Which is more reliable for moving cargo?
A robot that carries every shipment itself making decisions, choosing routes, and adapting every time?
Or a robot that builds the railway, signalling system, checkpoints, and operating rules so thousands of shipments can move automatically through a controlled path?
For critical operations, the second approach is more reliable.
I see financial AI the same way.
Using an LLM directly to analyse every transaction introduces variability. The model can be influenced by context, prompting, model updates, training data, and accumulated human bias.
A better architecture is to use AI to build the railway.
Let AI design the detached system: fixed parsers, deterministic logic, accounting guidelines, validation rules, reconciliation checks, and predefined financial indicators.
Then let financial data travel through that controlled system repeatedly.
The AI does not need to “think” about every transaction.
It is called again only when the system encounters an exception or complexity that genuinely requires reasoning.
AI builds the railway.
Deterministic systems move the cargo.
AI handles the exceptions.
For financial systems, reliability should come from architecture not from asking a probabilistic model to make the same judgement thousands of times.
