SAS named as a Leader in AI-based text analytics by independent research firm
Finding insights in unstructured data befuddles many organizations, but overcoming the challenge is possible with next-generation analytics tools powered by artificial intelligence. SAS’ best-in-class analytics help businesses uncover these opportunities, and SAS has been named a Leader in The Forrester Wave™: AI-Based Text Analytics Platforms, Q2 2018. The report also noted SAS’ “comprehensive” visual user interface.
“Text analytics can help solve a number of complex business problems such as detecting fraud and assessing customer feedback,” said Mary Beth Ainsworth, AI and Language Analytics Strategist at SAS. “SAS gives organizations the power of natural language processing, machine learning and linguistic rules in a visual dashboard to reveal insights in their data.”
SAS® Visual Text Analytics uses intelligent algorithms and natural language processing (NLP) techniques to automatically extract relationships and patterns within unstructured data, thereby eliminating the need for manual analysis. The NLP tools help users in sentiment analysis, speech to text, natural language understanding and natural language generation. For example, accessing and analyzing otherwise untapped data through NLP has allowed financial institutions to improve the efficiency and accuracy of managing anti-money laundering (AML) investigations. When tedious tasks such as monitoring negative news or scanning trade documents for illicit activity are automated, investigators can be sure they are using a consistent risk-based approach. This allows users to understand which cases present the greatest risks, and then prioritize for investigation.
SAS earned top marks in the Forrester report in many sub-categories for current offering including: analytics, ease of use, mix of rules and machine learning, depth of functionality, and others.
The report states: “SAS’s brand speaks for itself as a leader in advanced analytics; as a result, SAS Visual Text Analytics comes with a number of machine learning models. Users can also leverage other capabilities of the platform, such as forecasting and optimization, to deliver predictive, prescriptive, and actionable analytics.”
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