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Why Is KYC Necessary for Banking Institution Security?

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Tookitaki
5 min
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The aircraft hijackers who carried out the deadliest attack on America on September 11, 2001 used The Hudson United Bank of New Jersey as one of the financial institutions to facilitate their attack. According to the 9/11 Commission, money-laundering safeguards in the financial industry at the time were not designed to identify or disrupt the kind of deposits, withdrawals, and wire transfers that assisted in the attacks. As a result, Know Your Customer (KYC) rules were created as part of the Patriot Act to prevent terrorist operations and financial crimes.

 

What is the difference between KYC and AML?

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.

To combat the rising problem of money laundering, national and international agencies all over the globe issue guidelines to the banking 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 programmes.

 

Why KYC (Know Your Customer) Was Implemented for Banking

Know Your Customer (KYC) legislation was enacted as part of the Patriot Act to combat terrorism financing and financial crimes.
Because money launderers and other criminals frequently use false identities to conceal their true identities during the onboarding process, KYC policies require financial institutions to “get to know” their customers by confirming to a high level of assurance that those customers are who they say they are.

With so much relying on KYC and Customer Identification Procedures (CIP) in banking getting it right, and with increasing customer onboarding taking place online, it’s no wonder that financial institutions are searching for effective technology to remotely verify consumers’ identities. In this article, we’ll look at some of those technologies and how they’re being utilised in financial services to meet KYC and enhanced due diligence standards.

Why is KYC compliance required?

For decades, the United States Department of the Treasury has enacted legislation requiring financial institutions to help the government in identifying and combating money laundering.

For example, the Bank Secrecy Act of 1970 mandates financial firms to preserve specified documents related to money laundering, tax evasion or other criminal activities. In 2016, the Treasury’s Financial Crimes Enforcement Network (FinCEN) issued a series of rulings to clarify and tighten Customer Due Diligence (CDD) obligations and Anti-Money Laundering (AML) measures.

Requiring financial institutions to perform due diligence in order to understand who their customers are and what types of transactions they engage in is a critical component of combating all forms of illicit financial activity, from terrorist financing and sanctions evasion to more traditional financial crimes.

Banks spent more than $100 billion in 2016 to satisfy KYC compliance and regulators, and it is expected that compliance costs would climb by four to ten percent by 2021. Despite these massive investments, according to Fenergo data, approximately $26 billion in fines were levied on financial institutions in the previous decade for noncompliance with AML and KYC standards.

KYC Procedures Used by Banks and Financial Institutions

FinCEN specified four minimal elements needed for an efficient KYC procedure in order to clarify and reinforce CDD regulations and fulfil KYC in the financial industry.
These regulatory obligations include:

  1. Identifying and validating consumers’ identities
  2. Monitoring client activity for suspicious transactions on a continual basis, as well as preserving and updating customer information depending on risk indicators.
  3. Identifying and authenticating the identification of legal entity customers’ beneficial owners (i.e., natural individuals who own or control legal entities)
  4. Recognising the nature and purpose of customer connections in order to create a customer risk profile

 

What is required from customers during the onboarding process?

To comply with these KYC regulations, financial institutions must collect and verify identification information when onboarding new customers. The criteria differ depending on whether the bank account is for an individual or a corporation. Individual clients who visit a bank in person will carry some kind of identification, such as a driver’s licence or passport, as well as proof of address and any other documentation that may be necessary for the transaction. The banker examines the customer’s documents to ensure that they are who they claim to be.

Additional documentation establishing the identity of beneficial owners (e.g., articles of incorporation) and business activity (e.g., profit and loss statements) is necessary for business accounts.

When clients open accounts online, the processes become significantly more complicated. Customers’ digital identities must now be verified by financial institutions to ensure that they correspond to their actual, physical identities. To establish a trustworthy link between a digital identity and a real person, a rigorous identity verification mechanism is required to ensure the person is who they claim to be and to monitor any questionable behaviour. This approach may employ a combination of biometrics for example, machine learning, and/or document or ID verification.

Regtech for KYC and 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.

Furthermore, 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 high 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 field of AML compliance, a sophisticated solution that can capture changing client behaviour through effective detection of risk indicators and regularly update customer profiles as underlying activities change is urgently required. There are Regtech solutions available to ensure correct AML- KYC compliance in a long-term way.

Tookitaki’s solutions for AML – KYC compliance

Many financial institutions are now using Tookitaki’s unique solutions.

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
22 Aug 2025
4 min
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Stopping Fraud in Its Tracks: Transaction Fraud Prevention in Taiwan’s Digital Age

Fraud moves fast and in Taiwan’s digital-first economy, transaction fraud prevention has become the frontline of trust.

With payment volumes soaring across e-wallets, online banking, and instant transfers, the fight against fraud is no longer about catching criminals after the fact. It’s about detecting and stopping them in real time. Advanced platforms such as Tookitaki’s FinCense are redefining how financial institutions in Taiwan and beyond approach this challenge — blending AI, collaboration, and regulatory alignment to build smarter defences.

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Taiwan’s Digital Finance Boom and the Fraud Challenge

Taiwan has become one of Asia’s leaders in digital payments, with e-wallet adoption rising sharply and cross-border transactions powering e-commerce. But speed and convenience come with vulnerabilities:

  • Account Takeover (ATO): Fraudsters gain access to accounts via phishing or malware.
  • Money Mules: Recruited individuals move illicit funds through small-value transactions.
  • Synthetic Identities: Fake profiles slip past onboarding checks to exploit payment rails.

Regulators such as the Financial Supervisory Commission (FSC) have ramped up requirements, urging banks and payment firms to adopt risk-based monitoring. But compliance alone isn’t enough — prevention requires smarter tools and adaptive intelligence, the kind being pioneered by Tookitaki’s AI-powered compliance platform.

What Is Transaction Fraud Prevention?

At its core, transaction fraud prevention means identifying, analysing, and blocking suspicious payments before they can be completed. Unlike post-event investigations, prevention focuses on:

  1. Real-Time Detection – Flagging anomalies instantly.
  2. Behavioural Analytics – Profiling normal user patterns to spot deviations.
  3. Risk Scoring – Assigning risk levels to every transaction.
  4. Adaptive Learning – Using AI to refine rules as fraud evolves.

For Taiwan, where instant payments via the Financial Information Service Co. (FISC) platform are mainstream, real-time fraud prevention is a necessity. Platforms like FinCense help banks achieve this by combining speed with precision.

Key Fraud Risks in Taiwan

1. Account Takeover via Phishing

Taiwanese banks report rising cases of SMS phishing (“smishing”), where fraudsters impersonate institutions. Once accounts are breached, rapid fund transfers are executed before victims react.

2. Online Investment Scams

Cross-border scam syndicates target Taiwanese consumers with fraudulent investment schemes, funnelling proceeds through mule networks.

3. Social Engineering

“Pig butchering” scams, romance fraud, and fake job offers have become prominent, with victims manipulated into initiating fraudulent transfers themselves.

4. Merchant Fraud

E-commerce sellers set up fake storefronts, collect payments, and disappear, leaving banks to handle disputes and reputational risks.

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Strategies for Effective Transaction Fraud Prevention

Real-Time Monitoring

Fraud can unfold in seconds. Systems must analyse every transaction as it occurs, applying machine learning to flag suspicious transfers instantly. Tookitaki’s FinCense does this by ingesting real-time data streams and applying dynamic thresholds that adapt as fraud tactics change.

AI-Driven Risk Modelling

Instead of static rules, AI models learn from both fraud attempts and genuine behaviour. For example, FinCense leverages federated learning from a global network of institutions, enabling it to detect anomalies like unusual device fingerprints or abnormal transaction velocity — even when fraudsters attempt never-before-seen tactics.

Cross-Institution Collaboration

Fraudsters rarely confine themselves to one bank. Taiwan’s industry can strengthen defences by sharing red flags across institutions. Through the AFC Ecosystem, Tookitaki empowers banks and fintechs to access shared typologies and indicators, helping the industry act collectively against emerging fraud schemes.

Regulatory Alignment

The FSC requires strict fraud monitoring standards. Tookitaki’s compliance solutions are designed with explainable AI and governance frameworks, aligning directly with regulatory expectations while maintaining operational efficiency.

Customer Awareness

Technology alone isn’t enough. Banks should run consumer education campaigns to help customers spot phishing attempts and suspicious investment offers. FinCense complements this by reducing false positives, ensuring customers are not unnecessarily disrupted while genuine fraud attempts are intercepted.

Transaction Fraud Prevention in Practice

Case Example:

A Taiwanese bank detected an unusual pattern where multiple accounts began transferring small sums to the same overseas merchant. Using behavioural analytics powered by AI, the system flagged it as mule activity. Within minutes, the institution froze accounts, reported to the FSC, and prevented further losses.

Solutions like FinCense allow this type of proactive monitoring at scale, reducing detection lag and limiting potential reputational damage.

How Technology Is Raising the Bar

Transaction fraud prevention is no longer just about blacklists or simple thresholds. Cutting-edge solutions now combine:

  • Machine Learning Models trained on fraud typologies
  • Federated Intelligence Sharing across institutions to learn from global red flags
  • Explainable AI (XAI) to ensure transparency in decisions
  • Automated Investigation Tools to reduce false positives and improve efficiency

Tookitaki’s FinCense unites these capabilities into a single compliance platform — enabling financial institutions in Taiwan to monitor transactions in real time, adapt to evolving risks, and demonstrate clear accountability to regulators.

Why Transaction Fraud Prevention Matters for Taiwan’s Reputation

Taiwan’s financial system is a trusted hub in Asia. Yet with global watchdogs like FATF scrutinising AML/CFT effectiveness, a weak approach to fraud prevention could tarnish the country’s standing.

Robust prevention not only protects banks and customers — it safeguards Taiwan’s role as a secure, innovation-driven financial market. Tookitaki’s role as the “Trust Layer to fight financial crime” helps institutions balance growth and security, ensuring trust remains central to Taiwan’s digital finance journey.

Conclusion: Building Smarter Defences for Tomorrow

Fraudsters are fast, but Taiwan’s financial industry can be faster. By investing in transaction fraud prevention powered by AI, data collaboration, and regulatory alignment, banks and payment firms can build a financial system rooted in trust.

With advanced platforms like Tookitaki’s FinCense, institutions can move beyond reactive defence and adopt proactive, intelligent, and collective prevention strategies. Taiwan now has the opportunity to set the benchmark for Asia — proving that convenience and security can go hand in hand.

Stopping Fraud in Its Tracks: Transaction Fraud Prevention in Taiwan’s Digital Age
Blogs
22 Aug 2025
5 min
read

Chasing Zero Fraud: Finding the Best Anti-Fraud Solution for Australia

Fraudsters are getting smarter — but the best anti-fraud solutions are evolving even faster.

Fraud in Australia is no longer just about stolen credit cards or phishing emails. Today, fraudsters use AI deepfakes, synthetic identities, and mule networks to move billions through legitimate institutions. Scamwatch reports that Australians lost over AUD 3 billion in 2024, and regulators are tightening expectations. In this climate, choosing the best anti-fraud solution isn’t just an IT decision — it’s a strategic imperative.

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Why Fraud Prevention Has Become Business-Critical in Australia

1. Instant Payment Risks

The New Payments Platform (NPP) has made payments faster, but it also allows criminals to launder money in seconds.

2. Social Engineering & Scam Surge

Romance scams, impersonation fraud, and investment scams are rising sharply. Many involve victims authorising payments themselves — a challenge for traditional detection systems.

3. Regulatory Pressure

AUSTRAC and ASIC expect financial institutions to adopt proactive fraud prevention. Weak controls can lead to fines, reputational loss, and customer churn.

4. Consumer Trust

Australians expect safe, frictionless digital experiences. A single fraud incident can erode customer loyalty.

What Defines the Best Anti-Fraud Solution?

1. Real-Time Fraud Detection

The solution must monitor and analyse transactions instantly, with no batch delays.

  • Velocity monitoring
  • Device and IP fingerprinting
  • Behavioural biometrics
  • Pattern recognition

2. AI and Machine Learning

The best anti-fraud systems use AI to adapt to new typologies:

  • Spot anomalies that rules miss
  • Reduce false positives
  • Continuously improve detection accuracy

3. Multi-Channel Protection

Covers fraud across:

  • Bank transfers
  • Card payments
  • E-wallets and digital wallets
  • Remittances and cross-border corridors
  • Crypto exchanges

4. End-to-End Case Management

Integrated workflows that allow fraud teams to investigate, resolve, and report within the same system.

5. Regulatory Alignment

Supports AUSTRAC compliance with audit trails, suspicious matter reporting, and explainability.

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Use Cases for Anti-Fraud Solutions in Australia

  • Account Takeover (ATO): Detects unusual login + transfer behaviour.
  • Payroll Fraud: Flags sudden beneficiary changes in salary disbursement files.
  • Romance & Investment Scams: Detects unusual transfer chains to new or overseas accounts.
  • Card-Not-Present Fraud: Blocks suspicious e-commerce transactions.
  • Crypto Laundering: Identifies fiat-to-crypto activity linked to high-risk wallets.

Red Flags the Best Anti-Fraud Solution Should Catch

  • Large transfers to newly added beneficiaries
  • Multiple small transactions in rapid succession (smurfing)
  • Login from a new device/IP followed by immediate transfers
  • Customers suddenly transacting with high-risk jurisdictions
  • Beneficiary accounts linked to mule networks

How to Choose the Best Anti-Fraud Solution in Australia

Key questions to ask:

  1. Can it handle real-time detection across all channels?
  2. Does it integrate seamlessly with your AML systems?
  3. Is it powered by adaptive AI that learns from evolving fraud tactics?
  4. How well does it reduce false positives?
  5. Does it meet AUSTRAC’s compliance requirements?
  6. Does it come with local expertise and support?

Spotlight: Tookitaki’s FinCense as the Best Anti-Fraud Solution

Among global offerings, FinCense is recognised as one of the best anti-fraud solutions for Australian institutions.

  • Agentic AI detection for real-time fraud monitoring across banking, payments, and remittances.
  • Federated learning from the AFC Ecosystem, bringing in global crime typologies and real-world scenarios.
  • FinMate AI copilot helps investigators close cases faster with summarised alerts and recommendations.
  • Cross-channel visibility covering transactions from cards to crypto.
  • Regulator-ready transparency with explainable AI and complete audit trails.

FinCense not only detects fraud — it prevents it by continuously learning and adapting to new scam typologies.

Conclusion: Prevention = Protection = Trust

In Australia’s high-speed financial landscape, the best anti-fraud solution is the one that balances real-time detection, adaptive intelligence, and seamless compliance. It’s not just about stopping fraud — it’s about building trust and future-proofing your institution.

Pro tip: Don’t just ask if a solution can detect today’s fraud. Ask if it can evolve with tomorrow’s scams.

Chasing Zero Fraud: Finding the Best Anti-Fraud Solution for Australia
Blogs
21 Aug 2025
5 min
read

Malaysia’s Compliance Edge: Why an Industry-Leading AML Solution Is Now Essential

Financial crime is moving faster than ever — and Malaysia needs an AML solution that can move faster still.

The Rising Stakes in Malaysia’s Fight Against Financial Crime

In Malaysia, the financial sector is at a crossroads. With rapid digitalisation, the boom in fintech adoption, and cross-border flows surging, financial crime has found new entry points. Bank Negara Malaysia (BNM) has been firm in its stance: compliance is not optional, and institutions that fail to meet evolving standards face reputational and financial fallout.

At the same time, fraudsters are becoming more sophisticated. From money mule networks exploiting young workers and students to investment scams powered by social engineering and deepfakes, Malaysia is seeing threats that transcend borders.

Against this backdrop, the demand is clear: financial institutions need an industry-leading AML solution that not only meets regulatory expectations but also builds consumer trust in a fast-changing market.

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Why “Industry Leading” Is More Than a Buzzword

Every vendor claims to offer the “best” AML software, but in practice, very few solutions rise to the level of being industry leading. In the Malaysian context, where financial institutions must juggle FATF recommendations, BNM guidelines, and ASEAN cross-border risks, the definition of “industry leading” is clear.

An AML solution in Malaysia today must be:

  • AI-driven and adaptive — able to evolve with new money laundering and fraud typologies.
  • Regulator-aligned — transparent, explainable, and in line with AI governance principles.
  • Comprehensive — covering both AML and fraud in real-time, across multiple payment channels.
  • Scalable — capable of supporting banks and fintechs with diverse customer bases and transaction volumes.
  • Collaborative — leveraging intelligence beyond siloed data to detect emerging risks faster.

Anything less leaves financial institutions vulnerable.

The Challenge with Legacy AML Systems

Many Malaysian banks and fintechs still rely on legacy transaction monitoring systems. While these systems may tick the compliance box, they struggle with modern threats. The common pain points include:

  • High false positives — compliance teams are overwhelmed with noise instead of meaningful alerts.
  • Static rule sets — traditional systems cannot keep pace with the speed of criminal innovation.
  • Limited explainability — leaving compliance officers unable to justify decisions to regulators.
  • Fragmentation — siloed systems across AML and fraud prevention create blind spots in detection.

The result? Compliance teams are overstretched, risks are missed, and customer trust is eroded.

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Tookitaki’s FinCense: Malaysia’s Industry-Leading AML Solution

This is where Tookitaki’s FinCense stands apart — not just as another AML system, but as the Trust Layer to fight financial crime.

FinCense is purpose-built to help financial institutions in Malaysia and beyond move from reactive compliance to proactive prevention. Here’s why it leads the industry:

1. Agentic AI Workflows

FinCense harnesses Agentic AI, a next-generation compliance framework where AI agents don’t just analyse data but take proactive actions across the investigation lifecycle. This enables:

  • Automated alert triage
  • Smarter case management
  • Real-time recommendations for compliance officers

The outcome: compliance teams spend less time firefighting and more time making strategic decisions.

2. Federated Learning: Collective Intelligence at Scale

Unlike siloed systems, FinCense taps into a federated learning model through the AFC Ecosystem — a community-driven network of financial institutions, regulators, and compliance experts. This allows Malaysian banks to detect threats that may have first emerged in other ASEAN markets, giving them a head start against syndicates.

3. Explainable, Regulator-Aligned AI

Trust in compliance technology hinges on explainability. FinCense is designed to be fully explainable and auditable, aligned with frameworks like Singapore’s AI Verify. For Malaysian banks, this ensures regulators can clearly understand the basis for alerts, reducing friction and enhancing oversight.

4. End-to-End Coverage: AML + Fraud

FinCense goes beyond AML, offering integrated coverage across:

  • Transaction monitoring
  • Name screening
  • Fraud detection
  • Smart disposition and narration tools for investigations

This eliminates the need for multiple systems and ensures compliance teams have a single view of risk.

5. ASEAN Market Fit

FinCense is not a one-size-fits-all solution. Its scenarios and typologies are tailored to the realities of ASEAN markets, including Malaysia’s unique mix of cross-border remittances, e-wallet adoption, and high cash usage. This localisation ensures higher detection accuracy and relevance.

What This Means for Malaysian Banks and Fintechs

Adopting an industry-leading AML solution like FinCense translates to tangible benefits:

  • Reduced Compliance Costs — through automation and lower false positives.
  • Faster, More Accurate Detection — stopping illicit funds before they can be layered or withdrawn.
  • Regulatory Confidence — meeting BNM and FATF expectations with explainable, auditable AI.
  • Stronger Customer Trust — safeguarding against scams and building confidence in digital finance.

With Malaysia pushing to strengthen its financial system and attract international investment, trust is the new currency. A compliance framework that prevents financial crime effectively is no longer optional — it is foundational.

The Road Ahead: Building Malaysia’s Trust Layer

Financial crime is only going to get smarter. With the rise of instant payments, deepfake-driven scams, and cross-border mule networks, Malaysia’s financial sector needs a solution that evolves just as quickly.

Tookitaki’s FinCense is more than software — it is the Trust Layer that empowers banks and fintechs to detect risks early, protect customers, and stay a step ahead of regulators and criminals alike.

For Malaysian financial institutions, the choice is clear: staying competitive in the region means adopting an industry-leading AML solution that can deliver speed, precision, and transparency at scale.

Malaysia’s Compliance Edge: Why an Industry-Leading AML Solution Is Now Essential