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Endpoint

POST /api/simulation/sensitivity
Performs a sensitivity analysis to identify which financial parameters have the greatest impact on achieving your goal. This helps users understand which aspects of their financial situation to prioritize for improvement.

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Request Body

The request body uses the same SimulationRequest schema as the standard simulation endpoint.
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financialProfile
object
required
Complete financial profile containing current financial state.
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userInputs
object
required
User-specific information affecting simulation parameters.
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goal
object
required
Financial goal parameters for the analysis.
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simulationParams
object
Optional simulation parameters.

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Response

Returns sensitivity analysis results showing the impact of parameter changes.
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baseProbability
number
Baseline success probability with current parameters (0.0 - 1.0).
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sensitivities
object
Map of parameter names to sensitivity metrics. Each parameter tested shows how modifying it affects success probability.
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mostImpactful
string
Name of the parameter that has the greatest impact on success probability when modified.
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recommendations
array
Array of actionable recommendations based on the sensitivity analysis, ordered by potential impact.

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Example Request

curl -X POST "https://api.drift.example/api/simulation/sensitivity" \
  -H "Content-Type: application/json" \
  -d '{
    "financialProfile": {
      "liquidAssets": 15420.50,
      "creditDebt": 3250.00,
      "loanDebt": 28500.00,
      "monthlyLoanPayments": 425.00,
      "monthlyIncome": 6500.00,
      "monthlyBills": 850.00,
      "monthlySpending": 4120,
      "spendingByCategory": {
        "Grocery": 450.75,
        "Restaurants": 320.50,
        "Gas": 180.00
      },
      "spendingVolatility": 0.18
    },
    "userInputs": {
      "monthlyIncome": 6500,
      "age": 32,
      "riskTolerance": "medium"
    },
    "goal": {
      "targetAmount": 50000,
      "timelineMonths": 36,
      "goalType": "house_downpayment"
    },
    "simulationParams": {
      "nSimulations": 100000
    }
  }'

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Example Response

{
  "baseProbability": 0.73,
  "sensitivities": {
    "monthlyIncome": {
      "delta": 0.10,
      "newProbability": 0.815,
      "impact": 0.085
    },
    "monthlySpending": {
      "delta": -0.10,
      "newProbability": 0.802,
      "impact": 0.072
    },
    "creditDebt": {
      "delta": -0.50,
      "newProbability": 0.773,
      "impact": 0.043
    },
    "riskTolerance": {
      "delta": "high",
      "newProbability": 0.758,
      "impact": 0.028
    },
    "liquidAssets": {
      "delta": 0.20,
      "newProbability": 0.751,
      "impact": 0.021
    }
  },
  "mostImpactful": "monthlyIncome",
  "recommendations": [
    "Increasing monthly income by 10% would improve success probability to 81.5% (+8.5%)",
    "Reducing monthly spending by 10% would improve success probability to 80.2% (+7.2%)",
    "Paying down 50% of credit debt would improve success probability to 77.3% (+4.3%)",
    "Increasing risk tolerance to 'high' would improve success probability to 75.8% (+2.8%)",
    "Building liquid assets by 20% would improve success probability to 75.1% (+2.1%)"
  ]
}

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Understanding the Results

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Impact Interpretation

  • Positive impact: Indicates that increasing the parameter (or decreasing for debt/spending) improves success probability
  • Magnitude: Larger absolute impact values indicate parameters that are more influential
  • Actionability: Focus on parameters with high impact that you can realistically change

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Common Parameter Tests

The sensitivity analysis typically tests variations in:
  • Monthly Income: +10% increase
  • Monthly Spending: -10% decrease
  • Credit Debt: -50% reduction
  • Liquid Assets: +20% increase
  • Risk Tolerance: Shifting from current to higher/lower level
  • Timeline: Extending the goal timeline

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Using Recommendations

Recommendations are ordered by impact magnitude. Prioritize:
  1. High-impact changes you can control (income, spending)
  2. Medium-impact changes requiring planning (debt reduction)
  3. Low-impact optimizations (asset allocation, timeline adjustments)

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Error Responses

500 Internal Server Error 
{
  "error": "Failed to run sensitivity analysis"
}

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Usage Notes

  • Sensitivity analysis runs multiple simulations (one baseline + one per parameter tested), so it takes longer than a single simulation
  • Results help identify which financial improvements would most effectively increase goal achievement probability
  • The analysis assumes you can modify each parameter independently; in practice, some parameters may be correlated
  • Use this endpoint to create “what-if” scenarios for financial planning conversations

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