Decisions in today?s demanding business environment often require participation of a group of decision makers. Although decision complexity increases by the number of the participating decision makers, in many cases it is necessary to combine experts? knowledge to minimize risk. Banking sector is a domain where decision makers face decision problems and need appropriate methodologies and tools to support them. However, complexity in tools and methodologies directs them to follow less structured methodologies, mostly heuristic based. Considering the above issues, we present our approach towards a Group Decision Support System, which utilizes muliticirteria analysis and multiagent modeling, and is oriented towards sorting decisions in the financial sector.