Create train_model.py

train_model.py

@@ -0,0 +1,23 @@
+import pandas as pd
+from sklearn.ensemble import RandomForestClassifier
+import pickle
+
+# SME-Focused Dataset
+data = pd.DataFrame({
+    "amount": [500,12000,800,15000,300,20000,600,18000],
+    "hour": [14,2,13,1,15,3,16,0],
+    "new_customer": [0,1,0,1,0,1,0,1],
+    "refund_request": [0,0,1,1,0,1,0,1],
+    "location_mismatch": [0,1,0,1,0,1,0,1],
+    "fraud": [0,1,0,1,0,1,0,1]
+})
+
+X = data.drop("fraud", axis=1)
+y = data["fraud"]
+
+model = RandomForestClassifier(n_estimators=100)
+model.fit(X, y)
+
+pickle.dump(model, open("fraud_model.pkl", "wb"))
+
+print("SME Fraud Model Created Successfully!")