Fannie Mae's loan-level disclosure format hasn't stood still since 1999. Field
names get renamed, delinquency status codes get re-bucketed, new modification
flags get introduced mid-stream, and the agencies don't always flag these
changes loudly. A field like dq_status can mean something subtly
different in a 2008 origination file than it does in a 2022 one, and nothing in
the raw data tells you that happened.
If you're querying across 20+ years of vintage data, which is exactly what credit and prepay analysis requires, that silent drift turns into silently wrong answers.
The common pattern: someone notices a field changed, patches the ingestion script to handle the new format, and moves on. The fix lives in a commit message or a Slack thread, not in anything queryable. Six months later, a different engineer hits the same vintage boundary, doesn't know the history, and either reintroduces the bug or burns a day rediscovering it.
We externalize format history as a database object: the Format Registry. Every agency format change becomes a new registry entry: which fields existed, what they meant, and exactly when the change took effect. It's bi-temporal (it tracks both when a format was valid in the source data and when we recorded that fact) and fully replayable. We can reconstruct exactly how any vintage of loan data should be parsed and interpreted, audit-proof, without code archaeology.
Staging retains the native agency format as originally published; the semantic layer is MISMO-aligned on top of that, with the Format Registry as the bridge between the two.
Stable field semantics across vintages aren't a nice-to-have when an LLM is the
one writing the query. An agent that doesn't know dq_status changed
meaning in 2015 won't ask. It'll just hallucinate a consistent-sounding answer
from inconsistent data. MISMO alignment plus the Format Registry means a query
spanning multiple vintages returns what it actually claims to return, whether a
human or an agent wrote it.
Want to see the Format Registry in action across Fannie Mae, Freddie Mac, and Ginnie Mae data?
Request Early Access →