KYC Not Enough? Growing Importance of Know Your Transaction (KYT)

Have you heard of Know Your Business (KYB) or Know Your Customer (KYC)? Of course, you have! These concepts are well-known to most people in the business world as they help ensure the origin of transactions. But what about the transaction itself?

There are undoubtedly various purposes for transactions that organizations would want to be aware of, and that’s where Know Your Transaction (KYT) comes in. With KYT, businesses can gain a deeper understanding of their transactions and take the necessary steps to mitigate any risks.

What is Know Your Transaction (KYT)?

KYT is an approach to using data from transactions in real-time to profile all parties involved, and predict whether a transaction is usual or not, adding context to the alert, and allowing the analyst to make more informed and faster decisions. KYT know your transaction leverages data and looks comprehensively at all transactions, thereby generating much richer insights.

KYT is not a specific system or program in itself, but rather an approach or methodology used by financial institutions to enhance transaction monitoring and compliance efforts.

It involves leveraging technology, data analytics, and comprehensive data sets to gain deeper insights into individual transactions, detect patterns of suspicious activity, and identify potential money laundering or other financial crimes.

KYC Vs KYT: The Key Differences

Both KYC and KYT are important in identifying potential risks but differ in their approaches.

When opening a bank account, insurance policy, investment, or pension scheme, the term Know Your Customer is often mentioned. This critical step ensures that businesses thoroughly understand their clients, their identities, and the potential risks involved in establishing a business relationship. This process is paramount to preventing illegal activities and safeguarding financial institutions from fraud.

On the other hand, Know Your Transaction involves obtaining comprehensive, granular, data-centric information about their customers’ transactions. For instance, major economic activities could occur in a customer’s account, from domestic cash transactions to international card transactions, remittances (inward and outward), cross-border transactions, and trade finance transactions to bills.

KYT know your transaction enables banks and financial institutions to identify, monitor, and report suspicious or unusual transactions, ensuring compliance with regulatory requirements.

Why is KYC Not Enough?

Financial institutions are facing increasingly stringent KYC requirements, as global regulators aim to standardize guidelines for customer due diligence. However, despite guidelines detailing uniform requirements for what information should be gathered about the customer, they cannot be considered universally accepted standards.

While some countries have established defined rules and processes to comply with these requirements, others leave it up to businesses to adopt their own strategy.

Currently, many institutions still rely on static manual processes for KYC and due diligence. This means that once a customer’s credentials have been verified, there is often little to no follow-up or ongoing monitoring to ensure that the customer doesn’t pose a risk in the long run.

Additionally, client records are frequently stored in paper form after onboarding, until legal requirements mandate otherwise. This presents a significant challenge for banks and other financial institutions, as they search for ways to address these issues and maintain compliance.

Why is KYT Gaining Importance?

KYT implementation is essential because it helps financial institutions comply with Anti-Money Laundering (AML) and Counter-Terrorist Financing (CTF) regulations and protect themselves from legal, economic, and reputational risks.

KYT is no longer optional but a regulatory requirement to prevent financial crimes such as money laundering. You may have heard of solutions, such as Transaction Monitoring Systems (TMS), Anti-Money Laundering (AML), or Customer Due Diligence (CDD); these components collectively contribute to the effectiveness of the KYT approach in detecting and preventing suspicious activity and financial crimes.

The Financial Action Task Force (FATF) recommendations, the European Union’s Fourth Anti-Money Laundering Directive (AMLD4), and the United States Bank Secrecy Act (BSA) require financial institutions to implement a risk-based approach to AML/CTF compliance and adopt measures such as customer due diligence, transaction monitoring, and reporting suspicious activities to the relevant authorities.

For instance, in the United States, a joint statement from five regulatory authorities highlighted the importance of investing in Artificial Intelligence (AI) and other technological advancements to enhance compliance programs.

KYT: Regulatory Landscape

There are no specific global regulations that solely focus on KYT; however, these practices are commonly integrated within the broader regulatory frameworks for anti-money laundering (AML) and counter-terrorism financing (CTF).

The guidelines for these regulations may vary across countries and jurisdictions, but financial institutions must comply with the specific guidelines established by their respective national authorities. Below are some examples of regulatory frameworks that encompass KYT principles:

Financial Crimes Enforcement Network (FinCEN) – United States

• FinCEN, a bureau of the U.S. Department of the Treasury, administers the Bank Secrecy Act (BSA) and provides guidance and regulations related to AML and CTF.
• U.S. financial institutions must implement effective transaction monitoring systems to identify and report suspicious activities. These systems involve ongoing due diligence on customer transactions.
• For instance, The USA PATRIOT ACT amended the Bank Secrecy Act (BSA) by introducing Section 352, which mandates financial institutions to take cognizance of an effective anti-money laundering (AML) compliance program.
• The Act recommends that to confirm compliance with regulations; financial institutions must establish risk-based procedures for ongoing customer due diligence to detect and report any suspicious transactions while also ensuring the regular maintenance and updating of customer information.

European Union (EU) – Anti-Money Laundering Directive (AMLD)

• The EU has implemented several directives to combat money laundering and terrorist financing, including the AMLD.
• The AMLD sets out requirements for customer due diligence, risk assessments, and transaction monitoring to detect and report suspicious transactions.
• The directive mandates measures to include identifying and verifying client identities, monitoring ongoing transactions, and reporting suspicious transactions. These mandates are regularly updated to address and minimize the risks associated with money laundering and terrorist financing.

Financial Action Task Force (FATF) Recommendations

• The FATF provides global standards and recommendations for AML and CTF measures.
• While the FATF primarily focuses on Know Your Customer (KYC), its recommendations emphasize the need for ongoing monitoring and understanding of customer transactions as part of effective AML/CFT programs.
• The interpretative note accompanying FATF Recommendation 10 on Customer Due Diligence emphasizes the importance of considering four risk factors:
  • Products, services, and transactions
  • Customer-related risks
  • Risks associated with specific countries and geographical areas
  • Risks related to distribution channels
• In jurisdictions with robust anti-money laundering and countering the financing of terrorism frameworks, it is a legal requirement to report any suspicious transactions promptly upon detection.

The Challenges of Implementing an Effective KYT Program

Implementing Know Your Transaction (KYT) practices can pose several challenges for organizations. We have listed a few key challenges here:

Data Volume and Velocity: With millions of daily transactions, managing and processing such a massive volume of data in real-time can be daunting. Organizations need robust infrastructure and systems capable of handling and analyzing large amounts of transactional data without compromising performance.

Data Quality and Integration: Ensuring transaction data’s accuracy, completeness, and consistency is crucial for effective KYT. However, data from different sources may vary in quality and format, making integrating and analyzing the data effectively challenging. Data cleansing and standardization processes are necessary to address these challenges.

False Positives and False Negatives: Implementing rule engines and algorithms for transaction analysis may result in false positives (flagging legitimate transactions as suspicious) or false negatives (overlooking actual suspicious transactions). Striking the right balance between accurately identifying suspicious activities and minimizing false alerts is a continuous challenge.

Regulatory Compliance: Maintaining ever-changing regulatory requirements and guidelines can be demanding. Organizations must ensure their KYT practices align with the latest anti-money laundering (AML) and counter-terrorism financing (CFT) regulations, often involving complex legal and compliance considerations.

Resource Allocation: Deploying and maintaining advanced technologies, such as automation and machine learning, requires substantial investments in infrastructure, skilled personnel, and ongoing training. Organizations need to allocate sufficient resources to implement and manage KYT practices effectively.

Privacy and Data Protection: KYT practices involve collecting and analyzing sensitive customer data, raising concerns regarding confidentiality and data protection. Organizations must implement robust security measures and adhere to data privacy regulations to safeguard customer information.

Cross-Border Transactions: For organizations operating in multiple jurisdictions, cross-border transactions introduce additional complexities. Countries may have varying AML/CFT frameworks and reporting requirements, necessitating a comprehensive understanding of global compliance obligations.

KYT: Tech Enablers

Artificial Intelligence (AI) and Machine Learning (ML): AI and ML algorithms can analyze real-time transactional data, identify patterns, and detect anomalies. These technologies continuously learn and adapt to evolving risks, improving accuracy in identifying suspicious transactions.

Rule-Based Engines: Rule engines apply predefined rules and criteria to transaction data to identify potential red flags. These rules can be customized based on specific risk profiles, compliance requirements, and regulatory guidelines.

Robotic Process Automation (RPA): RPA automates repetitive and rule-based tasks, reducing manual effort and increasing operational efficiency. It can be utilized for data extraction, validation, and generating alerts, improving the speed and accuracy of transaction monitoring.

Natural Language Processing (NLP): NLP technologies enable the analysis of unstructured data sources such as news articles, social media, and online forums. They help identify relevant information and sentiments indicating potential risks or illicit activities.

An Overview of the KYT Approach

KYT adoption in the financial services sector is expected to follow a gradual progression to gain trust and demonstrate its value. The journey can be divided into several phases:

Initial Phase: During this stage, KYT will enhance screening alerts by providing additional context through analytics scores, helping prioritize alerts, and aiding analysts in making more informed decisions. The feedback from analysts will contribute to building a labeled dataset for training and improving the model.

Intermediate Phase: In the subsequent phase, the model will be capable of suggesting decisions that analysts can validate or reject. This iterative feedback loop will further enhance the model’s accuracy by incorporating real-world outcomes.

Advanced Phase: Once the training cycle is complete, the model will have a high level of accuracy, potentially surpassing human decision-making. At this point, the model can autonomously handle a significant portion of alerts, with appropriate supervision and auditing to ensure compliance.

With the increasing volume of digital transactions and the need for seamless payments, relying on outdated technology for transaction screening is no longer viable. KYT offers a risk-free approach to expediting the alert resolution process by providing enriched context to analysts, ultimately reducing the number of alerts requiring manual intervention.

KYT Use Cases and Importance Across Industries

KYT practices find use cases in a wide range of industries. Here are some examples:

Banking and Financial Services: KYT is crucial for banks and financial institutions to detect and prevent money laundering, fraud, and other financial crimes. It helps monitor customer transactions, identify suspicious activities, and ensure compliance with regulatory requirements.

E-commerce and Retail: KYT plays a vital role in fraud prevention and risk management in online transactions. By analyzing real-time transaction data, businesses can identify fraudulent patterns, flag suspicious transactions, and protect themselves and their customers from fraudulent activities.

Cryptocurrency: With the rise of cryptocurrencies, KYT is essential for maintaining transparency, preventing illicit activities, and complying with regulatory frameworks. It helps cryptocurrency exchanges and platforms monitor transactions, detect suspicious behavior, and ensure compliance with anti-money laundering (AML) and KYC regulations.

Overall, KYT is of utmost importance across several industries to enhance transaction monitoring, prevent financial crimes, ensure compliance with regulations, and protect businesses and customers from risks associated with illicit activities.