In this article, which serves as an introduction, the authors take a closer look at theoretical definitions as well as empirical manifestations of money laundering. They discuss the judicial definition and the often used theoretical distinction between ‘three stages’ of money laundering. Furthermore, the authors provide the reader with a quick overview of several forms of money laundering. This overview is based on actual criminal investigations. It covers the transfer of cash money and ‘concealed consumption’, both of which are frequently overlooked by authors who use the three stages model. Also ‘traditional’ forms of money laundering such as loan backs, abuse of legal trade, feigning gambling profit, structuring of real estate deals and ‘new’ forms, i.e. the use of bitcoins, are dealt with.

In Dutch criminal money laundering investigations there is no need to fully proof the predicate offence. When a criminal suspicion of money laundering exists without a direct connection to the predicate offence it’s the suspect who must prove the legal origin of his income or possessions. If the suspect doesn’t succeed in this, the judge will rule that the origin has to be criminal. This article shows in six steps how judges rule in this kind of cases and how an investigation can be done. These six steps are combined with examples from recent jurisprudence. The goal of this article is to raise awareness on this subject in order to operate more efficiently and effectively in money laundering investigations.

In 2014, almost all countries of the European Community have revised their National Accounts. Besides the introduction of some important methodological and theoretical improvements, now income from illegal activities are included in the estimates of the national income. For the Netherlands the inclusion of illegal activities has increased gross national income by some 0.4%. This is less than the overall average for the European Community.

Offshore companies play a substantial role in the laundering of dirty money, especially in bigger cases. This article reflects on the definition of offshore companies and analyses several cases of money laundering through these often complicated financial business structures. The lack of knowledge on offshore money laundering practices hampers criminal investigation worldwide. Improving the registration of cases and sharing knowledge internationally would help to develop better prevention measures and to detect money laundering through offshore companies. The author also provides a list of risk indicators signalizing possible abuse of offshore companies.

This research takes a closer look at the criminal careers of 89 offenders who are involved in offering hawala services. The main finding is that 61% has a criminal record that does not consist of hawala related offenses. This finding is important from both a policy and criminological perspective. Firstly, incorporating hawala in the legal financial sector is a difficult prospect with the current people involved. Somehow the sector needs to be cleaned up. Secondly, the findings tie in with other research about criminal careers in organized crime. About two-thirds came into contact with the authorities later in life. However, an important caveat to the authors’ findings is that the outcomes are based on a known group of offenders. The total size of the hawala population is a dark number.

In this article the authors use empirical data from the Dutch Organised Crime Monitor to give empirical insight into the investments of organised crime offenders in legal economy. Using a dataset of 1,196 individual investments, they look into what kind of assets offenders purchase and where these assets are located. The authors use the empirical results to assess the tenability of different theoretical perspectives and assumptions that are present in the literature on money laundering and organised crime: the standard economic approach, the criminal infiltration approach and the social opportunity structure. The results of this study show that offenders predominantly invest in their home country and that their investments consist of tangible, familiar assets such as residences and other real estate and companies from well-known sectors. Investments such as bonds as well as stocks in companies in which offenders are not personally involved, were only found in a small number of cases. To put it differently: offenders usually stay close to home with their investments. Based on these results, the concept of social opportunity structure seems to be best suited to understand offenders’ investment choices.

Dutch policy makers, as elsewhere, have a strong belief in the effectiveness of asset recovery legislation. There are high expectations concerning the amounts of crime money to be collected, and the collection thereof would enable theauthorities to tackle serious, organized crime and fill the treasury. However, the results of the authors’ empirical research into the actual execution of ‘recovery orders’ show a different image. The majority of asset recovery cases concerns cases with low payment obligations (under € 5,000), indicating that mainly ‘smaller fishes’ are targeted. In general, the collection of crime money proves to be a difficult endeavour. Large amounts are not collected and there are long execution times. Policy makers who publicly announce high expectations, and who budget the expected incomes from asset recovery, do not practice evidence-based policy making and give leeway to false hopes which then require new (legislative) measures.

All EU Member States developed anti-money laundering policies based on EU directives and FATF recommendations. While uniformity in this policy area is needed for international cooperation, the different countries are facing different money laundering challenges and interpret the goal of anti-money laundering policy quite differently. This article analyses the money laundering threat in each EU Member State and the effectiveness of the corresponding policy reaction. Furthermore, the authors identify four types of anti-money laundering policy in the EU and classify each country in one of the four types by using the statistical method of cluster analysis.