دانلود رایگان مقاله مبارزه با پولشویی با تکنولوژی: انگلستان

abstract

Article history: Received 4 December 2016 Received in revised form 29 October 2017 Accepted 21 November 2017 Available online 2 December 2017 This paper presents a longitudinal interpretive case study of a UK bank's efforts to combat Money Laundering (ML) by expanding the scope of its profiling of ML behaviour. The concept of structural coupling, taken from systems theory, is used to reflect on the bank's approach to theorize about the nature of ML-profiling. The paper offers a practical contribution by laying a path towards the improvement of money laundering detection in an organizational context while a set of evaluation measures is extracted from the case study. Generalizing from the case of the bank, the paper presents a systems-oriented conceptual framework for ML monitoring.

5. Discussion

5.1. Implications for practice & contributions

Abstracting from the case, we can look to implications for institutions that try to improve in their handling of AML. One important aspect is that the (AML) system, in its efforts to reduce the complexity of the environment, is forced to succumb to a default two-step reduction of environmental complexity. The first step involves complexity reduction via technology: data from the environment are internalized by the system, which trigger algorithms based on what phenomenon is being modeled. The second step is a follow-up complexity-reduction by human activity systems. As shown in Table 1, the (AML) system develops three types of structural couplings for TPR improvements: i) internal (between itself as a subsystem of the bank and other departments like marketing), ii) selfreferential (with AML recursive explorations like that in phase 3 – step 1), iii) classic/external types of structural couplings with the environment of the bank. These should not be thought of as distinct but as intertwined, affecting ML modeling efforts in complex ways. They are depicted in the conceptual model as [A], [B], and [C].