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FinEngine
Deterministic financial math & BDT-precision engine
FinEngine is an open-source computational framework solving IEEE-754 floating-point rounding anomalies in client-side fintech. It delivers deterministic integer arithmetic, native BDT (Bangladeshi Taka) sub-unit precision, and zero-knowledge client-side privacy. Built for reducing-balance loan amortization, APR/XIRR engines, and audit-compliant ledger validation, backed by Crossref and Zenodo research archives.
Includes @finengine/core (integer math), @finengine/math (reducing-balance amortization, APR, XIRR), and @finengine/ui (headless KPI helpers). Built for developers and finance researchers who require absolute computational accuracy.
Looking forward to your critical feedback on our calculation models!
For any developers curious about the under-the-hood math: instead of dealing with floating-point drift (0.1 + 0.2 !== 0.3), FinEngine shifts all currency amounts, such as BDT (Bangladeshi Taka), into discrete integer sub-units (poisha / cents, scaled * 100) before running any reducing-balance amortization or XIRR loops. Would love to hear how other teams handle precision in client-side financial ledgers.
About FinEngine on Product Hunt
“Deterministic financial math & BDT-precision engine”
FinEngine was submitted on Product Hunt and earned 0 upvotes and 2 comments, placing #82 on the daily leaderboard. FinEngine is an open-source computational framework solving IEEE-754 floating-point rounding anomalies in client-side fintech. It delivers deterministic integer arithmetic, native BDT (Bangladeshi Taka) sub-unit precision, and zero-knowledge client-side privacy. Built for reducing-balance loan amortization, APR/XIRR engines, and audit-compliant ledger validation, backed by Crossref and Zenodo research archives.
FinEngine was featured in Open Source (68.9k followers), Fintech (47.5k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 65.4k products, making this a competitive space to launch in.
Who hunted FinEngine?
FinEngine was hunted by Md Golam Mubasshir Rafi. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Md Golam Mubasshir Rafi
Hey Product Hunt,
I am Rafi, a finance researcher and developer launching FinEngine on behalf of CFSBR.
JavaScript's IEEE-754 drift introduces compounding rounding errors in financial ledgers. FinEngine solves this via deterministic integer arithmetic, native BDT poisha precision, and 100% client-side execution (zero data leakage).
Links & Verification:
• Simulation Lab & Docs: https://finengine.js.org
• GitHub Repository (MIT): https://github.com/gmrafi/FinEngine
• Methodology Paper (Crossref DOI): https://doi.org/10.67226/cfsbr.fe.2026.001.v1
• Software Archive (Zenodo DOI): https://doi.org/10.5281/zenodo.22769501
Architecture:
Includes @finengine/core (integer math), @finengine/math (reducing-balance amortization, APR, XIRR), and @finengine/ui (headless KPI helpers). Built for developers and finance researchers who require absolute computational accuracy.
Looking forward to your critical feedback on our calculation models!