https://www.tandfonline.com/doi/epub/10.1080/25741292.2020.1725366?needAccess=true
This paper uses anti-money laundering as a case study to illustrate the benefits of cross-disciplinary engagement when major policymaking functions develop separately from public policy design principles. It finds that the anti-money laundering policy intervention has less than 0.1 percent impact on criminal finances, compliance costs exceed recovered criminal funds more than a hundred times over, and banks, taxpayers and ordinary citizens are penalized more than criminal enterprises. The data are poorly validated and methodological inconsistencies rife, so findings cannot be definitive, but there is a huge gap between policy intent and results. The scale of the problem not addressed by “solutions” repeatedly “fixing” the same perceived issues suggest that blaming banks for not “properly” implementing anti-money laundering laws is a convenient fiction. Fundamental problems may lie instead with the design of the core policy prescription itself. With an important policymaking function operating largely as an independent silo of specialist knowledge, this paper suggests that active engagement with critical, diverse perspectives, and deeper connections between the anti-money laundering movement and other disciplines (notably, policy effectiveness, outcomes and evaluation principles of public policy) should contribute to better results.
Public policy, evaluation, policy success/failure, global governance, anti-money laundering, AML/CFT
A worldwide policy paradigm enforcing complex anti-money laundering laws gives the comfort of activity and feeling of security but does not make us safe from crime. Letting criminal enterprises retain up to 99.95 percent of criminal proceeds, the modern anti-money laundering experiment unwittingly enables, protects and supports terrorists, drug, human, arms and wildlife traffickers, sex and labor exploiters, and corrupt officials, fraudsters and tax evaders on a global scale. Anti-money laundering is a globally significant policymaking function affecting millions of businesses and billions of people daily, so it seems odd that policy design issues are mostly addressed independently. More explicit connections with the rigor of policy science should contribute to better results.
The modern anti-money laundering movement is fundamentally ineffective, with evidence of policy failure obscured by idiosyncratic “effectiveness” evaluations poorly connected with policy design principles. This section briefly notes some of the key problems detailed later in this paper.
Despite trillions of dollars poured into the global 30-year “war” against money laundering, the anti-money laundering movement remains unable to show policy success.
To evaluate outcomes, the key policy issue is the standard by which effectiveness should be assessed. The primary goal…was to use money flows to detect and prevent serious crime, and thereby…reduce and prevent the economic and social harm caused by serious profit-motivated crime. It is against such outcomes that effectiveness might best be judged. Curiously, no such (crime reduction and prevention) measures were identified. (Pol
Absent specific, measurable crime reduction and prevention objectives since the beginning of the modern anti-money laundering experiment in 1990, so-called “outcome” metrics of a new “effectiveness” methodology (operational since 2014) also fail meaningfully to assess effectiveness, outlined in Section 5. In essence, “misapplication of outcome labels to outputs and activities miss an opportunity properly to evaluate outcomes, as the impact and effect of [anti-money laundering] policies” (Pol 2018a, 216). Consequently, the anti-money laundering movement remains incapable of demonstrating effectiveness as generally understood in public policy as the impact and effect of policy intervention.
Furthermore, the absence of adequate success metrics likely contributes to relatively little awareness (and less acceptance) of policy failure, compounding and extending three decades marked by results measured as a fraction of a percentage point away from complete failure.
This paper uses elements of cost-benefit analysis so routine in public policy as to be mundane, yet surprisingly rare in anti-money laundering discourse (reflecting a persistent reluctance to consider costs or show outcomes in terms of the impact of policy intervention). This method joins a line of scholarship critically testing core elements of the anti-money laundering system; notably, its limited capacity to prevent serious profit-motivated crime and terrorism (Anand 2011; Brzoska 2016; Chaikin 2009; Ferwerda 2009; Findley, Nielson, and Sharman 2014; Harvey 2008; Levi 2002, 2012; Levi and Maguire 2004; Levi and Reuter 2006, 2009; Naylor 2005; Pol 2018b; Reuter and Truman 2004; Rider 2002a, 2002b, 2004; Sharman 2011; van Duyne 2003, 2011; Verhage 2017).
Compounding the above issues, even striking parallels between the public policy and anti-money laundering fields appear not to have prompted much cross-fertilization between them.
For example, Peters’ (2015, 270) “simplistic tools” of performance management metrics (undermining the capacity to address higher-order issues, and contributing to policy failure) is reflected in anti-money laundering ratings, but, absent much cross-disciplinary discourse, there is little opportunity to benefit from such warnings. The first independent assessments of new ratings intended to gauge the effectiveness of money laundering controls found simplistic metrics incapable of assessing outcomes (Pol 2018a), and an evaluation system with little resemblance to evaluations as “generally understood by public policy and social science researchers, namely how well an intervention does in achieving its goals” (Levi, Reuter, and Halliday 2018, 310). Despite such structural design flaws there remain surprisingly few connections between anti-money laundering practice and the scholarship and practice of public policy. (Examples include de Koker and Turkington 2015; Halliday, Levi, and Reuter 2014; Levi et al. 2018; McConnell 2015, 238; Pol 2018a, 2018b, 2019a, 2020; Sharman 2011; Zoppei 2017).
Few explicit connections with policy design principles may help explain scant recognition that the core “compliance” intervention model may itself significantly contribute to poor results.