Regulatory Ramblings: Episode 78 – How Well Does the Money Laundering Control System Work? Spotlight on: Rethinking AI Regulation: Why Current Approaches Fall Short | Thomas Fox – Compliance Evangelist

The podcast begins with a brief conversation between Oonagh and Regulatory Ramblings host Ajay Shamdasani about her September 8, 2025, LinkedIn article, “Rethinking AI Regulation: Why Current Approaches Are Falling Short.”

Her key message: “AI isn’t just a technology—it’s an ecosystem. Regulating it requires cooperation, adaptability, and vision. Anything less will fail.”

She stresses that AI evolves faster than regulators can keep up. Governments worldwide struggle to design frameworks that govern pervasive, adaptive, and borderless AI without stifling innovation or missing risks.

She cites Hong Kong’s dilemma: enforcing AI-content labelling rules in a small market with weak enforcement. Without robust mechanisms, watermarking and labelling may be ignored. The problem is global.

Hong Kong’s challenges:

1. Fragmented laws – reliance on privacy, IP, and finance statutes leaves gaps.

2. Weak enforcement – watermarking is easy to evade, compliance varies.

3. Scale/coordination issues – small markets can’t diverge too far from global standards.

4. Ethical risks – misinformation, bias, and liability remain unaddressed.

Oonagh points to models abroad:

• EU AI Act – ambitious, risk-based: bans unacceptable AI, regulates high-risk (biometrics, healthcare, finance) with strict compliance, and applies light rules to minimal risk. Strong but resource-heavy.

• Singapore Model – voluntary best practices, sandboxes, and collaboration. Innovation-friendly but lacks legal teeth.

For Hong Kong, she recommends: unified AI regulation, risk-based oversight, robust enforcement tools, a central regulator, public education, and global alignment. “Regulation must evolve as quickly as AI itself—not to slow it down, but to ensure innovation happens safely and transparently.”

The discussion then shifts to Mirko and Peter’s article, “How Well Does the Money Laundering Control System Work?” Their key question: has AML made laundering harder? Evidence suggests not.

Findings:

• No proof laundering is harder or less prevalent.

• International evaluations often symbolic.

• AML costs high, with unintended effects like de-risking.

• Private entities bear operational burdens.

Seven observations: banks face fines but few executive convictions; laundering remains simple; rich jurisdictions benefit; AML yields some intelligence but risks data misuse; and compliance costs are rarely debated.

Their abstract notes globalization has expanded laundering methods, while AML grows expensive and intrusive without proving effective. Major banks fail obligations, oversight is weak, and reforms are scarce.

They observe that basic laundering dominates, crypto use is limited, and most launderers handle their own funds. SAR systems are unsustainable—e.g., 4M reports filed annually in the U.S., overwhelming regulators. Defensive filing by banks further clogs the system.

Policy suggestions: set realistic goals, adopt new effectiveness metrics, balance AML controls with financial inclusion. Mirko stresses differing typologies across criminals; Peter notes U.S. plans to scale back enforcement may lead to selective application. See less –

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