train_model.py

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!")