When the KYT tool becomes a zombie system: what you think is Compliance is actually a trap.

Insiders know that there are two types of compliance: one is for regulators, and the other is genuinely effective. The former is called "Compliance Theater," while the latter is real Risk Management. Sadly, the vast majority of institutions, especially those fintech companies racing on the wind, are unconsciously performing the former.

What is the essence of the "Compliance Theater"? It is a stage meticulously built to cope with inspections, obtain licenses, and appease investors. On this stage, the correctness of processes outweighs everything, and the quality of reports is far more important than the rate of risk identification. The actors (compliance officers) recite lines that have long been written (compliance manuals) and operate luxurious props (expensive systems), showcasing a scene of prosperity to the audience below (regulatory agencies). As long as the performance is good, the license is obtained, and financing is in place, everyone is happy.

In this grand play, the most glamorous, most expensive, and most deceptive prop is those "zombie systems" that appear to be running 24/7, but in reality, have long since lost their essence and are merely empty shells. Especially the KYT (Know Your Transaction) system, which should be the sharpest scout on the front line of Anti-Money Laundering (AML), often falls first in the line of duty, turning into a zombie that only consumes budget and provides a false sense of security. It quietly lies in the server, with green lights flashing, reports being generated, everything seems normal—until a real bomb explodes right under its nose.

This is the biggest Compliance trap. You think you have purchased the top-notch equipment and built an impregnable defense, but in reality, you are just feeding a zombie with money and resources. It will not protect you; it will only make you die without a clear cause when disaster strikes.

So, the question arises: why do the KYT tools that we invest heavily in and expend human resources to procure sometimes become mere husks? Behind this, is it a fatal mistake in technology selection, a complete breakdown in process management, or an inevitable result of both?

Today, we will focus on the "Compliance theater" of the fintech and payment industry, the hottest stage, especially in the Southeast Asian market where the regulatory environment is complex and ever-changing, and business growth is like a runaway horse. Here, real dramas are unfolding, and what we need to do is lift the curtain and see the truth behind the scenes.

Act One: Zombie System Analysis - How Your KYT Tool 'Died'?

The birth of a "zombie system" is not an overnight phenomenon. It does not suddenly die due to a shocking vulnerability or a catastrophic outage, but instead, like a frog in boiling water, it gradually loses its ability to perceive, analyze, and respond in the day-to-day "normal operation," ultimately becoming an empty shell that only maintains vital signs. This process can be dissected from both technical and procedural dimensions to see how a originally fully functional KYT system steps toward "death."

Technical Level "Brain Death": Single Point of Failure and Data Islands

Technology is the brain of the KYT system. When the neurons of the brain are disconnected, information input is hindered, and the analysis model becomes rigid, the system enters a state of "brain death." It is still processing data, but it has lost the ability to understand and judge.

Cognitive Blind Spot of a Single Tool: Seeing the World with One Eye

Over-reliance on a single KYT tool is the primary and most common reason for system failure. This is almost common knowledge within the industry, but in the script of the "Compliance Theater", this point is often selectively ignored in pursuit of so-called "authority" and "simplified management".

Why is it said that a single tool is deadly? Because no single tool can cover all risks. It's like having a sentry monitor enemies coming from all directions at once; he will always have blind spots. Recently, a research report released by Singapore licensed digital asset service provider MetaComp revealed this harsh reality through testing data. The study analyzed over 7,000 real transactions and found that relying solely on one or two KYT tools for screening could lead to as much as 25% of high-risk transactions being erroneously cleared. This means that a quarter of the risk is being directly ignored. This is no longer a blind spot, but a black hole.

Figure 1: Comparison of "False Clean Rate" under different combinations of KYT tools

Data Source: MetaComp Research - Comparative Analysis of On-Chain KYT for AML&CFT, July 2025. The chart shows that when the risk threshold is set to "Medium-High Risk," the false negative rate for a single tool can reach up to 24.55%, while the combination of two tools can go up to 22.60%, and the combination of three tools drops sharply to 0.10%.

This enormous risk exposure stems from the inherent flaws of the KYT tool ecosystem. Each tool is built on its own proprietary data sets and intelligence gathering strategies, resulting in natural differences and blind spots in the following aspects:

• Data Source Variability

Some tools may be closely related to U.S. law enforcement and have stronger coverage of risk addresses involving the North American region; others may focus on the Asian market and have more timely intelligence on localized fraud networks. No single tool can simultaneously be the intelligence king for all regions globally.

• Different Focus on Risk Types

Some tools are good at tracking addresses related to OFAC sanctions lists, while others excel at identifying mixing services or darknet markets. If the tool you choose is not proficient in identifying the main types of risks your business faces, then it is basically just a decoration.

• Update Delays and Intelligence Lags

The lifecycle of a black market address may be very short. A risk address marked by one tool today may take several days or even weeks for another tool to synchronize. This time lag in intelligence is sufficient for money launderers to complete multiple rounds of operations.

Therefore, when an institution places all its hopes on a single KYT tool, it is essentially gambling—betting that all the risks it encounters are precisely within the "cognitive scope" of this tool.

The "Malnutrition" Caused by Data Silos: Without a Source of Water, How Can It Flow?

If a single tool is narrow-minded, then data silos are a complete "malnutrition." The KYT system has never been an isolated system; its effectiveness is based on a comprehensive understanding of counterparties and trading behaviors. It needs to continuously obtain "data nutrients" from multiple sources such as KYC (Know Your Customer) systems, customer risk rating systems, and business systems. When these data channels are blocked or the quality of the data itself is low, KYT becomes a water source without origin, losing its judgment benchmark.

In many rapidly growing payment companies, this scenario is not uncommon:

The KYC team is responsible for customer onboarding, and their data is stored in System A; the risk control team is responsible for transaction monitoring, and their data is in System B; the compliance team is responsible for AML reporting, and they use System C. The three systems belong to different departments and are provided by different vendors, with almost no real-time data interaction between them. As a result, when the KYT system analyzes a real-time transaction, the customer risk rating it relies on may still be the static information entered by the KYC team three months ago. This customer may have exhibited various high-risk behaviors during these three months, but this information is trapped in the risk control team's System B, and the KYT system is unaware of it.

The direct consequence of this "malnutrition" is that the KYT system cannot establish an accurate Behavioral Baseline for customer behavior. One of the core capabilities of an effective KYT system is to identify "abnormalities"—that is, transactions that deviate from the customer's normal behavior pattern. However, if the system does not even know what a customer's "normal" is, how can it identify "abnormalities"? Ultimately, it can only regress to relying on the most primitive and crude static rules, generating a large number of worthless "garbage alerts," moving one step closer to being a "zombie."

The "Carving a Boat to Seek a Sword" of Static Rules: Using Old Maps to Find New Lands

Criminal methods are evolving rapidly, from the traditional "smurfing" to using DeFi protocols for cross-chain money laundering, and now to conducting fake transactions through NFT markets. The complexity and concealment of these methods are growing exponentially. However, many "zombie KYT systems" still rely on rule sets that are several years outdated, much like using an old nautical chart to search for new lands, destined to achieve nothing.

Static rules, such as "a single transaction exceeding $10,000 triggers an alert," are hardly worth mentioning for today's black market practitioners. They can easily use automated scripts to split a large sum of money into hundreds or thousands of small transactions, perfectly bypassing such simple thresholds. The real threat lies in complex behavioral patterns:

• A newly registered account engages in a large number of small, high-frequency trades with numerous unrelated counterparties in a short period of time.
• After the rapid influx of funds, they are immediately dispersed through multiple addresses without any stay, forming a typical "Peel Chain."
• The trading path involves high-risk mixing services, unregistered exchanges, or addresses in sanctioned areas.

These complex patterns cannot be effectively described and captured by static rules. What they need is a machine learning model that can understand transaction networks, analyze funding links, and learn risk characteristics from massive amounts of data. A healthy KYT system should have rules and models that are dynamic and self-evolving. In contrast, a "zombie system" loses this capability; once its rule base is set, it rarely gets updated, ultimately falling far behind in the arms race against illicit activities, leading to a complete "brain death."

Process-level "heartbeat stop": from "one-time solution" to "alarm fatigue"

If technical defects lead to "brain death" of the system, then the collapse of process management directly results in "heartbeat cessation." A system, no matter how technologically advanced, is merely an expensive pile of code without the correct processes to drive and respond to it. In the "compliance theater," failures in processes are often more concealed and more lethal than failures in technology.

The Illusion of "Victory Upon Launch": Treating Weddings as the End Point of Love

Many companies, especially startups, approach compliance building with a "project-based" mindset. They believe that the procurement and launch of the KYT system is a project with a clear start and end. Once the system is successfully launched and passes regulatory acceptance, the project is declared a victorious end. This is the most typical illusion of the "compliance theater"—mistaking the wedding for the end of love, thinking that from then on, they can rest easy.

However, the lifecycle of a KYT system starts the day it goes live. It is not a tool that can be a "one-and-done" solution, but rather a "living entity" that requires continuous care and optimization. This includes:

• Continuous Parameter Calibration

The market is changing, customer behaviors are changing, and money laundering techniques are changing. The monitoring thresholds and risk parameters of the KYT system must be adjusted accordingly. A $10,000 alarm threshold that was reasonable a year ago may have become meaningless after a tenfold increase in transaction volume.

• Regular Rule Optimization

As new risks emerge, it is necessary to continuously develop and deploy new monitoring rules. At the same time, it is also essential to regularly assess the effectiveness of old rules and eliminate those "garbage rules" that only produce false positives.

• Necessary Model Retraining

For systems using machine learning models, it is essential to regularly retrain the models with the latest data to ensure their ability to identify new risk patterns and prevent model decay.

When an organization falls into the illusion of "going live equals victory", these crucial follow-up maintenance tasks are often neglected. No one is responsible, there is no budget support, and the KYT system is like a sports car abandoned in a garage; no matter how good the engine is, it will slowly rust and ultimately turn into a pile of scrap metal.

"Alarm Fatigue" Overwhelms Compliance Officers: The Last Straw

An improperly configured and poorly maintained "zombie system" can lead to the most direct and disastrous consequence: the generation of massive amounts of false positive alerts. According to industry observations, in many financial institutions, over 95% to even 99% of the alerts generated by the KYT system are ultimately verified as false alarms. This is not just an issue of inefficiency; it can trigger a deeper crisis—"alert fatigue."

We can imagine the daily routine of a Compliance Officer:

Every morning, he opens the case management system and sees hundreds of pending alerts. He clicks on the first one, and after half an hour of investigation, finds it to be normal business behavior from a client, so he closes it. The second one is the same. The third one is still the same... Day after day, he is drowned in an endless ocean of false positives. The initial vigilance and seriousness are gradually replaced by numbness and negligence. He starts looking for 'shortcuts' to quickly close alerts, and his trust in the system drops to freezing point. Eventually, when a real high-risk alert appears among them, he might just glance at it and habitually mark it as a 'false positive' before closing it.

"Alert fatigue" is the last straw that breaks the compliance defense line. It psychologically destroys the combat effectiveness of the compliance team, turning them from "hunters" of risks into "cleaners" of alerts. The entire compliance department's energy is consumed in ineffective battles against a "zombie system," while the real criminals swagger through the defenses, hidden by the clamor of alerts.

At this point, a KYT system has completely "stopped beating" in terms of process. It is still generating alerts, but these "heartbeats" have lost their meaning, with no one responding and no one believing. It has completely turned into a zombie.

A friend of mine had an enterprise that staged a classic "Compliance Theater" to obtain a license and please investors: they announced with great fanfare that they had purchased the industry's top KYT tools, using this as a promotional capital for their commitment to the highest compliance standards. However, to save money, they only bought services from one supplier. The management's logic was: "We used the best, so don't blame me if something goes wrong." They selectively forgot that any single tool has its blind spots.

In addition, the compliance team is understaffed and lacks technical knowledge, so they can only use the most basic static rule templates provided by the vendors. Monitoring large transactions and filtering a few publicly available blacklist addresses is considered completing the task.

The most critical thing is that once the business volume increases, the system alarms come in like snowflakes. Junior analysts quickly discovered that over 95% of them were false alarms. In order to meet KPIs, their work shifted from "investigating risks" to "closing alarms." Over time, no one took the alarms seriously anymore.

Professional money laundering gangs quickly caught the scent of rotten meat. They used the simplest yet most effective methods to turn this "zombie system" into their own ATM: by employing the "Smurfing" tactic of "breaking it down into smaller parts," they split the funds from illegal gambling into thousands of small transactions below the monitoring threshold, disguising them as e-commerce returns. In the end, it was not their team members who triggered the alarm, but their partner bank. When the regulatory investigation letter arrived at the CEO's desk, they were still in a daze, and it was reported later that their license was revoked.

Figure 2: Comparison of Risk Levels Across Different Blockchain Networks

Data Source: MetaComp Research - Comparative Analysis of On-Chain KYT for AML&CFT, July 2025. The chart shows that in the sampled data, the proportion of transactions on the Tron chain rated as "severe," "high," or "medium-high" risk is significantly higher than that on the Ethereum chain.

The stories around us are a mirror, reflecting the shadows of countless fintech companies performing in the "Compliance Theater." They may not have fallen yet, simply because they are lucky and haven't been targeted by professional criminal gangs. But ultimately, it is just a matter of time.

Act Two: From "Zombie" to "Sentinel" - How to Awaken Your Compliance System?

After revealing the pathology of the "zombie system" and witnessing the tragedy of the "compliance theater," we cannot simply remain in criticism and lamentation. As practitioners on the front lines, what we are more concerned with is: how to break the deadlock? How to awaken a dying "zombie" and turn it into a true capable and defensive "frontline sentry"?

The answer does not lie in purchasing a more expensive and "authoritative" single tool, but in a complete transformation from concept to tactics. This methodology has long been an unspoken secret among the true pragmatists in the circle. MetaComp's research systematically quantifies and publicizes it for the first time, providing us with a clear and actionable battle manual.

Core Solution: Say Goodbye to Solo Acts and Embrace a "Multi-Layer Defense System"

First of all, we must completely abandon the mindset of "just buying a tool and it's done" from the root of our thinking. True compliance is not a one-man show, but a positional battle that requires constructing a deep defense system. You cannot expect a single sentry to stop thousands of troops; what you need is a three-dimensional defense network composed of sentries, patrols, radar stations, and intelligence centers.

Tactical Core: Multi-Tool Combo

The tactical core of this defense system is the "multi-tool combination punch." The blind spots of a single tool are inevitable, but the blind spots of multiple tools are complementary. Through cross-validation, we can minimize the hiding space of risks to the greatest extent.

So, the question arises, how many tools are really needed? Two? Four? Or is more better?

MetaComp's research provides a crucial answer: The combination of three tools is the golden rule for achieving the best balance between effectiveness, cost, and efficiency.

We can understand this "three-piece set" in a simple way:

• The first tool is your "frontline sentinel"

It may have the widest coverage and can detect most conventional risks.

• The second tool is your "Special Patrol Team"

It may have unique reconnaissance capabilities in a specific area (such as DeFi risk, specific regional intelligence) to detect covert threats that the "sentinels" cannot see.

• The third tool is your "back-end intelligence analyst"

It may possess the most powerful data correlation analysis capability, able to connect the fragmented clues discovered by the first two and outline a complete risk profile.

When these three work together, their power is far from a simple sum. Data shows that upgrading from dual tools to triple tools results in a qualitative leap in compliance effectiveness. The MetaComp report indicates that a well-designed three-tool screening model can reduce the false clean rate of high-risk transactions to below 0.10%. This means that 99.9% of known high-risk transactions will be captured. This is what we refer to as 'effective compliance.'

In contrast, upgrading from three tools to four tools can further reduce the missed report rate, but the marginal benefits are already very small, while the costs and time delays brought about are significant. Research shows that the screening time for the four tools can be as long as 11 seconds, while the three tools can be controlled to around 2 seconds. In payment scenarios that require real-time decision-making, this 9-second gap could be a matter of life and death for user experience.

Figure 3: The Trade-off Between Effectiveness and Efficiency of KYT Tool Combination

Data Source: MetaComp Research - Comparative Analysis of On-Chain KYT for AML&CFT, July 2025. The chart visually demonstrates the impact of increasing the number of tools on reducing the "missed report rate" (effectiveness) and increasing "processing time" (efficiency), clearly indicating that the combination of three tools is the most cost-effective choice.

Methodology Implementation: Establish Your Own "Rule Engine"

Choosing the right "trio" combination only completes the equipment upgrade. The more critical aspect is how to command this multi-unit force to cooperate in combat. You cannot let the three tools operate independently; you need to establish a unified command center - that is, your own "rule engine" that is independent of any single tool.

Step 1: Standardization of Risk Classification - Speaking the Same Language

You cannot be led by the nose by tools. Different tools may describe the same risk using different labels such as "Coin Mixer," "Protocol Privacy," "Shield," etc. If your compliance officer needs to remember the "dialects" of each tool, it would be a disaster. The correct approach is to establish a set of internally unified and clear risk classification standards, and then map all the risk labels of the tools you integrate into your own standard system.

For example, you can establish the following standardized categories:

Table 1: Example of Risk Category Mapping. In this way, no matter which new tool is integrated, you can quickly "translate" it into a unified internal language, enabling cross-platform horizontal comparisons and unified decision-making.

Step 2: Unify Risk Parameters and Thresholds - Set Clear Boundaries

With a unified language, the next step is to establish unified "rules of engagement." You need to set clear and quantifiable risk thresholds based on your own risk appetite and regulatory requirements. This is a key step in transforming subjective "risk appetite" into objective, machine-executable instructions.

This set of rules should not be just a simple amount threshold, but rather a more complex, multidimensional combination of parameters, such as:

• Severity Level Definition

Identify which risk categories fall under "Severe" (such as sanctions, terrorist financing), which fall under "High Risk" (such as theft, dark web), and which are considered "Acceptable" (such as exchanges, DeFi).

• Transaction-Level Taint %

Define the proportion of funds in a transaction that indirectly comes from high-risk sources that triggers an alert. This threshold needs to be scientifically set through extensive data analysis, rather than being decided arbitrarily.

• Cumulative Taint % at Wallet Level

Define a wallet that needs to be marked as a high-risk wallet when the proportion of funds transacted with high-risk addresses reaches a certain level throughout its entire transaction history. This can effectively identify those "old fox" addresses that have been engaged in gray market trading for a long time.

These thresholds are the "red lines" you set for the Compliance system. Once reached, the system must respond according to the predefined script. This makes the entire compliance decision-making process transparent, consistent, and defensible.

Step 3: Design a Multi-layer Screening Workflow - A Three-dimensional Strike from Point to Surface

Finally, you need to integrate the standardized classifications and unified parameters into an automated multi-layer screening workflow. This process should act like a sophisticated funnel, filtering layer by layer, gradually focusing to achieve precise strikes against risks while avoiding excessive interference with a large number of low-risk transactions.

An effective workflow should at least include the following steps:

Figure 4: An example of an effective multi-layer screening workflow (adapted from MetaComp KYT methodology) 1. Initial Screening

All transaction hashes and counterparty addresses are first scanned in parallel using the "three-piece set" tool. If any tool raises an alert, the transaction moves to the next stage. 2. Direct Exposure Assessment

The system determines whether the alert is a "direct exposure", meaning that the counterparty address itself is a marked "serious" or "high-risk" address. If so, this falls under the highest priority alerts and should immediately trigger a freeze or manual review process. 3. Transaction-Level Exposure Analysis（交易级暴露分析）

If there is no direct exposure, the system will start "funding tracing", analyzing how much of the transaction's funds can be indirectly traced back to the risk source (Taint %). If this percentage exceeds the preset "transaction level threshold", it will proceed to the next step. 4. Wallet-Level Exposure Analysis

For cases where the trading-level risk exceeds the limit, the system will conduct a "comprehensive examination" of the counterparty's wallet, analyzing the overall risk status of its historical transactions (Cumulative Taint %). If the wallet's "health status" is also below the preset "wallet-level threshold," the transaction will ultimately be confirmed as high risk. 5. Decision Outcome

Based on the final risk rating (Severe, High, Medium High, Medium Low, Low), the system automatically or prompts manual execution of corresponding actions: release, intercept, return, or report.

The brilliance of this process lies in its transformation of risk identification from a simple "yes/no" judgment into a three-dimensional assessment process that moves from points (single transactions) to lines (funding links) and then to surfaces (wallet profiles). It effectively distinguishes between severe risks that are "directly hit" and potential risks that are "indirectly contaminated," thus achieving optimal resource allocation—responding quickly to the highest risk transactions, conducting in-depth analysis on medium risk transactions, and rapidly approving the vast majority of low-risk transactions, perfectly resolving the conflict between "alert fatigue" and "user experience."

Epilogue: Dismantle the Stage and Return to the Battlefield

We spent a long time dissecting the pathology of the "zombie system", reviewing the tragedy of the "compliance theater", and discussing the "operating manual" for waking up the system. Now, it's time to return to the starting point.

The biggest harm of the "Compliance Theater" is not how much budget and manpower it consumes, but the kind of fatal, false "sense of security" it brings. It leads decision-makers to mistakenly believe that risks have been controlled, causing executors to become numb in their day-to-day ineffective labor. A silent "zombie system" is far more dangerous than a system that does not exist at all, because it lulls you into a false sense of security, leading you towards danger.

In today's era where black market technology and financial innovation are iterating in sync, relying on a single tool for KYT monitoring is akin to running naked on a battlefield filled with gunfire. Criminals now possess an unprecedented arsenal—automated scripts, cross-chain bridges, privacy coins, and DeFi mixing protocols. If your defense system is still at the level of a few years ago, then being breached is just a matter of time.

True compliance is never a performance aimed at pleasing the audience or passing inspections. It is a hard battle, a protracted war that requires excellent equipment (a combination of multi-layered tools), tight tactics (a unified risk methodology), and outstanding soldiers (a professional compliance team). It does not need a glamorous stage and hypocritical applause; what it needs is respect for risk, honesty with data, and continuous refinement of processes.

Therefore, I call on all practitioners in this industry, especially those who hold resources and decision-making power: please give up the illusion of a "silver bullet" solution. There is no magical tool in the world that can solve all problems once and for all. The construction of a compliance system has no end; it is a dynamic lifecycle process that needs to be continuously iterated and improved based on data feedback. The defense system you establish today may have new vulnerabilities tomorrow, and the only way to respond is to remain vigilant, continue learning, and keep evolving.

It is time to dismantle the false stage of the "Compliance Theater." Let's return to the challenging yet opportunity-filled battlefield of real risks with the truly effective "Sentinel System." Because only there can we truly safeguard the value we want to create.