Open AccessIdentification of individualization techniques for criminal records in sanction lists
Author(s) -
Gonzalo M Arias,
Pablo Peláez,
Fredy E. Hoyos
Publication year - 2019
Publication title -
international journal of power electronics and drive systems/international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2578
pISSN - 2722-256X
DOI - 10.11591/ijece.v9i5.pp3798-3803
Subject(s) - computer science , identification (biology) , confidentiality , order (exchange) , process (computing) , string (physics) , agile software development , data mining , artificial intelligence , computer security , software engineering , botany , physics , finance , quantum mechanics , economics , biology , operating system
Using efficient searching techniques on sanctions list 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 data irrelevant for that particular search.