Solving IEEE-754 Floating-Point Errors in Client-Side Fintech: Introducing FinEngine

Md Golam Mubasshir Rafi — Tue, 15 Sep 2026 19:40:32 +0000

Modern fintech demands deterministic precision. In finance, there is no room for approximation—every minor fractional unit must remain 100% audit-compliant.

Yet JavaScript, the backbone of client-side web applications, introduces structural challenges through IEEE-754 floating-point arithmetic. A single rounding drift can compound across amortization schedules and ledger balances.

To address this challenge and establish local currency primitives, we launched FinEngine—an open-source computational framework under the Centre for Fintech and Strategic Business Research (CFSBR).

Core Features (v0.3.0)

@finengine/core: Solves floating-point drift, introduces BDT sub-unit precision, and guarantees balanced ledger validation.
@finengine/math: Deterministic engines for reducing-balance loan amortization, repayment schedules, APR, XIRR, and Debt-Burden Ratio (DBR) stress tests.
@finengine/ui: Pre-built financial micro-components and KPI calculators.
100% Client-Side Privacy: All computations run locally inside the browser. Sensitive financial information is never transmitted to an external server.

Academic & Software Integrity

CrossRef DOI: 10.67226/cfsbr.fe.2026.001.v1
Zenodo Archive: 10.5281/zenodo.22769501

Explore the project:

Live Documentation & Labs: https://finengine.js.org
GitHub Repository: https://github.com/gmrafi/FinEngine

DEV Community: Md Golam Mubasshir Rafi

Solving IEEE-754 Floating-Point Errors in Client-Side Fintech: Introducing FinEngine

Core Features (v0.3.0)

Academic & Software Integrity