# models/fraud_detection_model.py
from tensorflow.keras.models import load_model

def load_fraud_detection_model(model_path):
    return load_model(model_path)

def predict_fraud(model, data):
    # Placeholder for model prediction logic
    # Replace with actual prediction logic
    return model.predict_classes(data)
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout

def build_model(input_dim):
    model = Sequential()
    model.add(Dense(64, input_dim=input_dim, activation='relu'))
    model.add(Dropout(0.5))
    model.add(Dense(1, activation='sigmoid'))
    model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
    return model