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The Rise of AI Adoption for AML Compliance Amid COVID-19

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Tookitaki
31 August 2021
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4 min

Introduction: Embracing AI and ML for AML Compliance in a Challenging Time

Financial institutions increasingly adopt AI and machine learning (ML) technologies for anti-money laundering (AML) compliance in response to the COVID-19 pandemic. A new study by KPMG, SAS, and the Association of Certified Anti-Money Laundering Specialists (ACAMS) found that a third of financial institutions are accelerating their AI and ML adoption for AML purposes.

Key Findings from the ACAMS Survey

The survey primarily asked each respondent how their employer is using or has used technology to detect money laundering. Here are some of the key findings of the survey:

Increasing AI/ML adoption

More than half (57%) of respondents said they have either deployed AI/ML into their AML compliance processes, are piloting AI solutions, or plan to implement them in the next 12-18 months. A quarter of respondents describe themselves as ‘industry leaders’ and ‘innovators’ and 24% as fast followers actively watching the progress of the industry pioneers. Meanwhile, 29% recognise themselves as ‘mainstream adopters’ who generally adopt technology once it has hit critical mass in their industry, and 22% as conservative ‘late adopters’ who resist change as long as they can.

The COVID-19 impact on adoption

39% of the compliance professionals surveyed said their AI/ML adoption plans will continue unchanged, despite the pandemic’s disruption. Meanwhile, 33% say their AI/ML plans have been accelerated and 28% say their timelines have been delayed due to the pandemic. “For institutions on the AI adoption path, they stayed the course with their AI implementation despite COVID impacts and did not derail or slow implementations,” said Tom Keegan, principal US solution leader for financial crimes at KPMG.

The AI/ML impact on AML compliance

There are three ways in which data-driven AI and ML help improve AML compliance: 1) It increases the quality of investigations and regulatory filings, 2) The reduction of false positives and resulting operational costs and 3) It detects complex risks by finding the patterns that traditional transaction monitoring rules cannot.

The AI/ML value proposition

When asked about the areas where AI/ML implementation offers the most value, 39% opted for reduction in false positives and negatives at source for the transaction monitoring process. 38% opted for assistance to investigators to get a better answer more quickly and 22% opted for classification of high and low-risk alerts before they are touched.

AI/ML implementation

When it comes to the implementation of AI/ML solutions, over half (54%) considered advisory firms and/or technology vendors to be the best source for industry best practices on the adoption. Meanwhile, 22% said industry trade organisations are the most trusted source.

Regulatory stance on AI/ML

When asked about their AML regulator’s position on the implementation of AI/ML, 66% said their regulator promotes and encourages these technology innovations. Meanwhile, 28% said their regulator is apprehensive about AI/ML and 6% said their regulator is resistant to change and likely to stick with existing practices.

Small financial institutions are serious about AI/ML

The report revealed that 16% of smaller financial institutions (valued below US$1 billion) view themselves as industry leaders in AI adoption, alongside 28% of large financial institutions (with assets greater than $1 billion). This highlights that advanced technological solutions are also within reach for smaller financial organizations.

Why AI and ML Matter for AML Compliance Now More Than Ever

The potential for artificial intelligence (AI) in the AML compliance space is immense, with several factors driving its increased adoption among financial institutions. The COVID-19 pandemic has brought about a surge in complexity and sophistication of AML threats, as criminals exploit the disruptions caused by the crisis to launder money through innovative means. As a result, financial institutions are now faced with the challenge of detecting and preventing a greater range of money laundering schemes.

In addition to the growing complexity of AML threats, financial institutions must also grapple with vast volumes of data to analyze in their efforts to combat money laundering. This data comes from various sources, including customer transactions, account information, and external databases. The sheer volume of information can be overwhelming for traditional AML systems, which often struggle to process and analyze this data effectively.

Another challenge financial institutions face is the rise in false alerts, which occur when an AML system generates an alert for a transaction that is ultimately determined to be non-risky. False alerts significantly burden compliance teams, as they must investigate each alert thoroughly before determining its legitimacy. This consumes valuable time and resources and can lead to a backlog of alerts waiting to be reviewed.

Furthermore, many financial institutions continue to rely on manual processes for AML compliance, which can be both time-consuming and prone to human error. Manual processes also struggle to keep pace with the rapidly evolving nature of money laundering schemes and regulatory requirements, leaving institutions vulnerable to financial crime.

Compliance costs have ballooned in recent years, with financial institutions facing increasing regulatory scrutiny and hefty fines for non-compliance. This has prompted many institutions to invest in more efficient and effective AML solutions to achieve holistic risk coverage and reduce compliance costs.

Tookitaki’s AI-Powered AML Compliance Platform

Tookitaki offers the Anti-Money Laundering Suite (AMLS). This end-to-end AI-powered AML/CFT solution ensures operational efficiency, low risk, and better returns for the banking and financial services (BFS) industry. The solution is validated by leading global advisory firms and banks across Asia Pacific, Europe, and North America.

Tookitaki's AMLS platform covers three pillars of AML activity:

  • Transaction Monitoring
  • Name and Transaction Screening
  • Customer Risk Assessment

Tookitaki has also developed the Typology Repository to power AMLS with comprehensive financial crime detection capabilities. The repository gathers intelligence from AML experts, regulators, financial institutions, and industry partners worldwide to identify and address new money laundering techniques.

Revamping AML Compliance Programs with Tookitaki

Of course, the pandemic has provided criminals with more opportunities to gain and clean their ill-gotten money. However, financial institutions also have options to reform and turbocharge their AML compliance measures by applying a risk-based approach and using modern technology. 

As money laundering patterns continue to evolve, Tookitaki’s AML compliance solutions, powered by advanced machine learning, can help financial institutions revamp their compliance programs for lower cost of compliance, improved decision accuracy, and better automation of repetitive tasks.

Book a demo of our award-winning AMLS solution by contacting us.

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30 Jul 2025
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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.

20250730_2107_Cybersecurity Precaution Scene_remix_01k1dzk8hwfd4t9rd8mkhzgr1w

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
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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?