Quantitative parameters of anti-money laundering regulation

Abstract

Subject. As financial institutions carry out a huge number of transactions, the financial sector definitely needs to automate some control procedures, including anti-money laundering ones. The effectiveness of automated control measures directly depends on how adequately tasks for the software are written. The article examines the impact of macroeconomic indicators, such as GDP per capita, average wage, and the scale of the shadow economy in the G20 countries and in two of the CIS countries (Belarus and Tajikistan) on thresholds of the fixed limit of transaction (FLT), which is regulated with the anti-money laundering legislation, including the fixed limit of cash transaction (FLCT). Objectives. I investigate approaches to setting FLT (FLCT) in different countries and formulate my opinion on this issue. Methods. The methodological basis of the study was made up of empirical and logical constructions, statistical analysis, synthesis, systems approach. Results. I identified why FLT (FLCT) are denied. This happens due to lawmakers’ confidence in the effectively controlled financial sector, or the corruption pressure. The countries with FLT (FLCT) introduce and use them formally. The article presents the risk-based approach to measuring the FLCT based on the macroeconomic indicators (average annual wages, savings per capita). Conclusions and Relevance. The case of Russia shows that the inflation undermines the barrier function of FLT (FLCT), while the analytical division of financial intelligence has to handle more issues. The proposed approach will help reduce costs the financial system incurs to process financial information in order to counter money laundering.