OpenAI has introduced a financial services product that brings professional data, analysis and granular citations into one environment. Its initial emphasis is on research and investment banking. The question it raises for leasing is more familiar: can we trace every number in a credit file to its source?
An application draws on accounts, statements, company records and asset documents. When a system turns these into a credit memo, the reader needs to see which document supports each claim, when it was produced and where the model has made an inference. A polished paragraph cannot stand in for evidence.
A faster first draft has value. A draft without reliable references merely transfers the work to the person asked to approve it.
I would start with a simple rule: no decision-relevant figure without a traceable source. The model may assemble and question the evidence. Credit authority remains with the people responsible for the decision.
How much time does your team spend finding the evidence behind a credit recommendation?
Source: https://openai.com/index/introducing-chatgpt-financial-services/