Key insights
-
South Korea is transitioning crypto market surveillance to AI-driven systems, where algorithms automatically detect suspicious trading activity and replace manual processes.
-
The new detection model uses a sliding window grid search technique and scans overlapping time segments to detect abnormal patterns such as unusual volume increases.
-
By 2026, the financial regulator plans to expand AI capabilities with tools to detect coordinated trading account networks and track manipulated funding sources.
-
Regulators are considering proactive intervention measures such as temporary transaction or payment suspensions to freeze suspicious activities early and prevent the withdrawal of illicit profits.
South Korea is advancing its oversight of the cryptocurrency market by switching to AI-driven supervision. Algorithms now perform initial detection of suspicious activity rather than relying solely on human investigators.
As cryptocurrency trading becomes faster, more decentralized and more difficult to monitor manually, regulators are using artificial intelligence to detect irregularities and anomalies more quickly.
At the heart of this development is the Financial Supervisory Service's (FSS) expanded Virtual Assets Intelligence System for Trading Analysis (VISTA). This upgrade reflects the recognition that traditional, manual, case-by-case reviews can no longer keep pace with today's dynamic digital asset markets.
This article explains how South Korea's financial regulators are using improved AI systems to automatically detect crypto market manipulation, improve monitoring, analyze trading patterns, and plan advanced tools. It is also exploring faster intervention and alignment of crypto supervision with broader financial markets.
Why South Korea is improving its crypto monitoring tools
Crypto markets produce massive amounts of data across exchanges, tokens and timelines. Manipulative tactics such as pump-and-dump schemes, wash trading, or spoofing often result in sudden breakouts that are difficult to detect. Manually identifying suspicious phases in crypto activity is becoming increasingly difficult at current market scale. As interconnected trading patterns become more complex, automated systems are designed to continuously scan and flag potential problems.
This automation is in line with Korea's broader efforts to strengthen oversight of digital markets, especially as cryptocurrencies become more integrated with retail investors and the overall financial system.
What VISTA does and how the recent upgrade improves it
VISTA serves as the FSS's primary platform for investigating unfair trading in digital assets. The previous version required analysts to specify time periods of suspected manipulation before conducting analysis, which limited the scope of detection.
The current upgrade adds an automated detection algorithm that can independently locate potential tampering periods without manual input. The system now searches the entire data set, allowing investigators to review suspicious sections that might otherwise go unnoticed.
According to the supervisory authority, the system was able to successfully identify all known manipulation periods in internal tests based on completed investigation cases. Additionally, additional intervals that were difficult to detect using traditional methods were identified.
Did you know? Some crypto exchanges process more individual trades in a single hour than traditional exchanges process in an entire trading day. Therefore, continuous automated monitoring is essential for regulators who want to monitor risks in real time.
How automatic detection works
Using a sliding window grid search approach, the algorithm divides trading data into overlapping time periods of different durations. These segments are then examined for abnormalities.
The model scans every possible subperiod and identifies patterns associated with manipulation without requiring investigators to determine where misconduct may have occurred. Examples of such patterns include sharp price spikes followed by quick reversals or unusual increases in volume.
Rather than replacing human oversight, the model prioritizes high-risk segments, allowing teams to focus on critical windows instead of having to manually review the entire data set.
Did you know? In crypto markets, price manipulation can sometimes occur in windows of less than five minutes, a time frame too short for most human-run monitoring systems to reliably capture.
Upcoming AI improvements by 2026
The FSS has secured funding for incremental AI improvements through 2026. Key planned features include:
-
Tools for identifying networks of coordinated trading accounts: These systems aim to detect clusters of synchronized accounts, a common feature of organized manipulation schemes.
-
Comprehensive analysis of trading-related texts across thousands of crypto assets: By studying abnormal advertising activity or narrative spikes along with market data, regulators hope to better understand how attention shocks and price movements interact.
-
Tracing the origin of the funds used in the manipulation: Linking suspicious deals to funding sources could strengthen law enforcement and reduce the ability of malicious actors to cover their tracks.
Did you know? Early market surveillance algorithms in traditional finance were originally designed to detect insider trading in stocks, not crypto. Many of today's tools are adaptations of models developed for stock markets decades ago.
Transition to proactive intervention in South Korea
South Korea's AI surveillance initiative aims for faster responses. The Financial Services Commission is considering a payment suspension mechanism that could temporarily block transactions linked to suspected manipulation.
This approach is intended to prevent profits from being withdrawn prematurely or laundered. Although this is not yet complete, it suggests that regulators will move from reactive to preventative enforcement.
Preventive measures raise important governance issues around thresholds, oversight and the risk of false positives – issues that regulators must address carefully.
This crypto-focused initiative is in line with efforts in traditional capital markets. The Korea Exchange is implementing an AI-based monitoring system to detect stock manipulation earlier. The idea is to create a unified approach across all asset classes, combining trading data, behavioral advice and automated risk assessment.
Strengths and limitations of AI surveillance
AI-based systems are able to detect repetitive, pattern-related misconduct such as wash trading or coordinated price spikes. They improve consistency by flagging suspicious behavior, even if it occurs in small or short-lived time windows.
For stock exchanges, AI-driven monitoring increases expectations for data quality and monitoring capabilities. It also improves cooperation with regulators. With AI models, monitoring becomes continuous instead of episodic.
Traders and issuers should expect greater scrutiny of subtle manipulative patterns that have previously escaped attention. Although detection begins algorithmically, in practice the penalties are still significant.
However, automated monitoring has certain limitations. Cross-venue manipulation, off-platform coordination, and subtle narrative techniques remain difficult to detect. AI models also require regular assessment to avoid bias, deviation, or flagging of legitimate activity.
AI tools support human investigators, not replace them.
Designing a new enforcement framework
South Korea's strategy includes AI models based on continuous monitoring, automated prioritization and faster action. As these systems evolve, it will be critical to balance efficiency with transparency, due process and accountability.
The implementation of these models will not only impact Korean crypto markets, but also the way other jurisdictions approach regulating digital assets in the era of algorithmic trading and mass participation.
Cointelegraph retains full editorial independence. The selection, commissioning and publication of features and magazine content is not influenced by advertisers, partners or business relationships.
