Tutorial series
MF360: Mutual Fund Intelligence Platform
Trustworthy answers from messy Indian mutual-fund data: methodology first, corrections as rows, golden portfolios as proof.
Case study: MF360: Mutual Fund Intelligence Platform
- Part 1
Method and monolith: how a 383-file project stays coherent
Follow one investor from CAS upload to reviewed portfolio while learning the doc/ vs docs/ split, task protocol, and DDD layers that keep it coherent.
- Part 2
Domain core: frozen entities, masked identity, honest tax
Build value objects that can't hold invalid states, PAN handling that can't leak, and a tax engine with FY rules — verbatim code included.
- Part 3
Money math: XIRR, TER leakage, overlap, and harvesting
Compute what Ravi actually pays and earns: XIRR with fallbacks, regular-vs-direct lifetime cost, overlap flags, and tax-loss harvesting — formulas first.
- Part 4
Ingestion: CAS files, deltas, NAVs, and fuzzy matching
Turn Ravi's messy statements into validated facts: CAS parsing, correction rows, NAV pipeline, and 4-strategy scheme mapping with confidences.
- Part 5
API, security, testing, and capstone
Serve Ravi's data with RLS and masked PANs, prove money math with 24 golden portfolios, and keep the glossary and principles worth stealing.