The book held one snapshot per loan, so there was no history at all and
nothing a model could learn from. Two routes now fill it, and the
difference between them is stated rather than implied: generate
synthetic monthly snapshots for the prototype, or backfill month-end
extracts from the lender's core, which is the real path — every core can
answer "what did the book look like at each month end last year",
because it is the query behind their regulatory returns.
LoanRecord.source is stamped at every write site: SEEDED,
SEEDED_HISTORY, UPLOAD, or the connector profile code. Coverage reports
three buckets — synthetic, real, and unknown provenance — and never
folds unknown into real, because an unlabelled row is not evidence of a
lender extract. With no real extract on the book it reports
trainable:false and says why in words. Generation never overwrites an
existing row, so a real extract survives a regeneration untouched, and
purge removes only what was generated.
The generator's arithmetic had to be got right and was not at first.
Real DPD steps: pay and cure to zero, or miss and roll forward one
instalment period. The first version drew the day-of-month slack per
month, so consecutive months differed by anything from 1 to 59 days — a
shape no loan book produces, and one that would have taught a model a
transition matrix nothing real generates. The slack is now fixed per
delinquency episode, since a due date does not move between two missed
payments: an account 5 days down that misses again is 35 days down, not
12. For the run reaching the anchor it is derived from the anchor's own
DPD, so the series joins today's number exactly rather than near it.
DpdWalk is shared with the simulated adapters, which previously returned
today's DPD for every requested date — a backfill through them would
have been a flat line, which is exactly the shape that makes a training
label useless and which a chart would have hidden.
Verified against a running instance: 3,256 snapshots across 142 loans,
24 monthly extract dates spanning 2024-08 to 2026-07, 100% of
enterprises now carrying history, every generated series rolling by
exactly 30 — the only non-30 steps being joins to pre-existing rows the
generator correctly refused to overwrite. A 6-month Finacle backfill
pulled 264 rows and staged them for review.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
The loan book is the training label and the one input no public feed
supplies. Integrating with a lender's core is not a technical unknown —
it is an onboarding process per bank, with a schema agreed in a room.
What can be built before that room is the seam, and this is it.
CoreBankingConnector fetches and returns rows; it never writes. Mapped
rows go to LoanBookEntryService.stage — the same validator an uploaded
spreadsheet goes through, landing in the same manual_entry_batch with
the same preview. A parallel validator for the automated path would be
the obvious shape and would eventually enforce the no-PII rule
differently.
FileDropConnector is real: it reads the newest matching file from a
directory a bank delivers to, and leaves it there so a failed run is
repeatable. Finacle, FLEXCUBE, BaNCS and an in-house REST LMS are
simulated, each emitting the same portfolio in its own column dialect —
DPD_DAYS, OVERDUE_DAYS, DAYS_OVERDUE, daysPastDue — which is what makes
the case for a mapping layer rather than asserting it.
The mapping is {canonical: vendor}, keyed by canonical name, so an
unmapped vendor column has no route through and is dropped at the
boundary. CUST_NAME and MOBILE_NO stay out structurally rather than by
anyone remembering. Auto-commit is off on every profile: a sync stages
and stops, keeping the rule that nothing is written until someone has
seen what will be. simulated is stamped per run, not read from the
profile, so switching a profile live cannot make old runs look real.
Fixes a real defect this surfaced: FORBIDDEN_COLUMNS matched on the
exact normalised name, so CUST_NAME — what Finacle actually calls it —
was missed, and a directly uploaded bank file would have kept the
borrower's name in manual_entry_line.raw_row. Matching now splits
separators and camelCase, catching borrowerMobile too, while
loan_account_ref still splits clean.
Verified against a running instance: Finacle 44/44 accepted with 4
columns dropped, the file drop 2 accepted and 1 UNKNOWN_ENTERPRISE
rejected from a real CSV, and both CUST_NAME and borrowerMobile refused
at mapping save.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Spring Boot 4 / Java 17 / Postgres. Masters and serving (A), Agmarknet and
climate ingestion (B), feature store with 14 derivations (C), SpEL rule
engine and risk scoring (D).
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
