I need a dynamic statistical model that lets the user define ratings across multiple probability sets, automatic classification in to risk tiers, stress-tests with a full Monte Carlo simulation clearly showing outputs that are then linked to a projected income statement. The spreadsheet should be clean, clearly laid out, and fully link-driven so I can change any assumption in one place and watch the impacts flow through revenue, COGS, operating expenses, EBITDA, tax and finally net income. Here is what I’m after: • You build the core model using dummy data that is able to run statistical simulations in Excel. • Key drivers—product pricing, loan-to-value, various probability metrics for product's associated risk tier, classified into 4 tiers, impacts on capital stack, revenue growth, cost structure, margins, tax, or any other variables we agree on—sit in an inputs tab with adjustable probability distributions rather than single-point estimates. • A Monte Carlo engine (Excel VBA, Python, @RISK, Crystal Ball—use the tool you’re comfortable with) runs thousands of iterations, captures the resulting distributions for revenue, EBIT and net income, and produces summary charts: histograms, cumulative probability curves and a tornado sensitivity. • Final deliverable is the model file plus a brief read-me or loom walkthrough so I understand how to tweak assumptions and rerun the simulation myself. Acceptance criteria: the model updates without errors when any driver is changed; fully linked; the simulation runs end-to-end on my machine; charts automatically refresh; and I can see the percentile bands (P10, P50, P90) for net income, reinsurance loss ratios. If you’ve built probabilistic financial models before (similar to insurance models), let me know. Looking forward to working with you.