I keep seeing people recommend chatgpt for financial modeling and I need to push back because I spent a month testing it for multifamily underwriting and the results were not close to usable.
Pasting rent rolls, T12s, operating statements and asking it to build models, you get fragments. A few formulas, a cash flow table, maybe a cap rate calculation. Nothing ties together into a workbook you could hand to an investment committee. Fifteen rounds of prompting later and you've spent the same time you would have just building it in excel, except now you also have to debug whatever chatgpt hallucinated in cell D47.
Problem with chatgpt is that it doesn't maintain state across a complex multi-step task. It treats each prompt like a fresh conversation even in the same thread. An underwriting model where assumptions feed cash flows which feed returns which feed sensitivities requires coherence across all those layers and it fragments.
Purpose-built tools are architecturally different. They decompose the task, run autonomously for 15 to 30 minutes, check intermediate outputs, return a complete workbook with actual excel formulas. That's not a model quality difference, that's a design philosophy difference.
Chatgpt for quick questions and brainstorming, yes. For anything where the output IS the deliverable, no. Different architecture for different jobs.
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