analytics throughout an organisation ’ s decision layers .
This enables insurers to implement two different types of decisioning : 1 ) automated , wherein analytics is embedded in the background of operational processes to drive decisions at scale , with limited human intervention and at the point where they provide the most value ; and 2 ) augmented , which integrates analytical insights into the user experience to support human decision making at an insurer , such as chat applications or interactive charts .
Q : Which background technologies enable the SAS analytics platform ?
A : Firstly , SAS ’ data management capabilities control data quality , governance and integration to enable an insurer to exploit a wide range of new data sources . All data is now Big Data , and IoT presents a great case in point . As insurers look to support connected cars , property and people , SAS can bring its deep IoT processing experience to deliver solutions for streaming data and analytics on the edge .
Next , understanding and leveraging Big Data requires solid capabilities in advanced analytics , principally : predictive modelling , AI ( including image processing and natural language processing ) and machine learning . SAS
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