The Financial Profile: A strategy to detect asset laundering

Abstract

This paper describes the way financial institutions and other economic sectors generate customer profiles as a tool to prevent and detect asset laundering. The process consists of gathering customer information along with their financial history in order to set profiles that - together with the features of each transaction and in accordance with what one expects from each group of customers - makes a comparison between the former and real and everyday transactions.

These means lie on statistical tools and data mining that allow us to forecast customer behavior based on their socioeconomic and demographic characteristics.

Detection of out-of-the-common transactions is not enough to prevent and detect asset laundering since it is necessary to commence a scientific-type investigation stage that includes financial institutions’ hypotheses, as they hold a key role in setting procedures to take.

From a technological point of view, the tools that support this task may be divided into two groups according to their main function: knowledge generation and alert generation.