feat: add wealth gap visualizer with Fed Reserve benchmarks

Made-with: Cursor
1 month ago · 6c30617afb
2 changed files with 240 additions and 0 deletions
--- a/agent/evals/test_wealth_visualizer.py
+++ b/agent/evals/test_wealth_visualizer.py
@ -0,0 +1,66 @@
+import sys
+import os
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'tools'))
+from wealth_visualizer import analyze_wealth_position
+
+
+def test_wealth_above_median():
+    result = analyze_wealth_position(
+        portfolio_value=94000, age=34, annual_income=120000
+    )
+    assert result["current_position"]["total_net_worth"] == 94000
+    assert "above median" in result["current_position"]["you_vs_median"]
+    assert result["retirement_projection"]["monthly_income_at_retirement"] > 0
+    assert "honest_assessment" in result
+
+
+def test_wealth_below_median():
+    result = analyze_wealth_position(
+        portfolio_value=15000, age=45, annual_income=80000
+    )
+    # 45-54 median is $247k, $15k is well below
+    assert result["current_position"]["total_net_worth"] == 15000
+    assert result["current_position"]["total_net_worth"] < 247000
+    assert "honest_assessment" in result
+
+
+def test_wealth_includes_real_estate():
+    result = analyze_wealth_position(
+        portfolio_value=94000, age=40,
+        annual_income=150000, real_estate_equity=140000
+    )
+    assert result["current_position"]["total_net_worth"] == 234000
+    assert result["current_position"]["real_estate_equity"] == 140000
+
+
+def test_early_retirement_scenario():
+    result = analyze_wealth_position(
+        portfolio_value=500000, age=40,
+        annual_income=200000, target_retirement_age=55
+    )
+    assert result["retirement_projection"]["years_to_retirement"] == 15
+    assert len(result["what_if_scenarios"]) >= 2
+
+
+def test_retirement_math_reasonable():
+    result = analyze_wealth_position(
+        portfolio_value=100000, age=35,
+        annual_income=100000, annual_savings=15000,
+        target_retirement_age=65
+    )
+    projected = result["retirement_projection"]["projected_total_at_retirement"]
+    assert projected > 700000
+    assert projected < 5000000
+
+
+def test_savings_grade_low_vs_high():
+    result_low = analyze_wealth_position(
+        50000, 30, 100000, annual_savings=5000
+    )
+    result_high = analyze_wealth_position(
+        50000, 30, 100000, annual_savings=30000
+    )
+    low_grade = result_low["savings_analysis"]["savings_grade"]
+    high_grade = result_high["savings_analysis"]["savings_grade"]
+    assert low_grade in ["critical", "minimum", "low"]
+    assert high_grade in ["excellent", "exceptional"]
--- a/agent/tools/wealth_visualizer.py
+++ b/agent/tools/wealth_visualizer.py
@ -0,0 +1,174 @@
+"""
+Wealth Gap Visualizer
+Compares actual net worth against Federal Reserve median wealth by age group.
+Projects retirement income and shows what-if scenarios.
+Source: Federal Reserve Survey of Consumer Finances 2022
+"""
+
+FED_WEALTH_DATA = {
+    "under_35": {
+        "median": 39000, "p25": 7000,
+        "p75": 168000, "p90": 466000,
+    },
+    "35_to_44": {
+        "median": 135000, "p25": 22000,
+        "p75": 461000, "p90": 1100000,
+    },
+    "45_to_54": {
+        "median": 247000, "p25": 43000,
+        "p75": 791000, "p90": 1900000,
+    },
+    "55_to_64": {
+        "median": 365000, "p25": 71000,
+        "p75": 1200000, "p90": 2900000,
+    },
+    "65_to_74": {
+        "median": 409000, "p25": 83000,
+        "p75": 1380000, "p90": 3200000,
+    },
+}
+
+SAVINGS_GRADES = {
+    "exceptional": (0.30, "You are building wealth aggressively"),
+    "excellent":   (0.20, "You are on track for most goals"),
+    "good":        (0.15, "Solid progress"),
+    "minimum":     (0.10, "Basic — consider increasing"),
+    "critical":    (0.05, "Below recommended — increase urgently"),
+    "low":         (0.0,  "Saving very little — prioritize this"),
+}
+
+
+def _get_age_bracket(age: int) -> str:
+    if age < 35:
+        return "under_35"
+    elif age < 45:
+        return "35_to_44"
+    elif age < 55:
+        return "45_to_54"
+    elif age < 65:
+        return "55_to_64"
+    else:
+        return "65_to_74"
+
+
+def analyze_wealth_position(
+    portfolio_value: float,
+    age: int,
+    annual_income: float,
+    annual_savings: float = None,
+    target_retirement_age: int = 65,
+    real_estate_equity: float = 0,
+) -> dict:
+    """Compare net worth against Fed Reserve benchmarks and project retirement."""
+
+    # Step 2: Total net worth
+    total_net_worth = portfolio_value + real_estate_equity
+
+    # Step 3: Percentile position
+    bracket_key = _get_age_bracket(age)
+    bracket = FED_WEALTH_DATA[bracket_key]
+
+    if total_net_worth >= bracket["p90"]:
+        position = "top 10%"
+    elif total_net_worth >= bracket["p75"]:
+        position = "75th-90th percentile"
+    elif total_net_worth >= bracket["median"]:
+        position = "50th-75th percentile"
+    elif total_net_worth >= bracket["p25"]:
+        position = "25th-50th percentile"
+    else:
+        position = "bottom 25%"
+
+    diff_from_median = total_net_worth - bracket["median"]
+    if diff_from_median >= 0:
+        vs_median = f"+${diff_from_median:,.0f} above median"
+    else:
+        vs_median = f"${abs(diff_from_median):,.0f} below median"
+
+    # Step 4: Savings analysis
+    savings = annual_savings if annual_savings is not None else annual_income * 0.15
+    savings_rate = savings / annual_income if annual_income > 0 else 0
+
+    grade = "low"
+    for g, (threshold, _) in SAVINGS_GRADES.items():
+        if savings_rate >= threshold:
+            grade = g
+            break
+
+    # Step 5: Retirement projection
+    years = max(1, target_retirement_age - age)
+    growth_rate = 0.07
+
+    future_portfolio = portfolio_value * ((1 + growth_rate) ** years)
+    future_savings = savings * (
+        ((1 + growth_rate) ** years - 1) / growth_rate
+    )
+    total_at_retirement = future_portfolio + future_savings
+    monthly_retirement_income = (total_at_retirement * 0.04) / 12
+
+    # Step 6: What-if scenarios
+    # Scenario 1: save 5% more
+    extra_annual = annual_income * 0.05
+    extra_future = extra_annual * (
+        ((1 + growth_rate) ** years - 1) / growth_rate
+    )
+    extra_monthly = (extra_future * 0.04) / 12
+
+    # Scenario 2: retire 5 years earlier
+    years_early = max(1, years - 5)
+    early_portfolio = portfolio_value * ((1 + growth_rate) ** years_early)
+    early_savings_val = savings * (
+        ((1 + growth_rate) ** years_early - 1) / growth_rate
+    )
+    early_monthly = ((early_portfolio + early_savings_val) * 0.04) / 12
+
+    # Build honest assessment
+    peer_clause = f"You are in the {position} for your age group."
+    retirement_clause = (
+        f"At your current savings rate, you can expect "
+        f"${round(monthly_retirement_income):,}/mo at retirement."
+    )
+    honest_assessment = f"{peer_clause} {retirement_clause}"
+
+    return {
+        "current_position": {
+            "age": age,
+            "total_net_worth": total_net_worth,
+            "portfolio_value": portfolio_value,
+            "real_estate_equity": real_estate_equity,
+            "vs_peers": position,
+            "median_for_age": bracket["median"],
+            "you_vs_median": vs_median,
+            "percentile_estimate": position,
+        },
+        "savings_analysis": {
+            "annual_savings_used": savings,
+            "savings_rate": round(savings_rate, 3),
+            "savings_grade": grade,
+            "assessment": SAVINGS_GRADES[grade][1],
+        },
+        "retirement_projection": {
+            "target_retirement_age": target_retirement_age,
+            "years_to_retirement": years,
+            "projected_total_at_retirement": round(total_at_retirement),
+            "monthly_income_at_retirement": round(monthly_retirement_income),
+            "assumptions": "7% annual growth, 4% withdrawal rate",
+        },
+        "what_if_scenarios": [
+            {
+                "scenario": "Save 5% more per year",
+                "extra_monthly_at_retirement": round(extra_monthly),
+                "description": (
+                    f"Adding ${extra_annual:,.0f}/yr gives "
+                    f"${round(extra_monthly):,} more per month at retirement"
+                ),
+            },
+            {
+                "scenario": f"Retire 5 years earlier (age {target_retirement_age - 5})",
+                "monthly_income": round(early_monthly),
+                "vs_normal_retirement": round(early_monthly - monthly_retirement_income),
+            },
+        ],
+        "honest_assessment": honest_assessment,
+        "data_source": "Federal Reserve Survey of Consumer Finances 2022",
+    }