Identification of individualization techniques for criminal records in sanction lists

Abstract

Using efficient searching techniques on sanctions lists and press articles allows a better filtering on individuals and entities to establish a commercial relationship with, including those who are going to have access to confidential information belonging to the company, in order to minimize the risk of leakage or information mismanagement. That process of filtering on individuals or entities could be automated by using individualization algorithms, searching techniques based on string comparisons, artificial intelligence, and facial recognition. Diverse methods were examined to be applied on each mentioned technique in order to identify which ones are ideal to its application on individualization due to their characteristics, in order to obtain agile and reliable results; taking into account that different methods are complementary and not exclusive, and that their combination allows to minimize human interaction in the classification of information, avoiding analysis of irrelevant data for that particular search.