Monte Carlo simulations have become an essential tool for retirement planning, allowing users to model thousands of financial outcomes based on variables like investment returns, inflation, and life expectancy. Using AI assistant Claude, the author generated a detailed simulation for a hypothetical couple—Joe and Jane Average—without needing programming skills or statistical expertise. 

Claude translated the couple’s retirement goals and financial data into a 5,000-iteration simulation using historical return data and a 60/40 stock-bond allocation, delivering a 95.78% success rate for retirement sustainability. 

The simulation projected a median portfolio of $28.2 million by Jane’s life expectancy, with very low depletion risk even in advanced age. Key strengths of the plan included strong pre-retirement savings, realistic spending goals, a balanced asset mix, and delayed Social Security filing. 

Finsum: Monte Carlo simulation can give you the edge to navigate and model various situations to deliver the best results to your clients.