How South Korea Is Using AI to Detect Crypto Market Manipulation

key takeaways

• South Korea is transitioning crypto market monitoring to an AI-powered system, in which algorithms automatically detect suspicious trading activity, replacing manual processes.

• The new detection model employs a sliding-window grid search technique, which scans overlapping time segments to identify unusual patterns such as abnormal volume growth.

• By 2026, the financial supervisory service plans to enhance AI capabilities with tools to detect coordinated trading account networks and detect manipulated funding sources.

• Regulators are exploring proactive intervention measures, such as temporary transaction or payment suspensions, to quickly put a stop to suspicious activity and prevent illicit profit withdrawals.

South Korea is stepping up its cryptocurrency market surveillance by transitioning to AI-powered monitoring. Algorithms now do the initial detection of suspicious activities instead of relying solely on human investigators.

As crypto trading grows faster, more decentralized and becomes harder to monitor manually, regulators are taking advantage of artificial intelligence to more quickly identify irregularities and anomalies.

At the heart of this development is the Financial Supervisory Service (FSS)’s Advanced Virtual Assets Intelligence System for Trading Analysis (VISTA). This upgrade reflects the recognition that traditional, manual, case-by-case investigations can no longer keep pace with today’s dynamic digital asset markets.

This article explains how South Korea’s financial regulators are using advanced AI systems to automatically detect crypto market manipulation, improve surveillance, analyze trading patterns, and plan advanced tools. It also seeks sharper intervention and alignment of crypto oversight with broader financial markets.

Why is South Korea expanding its crypto surveillance tools?

Crypto markets produce massive amounts of data on exchanges, tokens, and timelines. Manipulating strategies such as pump-and-dump schemes, wash trading or spoofing often create sudden bursts that are difficult to detect. It has become increasingly challenging to manually identify suspicious periods in crypto activity at the current market scale. As interconnected trading patterns become more complex, automated systems are designed to continuously scan and flag potential issues.

This automation aligns with Korea’s broader effort to strengthen oversight of digital markets, especially as crypto becomes more deeply integrated with retail investors and the overall financial system.

What does VISTA do and how does the recent upgrade improve it?

VISTA serves as the FSS’s primary platform for investigating improper trading in digital assets. In its earlier version, analysts had to specify a time frame for suspected manipulation before running the analysis, which limited the range of detection.

Recent upgrades have added an automatic detection algorithm that can independently indicate potential manipulation periods without manual input. The system now searches the entire data set, helping investigators review suspicious gaps that might otherwise go unnoticed.

According to the regulator, the system successfully identified all known manipulation periods in internal tests using full test cases. It also identified additional gaps that were difficult to detect using traditional methods.

Do you know? Some crypto exchanges process more individual trades in an hour than traditional stock exchanges do in an entire trading day, making constant automated monitoring necessary for regulators monitoring real-time risks.

How does automatic detection operate?

Applying a sliding-window grid search approach, the algorithm divides the trading data into overlapping time segments of different durations. It then assesses these segments for anomalies.

The model scans every possible sub-period, identifying patterns associated with manipulation without requiring investigators to determine where the misconduct may have occurred. Examples of such patterns include a sharp price increase followed by a rapid reversal or an unusual increase in volume.

Rather than replacing human inspection, the model prioritizes high-risk areas, enabling teams to focus on critical windows rather than manually reviewing the entire data set.

Do you know? In crypto markets, price manipulation can sometimes occur in windows lasting less than five minutes, which is too short a time frame for most human-led monitoring systems to reliably capture.

Upcoming AI enhancements by 2026

FSS has secured funding for phased AI improvements through 2026. Main planned features include:

• Tools designed to identify networks of coordinated trading accounts: The purpose of these systems is to detect groups of accounts acting in sync, a common feature of organized manipulation schemes.

• Large-scale analysis of text related to trading across thousands of crypto assets: By examining market data as well as unusual promotional activity or narrative spikes, regulators hope to better understand how attention shocks and price movements interact.

• Tracing the origin of money used in manipulation: Linking suspicious businesses to funding sources can strengthen enforcement cases and reduce the ability of bad actors to obscure their tracks.

Do you know? Early market monitoring algorithms in traditional finance were originally designed to detect insider trading in equities, not crypto. Many of today’s instruments are adaptations of models created decades ago for stock exchanges.

Shift toward active intervention in South Korea

South Korea’s AI surveillance campaign demands quick response. The Financial Services Commission is considering a payment suspension mechanism that could temporarily halt transactions involving suspected manipulation.

The purpose of this approach is to prevent early withdrawal or plunder of profits. Although it has not yet been finalized, it suggests a shift from reactive to preventive enforcement by regulators.

Preemptive actions raise important governance questions around limits, oversight, and the risk of false positives, issues that regulators will need to pay careful attention to.

This crypto-focused initiative parallels efforts in traditional capital markets. The Korea Exchange is implementing an AI-based monitoring system to identify stock manipulation in advance. The idea is to create an integrated approach across asset classes by combining trading data, behavioral signals and automated risk assessment.

Strengths and limitations of AI surveillance

AI-based systems specialize in detecting repetitive, pattern-driven misconduct such as wash trading or coordinated price spikes. They increase stability by flagging suspicious behavior even when it occurs in small or short-term windows.

For exchanges, AI-powered monitoring raises expectations regarding data quality and monitoring capabilities. It also enhances cooperation with regulators. With AI models, monitoring becomes continuous rather than episodic.

Traders and issuers should expect greater scrutiny of subtle manipulation patterns that previously escaped attention. While identification begins algorithmically, real-world penalties remain significant.

But automated monitoring has some limitations. Cross-venue manipulation, off-platform coordination and subtle narrative engineering are difficult to detect. AI models also require regular evaluation to avoid bias, drift, or flagging legitimate activity.

AI tools support, not replace, human investigators.

Shaping a new enforcement framework

South Korea’s strategy includes AI models built around continuous monitoring, automated prioritization and swift action. As these systems evolve, it will be important to balance efficiency with transparency, due process, and accountability.

The implementation of these models will not only shape Korea’s crypto markets, but also the way other jurisdictions regulate digital assets in the era of algorithmic trading and collective participation.