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 系统, 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 设计 the detached 系统: fixed parsers, deterministic logic, accounting guidelines, validation rules, reconciliation checks, and predefined financial indicators.
然后 let financial data travel through that controlled 系统 repeatedly.
The AI does not need to “think” about every transaction.
It is called again only when the 系统 encounters an exception or complexity that genuinely requires reasoning.
AI builds the railway.
确定性 系统 move the cargo.
AI handles the exceptions.
For financial 系统, reliability should come from architecture not from asking a probabilistic model to make the same judgement thousands of times.
