How do I judge whether generated remittance and allocation records are realistic enough?

Start by checking internal consistency, because it can be tested mechanically. Allocations should sum to line amounts, closed items should have zero balance, dates should run in a sensible order, and every foreign key should resolve. A loader script that reports violations takes little effort and catches structural faults early.

Next, inspect the messiness. Matching is difficult because references are partial, amounts are rounded and customers pay in odd patterns. Sample the payer text fields and ask whether they vary in the ways your own feeds vary: truncation, abbreviations, transposed digits, bundled invoice numbers. Check that hard cases are not all clustered at one difficulty level.

Then inspect policy fit. Read a few policies and pick tasks at random. Can you work out the expected answer from the policy and the state? If a task has two defensible answers and the expected outcome names only one, flag it.

Finally, assess grounding and disclosure. The data is generated, so ask how patterns were derived, whether any value could be traced to a real payer or account, and what review was applied. Do not assume generation removes that risk; ask for the method and test it on a sample.

Treat your own domain staff as reviewers. A short review by people who do this work will reveal unrealistic cases faster than a metric will.