How to build a fraud detection solution

Description

Summary

• As businesses continue to shift toward online credit card payments, there is a rising need to have an effective fraud detection solution capable of real-time, actionable alerts.
• SELECT * FROM `qp-fraud-detection.cc_data.training_data` With data stored on BigQuery, it becomes easy to train machine learning models using BigQuery ML without needing to set up or procure infrastructure, saving time, money and complexity when productionizing the design pattern.
• In the case of credit card transactions, a Dataflow pipeline can ingest real-time data continuously and automatically scales based on the transaction volume without human involvement.. With the model working, we can now add this to the streaming Dataflow pipeline.
• First, instead of hosting the model on AI Platform, you can use a local version of the model saved on Dataflow workers and call it directly for prediction during the stream processing pipeline for each transaction, which can improve performance and reduce latency (documentation).