Fraud Detection: Random Forest Model - Deployment

We read the trained model, as well as the new transaction and applies the model to classify it. We use a Rule Engine node to apply a threshold. In case a transaction is classified as fraudulent the workflow sends an email to notify of a fraud.

This workflow demonstrates how we can use the trained Random Forest Model on new data by performing the following steps:

1. Read the model and new data

2. Apply the model on the new transaction

Read the model and new data

Apply the model on the new transaction