AWS Launches Fraud Detector To Automate AI

AWS continued their course towards world domination today when they launched Fraud Detector – a solution that combines automated customized model creation with realtime use of that model for future transactions. This is useable AI delivered to prevent fraud in realtime.

The solution appears to fully automate all the steps of machine learning to deliver a customized deployable model in minutes versus weeks or even months.

The solution appears to have some easy steps to follow to use machine learning models very simply.

Amazon claims the new service will offer merchants and retailers the ability to:

  • Stop Try Before You Buy Fraud – Identify accounts that are more likely to abuse ‘Try Before You Buy’ programs such as fashion services that ship clothing and accessories for you to explore before sending payment.
  • Stop New Account Fraud – Accurately distinguish between legitimate and high-risk customer account registrations so that you can selectively introduce additional steps or checks based on risk. For example, you can set up your customer account registration workflow to require additional email and phone verification steps only for account registrations that exhibit high-risk characteristics.
  • Stop Guest Checkout Fraud – Spot potential fraudsters even among customers without a history of transactions. Customers who transact regularly typically use a registered account. As a result, you have a history of transactions which makes it easier to identify potential fraud. Guest checkout, on the other hand, has no historical account usage or user behavior data which makes fraud detection much harder. With Amazon Fraud Detector, you can send as little as an email and IP address from a guest checkout order to assess its potential fraud risk so you can decide whether to accept it, review it, or collect more customer details. 

Amazon claims that their Fraud Detector’s machine learning models can identify up to 80% more potential bad actors than traditional methods. 

They have identified 2 customers that are currently using the service – Vacasa (the largest full-service vacation rental management company in North America, with more than 23,000 vacation homes in 17 countries serving over 2 million guests per year) and Charles Schwab (a leading investment firm).

Rule Writing and Case Management

The solution goes a step further than just machine learning and provides a rule-writing function that can be used in combination with the scores as well as a case management list function to review transactions that fit the score or rule criteria

This looks like a pretty good advancement for AWS which is already being used by tens of thousands of data scientists and analysts globally to fight fraud.

Frank McKenna is the Chief Fraud Strategist for PointPredictive and a Fraud Consultant based in San Diego California