Uppsala Security, a provider of security tools and services for Crypto AML/CTF, Transaction Risk Management, Regulatory Compliance, Transaction Tracking, and Cyber Security recently announced that it has developed a new Crypto Threat Detection System (CTDS) that handles Suspicious Transaction Reporting (STR) and Counterfeit Currency Reporting (CTR) “for millions of additional virtual asset wallets with just one click through Artificial Intelligence-based suspicious transaction detection systems.”
In South Korea the “Travel Rule” was mandatory “for domestic virtual asset service providers (VASPs) as of March 2022, and it emerged as a safety tool for preventing Money Laundering.”
However, Uppsala Security explains that simply “collecting and exchanging data on virtual asset senders and receivers does not completely eliminate the risk of sanctions as high as hundreds of Millions of KRW in fines and warnings from the Financial Intelligence Unit (FIU).”
According to the results of an on-site inspection released by South Korea’s Financial Intelligence Unit (koFIU) on the 29th of September, virtual asset operators “must identify and analyze the Money Laundering risks inherent in virtual asset transactions in order to differentiate how these should be handled and also continue to monitor and report transactions even after reporting suspicious transactions to the FIU.”
However, the industry’s position is that “it is extremely challenging to check and monitor suspected transactions of numerous wallets manually (one by one) with insufficient compliance monitoring personnel.”
In response, Uppsala Security “detailed the background of the Crypto Threat Detection System’s (CTDS) development, explaining its capabilities to establish an efficient virtual asset Money Laundering prevention system in compliance with the ‘Travel Rule’ and similar regulations with a minimum number of dedicated personnel and significant time reduction.”
CTDS can “automatically check the risk of suspicious transactions and high-value transactions of millions of wallets by simply using the drag and drop function of CSV files containing large amounts of wallet addresses.”
The tool uses Machine Learning algorithms “based on 24 suspicious transaction scenarios, for example wallets that have been involved in Money Laundering or fraud and that are in & out of the online market or have shown abnormal transaction patterns.”
There are 4 different risk categories that can “be attributed to the investigated wallets: Extremely High Risk, High Risk, Medium Risk and Low Risk.” In addition, wallets with large funds of more than KRW 20 Million “can be filtered out at the same time and used as Counterfeit Currency Reporting (CTR) indicators.”
An official at Uppsala Security explained:
“Reports on suspected and high-value transaction wallets can be immediately downloaded as PDF files, and the data can be used as essential evidence when reporting suspicious transactions to the FIU.”
In addition, CTDS is a SaaS (Software as a Service) type of per-wallet service that “enables all virtual asset AML functions to be used in a one-stop manner, and the related cost is significantly reduced compared to the existing virtual asset AML implementations, which can cost up to tens of Millions of dollars.”
Min-woo Ku, South Korea’s country manager at Uppsala Security, said:
“The Terra-LUNA crisis has raised the interest of financial authorities and the industry in protecting investors and tightening regulations on Anti-Money Laundering measures. The Crypto Threat Detection System (CTDS) is a low initial investment and simple introduction method (SaaS), so it is of great help to virtual asset service providers (VASPs) who have difficulties in complying with the Special Act due to a shortage of compliance supervisors, or who want to capture both external credibility and customer protection.”