What is KYT and why does it matter in compliance

What exactly is KYT?

Know Your Transaction (KYT) is software that provides organizations with crucial analysis to discover and identify suspicious fraudulent transactions made by customers based on their backgrounds and profiles.

A blockchain development company often focuses on building decentralized applications and smart contracts using blockchain development. These applications and contracts are designed to be secure and transparent, making them well-suited for a wide range of industries. However, as the use of blockchain technology becomes more widespread, it is important for these companies to also focus on compliance and "know your transaction" (KYT) measures. Compliance refers to the act of following laws, regulations, and guidelines that are relevant to the company's operations. KYT measures are used to identify and track the source of transactions on a blockchain network, in order to detect and prevent illicit activities such as money laundering and fraud. By implementing both strong technical solutions and compliance measures, a blockchain development company can ensure that its products and Blockchain development services are secure, transparent, and compliant with relevant laws and regulations

An effective KYT system enables financial institutions (FIs) to check for suspicious transactions by linking customer profiles to personal transactions.

Why is KYT necessary, and what problems can it solve?

On the one hand, blockchain characteristics such as decentralization, openness, autonomy, the immutability of information, and anonymity pose significant challenges for regulators.

On the other hand, digital financial enterprises find it challenging to conduct due diligence. Numerous digital financial institutions are incapable of identifying illegal transactions, assessing transaction risks, determining the status of user counterparty accounts, and assisting users in freezing suspicious addresses.

KYT (Know Your Transactions) enables VASP (virtual asset service providers), like cryptocurrency exchanges, to learn more about the physical identities of their customers and their transaction behaviours to detect money laundering, fraud, and other illegal activities.

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How does KYT function?

The Singapore Monetary Authority (MAS) identifies four stages in the transaction monitoring procedure.

Stage 1: Understanding the customer

Before establishing business relationships, financial institutions (FI) must ensure that their risk assessment frameworks and customer due diligence (CDD) measures are aligned with MAS's AML/CFT Notices during the initial phase of TM. These frameworks should be capable of identifying the risks that customers pose. Having established business relationships, FIs must maintain a current understanding of their customers.

Stage 2: Risk-Based Calibration

The second phase of TM is risk-based system calibration. Financial institutions must tailor their TM system to their "specific risks, contexts, and needs." Only when the parameter, threshold, and scenario settings are "appropriately configured and implemented" can financial institutions effectively use TM to "flag unusual transactions with a reasonable degree of certainty of potential ML/TF characteristics warranting further investigation."

Additionally, FIs should conduct periodic backtesting. Backtesting is analyzing historical data to "generate results and assess risk and profitability before risking actual capital." Backtesting enables businesses to determine if their TM requires modifications. This ensures the organization remains current and enables more precise monitoring of customer transactions and behaviours.

Under risk-based calibration, financial institutions must also consider the reliability of data. To what extent are data accurate and complete? True, comprehensive, and consistent." Consequently, this could implement adequate detection control checks to "ensure that data are captured completely and accurately in source systems and transmitted to their TM systems." The checks enable FIs to detect, evaluate, and explain any anomalies and failures resulting from data integrity issues.

Stage 3: Robust implementation

The primary challenge of operating a TM system is ensuring the quality, accuracy, and consistency of employees who handle TM alerts. Therefore, FIs need to provide their employees with adequate training and direction to carry out their responsibilities effectively. To strengthen the TM process, FIs could conduct pre-transaction checks, handle alerts appropriately, and document the process.

Stage 4: Resolve and Improve

In the final phase of TM, when FIs discover that particular transactions are questionable or appear fraudulent, they must file suspicious transaction reports (STRs) immediately by contacting the Suspicious Reporting Office (STRO). If, after filing for STR, the FI chooses to maintain the business relationship with the customer, it must take appropriate measures to mitigate the risks associated with these suspicious customer accounts. These are known as post-STR practices. Last but not least, FIs must conduct quality assurance (QA) tests on a sample of alerts to ensure the efficiency and effectiveness of the TM process.

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What are the benefits of the newly implemented KYT?

Using 1 billion or more address tags (mapping addresses to real-world entities), blockchain big data analytics technology and advanced AI technology, the cryptocurrency AML compliance and analytics platform creates a cryptocurrency tracking and AML system that can help VASPs build KYT and continuous risk assessment capabilities.

KYT can assist clients in avoiding interactions with potentially malicious or risky addresses, meeting global regulatory requirements, preventing damage to client funds and reputation, and identifying abnormal behaviour. In addition, the Path Tracing feature can intelligently expand suspicious addresses to facilitate risk verification.

  • Exemplary risk scoring system
    KYT includes an exhaustive risk-scoring mechanism. Through continuous monitoring of crypto transactions, risk penetration analysis of fund flow for each transaction, and an advanced abnormal behaviour analysis engine, it provides clients with professional and comprehensive risk assessment reports. Not only is the risk score of the address/transaction provided, but also the details and characteristics of each risky transaction, enabling users to understand the risk situation comprehensively.
  • Industry-leading capabilities in intelligent behaviour analysis
    KYT has accumulated more than one billion abnormal address labels, and these labels can be mapped to real-world entities. In addition, it has an efficient, intelligent analysis engine designed independently using machine learning and deep learning technologies to detect high-risk transactions promptly and alert users beforehand.
  • Simple-to-use Web and API methods
    KYT can provide a user-friendly interface and expert API integration solutions to meet the needs of businesses in various scenarios.

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