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The purpose of this paper is to utilise underused information in anti-money laundering rating data to assist policymaking and research.

This paper explores what evidence “hidden in plain sight” in official anti-money laundering rating data reveals about claims justifying the expansion of money laundering controls in response to European bank scandals.

A perceived lack of international coordination influencing the policy response to a series of alleged anti-money laundering breaches does not accord with the anti-money laundering industry’s own evidence base.

Responding to new crises with superficial solutions without addressing fundamental questions with a multi-disciplinary perspective risks repeating and extending a decade-long cycle of ineffectiveness in efforts to mitigate the social and economic harms from profit-motivated crime.

This paper draws fresh conclusions from the anti-money laundering industry’s “main” data set, underused in policymaking and research.

This paper aims to increase the transparency of information in official anti-money laundering rating data to assist evidence-informed decision-making in compliance, policy-making and research.

This paper converts anti-money laundering rating data into information-rich visualisations, reintroduces a comparison methodology and ranks all anti-money laundering regimes evaluated to date.

Official anti-money laundering ratings as currently structured and presented offer surprisingly little policy-relevant information. Persistent failure to transform available data into information for knowledge and insight suggests that the risk has been realised that impressionistic judgments or politicised interests drive the policy agenda at least as much as objective evidence or substantive economic and social goals.

Any reluctance to generate policy-relevant information from the industry’s primary data set or disinclination to engage constructively with a growing body of independent critical policy effectiveness evidence calls into question whether implementing anti-money laundering controls with some prospect of achieving substantial societal benefits, or perpetuating the current system, prevails.

With a dearth of scholarship at the intersection of money laundering and policy effectiveness scholarship and practice, this paper combines elements of these disciplines and examines anti-money laundering effectiveness from a different viewpoint. Rather than seeking to measure money laundering or estimate the proportion of criminal proceeds successfully intercepted, this paper draws directly from the anti-money laundering industry’s own “main” data set.

The purpose of this paper is to advance debate and prompt new strategies substantially to improve the capacity to disrupt serious profit-motivated crime.

Using interdiction rates (the proportion of criminal funds seized or forfeited) as an interim proxy effectiveness indicator, this article challenges elements of the dominant anti-money laundering/counter-financing of terrorism (AML/CFT) narrative, and reflects on policy effectiveness and outcomes.

Interdiction rates in jurisdictions surveyed hardly constitute a rounding error in the accounts of profit motivated criminal enterprises. The current AML/CFT model appears almost completely ineffective in disrupting illicit finances and serious crime.

With such research at an early stage, some data are poorly substantiated and methodological inconsistencies rife.

For policy interventions with a reasonable prospect for crime not to pay, beyond rhetoric, frank evaluation of results and a potential step-change in policy, regulatory and enforcement vision and capability, may be required.

Scholars have exposed a paucity of meaningful links between AML/CFT controls and crime and terrorism prevention, yet the dominant narrative persists largely unchecked. This paper examines components of that narrative in the context of scholarship on “bullshit”.

This article aims to constructively critique the new global methodology for evaluating the effectiveness of anti-money laundering regimes against defined outcomes.

With surprisingly little discussion at the intersection of the money laundering and policy effectiveness and outcomes scholarship and practice, this article combines elements of these disciplines and recent peer-review evaluations, to qualitatively assess the Financial Action Task Force’s (FATF’s) anti-money laundering “effectiveness” methodology.

FATF’s “effectiveness” methodology does not yet reflect an outcome-oriented framework as it purports. Misapplication of outcome labels to outputs and activities miss an opportunity to evaluate outcomes, as the impact and effect of anti-money laundering policies.

If the “outcomes” of the “effectiveness” framework do not match the crime and terrorism prevention policy goals of nation states, the new “main” component for assessing the effectiveness of anti-money laundering regimes potentially detracts focus and resources from, rather than towards, intended policy objectives.

There is a dearth of scholarship whether the global anti-money laundering “effectiveness” framework is sufficiently robust to assess effectiveness as it purports. This article begins addressing that gap.

Money laundering and terrorism financing use the banking sector system illegally and result in enormous losses for the state and nation. Regulatory Technology (RegTech) is an important part of effectively preventing money laundering and terrorism financing. However, the implementation of RegTech related to the prevention of money laundering and terrorist financing, especially in the Indonesian banking sector, has not been widely studied and discussed. Therefore, this study aims to provide empirical testing evidence regarding the effectiveness of RegTech implementation in the Indonesian banking sector to prevent money laundering and terrorist financing.

This study uses primary data obtained through a survey distributed to 160 bankers who work in eight different banks in Indonesia with a 95% confidence level and a confidence interval of 7.75. The criteria needed to determine the sample in this study are individuals who actively work as staff whose work is directly related to banking; individuals who are actively working in banks registered with OJK; individuals who have been actively working in the banking sector in Indonesia for at least three years. The data that has been obtained were analyzed using the SmartPLS application to test the validity and reliability, descriptive statistics and structural models (inner model).

The results of this study indicate that electronic know your customer (eKYC), transaction monitoring (TM), cost and time efficiencies (CTE) influence the prevention of anti-money laundering (AML) and countering financing of terrorism (CFT) in the Indonesian banking sector. However, eKYC and CTE have little influence on AML-CFT in the Indonesian banking sector. Meanwhile, TM has a moderate influence on AML-CFT in the Indonesian banking sector. In addition, in general, most bankers agree that the bank they work for has followed the guidelines, policies and regulations that have been given.

This study uses the Indonesian banking sector as a research subject that raises the effectiveness of the implementation of the use of RegTech to prevent money laundering and terrorism financing.

The significant impact of innovation in stimulating economic growth cannot be overemphasized, more importantly from policy perspective. For this reason, the relationship between innovation and economic growth in developing economies such as the ones in Africa has remained topical. Yet, innovation as a concept is multi-dimensional and cannot be measured by just one single variable. With hindsight of the traditional measures of innovation in literature, we augment it with the number of scientific journals published in the region to enrich this discourse.

We focus on an approach that explores innovation policy qualitatively from various policy documents of selected countries in the region from three policy perspectives (i.e. institutional framework, financing and diffusion and interaction). We further investigate whether innovation as perceived differently is important for economic growth in 25 economies in sub-Saharan Africa over the period 1990–2016. Instrumental variable estimation of a threshold regression is used to capture the contributions of innovation as a multi-dimensional concept on economic growth, while dealing with endogeneity between the regressors and error term.

The results from both traditional panel regressions and IV panel threshold regressions show a positive relationship between innovation and economic growth, although the impact seems negligible. Institutional quality dampens innovation among low-regime economies, and the relation is persistent regardless of when the focus is on aggregate or decomposed institutional factors. The impact of innovation on economic growth in most regressions is robust to different dimensions of innovation. Yet, the coefficients of the innovation variables in the two regimes are quite dissimilar. While most countries in the region have offered financial support in the form of budgetary allocations to strengthen institutions, barriers to the design and implementation of innovation policies may be responsible for the sluggish contribution of innovation to the growth pattern of the region.

Segregating economies of Africa into two distinct regimes based on a threshold of investment in education as a share of GDP in order to understand the relationship between innovation and economic growth is quite novel. This lends credence to the fact that innovation as a multifaceted concept does not take place by chance – it is carefully planned. We have enriched the discourse of innovation and thus helped in deepening understanding on this contentious subject.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.

Evaluates changes in the welfare system in Sweden, the UK and the USA over a decade, basing arguments on the divergence of economic globalization and domestic forces. Presents brief economic snapshots of each country, stating quite categorically that the welfare state is an impediment to capitalist profit‐making, hence all three nations have retrenched welfare systems in the hope of remaining globally economically competitive. Lays the responsibility for retrenchment firmly at the door of conservative political parties. Takes into account public opinion, national institutional structures, multiculturalism and class issues. Explores domestic structures of accumulation (DSA) and refers to changes in the international economy, particularly the Bretton Woods system (Pax Americana), and notes how the economic health of nations mirrors that of the US. Investigates the roles of multinationals and direct foreign investment in the global economy, returning to how economic policy affects the welfare state. Points out the changes made to the welfare state through privatization, decentralization and modification of public sector financing. Concludes that the main result has been an increase in earnings inequality and poverty.

This study applies asymmetric rather than conventional symmetric analysis to advance theory in occupational psychology. The study applies systematic case-based analyses to model complex relations among conditions (i.e., configurations of high and low scores for variables) in terms of set memberships of managers. The study uses Boolean algebra to identify configurations (i.e., recipes) reflecting complex conditions sufficient for the occurrence of outcomes of interest (e.g., high versus low financial job stress, job strain, and job satisfaction). The study applies complexity theory tenets to offer a nuanced perspective concerning the occurrence of contrarian cases – for example, in identifying different cases (e.g., managers) with high membership scores in a variable (e.g., core self-evaluation) who have low job satisfaction scores and when different cases with low membership scores in the same variable have high job satisfaction. In a large-scale empirical study of managers (n = 928) in four (contextual) segments of the farm industry in New Zealand, this study tests the fit and predictive validities of set membership configurations for simple and complex antecedent conditions that indicate high/low core self-evaluations, job stress, and high/low job satisfaction. The findings support the conclusion that complexity theory in combination with configural analysis offers useful insights for explaining nuances in the causes and outcomes to high stress as well as low stress among farm managers. Some findings support and some are contrary to symmetric relationship findings (i.e., highly significant correlations that support main effect hypotheses).

The paper published below was prepared by Taylor Ostrander for Frank Knight’s course, Economic Theory, Economics 301, during the Fall 1933 quarter.