How can I inspect the quality of generated allocation data before using it?

Quality in this kind of material is mostly about internal consistency and defensible ground truth. A buyer can test both before using any of it for training or evaluation.

Start with arithmetic and referential checks. Every allocation should reference a real bank line and a real open item. Open amounts should equal original amounts minus applied amounts and credits. A script can verify these across a whole release.

Next, check the reference outcomes. Sample a set of tasks and have someone who knows receipts processing work them without seeing the answer. Where they disagree with the reference, decide whether the policy was ambiguous or the reference was wrong. Both findings are useful.

Then look at the spread of difficulty. If nearly every task has a clean reference match, scores will cluster near the top and tell you little. If nearly every task is an exception, you lose the ability to see whether an agent handles routine work.

Finally, inspect for grounding and disclosure risk. Generated data can still echo patterns or strings from its sources. Ask how the output was produced, look for names, account numbers or free text that appear too realistic or too specific, and raise anything suspicious with the provider.

Quality checks do not replace a pilot on your own harness. They tell you whether the material is fit to be tested, not whether it will predict how your agents behave in production.