Hey all, member of the benchmark team here! The goal for this project was to see how LLMs well could do bookkeeping without an overly opinionated scaffold. We gave them access to processed transaction records and code execution tools, but it was up to them to choose exactly how to use those.

Claude and Grok 4 did reasonably well (within CPA baselines) for the first few months, but tended to degrade as more data came in. Interestingly, the failures aren’t exclusively a context length problem, as we reset the context monthly (with past decisions, accruals/deferrals, and comments available via tool calls) and the types of errors appear to be more reward hacking vs pure hallucinations.

Accounting is very interesting in an RL-first world as it is pretty easy to develop intermediate rewards for training models. We are pretty sure that we can juice the performance more with a far more rigid scaffold, but that’s less relevant from a capabilities research perspective. We’re pushing down this research direction and will see how it goes.

Let us know if you have any questions!