Purpose -This paper aims to provide a macro analysis of the USA's anti-money laundering (AML) legislation. In examining the context and consequences of these regulations, a general determination can be made on the effectiveness of the current US AML legislation. The major AML regulations in the USA are covered under the Bank Secrecy Act, USA Patriot Act and the Office of Foreign Assets Control. It is difficult to determine what constitutes as implementation and maintenance of effective AML Compliance Programs because US federal AML requirements remain largely dynamic. This paper will provide some context to why certain major AML regulations were established as well as the reasoning behind their implementation. This paper will then attempt to determine the effectiveness of current AML regulations, particularly on the banking sector, by looking at several cases of alleged failure to maintain effective AML Compliance Programs. An examination will be conducted on HSBC's $1.9 billion settlement in 2012 to the US government, as HSBC failed to establish a reasonable AML program according to the US Department of Justice press releases. Design/methodology/approach -A brief description of major US AML regulations pertaining to the 2012 HSBC case is first made. Also, a look into the frequency of suspicious activity report (SAR) filings as well as initiated money laundering investigations is made. The paper critically analyzes the Financial Action Task Force (FATF)'s evaluation of US AML regulations. Findings -It is evident that the FATF held an accurate evaluation of US AML regulations being both very comprehensive and severely enforced. The main criticism is with the implementation of these regulations driving adverse economic and social effects. Financial institutions fear being charged with not having a proper AML program; this causes banks to be more inclined to inflate SARs as well as engage in financial exclusion. It is difficult to prevent these adverse effects, as they directly result from having strict and comprehensive AML legislation, which is necessary to prevent and detect money being laundered. Practical implications -A determination as to whether US AML regulations need strengthening or is too strict in that it causes adverse effects. Originality/value -A macro analysis of America's AML legislation is severely needed. Many papers on the issue lack a thorough description of the large-scale socio-economic effects of the AML programs of American financial institutions.
A macro perspective examining the general nature of AI implementations and how enforcement should be structured under the new frontier of AI technologies is severely needed. The paper critically analyzes real and potential ethical impacts of AI-enabled systems as well as the standard process regulators, researchers, and firms use to assess the risks of these technologies. Three real-world cases are detailed as each type of AI implementation highlights varying degrees of ethical impacts. The paper surveys whether the current September 2020 European Parliament standard titled "European framework on ethical aspects of artificial intelligence, robotics and related technologies" will handle all cases effectively. Future regulators enforcing principles must be able to discern how each AI implementation should be handled as it is evident that there is a spectrum of ethical applicability on the use-case level. The cases examined are in using AI to automate the mortgage application process, find matching attributes for trade reconciliation tasks, and optimizing order entries within trading algorithms. The focus of the cases provided is in the financial industry as firms in this sector, on average, spend the highest percentage of their total revenue on information technology projects. Though the EU framework is thorough in recommending an ex-ante approach, providing risk classifications, and detailing effective measures to mitigate harm from AI-enabled systems, it falls short in identifying certain macroeconomic harms caused by AI-enabled systems and tracking the applications responsible within complex, interlinked systems.
Background Anticipated to overhaul the structure of market risk teams, IT teams, and trading desks within banks by 2023, Basel III's Fundamental Review of the Trading Book requirements will also increase capital charges banks will incur globally. The case study focuses on describing what is needed with regards to the risk factor eligibility test (RFET) as well as for implementing a data pool to lower capital charges. By establishing a consortium of banks per region to implement a data pooling solution, participants can prove a wider breadth of modellable risk factors per asset class and use the Internal Models Approach (IMA) of valuing risk to lower capital charge requirements significantly. Case description First, a description on the historical context surrounding the Fundamental Review of the Trading Book rules and the business requirements needed to comply with the risk factor eligibility test is made. Then an examination is conducted on the innovative data pooling initiative implemented by CanDeal, TickSmith Corp., and the 6 largest Canadian banks to lower capital charge requirements under the Fundamental Review of the Trading Book. Discussion and evaluation A description is made on what types of data, expertise, and technology is needed to calculate for risk factor modellability. It is up to each firm to decide if the benefits to using the Internal Models Approach to lower capital charges outweighs implementation and running costs of the underlying data platform. Implementing a data pool for each region comes with challenges that include anti-competition law that may block the initiative, varied benefits to each competitive participant, and data security concerns. Conclusion It is evident that the data pool innovation provides benefits to lowering capital charges as the Canadian banks have seen an increase of modellability by several factors using the sample bond asset class. While each firm must still determine internally if the benefits outweighs the technological costs they will incur, it is clear that regulators are pushing for increased data retention and scrutiny.
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