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Understanding the Meaning of KYC and its Difference with AML

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Tookitaki
10 Sep 2020
5 min
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In the regulatory compliance space, the terms KYC and AML are often used interchangeably and are seen as the same thing. However, this is far from the truth, as both KYC and AML differ greatly in their meaning, especially in a regulatory context. The full forms of AML and KYC are Anti Money Laundering and Know Your Customer, respectively.

In order to address the growing problem of money laundering, both national and international bodies around the world provide guidelines for the finance industry. These impose certain screening and monitoring processes on all financial institutions so that the financial system is safeguarded from abuse by criminals. These AML checks in general are called AML-KYC compliance programs. However, KYC is a standalone process and there are separate KYC rules to be followed by financial institutions.

In order to successfully comply with anti-money laundering regulations, financial institutions must understand their AML and KYC obligations and develop effective AML-KYC compliance programmes.

Understanding AML

Anti-money laundering (AML) refers to the overall, broader measures and processes that financial institutions and governments use in order to prevent and combat financial crimes, specifically money laundering and terrorist financing. AML regulations are dictated by international bodies such as the United Nations Office on Drugs and Crime (UNODC) and Financial Action Task Force (FATF), regional bodies like the Financial Crimes Enforcement Network (FinCEN) and The Financial Industry Regulatory Authority (FINRA) in the US, as well as local governments and bodies.

The AML policy forms part of the broader, complete AML compliance program of a financial institution.

KYC and money laundering

Know Your Customer or KYC is a fundamental process in any financial institution’s anti-money laundering program. It is defined as the process through which these institutions gather information on their clients and verify their identities. This greatly helps them to adequately assess the risk associated with each client. For example, all customers of a bank must be verified before they can use services such as checking accounts and credit cards. Fintech companies are mandated to gather ample, verifiable information on their client and their identity in order to determine their legitimacy before beginning any business activities.

What is the difference between AML and KYC?

The difference between AML and KYC primarily lies in the notion that AML is an umbrella term for the full range of regulatory processes that firms must implement in order to carry out businesses legitimately. On the other hand, KYC (Know Your Customer) is a smaller component of AML that consists of firms verifying their customers’ identities. It is one of the steps in the larger AML compliance process.

A lot of financial institutions often get confused between KYC and AML, blur the lines between the two processes, and are subject to disciplinary action by regulatory bodies as a result. They can be fined or even sentenced to prison time based on the severity of the offence.

The key differences between KYC and AML are given in the following table. 

difference-between-aml-and-kyc-1-1

 

How KYC and AML are connected

KYC and AML are deeply interconnected processes. KYC is the first step in the implementation of an AML programme or policy. It is the process through which the client’s identity is verified. The objective of KYC checks is to understand the clients, their demographics and financial dealings on a deeper level, in order to effectively manage AML risks. In general KYC involves the following processes:

  • Customer Due Diligence or CDD: It is the basic process of verifying customer identity either physically or through electronic means. It is applicable to all customers of a business.
  • Enhanced Due Diligence or EDD: It is a more advanced KYC procedure that is used primarily for high-risk customers. These customers are generally more prone to being involved in financial crimes, including money laundering and terrorist financing, hence the need for more thorough verification and sometimes more verification after onboarding.

 

Other elements in AML compliance

In addition to KYC, the AML compliance process involves the following elements:

  • Risk-based AML policies
  • Ongoing risk assessment and ongoing monitoring
  • AML compliance training programs for staff
  • Internal controls and internal audits

 

Importance of KYC and AML in banking​​

Both KYC and AML both play an integral role in a bank’s regulatory compliance. And to top it off, they are both risk-based approaches as well. They also share some common features such as client identification and risk management. But it is important to always bear in mind that these processes are not the same and serve varied functions. This will help banks to find the right professionals and team to take up each task — AML or KYC — and do it justice.

The prevention and implementation of anti-money laundering require an in-depth knowledge of a lot of factors. From the inner workings of the finance industry to an understanding of local, regional, national and international anti-money laundering regulations and rules, a successful AML professional must have a skill set beyond that of KYC.

Regtech for KYC – AML compliance

Apart from having skilled professionals, financial institutions should also invest in effective software solutions to run their AML compliance programmes successfully. Many of the current AML-KYC solutions are not robust to capture the complexities of modern-day customer risk management. Customer AML risk ratings are either carried out manually or are based on models that use a limited set of pre-defined risk parameters. This leads to inadequate coverage of risk factors which vary in number and weightage from customer to customer.

Further, the information for most of these risk parameters is static and collected when an account is opened. Often, information about customers is not updated in the required format and frequency. The current models do not consider all the touchpoints of a customer’s activity map and inaccurately score customers, failing to detect some high-risk customers and often misclassifying thousands of low-risk customers as high risk.

Misclassification of customer risk leads to unnecessary case reviews, resulting in excessive costs and customer dissatisfaction. Adding to this, the static nature of the risk parameters fails to capture the changing behaviour of customers and dynamically adjust the risk ratings, exposing financial institutions to emerging threats.

Using artificial intelligence and machine learning

Today, modern technologies like AI and machine learning are getting widespread attention for their ability to improve business processes and regulators are encouraging banks to adopt innovative approaches to combat money laundering. In the area of AML compliance, the need of the hour is a sophisticated technology that can capture changing customer behaviour through proper identification of risk indicators and continuously update customer profiles as underlying activities change. There are various Regtech solutions that can ensure proper AML-KYC compliance in a sustainable manner.

Tookitaki’s solutions for AML – KYC compliance

Tookitaki developed an end-to-end AML-KYC compliance platform called the Anti-Money Laundering Suite (AMLS). It offers multiple solutions catering to the core AML activities such as transaction monitoring, name screening, transaction screening and customer risk scoring. Powered by advanced machine learning, AMLS addresses the market needs and provides an effective and scalable AML compliance solution.

To know more about our AML solution and its unique features, please contact us. 

 

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Blogs
12 Sep 2025
6 min
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Cracking the Case: Why AML Case Management Software is a Game Changer for Banks in Australia

As compliance risks mount, AML case management software is helping Australian banks move faster, smarter, and with greater confidence.

Introduction

Anti-money laundering (AML) compliance is not only about detecting suspicious activity. It is also about what happens next. Every suspicious matter must be investigated, documented, and, if necessary, reported to regulators like AUSTRAC. For banks and fintechs, the investigation process is often where compliance bottlenecks occur.

Enter AML case management software. These platforms streamline investigations, reduce manual work, and create regulator-ready records that satisfy AUSTRAC requirements. In Australia, where the New Payments Platform (NPP) has intensified real-time compliance pressures, case management has become a core part of the compliance tech stack.

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What is AML Case Management Software?

AML case management software provides a centralised platform for investigating, documenting, and resolving suspicious alerts. Instead of relying on spreadsheets, emails, and fragmented tools, investigators work within a single system that:

  • Collects alerts from monitoring systems.
  • Provides contextual data for faster decision-making.
  • Tracks actions and escalations.
  • Generates regulator-ready reports and audit trails.

In short, it is the engine room of AML compliance operations.

Why Case Management Matters in AML

1. Rising Alert Volumes

Banks generate thousands of alerts daily, most of which turn out to be false positives. Without case management, investigators drown in manual work.

2. AUSTRAC Expectations

Regulators require detailed audit trails for how alerts are reviewed, decisions made, and reports submitted. Poor documentation is a compliance failure.

3. Operational Efficiency

Manual workflows are slow and error-prone. Case management software reduces investigation times, freeing up staff for higher-value work.

4. Reputational Risk

Missed suspicious activity can lead to penalties and reputational damage, as seen in recent high-profile AUSTRAC enforcement cases.

5. Staff Retention

Investigator burnout is real. Streamlined workflows reduce frustration and improve retention in compliance teams.

Core Features of AML Case Management Software

1. Centralised Investigation Hub

All alerts flow into one platform, giving investigators a single view of risks across channels.

2. Automated Workflows

Routine tasks like data collection and alert assignment are automated, reducing manual effort.

3. Risk Scoring and Prioritisation

Alerts are prioritised based on severity, ensuring investigators focus on the most urgent cases.

4. Collaboration Tools

Teams can collaborate in-platform, with notes, escalation paths, and approvals tracked transparently.

5. Regulator-Ready Reporting

Generates Suspicious Matter Reports (SMRs), Threshold Transaction Reports (TTRs), and International Funds Transfer Instructions (IFTIs) aligned with AUSTRAC standards.

6. Audit Trails

Tracks every action taken on a case, creating clear evidence for regulator reviews.

7. AI Support

Modern platforms integrate AI to summarise alerts, suggest next steps, and reduce investigation times.

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Challenges Without Case Management

  • Fragmented Data: Investigators waste time gathering information from multiple systems.
  • Inconsistent Documentation: Different staff record cases differently, creating compliance gaps.
  • Slow Turnaround: Manual workflows cannot keep up with real-time payment risks.
  • High Operational Costs: Large teams are needed to handle even moderate alert volumes.
  • Regulatory Exposure: Poorly documented investigations can result in AUSTRAC penalties.

Red Flags That Demand Strong Case Management

  • Customers sending high-value transfers to new beneficiaries.
  • Accounts showing rapid pass-through activity with no balances.
  • Cross-border remittances involving high-risk jurisdictions.
  • Unexplained source of funds or reluctance to provide documentation.
  • Device or location changes followed by suspicious transactions.
  • Multiple accounts linked to the same IP address.

Each of these scenarios must be investigated thoroughly and consistently. Without effective case management, important red flags may slip through the cracks.

Case Example: Community-Owned Banks Taking the Lead

Community-owned banks like Regional Australia Bank and Beyond Bank have adopted advanced compliance platforms with case management capabilities to strengthen investigations. By doing so, they have reduced false positives, streamlined workflows, and maintained strong AUSTRAC alignment.

Their success shows that robust case management is not just for Tier-1 institutions. Mid-sized banks and fintechs can also achieve world-class compliance by adopting the right technology.

Spotlight: Tookitaki’s FinCense

FinCense, Tookitaki’s end-to-end compliance platform, includes advanced case management features designed to support Australian institutions.

  • Centralised Investigations: All alerts flow into one unified case management system.
  • FinMate AI Copilot: Summarises alerts, suggests actions, and drafts regulator-ready narratives.
  • Federated Intelligence: Accesses real-world scenarios from the AFC Ecosystem to provide context for investigations.
  • Regulator Reporting: Auto-generates AUSTRAC-compliant SMRs, TTRs, and IFTIs.
  • Audit Trails: Tracks every investigator action for transparency.
  • Cross-Channel Coverage: Banking, wallets, remittances, cards, and crypto all integrated.

With FinCense, compliance teams can move from reactive investigations to proactive case management, improving efficiency and resilience.

Best Practices for AML Case Management in Australia

  1. Integrate Case Management with Monitoring Systems: Avoid silos by connecting transaction monitoring, screening, and case management.
  2. Use AI for Efficiency: Deploy AI copilots to reduce false positives and accelerate reviews.
  3. Document Everything: Ensure audit trails are complete, consistent, and regulator-ready.
  4. Adopt a Risk-Based Approach: Focus resources on high-risk customers and transactions.
  5. Invest in Staff Training: Technology is only as good as the people using it.
  6. Conduct Regular Reviews: Independent audits of case management processes are essential.

The Future of AML Case Management Software

1. AI-First Investigations

AI copilots will increasingly handle routine case reviews, leaving human analysts to focus on complex scenarios.

2. Integration with NPP and PayTo

Case management will need to handle alerts tied to real-time and overlay services.

3. Collaboration Across Institutions

Shared intelligence networks will allow banks to collaborate on fraud and money laundering investigations.

4. Predictive Case Management

Instead of reacting to alerts, future platforms will predict high-risk customers and transactions before fraud occurs.

5. Cost Efficiency Focus

With compliance costs rising, automation will be critical to keeping operations sustainable.

Conclusion

In Australia’s fast-paced financial environment, AML case management software is no longer optional. It is a necessity for banks, fintechs, and remittance providers navigating AUSTRAC’s expectations and real-time fraud risks.

Community-owned banks like Regional Australia Bank and Beyond Bank show that advanced case management is achievable for institutions of all sizes. Platforms like FinCense provide the tools to manage alerts, streamline investigations, and build regulator-ready records, all while reducing costs.

Pro tip: The best case management systems are not just about compliance. They help institutions stay resilient, protect customers, and build trust in a competitive market.

Cracking the Case: Why AML Case Management Software is a Game Changer for Banks in Australia
Blogs
11 Sep 2025
6 min
read

Inside Taiwan’s War on Scams: The Future of Financial Fraud Solutions

Fraudsters are innovating as fast as fintech, and Taiwan needs smarter financial fraud solutions to keep pace.

From instant payments to digital wallets, Taiwan’s financial sector has embraced speed and convenience. But these advances have also opened new doors for fraud: phishing, investment scams, mule networks, and synthetic identities. In response, banks, regulators, and technology providers are racing to deploy next-generation financial fraud solutions that balance security with seamless customer experience.

The Rising Fraud Challenge in Taiwan

Taiwan’s economy is increasingly digital. Contactless payments, mobile wallets, and cross-border e-commerce have flourished, bringing convenience to millions of consumers. At the same time, the risks have multiplied:

  • Social Engineering Scams: Romance scams and “pig butchering” schemes are draining consumer savings.
  • Cross-Border Syndicates: International fraud networks exploit Taiwan’s financial rails to launder illicit proceeds.
  • Account Takeover (ATO): Fraudsters use phishing and malware to compromise accounts, moving funds rapidly before detection.
  • Fake E-Commerce Merchants: Fraudulent sellers create websites or storefronts, collect payments, and disappear, eroding trust in digital platforms.
  • Crypto-Linked Fraud: With the rise of virtual assets, scams tied to unlicensed exchanges and token offerings have surged.

According to the Financial Supervisory Commission (FSC), fraud complaints involving online transactions have climbed steadily over the past three years. Taiwan’s Bankers Association has echoed these concerns, urging members to invest in advanced fraud monitoring and customer awareness campaigns.

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What Are Financial Fraud Solutions?

Financial fraud solutions encompass the frameworks, strategies, and technologies that institutions use to prevent, detect, and respond to fraudulent activities. Unlike traditional approaches, which often rely on siloed checks, modern solutions are designed to provide end-to-end protection across the entire customer lifecycle.

Key components include:

  1. Transaction Monitoring – Analysing every payment in real time to detect anomalies.
  2. Identity Verification – Validating users with biometric checks, device fingerprinting, and KYC processes.
  3. Behavioural Analytics – Profiling user habits to flag suspicious deviations.
  4. AI-Powered Detection – Using machine learning models to anticipate and intercept fraud.
  5. Collaborative Intelligence – Sharing typologies and red flags across institutions.
  6. Regulatory Compliance – Ensuring alignment with FSC directives and FATF standards.

In Taiwan, where payment volumes are exploding and scams dominate the headlines, these solutions are not optional. They are essential.

Why Taiwan Needs Smarter Fraud Solutions

Several factors make Taiwan uniquely vulnerable to financial fraud.

  • Instant Payments via FISC: The Financial Information Service Co. operates the backbone of Taiwan’s real-time payments. With millions of transactions per day, fraud can occur within seconds, leaving little room for manual intervention.
  • Cross-Border Exposure: Taiwan’s strong trade links and remittance flows expose banks to fraud originating abroad, often tied to organised crime.
  • High Digital Adoption: With rapid uptake of e-wallets and online banking, consumers are more exposed to phishing and fake websites.
  • Public Trust: Fraud scandals frequently make headlines, creating reputational risk for banks that fail to protect their customers.

Without robust solutions, financial institutions risk losses, regulatory penalties, and erosion of customer confidence.

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Components of Effective Financial Fraud Solutions

AI-Driven Monitoring

Fraudsters continually adapt their methods. Static rules cannot keep up. AI-powered systems like Tookitaki’s FinCense continuously learn from evolving fraud attempts, helping banks identify subtle anomalies such as unusual login patterns or abnormal transaction velocity.

Behavioural Analytics

By analysing customer habits, institutions can detect deviations in real time. For example, if a user typically transfers small amounts domestically but suddenly sends large sums overseas, the system can raise alerts.

Federated Intelligence

Fraudsters target multiple institutions simultaneously. Sharing intelligence is key. Through Tookitaki’s AFC Ecosystem, Taiwanese institutions can access global fraud scenarios and typologies contributed by experts, enabling them to spot patterns that might otherwise slip through.

Smart Investigations

Compliance teams often struggle with false positives. FinCense reduces noise by applying AI to prioritise alerts, ensuring investigators focus on genuine risks while improving operational efficiency.

Customer Protection

Fraud prevention must protect without creating friction. Solutions that combine strong authentication, transparent processes, and smooth user experience help safeguard both customers and brand reputation.

Taiwan’s Regulatory Backdrop

The FSC has emphasised the importance of proactive fraud monitoring and has urged banks to implement real-time systems. Taiwan is also under the lens of FATF evaluations, which review the country’s AML and CFT frameworks.

Regulatory expectations include:

  • Comprehensive monitoring for suspicious activity.
  • Alignment with FATF’s risk-based approach.
  • Demonstrated capability to detect new and emerging fraud typologies.
  • Transparent audit trails that show how fraud alerts are handled.

Tookitaki’s FinCense addresses these requirements directly, combining explainable AI with audit-ready reporting to ensure regulatory alignment.

Case Study: Investment Scam Typology

Imagine a Taiwanese consumer is lured into a fraudulent investment scheme promising high returns. Funds are transferred into multiple mule accounts before being layered into overseas merchants.

Traditional rule-based systems may only flag the activity after multiple complaints. With FinCense, the fraud can be intercepted earlier. The platform’s federated learning detects similar patterns across institutions, recognising the hallmarks of mule activity and flagging the transactions in near real time.

This proactive approach demonstrates how advanced fraud solutions transform outcomes.

Technology at the Heart of Financial Fraud Solutions

The new era of fraud prevention in Taiwan is technology-driven. Leading platforms integrate:

  • Machine Learning Models trained on large and diverse fraud data sets.
  • Explainable AI (XAI) that provides clarity to regulators and compliance teams.
  • Real-Time Decision Engines that act within seconds.
  • Automated Dispositioning that reduces manual investigation overhead.
  • Cross-Border Data Insights that connect red flags across jurisdictions.

Tookitaki’s FinCense embodies this approach. Positioned as the Trust Layer to fight financial crime, it enables institutions in Taiwan to defend against fraud while maintaining operational efficiency and customer trust.

The Role of Consumer Awareness

Even the best technology cannot prevent every scam if customers are unaware of the risks. Taiwanese banks have a responsibility to educate consumers about common tactics such as smishing, fake job offers, and fraudulent investment opportunities.

Paired with AI-powered monitoring, awareness campaigns create a stronger, dual-layer defence. When customers know what to avoid and banks know how to intervene, fraud losses can be significantly reduced.

Building Trust and Inclusion

Fraud prevention is not just about stopping crime. It is also about building trust in the financial system. In Taiwan, where digital inclusion is a national priority, protecting vulnerable groups such as the elderly or first-time online banking users is critical.

Advanced fraud solutions ensure these groups can safely access financial services. By reducing fraud risk, banks help drive inclusion while protecting the integrity of the broader economy.

Collaboration Is the Future

Fraudsters are organised, networked, and global. Taiwan’s response must be the same. The future lies in collaborative solutions that connect institutions, regulators, and technology providers.

The AFC Ecosystem exemplifies this model, enabling knowledge sharing across borders and empowering institutions to stay ahead of evolving scams. Taiwan’s adoption of such frameworks can serve as a model for Asia.

Conclusion: Trust Is Taiwan’s Real Currency

In today’s financial system, trust is the currency that matters most. Financial fraud solutions are not only about protecting transactions but also about preserving confidence in the digital economy.

By leveraging advanced platforms such as Tookitaki’s FinCense, Taiwanese banks and fintechs can transform fraud prevention from a reactive defence to a proactive, intelligent, and collaborative strategy. The result is a financial system that is both innovative and resilient, positioning Taiwan as a leader in fraud resilience across Asia.

Inside Taiwan’s War on Scams: The Future of Financial Fraud Solutions
Blogs
11 Sep 2025
6 min
read

Account Takeover Fraud Detection: Protecting Australian Banks from a Growing Threat

Account takeover fraud is on the rise in Australia, and banks need advanced detection strategies to safeguard customers and meet AUSTRAC expectations.

Introduction

Imagine waking up to find that someone has drained your bank account overnight. This is the reality of account takeover (ATO) fraud, one of the fastest-growing financial crime threats worldwide. In Australia, with digital banking and real-time payments now the norm, account takeover fraud is becoming more frequent and costly.

For banks, fintechs, and payment providers, effective account takeover fraud detection is essential. It protects customers, preserves trust, and ensures compliance with AUSTRAC’s AML/CTF regulations. This blog explores how ATO works, red flags to watch for, and the strategies Australian institutions can use to fight back.

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What is Account Takeover Fraud?

Account takeover occurs when a criminal gains unauthorised access to a legitimate customer’s account. Once inside, they can:

  • Transfer funds instantly to mule accounts.
  • Make purchases using linked cards or wallets.
  • Change contact details to lock the victim out.
  • Exploit accounts for money laundering or layering activity.

ATO is often the starting point for broader fraud and laundering schemes.

How Criminals Commit Account Takeover

1. Phishing and Social Engineering

Fraudsters trick customers into revealing login credentials through fake emails, calls, or SMS messages.

2. Credential Stuffing

Stolen username and password combinations from data breaches are tested across multiple accounts.

3. Malware and Keylogging

Infected devices capture keystrokes, giving fraudsters access to login details.

4. SIM-Swapping

Mobile numbers are hijacked to intercept one-time passwords (OTPs).

5. Insider Threats

Employees with privileged access may collude with criminals to compromise accounts.

Why Account Takeover is a Major Risk in Australia

1. Real-Time Payments via NPP

Once fraudsters access an account, they can move funds instantly using the New Payments Platform. There is little time for recovery once the transfer is complete.

2. Scam Epidemic

ATO often overlaps with authorised push payment scams, where victims are manipulated into approving fraudulent transfers.

3. Increasing Digital Banking Adoption

With more Australians banking online and via apps, the attack surface for fraudsters has expanded significantly.

4. Regulatory Focus

AUSTRAC expects institutions to have systems capable of detecting suspicious login behaviour and unusual account activity.

Red Flags for Account Takeover Fraud Detection

  • Logins from unusual geographic locations.
  • Sudden device changes, such as a new mobile or browser.
  • Rapid changes in account details (email, phone number) followed by transactions.
  • High-value transfers to newly added beneficiaries.
  • Multiple failed login attempts followed by success.
  • Rapid pass-through activity with no account balance retention.
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Impact of Account Takeover Fraud

  1. Financial Losses: Customers may lose life savings, and banks may face liability.
  2. Reputational Damage: Trust erodes quickly when customers feel unsafe.
  3. Regulatory Penalties: Failing to detect and report ATO-related laundering can lead to AUSTRAC fines.
  4. Operational Burden: Investigating false positives consumes significant resources.

Strategies for Effective Account Takeover Fraud Detection

1. Real-Time Monitoring

Continuous risk scoring of logins, device activity, and transactions ensures fraud is detected as it happens.

2. Behavioural Analytics

Monitoring how users type, swipe, or interact with apps can reveal when an account is being accessed by someone else.

3. Device Fingerprinting

Unique device IDs and browser configurations help spot unauthorised access.

4. Multi-Factor Authentication (MFA)

Strengthens login security, though fraudsters may still bypass via SIM swaps or phishing.

5. AI and Machine Learning

Adaptive models detect unusual behaviour patterns without relying solely on rules.

6. Integrated Case Management

Alerts should flow directly to investigators with full context for rapid resolution.

7. Customer Education

Raising awareness of phishing and scams helps reduce the number of compromised accounts.

Challenges in Detecting ATO Fraud

  • False Positives: Legitimate unusual activity, such as travel, can trigger alerts.
  • Speed of Attacks: Fraudsters exploit real-time payments to move funds before detection.
  • Data Silos: Fragmented systems make it difficult to connect login and transaction activity.
  • Evolving Tactics: Criminals constantly refine phishing, malware, and credential-stuffing methods.

Case Example: Community-Owned Banks Taking Action

Community-owned banks like Regional Australia Bank and Beyond Bank are deploying advanced compliance platforms to detect account takeover fraud in real time. Despite their smaller scale, these institutions have strengthened customer protection while ensuring AUSTRAC compliance.

Their example shows that innovation in fraud detection is not limited to the big four banks. With the right technology, mid-sized institutions can deliver world-class protection.

Spotlight: Tookitaki’s FinCense for ATO Detection

FinCense, Tookitaki’s compliance platform, provides specialised features for account takeover fraud detection:

  • Real-Time Detection: Identifies suspicious login and transaction behaviour instantly.
  • Agentic AI: Adapts continuously to new fraud tactics while minimising false positives.
  • Federated Intelligence: Accesses scenarios from the AFC Ecosystem, providing insight into emerging ATO techniques.
  • FinMate AI Copilot: Summarises alerts, recommends next steps, and drafts regulator-ready reports.
  • Cross-Channel Coverage: Monitors activity across banking, wallets, remittances, and crypto.
  • AUSTRAC Alignment: Generates suspicious matter reports and maintains full audit trails.

By integrating these capabilities, FinCense allows Australian institutions to stop account takeover fraud before losses occur.

Future Trends in Account Takeover Fraud Detection

  1. Deepfake Impersonation: Fraudsters may use AI-generated voices or videos to bypass authentication.
  2. Smarter Bot Attacks: Automated credential stuffing will become more sophisticated.
  3. Shared Industry Databases: Banks will collaborate on intelligence to stop fraud mid-flight.
  4. AI-Powered Investigations: Copilots like FinMate will take on more of the investigative workload.
  5. Balance Between Security and UX: Customer-friendly authentication will remain a priority.

Conclusion

Account takeover fraud is one of the most dangerous threats facing Australian banks, fintechs, and payment providers today. Criminals exploit compromised credentials to move funds instantly, leaving little time for recovery.

For institutions, effective account takeover fraud detection requires a combination of real-time monitoring, behavioural analytics, adaptive AI, and regulator-ready reporting. Community-owned banks like Regional Australia Bank and Beyond Bank prove that strong defences are achievable for institutions of all sizes.

Pro tip: Do not rely solely on stronger logins. Combine authentication with real-time behavioural monitoring and AI-driven detection to stay ahead of account takeover fraud.

Account Takeover Fraud Detection: Protecting Australian Banks from a Growing Threat