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Money Laundering Research Related to Technology Restructuring Transactional Data for Link Analysis in the FinCEN AI System Due to the nature and costs of data collection, many realworld databases consist of large numbers of independent transactions. Finding evidence of structured groups of entities reflected in this data is a task aptly suited to Link Analysis. However, the databases usually must be restructured to allow effective search and analysis of the linkage structures hidden in the original transactions. The FinCEN AI System (FAIS) is an example of such an application. We briefly discuss the process of database restructuring and show how it is used to support the discovery and analysis of evidence of money laundering in a database of cash transactions. Henry G. Goldberg
Applying Data Mining in Investigating Money Laundering In this paper, we study the problem of applying data mining to facilitate the investigation of money laundering crimes (MLCs). We have identified a new paradigm of problems --- that of automatic community generation based on uni-party data, the data in which there is no direct or explicit link information available. Consequently, we have proposed a new methodology for Link Discovery based on Correlation Analysis (LDCA). Zhongfei (Mark) Zhang
Tracking Dirty Proceeds: Exploring Data Mining Technologies As Tools To Investigate Money Laundering Money laundering enforcement operations in the USA and abroad have developed in the past decade from the simple use of informant information to the sophisticated analysis of voluminous, complex financial transaction arrays. Traditional investigative techniques aimed at uncovering patterns consume numerous man-hours. The volume of these records and the complexity of the relationships call for innovative techniques that can aid financial investigators in generating timely, accurate leads. Data mining techniques are well suited for identifying trends and patterns in large data sets often comprised of hundreds or even thousands of complex hidden relationships. This paper explores the use of innovative data mining methodologies that could enhance law enforcement’s ability to detect, reduce, and prevent money laundering activities. This paper provides an overview of the money laundering problem in the USA and overseas and describes the nature and scope of the money laundering problems. It reviews traditional approaches to financial crime investigation and discusses various innovative data mining and artificial intelligence-based solutions that can assist financial investigators. R. C. Watkins
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