Paper Info
Title
Enterprise Risk Analytics: Automatic Analysis Of Risk Factors From Textual Feedbacks
Abstract
There has been a growing need to automatically identify, extract and analyze risk related statements from textual data. In this paper, we have exploited natural language processing research to develop a risk analytics framework that processes human-reported risk statements to analyzes the enterprise risk description texts to classify them into valid and invalid risk categories, and perform analytics to extract information from the text pertaining to the different categories of risks and their possible cause and impacts. A manual annotation study from management experts using risk descriptions collected for a specific organization was conducted to evaluate the framework. The evaluation showed promising results for automated risk analysis and identification.
Year
Venue
Field
2016
2016 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)
Data science,Enterprise risk management,Pragmatics,Risk analysis (business),Computer science,Manual annotation,Analytics
DocType
ISSN
Citations 
Conference
1062-922X
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Tirthankar Dasgupta17626.41
Lipika Dey247547.53