diff --git a/TM1py/Services/CellService.py b/TM1py/Services/CellService.py
index 4d904b08..9a8a3d1f 100644
--- a/TM1py/Services/CellService.py
+++ b/TM1py/Services/CellService.py
@@ -45,6 +45,7 @@
     abbreviate_mdx,
     build_cellset_from_pandas_dataframe,
     build_csv_from_cellset_dict,
+    build_dataframe_aggregate_intersections,
     build_dataframe_from_csv,
     build_mdx_and_values_from_cellset,
     build_mdx_from_cellset,
@@ -1068,7 +1069,7 @@ def write_dataframe_async(
         slice_size_of_dataframe: int = 250_000,
         max_workers: int = 8,
         dimensions: Iterable[str] = None,
-        increment: bool = False,
+        increment: bool = True,
         sandbox_name: str = None,
         deactivate_transaction_log: bool = False,
         reactivate_transaction_log: bool = False,
@@ -1083,7 +1084,7 @@ def write_dataframe_async(
         :param slice_size_of_dataframe: Number of rows for each DataFrame slice, e.g. 10000
         :param max_workers: Max number of threads, e.g. 14
         :param dimensions:
-        :param increment: increment or update cell values. Defaults to False.
+        :param increment: increment or update cell values. Defaults to True.
         :param sandbox_name: name of the sandbox or None
         :param deactivate_transaction_log:
         :param reactivate_transaction_log:
@@ -1127,6 +1128,9 @@ async def _write_async(df: "pd.DataFrame"):
 
             return failures
 
+        if increment:
+            data = build_dataframe_aggregate_intersections(data, sum_numeric_duplicates=True)
+
         exceptions = asyncio.run(_write_async(data))
         if not exceptions:
             return
diff --git a/TM1py/Utils/Utils.py b/TM1py/Utils/Utils.py
index f84bbab3..dc5f5852 100644
--- a/TM1py/Utils/Utils.py
+++ b/TM1py/Utils/Utils.py
@@ -937,6 +937,23 @@ def build_cellset_from_pandas_dataframe(
 
     :return: a CaseAndSpaceInsensitiveTuplesDict
     """
+    df = build_dataframe_aggregate_intersections(df, sum_numeric_duplicates)
+
+    cellset = CaseAndSpaceInsensitiveTuplesDict(
+        dict(zip(df.iloc[:, :-1].itertuples(index=False, name=None), df.iloc[:, -1].values))
+    )
+    return cellset
+
+
+@require_pandas
+def build_dataframe_aggregate_intersections(df: "pd.DataFrame", sum_numeric_duplicates: bool = True) -> "pd.DataFrame":
+    """
+
+    param sum_numeric_duplicates: Aggregate numerical values for duplicated intersections
+    param df: A Dataframe, with dimension-column mapping in correct order.
+
+    :return: A Dataframe
+    """
     if isinstance(df.index, pd.MultiIndex):
         df.reset_index(inplace=True)