LincPayandClaude Opus 5
a18c2f335f
The CBS/LMS extract is the deepest gap in the system: emi_delay and emi_to_inflow are computed from the loan book, and DPD history is the training label without which the model cannot be trained at all. This is how a real book gets in before a lender builds a nightly feed. Two schema problems had to be fixed first. loan_record had a unique index on accountRef alone, so the table could hold only each loan's current state — every monthly extract overwriting the evidence the model is meant to learn from. The key is now (accountRef, asOfDate): one row per loan per extract. The old constraint must be dropped by hand, as ddl-auto adds indexes but never removes them. emi_delay and emi_to_inflow took the worst DPD across every row at or before the scoring date, which with snapshots present would report a loan sixty days down in March as sixty days down today. Both now read the newest extract per accountRef. The history is there to train on, not to be summarised as the present. The no-PII promise is enforced at the parse boundary. A file whose headers carry a name, phone, Aadhaar, PAN, account number or address is rejected outright with the offending columns named, rather than having the column quietly dropped — a bank must learn the data is unwanted before it builds a nightly job that keeps sending it. ManualEntryLine now stores the row as supplied, so commit reads the file's own columns rather than a re-parse of a file nobody kept, and an auditor sees what the bank sent rather than our reading of it. Verified: a six-month, two-loan book uploads as 12 snapshots; a file with customer_name and mobile_no is refused whole; and emi_delay reports 2 for a loan that peaked at 3 and is now 2. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>