diff --git a/backend/epc_client/client.py b/backend/epc_client/client.py
index 33f25ef5..0e3b48fc 100644
--- a/backend/epc_client/client.py
+++ b/backend/epc_client/client.py
@@ -7,7 +7,11 @@ from typing import Callable, Optional
 import httpx
 import pandas as pd
 
-from backend.epc_client.exceptions import EpcApiError, EpcNotFoundError, EpcRateLimitError
+from backend.epc_client.exceptions import (
+    EpcApiError,
+    EpcNotFoundError,
+    EpcRateLimitError,
+)
 from backend.epc_client._retry import call_with_retry
 from datatypes.epc.domain.epc_property_data import EpcPropertyData
 from datatypes.epc.domain.mapper import EpcPropertyDataMapper
@@ -26,6 +30,7 @@ class EpcSearchResult:
     current_energy_efficiency_band: str
     registration_date: str
 
+    @property
     def full_address(self) -> str:
         parts = [
             self.address_line_1,
@@ -68,12 +73,16 @@ class EpcClientService:
             return None
 
         # Round 1: score on addressLine1 only
-        cert_num = self._pick_best_cert(candidates, address, use_full_address=False, fn=get_uprn_candidates)
+        cert_num = self._pick_best_cert(
+            candidates, address, use_full_address=False, fn=get_uprn_candidates
+        )
         if cert_num:
             return self._safe_get(cert_num)
 
         # Round 2: score on all address lines joined
-        cert_num = self._pick_best_cert(candidates, address, use_full_address=True, fn=get_uprn_candidates)
+        cert_num = self._pick_best_cert(
+            candidates, address, use_full_address=True, fn=get_uprn_candidates
+        )
         if cert_num:
             return self._safe_get(cert_num)
 
@@ -145,14 +154,18 @@ class EpcClientService:
         use_full_address: bool,
         fn: Callable[..., pd.DataFrame],
     ) -> Optional[str]:
-        df = pd.DataFrame([
-            {
-                "address": r.full_address() if use_full_address else r.address_line_1,
-                "uprn": str(r.uprn) if r.uprn is not None else "",
-                "certificate_number": r.certificate_number,
-            }
-            for r in candidates
-        ])
+        df = pd.DataFrame(
+            [
+                {
+                    "address": (
+                        r.full_address() if use_full_address else r.address_line_1
+                    ),
+                    "uprn": str(r.uprn) if r.uprn is not None else "",
+                    "certificate_number": r.certificate_number,
+                }
+                for r in candidates
+            ]
+        )
 
         scored = fn(df, user_address=user_address)
         if scored.empty: