How to Build A Fraud Detection Solution

How to Build A Fraud Detection Solution

How to build a serverless real-time credit card fraud detection solution. We developed a smart analytics design pattern that enables you to build a scalable real-time fraud detection solution in one hour using serverless, no-ops products on Google Cloud.

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. In collaboration with Quantiphi, an award-winning Google Cloud Premier Partner with  experience engaging with global financial institutions, we developed a smart analytics design pattern that enables you to build a scalable real-time fraud detection solution in one hour using serverless, no-ops products on Google Cloud. In addition to setting up fraud notifications, we also show how you can build dashboards to monitor the performance of the fraud detection pipeline.

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Check out the dashboard here

Because all of the Google Cloud products used in this solution are serverless and fully managed, this means you won't need to spend time setting up and maintaining infrastructure, enabling you to focus on getting the solution up and running in an hour. This blog post will be a technical dive into how the solution works: 

  1. Preparing the data on BigQuery
  2. building the fraud detection model using BigQuery ML
  3. hosting the BigQuery ML model on AI Platform to make online predictions on streaming data using Dataflow
  4. setting up alert-based fraud notifications using Pub/Sub
  5. creating operational dashboards for business stakeholders and the technical team using Data Studio

data analytics serverless

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