Practical articles on the financial challenges facing SaaS founders, events operators, and their investors — including how machine learning and generative AI are changing what a CFO can deliver.
Ten practical applications of AI and machine learning inside a real finance function — from automating month-end and driver-based cash and EBITDA forecasting to anomaly detection, RAG over contracts, and explainable credit scoring — and where a stretched team should actually start.
Read article →How XGBoost and Random Forest classification models turn customer behaviour data into a weekly churn probability score — identifying at-risk accounts weeks before they cancel, so you can intervene while there is still time.
Read article →How LLM pipelines using enterprise LLM APIs automate board pack commentary, variance narratives, and financial document analysis — with practical examples and the prompt engineering patterns that make them reliable.
Read article →ARR, NRR, CAC payback, churn, and LTV:CAC ratio — why each matters to a SaaS investor, what each reveals about the health of your business, and how Python eliminates the manual work of tracking them monthly.
Read article →The architecture, assumptions, and weekly discipline behind a rolling cashflow model that gives boards genuine visibility of financial runway — with a real example of how it averted a liquidity shortfall in a PE-backed events business.
Read article →Six warning signs that your finance operation has not scaled with your business — from a management accounts close that takes too long to a board pack that no one trusts — and what to do about each one.
Read article →Most of these articles reflect challenges Graeme has solved directly. If any resonate with your situation, let’s talk.
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