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.

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.

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.

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?

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.

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.

When transactions move in real-time, monitoring them can’t be manual;  it has to be automated.

Malaysia’s Digital Finance Boom Comes with New Risks

Malaysia is in the middle of a financial revolution. Digital wallets, instant payments, QR-based transfers, and cross-border remittances are no longer novelties — they are everyday realities for millions of Malaysians. Bank Negara Malaysia (BNM) has been actively pushing the industry towards modernisation while tightening compliance around anti-money laundering (AML) and counter-terrorist financing (CTF).

But as the payments ecosystem accelerates, so does the pace of financial crime. Fraudsters and money launderers are exploiting the very systems designed to improve convenience. From cross-border mule accounts to deepfake-powered scams, Malaysia’s financial institutions are dealing with a wave of threats that move in real time.

This is why automated transaction monitoring is no longer optional — it is the backbone of modern compliance.

The Current Landscape in Malaysia

Malaysia’s regulatory and risk environment underscores the urgency:

• Bank Negara Malaysia’s vigilance — BNM expects banks and fintechs to implement robust monitoring systems, aligned with FATF standards.
• Rising financial crime losses — scams, fraud, and laundering cases have surged, with cross-border syndicates targeting both banks and digital wallets.
• FATF pressures — Malaysia, like many ASEAN nations, faces scrutiny to demonstrate strong AML/CFT controls.

Despite these developments, many institutions still rely on legacy or semi-automated systems. These tools can’t cope with today’s realities of high-volume, high-speed transactions — leaving dangerous gaps in detection.

What Is Automated Transaction Monitoring?

At its core, automated transaction monitoring is a compliance system that uses technology — often AI and machine learning — to monitor financial transactions in real time.

Instead of static rules or manual checks, automated systems:

• Flag unusual activity instantly
• Analyse multiple data points (customer profile, device, geography, frequency, transaction type)
• Apply risk scoring dynamically
• Continuously learn and adapt from new patterns

In a country like Malaysia, where millions of transactions are processed daily across banks, e-wallets, and fintech apps, this automation is the difference between spotting a mule account early or missing it entirely.

Key Features of Automated Transaction Monitoring

An effective automated transaction monitoring system goes beyond alerting. The best solutions typically include:

1. Real-Time Detection

Transactions are monitored as they happen, allowing suspicious behaviour to be flagged before funds can disappear.

2. AI and Machine Learning

Instead of relying solely on fixed rules, AI models identify emerging typologies — for example, new scams targeting retirees or synthetic identity fraud.

3. Risk-Based Scoring

Each transaction is assessed against multiple risk factors. This allows compliance teams to prioritise high-risk cases instead of drowning in false positives.

4. Adaptive Thresholds

Automated systems adjust thresholds based on behaviour and trends, reducing reliance on static limits.

5. Explainability and Auditability

Modern automated systems provide full transparency into why a transaction was flagged, ensuring regulators can trace every decision.

The Limitations of Traditional Monitoring

Why can’t legacy systems keep up? The answer lies in their design. Traditional monitoring solutions are:

• Rule-Based Only — they cannot detect new laundering patterns until rules are manually updated.
• False-Positive Heavy — Compliance teams waste time reviewing thousands of unnecessary alerts.
• Slow — with manual investigations and delays, criminals can layer and withdraw funds before action is taken.
• Fragmented — many banks run separate systems for fraud and AML, creating blind spots across channels.

In short, legacy systems are outmatched by the speed and creativity of today’s financial criminals.

Why Malaysia Needs Automated Transaction Monitoring Now

Several trends make automation urgent in Malaysia:

1. Instant Payments and QR Adoption

Malaysia is leading in QR payment adoption under DuitNow QR. But instant transfers also mean funds can vanish in seconds. Manual checks simply can’t keep up.

2. Mule Account Proliferation

Young adults and low-income individuals are being recruited as money mules. Automated monitoring can spot hub-and-spoke patterns of inflows and outflows, even across institutions.

3. Cross-Border Laundering Risks

Malaysia’s central position in ASEAN makes it attractive for syndicates layering funds through remittances and fintech platforms.

4. Regulatory Scrutiny

BNM expects institutions to demonstrate not just compliance but proactive risk management. Automated monitoring directly supports this.

5. Rising Compliance Costs

Manual investigation and outdated systems increase compliance overheads. Automation offers efficiency without compromising accuracy.

Tookitaki’s FinCense: Automated Monitoring Reimagined

This is where Tookitaki’s FinCense steps in — not as another monitoring tool, but as Malaysia’s Trust Layer to fight financial crime.

Here’s how FinCense sets the benchmark for automated transaction monitoring:

1. Agentic AI Workflows

FinCense uses Agentic AI — intelligent agents that don’t just detect but also triage, narrate, and recommend actions. This means:

• Alerts are prioritised automatically
• Investigations come with auto-generated narratives regulators can understand
• Compliance teams save hours per case

2. Federated Learning: Shared Intelligence, Locally Applied

Through the AFC Ecosystem, FinCense ingests insights from hundreds of institutions across APAC while keeping data private. For Malaysia, this means early detection of scams or laundering patterns first seen in neighbouring markets.

3. End-to-End Coverage

Instead of separate systems, FinCense integrates:

• AML transaction monitoring
• Fraud prevention
• Screening
• Smart disposition tools

This single view of risk eliminates blind spots and reduces costs.

4. Explainability and Governance

FinCense is built with explainable AI, ensuring every flagged transaction is fully auditable and regulator-friendly — critical under BNM’s watch.

5. Proven ASEAN Fit

FinCense’s scenarios are tailored to ASEAN realities — high-volume remittances, e-wallet fraud, QR payments — making it highly relevant to Malaysian institutions.

A Scenario in Action

Consider this example:

• A mule account in Malaysia begins receiving small but rapid inflows from multiple e-wallets.
• Within hours, funds are layered through QR-based merchants and remitted abroad.
• A traditional rules-based system might not detect this until after funds are gone.

With FinCense’s automated monitoring:

• Real-time detection identifies the unusual inflows.
• Federated learning recognises the pattern from similar cases in Singapore.
• Agentic AI prioritises the alert, generates a narrative, and recommends freezing the account.

The result: risk is stopped in its tracks, customers are protected, and compliance officers have clear documentation for regulators.

The Business Impact for Malaysian Banks and Fintechs

Implementing automated transaction monitoring isn’t just about ticking regulatory boxes. It delivers strategic advantages:

• Faster Detection = Safer Customers — protecting consumers from scams builds long-term trust.
• Lower Compliance Costs — automation reduces manual workloads and investigation costs.
• Better Regulator Relationships — explainable AI ensures smooth audits and inspections.
• Competitive Edge — institutions with advanced compliance are more attractive to global partners and investors.

In Malaysia’s increasingly competitive financial services sector, trust is not just a regulatory requirement — it is a business differentiator.

The Road Ahead: Building Malaysia’s Trust Layer

As Malaysia continues to embrace real-time payments, open banking, and digital finance, the risks will only intensify. Manual or outdated monitoring systems simply cannot keep pace.

Automated transaction monitoring is the future — and with solutions like Tookitaki’s FinCense, financial institutions can stay ahead of criminals while reducing costs and strengthening compliance.

For Malaysia’s banks and fintechs, the choice is no longer about whether to automate — but how fast they can adopt an industry-leading trust layer that evolves as quickly as financial crime does.