SANTA CLARA, California, Dec. 5, 2017
The DataVisor UML Solution anticipates potential threats with high accuracy and reduces additional attacks by up to 50%
SANTA CLARA, California, Dec. 5, 2017 /PRNewswire/ -- Based on its recent analysis of the fraud detection industry, Frost & Sullivan recognizes DataVisor with the 2017 Global Technology Innovation Award for its unique DataVisor Unsupervised Machine Learning (UML) Solution. It helps solve two important problems facing modern organizations: the explosion of fraud and the strong increase of fraud loss, and the high number of false positives and negatives in transaction monitoring for money laundering.
"Traditional fraud detection solutions and anti-money laundering (AML) transaction monitoring systems are built around a set of rules or supervised machine learning models that require frequent updates based on the changing nature of the attacks," said Jean-Noël Georges Global Program Director Digital Transformation Practice. "In contrast, DataVisor's UML Solution does not use historical data to derive patterns from, which allows it to find new attacks and reduces the need for constant updates."
The DataVisor UML Solution can provide a risk score for each account and account activity to facilitate effective intervention as needed. Furthermore, the solution is optimized to respond to constraints in real time and detect fraudulent or suspicious activity. It has the ability to anticipate potential threats and attacks with high accuracy, resulting in up to a 50% reduction in additional attacks. The innovative architecture of the product is based on two key components:
DataVisor created the UML Solution platform to be diverse and scalable in its applications, and was designed it to be data agnostic in order to support a wide range of case studies throughout various industries such as banking, eCommerce, social networking, and mobile gaming. The solution's detection services are also diverse, providing three main services for fraud (application fraud, account takeover fraud, and transaction fraud) and two main services for AML transaction monitoring systems (reducing false positives and false negatives). Frost & Sullivan notes that the diversity and flexibility of the platform truly sets it apart from the competition.
"The platform is based on an established technology stack, including Hadoop, Apache Spark, and Elasticsearch. By taking a partnership approach with technology leaders, DataVisor is aligned with the latest technology evolutions regarding Big Data and machine learning, positioning its solution well to handle future needs and challenges," said Georges.
Each year, Frost & Sullivan presents this award to the company that has developed a product with innovative features and functionality that is gaining rapid acceptance in the market. The award recognizes the quality of the solution and the customer value enhancements it enables.
Frost & Sullivan Best Practices awards recognize companies in a variety of regional and global markets for demonstrating outstanding achievement and superior performance in areas such as leadership, technological innovation, customer service, and strategic product development. Industry analysts compare market participants and measure performance through in-depth interviews, analysis, and extensive secondary research to identify best practices in the industry.
DataVisor provides the most advanced fraud detection and anti-money laundering solution designed to uncover unknown attacks. DataVisor enhances existing financial fraud detection and anti-money laundering systems by providing a DataVisor Score based on a combination of an Unsupervised Machine Learning (UML) algorithm and intelligence derived from the Global Intelligence Network (GIN). To date, DataVisor has processed over 600 billion events, detected 100M+ bad accounts, and protected over 2 billion user accounts from some of the largest financial institutions and online services in the world. For more information, visit www.datavisor.com.
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