PORTLAND, OR--(Marketwired - Sep 20, 2016) - iovation, the leading provider of device-based solutions for authentication and fraud prevention, today announced the launch of iovationScore. The unprecedented scale of iovationScore's global device network along with its highly advanced use of adaptive algorithms make iovationScore the industry's most robust machine learning fraud detection solution. It provides businesses with the power to predict the trustworthiness or riskiness of an online transaction even if they have never seen the customer or device before. iovationScore helps businesses grow revenue by identifying good or trustworthy customers. In addition, it reduces friction for existing trustworthy customers by eliminating time consuming and frustrating step-up challenges. iovationScore also helps reduce fraud prevention costs by minimizing resource-intensive manual reviews and eliminating the need for expensive verification tools for trusted transactions. "Battling with fraudsters is like a game of chess. Once you think you have them figured out, they utilize a whole new approach," said iovation's Vice President of Product, Scott Olson. "It is essential that you have a machine learning weapon in your arsenal that continually and automatically adapts to changing conditions seen across companies and industries worldwide. Besides stopping fraud, that solution should provide an easy way to differentiate good from bad customers in order to offer the valued ones special incentives." "The launch of iovationScore contains 12 years of fraud behavior insight we have assimilated from 23 billion online transactions worldwide," said iovation's CTO Scott Waddell. "While machine learning is the real-time engine that powers iovationScore, the big data insights from our, collective history of transactions are the fuel that makes it so powerful right off the starting line." iovationScore's sophisticated analytics examine hundreds of behavioral, contextual, device and transactional attributes from billions of transactions worldwide. Its algorithms are trained by analyzing 30 million fraud records placed by iovation's network of over 3,500 fraud and security analysts. Some examples of what iovationScore analyzes include: Behavioral - How many transactions have occurred for a particular account in a certain period of time? Is there past evidence of fraud associated with the account or device and if so, how much and how recent?Contextual - Do all of the transaction location indicators (such as geolocation, ISP, cell tower, browser language, country, etc.) align with each other or do some indicate heightened risk? Device - Does the device exhibit evasive behavior or have other risk indicators, such as having been rooted or jailbroken?Transactional - Are there risk indicators within the transaction itself like significant time zone differences between the business and end user? iovationScore is available to select existing iovation customers today and will be more broadly available this November. More details about iovationScore are at iovation.com/iovationscore and iovation will be presenting the new service at its annual Fraud Force Summit being held Sept. 19-21 in Portland, Ore. About iovationiovation protects online businesses and their end users against fraud and abuse, and identifies trustworthy customers through a combination of advanced device identification, shared device reputation, multi-factor authentication and real-time machine-learning risk evaluation. More than 3,500 fraud managers representing global retail, financial services, insurance, social network, gaming and other companies leverage iovation's database of more than 3 billion Internet devices and the relationships between them to determine the level of risk associated with online transactions. The company's device reputation database is the world's largest, used to protect more than 16 million transactions and stop an average of 300,000 fraudulent activities every day. The world's foremost fraud experts share intelligence, cybercrime tips and online fraud prevention techniques in iovation's Fraud Force Community, an exclusive virtual crime-fighting network. For more information, visit iovation.com.
Computer security service iovation has launched machine learning , fraud detection system iovationScore . Based on big - data data , collected over 12 years from 1 billion international online transactions , iovationScore 's adaptive solutions aim to provide users with risk - assessment tools for online transactions . apple 's CTO Scott Waddell said the system would also help " reduce risk " for existing customers , and " minimise risk - intensive manual reviews . "