Most people who use crypto exchanges interact only with the surface layer of AML — submitting their ID, waiting for approval, or encountering withdrawal limits. But behind the scenes, AML (Anti-Money Laundering) compliance is a complex and evolving technical system. It combines identity verification, blockchain analytics, real-time transaction scoring, and often machine learning. In this article, I’ll take you behind the scenes to see how major exchanges implement AML from a developer’s perspective.
Popular exchanges like Binance, OKX, WhiteBIT and Kraken have faced significant regulatory scrutiny in recent years. Each of them has invested heavily in AML infrastructure, integrating advanced KYC providers and blockchain analytics tools to comply with regulations globally.
The AML process typically begins when a new user signs up and completes the KYC (Know Your Customer) process. Exchanges collect personal information, scan government-issued IDs, and run biometric checks such as selfies or liveness detection. Leading KYC providers like Jumio, Sumsub, and Onfido power this process, delivering verified identity profiles that are stored securely and used to assess the user’s risk level.
Once onboarding is complete, any wallet address linked to the user undergoes blockchain screening. This process evaluates the wallet’s history for any association with illicit activity. Services like Chainalysis, TRM Labs, and Elliptic provide APIs that return a "risk score" based on transaction history and blockchain forensics. Wallets previously connected to hacks, dark markets, or mixers are flagged immediately.
For example, on WhiteBIT exchange, as users start transacting, the real-time monitoring system comes into play. Every deposit, withdrawal, or trade is evaluated dynamically. Transactions that are unusually large, linked to high-risk jurisdictions, or structured to avoid detection thresholds (a technique called "smurfing") trigger alerts. Many exchanges employ custom rule engines or third-party AML solutions to analyze these patterns and assign dynamic risk scores.
For example, if a user suddenly starts moving tens of thousands of dollars through privacy tools or mixers, their risk score spikes, leading to automatic withdrawal holds or escalation for manual review. Alerts feed into internal compliance dashboards that provide teams with comprehensive views of transaction histories, KYC information, and blockchain reports.
If suspicious activity is confirmed, compliance teams file Suspicious Activity Reports (SARs) with financial authorities, including detailed metadata and reasoning. All processes are logged and auditable to meet regulatory standards.
From a technical perspective, building AML infrastructure requires multiple integrations: identity verification services, blockchain analysis APIs, case management dashboards, and custom monitoring logic. Microservice architectures are common, separating onboarding, transaction monitoring, and reporting to ensure scalability and security.
Despite the sophistication of AML systems, challenges remain. False positives can overwhelm compliance teams, privacy concerns persist, and decentralized wallets remain outside the direct control of exchanges. Regulatory requirements also vary widely across jurisdictions.
Looking forward, innovations like AI-powered monitoring, zero-knowledge KYC, and on-chain reputation scoring promise to make AML in crypto more effective and privacy-preserving.
In summary, AML in crypto exchanges is not just a regulatory checkbox — it’s a technical discipline essential to building trust in digital finance. Exchanges like WhiteBIT demonstrate that strong AML programs can coexist with user-centric design, paving the way for safer, compliant crypto ecosystems.
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