Personalizing Actions in Context for Risk Management Using Semantic Web Technologies View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2017-10-04

AUTHORS

Jiewen Wu , Freddy Lécué , Christophe Gueret , Jer Hayes , Sara van de Moosdijk , Gemma Gallagher , Peter McCanney , Eugene Eichelberger

ABSTRACT

The process of managing risks of client contracts is manual and resource-consuming, particularly so for Fortune 500 companies. As an example, Accenture assesses the risk of eighty thousand contracts every year. For each contract, different types of data will be consolidated from many sources and used to compute its risk tier. For high-risk tier contracts, a Quality Assurance Director (QAD) is assigned to mitigate or even prevent the risk. The QAD gathers and selects the recommended actions during regular portfolio review meetings to enable leadership to take the appropriate actions. In this paper, we propose to automatically personalize and contextualize actions to improve the efficacy. Our approach integrates enterprise and external data into a knowledge graph and interprets actions based on QADs’ profiles through semantic reasoning over this knowledge graph. User studies showed that QADs could efficiently select actions that better mitigate the risk than the existing approach. More... »

PAGES

367-383

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-68204-4_32

DOI

http://dx.doi.org/10.1007/978-3-319-68204-4_32

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1092091875


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