Abstract
The anti-money laundering, combating the financing of terrorism and combating proliferation financing (AML/CFT/CPF shortened to AML/CFT for simpler terminology) regulations have altered the way businesses are conducted to ensure that they are not abused for money laundering, terrorism financing or proliferation financing (ML/TF/PF). In the financial services sector, client due diligence (CDD) is an important aspect of every financial system as it enables businesses to know all the information pertaining to their clients. This process which is also known as know your client (KYC) must be done using a risk-based approach. The risk-based approach entails identifying the category of clients that a financial institution has, the nature of the business relationship and the type of service or product required, as well as allocating the level of ML/TF/PF risk which the client or service or product will pose to the business. Such risk will then inform the level of due diligence which the financial institution needs to conduct, such as simplified or enhanced due diligence.
The AML/CFT regulations in this area are very specific and must be strictly observed as non-compliance has dire consequences for a financial institution hence making the whole process expensive and time consuming hence the need to find ways to make the process less consuming while complying with the regulations. Artificial intelligence (AI), a general-purpose technology, has been dubbed as the cornerstone of the fourth industrial revolution (4IR) and is being utilised by various businesses in various industry sectors. In the financial services sector AI has been shown to be used for AML/CFT. It can be used to conduct CDD at the onboarding stage and for transaction monitoring and has been shown to bring efficiency in banking processes such as account opening, verification of documents, picking up unusual transactions and finding new trends of laundering activities, thus taking the fight against ML/TF/PF to a new level. However, there are some negative consequences which may arise due to the use of AI, hence the need to find ways to resolve such issues to ensure that it works as a panacea to financial crimes and not as an enabler for criminals.
The research was conducted to interrogate the relationship between the risk-based approach to CDD for the purposes of combating ML/TF/PF and AI and the legal implications thereof. It was found that AI can be used in a risk-based approach to CDD and that it enhances efficiency in this regard hence leading to better compliance with
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AML/CFT legal obligations. However, care must be taken to ensure that the use of AI does not violate basic human rights hence the need to have regard to AI related ethics.
Key words
Money laundering, terrorism financing, proliferation financing, client due diligence, know your client, financial institutions, banks, artificial intelligence, risk-based approach, anti-money laundering, combating financing of terrorism, combating proliferation financing, financial inclusion, compliance, AI ethics.