Authors:
Cláudio Alexandre
and
João Balsa
Affiliation:
Universidade de Lisboa, Portugal
Keyword(s):
Multiagent Systems, Intelligent Agents, Money Laundering.
Related
Ontology
Subjects/Areas/Topics:
Agent Models and Architectures
;
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Distributed and Mobile Software Systems
;
Enterprise Information Systems
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Multi-Agent Systems
;
Software Engineering
;
Symbolic Systems
Abstract:
The huge amount of bank operations that occur every day makes it extremely hard for financial institutions to
spot malicious money laundering related operations. Although some predefined heuristics are used they aren’t
restrictive enough, still leaving to much work for human analyzers. This motivates the need for intelligent
systems that can help financial institutions fight money laundering in a diversity of ways, such as: intelligent
filtering of bank operations, intelligent analysis of suspicious operations, learning of new detection and analysis
rules. In this paper, we present a multiagent based approach to deal with the problem of money laundering
by defining a multiagent system designed to help financial institutions in this task, helping them to deal with
two main problems: volume and rule improvement. We define the agent architecture, and characterize the
different types of agents, considering the distinct roles they play in the process.