Pitfall of Black Box AI at Banks: Explaining Your Models to Regulators
The use cases of artificial intelligence (AI) and machine learning in front-office, middle-office and back-office activities at banks are growing slowly but steadily. The major areas of AI play include customer service (virtual assistants, chatbots, etc.), fraud detection, risk management, predictive analytics, and automation. Like in any other industries, AI, if implemented the right product in the right manner, can increase the efficiency of banking operations as well as reduce their cost (up to more than USD 1 trillion by 2030, according to experts). Of course, there are problems related to distinct data sets and data privacy that curtail the implementation of these technologies. However, AI would turn into a new normal at banks as existing workflows are set to become unsustainable due to the ever-increasing scale of operations. These days, most banks are operating round the clock due to the emergence of online banking and mobile banking. Along with that, the financial inclusion initiatives across the globe would see a gigantic rise in the volume of banking operations. Therefore, banks would require rapid processing abilities to stay relevant and ensure the satisfaction of various stakeholders including customers and regulators.
Though the field is somewhat set for AI at banks with the advent of mobile technology, data availability and abundance of open-source APIs, there are certain systemic problems that banks are concerned about. Banks are worried if their regulators would accept the use of technologies, which are relatively new and different from the existing ones to a great extent. There are also risks related to possible biases in machine learning algorithms due to data quality and data accuracy. Black box AI algorithms are another concern that can hinder the adoption of AI in banking. Here, we are trying to explain the concept of black box AI, its problems and how banks can overcome the challenge.
What is black box AI?
Black box AI is a problem in machine learning where even the designers of an algorithm cannot explain why and how it arrived at a specific decision. The fundamental problem here is: if we cannot figure out how AI has come up with its decisions, how can we trust AI? This trust issue led to the failure of IBM Watson (especially (Watson for Oncology), one of the best-known AI innovations in recent times. The main problem with a black box model is its inability to identify possible biases in the machine learning algorithms. Biases can come through prejudices of designers and faulty training data, and these biases lead to unfair and wrong decisions. Bias can also happen when model developers do not implement the proper business context to come up with legitimate outputs.
The same problem is relevant in the banking industry as well. If regulators pose a question: how AI has reached at a conclusion with regard to a banking problem, banks should be able to explain the same. For example, if an AI solution dealing with anti-money laundering compliance comes up with an anomalous behaviour or suspicious activity in a transaction, the bank using the solution should be able to explain the reason why the solution has arrived at that decision. Such an audit is not possible with a black box AI model. The same concern was expressed by Federal Reserve Gov. Lael Brainard in a November 2018 speech. “AI can introduce additional complexity because many AI tools and models develop analysis, arrive at conclusions, or recommend decisions that may be hard to explain. For instance, some AI approaches are able to identify patterns that were previously unidentified and are intuitively quite hard to grasp. Depending on what algorithms are used, it is possible that no one, including the algorithm's creators, can easily explain why the model generated the results that it did,” she said.
Not just AI, Banks need explainable AI
Explainable AI or interpretable AI or transparent AI deals with techniques in artificial intelligence which can make machine learning algorithms trustworthy and easily understandable by humans. Explainability has emerged as a critical requirement for AI in many cases and has become a new research area in AI. As mentioned by the Defense Advanced Research Projects Agency under the US Department of Defense: “New machine-learning systems will have the ability to explain their rationale, characterize their strengths and weaknesses, and convey an understanding of how they will behave in the future.”
In the banking industry, which is subject to stricter regulatory oversight across the globe, an incorrect decision can cost billions of dollars for an institution. If a bank wants to employ AI, it is imperative for it to subject the particular solution to rigorous, dynamic model risk management and validation. The bank must ensure that the proposed AI solution has the required transparency depending on the use case. As an AI solutions provider, Tookitaki has always considered explainability as a must-have feature in its offerings. Its unique technology demystifies modern machine learning and gives clients the knowledge and tools to outperform the competition. Tookitaki solutions feature a ‘Glass box’ audit module that brings algorithmic transparency by providing thorough explanations for predictions.
There is no doubt that AI can bring in revolutionary changes in the banking sector. For that to happen, it is mandatory that banks should take the necessary oversight to prevent their AI models from being a black box. As of now, the AI use cases are mostly in low-risk banking environments, where human beings still take the final decision with machines just providing valuable assistance in decision making. In future, banks will be under pressure to remove some of the human oversight for cost savings amid increasing scale of operations. At that point, banks cannot run with risky black box models that can lead to inefficiencies and risks. They need to ensure that their AI solutions are trustworthy and have the required transparency to satisfy internal and external audits. In short, the bright future of AI in banking could be assured only through explainable AI.
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Stablecoins Are Booming. Is Compliance Falling Behind?
Programmable money isn’t a futuristic buzzword anymore — it’s here, and it’s scaling at breakneck speed. In 2024, stablecoin transactions exceeded $27 trillion, surpassing Visa and Mastercard combined. From international remittances to e-commerce, stablecoins are reshaping how money moves across borders.
But there’s a catch: the same features that make stablecoins so powerful — speed, cost efficiency, accessibility — also make them attractive for financial crime. Instant, irreversible, and identity-light transactions have created a compliance challenge unlike any before. For regulators, banks, and fintechs, the question is clear: can compliance scale as fast as stablecoins?

The Rise of Stablecoins: More Than Just Crypto
Stablecoins are digital tokens pegged to a stable asset like the U.S. dollar or euro. Unlike Bitcoin or Ether, they aren’t designed for volatility — they’re designed for utility. That’s why they’ve become the backbone of digital payments and decentralised finance (DeFi).
- Cross-border remittances: Workers abroad can send money home cheaply and instantly.
- Trading and settlements: Exchanges use stablecoins as liquidity anchors.
- Merchant adoption: From small retailers to payment giants like PayPal (with its PYUSD stablecoin launched in 2023), stablecoin rails are entering mainstream commerce.
With global players like USDT (Tether) and USDC (Circle) dominating, and even central banks exploring CBDCs (Central Bank Digital Currencies), it’s clear stablecoins are no longer niche. They are programmable, scalable, and systemically important.
But scale brings scrutiny.
The Compliance Gap: Why Old Tools Don’t Work
Most financial institutions still rely on compliance infrastructure designed decades ago for slower, linear payment systems. Batch settlements, SWIFT messages, and pre-clearing windows gave compliance teams time to check, flag, or stop suspicious activity.
Stablecoins operate on entirely different principles:
- Real-time settlement: Transactions confirm in seconds.
- Pseudonymous wallets: No guaranteed link between a wallet and its true owner.
- DeFi composability: Funds can move through multiple protocols, contracts, and blockchains with no central chokepoint.
- Irreversibility: Once sent, funds can’t be clawed back.
This creates an environment where bad actors can launder funds at the speed of code. Legacy compliance systems — built for yesterday’s risks — simply cannot keep up.
The New Typologies Emerging on Stablecoin Rails
Financial crime doesn’t stand still. It adapts to new rails faster than regulation or compliance can. Here are some typologies unique to stablecoins:
- Money Mule Networks
Organised groups recruit international students or gig workers to act as “cash-out points,” moving illicit funds through stablecoin wallets before converting back to fiat. - Cross-Chain Laundering
Criminals exploit bridges between blockchains (e.g., Ethereum to Tron or Solana) to break traceability, making it harder to follow the money. This tactic was highlighted in multiple reports after North Korea’s Lazarus Group laundered hundreds of millions in stolen crypto across chains. - DeFi Layering
Funds are routed through decentralised exchanges, lending platforms, or automated market makers to mix flows and obscure origins. The U.S. Treasury’s sanctions on Tornado Cash in 2022 marked a watershed moment, underscoring how DeFi mixers can become systemic laundering tools. - Sanctions Evasion
With traditional banking rails restricted, sanctioned entities increasingly turn to stablecoins. The U.S. Office of Foreign Assets Control (OFAC) has flagged stablecoin usage in multiple enforcement actions tied to Russia and other high-risk jurisdictions.
Each of these typologies highlights the speed, complexity, and opacity of stablecoin-based laundering. They don’t look like traditional fiat red flags — they demand new methods of detection.

What Compliance Needs to Look Like for Stablecoins
To match the speed of programmable money, compliance must itself become programmable, adaptive, and dynamic. Static, rule-based systems are insufficient. Instead, compliance must shift to a risk infrastructure that is:
1. Risk-in-Motion Monitoring
Rather than flagging transactions after they settle, monitoring must happen in real time, detecting structuring, layering, and unusual flow patterns as they unfold.
2. Smart Sanctions & Wallet Screening
Name checks aren’t enough. Risk detection must consider wallet metadata, behavioural history, device intelligence, and network analysis to surface high-risk entities hidden behind pseudonyms.
3. Wallet Risk Scoring
A static “high-risk wallet list” doesn’t work in a world where wallets are created and discarded easily. Risk scoring must be dynamic and contextual, combining geolocation, device, transaction history, and counterparties into evolving risk profiles.
This is compliance at the speed of programmable money.
Tookitaki’s FinCense: Building the Trust Layer for Stablecoins
At Tookitaki, we’re not retrofitting legacy tools to fit this new world. We’re building the infrastructure-grade compliance layer programmable money deserves.
Here’s how FinCense powers trust on stablecoin rails:
- Risk-in-Motion Monitoring
Detects structuring, layering, and anomalous flows across chains in real time. - Smart Sanctions & Wallet Screening
Goes beyond simple lists, screening metadata, networks, and behavioural red flags. - Wallet Risk Scoring
Integrates device, location, and transaction intelligence to give every wallet a living, breathing risk profile. - Federated Intelligence from the AFC Ecosystem
Scenarios contributed by 200+ compliance experts worldwide enrich the system with the latest typologies. - Agentic AI for Investigations
Accelerates investigations with an AI copilot, surfacing insights and reducing false positives.
FinCense is modular, composable, and built for the future of programmable finance. Whether you’re a digital asset exchange, fintech, or bank integrating stablecoin rails, it enables you to operate with trust and resilience.
Conclusion: Scaling Trust with Stablecoins
Stablecoins are here to stay. They’re reshaping payments, cross-border transfers, and financial inclusion. But they’re also rewriting the rules of financial crime.
The next phase of growth won’t be defined by speed or accessibility alone — it will be defined by trust. And trust comes from compliance that can move as fast and adapt as dynamically as programmable money itself.
Stablecoins will define the next decade of finance. Whether they become rails for inclusion or loopholes for crime depends on how we build trust today. Tookitaki’s FinCense is here to make that trust possible.

Ferraris, Ghost Cars, and Dirty Money: Inside Australia’s 2025 Barangaroo Laundering Scandal
In July 2025, Sydney’s Barangaroo precinct became the unlikely stage for one of Australia’s most audacious money laundering cases. Beyond the headlines about Ferraris and luxury goods lies a sobering truth: criminals are still exploiting the blind spots in Australia’s financial crime defences.
A Case That Reads Like a Movie Script
On 30 July 2025, Australian police raided properties across Sydney and arrested two men—Bing “Michael” Li, 38, and Yizhe “Tony” He, 34.
Both men were charged with an astonishing 194 fraud-related offences. Li faces 87 charges tied to AUD 12.9 million, while He faces 107 charges tied to about AUD 4 million. Authorities also froze AUD 38 million worth of assets, including Bentleys, Ferraris, designer goods, and property leases.
At the heart of the case was a fraud and laundering scheme that funnelled stolen money into the high-end economy of cars, luxury fashion, and short-term property leases. Investigators dubbed them “ghost cars”—vehicles purchased as a way to obscure illicit funds.
It’s a tale that grabs attention for its glitz, but what really matters is the deeper lesson: Australia still has critical AML blind spots that criminals know how to exploit.

How the Syndicate Operated
The mechanics of the scheme reveal just how calculated it was:
- Rapid loan cycling: The accused are alleged to have obtained loans, often short-term, which were cycled quickly to create complex repayment patterns. This made tracing the origins of funds difficult.
- Luxury asset laundering: The money was used to purchase high-value cars (Ferraris, Bentleys, Mercedes) and designer items from brands like Louis Vuitton. Assets of prestige become a laundering tool, integrating dirty money into seemingly legitimate wealth.
- Property as camouflage: Short-term leases of expensive properties in Barangaroo and other high-end districts provided both a lifestyle cover and another channel to absorb illicit funds.
- Gatekeeper loopholes: Real estate agents, accountants, and luxury dealers in Australia are not yet fully bound by AML/CTF obligations. This gap created the perfect playground for laundering.
What’s striking is not the creativity of the scheme—it’s the simplicity. By targeting sectors without AML scrutiny, the syndicate turned everyday transactions into a pipeline for cleaning millions.
The Regulatory Gap
This case lands at a critical time. For years, Australia has been under pressure from the Financial Action Task Force (FATF) to extend AML/CTF laws to the so-called “gatekeeper professions”—real estate agents, accountants, lawyers, and dealers in high-value goods.
As of 2025, these obligations are still not fully in place. The expansion is only scheduled to take effect from July 2026. Until then, large swathes of the economy remain outside AUSTRAC’s oversight.
The Barangaroo arrests underscore what critics have long warned: criminals don’t wait for legislation. They are already steps ahead, embedding illicit funds into sectors that regulators have yet to fence off.
For businesses in real estate, luxury retail, and professional services, this case is more than a headline—it’s a wake-up call to prepare now, not later.

Why This Case Matters for Australia
The Barangaroo case isn’t just about two individuals—it highlights systemic vulnerabilities in the Australian financial ecosystem.
- Criminal Adaptation: Syndicates will always pivot to the weakest link. If banks tighten their checks, criminals move to less regulated industries.
- Erosion of Trust: When high-value markets become conduits for laundering, it damages Australia’s reputation as a clean, well-regulated financial hub.
- Compliance Risk: Businesses in these sectors risk being blindsided by new regulations if they don’t start implementing AML controls now.
- Global Implications: With assets like luxury cars and crypto being easy to move or sell internationally, local failures in AML quickly ripple across borders.
This isn’t an isolated story. It’s part of a broader trend where fraud, luxury assets, and regulatory lag intersect to create fertile ground for financial crime.
Lessons for Businesses
For financial institutions, fintechs, and gatekeeper industries, the Barangaroo case offers several practical takeaways:
- Monitor for rapid loan cycling: Short-term loans repaid unusually fast, or loans tied to sudden high-value purchases, should trigger alerts.
- Scrutinise asset purchases: Repeated luxury acquisitions, especially where the source of funds is vague, are classic laundering red flags.
- Don’t rely solely on regulation: Just because AML obligations aren’t mandatory yet doesn’t mean businesses can ignore risk. Voluntary adoption of AML best practices can prevent reputational damage.
- Collaborate cross-sector: Banks, real estate firms, and luxury dealers must share intelligence. Laundering rarely stays within one sector.
- Prepare for 2026: When the law expands, regulators will expect not just compliance but also readiness. Being proactive now can avoid penalties later.
How Tookitaki’s FinCense Can Help
The Barangaroo case demonstrates a truth that regulators and compliance teams already know: criminals are fast, and rules often move too slowly.
This is where FinCense, Tookitaki’s AI-powered compliance platform, makes the difference.
- Scenario-based Monitoring
FinCense doesn’t just look for generic suspicious behaviour—it monitors for specific typologies like “rapid loan cycling leading to high-value asset purchases.” These scenarios mirror real-world cases, allowing institutions to spot laundering patterns early. - Federated Intelligence
FinCense leverages insights from a global compliance community. A laundering method detected in one country can be quickly shared and simulated in others. If the Barangaroo pattern emerged elsewhere, FinCense could help Australian institutions adapt almost immediately. - Agentic AI for Real-Time Detection
Criminal tactics evolve constantly. FinCense’s Agentic AI ensures models don’t go stale—it adapts to new data, learns continuously, and responds to threats as they arise. That means institutions don’t wait months for rule updates; they act in real time. - End-to-End Compliance Coverage
From customer onboarding to transaction monitoring and investigation, FinCense provides a unified platform. For banks, this means capturing anomalies at multiple points, not just after funds have already flowed into cars and luxury handbags.
The result is a system that doesn’t just tick compliance boxes but actively prevents fraud and laundering—protecting both businesses and Australia’s reputation.
The Bigger Picture: Trust and Reputation
Australia has ambitions to strengthen its role as a regional financial hub. But trust is the currency that underpins global finance.
Cases like Barangaroo remind us that even one high-profile lapse can shake investor and customer confidence. With scams and laundering scandals making headlines globally—from Crown Resorts to major online frauds—Australia cannot afford to be reactive.
For businesses, the message is clear: compliance isn’t just about avoiding fines, it’s about protecting your licence to operate. Customers and partners expect vigilance, transparency, and accountability.
Conclusion: A Warning Shot
The Barangaroo “ghost cars and luxury laundering” saga is more than a crime story—it’s a preview of what happens when regulation lags and businesses underestimate financial crime risk.
With AUSTRAC set to extend AML coverage in 2026, industries like real estate and luxury retail must act now. Waiting until the law forces compliance could mean walking straight into reputational disaster.
For financial institutions and businesses alike, the smarter path is to embrace advanced solutions like Tookitaki’s FinCense, which combine scenario-driven intelligence with adaptive AI.
Because at the end of the day, Ferraris and Bentleys may be glamorous—but when they’re bought with dirty money, they carry a far higher cost.

Cracking Down Under: How Australia Is Fighting Back Against Fraud
Fraud in Australia has moved beyond stolen credit cards, today’s threats are smarter, faster, and often one step ahead.
Australia is facing a new wave of financial fraud—complex scams, cyber-enabled deception, and social engineering techniques that prey on trust. From sophisticated investment frauds to deepfake impersonations, criminals are evolving rapidly. And so must our fraud prevention strategies.
This blog explores how fraud is impacting Australia, what new methods criminals are using, and how financial institutions, businesses, and individuals can stay ahead of the game. Whether you're in compliance, fintech, banking, or just a concerned citizen, fraud prevention is everyone’s business.
The Fraud Landscape in Australia: A Wake-Up Call
In 2024 alone, Australians lost over AUD 2.7 billion to scams, according to data from the Australian Competition and Consumer Commission (ACCC). The Scamwatch program reported an alarming rise in phishing, investment scams, identity theft, and fake billing.
A few alarming trends:
- Investment scams accounted for over AUD 1.3 billion in losses.
- Business email compromise (BEC) and invoice fraud targeted SMEs.
- Romance and remote access scams exploited personal vulnerability.
- Deepfake scams and AI-generated impersonations are on the rise, particularly targeting executives and finance teams.
The fraud threat has gone digital, cross-border, and real-time. Traditional controls alone are no longer enough.

Why Fraud Prevention Is a National Priority
Fraud isn't just a financial issue—it’s a matter of public trust. When scams go undetected, victims don’t just lose money—they lose faith in financial institutions, government systems, and digital innovation.
Here’s why fraud prevention is now top of mind in Australia:
- Real-time payments mean real-time risks: With the rise of the New Payments Platform (NPP), funds can move across banks instantly. This has increased the urgency to detect and prevent fraud in milliseconds—not days.
- Rise in money mule networks: Criminal groups are exploiting students, gig workers, and the elderly to launder stolen funds.
- Increased regulatory pressure: AUSTRAC and ASIC are putting more pressure on institutions to identify and report suspicious activities more proactively.
Common Fraud Techniques Seen in Australia
Understanding how fraud works is the first step to preventing it. Here are some of the most commonly observed fraud techniques:
a) Business Email Compromise (BEC)
Fraudsters impersonate vendors, CEOs, or finance officers to divert funds through fake invoices or urgent payment requests. This is especially dangerous for SMEs.
b) Investment Scams
Fake trading platforms, crypto Ponzi schemes, and fraudulent real estate investments have tricked thousands. Often, these scams use fake celebrity endorsements or “guaranteed returns” to lure victims.
c) Romance and Sextortion Scams
These scams manipulate victims emotionally, often over weeks or months, before asking for money. Some even involve blackmail using fake or stolen intimate content.
d) Deepfake Impersonation
Using AI-generated voice or video, scammers are impersonating real people to initiate fund transfers or manipulate staff into giving away sensitive information.
e) Synthetic Identity Fraud
Criminals use a blend of real and fake information to create a new, ‘clean’ identity that can bypass onboarding checks at banks and fintechs.

Regulatory Push for Smarter Controls
Regulators in Australia are stepping up their efforts:
- AUSTRAC has introduced updated guidance for transaction monitoring and suspicious matter reporting, pushing institutions to adopt more adaptive, risk-based approaches.
- ASIC is cracking down on investment scams and calling for platforms to implement stricter identity and payment verification systems.
- The ACCC’s National Anti-Scam Centre launched a multi-agency initiative to disrupt scam operations through intelligence sharing and faster response times.
But even regulators acknowledge: compliance alone won't stop fraud. Prevention needs smarter tools, better collaboration, and real-time intelligence.
A New Approach: Proactive, AI-Powered Fraud Prevention
The most forward-thinking banks and fintechs in Australia are moving from reactive to proactive fraud prevention. Here's what the shift looks like:
✅ Real-Time Transaction Monitoring
Instead of relying on static rules, modern systems use machine learning to flag suspicious behaviour—like unusual payment patterns, high-risk geographies, or rapid account-to-account transfers.
✅ Behavioural Analytics
Understanding what ‘normal’ looks like for each user helps detect anomalies fast—like a customer suddenly logging in from a new country or making a large transfer outside business hours.
✅ AI Copilots for Investigators
Tools like AI-powered investigation assistants can help analysts triage alerts faster, recommend next steps, and even generate narrative summaries for suspicious activity reports.
✅ Community Intelligence
Fraudsters often reuse tactics across institutions. Platforms like Tookitaki’s AFC Ecosystem allow banks to share anonymised fraud scenarios and red flags—so everyone can learn and defend together.
✅ Federated Learning Models
These models allow banks to collaborate on fraud detection algorithms without sharing customer data—bringing the power of collective intelligence without compromising privacy.
Fraud Prevention Best Practices for Australian Institutions
Whether you're a Tier-1 bank or a growing fintech, these best practices are critical:
- Prioritise real-time fraud detection tools that work across payment channels and digital platforms.
- Train your teams—fraudsters are exploiting human error more than technical flaws.
- Invest in explainable AI to build trust with regulators and internal stakeholders.
- Use layered defences: Combine transaction monitoring, device fingerprinting, behavioural analytics, and biometric verification.
- Collaborate across the ecosystem—join industry platforms, share intel, and learn from others.
How Tookitaki Supports Fraud Prevention in Australia
Tookitaki is helping Australian institutions stay ahead of fraud by combining advanced AI with collective intelligence. Our FinCense platform offers:
- End-to-end fraud and AML detection across transactions, customers, and devices.
- Federated learning that enables risk detection with insights contributed by a global network of financial crime experts.
- Smart investigation tools to reduce alert fatigue and speed up response times.
The Role of Public Awareness in Prevention
It’s not just institutions—customers play a key role too. Public campaigns like Scamwatch, educational content from banks, and media coverage of fraud trends all contribute to prevention.
Simple actions like verifying sender details, avoiding suspicious links, and reporting scam attempts can go a long way. In the fight against fraud, awareness is the first line of defence.
Conclusion: Staying Ahead in a Smarter Fraud Era
Fraud prevention in Australia can no longer be treated as an afterthought. The threats are too advanced, too fast, and too costly.
With the right mix of technology, collaboration, and education, Australia can stay ahead of financial criminals—and turn the tide in favour of consumers, businesses, and institutions alike.
Whether it’s adopting AI tools, sharing threat insights, or empowering individuals, fraud prevention is no longer optional. It’s the new frontline of trust.

Stablecoins Are Booming. Is Compliance Falling Behind?
Programmable money isn’t a futuristic buzzword anymore — it’s here, and it’s scaling at breakneck speed. In 2024, stablecoin transactions exceeded $27 trillion, surpassing Visa and Mastercard combined. From international remittances to e-commerce, stablecoins are reshaping how money moves across borders.
But there’s a catch: the same features that make stablecoins so powerful — speed, cost efficiency, accessibility — also make them attractive for financial crime. Instant, irreversible, and identity-light transactions have created a compliance challenge unlike any before. For regulators, banks, and fintechs, the question is clear: can compliance scale as fast as stablecoins?

The Rise of Stablecoins: More Than Just Crypto
Stablecoins are digital tokens pegged to a stable asset like the U.S. dollar or euro. Unlike Bitcoin or Ether, they aren’t designed for volatility — they’re designed for utility. That’s why they’ve become the backbone of digital payments and decentralised finance (DeFi).
- Cross-border remittances: Workers abroad can send money home cheaply and instantly.
- Trading and settlements: Exchanges use stablecoins as liquidity anchors.
- Merchant adoption: From small retailers to payment giants like PayPal (with its PYUSD stablecoin launched in 2023), stablecoin rails are entering mainstream commerce.
With global players like USDT (Tether) and USDC (Circle) dominating, and even central banks exploring CBDCs (Central Bank Digital Currencies), it’s clear stablecoins are no longer niche. They are programmable, scalable, and systemically important.
But scale brings scrutiny.
The Compliance Gap: Why Old Tools Don’t Work
Most financial institutions still rely on compliance infrastructure designed decades ago for slower, linear payment systems. Batch settlements, SWIFT messages, and pre-clearing windows gave compliance teams time to check, flag, or stop suspicious activity.
Stablecoins operate on entirely different principles:
- Real-time settlement: Transactions confirm in seconds.
- Pseudonymous wallets: No guaranteed link between a wallet and its true owner.
- DeFi composability: Funds can move through multiple protocols, contracts, and blockchains with no central chokepoint.
- Irreversibility: Once sent, funds can’t be clawed back.
This creates an environment where bad actors can launder funds at the speed of code. Legacy compliance systems — built for yesterday’s risks — simply cannot keep up.
The New Typologies Emerging on Stablecoin Rails
Financial crime doesn’t stand still. It adapts to new rails faster than regulation or compliance can. Here are some typologies unique to stablecoins:
- Money Mule Networks
Organised groups recruit international students or gig workers to act as “cash-out points,” moving illicit funds through stablecoin wallets before converting back to fiat. - Cross-Chain Laundering
Criminals exploit bridges between blockchains (e.g., Ethereum to Tron or Solana) to break traceability, making it harder to follow the money. This tactic was highlighted in multiple reports after North Korea’s Lazarus Group laundered hundreds of millions in stolen crypto across chains. - DeFi Layering
Funds are routed through decentralised exchanges, lending platforms, or automated market makers to mix flows and obscure origins. The U.S. Treasury’s sanctions on Tornado Cash in 2022 marked a watershed moment, underscoring how DeFi mixers can become systemic laundering tools. - Sanctions Evasion
With traditional banking rails restricted, sanctioned entities increasingly turn to stablecoins. The U.S. Office of Foreign Assets Control (OFAC) has flagged stablecoin usage in multiple enforcement actions tied to Russia and other high-risk jurisdictions.
Each of these typologies highlights the speed, complexity, and opacity of stablecoin-based laundering. They don’t look like traditional fiat red flags — they demand new methods of detection.

What Compliance Needs to Look Like for Stablecoins
To match the speed of programmable money, compliance must itself become programmable, adaptive, and dynamic. Static, rule-based systems are insufficient. Instead, compliance must shift to a risk infrastructure that is:
1. Risk-in-Motion Monitoring
Rather than flagging transactions after they settle, monitoring must happen in real time, detecting structuring, layering, and unusual flow patterns as they unfold.
2. Smart Sanctions & Wallet Screening
Name checks aren’t enough. Risk detection must consider wallet metadata, behavioural history, device intelligence, and network analysis to surface high-risk entities hidden behind pseudonyms.
3. Wallet Risk Scoring
A static “high-risk wallet list” doesn’t work in a world where wallets are created and discarded easily. Risk scoring must be dynamic and contextual, combining geolocation, device, transaction history, and counterparties into evolving risk profiles.
This is compliance at the speed of programmable money.
Tookitaki’s FinCense: Building the Trust Layer for Stablecoins
At Tookitaki, we’re not retrofitting legacy tools to fit this new world. We’re building the infrastructure-grade compliance layer programmable money deserves.
Here’s how FinCense powers trust on stablecoin rails:
- Risk-in-Motion Monitoring
Detects structuring, layering, and anomalous flows across chains in real time. - Smart Sanctions & Wallet Screening
Goes beyond simple lists, screening metadata, networks, and behavioural red flags. - Wallet Risk Scoring
Integrates device, location, and transaction intelligence to give every wallet a living, breathing risk profile. - Federated Intelligence from the AFC Ecosystem
Scenarios contributed by 200+ compliance experts worldwide enrich the system with the latest typologies. - Agentic AI for Investigations
Accelerates investigations with an AI copilot, surfacing insights and reducing false positives.
FinCense is modular, composable, and built for the future of programmable finance. Whether you’re a digital asset exchange, fintech, or bank integrating stablecoin rails, it enables you to operate with trust and resilience.
Conclusion: Scaling Trust with Stablecoins
Stablecoins are here to stay. They’re reshaping payments, cross-border transfers, and financial inclusion. But they’re also rewriting the rules of financial crime.
The next phase of growth won’t be defined by speed or accessibility alone — it will be defined by trust. And trust comes from compliance that can move as fast and adapt as dynamically as programmable money itself.
Stablecoins will define the next decade of finance. Whether they become rails for inclusion or loopholes for crime depends on how we build trust today. Tookitaki’s FinCense is here to make that trust possible.

Ferraris, Ghost Cars, and Dirty Money: Inside Australia’s 2025 Barangaroo Laundering Scandal
In July 2025, Sydney’s Barangaroo precinct became the unlikely stage for one of Australia’s most audacious money laundering cases. Beyond the headlines about Ferraris and luxury goods lies a sobering truth: criminals are still exploiting the blind spots in Australia’s financial crime defences.
A Case That Reads Like a Movie Script
On 30 July 2025, Australian police raided properties across Sydney and arrested two men—Bing “Michael” Li, 38, and Yizhe “Tony” He, 34.
Both men were charged with an astonishing 194 fraud-related offences. Li faces 87 charges tied to AUD 12.9 million, while He faces 107 charges tied to about AUD 4 million. Authorities also froze AUD 38 million worth of assets, including Bentleys, Ferraris, designer goods, and property leases.
At the heart of the case was a fraud and laundering scheme that funnelled stolen money into the high-end economy of cars, luxury fashion, and short-term property leases. Investigators dubbed them “ghost cars”—vehicles purchased as a way to obscure illicit funds.
It’s a tale that grabs attention for its glitz, but what really matters is the deeper lesson: Australia still has critical AML blind spots that criminals know how to exploit.

How the Syndicate Operated
The mechanics of the scheme reveal just how calculated it was:
- Rapid loan cycling: The accused are alleged to have obtained loans, often short-term, which were cycled quickly to create complex repayment patterns. This made tracing the origins of funds difficult.
- Luxury asset laundering: The money was used to purchase high-value cars (Ferraris, Bentleys, Mercedes) and designer items from brands like Louis Vuitton. Assets of prestige become a laundering tool, integrating dirty money into seemingly legitimate wealth.
- Property as camouflage: Short-term leases of expensive properties in Barangaroo and other high-end districts provided both a lifestyle cover and another channel to absorb illicit funds.
- Gatekeeper loopholes: Real estate agents, accountants, and luxury dealers in Australia are not yet fully bound by AML/CTF obligations. This gap created the perfect playground for laundering.
What’s striking is not the creativity of the scheme—it’s the simplicity. By targeting sectors without AML scrutiny, the syndicate turned everyday transactions into a pipeline for cleaning millions.
The Regulatory Gap
This case lands at a critical time. For years, Australia has been under pressure from the Financial Action Task Force (FATF) to extend AML/CTF laws to the so-called “gatekeeper professions”—real estate agents, accountants, lawyers, and dealers in high-value goods.
As of 2025, these obligations are still not fully in place. The expansion is only scheduled to take effect from July 2026. Until then, large swathes of the economy remain outside AUSTRAC’s oversight.
The Barangaroo arrests underscore what critics have long warned: criminals don’t wait for legislation. They are already steps ahead, embedding illicit funds into sectors that regulators have yet to fence off.
For businesses in real estate, luxury retail, and professional services, this case is more than a headline—it’s a wake-up call to prepare now, not later.

Why This Case Matters for Australia
The Barangaroo case isn’t just about two individuals—it highlights systemic vulnerabilities in the Australian financial ecosystem.
- Criminal Adaptation: Syndicates will always pivot to the weakest link. If banks tighten their checks, criminals move to less regulated industries.
- Erosion of Trust: When high-value markets become conduits for laundering, it damages Australia’s reputation as a clean, well-regulated financial hub.
- Compliance Risk: Businesses in these sectors risk being blindsided by new regulations if they don’t start implementing AML controls now.
- Global Implications: With assets like luxury cars and crypto being easy to move or sell internationally, local failures in AML quickly ripple across borders.
This isn’t an isolated story. It’s part of a broader trend where fraud, luxury assets, and regulatory lag intersect to create fertile ground for financial crime.
Lessons for Businesses
For financial institutions, fintechs, and gatekeeper industries, the Barangaroo case offers several practical takeaways:
- Monitor for rapid loan cycling: Short-term loans repaid unusually fast, or loans tied to sudden high-value purchases, should trigger alerts.
- Scrutinise asset purchases: Repeated luxury acquisitions, especially where the source of funds is vague, are classic laundering red flags.
- Don’t rely solely on regulation: Just because AML obligations aren’t mandatory yet doesn’t mean businesses can ignore risk. Voluntary adoption of AML best practices can prevent reputational damage.
- Collaborate cross-sector: Banks, real estate firms, and luxury dealers must share intelligence. Laundering rarely stays within one sector.
- Prepare for 2026: When the law expands, regulators will expect not just compliance but also readiness. Being proactive now can avoid penalties later.
How Tookitaki’s FinCense Can Help
The Barangaroo case demonstrates a truth that regulators and compliance teams already know: criminals are fast, and rules often move too slowly.
This is where FinCense, Tookitaki’s AI-powered compliance platform, makes the difference.
- Scenario-based Monitoring
FinCense doesn’t just look for generic suspicious behaviour—it monitors for specific typologies like “rapid loan cycling leading to high-value asset purchases.” These scenarios mirror real-world cases, allowing institutions to spot laundering patterns early. - Federated Intelligence
FinCense leverages insights from a global compliance community. A laundering method detected in one country can be quickly shared and simulated in others. If the Barangaroo pattern emerged elsewhere, FinCense could help Australian institutions adapt almost immediately. - Agentic AI for Real-Time Detection
Criminal tactics evolve constantly. FinCense’s Agentic AI ensures models don’t go stale—it adapts to new data, learns continuously, and responds to threats as they arise. That means institutions don’t wait months for rule updates; they act in real time. - End-to-End Compliance Coverage
From customer onboarding to transaction monitoring and investigation, FinCense provides a unified platform. For banks, this means capturing anomalies at multiple points, not just after funds have already flowed into cars and luxury handbags.
The result is a system that doesn’t just tick compliance boxes but actively prevents fraud and laundering—protecting both businesses and Australia’s reputation.
The Bigger Picture: Trust and Reputation
Australia has ambitions to strengthen its role as a regional financial hub. But trust is the currency that underpins global finance.
Cases like Barangaroo remind us that even one high-profile lapse can shake investor and customer confidence. With scams and laundering scandals making headlines globally—from Crown Resorts to major online frauds—Australia cannot afford to be reactive.
For businesses, the message is clear: compliance isn’t just about avoiding fines, it’s about protecting your licence to operate. Customers and partners expect vigilance, transparency, and accountability.
Conclusion: A Warning Shot
The Barangaroo “ghost cars and luxury laundering” saga is more than a crime story—it’s a preview of what happens when regulation lags and businesses underestimate financial crime risk.
With AUSTRAC set to extend AML coverage in 2026, industries like real estate and luxury retail must act now. Waiting until the law forces compliance could mean walking straight into reputational disaster.
For financial institutions and businesses alike, the smarter path is to embrace advanced solutions like Tookitaki’s FinCense, which combine scenario-driven intelligence with adaptive AI.
Because at the end of the day, Ferraris and Bentleys may be glamorous—but when they’re bought with dirty money, they carry a far higher cost.

Cracking Down Under: How Australia Is Fighting Back Against Fraud
Fraud in Australia has moved beyond stolen credit cards, today’s threats are smarter, faster, and often one step ahead.
Australia is facing a new wave of financial fraud—complex scams, cyber-enabled deception, and social engineering techniques that prey on trust. From sophisticated investment frauds to deepfake impersonations, criminals are evolving rapidly. And so must our fraud prevention strategies.
This blog explores how fraud is impacting Australia, what new methods criminals are using, and how financial institutions, businesses, and individuals can stay ahead of the game. Whether you're in compliance, fintech, banking, or just a concerned citizen, fraud prevention is everyone’s business.
The Fraud Landscape in Australia: A Wake-Up Call
In 2024 alone, Australians lost over AUD 2.7 billion to scams, according to data from the Australian Competition and Consumer Commission (ACCC). The Scamwatch program reported an alarming rise in phishing, investment scams, identity theft, and fake billing.
A few alarming trends:
- Investment scams accounted for over AUD 1.3 billion in losses.
- Business email compromise (BEC) and invoice fraud targeted SMEs.
- Romance and remote access scams exploited personal vulnerability.
- Deepfake scams and AI-generated impersonations are on the rise, particularly targeting executives and finance teams.
The fraud threat has gone digital, cross-border, and real-time. Traditional controls alone are no longer enough.

Why Fraud Prevention Is a National Priority
Fraud isn't just a financial issue—it’s a matter of public trust. When scams go undetected, victims don’t just lose money—they lose faith in financial institutions, government systems, and digital innovation.
Here’s why fraud prevention is now top of mind in Australia:
- Real-time payments mean real-time risks: With the rise of the New Payments Platform (NPP), funds can move across banks instantly. This has increased the urgency to detect and prevent fraud in milliseconds—not days.
- Rise in money mule networks: Criminal groups are exploiting students, gig workers, and the elderly to launder stolen funds.
- Increased regulatory pressure: AUSTRAC and ASIC are putting more pressure on institutions to identify and report suspicious activities more proactively.
Common Fraud Techniques Seen in Australia
Understanding how fraud works is the first step to preventing it. Here are some of the most commonly observed fraud techniques:
a) Business Email Compromise (BEC)
Fraudsters impersonate vendors, CEOs, or finance officers to divert funds through fake invoices or urgent payment requests. This is especially dangerous for SMEs.
b) Investment Scams
Fake trading platforms, crypto Ponzi schemes, and fraudulent real estate investments have tricked thousands. Often, these scams use fake celebrity endorsements or “guaranteed returns” to lure victims.
c) Romance and Sextortion Scams
These scams manipulate victims emotionally, often over weeks or months, before asking for money. Some even involve blackmail using fake or stolen intimate content.
d) Deepfake Impersonation
Using AI-generated voice or video, scammers are impersonating real people to initiate fund transfers or manipulate staff into giving away sensitive information.
e) Synthetic Identity Fraud
Criminals use a blend of real and fake information to create a new, ‘clean’ identity that can bypass onboarding checks at banks and fintechs.

Regulatory Push for Smarter Controls
Regulators in Australia are stepping up their efforts:
- AUSTRAC has introduced updated guidance for transaction monitoring and suspicious matter reporting, pushing institutions to adopt more adaptive, risk-based approaches.
- ASIC is cracking down on investment scams and calling for platforms to implement stricter identity and payment verification systems.
- The ACCC’s National Anti-Scam Centre launched a multi-agency initiative to disrupt scam operations through intelligence sharing and faster response times.
But even regulators acknowledge: compliance alone won't stop fraud. Prevention needs smarter tools, better collaboration, and real-time intelligence.
A New Approach: Proactive, AI-Powered Fraud Prevention
The most forward-thinking banks and fintechs in Australia are moving from reactive to proactive fraud prevention. Here's what the shift looks like:
✅ Real-Time Transaction Monitoring
Instead of relying on static rules, modern systems use machine learning to flag suspicious behaviour—like unusual payment patterns, high-risk geographies, or rapid account-to-account transfers.
✅ Behavioural Analytics
Understanding what ‘normal’ looks like for each user helps detect anomalies fast—like a customer suddenly logging in from a new country or making a large transfer outside business hours.
✅ AI Copilots for Investigators
Tools like AI-powered investigation assistants can help analysts triage alerts faster, recommend next steps, and even generate narrative summaries for suspicious activity reports.
✅ Community Intelligence
Fraudsters often reuse tactics across institutions. Platforms like Tookitaki’s AFC Ecosystem allow banks to share anonymised fraud scenarios and red flags—so everyone can learn and defend together.
✅ Federated Learning Models
These models allow banks to collaborate on fraud detection algorithms without sharing customer data—bringing the power of collective intelligence without compromising privacy.
Fraud Prevention Best Practices for Australian Institutions
Whether you're a Tier-1 bank or a growing fintech, these best practices are critical:
- Prioritise real-time fraud detection tools that work across payment channels and digital platforms.
- Train your teams—fraudsters are exploiting human error more than technical flaws.
- Invest in explainable AI to build trust with regulators and internal stakeholders.
- Use layered defences: Combine transaction monitoring, device fingerprinting, behavioural analytics, and biometric verification.
- Collaborate across the ecosystem—join industry platforms, share intel, and learn from others.
How Tookitaki Supports Fraud Prevention in Australia
Tookitaki is helping Australian institutions stay ahead of fraud by combining advanced AI with collective intelligence. Our FinCense platform offers:
- End-to-end fraud and AML detection across transactions, customers, and devices.
- Federated learning that enables risk detection with insights contributed by a global network of financial crime experts.
- Smart investigation tools to reduce alert fatigue and speed up response times.
The Role of Public Awareness in Prevention
It’s not just institutions—customers play a key role too. Public campaigns like Scamwatch, educational content from banks, and media coverage of fraud trends all contribute to prevention.
Simple actions like verifying sender details, avoiding suspicious links, and reporting scam attempts can go a long way. In the fight against fraud, awareness is the first line of defence.
Conclusion: Staying Ahead in a Smarter Fraud Era
Fraud prevention in Australia can no longer be treated as an afterthought. The threats are too advanced, too fast, and too costly.
With the right mix of technology, collaboration, and education, Australia can stay ahead of financial criminals—and turn the tide in favour of consumers, businesses, and institutions alike.
Whether it’s adopting AI tools, sharing threat insights, or empowering individuals, fraud prevention is no longer optional. It’s the new frontline of trust.
