.
  • Transaction Monitoring: This involves monitoring customer transactions on an ongoing basis to identify suspicious activity. 

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Limitations of Traditional AML Detection Methods

While these methods have been foundational in AML efforts, they come with their own set of limitations:

  • High False Positive Rates: Rule-based systems tend to generate a large number of false alerts, leading to wasted resources in chasing down these false leads.
  • Limited Adaptability: Traditional systems lack the flexibility to adapt to new patterns of money laundering, leaving institutions vulnerable to innovative laundering techniques.
  • Resource Intensive: The manual processes involved in traditional AML detection methods are time-consuming, labour-intensive, and prone to human error.
  • Lack of Comprehensive Risk Coverage: Due to their static nature, these systems often fail to cover all possible risk scenarios, leading to gaps in detection.

The Need for a New Approach

Given the limitations of traditional AML detection methods, a more sophisticated, adaptive, and comprehensive approach is needed to tackle the ever-evolving money laundering landscape effectively. This calls for an innovative solution that reduces the number of false positives, identifies hidden patterns of suspicious activities, ensures comprehensive risk coverage, and offers swift adaptability to new typologies of financial crime. 

That's precisely where Tookitaki's cutting-edge AML detection technology, backed by artificial intelligence and machine learning, enters the fray, addressing these limitations and revolutionizing the AML landscape, particularly in Malaysia's dynamic financial ecosystem.

Introduction to Tookitaki

Tookitaki: Redefining the Landscape of AML Detection

Tookitaki, a trailblazer in the world of Regtech, is transforming the battle against financial crime by leveraging artificial intelligence and machine learning. The company has made strides in dismantling outdated, siloed AML approaches and replacing them with a groundbreaking Anti-Money Laundering Suite (AMLS) and an Anti-Financial Crime (AFC) Ecosystem.

The AMLS is an end-to-end operating system designed to modernize compliance processes, while the AFC Ecosystem represents a community of experts devoted to uncovering hidden money trails. Tookitaki's unique approach effectively uncovers suspicious activity, ensures comprehensive risk coverage, and significantly reduces false alerts by bringing these two powerhouses together. This, in turn, enhances detection accuracy and streamlines the compliance process.

How Tookitaki Stands Out

Tookitaki's technology distinguishes itself from traditional methods in a number of significant ways:

  • Advanced AI and Machine Learning: Tookitaki's solutions harness the power of AI and machine learning to detect hidden patterns and trends that would be impossible to identify with traditional rule-based systems.
  • Community-Based Approach: By uniting a community of experts through the AFC Ecosystem, Tookitaki ensures that financial institutions stay ahead of emerging threats and evolving money laundering techniques.
  • Comprehensive Risk Coverage: With its innovative AMLS, Tookitaki provides robust and complete risk coverage, leaving no room for blind spots.
  • Reduced False Alerts: Tookitaki's superior detection techniques and intelligent systems significantly reduce the number of false alerts, thereby improving efficiency and freeing up valuable resources.
  • Quick Adaptability: Owing to its machine learning capabilities, Tookitaki's system can quickly adapt to new typologies, ensuring that financial institutions are always prepared for evolving threats.

In a world where money laundering tactics are continuously evolving, Tookitaki's advanced and innovative solutions are spearheading a new age of financial crime detection and prevention, securing Malaysia's financial ecosystem and beyond.

Tookitaki's AML Detection Technology

A New Era of AML Detection

Tookitaki's AML detection technology stands as a testament to the power of artificial intelligence and machine learning in combating financial crime. At the heart of this revolutionary technology lies the Anti-Money Laundering Suite (AMLS), an advanced operating system meticulously designed to modernize compliance processes, detect suspicious activities with remarkable accuracy, and drastically reduce false alerts.

The Modules of the AMLS Platform

The AMLS platform is built around a modular design comprising several critical components that work in unison to deliver effective and efficient AML detection solutions.

  • Smart Screening: This module includes Prospect Screening, Name Screening, and Transaction Screening solutions.
  • Dynamic Risk Scoring: This module employs Prospect Risk Scoring and Customer Risk Scoring techniques to evaluate the potential risk associated with each customer.
  • Transaction Monitoring: This module monitors customer transactions, capturing suspicious activities that might otherwise slip through the cracks. Its ability to discern unusual patterns is critical in the timely detection and prevention of money laundering attempts.
  • Case Manager: This module manages flagged cases efficiently, ensuring that each suspicious activity receives the attention it warrants. It provides a systematic way to review, investigate, and report potential cases of money laundering.
AMLS modules

Enhancing Detection Accuracy, Reducing False Alerts

Tookitaki's Transaction Monitoring technology takes detection accuracy to new heights while significantly cutting down on false alerts. Its built-in sandbox environment allows for swift testing and deployment of new typologies, ensuring that the system is continually updated to detect the latest money laundering tactics.

Its advanced pattern-based detection technique also leverages real-world red flag typologies, significantly enhancing detection accuracy. An automated threshold tuning feature has reduced the manual effort involved in threshold tuning by over 70%, streamlining the detection process.

Moreover, the system has a unique ability to detect new suspicious cases that are not detected by primary systems, serving as a reliable second line of defence. As a result, this vastly reduces the number of false positives and allows investigators to focus on high-priority alerts.

Through these innovative features, Tookitaki's AML detection technology offers a highly accurate, efficient, and comprehensive solution to combat money laundering, revolutionizing AML detection in Malaysia and across the globe.

Impact of Tookitaki's Technology in Malaysia

Tookitaki's technology has delivered tremendous value to Malaysia's financial sector. The AMLS platform has significantly reduced the burden of false alerts by employing AI-driven detection techniques, allowing investigators to focus their resources on high-risk activities. Furthermore, its ability to seamlessly integrate with existing systems while offering an extra layer of protection has boosted the overall confidence in the compliance processes. Financial institutions can now trust their compliance efforts to be timely, accurate, and efficient.

The ripple effect of this technology extends beyond individual institutions to the broader financial ecosystem. As the risk of money laundering is mitigated, the reputation of Malaysia's financial sector is significantly enhanced, potentially attracting more foreign investments and fostering greater economic stability.

Tookitaki is revolutionizing the current landscape of AML detection and setting the stage for future advancements. Its AI-driven, modular approach to AML compliance has paved the way for a new era in financial security. The integration of AI and machine learning in AMLS has opened a realm of possibilities for further exploration and advancements, not only in the detection of money laundering but also in the broader sphere of financial crime prevention.

Securing the Future of AML Detection: A Recap

The significance of advanced AML detection in securing a nation's financial ecosystem cannot be overstated. As financial crime tactics evolve, our approaches to detecting and preventing them must do the same. It's here that Tookitaki has boldly stepped in, introducing a revolutionary AML detection technology that leverages the power of AI and machine learning.

With its comprehensive, modular, and AI-driven AMLS platform, Tookitaki has made significant strides in enhancing detection accuracy and reducing false alerts. Its impact on Malaysia's financial sector has been remarkable, contributing to a safer, more secure financial environment and reinforcing the nation's reputation in the global financial community.

However, the journey doesn't stop here. The future promises more advancements and improvements in AML detection technology, with Tookitaki at the forefront, continually pushing the boundaries of what is possible in the battle against financial crime. To assess the power and potential of Tookitaki's AML solutions, we invite you to experience them firsthand. Book a demo today and discover how Tookitaki can enhance your compliance processes, safeguard your operations, and contribute to a more secure financial future.


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Blogs
02 Sep 2025
5 min
read

Busted in Bangsar South: Inside Malaysia’s Largest Scam Call Centre Raid

In August 2025, Malaysian police stormed a five-storey office in Bangsar South, Kuala Lumpur, arresting more than 400 people linked to what is now called the country’s largest scam call centre operation.

The raid made headlines worldwide, not only for its scale but also because of its alleged link to Doo Group, a Singapore-based fintech that sponsors English football giant Manchester United. The case has cast a harsh spotlight on the industrial scale of financial crime in Southeast Asia and the reputational risks it poses for both financial institutions and global brands.

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Background of the Scam

The dramatic raid took place on 26 August 2025, when Malaysian authorities swept into a commercial tower in Bangsar South, a thriving business district in Kuala Lumpur. Inside, they discovered a massive call centre allegedly set up to defraud victims across multiple countries.

Over 400 individuals were arrested. Videos of employees being escorted into police vans quickly went viral, symbolising the scale and industrial nature of the operation.

Initial reports linked the call centre to Doo Group, a global financial services provider with operations across Singapore, Hong Kong, London, Sydney, and Dubai. While the company has insisted that its operations remain unaffected and that it is cooperating fully with investigators, the reputational damage was already significant.

The Bangsar South raid is part of Malaysia’s wider anti-scam campaign. By mid-2025, authorities had arrested over 11,800 suspects in similar cases, with financial losses amounting to RM 1.5 billion (USD 355 million). The Bangsar South case, however, stands out because of its size, its international profile, and its link to a company with a global brand presence.

What the Case Revealed

The raid revealed troubling insights into how financial crime networks operate in the region:

1. Industrialised Fraud

A workforce of over 400 suggests this was not a small, fly-by-night scam but a structured enterprise. Staff were reportedly trained to follow scripts, handle objections, and target victims methodically, mirroring the efficiency of legitimate customer service operations.

2. Global Targeting

Reports indicate the call centre targeted victims not just in Malaysia but also overseas, raising questions about how funds were laundered across borders. The multilingual capabilities of employees further suggest international reach.

3. Reputation at Risk

The alleged connection to Doo Group highlights how reputable financial companies can be pulled into fraud narratives. Even if not directly complicit, the association underscores how thin the line can be between legitimate fintech operations and the shadow economy.

4. Oversight Gaps

The case also points to challenges regulators face in monitoring sprawling call centre operations and cross-border financial flows. By the time raids occur, thousands of victims may already have been defrauded.

Impact on Financial Institutions and Corporates

The Bangsar South raid is not just a law enforcement victory. It is a warning signal for the financial industry.

1. Reputational Fallout

When a Manchester United sponsor is linked to scams, it is not just the company that suffers. Brand trust in fintech, sports, and banking becomes collateral damage. This raises the stakes for due diligence in sponsorships and partnerships.

2. Investor and Customer Confidence

Digital finance thrives on trust. When fintechs are tied to scandals, investors hesitate and customers second-guess their safety. The Bangsar South case risks dampening enthusiasm for fintech adoption in Malaysia and the wider region.

3. Operational Risks for Banks

For financial institutions, call centre scams translate into suspicious transaction flows, mule account proliferation, and higher compliance costs. Traditional transaction monitoring often struggles to flag layered, cross-border flows connected to scams of this scale.

4. Regional Implications

Malaysia’s crackdown shows commendable resolve, but it also exposes the country as a hub for organised scam activity. This dual image, both a problem centre and an enforcement leader, will shape how regional regulators approach financial crime.

ChatGPT Image Sep 2, 2025, 12_42_49 PM

Lessons Learned from the Scam

  1. Scale ≠ Legitimacy
    A large workforce and polished infrastructure do not guarantee a legitimate business. Regulators and partners must look beyond appearances.
  2. Due Diligence is Non-Negotiable
    Global brands and institutions need deeper checks before partnerships. A sponsorship or corporate tie-up can quickly become a reputational liability.
  3. Regulatory Vigilance Matters
    The Bangsar South raid shows what decisive enforcement looks like, but it also reveals how long such scams can operate before being stopped.
  4. Cross-Border Cooperation is Critical
    Victims were likely spread across multiple jurisdictions. Without international collaboration, enforcement remains reactive.
  5. Public Awareness is Essential
    Scam call centres thrive because victims are unaware. Public education campaigns must go hand-in-hand with enforcement.

The Role of Technology in Prevention

Conventional compliance methods, such as simple blacklist checks or static rules, are no match for scam call centres operating at an industrial scale. To counter them, financial institutions need adaptive, intelligence-driven defences.

This is where Tookitaki’s FinCense and the AFC Ecosystem come in:

  • Typology-Driven Detection
    FinCense continuously updates detection logic based on real scam scenarios contributed by 200+ global financial crime experts in the AFC Ecosystem. This means emerging call centre scam patterns can be identified faster.
  • Agentic AI
    At the heart of FinCense is an Agentic AI framework, a network of intelligent agents that not only detect suspicious activity but also explain every decision in plain language. This reduces investigation time and builds regulator confidence.
  • Federated Learning
    Through federated learning, FinCense enables banks to share insights on scam flows and mule account behaviours without compromising sensitive data. It is collective intelligence at scale.
  • Smart Case Disposition
    When alerts are triggered, FinCense’s Agentic AI generates natural-language summaries, helping investigators prioritise critical cases quickly and accurately.

Moving Forward: The Future of Scam Call Centres

The Bangsar South raid may have shut down one operation, but the fight against scam call centres is far from over. As enforcement improves, fraudsters will adopt AI-driven tools, deepfake impersonations, and more sophisticated laundering methods.

For financial institutions, the path forward is clear:

  • Strengthen collaboration with regulators and peers to track cross-border scam flows.
  • Invest in adaptive technology like FinCense to stay ahead of criminal innovation.
  • Educate customers relentlessly about new fraud tactics.

The raid was a victory, but it was also a warning.

If one call centre with 400 employees can operate in plain sight, imagine how many others remain hidden. The only safe strategy for financial institutions is to stay one step ahead with collaboration, intelligence, and next-generation technology.

Busted in Bangsar South: Inside Malaysia’s Largest Scam Call Centre Raid
Blogs
28 Aug 2025
6 min
read

Locked on Video: Inside India’s Chilling Digital Arrest Scam

It began with a phone call. A senior citizen in Navi Mumbai answered a number that appeared to belong to the police. Within hours, she was trapped on a video call with men in uniforms, accused of laundering money for terrorists. Terrified, she wired ₹21 lakh into what she believed was a government-controlled account.

She was not alone. In August 2025, cases of “digital arrest” scams surged across India. An elderly couple in Madhya Pradesh drained nearly ₹50 lakh of their life savings after spending 13 days under constant video surveillance by fraudsters posing as investigators. In Rajkot, criminals used the pretext of a real anti-terror operation to extort money from a student.

These scams are not crude phishing attempts. They are meticulously staged psychological operations, exploiting people’s deepest fears of authority and social disgrace. Victims are not tricked into handing over passwords. They are coerced, minute by minute, into making transfers themselves. The results are devastating, both for individuals and the wider financial system.

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Background of the Scam

The anatomy of a digital arrest scam follows a chillingly consistent script.

1. The Call of Fear
Fraudsters begin with a phone call, often masked to resemble an official number. The caller claims the victim’s details have surfaced in a serious crime: drug trafficking, terror financing, or money laundering. The consequences are presented as immediate arrest, frozen accounts, or ruined reputations.

2. Escalation to Video
To heighten credibility, the fraudster insists on switching to a video call. Victims are connected to people wearing uniforms, holding forged identity cards, or even sitting before backdrops resembling police stations and courtrooms.

3. Isolation and Control
Once on video, the victim is told they cannot disconnect. In some cases, they are monitored round the clock, ordered not to use their phone for any purpose other than the call. Contact with family or friends is prohibited, under the guise of “confidential investigations.”

4. The Transfer of Funds
The victim is then directed to transfer money into so-called “secure accounts” to prove their innocence or pay bail. These accounts are controlled by criminals and serve as the first layer in complex laundering networks. Victims, believing they are cooperating with the law, empty fixed deposits, break retirement savings, and transfer sums that can take a lifetime to earn.

The method blends social engineering with coercive control. It is not the theft of data, but the hijacking of human behaviour.

What the Case Revealed

The 2025 wave of digital arrest scams in India exposed three critical truths about modern fraud.

1. Video Calls Are No Longer a Guarantee of Authenticity
For years, people considered video more secure than phone calls or emails. If you could see someone’s face, the assumption was that they were genuine. These scams demolished that trust. Fraudsters showed that live video, like written messages, can be staged, manipulated, and weaponised.

2. Authority Bias is a Fraudster’s Greatest Weapon
Humans are hardwired to respect authority, especially law enforcement. By impersonating police or investigators, criminals bypass the victim’s critical reasoning. Fear of prison or social disgrace outweighs logical checks.

3. Coercion Multiplies the Damage
Unlike phishing or one-time deceptions, digital arrests involve prolonged psychological manipulation. Victims are kept online for days, bombarded with threats and false evidence. Under this pressure, even cautious individuals break down. The results are not minor losses, but catastrophic financial wipe-outs.

4. Organised Networks Are Behind the Scenes
The professionalism and scale suggest syndicates, not lone operators. From forged documents to layered mule accounts, the fraud points to criminal hubs capable of running scripted operations across borders.

Impact on Financial Institutions and Corporates

Though victims are individuals, the implications extend far into the financial and corporate world.

1. Reputational Risk
When victims lose life savings through accounts within the banking system, they often blame their bank as much as the fraudster. Even if technically blameless, institutions suffer a hit to public trust.

2. Pressure on Fraud Systems
Digital arrest scams exploit authorised transactions. Victims themselves make the transfers. Traditional detection tools that focus on unauthorised access or password breaches cannot easily flag these cases.

3. Global Movement of Funds
Money from scams rarely stays local. Transfers are routed across borders within hours, layered through mule accounts, e-wallets, and fintech platforms. This complicates recovery and exposes gaps in international coordination.

4. Corporate Vulnerability
The threat is not limited to retirees or individuals. In Singapore earlier this year, a finance director was tricked into wiring half a million dollars during a deepfake board call. Digital arrest tactics could just as easily target corporate employees handling high-value transactions.

5. Regulatory Expectations
As scams multiply, regulators are pressing institutions to demonstrate stronger customer protections, more resilient monitoring, and greater collaboration. Failure to act risks not only reputational damage but also regulatory penalties.

ChatGPT Image Aug 27, 2025, 11_32_20 AM

Lessons Learned from the Scam

For Individuals

  • Treat unsolicited calls from law enforcement with suspicion. Real investigations do not begin on the phone.
  • Verify independently by calling the published numbers of agencies.
  • Watch for signs of manipulation, such as demands for secrecy or threats of immediate arrest.
  • Educate vulnerable groups, particularly senior citizens, about how these scams operate.

For Corporates

  • Train employees, especially those in finance roles, to recognise coercion tactics.
  • Require secondary verification for urgent, high-value transfers, especially when directed to new accounts.
  • Encourage a speak-up culture where staff can challenge suspicious instructions without fear of reprimand.

For Financial Institutions

  • Monitor for mule account activity. Unexplained inflows followed by rapid withdrawals are a red flag.
  • Run customer awareness campaigns, explaining how digital arrest scams work.
  • Share intelligence with peers and regulators to prevent repeat incidents across institutions.

The Role of Technology in Prevention

Digital arrest scams prove that traditional safeguards are insufficient. Fraudsters are not stealing credentials but manipulating behaviour. Prevention requires smarter, adaptive systems.

1. Behavioural Monitoring
Transactions made under duress often differ from normal patterns. Advanced analytics can detect anomalies, such as sudden large transfers from accounts with low historical activity.

2. Typology-Driven Detection
Platforms like Tookitaki’s FinCense leverage the AFC Ecosystem to encode real-world scam scenarios into detection logic. As digital arrest typologies are identified, they can be integrated quickly to improve monitoring.

3. AI-Powered Simulations
Institutions can run simulations of coercion-based scams to test whether their processes would withstand them. These exercises reveal gaps in escalation and verification controls.

4. Federated Learning for Collective Defence
With federated learning, insights from one bank can be shared across many without exposing sensitive data. If one institution sees a pattern in digital arrest cases, others can benefit almost instantly.

5. Smarter Alert Management
Agentic AI can review and narrate the context of alerts, allowing investigators to understand whether unusual activity stems from duress. This speeds up response times and prevents irreversible losses.

Conclusion

The digital arrest scam is not just a fraud. It is a form of psychological captivity, where victims are imprisoned through fear on their own devices. In 2025, India saw a surge of such cases, stripping people of their savings and shaking trust in digital communications.

The message is clear: scams no longer rely on technical breaches. They rely on exploiting human trust. For individuals, the defence is awareness and verification. For corporates, it is embedding strong protocols and encouraging a culture of questioning. For financial institutions, the challenge is profound. They must detect authorised transfers made under coercion, collaborate across borders, and deploy AI-powered defences that learn as fast as the criminals do.

If 2024 was the year of deepfake deception, 2025 is becoming the year of coercion-based fraud. The industry’s response will determine whether scams like digital arrests remain isolated tragedies or become a systemic crisis. Protecting trust is no longer optional. It is the frontline of financial crime prevention.

Locked on Video: Inside India’s Chilling Digital Arrest Scam
Blogs
01 Sep 2025
6 min
read

Inside the New Payments Platform (NPP): How Australia’s Real-Time Payments Are Changing Finance and Fraud

Australia’s real-time payments revolution is reshaping finance, but it also brings new risks and compliance challenges.

Imagine sending money to a friend, paying a bill, or receiving your salary in seconds, no matter the day or hour. That vision became reality in Australia with the launch of the New Payments Platform (NPP) in 2018. Since then, the NPP has transformed how Australians transact, powering faster, smarter, and more flexible payments.

But while the benefits are undeniable, the NPP has also introduced fresh risks. Fraudsters and money launderers now exploit the speed of real-time payments, forcing banks, fintechs, and regulators to rethink how they approach compliance. In this blog, we take a deep look at the NPP, exploring its origins, features, benefits, risks, and what the future holds.

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What is the New Payments Platform (NPP)?

The NPP is Australia’s real-time payments infrastructure, designed to allow funds to be transferred between bank accounts in seconds. Unlike traditional bank transfers, which could take hours or days, the NPP settles payments instantly, around the clock, 365 days a year.

A Collaborative Effort

The NPP was launched in February 2018 as a collaborative initiative between the Reserve Bank of Australia (RBA), major banks, and key financial institutions. It was developed to modernise Australia’s payments infrastructure and to match the expectations of a digital-first economy.

Core Components of the NPP

  1. Fast Settlement Service (FSS): Operated by the RBA, this ensures transactions settle instantly across participating banks.
  2. Overlay Services: Products built on top of the NPP to offer tailored use cases, such as Osko by BPAY for fast peer-to-peer payments.
  3. PayID: A feature that allows customers to link easy identifiers such as email addresses or phone numbers to bank accounts for faster payments.
  4. ISO 20022 Data Standard: Enables rich data to travel with payments, improving transparency and reporting.

The NPP is not just a new payment rail. It is an entirely new ecosystem designed to support innovation, competition, and efficiency.

Key Features of the NPP

  • Speed: Transactions settle in less than 60 seconds.
  • Availability: Operates 24/7/365, unlike traditional settlement systems.
  • Rich Data: ISO 20022 messaging allows businesses to include detailed payment references.
  • Flexibility: Overlay services enable innovative new use cases, from consumer-to-business payments to government disbursements.
  • Ease of Use: PayID removes the need for remembering BSB and account numbers.

Benefits of the NPP for Australia

1. Consumer Convenience

Everyday Australians can send and receive money instantly. Whether splitting a dinner bill or paying rent, transactions are seamless and fast.

2. Business Efficiency

Businesses benefit from faster supplier payments, real-time payroll, and improved cash flow management. For SMEs, this reduces dependency on costly credit.

3. Government Services

Government agencies can issue refunds, grants, and welfare payments in real time, improving citizen experience and efficiency.

4. Financial Inclusion and Innovation

The NPP creates opportunities for fintechs to build new payment products and services, driving competition and giving consumers more choice.

5. Enhanced Transparency

The rich data standards improve reconciliation and reduce errors, saving time and cost for businesses.

The Risks and Challenges of Real-Time Payments

As with any innovation, the NPP comes with challenges. The very features that make it attractive to consumers also make it attractive to fraudsters and money launderers.

1. Authorised Push Payment (APP) Scams

Fraudsters use social engineering to trick customers into sending money themselves. Because NPP payments are instant, victims often cannot recover funds once transferred.

2. Money Mule Networks

Criminals exploit mule accounts to move illicit funds quickly. Dormant accounts or those opened with synthetic identities are often used as conduits.

3. Increased Operational Pressure

Compliance teams that once had hours to review suspicious transactions now have seconds. This shift requires entirely new approaches to monitoring.

4. False Positives and Noise

Traditional systems generate vast numbers of false positives, which overwhelm investigators. With NPP volumes growing, this problem is magnified.

5. Cyber and Identity Risks

Fraudsters use phishing, malware, and stolen credentials to take over accounts and push funds instantly.

ChatGPT Image Aug 26, 2025, 10_17_36 AM

Regulatory and Industry Response

Australian regulators have moved swiftly to address these risks.

  • AUSTRAC: Expects banks and payment providers to implement effective real-time monitoring and suspicious matter reporting tailored to NPP risks.
  • ASIC: Focuses on consumer protection and ensuring victims of scams are treated fairly.
  • Industry Initiatives: The Australian Banking Association has been working on scam-reporting frameworks and shared fraud detection systems across banks.
  • Government Action: Proposals to make banks reimburse scam victims are under consideration, following models in the UK.

The message is clear: institutions must invest in smarter compliance and fraud prevention tools.

Fraud and AML in the NPP Era

Why Legacy Systems Fall Short

Legacy monitoring systems were built for batch processing. They cannot keep up with the millisecond-level requirements of real-time payments. By the time a suspicious transaction is flagged, the funds are gone.

What Next-Gen Solutions Look Like

Modern systems use AI and machine learning to:

  • Detect anomalies in real time.
  • Link suspicious activity across accounts, devices, and geographies.
  • Reduce false positives by learning from investigator feedback.
  • Provide regulator-ready explanations for every alert.

Key Fraud Red Flags in NPP Transactions

  • Large transfers to newly created accounts.
  • Multiple small payments designed to avoid thresholds.
  • Sudden changes in device or login behaviour.
  • Beneficiaries in high-risk jurisdictions.
  • Rapid pass-through activity with no balance retention.

Spotlight on Technology: Tookitaki’s Role

As the risks around NPP accelerate, technology providers are stepping up. Tookitaki’s FinCense is purpose-built for the demands of real-time payments.

How FinCense Helps

  • Real-Time Monitoring: Detects suspicious activity in milliseconds.
  • Agentic AI: Continuously adapts to new scam typologies, reducing false positives.
  • Federated Intelligence: Accesses insights from the AFC Ecosystem, a global compliance community, while preserving privacy.
  • FinMate AI Copilot: Assists investigators with summaries, recommendations, and regulator-ready narratives.
  • AUSTRAC-Ready Compliance: Built-in reporting for SMRs, TTRs, and detailed audit trails.

Local Adoption

FinCense is already being used by community-owned banks like Regional Australia Bank and Beyond Bank. These partnerships demonstrate that even mid-sized institutions can meet AUSTRAC’s expectations while delivering excellent customer experiences.

The Future of NPP in Australia

The NPP is still evolving. Several developments will shape its future:

1. PayTo Expansion

PayTo, a digital alternative to direct debit, is gaining traction. It allows consumers to authorise payments directly from their accounts, offering flexibility but also new fraud vectors.

2. Cross-Border Potential

Future integration with Asia-Pacific payment systems could expand NPP beyond Australia, increasing both opportunities and risks.

3. Smarter Fraud Typologies

Criminals are already exploring ways to exploit deepfake technology, synthetic identities, and AI-driven scams. Fraud prevention must evolve just as quickly.

4. Industry Collaboration

Expect stronger cooperation between banks, fintechs, regulators, and technology vendors. Shared fraud databases and federated intelligence models will be crucial.

Conclusion

The New Payments Platform has reshaped Australia’s payments landscape. It delivers speed, convenience, and innovation that benefit consumers, businesses, and government agencies. But with opportunity comes risk.

Fraudsters have been quick to exploit the instant nature of NPP, forcing institutions to rethink how they detect and prevent financial crime. The solution lies in real-time, AI-powered monitoring platforms that adapt to new typologies and reduce compliance costs.

For Australian institutions, the NPP is more than a payment rail. It is the foundation of a new financial ecosystem. The winners will be those who embrace innovation, partner with the right AML vendors, and build trust through smarter compliance.

Pro tip: If your institution still relies on batch monitoring, you are already behind. Now is the time to modernise and future-proof your compliance with intelligent fraud and AML platforms.

Inside the New Payments Platform (NPP): How Australia’s Real-Time Payments Are Changing Finance and Fraud