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SIMULATION ENGINE
The Affordability Pilot
"Can I afford this?" — actually answered with mathematical precision, not gut feeling.
10,000 simulations. One clear answer.
Before you commit to a purchase, the Affordability Pilot runs Monte Carlo simulations against your real financial position. It factors in upcoming bills, historical spending patterns, and black swan events (5% chance of a £300–£1,000 emergency).
The output is a probability: >90% = GO, 70–90% = CAUTION, <70% = NO.
Affordability Check
£500 iPad
10,000 simulations
94.2%
Probability of Success
GOBreakdown
Current balance after obligations£1,071.75
After purchase£571.75
Upcoming obligations (next 30 days)£1,365
Expected income£2,400
Buffer remaining£606.75
Black swan reserveAdequate
Affordability Check
£2,000 Holiday
10,000 simulations
61.3%
Probability of Success
NOInsufficient buffer for upcoming rent + bills. Consider after next payday.
Technical Specification
Method: Monte Carlo simulation (10,000 iterations) Inputs: Current balance, obligations, spending history Black swan: 5% probability of emergency (£300-£1,000) Output: Success probability, action, buffer remaining Thresholds: >90% → APPROVED (GO) 70-90% → CAUTION <70% → REJECTED (NO) Latency: <500ms for 10,000 iterations History: All checks logged for spending pattern analysis
affordability-mobile-check.pngMobile app showing real-time affordability check at point of purchase
affordability-history.pngAffordability check history showing past decisions and outcomes
API Endpoints
POST
/api/v1/affordability/simulateRun affordability checkGET
/api/v1/affordability/scoreGet current affordability scoreGET
/api/v1/affordability/historyCheck history