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Achieving Holistic Risk Coverage in AML with Tookitaki's Software

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Tookitaki
23 January 2023
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4 min

Anti-Money Laundering (AML) and Counter-Terrorist Financing (CTF) regulations are constantly evolving, making it difficult for financial institutions to stay compliant. The challenge is even greater for fast-scaling digital banks and fintech companies that need to comply with regulations in multiple countries and regions. Traditional AML systems, based on rule-based algorithms, often generate a high number of false positives, leading to increased compliance costs and reduced operational efficiency.

Utilizing Advanced Technologies

Global regulators such as the Financial Action Task Force (FATF) have always stressed on the importance of using modern technologies in AML. Advanced technologies, such as machine learning and big data analytics provide a comprehensive approach to detect and prevent any risks associated with money laundering or other illicit activities. They can be used in multiple AML use cases such as customer screening, transaction monitoring and AML risk assessment. These solutions enable organizations to identify suspicious activity more quickly and efficiently than ever before, therefore providing them with an extra layer of security.

Robust Monitoring Systems

Robust monitoring systems with proper audit trails provide organizations with a comprehensive view of potential money laundering schemes as well as other financial crimes. With vigilant monitoring in place, organizations can effectively mitigate their risk level by ensuring that all suspicious activity is accurately identified and addressed without delay. Additionally, these audits serve as additional evidence of compliance when reporting to regulatory bodies.

Risk Management Strategies

It’s important for organizations to establish clear guidelines for their AML policies and ensure that they are properly implemented across the entire organization. Having a well-defined policy allows companies to effectively manage risk while still maintaining efficient operations at all times. It is also crucial to regularly review existing practices and assess any potential weak spots in order to keep up with the ever-evolving regulations pertaining AML/CFT practices .

The Community Approach to AML

A community-based approach to AML is necessary for financial institutions to achieve holistic risk coverage because it allows for the sharing and analysis of information and intelligence among a group of organizations. This allows for the identification of patterns and trends in financial crime that may not be visible to individual institutions. Furthermore, criminals are becoming increasingly sophisticated in their methods and are able to take advantage of silos that exist in traditional AML systems. A community-based approach allows for the breaking down of these silos and provides a more comprehensive view of financial crime.

Holistic Risk Coverage with Tookitaki AMLS

Tookitaki's FinCense is a comprehensive and end-to-end AML compliance platform designed to assist financial institutions in detecting, preventing and managing financial crimes. The platform is built on a foundation of "collective intelligence," which utilizes the expertise of a network of specialists in various aspects of financial crime to create an exhaustive library of typologies. This enables FinCense to seek out a diverse range of criminal activity.

The IAD version of FinCense is meant for fintech companies, including digital banks, e-wallets, and payment services companies, while the SAM version is meant for large traditional banks. With the use of advanced technologies and robust monitoring systems, these modules of FinCense provide financial institutions with holistic risk coverage and enable them to stay ahead of the curve in their compliance efforts.

AMLS comprises of four modules – Transaction Monitoring, Smart Screening, Customer Risk Scoring and Case Manager – that are optimized for Intelligent Alert Detection (IAD) and Smart Alert Management (SAM).

  • Transaction Monitoring: This module helps financial institutions identify and detect suspicious transactions, using advanced analytics and machine learning techniques. It also allows for the customization of transaction monitoring rules to meet specific regulatory requirements.
  • Smart Screening: This module helps financial institutions screen customers and transactions against various sanctions lists, watchlists, and other regulatory lists to ensure compliance with AML regulations. It also uses natural language processing (NLP) and machine learning to reduce false positives.
  • Customer Risk Scoring: This module helps financial institutions assess and manage customer risk by analyzing various data points, such as transaction history and demographic information. It also uses machine learning algorithms to continuously update and evolve customer risk profiles.
  • Case Manager: This module helps financial institutions streamline their AML compliance workflow by providing a centralized platform for case management and reporting. It allows for easy assignment, disposition, and reporting of cases, as well as the integration of data from other AMLS modules.

Tookitaki’s Community-based Approach

Tookitaki's community-based approach is based on the principle that financial crime risks are not restricted to individual financial institutions. Rather, these risks are interrelated and can be better understood by sharing information and intelligence across a community of financial institutions.

The Anti-Financial Crime (AFC) ecosystem is a separate entity, a growing community of anti-financial crime experts, born from Tookitaki’s vision for safety & security. Its goal is to discover the hidden money trails of criminals. Similar to global monitoring & policy-making institutions, the AFC ecosystem is a body of experts covering the entire spectrum of money-laundering. Their wealth of experience is operationalized to enable partner financial institutions in uncovering money trails which aren’t discoverable by today’s standards.

Tookitaki's software is powered by a collective intelligence of typologies, generated by the AFC Ecosystem, that provides the latest risk scenarios specific to each region. This allows financial institutions to stay ahead of the curve with the latest financial crime scenarios, regardless of the country or region they operate in.

Enhance Your Risk Coverage with FinCense

Tookitaki’s AML software provides holistic risk coverage for financial institutions in combating money laundering. Its community-based approach and range of modules enable financial institutions to stay compliant in today’s ever changing environment and uncover hidden money trails while also maximizing operational efficiency. If you're interested in learning more about how Tookitaki's FinCense can help your financial institution, request a demo today!

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Blogs
30 Jul 2025
5 min
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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.

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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.

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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:

  1. Prioritise real-time fraud detection tools that work across payment channels and digital platforms.
  2. Train your teams—fraudsters are exploiting human error more than technical flaws.
  3. Invest in explainable AI to build trust with regulators and internal stakeholders.
  4. Use layered defences: Combine transaction monitoring, device fingerprinting, behavioural analytics, and biometric verification.
  5. 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.

Cracking Down Under: How Australia Is Fighting Back Against Fraud
Blogs
29 Jul 2025
6 min
read

The CEO Wasn’t Real: Inside Singapore’s $499K Deepfake Video Scam

In March 2025, a finance director at a multinational firm in Singapore authorised a US$499,000 payment during what appeared to be a Zoom call with the company’s senior leadership. There was just one problem: none of the people on the call were real.

What seemed like a routine virtual meeting turned out to be a highly orchestrated deepfake scam, where cybercriminals used artificial intelligence to impersonate the company’s Chief Financial Officer and other top executives. The finance director, believing the request was genuine, wired nearly half a million dollars to a fraudulent account.

The incident has sent shockwaves across the financial and corporate world, underscoring the fast-evolving threat of deepfake technology.

Background of the Scam

According to Singapore police reports, the finance executive received a message from someone posing as the company’s UK-based CFO. The message requested an urgent fund transfer to facilitate a confidential acquisition. To build credibility, the fraudster set up a Zoom call — featuring multiple senior executives, all appearing and sounding authentic.

But the entire video call was fabricated using deepfake technology.

These weren’t just stolen profile photos; they were AI-generated likenesses with synced facial movements and realistic voices, mimicking actual executives. The finance director, seeing what seemed like familiar faces and hearing familiar voices, followed through with the transfer.

Only later did the company realise that the actual executives had never been on the call.

What the Case Revealed

This wasn’t just another phishing email or spoofed WhatsApp message. This was next-level digital deception. Here’s what made it chillingly effective:

  • Multi-party deepfake execution – The fraud involved several synthetic identities, all rendered convincingly in real-time to simulate a legitimate boardroom environment.
  • High-level impersonation – Senior figures like the CFO were cloned with accurate visual and vocal characteristics, heightening the illusion of authority and urgency.
  • Deeply contextual manipulation – The scam leveraged business context (e.g. M&A activity, board-level communications) that suggested insider knowledge.

Singapore’s police reported this as one of the most convincing cases of AI-powered impersonation seen to date — and issued a national warning to corporations and finance professionals.

Impact on Financial Institutions and Corporates

While the fraud targeted one company, its implications ripple across the entire financial system:

Deepfake Fatigue and Trust Erosion

When even video calls are no longer trustworthy, confidence in digital communication takes a hit. This undermines both internal decision-making and external client relationships.

CFOs and Finance Teams in the Crosshairs

Finance and treasury teams are prime targets for scams like this. These professionals are expected to act fast, handle large sums, and follow instructions from the top — making them vulnerable to high-pressure frauds.

Breakdown of Traditional Verification

Emails, video calls, and even voice confirmations can be falsified. Without secondary verification protocols, companies remain dangerously exposed.

ChatGPT Image Jul 29, 2025, 02_34_13 PM

Lessons Learned from the Scam

The Singapore deepfake case isn’t an outlier — it’s a glimpse into the future of financial crime. Key takeaways:

  1. Always Verify High-Value Requests
    Especially those involving new accounts or cross-border transfers. A secondary channel of verification — via phone or an encrypted app — is now a must.
  2. Educate Senior Leadership
    Executives need to be aware that their digital identities can be hijacked. Regular briefings on impersonation risks are essential.
  3. Adopt Real-Time Behavioural Monitoring
    Advanced analytics can flag abnormal transaction patterns — even when the request appears “approved” by an authority figure.
  4. Invest in Deepfake Detection Tools
    There are now software solutions that scan video content for artefacts, inconsistencies, or signs of AI manipulation.
  5. Strengthen Internal Protocols
    Critical payment workflows should always require multi-party authorisation, escalation logic, and documented rationale.

The Role of Technology in Prevention

Scams like this are designed to outsmart conventional defences. A new kind of defence is required — one that adapts in real-time and learns from emerging threats.

This is where Tookitaki’s compliance platform, FinCense, plays a vital role.

Powered by the AFC Ecosystem and Agentic AI:

  • Typology-Driven Detection: FinCense continuously updates its detection logic based on real-world scam scenarios contributed by financial crime experts worldwide.
  • AI-Powered Simulation: Institutions can simulate deepfake-driven fraud scenarios to test and refine their internal controls.
  • Federated Learning: Risk signals and red flags from across institutions are shared securely without compromising sensitive data.
  • Smart Case Disposition: Agentic AI reviews and narrates alerts, allowing compliance officers to respond faster and with greater clarity — even in complex scams like this.
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Moving Forward: Facing the Synthetic Threat Landscape

Deepfake technology has moved from the realm of novelty to real-world risk. The Singapore incident is a wake-up call for companies across ASEAN and beyond.

When identity can be faked in real-time, and fraudsters learn faster than regulators, the only defence is to stay ahead — with intelligence, collaboration, and next-generation tech.

Because next time, the CEO might not be real, but the money lost will be.

The CEO Wasn’t Real: Inside Singapore’s $499K Deepfake Video Scam
Blogs
28 Jul 2025
6 min
read

The Rising Cost of AML Compliance in Australia: Can Smarter Tools Reduce the Burden?

Anti-Money Laundering (AML) compliance in Australia has never been more critical — or more expensive.

As regulatory scrutiny increases and financial crime becomes more complex, financial institutions are under pressure to spend more time, money, and resources just to keep up.

But is this sustainable? And is there a smarter way to stay compliant without letting costs spiral out of control?

Let’s take a closer look at why compliance costs are rising, what’s at stake for banks and fintechs in Australia, and how modern AML solutions, powered by AI and collaboration, are helping institutions future-proof their compliance programmes.

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Why Are AML Compliance Costs Rising in Australia?

Over the past few years, Australia has seen a surge in regulatory activity around financial crime. From high-profile casino investigations to AUSTRAC’s growing enforcement role, the message is clear: AML compliance is non-negotiable.

Here’s what’s driving the rising cost:

1. Tighter Regulatory Expectations

AUSTRAC expects more than just basic transaction monitoring. Institutions must demonstrate proactive risk assessments, tailored customer due diligence (CDD), and robust ongoing monitoring — all supported by detailed documentation and audit trails.

2. More Complex Financial Crime

Criminals are getting smarter. Whether it’s mule networks exploiting instant payments or layering funds across crypto and traditional channels, detecting illicit activity now requires more sophisticated tools and deeper data insights.

3. Manual Workflows and Legacy Systems

Many institutions still rely on outdated systems and siloed processes, which increase the burden on compliance teams and inflate operational costs. Manually reviewing false positives or investigating fragmented alerts takes time — and people.

4. Reputational Risk and Fines

In recent years, enforcement actions have brought AML failures into public view — from Crown and Star casinos to financial institutions under investigation. The reputational damage, legal risk, and remediation costs far outweigh the cost of modernising compliance infrastructure.

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What Do Rising AML Costs Look Like on the Ground?

According to industry estimates, large Australian banks are spending hundreds of millions annually on compliance-related activities. Mid-sized banks and fintechs may not face the same scale, but they often carry a disproportionate burden due to leaner teams and tighter budgets.

Here’s where the costs add up:

  • Hiring and retaining skilled AML staff
  • Managing alert fatigue from legacy monitoring systems
  • Frequent audits and remediation exercises
  • Technology upgrades and consultant fees
  • Delays in customer onboarding due to manual CDD reviews

These costs aren’t just financial — they also affect speed, agility, and customer experience.

Can Smarter Tools Reduce the Burden?

The short answer: yes — but only if they’re the right tools.

Smarter AML compliance doesn't mean more tools. It means better tools that are purpose-built for modern financial crime risks. Here's what that looks like:

What Smarter AML Compliance Looks Like

1. Behavioural Transaction Monitoring

Modern systems go beyond rule-based monitoring to detect suspicious patterns based on behaviour. This reduces false positives and increases detection accuracy — freeing up analysts to focus on what matters.

2. Federated Learning and Shared Intelligence

Collaborative platforms enable institutions to share insights and typologies without sharing sensitive data. This reduces blind spots and helps detect new risks earlier — especially in cross-border and real-time payments.

3. Automation and AI Assistants

AI-powered investigation assistants can summarise alerts, prioritise high-risk cases, and auto-generate audit trails — helping compliance teams do more with less.

4. Dynamic Risk Scoring

Instead of static scoring, smarter systems update customer risk profiles in real-time based on behaviour, location, transaction type, and other dynamic inputs.

5. Plug-and-Play Integration

Modern AML solutions should integrate easily with core banking systems, customer onboarding tools, and case management platforms — reducing overhead and ensuring a seamless compliance workflow.

How Tookitaki’s FinCense Is Helping Australian Institutions Stay Ahead

At Tookitaki, we’ve designed FinCense to deliver smarter compliance — not just cheaper, but better.

Built on a modular, federated AI framework, FinCense empowers banks, fintechs, and payment platforms to stay ahead of financial crime risks without overburdening teams or budgets.

With FinCense, institutions get:

  • Up to 72% reduction in false positives
  • 3.5x faster case resolutions
  • Real-time, scenario-based monitoring tailored to local risks
  • Federated typology sharing via the AFC Ecosystem
  • Smart Disposition engine for audit-ready alert summaries

Whether you're dealing with domestic mule activity, complex layering, or regulatory audits — FinCense helps you detect, investigate, and respond with speed, accuracy, and confidence.

The Stakes Are Higher Than Ever

Financial crime is evolving rapidly, and so is the regulatory bar. But throwing more people, more tools, and more money at the problem isn’t the answer.

The future of AML compliance in Australia lies in smarter systems, collaborative intelligence, and scalable solutions that adapt as the threat landscape changes.

Final Thought

Rising AML compliance costs don’t have to mean rising pain.

With the right technology, institutions in Australia can reduce risk, improve efficiency, and build lasting trust with regulators and customers alike.

If you're ready to reduce the cost and complexity of compliance, without compromising on quality — Tookitaki is here to help.

The Rising Cost of AML Compliance in Australia: Can Smarter Tools Reduce the Burden?