--- /data/files/bmw/stocklab-finalization-20260910-211846/app_engines_screening_executor.py.before
+++ /data/files/bmw/stocklab-release-candidate-sl003-final-20260910-111453/app/engines/screening/executor.py
@@ -14,6 +14,38 @@
     "overall_score", "quality_score", "financial_health_score", "growth_score",
     "competitive_advantage_score", "valuation_score", "risk_score",
 }
+
+_PERCENTAGE_METRICS = {
+    "roic",
+    "roic_minus_wacc",
+    "revenue_growth_yoy",
+    "revenue_cagr_5y",
+    "eps_growth_yoy",
+    "fcf_growth_yoy",
+    "gross_margin",
+    "operating_margin",
+    "net_margin",
+    "fcf_margin",
+    "fcf_yield",
+    "dividend_yield",
+    "buyback_yield",
+    "shareholder_yield",
+    "roe",
+    "fcf_payout_ratio",
+}
+
+
+def _normalize_metric_threshold(
+    metric: str,
+    value: float | None,
+) -> float | None:
+    """Convert public percentage-point thresholds to stored ratio values."""
+    if value is None:
+        return None
+    if metric in _PERCENTAGE_METRICS:
+        return value / 100.0
+    return value
+
 
 _OP_MAP = {
     "gt": lambda col, v, v2: col > v,
@@ -41,7 +73,9 @@
             f"this build — see docs/SPEC_COVERAGE.md. Use relative='absolute' for now."
         )
     m = Metric.__table__.alias(f"metric_{f.metric}")
-    condition = _OP_MAP[f.op](m.c.value, f.value, f.value2)
+    value = _normalize_metric_threshold(f.metric, f.value)
+    value2 = _normalize_metric_threshold(f.metric, f.value2)
+    condition = _OP_MAP[f.op](m.c.value, value, value2)
     return exists(
         select(1).select_from(m).where(m.c.security_id == Security.id, m.c.metric_key == f.metric, condition)
     )