The Reliance on Artificial Intelligence
Measures to Curb Money Laundering
Practices in the South African Banking
Institutions and Real Estate Sector Cover Image

The Reliance on Artificial Intelligence Measures to Curb Money Laundering Practices in the South African Banking Institutions and Real Estate Sector
The Reliance on Artificial Intelligence Measures to Curb Money Laundering Practices in the South African Banking Institutions and Real Estate Sector

Author(s): Howard Chitimira
Subject(s): Commercial Law
Published by: Editura Universitară Danubius
Keywords: artificial intelligence; machine learning; money laundering; banks; automation;

Summary/Abstract: Money laundering includes any practice by which illicit perpetrators disguise the original ownership and control of their proceeds of criminal conduct by making them appear to have been derived from legitimate sources. Money laundering practices may give rise to poor market integrity and low public investor confidence in any country. Consequently, money laundering is outlawed in many countries, including South Africa. On the other hand, artificial intelligence (AI) could be defined as the simulation of human intelligence processes by computer systems and/or machines in order to learn or acquire certain information, reasoning and related rules, and/or applying such rules to reach approximate or definite conclusions and self-correction. Put differently, AI also involves the creation of intelligent machines that perform and react like humans. Accordingly, the article unpacks the flaws in the current South African anti-money laundering statutory regulatory framework. This done to, inter alia, recommend the use of artificial intelligence and other relevant measures to enhance the combating of money laundering in the South African banking and related financial institutions. In light of this, the author submits that South African banks should consider adopting artificial intelligence measures to detect and prevent the negative effects of money laundering in the banking sector, and related key sectors such as the real estate and financial markets sectors.

  • Issue Year: 16/2020
  • Issue No: 2
  • Page Range: 28-43
  • Page Count: 16
  • Language: English
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