This post was cowritten by Ziv Pollak, Machine Learning Team Lead, and Sarvi Loloei, Machine Learning Engineer at Clearly. The content and opinions in this post are those of the third-party authors and AWS is not responsible for the content or accuracy of this post. A pioneer in online shopping, Clearly launched their first site in 2000. Since then, we've grown to become one of the biggest online eyewear retailers in the world, providing customers across Canada, the US, Australia, and New Zealand with glasses, sunglasses, contact lenses, and other eye health products. Through its mission to eliminate poor vision, Clearly strives to make eyewear affordable and accessible for everyone.

Service providers from almost every industry are in the race to feature the best user experience for their online channels like web portals and mobile applications. This raises a new challenge. How do we stop illegal and fraudulent behaviors without impacting typical legitimate interactions? This challenge is even greater for organizations that offer paid services. These organizations need to validate payment transactions against fraudulent behaviors in their customer-facing applications. Although subsequent checks are performed by financial entities such as card networks and banks that run the payment transaction, the service providers remain responsible for the end-to-end payment process.

Several recent surveys show that more than 80% of consumers prefer spending with a credit card over cash. Thanks to advances in AI and machine learning (ML), credit card fraud can be detected quickly, which makes credit cards one of the safest and easiest payment methods to use. The challenge with cards, however, is that in some countries when fraud is suspected the credit card is blocked immediately, which leaves 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. With 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.

Amazon Fraud Detector is a fully managed service that makes it easy to identify potentially fraudulent online activities, such as the creation of fake accounts or online payment fraud. Unlike general-purpose machine learning (ML) packages, Amazon Fraud Detector is designed specifically to detect fraud. Amazon Fraud Detector combines your data, the latest in ML science, and more than 20 years of fraud detection experience from Amazon.com and AWS to build ML models tailor-made to detect fraud in your business. After you train a fraud detection model that is customized to your business, you create rules to interpret the model's outputs and create a detector to contain both the model and rules. You can then evaluate online activities for fraud in real time by calling your detector through the GetEventPrediction API and passing details about a single event in each request.

With less than a week to re:Invent 2020, we are feeling the excitement and thrill, and looking forward to seeing you all at the world's premier cloud learning event. As always, artificial intelligence (AI) and machine learning (ML) continue to be on the list of top topics with our customers and partners. We're making it bigger and better this year with the first ever machine learning keynote, over 50 technical breakout sessions, live racing with the AWS DeepRacer League, and more. You'll hear from AWS experts as well as many of our customers including NASCAR, Intuit, McDonalds, Mobileye, NFL, Siemens Energy, and many others, across industries such as sports, finance, retail, autonomous vehicles, manufacturing, and more. To help you plan your agenda for the extravaganza, here are a few highlights from the artificial intelligence and machine learning track at re:Invent 2020.

Online fraud is estimated to be costing businesses more than £3billion a year, according to the FBI's Internet Crime Report 2019. Excluding the United States, the United Kingdom is by far the worst affected country by number of victims. At Inawisdom, our post-fraud analyses have identified several patterns. The most common include using a common IP address or similar data in fraudulent accounts, such as email domains. In other cases, fraudsters fake the entered country, residential status, or work status when applying for accounts.

Amazon Web Services (AWS) has announced the general availability of Fraud Detector, a machine learning-powered service that helps organisations to tackle fraudulent activity. First launched at Amazon Re:invent last December, Fraud Detector uses the same technology that Amazon employs to fight fraudulent activity on its e-commerce marketplace. The tool requires no machine learning expertise, according to AWS, with Fraud Detector providing a selection of ready-made fraud detection AI templates that cover different use cases. To train their model, organisations simply upload historical data covering both fraudulent and legitimate transactions to AWS S3. Businesses with more advanced requirements can use their own models with the service using an integration with SageMaker, Amazon's managed AI platform.

Web services platform GoDaddy, payments products maker Truevo, and software maker ActiveCampaign are already among the customers and partners using Amazon Fraud Detector. Amazon Fraud Detector, a fully managed service, automatically identifies potentially fraudulent activity in milliseconds with no machine learning expertise required. AWS uses the same technology used by Amazon.com Amazon says businesses just need a few clicks in the Amazon Fraud Detector console to initiate a fraud investigation when the machine learning model predicts potentially fraudulent activity. While using Amazon Fraud Detector, customers use their historical data of both fraudulent and legitimate transactions to build, train, and deploy machine learning models that provide real-time, low-latency fraud risk predictions.

Using machine learning under the hood and based on over 20 years of fraud detection expertise from Amazon, Amazon Fraud Detector automatically …

Amazon Fraud Detector is a fully managed service that makes it easy to identify potentially fraudulent online activities such as online payment fraud and the creation of fake accounts. Globally each year, tens of billions of dollars are lost to online fraud. Companies conducting business online are especially prone to attacks from bad actors who often exploit different tactics such as creating fake accounts and making payments with stolen credit cards. Companies typically use fraud detection applications to identify fraudsters and stop them before they cause costly business disruptions. However, these applications often rely on business rules that don't keep up with the changing behaviors of fraudsters. More recent fraud detection applications have tried to use machine learning.