Writing
Notes on AI in Finance.
Where the agentic moment meets capital markets — what is happening, why it matters, and what I am building toward.
AEOLUS: Everyone Predicts Failures — The Money Is in Deciding When to Act
Failure prediction is commoditised. The hard, valuable problem in industrial AI is the closed loop after the prediction: deciding when to act so you lose the least revenue, under real constraints, with a governance trail an operator can deploy. Here is how I built that for a wind fleet.
Read post →
QUORUM: An AI Investment Committee That Argues Before It Decides — and Never Makes Up a Number
Most "AI investing" demos fail the same way: a confident model recalls a wrong figure. QUORUM splits the system in two — Python computes every number deterministically, the LLM only argues and narrates. Six agents debate from real market data and converge on a documented allocation.
Read post →
RegRadar: An Agentic Engine That Reads EU Regulation Without Hallucinating a Single Citation
Every act in the EU regulatory firehose carries concrete obligations a bank must implement. RegRadar extracts them, maps them to systems, ranks them by deadline, and drafts the gap-assessment memo — with every claim verified, programmatically, against the live EUR-Lex source. Here is the architecture that makes it trustworthy.
Read post →
CreditForge: What It Actually Takes to Build a Credit-Risk Model a Bank Would Sign Off On
EL = PD × LGD × EAD is one line. The 80% that makes a credit model bank-credible is everything around it — leakage-safe point-in-time targets, out-of-time validation, calibration, reason codes, fairness, and drift monitoring. Here is the full stack.
Read post →
Building Recoupe — Why Subrogation Is the Best Vertical to Pressure-Test Agentic AI
A multi-agent system that reads insurance claims, assigns fault by jurisdiction, computes what is recoverable, and pursues it — with grounded citations and an append-only audit trail. Here is what I learned shipping it.
Read post →
JPMorgan's $2B AI Bet: What 2,000 Use Cases Tell Us About Banking's Next Decade
Jamie Dimon spent $2B on AI in 2024 and built 2,000+ use cases. Here's what that signals for every engineer wanting to work in banking.
Read post →
The Bloomberg Terminal Is About to Be Eaten by an Agent
The $32K/year Terminal is the most valuable software seat in finance. AI agents can replicate 70% of its workflows for $99/month. Here is how the disruption plays out.
Read post →
Why Goldman's IndexGPT Is the First Real Glimpse of Agentic Wealth Management
Goldman patented IndexGPT in 2024 — an AI system that constructs custom investment indices on demand. It is a tiny product. It is also the future of wealth management.
Read post →
The Quant ML Revolution: How Two Sigma and Renaissance Are Rebuilding for the LLM Era
Traditional factor investing is dying. The funds that survive the next decade will be the ones that figured out how to ingest unstructured data at scale. Here is the shift in progress.
Read post →
MCP and the Quiet Death of Fintech APIs as We Know Them
Anthropic's Model Context Protocol launched in late 2024. Most people read it as a developer convenience. Inside fintech, it is the start of a much bigger rewrite.
Read post →