The research analysis focuses on reviewing the recent and credible literature on the topics of illegal prostitution, illegal drug use, and money laundering. The detailed assessment of these issues is analyzed under the framework of criminology and criminal justice with an emphasis on causes, policies, prevention, and solutions. When it comes to illegal prostitution, many women are victims of child abuse, underage sex trafficking, and a lack of education. The preventative policies are most effective under the context of legalization of practice, advancement of education among females, and better involvement of child protective services (CPS) in the identification of child abuse. In the case of illegal drug use, the correlational factors include mental health issues, low socioeconomic status, and the use of multiple drugs. Thus, the criminalization policies can be effective at prevention, but careful liberalization is necessary to help the existing addicts. However, money laundering requires heavy criminalization and sophisticated solutions due to an array of methods available to criminals. It is likely that the solution will need to involve powerful technologies, such as artificial intelligence or AI.
It is important to note that there are many problems related to illegal activities and crimes. The given research analysis will primarily focus on illegal drug use, illegal prostitution, and money laundering. All three criminal activities can be considered as separate domains and interest points of criminology, but they do have commonalities in their underlying causes and regulatory elements. On the basis of the review of credible and recent literature on these topics, several conclusions can be made. It can be stated that the legalization of prostitution is necessary, liberalization can be useful to fight illegal drug use, and technology needs to be deployed against money laundering.
In the case of prostitution, it is similar to the previous subject when it comes to questioning the effectiveness of criminalization. A study conducted with the use of a prostitution diversion program on women (n = 478) showed that decriminalization of criminal activity might be more effective than restrictive policies (Hickle & Roe-Sepowitz, 2017). The main reason is the fact that many sex trafficked prostitutes were not fully aware of being victims of the practice and perceived it as something undesirable but normal (Hickle & Roe-Sepowitz, 2017). For example, none of the sex trafficked women used the term when describing their own experiences, and many of them entered the sex trade industry before the age of 18 (Hickle & Roe-Sepowitz, 2017). In addition, many victims of sex trafficking experienced child abuse, domestic violence, and childhood rape with less likelihood of reporting it (Hickle & Roe-Sepowitz, 2017). In other words, there is strong evidence to question the effectiveness of criminalization.
It should be noted that preventative policies should always address the root cause of a problem. The criminalization of prostitution breeds sex trafficking because illegal prostitution becomes unregulated by state authorities (Hickle & Roe-Sepowitz, 2017). Since many victims of sex trafficking enter the industry as minors, they become accustomed to it and stop perceiving it as criminal even if they might possess the knowledge. The majority of such victims become vulnerable to sex traffickers from early childhood, which implies the need for policies in regard to child protective services. Therefore, criminalization does not prevent illegal prostitution but rather encourages it. The most effective policy would be bolstering the involvement of CPS in identifying the victims of child abuse, domestic violence, and childhood rape because these are clearly causal factors since they are widespread among sex trafficking victims. For the women already engaged in illegal prostitution, the most powerful measure would be the legalization and protection of sex workers from sex traffickers, gangs, and criminals.
Education, especially higher education, is critical in combatting illegal prostitution as well. A study on North American female escorts (n = 700) revealed that not only does education makes it less likely for women to engage in prostitution, but it improves their prostitution work compared to uneducated women (Cunningham & Kendall, 2017). In addition, many illegal prostitutes did not complete a college education (Cunningham & Kendall, 2017). The researchers show the fact that college-educated women and educated women, in general, tend to avoid prostitution due to the availability of other means to earn income. In the case of women, who opt for prostitution, educated females work with fewer clients, avoid problematic clients better, and combine sexual services with non-sexual activities (Cunningham & Kendall, 2017). Therefore, it is evident that education-based policies and measures can greatly help in reducing the likelihood of women entering the sex trade industry and improve the lives of the current prostitutes. The education system needs to implement programs to prevent young women from becoming prostitutes and allow the existing ones to be able to seek better options. These recommendations imply that the practice is decriminalized and even legalized.
Illegal Drug Use
When it comes to criminal justice and criminology, there are different perspectives on the plausible preventative measures, where one side might argue for criminalization and the other advocate for liberalization. In addition, such a discussion has two aspects, which involve preventing illegal drug use among non-users and dealing with addicts. Global research conducted across 20 nations (n = 36506) indicates that many current illegal drug users are more likely to seek help if the corresponding country adopts policies with more liberalized policies (Benfer et al., 2018). The latter includes milder punishments, such as fines instead of jail time, government outlets with legally available drugs, and legalization (Benfer et al., 2018). The primary reason for reluctance among drug addicts to seek help in countries with stricter policies in fear of a criminal sanction (Benfer et al., 2018). In other words, it is essential that national drug policies are reevaluated to find a balance between prevention and assistance for illegal drug users. Liberalization of such criminological frameworks might prove useful to prevent unnecessary incarcerations and elevating addicts from their addictions.
Abuse of illegal substances is a critical problem on a massive scale, which is manifested in its dangerous impact on society at large. For example, an opioid epidemic not only causes loss of life in terms of overdoses but incurs a significant economic impact due to reduced productivity, homelessness, and unemployment. In the last 15 years, 165000 people lost their lives to overdoses, and the big reason is fentanyl and other synthetic drugs, which tend to be highly toxic and potent (Gellad et al., 2017). However, illegal drug abuse is not limited to opioids since there is a wide range of substances prohibited by the law.
A study conducted to identify the common causal factors behind illegal drug use reveals that there are correlational characteristics. Most individuals (n = 818) are likely to be from low socioeconomic backgrounds, have mental health issues, and are poly-drug users (Metz et al., 2018). Thus, the lack of education, employment, and financial stability can increase the likelihood of drug abuse or illegal substances. When it comes to mental health problems, it is evident that the latter goes in parallel with the criminological activity. The majority of drug addicts tend to consume more than one particular drug. For example, an opioid user will likely use another illegal substance as well. However, one should note that correlation does not imply causation because it is possible that illegal drug use itself results in a decrease in socioeconomic status and mental health development.
Money laundering is a major international issue related to financial manipulations, corruption, and other forms of criminal activities. It is essentially a deceptive method of legitimizing criminally acquired funds by altering the ownership of a property through various transactions and transfers. A study conducted with the participation of money launderers, their advisers, experts, and officers (n = 209) revealed that there are 12 effective and commonly used methods (Teichmann, 2017). These include currency exchange offices, private cash deals, deposit boxes, Dubai banks, mergers and acquisitions, consulting firms, real estate projects, art, antiquities, diamonds, jewelry, and gold (Teichmann, 2017). In other words, there is a wide range of ways to conduct money laundering, which is among the most challenging problems to combat. The existing anti-money laundering mechanisms need to account for all of these methods since they are highly conventional and common among such criminals. In addition, cryptocurrencies are newly emerging forms of money laundering, which has a rather rare usage but needs to be accounted for in preventative measures (Teichmann, 2017). The sheer complexity of the matter makes it develop and design sophisticated criminalization frameworks.
Since the issue of money laundering is a complicated and challenging form of crime, new methods of prevention, tracking, monitoring, and identification need to be implemented. Such a solution can be provided by advanced technology, which is artificial intelligence. A study conducted with the use of AI and machine learning on transactions (n = 33134) used for training and testing showed promising results (Jullum et al., 2020). AI significantly outperformed the existing anti-money laundering mechanisms of the banking sector (Jullum et al., 2020). It identified the money laundering cases of reported and investigated transactions, reported and uninvestigated transactions, unreported and investigated transactions, and unreported and uninvestigated transactions (Jullum et al., 2020). In contrast, banks are only able to identify after a transaction is deemed suspicious, after which it is investigated and subsequently reported to determine whether or not it is money laundering or a legitimate one. Therefore, AI can offer a more accurate solution with a higher range of monitoring, which could be used the schemes outside the banking sector.
Moreover, money laundering includes a whole range of operations aimed at hiding the source of financial assets so that criminals can subsequently use them without compromising themselves. Usually, these operations are divided into three stages such as placement, layering, and integration (Teichmann, 2017). Placement takes place when illegally acquired funds are transferred to financial institutions for further alteration of ownership. Layering is the separation of criminal proceeds from their source through complex multi-layered financial transactions. Integration is the use of apparently legal transactions to disguise illegal income.
At the placement stage, it is necessary to change the form of funds in order to hide their illegal origin. For example, the proceeds from the illicit drug trade are small denominations that, in total, exceed the volume and weight of the drugs themselves (Teichmann, 2017). Converting them into larger bills, checks, or other financial documents is often done by businesses that deal with large amounts of cash used as cover. For example, shell companies are set up to launder large amounts of money in countries with strict bank secrecy laws or weak money laundering law enforcement. This money is then transferred from one fictitious company to another until it acquires the appearance of legitimately received funds. The aforementioned transactions must be disguised so as to eventually dissolve into the legitimate transactions that take place every day.
At the stage of integration, the criminal tries to transform the money received from illegal activities into funds that have an apparently legal origin: money is usually invested in a business, real estate, or the purchase of luxury goods. Money can be laundered through currency and stock exchanges, gold dealers, casinos, car dealers, insurance, and trading companies (Teichmann, 2017). Private and offshore banks, shell corporations, free trade zones, electronic systems, and merchant financial institutions can all camouflage illegal activity.
Therefore, uncontrolled money laundering can undermine the integrity of the country’s financial institutions and negatively affect exchange rates and interest rates due to the high integration of stock markets. Ultimately, this money enters the global financial systems, where it can undermine the economy and currency of individual countries, creating a serious threat to national and international security (Jullum et al., 2020). It is important to note that money laundering is an international problem, which is intertwined between developed and developing nations. The given global presence of the underlying operations makes it difficult to locate and persistently track the pathways of laundering. A close examination of the negative consequences explains why money laundering is such a multifaceted threat. Undermining the legitimate private sector is a big risk caused by money laundering. Money laundering often uses shell companies that mix the proceeds of illicit activities with legal funds in order to hide the funds. Such companies can have access to significant illegal funds, which allows them to subsidize their goods and services and sell them at prices well below market prices.
In conclusion, illegal prostitution should be legalized, and illegal drug use should be liberalized, whereas money laundering should use more sophisticated methods, such as AI. Firstly, illegal prostitution enables sex trafficking, where the victims are mostly uneducated and underage females with no awareness and perception of their victimhood. Secondly, illegal drug use should find a balance between prevention through criminalization and assistance to the existing addicts through some form of liberalization. Thirdly, money laundering is highly complex, with many effective methods available, which makes it impossible to combat without novel solutions, such as AI and machine learning. Thus, it is critical to address these issues by focusing on underlying causes with the use of effective policies and criminalization reforms.
Benfer, I., Zahnow, R., Barratt, M. J., Maier, L., Winstock, A., & Ferris, J. (2018). The impact of drug policy liberalization on willingness to seek help for problem drug use: A comparison of 20 countries. International Journal of Drug Policy, 56, 162–175.
Cunningham, S., & Kendall, T. D. (2017). Prostitution, hours, job amenities and education. Review of Economics of the Household, 15(4), 1055–1080.
Gellad, W. F., Good, C. B., & Shulkin, D. J. (2017). Addressing the opioid epidemic in the United States. JAMA Internal Medicine, 177(5), 1-2.
Hickle, K., & Roe-Sepowitz, D. (2017). “Curiosity and a pimp”: Exploring sex trafficking victimization in experiences of entering sex trade industry work among participants in a prostitution diversion program. Women & Criminal Justice, 27(2), 122–138.
Jullum, M., Løland, A., Huseby, R. B., Ånonsen, G., & Lorentzen, J. (2020). Detecting money laundering transactions with machine learning. Journal of Money Laundering Control, 23(1), 173–186.
Metz, V. E., Brown, Q. L., Martins, S. S., & Palamar, J. J. (2018). Characteristics of drug use among pregnant women in the United States: Opioid and non-opioid illegal drug use. Drug and Alcohol Dependence, 183, 261-266.
Teichmann, F. M. J. (2017). Twelve methods of money laundering. Journal of Money Laundering Control, 20(2), 130–137.