LIGHTS-OUT FINANCE
A fintech publication · Built on one thesis

Finance is going Lights Out.
This is the record of how.

The thesis: “Lights Out” is the end state — a finance function that runs itself, routes only exceptions to people, and keeps running overnight, at quarter-end, and through Day-1 events. What it delivers: humans and AI teaming on judgment, a continuous close, controls that execute and evidence themselves, and insight at the speed of the decision. Every finance function sits somewhere on this spectrum; the benchmark measures where you stand.

Each paper argues one move on that spectrum — with a working model you can run on your own numbers — and the benchmark measures where you stand.

Read the thesisSee how it branches
AB
Adil Bahir
Founder & Editor, Lights-Out Finance · Two decades in finance transformation, quantitative finance, and enterprise AI
The Lights-Out Finance Survey · inaugural benchmark now collecting
The Papers

The papers

Every paper is interactive: the argument, the architecture, and a working model — calibrated to your numbers, not taken on faith.

Explore every paper in the coverage matrix →

The Benchmark

The Lights-Out Finance Survey

Every paper is opinion until it meets data. The Lights-Out Maturity Index — six questions, two minutes, plain-language answers — measures where finance operations actually sit on the path from spreadsheets-and-heroics to autonomous. Anonymous responses build the benchmark this publication reports on: maturity by domain, by industry, by region.

Where does your operation sit?

The Lights-Out Maturity Index: six questions, two minutes, no scales to interpret. Your anonymous result joins the inaugural Lights-Out Finance Survey — the benchmark this publication reports on.

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About

The editor

Lights-Out Finance is written and edited by Adil Bahir — a Big 4 partner in CFO Advisory & Finance Transformation with more than twenty years across the Americas, EMEA, and APAC. His delivery record spans the Day-1 finance model for a $9B TMT divestiture, a $2.1B asset-management carve-out across 24 countries, reconciliation automation above 90% touchless across 37 countries, and $50M–$100M+ ERP transformation programs — the operational benchmarks referenced throughout these pages.

He holds a Doctor of Engineering (DEng.) in Artificial Intelligence from George Washington University, an MBA (Finance) from Cornell University, a Master in Financial Engineering from Queen’s University’s Smith School of Business, and an MEng/MBA from École des Ponts ParisTech; professional credentials include US CPA, CGMA, FRM, CQF, CTP, and CDAA. His work spans the full breadth of financial technology — ERP and core-banking modernization, treasury and capital markets platforms, quantitative finance, FinOps, and enterprise AI — with one thread throughout: taking finance functions to autonomous, exception-based operation.

Read the full masthead — the thesis, the framework, and the editorial principles →

Views expressed are the author’s own and do not represent any employer or affiliated organization.

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