Financial tools are getting smarter — but many still miss the most important variable: real life. In this interview, Frances Rahaim explains why AI, calculators, and generic financial advice often get money wrong — not because the math is bad, but because the assumptions are incomplete.
This conversation covers:
• Why averages and projections break down in real households
• How rigid models ignore timing, cash flow, and lived experience
• The difference between “technically correct” and actually useful If a tool leaves you feeling confused, blamed, or behind — the problem isn’t you. It’s the model. This episode is about why financial guidance has to adapt to people — not the other way around.
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