diff --git a/backend/Property.py b/backend/Property.py
index 418a35a1..c0f19ab5 100644
--- a/backend/Property.py
+++ b/backend/Property.py
@@ -128,16 +128,19 @@ class Property:
         It will be the same starting and ending EPC, as we don't have the expected EPC yet
         """
 
-        difference_record = self.epc_record - self.epc_record
+        # difference_record = self.epc_record - self.epc_record
 
         # TODO: change these lower and replace in the settings file
+        print("CHANGE THE LATEST FIELD TO REMOVE NUMBER HABITABLE ROOMS IF WE WANT TO USE STARTING/ENDING")
         fixed_data_col_names = MANDATORY_FIXED_FEATURES + LATEST_FIELD
         print("NEED TO CHANGE THE DASH TO LOWER CASE")
         fixed_data_col_names = [x.lower().replace("_", "-") for x in fixed_data_col_names]
 
         fixed_data = {k.replace("-", "_"): v for k, v in self.data.items() if k in fixed_data_col_names}
 
-        difference_record.append_fixed_data(fixed_data)
+        # difference_record.append_fixed_data(fixed_data)
+
+        difference_record = self.epc_record.create_EPCDifferenceRecord(self.epc_record, fixed_data)
 
         self.base_difference_record = TrainingDataset(datasets=[difference_record], cleaned_lookup=cleaned_lookup)
 
@@ -238,12 +241,15 @@ class Property:
                 # Note: often when the wall is insulatied, the internal/external insulation is not noted so we should
                 #       test the impact of using these booleans
                 if recommendation["type"] == "external_wall_insulation":
-                    output["external_insulation"] = True
-                    output["internal_insulation"] = False
+                    output["external_insulation_ending"] = True
+                    output["internal_insulation_ending"] = False
 
                 if recommendation["type"] == "internal_wall_insulation":
-                    output["external_insulation"] = False
-                    output["internal_insulation"] = True
+                    output["external_insulation_ending"] = False
+                    output["internal_insulation_ending"] = True
+
+                if recommendation["type"] == "cavity_wall_insulation":
+                    output['is_filled_cavity_ending'] = True
 
                 # TODO: perhaps detrimental
                 # When making a recommendation for the wall, we will also update the ventilation
@@ -314,7 +320,7 @@ class Property:
 
             if recommendation["type"] == "low_energy_lighting":
                 output["low_energy_lighting_ending"] = 100
-                output["lighting_energy_eff_starting"] = "Very Good"
+                output["lighting_energy_eff_ending"] = "Very Good"
 
             if recommendation["type"] == "windows_glazing":
                 output["multi_glaze_proportion_ending"] = 100
diff --git a/etl/epc/Pipeline.py b/etl/epc/Pipeline.py
index 0943b206..ba228d89 100644
--- a/etl/epc/Pipeline.py
+++ b/etl/epc/Pipeline.py
@@ -24,7 +24,8 @@ from etl.epc.settings import (
 
 # TODO: change in setting file
 MANDATORY_FIXED_FEATURES = [x.lower() for x in MANDATORY_FIXED_FEATURES]
-LATEST_FIELD = [x.lower() for x in LATEST_FIELD if x.lower() not in ROOM_FEATURES]
+# LATEST_FIELD = [x.lower() for x in LATEST_FIELD if x.lower() not in ROOM_FEATURES]
+LATEST_FIELD = [x.lower() for x in LATEST_FIELD]
 COMPONENT_FEATURES = [x.lower() for x in COMPONENT_FEATURES]
 RDSAP_RESPONSE = RDSAP_RESPONSE.lower()
 HEAT_DEMAND_RESPONSE = HEAT_DEMAND_RESPONSE.lower()
diff --git a/etl/epc/generate_scenarios_data.py b/etl/epc/generate_scenarios_data.py
index afe9ab98..172e8a27 100644
--- a/etl/epc/generate_scenarios_data.py
+++ b/etl/epc/generate_scenarios_data.py
@@ -183,7 +183,7 @@ for scenario_property in scenario_properties:
 
         if "windows" in measure:
             for rec in windows_recommendations:
-                if rec["type"] == "windows":
+                if rec["type"] == "windows_glazing":
                     windows_recs.append(rec)
 
         combi_list = [wall_recs, loft_recs, solar_recs, windows_recs]
@@ -240,8 +240,8 @@ all_predictions = model_api.predict_all(
     prediction_buckets={
         "sap_change_predictions": get_settings().SAP_PREDICTIONS_BUCKET,
         "heat_demand_predictions": get_settings().HEAT_PREDICTIONS_BUCKET,
-        "carbon_change_predictions": get_settings().CARBON_PREDICTIONS_BUCKET
-    }
+        "carbon_change_predictions": get_settings().CARBON_PREDICTIONS_BUCKET,
+    },
 )
 
 save_dataframe_to_s3_parquet(