Artificial intelligence isn’t the future of AML. It’s already here — and Singapore is leading the way.

As financial crime becomes more sophisticated, traditional compliance systems are falling behind. The rise of faster payments, cross-border laundering, synthetic identities, and deepfake-driven fraud has exposed the limitations of static rules and legacy software. In response, banks and fintechs in Singapore are turning to AML AI solutions that detect risks earlier, reduce false positives, and streamline investigations.

In this blog, we explore what an AML AI solution really looks like, how it works, and why institutions in Singapore are embracing it to stay ahead of both criminals and regulators.

Why AI Is a Game Changer for AML in Singapore

The Monetary Authority of Singapore (MAS) has made it clear — technology is a core part of the country’s fight against financial crime. Through initiatives like the AML/CFT Industry Partnership (ACIP) and the MAS Veritas framework for explainable AI, Singapore is building a regulatory environment that encourages innovation without compromising accountability.

At the same time, Singapore’s financial institutions are facing more complex challenges than ever:

• Mule accounts used in investment and job scams
• Layering of funds through e-wallets and remittance providers
• Abuse of shell companies in trade-based laundering
• Fraudulent fund flows enabled by deepfake impersonation
• Real-time payment risks with little recovery time

In this environment, artificial intelligence is not just helpful — it’s essential.

What Is an AML AI Solution?

An AML AI solution is a software platform that uses artificial intelligence to improve how financial institutions detect, investigate, and report suspicious activity.

It typically includes:

• Machine learning models for pattern detection
• Behavioural analytics to understand customer activity
• Natural language generation to summarise case findings
• Risk scoring algorithms that learn from historical decisions
• Automated decision support for analysts

Unlike rule-only systems, AI-powered solutions continuously learn and adapt, improving detection accuracy and operational efficiency over time.

Key Benefits of AML AI Solutions

1. Reduced False Positives

Traditional systems often generate too many alerts for low-risk behaviour. AI learns from past cases and analyst decisions to reduce noise and focus attention on true risk.

2. Faster Detection of New Threats

AI can identify suspicious patterns even if they haven’t been explicitly programmed into the system. This is especially valuable for emerging typologies like:

• Layering through multiple fintech apps
• Round-tripping via shell firms
• Structuring disguised as utility bill payments

3. Real-Time Risk Scoring

AI models assign risk scores to customers and transactions based on hundreds of variables. This allows institutions to prioritise alerts and allocate resources effectively.

4. Smarter Case Investigation

AI copilots can assist analysts by:

• Highlighting key transactions
• Surfacing related customer behaviour
• Drafting STR narratives in plain language

This reduces the time to close cases and improves consistency in reporting.

5. Continuous Learning

As more cases are resolved, AI models can learn what fraud and laundering look like in your specific environment, increasing precision with each iteration.

How AML AI Solutions Align with MAS Expectations

Singapore’s regulatory landscape encourages the use of AI — as long as it is transparent and explainable.

The MAS Veritas initiative provides a framework for:

• Fairness: Avoiding bias in AI decision-making
• Ethics: Using data responsibly
• Accountability: Ensuring decisions can be explained and audited

An effective AML AI solution must therefore include:

• Decision traceability for every alert
• Human override capabilities
• Clear documentation of how models work
• Regular testing and validation of AI accuracy

Platforms that follow these principles are more likely to meet MAS standards and earn regulator trust.

Core Capabilities to Look For in an AML AI Solution

1. AI-Driven Transaction Monitoring

The system should use machine learning models to detect anomalies across:

• Transaction amounts
• Frequency and velocity
• Device and location changes
• Peer comparison against similar customers

2. Scenario-Based Typology Detection

The best systems include real-world money laundering scenarios contributed by experts, such as:

• Placement via retail accounts
• Layering through shell companies
• Integration via fake invoicing or loan repayments

This context improves both alert accuracy and investigation clarity.

3. Investigation Copilots

Tools like FinMate from Tookitaki act as intelligent assistants that:

• Help analysts understand alert context
• Suggest next investigative steps
• Auto-generate draft narratives for STRs
• Surface links to previous related cases

4. Risk-Based Alert Prioritisation

AI should rank alerts based on impact, urgency, and regulatory relevance, ensuring that investigators spend their time where it matters most.

5. Simulation and Model Tuning

Institutions should be able to simulate how a new AI model or detection rule will perform before going live. This helps fine-tune thresholds and manage alert volumes.

6. Federated Learning for Shared Intelligence

AI systems that learn from shared typologies — without sharing customer data — offer the best of both worlds. This collaborative approach strengthens industry resilience.

How Tookitaki’s FinCense Delivers an AML AI Solution Built for Singapore

Tookitaki’s FinCense platform is a leading AML AI solution used by financial institutions across Asia, including Singapore. It’s built with local compliance, risk, and operational challenges in mind.

Here’s what makes it stand out:

Agentic AI Framework

FinCense uses modular AI agents that specialise in:

• Transaction monitoring
• Alert prioritisation
• Case investigation
• Regulatory reporting

Each agent is trained and validated independently, allowing institutions to scale features as needed.

Access to the AFC Ecosystem

The AFC Ecosystem is a community-driven repository of AML typologies. FinCense connects directly to this ecosystem, enabling institutions to:

• Download new scenarios
• Adapt quickly to regional threats
• Stay ahead of typologies involving mule accounts, trade flows, and fintech misuse

Smart Disposition and FinMate Investigation Copilot

These tools help analysts reduce investigation time by:

• Auto-summarising case data
• Providing contextual insights
• Offering explainable decision paths
• Supporting audit-ready workflows

MAS-Aligned Design and Veritas Readiness

FinCense is built for compliance with Singapore’s regulatory expectations, including:

• Integration with GoAML for STR filing
• Full decision traceability
• Regular model audits and validation reports
• Explainable AI components

Results Achieved by Institutions Using AML AI Solutions

Singapore-based banks and fintechs using FinCense have reported:

• Over 60 percent reduction in false positives
• Investigation turnaround times cut by half
• Stronger regulatory outcomes during audits
• Higher-quality STRs with better supporting documentation
• Improved morale and productivity in compliance teams

These outcomes demonstrate the power of combining local context, intelligent automation, and human decision support in a single solution.

When Should a Financial Institution Consider an AML AI Solution?

If you answer “yes” to more than two of the questions below, your organisation may be ready for an upgrade.

• Are you overwhelmed by false positives?
• Are you slow to detect emerging typologies?
• Is your investigation process mostly manual?
• Do STRs take hours to compile and submit?
• Are your current tools siloed or difficult to scale?
• Do regulators require more explainability than your system provides?

If these issues sound familiar, an AML AI solution could transform your compliance operations.

Conclusion: The Future of AML in Singapore Is Powered by AI

In Singapore’s fast-paced financial ecosystem, compliance teams face mounting pressure to do more with less — and to do it faster, smarter, and more transparently.

AML AI solutions offer a new way forward. By using intelligent automation, shared typologies, and explainable decisioning, institutions can move from reactive monitoring to proactive crime prevention.

Tookitaki’s FinCense shows what’s possible when AI is built for local regulators, regional threats, and real-world operations. The result is not just better compliance — it’s a smarter, stronger financial system.

Now is the time to stop relying on outdated rules and start trusting intelligent systems that learn, adapt, and protect.

The right vendor is not just selling software, they are safeguarding your institution’s future.

In the Philippines, the pressure to fight financial crime is mounting. The exit from the FATF grey list in 2024 signaled progress, but also raised expectations for financial institutions. Banks, fintechs, and remittance companies are now required to show that they can identify suspicious activity quickly and accurately. At the heart of this challenge is transaction monitoring software. And choosing the right vendor is as important as the technology itself.

Why Transaction Monitoring Matters More Than Ever

Transaction monitoring enables financial institutions to detect unusual or suspicious activity in real time or through batch analysis. It flags patterns such as structuring, round-tripping, or high-risk cross-border flows that may signal money laundering or fraud.

In the Philippines, several factors make monitoring critical:

• Large remittance inflows vulnerable to structuring and layering.
• High fintech adoption with e-wallets and digital banks processing instant payments.
• Cross-border risks as syndicates exploit correspondent banking channels.
• Heightened regulatory oversight from the BSP and AMLC.

For institutions, the right transaction monitoring system can be the difference between meeting compliance standards and facing regulatory penalties.

The Role of Transaction Monitoring Software Vendors

Software alone is not enough. Vendors provide the platforms, expertise, and ongoing support that make monitoring effective. A vendor is not just a provider, they are a partner in compliance. Their responsibilities include:

• Developing adaptive monitoring technology.
• Ensuring local regulatory alignment.
• Offering integration with core banking systems.
• Providing training and customer support.
• Continuously updating typologies and detection rules.

The choice of vendor directly impacts both compliance outcomes and operational efficiency.

What to Look For in Transaction Monitoring Software Vendors

When evaluating vendors in the Philippines, institutions should consider several factors:

1. Regulatory Alignment

Vendors must demonstrate familiarity with BSP and AMLC requirements, including STR filing standards, risk-based monitoring, and audit readiness.

2. Technology and Innovation

Modern systems should offer AI-driven monitoring, machine learning for anomaly detection, and explainability to satisfy regulators.

3. Local and Regional Expertise

Vendors should understand the Philippine market as well as regional risks such as cross-border laundering and remittance abuse.

4. Integration Capabilities

Seamless integration with legacy banking infrastructure is essential to ensure a single view of customer activity.

5. Scalability

Solutions should support institutions of different sizes, from rural banks to major commercial players.

6. Customer Support and Training

Strong after-sales support ensures that compliance teams can use the software effectively.

7. Collaborative Intelligence

The ability to share typologies and scenarios across banks without compromising data privacy enhances overall industry defences.

How Vendors Help Address Philippine Money Laundering Typologies

Top vendors ensure their systems detect common schemes in the Philippines:

• Remittance Structuring detected through repeated small-value transfers.
• Shell Companies exposed via unusual business-to-business transactions.
• Casino Laundering flagged through inconsistent deposit and withdrawal patterns.
• Trade-Based Laundering identified through mismatched invoices and payments.
• Terror Financing uncovered through frequent low-value transfers to high-risk geographies.

Challenges in Choosing Transaction Monitoring Vendors

Selecting the right vendor is not straightforward. Institutions face obstacles such as:

• Vendor Lock-In: Some vendors limit flexibility by tying institutions to proprietary technology.
• High Implementation Costs: Advanced solutions can strain budgets of smaller institutions.
• Complex Integration: Connecting to legacy core banking systems can delay deployment.
• Skill Gaps: Compliance teams may lack experience with sophisticated monitoring platforms.
• Evolving Threats: Vendors that fail to update systems regularly leave institutions exposed.

Best Practices for Selecting a Vendor

1. Conduct a Needs Assessment
   Identify specific risks, regulatory requirements, and resource constraints before shortlisting vendors.
2. Evaluate Proof of Concept (POC)
   Run test cases with vendors to see how their systems perform against real scenarios.
3. Prioritise Explainability
   Choose vendors that offer systems with clear reasoning behind flagged alerts.
4. Check Industry References
   Look for testimonials or case studies from other Philippine or ASEAN banks.
5. Focus on Partnership, Not Just Product
   A strong vendor offers training, updates, and support that extend beyond installation.

Global vs Local Vendors: Which Is Better?

Philippine institutions often face a choice between global and local vendors. Each has strengths:

• Global Vendors bring advanced AI, scalability, and a track record across markets. However, they may lack local context or flexibility.
• Local Vendors understand BSP and AMLC regulations and the Philippine market intimately, but may lack the resources or innovation speed of global players.

The best choice often depends on institution size, complexity, and risk appetite. Hybrid approaches, such as global technology with local implementation support, are increasingly popular.

The Tookitaki Advantage: A Vendor with a Difference

Tookitaki’s FinCense is more than just a transaction monitoring solution. It is built as a trust layer for financial institutions in the Philippines.

Why Tookitaki stands out among vendors:

• Agentic AI-Powered Detection that adapts to new laundering and fraud typologies.
• Federated Intelligence from the AFC Ecosystem, offering insights contributed by global compliance experts.
• False Positive Reduction through behavioural analytics and adaptive thresholds.
• Smart Disposition Engine that automates investigation summaries for STR filing.
• Explainable Outputs aligned with BSP and AMLC expectations.
• Proven Regional Experience with banks and fintechs across Asia-Pacific.

As a vendor, Tookitaki does not just deliver software. It partners with institutions to build resilient compliance frameworks that evolve with threats.

Conclusion: Choosing Vendors as Compliance Allies

In the Philippines, the stakes for compliance have never been higher. Choosing the right transaction monitoring software vendor is not just a procurement decision, it is a strategic move that defines an institution’s ability to fight financial crime.

The best vendors combine advanced technology with local expertise, strong support, and a collaborative mindset. They help banks move beyond compliance checklists to build trust, resilience, and growth.

Philippine institutions that partner with the right vendor today will not only meet regulatory requirements but also set the foundation for sustainable, secure, and customer-centric banking in the digital age.

With AUSTRAC raising expectations, Australian banks and fintechs need AML vendors who can deliver real-time, AI-driven compliance solutions.

Introduction

Australia’s financial sector is under mounting pressure to combat money laundering and terrorism financing. In recent years, AUSTRAC has intensified its supervision, issuing multi-million-dollar penalties to banks and casinos for failing to detect suspicious activity. At the same time, fraud typologies are becoming more sophisticated, with scams exploiting instant payments, mule accounts, and cross-border channels.

Against this backdrop, financial institutions must choose AML vendors that can keep pace with evolving risks. But not all vendors are created equal. The right partner should not only ensure compliance with AUSTRAC requirements but also strengthen customer trust and operational efficiency.

This blog explores the AML vendor landscape in Australia, what to look for in a partner, and why next-generation solutions like Tookitaki’s FinCense are setting a new benchmark for compliance.

The AML Landscape in Australia

1. Rising Compliance Expectations

AUSTRAC requires banks, fintechs, and remittance providers to implement robust AML/CTF programs, including transaction monitoring, sanctions screening, and suspicious matter reporting. Failures can result in fines and reputational harm.

2. The Real-Time Payments Challenge

The New Payments Platform (NPP) and PayTo enable instant transfers, forcing institutions to adopt real-time AML monitoring. Traditional batch-based tools are no longer sufficient.

3. Scam Epidemic

Australians lost more than AUD 3 billion in 2024 to scams, much of it facilitated through banking and payment systems. AUSTRAC has made scam detection part of its supervisory priorities.

4. Diverse Financial Ecosystem

Australia’s market includes Tier-1 banks, fintechs, payment providers, and community-owned banks like Regional Australia Bank and Beyond Bank. Each requires AML vendors that can scale to their size and complexity.

What Are AML Vendors?

AML vendors provide the technology, tools, and expertise financial institutions use to meet compliance obligations. Their solutions typically include:

• Transaction Monitoring Systems (TMS): Detect unusual patterns in customer activity.
• Sanctions and PEP Screening: Screen customers and transactions against global lists.
• Case Management Platforms: Help compliance teams investigate alerts.
• Customer Due Diligence (CDD): Verify customer identities and assess risk levels.
• Regulatory Reporting: Automate submission of Suspicious Matter Reports (SMRs), Threshold Transaction Reports (TTRs), and International Funds Transfer Instructions (IFTIs).
• Analytics and AI Models: Strengthen detection and reduce false positives.

Types of AML Vendors in Australia

1. Legacy Vendors
   • Long-established providers offering rule-based monitoring and screening tools.
   • Strength: Regulatory familiarity.
   • Weakness: Limited adaptability to modern real-time risks.
2. Global Vendors
   • International firms offering standardised AML platforms.
   • Strength: Scale and established presence.
   • Weakness: Solutions may not be tailored to AUSTRAC or the Australian market.
3. Specialist RegTech Vendors
   • Innovative firms like Tookitaki, focusing on AI-driven, cloud-ready, and AUSTRAC-aligned compliance.
   • Strength: Agility, advanced technology, and adaptability.
   • Weakness: Less brand recognition compared to legacy players (though closing fast).

Why Vendor Choice Matters

Choosing the wrong vendor can expose banks to major risks:

• Regulatory Penalties: Inadequate tools increase the chance of AUSTRAC fines.
• Customer Loss: Poor AML controls damage trust.
• Operational Inefficiency: Legacy tools flood investigators with false positives.
• Technology Obsolescence: Outdated systems cannot adapt to instant payments.

The right AML vendor provides not just compliance coverage but also operational efficiency and customer confidence.

Key Features to Look for in an AML Vendor

1. Real-Time Monitoring
   Essential for NPP and PayTo transactions that settle instantly.
2. Agentic AI
   Adaptive, explainable AI that reduces false positives while improving detection.
3. Federated Intelligence
   Access to shared typologies and scenarios across institutions without exposing sensitive data.
4. Regulatory Alignment
   Automated SMRs, TTRs, and IFTIs that meet AUSTRAC’s standards.
5. Case Management Integration
   Seamless workflows linking transaction alerts to investigations.
6. Cross-Channel Coverage
   Monitoring across banking, cards, wallets, remittances, and trade finance.
7. Explainability and Transparency
   Tools must produce outputs regulators can understand and audit.
8. Scalability
   Solutions must work for Tier-1 banks as well as smaller community-owned institutions.

Red Flags in AML Vendors

• Reliance on static, rules-based monitoring.
• Limited or outdated sanctions list integrations.
• No support for real-time NPP or PayTo screening.
• High false-positive rates with little model adaptability.
• Weak case management or lack of automation.
• Minimal presence in the Australian market.

Case Example: Community-Owned Banks Leading with Smarter Vendors

Community-owned banks such as Regional Australia Bank are proving that advanced AML tools are not only for Tier-1 players. By adopting next-generation vendor solutions, they have improved suspicious matter detection, reduced operational costs, and strengthened AUSTRAC reporting — all while building customer trust.

Spotlight: Tookitaki’s FinCense

FinCense, Tookitaki’s all-in-one compliance platform, is setting a new standard among AML vendors in Australia.

• Real-Time Detection: Screens NPP, PayTo, and cross-border transactions in milliseconds.
• Agentic AI: Continuously adapts to emerging laundering typologies while reducing false positives.
• Federated Intelligence: Leverages global scenarios from the AFC Ecosystem for stronger protection.
• Automated Regulatory Reporting: Generates AUSTRAC-ready SMRs, TTRs, and IFTIs with full audit trails.
• Integrated Case Management: Streamlines investigations with FinMate AI Copilot assisting compliance officers.
• Cross-Channel Coverage: Consolidates monitoring across banking, remittance, wallets, and cards.

With FinCense, Australian banks and fintechs can modernise compliance while lowering operational costs.

Best Practices for Selecting AML Vendors

1. Assess Local Fit: Ensure the vendor understands AUSTRAC and the Australian regulatory environment.
2. Prioritise AI and Automation: Reduce false positives and investigator workload.
3. Insist on Explainability: Ensure AI outputs can be audited and defended.
4. Look for Federated Intelligence: Gain insights from industry-wide typologies.
5. Evaluate Case Management Tools: Strong integration speeds up investigations.
6. Consider Cloud Readiness: Cloud-native solutions are faster to scale and upgrade.
7. Check References: Review case studies from institutions similar in size and scope.

The Future of AML Vendors in Australia

1. AI Governance Integration
   Vendors will embed explainable AI frameworks to meet regulator expectations.
2. Industry Collaboration
   Federated learning will become the standard for AML intelligence sharing.
3. Deeper Real-Time Capabilities
   Vendors must adapt fully to instant payments like NPP and PayTo.
4. End-to-End Platforms
   Institutions will prefer vendors offering unified AML and fraud prevention.
5. Cost-Efficient Solutions
   Vendors that reduce compliance costs while improving detection will stand out.

Conclusion

AML vendors are the backbone of compliance in Australia’s financial ecosystem. With AUSTRAC pushing for real-time, data-driven monitoring, institutions can no longer rely on outdated, static tools. The best vendors provide real-time detection, adaptive AI, and federated intelligence, all while ensuring regulatory alignment and operational efficiency.

Community-owned banks like Regional Australia Bank and Beyond Bank demonstrate that smart vendor choices can deliver Tier-1 capabilities without Tier-1 budgets. Platforms like Tookitaki’s FinCense represent the next generation of AML vendors, offering explainable AI, federated learning, and regulator-ready automation.

Pro tip: The best AML vendor is not just a technology provider. It is a strategic partner that helps you stay ahead of criminals while earning the trust of regulators and customers.