Financial Risk Prediction Analysis

I need an experienced analyst to run predictive analysis on my firm’s financial data with the clear objective of identifying potential risks before they materialise. The raw information is already exported from our accounting system (CSV format, roughly five years of monthly figures across revenue, expenses, cash flow and outstanding liabilities). Your task is to clean it, select the most relevant variables, build a reliable predictive model and translate the results into plain-language insights that managers can act on.

I’m open to the specific toolset you prefer—Python (pandas, scikit-learn), R or even a SQL-driven approach—as long as the workflow is reproducible. Accuracy and explainability matter more to me than fancy visualisation, but a concise dashboard or notebook that highlights red-flag indicators in real time would be a welcome bonus.

Deliverables
• Fully commented code or notebook showing data preparation, feature engineering and model training
• A short report (PDF or slide deck) that explains the model, the key risk drivers you uncovered and concrete recommendations for mitigation
• Any supporting files, ready for me to rerun on new data without extra setup

I will provide the dataset and answer domain questions promptly so you can move quickly from exploration to modelling.