Why FLOAT Data Types Can Corrupt Financial Databases and How to Fix It

Using FLOAT or DOUBLE PRECISION data types in SQL databases for financial calculations introduces tiny rounding errors due to the IEEE 754 binary representation standard used by modern CPUs. Fractions like 0.1 and 0.2 cannot be represented exactly in base-2 binary, causing values such as 0.1 + 0.2 to return 0.30000001192092896 instead of 0.3. Across millions of daily transactions involving prices, taxes, or account balances, these small errors can accumulate into significant cash discrepancies during reconciliation. PostgreSQL's NUMERIC type avoids this by storing exact base-10 digits in memory, guaranteeing penny-perfect arithmetic with zero floating-point drift. Database engineers are advised to always use NUMERIC with defined precision and scale for any financial columns in production schemas.