Python for Fintech: Precision Wars

In standard computing, 0.1 + 0.2 does NOT equal 0.3. It equals 0.30000000000000004. This is a floating-point error. For a video game, this doesn't matter. For a bank ledger, it is a fireable offense.

The "Fast but Wrong" Trap

Many languages prioritize floating-point speed (for graphics/science) over decimal accuracy. If you build a financial app using standard float types in JavaScript or Python, these microscopic errors compound. Over millions of transactions, they turn into accounting discrepancies that fail audits.

The Solution: Decimal Types & Atomic Math

We engineer financial backends using Python's decimal module and precise database constraints:

• Hard Accuracy: We define exact precision (e.g., 28 decimal places) for every calculation.
• Rounding Modes: We control exactly how rounding happens (Round Half to Even, Round Up, etc.) to match banking standards.
• ACID Transactions: Money is never "in flight." It moves from Account A to Account B in a single atomic database commit.

Don't Play with Money

You need an architecture that treats numbers as facts, not approximations.