Communications of the ACM
Knowledge engineering: principles and methods
Data & Knowledge Engineering - Special jubilee issue: DKE 25
Business Modeling With UML: Business Patterns at Work
Business Modeling With UML: Business Patterns at Work
Introduction to Multiagent Systems
Introduction to Multiagent Systems
Brain Meets Brawn: Why Grid and Agents Need Each Other
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Web services negotiation in an insurance grid
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
SOA for Profit, A Manager's Guide to Success with Service Oriented Architecture
SOA for Profit, A Manager's Guide to Success with Service Oriented Architecture
Ontologies for supporting negotiation in e-commerce
Engineering Applications of Artificial Intelligence
An overview of S-OGSA: A Reference Semantic Grid Architecture
Web Semantics: Science, Services and Agents on the World Wide Web
Securing business processes using security risk-oriented patterns
Computer Standards & Interfaces
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In this work we present two business templates able to decrease risk and decrease costs in the insurance market realizing a successful claim management process capable of going across company boundaries. Risks can be decreased by having fraud detection agents gather evidence for (possible) fraud chains, using ontologies that model knowledge about the various types of frauds, and the mappings between different back-offices of involved parties. Costs can be decreased by having agents dealing with the administrative process of claim handling, saving time and personnel costs. Another advantage is that these agents form an agent mediated marketplace where prices and quality for car repair are determined by market mechanisms, instead of long-term contracts. The fraud detection and car repair business templates are implemented in an InsuranceGrid combining grid, ontology and agent technology. Because of the need for autonomy and the complexity of decision making process underlying fraud detection, the InsuranceGrid was implemented as a multi-agent system. By using ontologies, the knowledge about the insurance domain and processes is explicitly represented, making the obtained model transparent, standardised and maintainable. Business decision makers from insurance companies recognize the business template with their opportunities to delegate claims handling tasks to business agents.