Compliance Hub

Transforming Compliance: AI in AML and Fraud Detection

Site Logo
Tookitaki
5 min
read

In the complex world of financial crime, Anti-Money Laundering (AML) and fraud detection plays a pivotal role.

It's a critical line of defense for financial institutions, helping to prevent money laundering and ensure regulatory compliance.

However, the landscape of AML fraud detection is constantly evolving.

New technologies, emerging threats, and shifting regulations present both challenges and opportunities for financial crime investigators.

This article aims to navigate these complexities, providing insights into the latest trends and technologies in AML fraud detection.

A graphic representation of AML fraud detection

Whether you're an investigator, a compliance officer, or an AML professional, you'll find practical applications and real-world examples to enhance your strategies and techniques.

The Critical Role of AML Fraud Detection in Financial Institutions

AML fraud detection is a cornerstone of risk management in financial institutions.

It's not just about preventing financial crimes like card fraud and account takeover.

AML fraud detection is also about ensuring compliance with regulations designed to prevent money laundering.

Non-compliance can result in hefty fines and reputational damage, making AML fraud detection a top priority for financial institutions.

In essence, AML fraud detection is a vital tool for maintaining the integrity of financial systems and protecting institutions from financial and reputational harm.

Challenges in AML Fraud Detection: Keeping Pace with Technological Advancements

The landscape of financial crime is constantly evolving, presenting significant challenges for AML fraud detection.

Criminals are becoming increasingly sophisticated, leveraging new technologies and methods to carry out illicit activities.

This rapid evolution requires financial crime investigators to stay abreast of the latest trends and technologies in the fintech industry.

However, keeping up with these advancements can be a daunting task.

Despite these challenges, staying updated is crucial for enhancing investigative techniques and strategies, and ultimately, for preventing financial crimes.

{{cta-first}}

Risk Management: A Core Component of AML Strategies

Risk management is a fundamental aspect of AML strategies.

It involves identifying, assessing, and mitigating the risks associated with money laundering and other financial crimes.

This process requires a deep understanding of the various types of financial crimes, including card fraud and account takeover.

By effectively managing these risks, financial institutions can enhance their AML compliance and fraud detection capabilities.

The Rise of Machine Learning and Artificial Intelligence in AML

The use of machine learning and artificial intelligence (AI) in AML is a game-changer.

These technologies offer improved detection capabilities, enabling financial institutions to identify suspicious activities more accurately and efficiently.

Machine learning algorithms can analyze vast amounts of data, identifying patterns and anomalies that may indicate fraudulent activity.

AI, on the other hand, can automate complex decision-making processes, reducing the workload for AML professionals.

Features Engineering: Crafting Predictive Variables from Raw Data

Features engineering is a critical process in AML systems.

It involves creating predictive variables from raw data, which can then be used by machine learning models to detect potential fraud.

This process requires a deep understanding of the data and the types of financial crimes that the institution is trying to prevent.

By effectively engineering features, financial institutions can enhance their AML fraud detection capabilities, making their systems more accurate and efficient.

The Shift from Rules-Based to Dynamic, Real-Time AML Systems

Traditional AML systems have been rules-based, relying on predefined criteria to flag potential fraud.

However, these systems are increasingly being supplemented with machine learning models.

This shift is driven by the need for more dynamic and adaptable AML systems that can keep pace with the evolving tactics of criminals.

Real-time detection is a key feature of these modern AML systems, enabling financial institutions to respond to potential fraud more quickly and effectively.

Detecting Suspicious Activities: The Real-Time Imperative

Detecting suspicious activities in real-time is a critical goal of modern AML systems.

By identifying and flagging suspicious transactions as they occur, institutions can prevent fraud more effectively.

Real-time detection also allows for quicker response times, which can be crucial in preventing significant financial losses.

However, achieving real-time detection requires robust systems and processes, as well as continuous monitoring and updating to ensure that the AML system remains effective against new and emerging threats.

Emerging Threats: Synthetic Identity and Other Evolving Risks

In the ever-evolving landscape of financial crime, new threats are constantly emerging.

One such threat is synthetic identity fraud, a complex type of fraud that involves the creation of a fictitious identity using a combination of real and fabricated information.

Detecting synthetic identity fraud poses a significant challenge for financial institutions, as these identities can often pass traditional verification checks.

To combat this and other evolving risks, AML systems must be equipped with advanced detection capabilities and must be regularly updated to keep pace with the latest fraud tactics.

{{cta-ebook}}

AML Compliance: Balancing Customer Experience with Robust Controls

AML compliance is a critical aspect of any financial institution's operations. It involves implementing robust controls to prevent money laundering and comply with regulatory requirements.

However, these controls must be balanced with the need to provide a seamless customer experience. Overly stringent controls can lead to customer dissatisfaction and potential loss of business.

For instance, false positives in fraud detection can lead to unnecessary delays and inconvenience for legitimate customers. Therefore, AML systems must be designed to minimize false positives while still effectively detecting fraudulent activities.

In essence, the challenge lies in creating an AML system that is both effective in fraud detection and efficient in its operations, ensuring customer satisfaction while maintaining regulatory compliance.

The Future of AML Fraud Detection: Predictive Analytics and Global Cooperation

The future of AML fraud detection lies in leveraging advanced technologies like predictive analytics. Predictive analytics uses historical data to forecast potential future events. In the context of AML, it can help identify patterns that may indicate potential money laundering activities before they occur.

Another key aspect of the future of AML is global cooperation. Financial crimes are not confined to national borders. They often involve complex networks that span multiple countries. Therefore, global cooperation is essential in combating these crimes.

This cooperation can take various forms, including information sharing between financial institutions and regulatory bodies, and standardisation of AML regulations across different jurisdictions. By working together, we can create a more effective global AML framework that is capable of combating the increasingly sophisticated methods used by criminals.

Conclusion: Staying Ahead in the Fight Against Financial Crime

The fight against financial crime is a constant battle. As criminals evolve their tactics, so too must financial institutions and their AML strategies. Staying ahead requires a combination of advanced technology such as Tookitaki's FinCense, robust processes, and skilled professionals.

It also requires a proactive approach. Rather than simply reacting to crimes after they occur, financial institutions must anticipate potential threats and take steps to prevent them. This requires continuous learning, adaptation, and innovation.

In the end, the goal of AML is not just to prevent financial crime. It's to protect the integrity of our financial systems, maintain public trust, and contribute to a safer, more secure society.

By submitting the form, you agree that your personal data will be processed to provide the requested content (and for the purposes you agreed to above) in accordance with the Privacy Notice

success icon

We’ve received your details and our team will be in touch shortly.

In the meantime, explore how Tookitaki is transforming financial crime prevention.
Learn More About Us
Oops! Something went wrong while submitting the form.

Ready to Streamline Your Anti-Financial Crime Compliance?

Our Thought Leadership Guides

Blogs
29 Aug 2025
5 min
read

AML Vendors in Australia: How to Choose the Right Partner in 2025

With AUSTRAC raising the bar on compliance, choosing the right AML vendor is no longer just a tech decision — it’s a strategic one.

The financial crime landscape in Australia is evolving at lightning speed. Fraudsters are exploiting the New Payments Platform (NPP), crypto exchanges, and cross-border corridors to launder billions. At the same time, AUSTRAC is demanding more from financial institutions, issuing record fines for compliance failures.

In this environment, financial institutions, fintechs, and remittance providers need more than just software. They need reliable AML vendors who can deliver cutting-edge technology, regulatory alignment, and ongoing support. But with so many options on the market, how do you choose the right one?

This blog explores the role of AML vendors, what to look for in a partner, common pitfalls to avoid, and how leading solutions like Tookitaki’s FinCense are changing the compliance game in Australia.

Talk to an Expert

Why AML Vendors Matter More Than Ever

1. Regulatory Scrutiny

AUSTRAC expects institutions to demonstrate not just compliance frameworks, but effective systems. Vendors that can’t prove effectiveness expose institutions to both regulatory and reputational risk.

2. Real-Time Payment Risks

NPP enables instant fund transfers, which fraudsters use to layer funds rapidly. AML vendors must provide real-time monitoring, not overnight batch processing.

3. Expanding Typologies

From mule networks and shell companies to crypto layering and trade-based laundering, criminal methods are growing more complex. AML vendors must constantly update detection capabilities.

4. Rising Costs of Compliance

AML compliance is among the largest operational expenses for Australian institutions. Vendors who reduce false positives and automate reporting can save millions.

What Do AML Vendors Provide?

At their core, AML vendors deliver technology and expertise to help institutions detect, prevent, and report financial crime. Their solutions typically cover:

  • Transaction monitoring (real-time and batch)
  • Customer onboarding and CDD/KYC
  • Sanctions and PEP screening
  • Case management workflows
  • Regulatory reporting (SMRs, TTRs, IFTIs)
  • AI and machine learning for anomaly detection
  • Audit trails and explainability

The best AML vendors also provide local compliance expertise, ongoing updates, and typology intelligence to ensure institutions stay ahead of both regulators and criminals.

ChatGPT Image Aug 26, 2025, 10_00_20 AM

Key Qualities of Top AML Vendors

1. AUSTRAC Compliance Alignment

The vendor must fully align with the AML/CTF Act requirements, including suspicious matter reporting and record-keeping.

2. Real-Time Monitoring

Essential for detecting suspicious activity across instant payments, remittance corridors, and cross-border transactions.

3. AI-Powered Detection

Advanced vendors offer machine learning and anomaly detection to reduce false positives and catch unknown patterns.

4. End-to-End Coverage

From onboarding to investigation, vendors should provide a unified platform covering all AML needs.

5. Explainability & Transparency

Glass-box AI and detailed audit trails ensure compliance teams can explain decisions to regulators.

6. Scalability & Flexibility

The solution must work for Tier-1 banks and fast-scaling fintechs alike. Cloud-native platforms are a plus.

7. Ongoing Support

Vendors should offer training, scenario updates, and local compliance support — not just software deployment.

Pitfalls to Avoid When Choosing AML Vendors

  • Choosing on Price Alone: Low-cost solutions may lack the intelligence and scalability to meet AUSTRAC standards.
  • Overlooking Integration: Systems that don’t integrate smoothly with existing banking cores and case management tools create operational bottlenecks.
  • Ignoring Update Frequency: Vendors who don’t regularly update typologies leave institutions exposed to new threats.
  • Black-Box AI: Lack of explainability increases regulatory risk.

Questions to Ask Potential AML Vendors

  1. How do you align with AUSTRAC compliance requirements?
  2. Do you provide real-time monitoring for NPP transactions?
  3. How do you reduce false positives compared to traditional systems?
  4. Can investigators access explainable alerts and audit trails?
  5. Do you provide ongoing typology updates and training?
  6. What is your track record in the Australian market?

Top Trends Among AML Vendors in 2025

  • Federated Intelligence Sharing: Vendors offering anonymised data sharing across institutions to detect emerging threats.
  • Agentic AI Assistants: Vendors embedding AI copilots to guide investigators in real time.
  • Simulation Engines: Ability to test new detection rules before live deployment.
  • Cross-Channel Risk Visibility: Unified monitoring across banking, payments, trade finance, and crypto.

Spotlight: Tookitaki as a Leading AML Vendor

Tookitaki’s FinCense is positioning itself among the top AML vendors in Australia by offering more than just compliance software:

  • Real-Time Monitoring: Detects fraud and laundering across NPP and cross-border corridors.
  • Agentic AI: Learns from evolving typologies while keeping false positives low.
  • Federated Learning: Insights from the AFC Ecosystem — a global community sharing real-world typologies.
  • FinMate AI Copilot: Generates case summaries, recommends actions, and supports faster investigations.
  • Audit-Ready Compliance: SMRs, TTRs, and detailed audit trails aligned with AUSTRAC standards.
  • End-to-End Platform: Covers onboarding, screening, monitoring, investigations, and reporting.

FinCense isn’t just a tool — it’s a trust layer that helps institutions build resilience, reduce compliance costs, and stay one step ahead of criminals.

Case Study Example: A Regional Australian Bank

A community-owned bank in Australia faced mounting compliance costs and a backlog of false positives. After deploying Tookitaki’s FinCense:

  • False positives dropped by 65%
  • Investigation speed doubled with FinMate’s summaries
  • AUSTRAC audit preparation time reduced from weeks to hours

The result? Lower costs, faster compliance, and stronger customer trust.

Future Outlook for AML Vendors in Australia

  • Closer Regulator Collaboration: Vendors working directly with AUSTRAC to ensure local alignment.
  • AI-First Compliance: Tools moving beyond rules to AI-powered, predictive monitoring.
  • Industry Collaboration: Shared platforms to combat mule networks and cross-border scams.
  • Sustainability: Vendors focusing on cost reduction and efficiency as compliance costs rise.

Conclusion: Choose Vendors That Build Trust, Not Just Tools

For Australian financial institutions, choosing the right AML vendor is a decision that goes beyond software. It’s about securing compliance, building trust, and preparing for an increasingly fast and complex financial crime landscape.

Pro tip: Evaluate vendors not just on features, but on their ability to evolve with both AUSTRAC’s expectations and criminal innovation. The right partner will save money, reduce risk, and future-proof your compliance programme.

AML Vendors in Australia: How to Choose the Right Partner in 2025
Blogs
27 Aug 2025
6 min
read

Fraud Prevention in the Banking Industry: The Australian Perspective

As fraud evolves in speed and sophistication, Australian banks must adopt smarter prevention strategies to protect customers and maintain trust.

Fraud has always been a challenge for banks, but in Australia today, it has become one of the most pressing risks facing the financial sector. With the rise of digital banking, real-time payments through the New Payments Platform (NPP), and cross-border transactions, fraudsters have more opportunities than ever to exploit vulnerabilities.

For banks, preventing fraud is no longer a compliance exercise. It is a business-critical function that directly affects profitability, reputation, and customer trust. This blog takes a closer look at fraud prevention in the banking industry, exploring the risks, regulatory expectations, and the most effective solutions being deployed in Australia.

Talk to an Expert

The Rising Tide of Banking Fraud in Australia

1. The Cost of Fraud to Australians

In 2024, Australians lost more than AUD 3 billion to scams and fraud, according to Scamwatch. A significant portion of these losses flowed through bank accounts, often enabled by authorised push payment (APP) scams and mule networks.

2. Real-Time Payments, Real-Time Risks

The NPP has made everyday banking faster and more convenient, but it has also given fraudsters a new tool. With funds moving instantly, banks have less time to detect suspicious activity, making proactive prevention critical.

3. Sophisticated Criminal Typologies

Fraudsters are no longer lone operators. They work in syndicates, often crossing borders and using advanced tactics such as deepfake impersonations, synthetic identities, and account takeover fraud.

4. Regulatory Scrutiny

AUSTRAC and ASIC have made it clear that banks are expected to have strong fraud prevention frameworks in place. Failing to act not only exposes banks to financial losses but also to regulatory penalties and reputational damage.

Common Types of Banking Fraud in Australia

1. Account Takeover (ATO)

Fraudsters gain control of a customer’s account through phishing, malware, or stolen credentials, then move funds instantly.

2. Authorised Push Payment (APP) Scams

Victims are tricked into authorising payments, often to mule accounts controlled by fraud syndicates.

3. Card Fraud

Both card-present and card-not-present fraud remain prevalent, especially in e-commerce channels.

4. Mule Accounts

Fraudsters use networks of mule accounts to layer and obscure illicit funds. These may be controlled by syndicates or unwitting participants.

5. Insider Fraud

Employees with access to sensitive systems may abuse their position to commit fraud, often in collusion with external actors.

6. Trade and Cross-Border Fraud

International corridors expose Australian banks to risks of trade-based money laundering and fraudulent remittance activity.

Red Flags Banks Must Monitor

  • Sudden changes in transaction behaviour, such as rapid high-value transfers.
  • Accounts that act as pass-throughs, with funds entering and exiting immediately.
  • Multiple accounts linked to the same device or IP address.
  • Customers reluctant to provide source-of-funds documentation.
  • Transfers to newly created or suspicious beneficiary accounts.
  • Unusual login behaviour, such as logins from overseas followed by transactions.

Regulatory Expectations on Fraud Prevention

Australian regulators expect banks to take a proactive, technology-led approach to fraud prevention.

  • AUSTRAC: Requires banks to have robust monitoring systems capable of detecting suspicious activity in real time, especially under the AML/CTF Act.
  • ASIC: Focuses on consumer protection, particularly in cases of APP scams where customers are tricked into transferring funds.
  • Australian Banking Association (ABA): Works with industry participants to develop shared frameworks for fraud detection and scam reimbursement models.
ChatGPT Image Aug 26, 2025, 01_52_51 PM

Best Practices for Fraud Prevention in the Banking Industry

1. Real-Time Transaction Monitoring

Banks must monitor every transaction in real time, scoring risk within milliseconds. This is essential for instant payments under the NPP.

2. AI and Machine Learning

AI-driven systems can adapt to new typologies, reduce false positives, and detect anomalies beyond static rules.

3. Behavioural Analytics

Studying how customers interact with banking platforms helps detect account takeover attempts or bot-driven fraud.

4. Strong Customer Authentication (SCA)

Multi-factor authentication, biometrics, and device fingerprinting reduce the likelihood of unauthorised access.

5. Network and Entity Analysis

By linking accounts, devices, and transactions, banks can uncover hidden mule networks.

6. Integrated Case Management

Centralised investigation platforms streamline workflows, enabling faster decisions and regulator-ready reports.

7. Collaboration and Intelligence Sharing

Banks must work together, sharing fraud data and typologies. Collaborative intelligence strengthens the sector’s resilience against syndicates.

Challenges Facing Banks in Fraud Prevention

  • Balancing Security and Customer Experience: Overly strict controls may frustrate customers, while lax controls create vulnerabilities.
  • Cost of Compliance: Implementing advanced fraud systems is expensive, but far cheaper than paying fines or losing trust.
  • Talent Shortages: Skilled fraud investigators and compliance professionals are in short supply in Australia.
  • Evolving Criminal Tactics: Fraudsters innovate constantly, forcing banks to remain agile and adaptive.

The Role of Technology in Modern Fraud Prevention

Technology is at the heart of modern fraud prevention strategies. Banks are increasingly turning to advanced solutions that combine AI, machine learning, and federated intelligence.

AI-Powered Detection

Machine learning models reduce false positives and detect new fraud patterns without manual intervention.

Federated Learning

Through networks like the AFC Ecosystem, banks can share anonymised typology data, improving detection across the industry without exposing sensitive customer data.

Agentic AI Assistants

AI copilots can summarise cases, recommend next steps, and assist investigators, saving valuable time.

Simulation Engines

Banks can test fraud scenarios against historical data before deploying detection rules live.

Case Example: Community-Owned Banks Leading the Way

Community-owned banks like Regional Australia Bank and Beyond Bank are adopting advanced fraud and AML solutions to strengthen their defences. By leveraging technology platforms such as Tookitaki’s FinCense, these banks are:

  • Detecting mule networks in real time.
  • Reducing false positives and investigation workload.
  • Staying AUSTRAC-ready with explainable alerts and automated reporting.
  • Demonstrating that even mid-sized banks can lead in compliance innovation.

These examples highlight that fraud prevention is not just for Tier-1 banks. Institutions of all sizes can leverage advanced tools to protect their customers and build trust.

Spotlight: Tookitaki’s FinCense for Fraud Prevention

FinCense, Tookitaki’s end-to-end compliance platform, is designed to address the challenges of modern fraud prevention in the banking industry.

  • Real-Time Monitoring: Detects fraud instantly across NPP and cross-border transactions.
  • Agentic AI: Continuously adapts to new fraud typologies with minimal false positives.
  • Federated Intelligence: Accesses real-world scenarios from a global community of compliance experts.
  • FinMate AI Copilot: Summarises cases and recommends actions for investigators.
  • Regulator-Ready Reporting: AUSTRAC compliance built in, with detailed audit trails.
  • Cross-Channel Coverage: Banking transfers, cards, wallets, and crypto monitored from a single platform.

By unifying fraud prevention and AML functions, FinCense reduces operational costs while strengthening resilience against financial crime.

The Future of Fraud Prevention in Australian Banking

Looking ahead, several trends will shape how banks approach fraud prevention:

  • Expansion of PayTo: As this NPP feature grows, new fraud typologies will emerge.
  • Rise of Deepfake Scams: Voice and video impersonation will challenge traditional controls.
  • Shared Fraud Databases: Banks will increasingly collaborate to stop scams mid-flight.
  • Cross-Border Intelligence: With Australia connected to Southeast Asia, cross-border monitoring will be vital.
  • Sustainability of Compliance: AI and automation will help reduce the cost of compliance while improving outcomes.

Conclusion

Fraud prevention in the banking industry is no longer optional or secondary. In Australia’s real-time, always-on financial environment, it is a strategic imperative. Banks that fail to act face not only financial losses but also reputational damage and regulatory penalties.

The path forward lies in adopting real-time, AI-powered fraud prevention platforms that combine detection, investigation, and compliance in a single ecosystem. Community-owned banks like Regional Australia Bank and Beyond Bank are already proving that with the right technology, any institution can meet the challenges of modern fraud.

Pro tip: Don’t just invest in fraud detection. Invest in fraud prevention solutions that adapt, scale, and build trust with your customers.

Fraud Prevention in the Banking Industry: The Australian Perspective
Blogs
26 Aug 2025
6 min
read

Fraud Screening Tools in Australia: Smarter Defences for a Real-Time World

With fraud losses crossing billions, Australian institutions need smarter fraud screening tools to protect both compliance and customer trust.

Fraud is now one of the biggest threats facing Australia’s financial system. Scamwatch data shows Australians lost over AUD 3 billion in 2024 to scams — a figure that continues to rise with digital banking adoption and real-time payment rails like the New Payments Platform (NPP).

Traditional fraud systems, built on static rules, simply can’t keep pace. That’s why financial institutions are turning to fraud screening tools powered by AI and behavioural intelligence to screen transactions, customers, and devices in real time.

But what exactly are fraud screening tools, and how should Australian businesses evaluate them?

Talk to an Expert

What Are Fraud Screening Tools?

Fraud screening tools are systems that automatically review transactions, user activity, and onboarding data to identify and block potentially fraudulent activity. They act as gatekeepers — scoring risk in milliseconds and deciding whether to approve, block, or escalate.

They’re used across industries:

  • Banks & Credit Unions: Screening wire transfers, cards, and online banking logins.
  • Fintechs: Vetting high volumes of digital onboarding and payment activity.
  • Remittance Providers: Screening cross-border corridors for fraud and laundering.
  • E-commerce Platforms: Stopping card-not-present fraud and refund abuse.
  • Crypto Exchanges: Detecting suspicious wallets and transaction flows.

Why Fraud Screening Tools Are Critical in Australia

1. Instant Payments Raise the Stakes

The NPP enables near-instant transactions. Fraudsters exploit this speed to move funds through mule accounts before detection. Tools must screen transactions in real time, not in batch.

2. Scam Surge in Social Engineering

Romance scams, impersonation fraud, and deepfake-driven attacks are spiking. Many involve “authorised push payments” where victims willingly transfer money. Screening tools must flag unusual transfer behaviour even when the customer approves it.

3. Regulatory Expectations

ASIC and AUSTRAC expect robust fraud and AML screening. Institutions must prove that they have effective, adaptive screening tools — not just compliance checklists.

4. Rising Cost of Compliance

Investigating false positives consumes massive resources. The right screening tools should cut operational costs by reducing unnecessary alerts.

Key Features of Effective Fraud Screening Tools

1. Real-Time Transaction Analysis

  • Millisecond-level scoring of payments, logins, and device sessions.
  • Monitors velocity (multiple payments in quick succession), device fingerprints, and geo-location mismatches.

2. AI & Machine Learning Models

  • Detect anomalies beyond static rule sets.
  • Learn continuously from confirmed fraud cases.
  • Reduce false positives by distinguishing genuine unusual behaviour from fraud.

3. Behavioural Biometrics

  • Analyse how users type, swipe, or navigate apps.
  • Identify “bots” and fraudsters impersonating legitimate customers.

4. Multi-Channel Coverage

  • Banking transfers, cards, digital wallets, remittances, and crypto — all screened in one platform.

5. Customer & Merchant Screening

  • KYC/KYB integration to verify identity documents.
  • Sanctions, PEP, and adverse media screening.

6. Explainability & Audit Trails

  • “Glass-box” AI ensures every flagged transaction comes with a clear reason code for investigators and regulators.

7. Case Management Integration

  • Alerts are fed directly into case management systems, enabling investigators to act quickly.
ChatGPT Image Aug 25, 2025, 12_31_37 PM

How Fraud Screening Tools Detect Common Threats

Account Takeover (ATO)

  • Detects logins from unusual devices or IPs.
  • Flags high-value transfers after suspicious logins.

Mule Networks

  • Screens for multiple accounts tied to one device.
  • Detects unusual fund flows in and out with little balance retention.

Synthetic Identity Fraud

  • Flags inconsistencies across ID documents, IP addresses, and behavioural signals.

Romance & Investment Scams

  • Detects repetitive small transfers to new beneficiaries.
  • Flags high-value transfers out of pattern with customer history.

Crypto Laundering

  • Screens wallet addresses against blacklists and blockchain analytics databases.

Red Flags That Tools Should Catch

  • Transactions at unusual hours (e.g., midnight high-value transfers).
  • Beneficiary accounts recently opened and linked to multiple small deposits.
  • Sudden change in login behaviour (new device, new location).
  • Customers reluctant to provide source-of-funds during onboarding.
  • Repeated failed logins followed by success and rapid transfers.

Evaluating Fraud Screening Tools: Questions to Ask

  1. Does the tool support real-time screening across NPP and cross-border payments?
  2. Is it powered by adaptive AI that learns from new scams?
  3. Can it reduce false positives significantly?
  4. Does it integrate with AML systems for holistic compliance?
  5. Is it AUSTRAC-aligned, with SMR-ready reporting?
  6. Does the vendor provide local market expertise in Australia?

The Cost of Weak Screening Tools

Without robust fraud screening, institutions face:

  • Direct losses from fraud payouts.
  • Regulatory fines for inadequate controls.
  • Reputational damage — customer trust is hard to regain once lost.
  • Operational drain from chasing false positives.

Spotlight: Tookitaki’s FinCense Fraud Screening Tools

FinCense, Tookitaki’s end-to-end compliance platform, is recognised for its advanced fraud screening capabilities.

  • Real-Time Monitoring: Screens transactions across banking, payments, and remittances in milliseconds.
  • Agentic AI: Detects known and unknown typologies while minimising false positives.
  • Federated Intelligence: Draws on real-world fraud scenarios contributed by compliance experts in the AFC Ecosystem.
  • FinMate AI Copilot: Provides investigators with instant case summaries and recommended actions.
  • Cross-Channel Coverage: Banking, e-wallets, remittance, crypto, and card transactions all covered in one system.
  • Regulator-Ready: Transparent AI with complete audit trails to satisfy AUSTRAC.

FinCense doesn’t just screen for fraud — it prevents it in real time, helping Australian institutions build both resilience and trust.

Future Trends in Fraud Screening Tools

  • Deepfake & Voice Scam Detection: Identifying manipulated audio and video scams.
  • Collaboration Networks: Shared fraud databases across institutions to stop scams mid-flight.
  • Agentic AI Assistants: Handling end-to-end fraud investigations with minimal human intervention.
  • Cross-Border Intelligence: Coordinated screening across ASEAN corridors, where many scams originate.

Conclusion: Smarter Screening, Stronger Defences

Fraud in Australia is becoming faster, more complex, and more costly. But with the right fraud screening tools, institutions can screen smarter, stop scams in real time, and stay on the right side of AUSTRAC.

Pro tip: Don’t settle for tools that only check boxes. The best fraud screening tools combine real-time detection, adaptive AI, and seamless compliance integration — turning fraud prevention into a competitive advantage.

Fraud Screening Tools in Australia: Smarter Defences for a Real-Time World