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Fintech Engineering Handbook
This comprehensive handbook outlines the fundamental patterns for engineering reliable financial software where correctness, persistence, and auditability are non-negotiable.
What: Author Voytek Pitula details essential fintech patterns based on three principles: no invented data, no lost data, and no trust. It covers money representation, double-entry bookkeeping, funds reservation, idempotency in distributed systems, and the implementation of audit trails.
Why it matters: As fintech systems increasingly rely on distributed services and third-party APIs, the manual reconciliation and integrity patterns described here have become standard requirements for maintaining a source of truth.
Takeaway: Consult the handbook's 'Flow 1' example when building critical money-movement systems to understand the required integration of reservation, audit trails, and reconciliation.
Deep dive
- Precision: Avoid floating-point types; store money as integers in smallest units or use arbitrary-precision decimals.
- Bookkeeping: Use double-entry ledgers; derive balances from movements rather than storing state.
- Consistency: Implement 'hold-and-release' patterns for fund reservations; use idempotency keys for all external API calls.
- Recovery: Design for resumability with persistent state machines instead of in-memory flows.
- Audit: Treat code commits and access control changes as part of the immutable financial audit trail.
- Reconciliation: Actively verify system state against third-party providers (banks, blockchains) to detect data drift.
Decoder
- Idempotency: A property of an operation where it can be applied multiple times without changing the result beyond the initial application.
- Double-entry bookkeeping: An accounting system where every transaction affects at least two accounts (debits and credits), ensuring the equation Assets = Liabilities + Equity remains balanced.
- CDC (Change Data Capture): A pattern where database write-ahead logs are tailed to stream state changes reliably to downstream systems.
- Saga pattern: A sequence of local transactions where each local transaction updates the database and publishes a message to trigger the next local transaction; if one fails, compensating transactions are executed to undo the changes.
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