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AWS Announces Five New Machine Learning Services That Reinvent and Improve Everyday Enterprise Tasks – With No Machine Learning Experience Required


AWS introduced new services that use AI to allow more developers to apply machine learning to create better end user experiences, including new machine learning-powered enterprise search, code reviews and profiling, fraud detection, medical transcription, and human review of AI predictions. Machine learning continues to grow at a rapid clip, and today there are tens of thousands of customers doing machine learning on AWS (twice as many as the next largest cloud provider), including many customers that opt to use AWS's fully managed AI Services like Alfresco, Bayer Crop Science, Cerner, CJ Cox Automotive, C-SPAN, Deloitte, Domino's, Emirates NBD, Fred Hutchinson Cancer Research Center, FICO, FINRA, Gallup, Kelley Blue Book, Kia, Mainichi Newspapers Co, NASA, PricewaterhouseCoopers, White House Historical Association, and Zola. In the past year, AWS has introduced several new fully managed AI Services like Amazon Personalize and Amazon Forecast that allow customers to benefit from the same personalization and forecasting machine learning technology used by Amazon's consumer business to power its award-winning customer experiences. AWS customers are interested in learning from Amazon's vast experience using machine learning at scale to improve operations and deliver better customer experiences, without needing to train, tune, and deploy their own custom machine learning models. Today, AWS is announcing five new AI services that build upon Amazon's rich experience with machine learning, and allow organizations of all sizes across all industries to adopt machine learning in their enterprises – with no machine learning experience required. Despite many attempts over many years, internal search remains a vexing problem for today's enterprises, and most employees still frequently struggle to find the information they need. Organizations have vast amounts of unstructured text data, much of it incredibly useful if it can be discovered, stored in many formats and spread across different data sources (e.g.

Build and visualize a real-time fraud prevention system using Amazon Fraud Detector


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.

Amazon Fraud Detector now generally available


Amazon Web Services (AWS) has announced the general availability of its machine learning-based fraud detection service. Amazon Fraud Detector is a fully managed service touted as making it easy to quickly identify potentially fraudulent online activities, such as online payment and identity fraud, the creation of fake accounts, and loyalty account and promotion code abuse "in milliseconds". To use the service, customers can select a pre-built machine learning model template; upload historical event data of both fraudulent and legitimate transactions to build, train, and deploy machine learning models; and create decision logic to assign outcomes to the predictions. "Customers of all sizes and across all industries have told us they spend a lot of time and effort trying to decrease the amount of fraud occurring on their websites and applications," Amazon machine learning VP Swami Sivasubramanian said. "By leveraging 20 years of experience detecting fraud coupled with powerful machine learning technology, we're excited to bring customers Amazon Fraud Detector so they can automatically detect potential fraud, save time and money, and improve customer experiences -- with no machine learning experience required."

Amazon Fraud Detector Can Accelerate How AI is Embedded in Your Business


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.

Event-based fraud detection with direct customer calls using Amazon Connect


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.