Posts about banking
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Governance Is a Design Problem
Compliance-first governance produces paperwork. Design-first governance produces systems you can actually explain to a regulator.
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The Risk Tiering Gap in Banking AI
Banks have AI ethics principles. They don't have risk tiering. That's the gap that matters.
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Inference Cost Collapse Is a Governance Liability
When AI agent calls approach zero cost, the natural rate-limiter on decision volume disappears — and oversight frameworks designed for prediction models break.
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The AI/DLT Conflation Trap in HKMA's March 2026 Strategic Review Mandate
HKMA's new strategic review circular bundles AI inference risk and smart contract risk into one workstream — a governance design flaw that will cause banks to under-govern both.
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Model Risk Management Was Not Built for This
SR 11-7 assumes models are tools that produce outputs for human review. AI agents are actors that take actions autonomously. Every assumption breaks.
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Your AI Risk Tier Is Probably Wrong
List-based and process-based approaches to AI risk classification both fail in predictable ways. The failure mode depends on which you chose.
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Human Oversight Doesn't Scale
Every AI governance framework demands human-in-the-loop. Nobody does the maths on what that means at enterprise scale.
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The Maker-Checker Trap
Most AI maker-checker implementations capture the correction but not the reason. That's a feedback loop with no signal.
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Your Ground Truth Is Someone Else's Process Outcome
When your model's labels come from human decisions rather than reality, you're not measuring what you think you're measuring.
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The Global Minimum of Governance
Governance isn't about catching every failure — it's about proving your process was reasonable when one happens. The real skill is knowing what to deliberately not monitor.
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China's AI Stack Is Now Hardware-Deep
DeepSeek V4 launching on Huawei Ascend NPUs signals that China's AI ecosystem is decoupling at the silicon layer — deeper and more durable than model-level divergence.
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AI Vendors Are Not Neutral Infrastructure
The DoD-Anthropic dispute reveals a new category of operational risk: foundation model vendors can unilaterally revoke access based on their own values, not just SLA violations.
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Three APAC Regulators Are Converging on AI Governance — Banks Should Build One Framework
MAS, PBOC, and HKMA are independently arriving at similar AI governance requirements. Banks regulated by all three have a narrow window to build one superset framework instead of three silos.
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The Agent Governance Gap Is Already Here
Agentic AI isn't a future governance problem — it arrived ungoverned, and this week saw the first enforcement action.
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What AlphaSense Charges Ten Thousand Dollars For
I built an AI landscape intelligence pipeline for zero marginal cost. Here's what it does and what it can't.
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What it actually takes to run an AI agent in a bank
The resistance to AI agents in banking isn't mostly cultural. It's infrastructure — and the gap is more interesting than the politics.
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Backtest vs Operational Validation: The Control You Think You Have
A model control that's never fired in production isn't a control — it's a hypothesis. The gap between backtest and operational validation is invisible until someone asks.
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The Upstream Constraint Pattern
In digital transformation, the bottleneck is almost always upstream of where the pain is felt. Mox is the cleanest case study.
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Banks Have an AX Problem They Don't Know About Yet
Banks are building AI agents to call their APIs. Those APIs weren't designed for agent callers. The mismatch is subtle, consequential, and almost nobody is talking about it.
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Three Things AML AI Models Still Get Wrong in 2026
The models aren't the problem. The operating models are. Three structural failures in AML AI from years building these systems inside a bank.
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The Real Reason Mox Won (and What It Means for AI Transformation)
Mox didn't win because they hired better designers. They won because they had no legacy to fight. The pattern applies directly to AI transformation.
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HK/APAC as an AI Hub for Financial Services: The Story Being Missed
Hong Kong has quietly run one of the most sophisticated GenAI experiments in global banking. Almost no one outside the region is paying attention.
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AI Agent Frameworks for Enterprise FS: What Actually Works vs. Hype
Most enterprise AI agent pilots in financial services fail at the same point: the second tool call. The problem isn't the framework.
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RAG for Compliance: The Hard Problem Is Chunking, Not Retrieval
Banks are deploying RAG for compliance and discovering the hard problem isn't retrieval. It's the pipeline before it.
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Banking DS to AI Consulting: What the Transition Actually Teaches You
The operational instincts built in production banking don't belong in the past. They're exactly what makes a practitioner-turned-consultant useful.
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Most Banks Don't Need an AI Strategy
The real project isn't artificial intelligence. It's the data infrastructure that AI exposes as broken.