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Several recent surveys show that more than 80% of consumers prefer spending with a card over cash. Thanks to advances in AI/ML card fraud can be detected extremely fast, making credit cards one of the safest and easiest payment methods to use. The challenge with cards, is that in some countries when fraud is suspected the credit card is blocked immediately, leaving the cardholder without a reason as to why, how or when. Depending on the situation it can take anywhere from a few hours to days until the customer is notified and even longer to resolve.

Using Amazon Connect a cardholder can be notified immediately of a suspected card fraud and interactively verify if the suspected transactions were indeed fraudulent over the phone or via SMS. Amazon Connect enables an event-based reaction providing the ability to contact the cardholder directly either via phone or SMS without the need for an agent-in-the-loop. This makes for an extremely cost effective and near frictionless cardholder experience.

This post shows you how to build, train and deploy a fraud detection model and rules using Amazon Fraud Detector and integrate predictions with Amazon Connect in order to connect with customers in real-time. Amazon Fraud Detector is a fully managed service that uses machine learning (ML) and more than 20 years of fraud detection expertise from Amazon, to identify potentially fraudulent activity so customers can catch more online fraud faster. Amazon Connect is an omnichannel cloud contact center that helps you provide superior customer service at a lower cost.

You will find the blog here:

See CONTRIBUTING for more information.

This library is licensed under the MIT-0 License. See the LICENSE file.