The Spreadsheet Killer

Enterprise tools cost six figures. Excel models break when you breathe on them. There’s a gap you could drive a truck through.

So I built the-spreadsheet-killer.

It’s a high-performance actuarial engine in Go. Zero dependencies. Just the standard library. It handles concurrent financial simulations, mass policy valuations, and Monte Carlo interest rate modelling at speeds that’ll make you wonder why you ever tolerated spreadsheets.

The Name

the-spreadsheet-killer (v*) is actuarial notation. When an annuity’s payments compound at rate j but are discounted at rate i, the adjusted discount factor is:

v* = (1 + j) · v

It’s an inside joke from university, one my lecturer and coursemates will recognise. If the math is niche enough, the project name should be too.

What It Actually Does

Policy valuation streams CSV files of insurance policies and calculates present values. Over a million records in under 300ms. It streams data instead of loading everything into RAM, so your laptop won’t start sounding like a jet engine.

Monte Carlo simulation generates interest rate paths for stochastic modelling. 100,000 paths with 10 time steps in about 100ms. Geometric Brownian motion with configurable drift and volatility. You can sit there tweaking parameters and watching it churn through simulations like they’re nothing.

CLI-first means no web dashboard, no config files, no GUI. Just flags and pipes:

./the-spreadsheet-killer -i 0.05 -j 0.02
./the-spreadsheet-killer read policies.csv --benchmark
./the-spreadsheet-killer montecarlo --paths=100000 --steps=10

Everything is composable. Pipe stuff in, get stuff out. Unix philosophy applied to actuarial science.

Why This Exists

I got tired of tools that treat actuarial work like it needs to be hidden behind layers of abstraction. The math isn’t that complicated. The data isn’t that special. What’s hard is doing it fast, at scale, and in a way you can actually audit.

the-spreadsheet-killer is the opposite of a black box. Every calculation is readable. Every assumption is visible. No hidden columns, no macros running in the background, no “we’ve always done it this way.”

The code is on GitHub. Go read it. Or don’t. But if you’re still running actuarial models in Excel, ask yourself why.