Financial Forecasting Engine
Generate forecasts using multiple statistical methods with best/base/worst scenario overlays, confidence intervals, and exportable projections.
Problem
Financial forecasting typically requires manual model building in Excel with limited ability to quickly compare methods or run scenario analysis. Teams need faster iteration on assumptions.
Approach
Implemented three statistical forecasting methods with automatic parameter optimization. Added a scenario planning layer that applies growth/decline adjustments, and built visualizations showing base forecast with 95% confidence intervals alongside best/worst case projections.
Outcome
A tool that demonstrates forecasting methodology, scenario planning, and statistical rigor — core competencies for any FP&A role requiring budget and revenue projection.
Details
Built a forecasting tool that applies multiple statistical methods (exponential smoothing, linear trend, moving average) to historical financial data and projects future values with confidence intervals.
Includes scenario planning controls that overlay best-case and worst-case growth/decline assumptions on top of the base statistical forecast.
Features cumulative forecast comparison across scenarios and month-over-month growth rate analysis.