3 files changed, 81 insertions, 8 deletions

diff --git a/python/collateral/__main__.py b/python/collateral/__main__.py
index dcf4e18a..01d2a283 100644
--- a/python/collateral/__main__.py
+++ b/python/collateral/__main__.py
@@ -66,12 +66,18 @@ cp_dict = {
 }
 
 
-def run_collateral(cp, fund, positions, workdate, engine):
+def run_collateral(cp, fund, positions, positions_rates, workdate, engine):
     cp_mod = import_module("." + cp, "collateral")
     lookback = 0
     while lookback < 2:
         try:
-            return cp_mod.collateral(workdate, positions, engine=engine, fund=fund)
+            return cp_mod.collateral(
+                workdate,
+                positions,
+                engine=engine,
+                fund=fund,
+                positions_irs=positions_rates,
+            )
         except FileNotFoundError as e:
             logger.warning(e)
             lookback += 1
@@ -99,12 +105,20 @@ for fund in ("Serenitas", "Brinker", "BowdSt"):
             index_col=["security_id", "maturity"],
             parse_dates=["maturity"],
         )
+        positions_rates = pd.read_sql_query(
+            "SELECT cleared_trade_id, notional, effective_date, maturity_date, payreceive, fixed_rate, folder, currency "
+            "FROM irs",
+            dawn_engine,
+            index_col=["cleared_trade_id"],
+            parse_dates=["effective_date", "maturity_date"],
+        )
         df[(fund, fcm.upper())] = run_collateral(
-            fcm, fund, positions, workdate, dawn_engine
+            fcm, fund, positions, positions_rates, workdate, dawn_engine
         )
+
     for cp in cp_dict[fund]["isda_cps"]:
         df[(fund, cp.upper())] = run_collateral(
-            cp, fund, bilat_positions, workdate, dawn_engine
+            cp, fund, bilat_positions, None, workdate, dawn_engine
         )
 
 df = pd.concat(df, names=["fund", "broker", "strategy"]).reset_index()
diff --git a/python/collateral/baml_fcm.py b/python/collateral/baml_fcm.py
index c7c892a4..6847eb93 100644
--- a/python/collateral/baml_fcm.py
+++ b/python/collateral/baml_fcm.py
@@ -1,5 +1,5 @@
 from . import DAILY_DIR, SftpClient
-from .common import compare_notionals, STRATEGY_CASH_MAPPING
+from .common import compare_notionals, compare_notionals_rates, STRATEGY_CASH_MAPPING
 import pandas as pd
 from sqlalchemy.exc import IntegrityError
 
@@ -11,12 +11,21 @@ def download_files(*args, fund="Serenitas", **kwargs):
     sftp.download_files("outgoing", DAILY_DIR / fund / "BAML_reports")
 
 
-def collateral(d, positions, *, engine, fund="Serenitas", **kwargs):
-    df = pd.read_csv(
+def load_csv(file_type, fund, d, **kwargs):
+    return pd.read_csv(
         DAILY_DIR
         / fund
         / "BAML_reports"
-        / f"OTC_Open_Positions_-_Credit_-_LMCG_{d:%Y%m%d}.CSV",
+        / f"OTC_Open_Positions_-_{file_type}_-_LMCG_{d:%Y%m%d}.CSV",
+        **kwargs,
+    )
+
+
+def collateral(d, positions, *, engine, fund="Serenitas", positions_irs, **kwargs):
+    df = load_csv(
+        "Credit",
+        fund,
+        d,
         usecols=[
             "MTM",
             "ACCRUEDCPN",
@@ -60,6 +69,33 @@ def collateral(d, positions, *, engine, fund="Serenitas", **kwargs):
         .reset_index(["folder", "currency"])
     )
     df = df.rename(columns={"folder": "Strategy", "currency": "Currency"})
+    df_rates = load_csv(
+        "Rates",
+        fund,
+        d,
+        usecols=[
+            "COBDATE",
+            "CLEAREDTRADEID",
+            "FIXEDRATE",
+            "NPV",
+            "DIRECTION",
+            "NOTIONAL",
+            "EFFDATE",
+            "MATDATE",
+        ],
+        index_col=["CLEAREDTRADEID"],
+        parse_dates=["MATDATE", "EFFDATE"],
+    )
+    compare_notionals_rates(df_rates, positions_irs, "BAML")
+    positions_irs["Amount"] = df_rates.reindex(positions_irs.index)["NPV"]
+    positions_irs.folder.replace(STRATEGY_CASH_MAPPING, inplace=True)
+    df_rates = (
+        positions_irs.groupby(["folder", "currency"])
+        .agg({"Amount": "sum"})
+        .reset_index(["folder", "currency"])
+    )
+    df_rates = df_rates.rename(columns={"folder": "Strategy", "currency": "Currency"})
+
     col_names = [
         "Statement Date",
         "AT",
@@ -105,5 +141,11 @@ def collateral(d, positions, *, engine, fund="Serenitas", **kwargs):
             )
     except IntegrityError:
         pass
+    df = pd.concat([df, df_rates])
+    df = (
+        df.groupby(["Strategy", "Currency"])
+        .agg({"Amount": "sum"})
+        .reset_index(["Strategy", "Currency"])
+    )
     df["date"] = d
     return df.set_index("Strategy")
diff --git a/python/collateral/common.py b/python/collateral/common.py
index 00b8c8e2..747ffb43 100644
--- a/python/collateral/common.py
+++ b/python/collateral/common.py
@@ -57,6 +57,23 @@ def compare_notionals(df: pd.DataFrame, positions: pd.DataFrame, fcm: str) -> No
             )
 
 
+def compare_notionals_rates(
+    df: pd.DataFrame, positions: pd.DataFrame, fcm: str
+) -> None:
+    check_notionals = positions.join(df["NOTIONAL"], how="left")
+    diff_notionals = check_notionals[
+        (check_notionals.notional != check_notionals.NOTIONAL)
+        & (check_notionals.notional != 0.0)
+    ]
+    if not diff_notionals.empty:
+
+        logger.error(f"Database and {fcm} FCM know different notionals")
+        for t in diff_notionals.itertuples():
+            logger.error(
+                f"{t.Index[0]}\t{t.Index[1]:%Y-%m-%d}\t{t.notional}\t{t.NOTIONAL}"
+            )
+
+
 def get_bilateral_trades(d: datetime.date, fund: str, engine: Engine) -> pd.DataFrame:
     df_cds = pd.read_sql_query(
         "SELECT cpty_id, folder, initial_margin_percentage * abs(notional) / 100 as IA "