A0175
Title: Culture "profiling", AI and AML: Efficacy vs ethics
Authors: Parvati Neelakantan - Indian Institute of Technology Kanpur (India) [presenting]
Abstract: Using extensive transaction and money laundering detection data at a globally important financial institution, the efficacy of including aspects of national culture is investigated in formulating anti-money laundering predictions. For corporate and individual accounts, Hofstede individualism scores of the country in which a customer is resident or from which a wire is sent/received are of first-order importance. When combined with account and transaction data, as well as even a proprietary institutional algorithm, individualism scores continue to determine the models' predictive performances. The efficacy finding of profiling in AML compliance underscores the need for stringent and enforced data protection safeguards, which can serve to ensure an individual's fundamental right to privacy.
