Fraud may wear many faces. But for enterprises, the cost of not catching it is always the same: reputation, revenue, and regulatory risk.

In Singapore’s fast-paced, high-trust economy, enterprise fraud has evolved far beyond simple scams. Whether it's internal collusion, digital payment abuse, cross-border laundering, or supplier impersonation, organisations need to rethink how they detect and prevent fraud at scale.

This blog explores how enterprise fraud detection is transforming in Singapore, what makes it different from consumer-level security, and what leading firms are doing to stay ahead.

What Is Enterprise Fraud Detection?

Unlike individual-focused fraud detection (such as stolen credit cards), enterprise fraud detection is designed to uncover multi-layered, systemic, and often high-value fraud schemes that target businesses, financial institutions, or governments.

It includes threats such as:

• Internal fraud (for example, expense abuse or payroll manipulation)
• Business email compromise (BEC)
• Procurement fraud and supplier collusion
• Cross-channel transaction fraud
• Laundering via corporate accounts or trade platforms

In Singapore, where enterprises increasingly operate across borders and digital channels, the attack surface for fraud is broader than ever.

Why It’s a Priority in Singapore’s Enterprise Landscape

1. High Volume, High Velocity

Singaporean enterprises operate in sectors like banking, logistics, trade, and technology. These sectors are prone to complex, high-volume transactions that make detecting fraud challenging.

2. Cross-Border Risks

As a regional hub, many Singaporean businesses handle payments, contracts, and supply chains that cross jurisdictions. This creates blind spots that fraudsters exploit.

3. Regulatory Pressure

The Monetary Authority of Singapore (MAS) has increased scrutiny on fraud resilience, cyber threats, and risk controls. This is especially true after high-profile scams and laundering cases.

4. Digital Transformation

Digital acceleration has outpaced many legacy risk controls. Fraudsters take advantage of the gaps between systems, departments, or verification processes.

Key Features of a Strong Enterprise Fraud Detection System

1. Multi-Channel Monitoring

From bank transfers to invoices, card payments, and internal logs, enterprise systems must analyse all channels in one place.

2. Real-Time Detection and Response

Enterprise fraud does not wait. Real-time flagging, blocking, and escalation are critical, especially for high-value transactions.

3. Risk-Based Scoring

Modern platforms use behavioural analytics and contextual data to assign risk scores. This allows teams to prioritise the most dangerous threats.

4. Cross-Entity Link Analysis

Detecting hidden relationships between users, accounts, suppliers, or geographies is key to uncovering organised schemes.

5. Case Management and Forensics

Built-in case tracking, audit logs, and investigator dashboards are vital for compliance, audit defence, and root cause analysis.

Challenges Faced by Enterprises in Singapore

Despite growing awareness, many Singaporean enterprises struggle with:

1. Siloed Systems

Fraud signals are spread across payment, HR, ERP, and CRM systems. This makes unified detection difficult.

2. Limited Intelligence Sharing

Few enterprises share typologies, even within the same sector. This limits collective defence.

3. Outdated Rule Engines

Many systems still rely on static thresholds or manual checks. These systems miss complex or new fraud patterns.

4. Overworked Compliance Teams

High alert volumes and false positives lead to fatigue and longer investigation times.

How AI Is Reshaping Enterprise Fraud Detection

The rise of AI-powered, scenario-based systems is helping Singaporean enterprises go from reactive to predictive fraud defence.

✅ Behavioural Anomaly Detection

Rather than just flagging large transactions, AI looks for subtle deviations like login location mismatches or unusual approval flows.

✅ Federated Learning

Tookitaki’s FinCense platform allows enterprises to learn from other organisations’ fraud patterns without sharing sensitive data.

✅ AI Copilots for Investigators

Tools such as FinMate assist human teams by surfacing key evidence, suggesting next steps, and reducing investigation time.

✅ End-to-End Visibility

Modern systems integrate with finance, HR, procurement, and customer systems to give a complete fraud view.

How Singaporean Enterprises Are Using Tookitaki for Fraud Detection

Leading organisations across banking, fintech, and commerce are turning to Tookitaki to future-proof their fraud defence. Here’s why:

• Scenario-Based Detection Engine
  FinCense uses over 200 expert-curated typologies to identify real-world fraud, including invoice layering and ghost vendor networks.
• Real-Time, AI-Augmented Monitoring
  Transactions are scored instantly, and high-risk cases are escalated before damage is done.
• Modular Agents for Each Risk Type
  Enterprises can plug in relevant AI agents such as those for trade fraud, ATO, or BEC without overhauling legacy systems.
• Audit-Ready Case Trails
  Every flagged transaction is supported by AI-generated narratives and documentation, simplifying compliance reviews.

Best Practices for Implementing Enterprise Fraud Detection in Singapore

1. Start with a Risk Map
   Identify your fraud-prone workflows. These might include procurement, payments, or expense claims.
2. Break Down Silos
   Integrate risk signals across departments to build a unified fraud view.
3. Use Real-World Scenarios
   Rely on fraud typologies tailored to Singapore and Southeast Asia rather than generic patterns.
4. Enable Human and AI Collaboration
   Let your systems detect, but your people decide, with AI assistance to speed up decisions.
5. Continuously Improve with Feedback Loops
   Use resolved cases to train your models and refine detection rules.

Conclusion: Enterprise Fraud Requires Enterprise-Grade Solutions

Enterprise fraud is growing smarter. Your defences should too.

In Singapore’s complex and high-stakes business environment, fraud detection cannot be piecemeal or reactive. Enterprises that invest in AI-powered, real-time, collaborative solutions are not just protecting their bottom line. They are building operational resilience and stakeholder trust.

The future of enterprise fraud detection lies in intelligence-led, ecosystem-connected platforms. Now is the time to upgrade.

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.

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.

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.

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.