Towards Ingenious Technology and the Robust Enforcement of Financial Markets Laws to Curb Money Laundering in Zimbabwe

Technology has positively contributed to the creation of financial markets and the facilitation of payments globally. The effective use of robust technology could enhance the consistent enforcement of financial market laws by curbing financial crimes in any country. This in turn would enhance the integrity of financial markets and promote the viability of financial markets. In relation to this, it appears that Zimbabwe has struggled to comply with international measures to combat money laundering and the financing of terrorism (AML/CFT) since it has poor financial market laws which are inconsistently enforced due inter alia to its poor money laundering detection mechanisms and inadequate resources. For instance, Zimbabwe has to date failed to make satisfactory progress to adopt and enforce adequate risk mitigation measures against money laundering practices in accordance with the Financial Action Task Force (FATF) recommendations. This is evidenced by the increased incidence of money laundering in Zimbabwean financial markets. Furthermore, the inconsistent enforcement of financial market laws has resulted in poor liquidity and the recent suspension of the Zimbabwe Stock Exchange (ZSE). The viability and integrity of the Zimbabwean financial market has thus been compromised. This article discusses the integration and use of robust technology in the Zimbabwean financial market to curb financial crimes such as money laundering and bank fraud. The adequacy of financial market laws and/or regulations will also be discussed vis-à-vis their consistent enforcement by relevant bodies such as the Financial Intelligence Inspectorate Evaluation Unit (FIU) in Zimbabwe. This is done to evaluate the use of technology to curb money laundering and promote a viable economy and financial market in Zimbabwe. It is submitted that the relevant authorities should promote the effective use of technological inventions like artificial intelligence (AI) and machine learning to curb money laundering, bank fraud and other related financial crimes in Zimbabwe.

Money laundering is generally defined as the channelling of cash or other funds generated from illegal activities through legitimate financial institutions and businesses to conceal the original illicit source of such funds. 9 In other words, money laundering is the act of obscuring the origins of money usually illegally obtained through the provision of an apparently legal source. 10 Information technologies including computers and other specialised digital devices which have sometimes promoted money laundering through the swift movement of illegally obtained funds, often amongst foreign banks and/or legitimate businesses. 11 Money laundering may take the form of placement, layering and/or integration. 12 Anyone who makes and/or accrues any form of benefit from any criminal conduct like corruption may be regarded as committing an act of money laundering. 13 Placement is the first stage of money laundering, wherein the money launderer introduces the illegally obtained profits into the formal financial system. 14 This is often done by breaking up large sums of money into less conspicuous smaller sums before depositing them into financial institutions. 15 This is done to ward off any suspicions that would otherwise arise if such money was deposited by the money launderer in large sums. Layering relates to the stage where the money launderer divides, blurs and moves the laundered money further away from the illegal source. 16 This may be done through the purchase of investment instruments or by transferring the money to jurisdictions which do not cooperate with or comply with anti-money laundering investigations and legislation such as international anti-money laundering/combating of the financing of terrorism (AML/CFT) measures. 17 Lastly, integration refers to the process where the money launderer moves the previously laundered money into the economy, usually through financial institutions, so that the money appears to originate from his or her legitimate business activities. 18 Money laundering is a global phenomenon and its occurrence in Zimbabwe is no exception. 19 It would be a threat to the integrity and functioning of the financial sector of any country. 20 Criminals may easily finance terrorist activities and/or criminal businesses through money laundering globally. 21 However, it is submitted that the cost of implementing effective anti-money laundering mechanisms often supersedes the proceeds to be recovered from the financial crime. 22 To this end, it is necessary to enact and implement robust anti-money laundering laws as well as to optimally utilise technology to detect and curb money laundering activities to promote viable financial markets. Accordingly, this article investigates the use of technological innovations to detect and curb money laundering in the Zimbabwean financial institutions and financial market.

Historical background and incidents of money laundering in Zimbabwe (2003-2020)
For the purposes of this article, the practices of money laundering will be traced from 2003, when bearer cheques where introduced into Zimbabwe by the Reserve Bank of Zimbabwe (RBZ) as legal tender. 23 It must be borne in mind that generally, money laundering flourishes in both formal and informal economies. To this end, it is important to note that the economy of Zimbabwe began declining in the 1990s 24 and as a result, a shift from the formal to the informal economy ensued. 25  Makina 2010 J Dev Soc 105-106, ZIMPREST was a successor programme to the ESAP which sought to address the social and political agenda of poverty reduction, land reform, black economic empowerment and the indigenisation of the Zimbabwean economy. ZIMPREST was unsuccessful due to the government's weak fiscal policy, the high inflation rate and the depreciation of the Zimbabwean dollar in 1998. 29 Mkodzongi and Lawrence 2019 Rev Afr Polit Econ 8, the FTLRP was initiated in 1998 to redistributed land from white-owned farms and estates to more than 150 000 black farmers primarily for growing crops and grazing land to landless and poor farmers in Zimbabwe. Additionally, the FTLRP allocated some farmlands to new black commercial farmers who had the skills and resources to farm profitably, reinvest and raise agricultural productivity in Zimbabwe.  61 Bwititi 2020 https://www.sundaymail.co.zw/old-mutual-in-govts-cross-hairs-zsegiant-faces-money-laundering-charges; Dzirutwe 2020 https://www.business live.co.za/bd/world/africa/2020-07-28-zimbabwe-trading-to-resume-but-old-mutualand-ppc-stocks-still-suspended/.

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PER / PELJ 2021 (24) 10 markets, as investors and traders rely inter alia on predictability and the consistent operation of financial markets.
In mid-2020 Ecocash 65 which is owned and operates under the auspices of Econet Wireless, was alleged to have created a fictitious mobile money platform which converted such mobile money into cash in order to facilitate the purchasing of foreign currency on the black market and to take the money out of Zimbabwe. 66 It appears that there were poor customer diligence measures for verifying mobile money customer identity documents, as evidenced by the number of fake mobile money accounts that exist in Zimbabwe. 67 For this reason the Financial Intelligence Inspectorate Evaluation Unit (FIU), which was formerly known as the Bank Use Promotion and Suppression of Money Laundering Unit ordered Ecocash to reregister all Ecocash agents in order to curb illicit foreign currency dealers who were now promoting illicit high volume transactions on the Ecocash as most illicit foreign currency dealers utilised Ecocash alongside other mobile money platforms like OneMoney, Telecash and Mycash money to commit money laundering. 68 This was also done to identify and curb illicit foreign currency dealing which promoted high volume transactions, especially on the Ecocash platform, which allegedly destabilised and distorted the foreign currency market. 69

The Bank Use Promotion and Suppression of Money Laundering Act [Chapter 24:24] 2 of 2004
The against a financial crisis mostly promoted by informal and imprudent banking practices such as money laundering and bank fraud 72 and in reaction to the ongoing Zimbabwean economic decline which started in the 1990s, when most private individuals and corporations in Zimbabwe avoided banks and the formal financial sector. 73 As a result, informal trading in goods and foreign currency gave rise to illicit trading activities such as money laundering in. 74 In other words, most foreign currency was held in the informal banking sector for illegal foreign currency dealings and money laundering. Moreover, the counterfeiting of bearer cheques and the externalisation of funds exacerbated the practice of money laundering. 75 The Money Laundering Act empowered the Bank Use Promotion and Suppression of Money Laundering Unit (Money Laundering Unit) to identify and seize any unlawful and illegitimate proceeds of all serious crimes, including drug trafficking and money laundering. 76 The Money Laundering Act promotes reliance on the formal banking institutions and the combating of money laundering by financial institutions and all private individuals. 77 However, it is silent on the use of AI and any other technological measures to curb money laundering, bank fraud and other financial crimes in Zimbabwe. 78

The Prevention of Corruption Act [Chapter 9:16] 27 of 2004
Corruption could be defined as an immoral act which violates the law of any country while exacerbating poverty and inequality among its people. 79  the most corrupt countries in Africa. 82 Other than the National Code on Corporate Governance (ZimCode) of 2014, which deals with the principles and standards of corporate governance, no measures have been adopted to promote ethical measures and corporate governance standards. 83 Unlike countries such as the United States of America (USA) and India, that have compulsory codes for corporate governance measures and corruptionrelated measures ("comply or else" approaches), 84 the ZimCode follows a "comply or explain" approach. 85 This is a more flexible regulatory approach which encourages individuals and corporations to take responsibility for and ownership of corporate governance standards. 86 It enables companies to follow a set of standards from which they choose, without their being mandated to comply with all of the set standards. 87 Companies are at liberty to choose principles that are applicable to them and they are expected to explain and justify the reasons behind their choice of corporate governance standards. 88 However, this approach seems not to be effective because there is rampant corruption and poor governance practice in banks, stateowned enterprises and other companies in Zimbabwe. Perhaps compulsory corporate governance measures that are strictly enforced by the relevant role-players should be introduced into Zimbabwe to effectively curb corruption and money laundering. 89 The Prevention of Corruption Act does not have any provision that encourages the use of technological measures to curb corruption and other related crimes such as money laundering and bank fraud.

The Money Laundering and Proceeds of Crime Act [Chapter 9:24] 4 of 2013
The Money Laundering and Proceeds of Crime Act 90 was enacted in 2013 in order to reinforce the criminalisation inter alia of money laundering, and the financing of terrorist offences, and to aid in the identification and freezing 82 Sifile Notably, the Proceeds of Crime Act deals with the identification and curbing of money laundering and the financing of terrorist offences. 95 However, the Eastern and Southern Africa Anti-Money Laundering Group (ESAAMLG) report of 2019 indicates that Zimbabwe is still struggling to comply with the FATF's AML/CFT recommendations due inter alia to the lack of adequate resources and the poor use of technological devices to detect and combat money laundering and bank fraud in its financial markets and financial institutions. 96 The Act does not expressly provide for the use of technology such as artificial intelligence (AI) and machine learning to curb money laundering and bank fraud.

The FIU
As stated earlier, the FIU was established by the Money Laundering Act 97 inter alia to provide for the promotion and use of the formal banking system.

The ESAAMLG
The ESAAMLG is a regional body established to accelerate the adoption and implementation of global recommendations and standards to curb money laundering and the financing of terrorism in some eastern and southern African countries. 109  FATF 2020 http://www.fatf-gafi.org/publications/fatfrecommendations/documents/ fatf-recommendations.html 7, recommendation 12 states that financial institutions and DNFBPs are required to take reasonable measures as part of their internal controls to determine if a customer or beneficial owner is a domestic or international organisation politically exposed people (PEP). Recommendation 16 applies to both cross-border and domestic wire transfers and seeks to prevent terrorists and other financial criminals from having unfettered access to wire transfers for moving their funds, and for detecting and curbing such misuse when it occurs. Recommendation 17 states that financial institutions and DNFBPs should be required to take appropriate steps to identify and assess their proliferation financing risks. Recommendation 20 states that the financial institutions must report any suspicious transactions to the relevant authorities immediately. Recommendation 24 states that competent authorities should be able to obtain, or have access in a timely fashion to, adequate, accurate and current information on the beneficial ownership and control of companies and other legal persons. Recommendation 25 states that countries should have regard to the FATF best practice guidelines on providing feedback to reporting financial institutions and other persons. terrorism are conducted in accordance with the FATF and other regional and international role-players. 111 However, it appears that the ESAAMLG does not oblige its member countries to employ appropriate technological measures such as AI to curb money laundering, bank fraud and other financially related crimes in their respective financial instruments and financial markets.

Evaluation of Zimbabwe's compliance with the FATF and ESAAMLG
In an assessment carried out by the ESAAMLG in 2019 to assess Zimbabwe's compliance with the FATF's AML/CFT measures and recommendations, it was stated that Zimbabwe was partially compliant with such measures and recommendations. 112 The FATF held that Zimbabwe fell short of adequate compliance on more serious AML/CFT offences and on most FATF recommendations, especially the recommendation to adopt robust measures to curb money laundering and the financing of terrorism offences in the financial market. 113 In other words, role-players such as the Zimbabwe Republic Police (ZRP), the Zimbabwe Immigration Revenue Authority (ZIMRA), the National Prosecuting Authority (NPA), the Zimbabwe Anti-Corruption Commission (ZACC) and the Financial Intelligence Unit were found to have inconsistent statistics on the prosecutions and convictions of offenders. 114 This could be attributed inter alia to a lack of a comprehensive understanding of money laundering offences and a lack of resources on the part of the enforcement authorities and other role-players in Zimbabwe. Zimbabwe does not have robust measures in place to detect, investigate and combat money laundering and the financing of terrorist offences. 115

Basel Committee on Banking Supervision (BCBS)
The BCBS is housed in the Bank for International Settlements in Basel (BIS) and was established in 1974 by the governors of the central banks of the Group of Ten (G10) countries as a committee of banking supervisory authorities. The BCBS is empowered to set guidelines for banking regulation globally. 116  regulations for banks globally. 117 In 1997 the BCBS issued the Core Principles for Effective Banking Supervision (Core Principles) which are minimum standards for the sound prudential regulation and supervision of banks globally. 118 Likewise, the Core Principles require all banks to have adequate policies and processes, including strict customer due diligence (CDD) rules, to promote high ethical and professional standards in the banking sector so as to prevent banks from being used for criminal activities like money laundering, bank fraud and the financing of terrorist activities. 119 To date, the BCBS has published three banking regulations conventionally referred to as the Basel protocols. 120 Although the BCBS and other relevant role-players have made commendable efforts to enhance the combating of bank fraud, money laundering and other illicit trading practices, they do not expressly oblige the member states to use AI to curb financial crimes such as money laundering.

United Nations Convention against Illicit Traffic in Narcotic Drugs and Psychotropic Substances 1988
Drugs have historically been among the main drivers of money laundering globally, due to the need of drug traffickers to transform proceeds from the illegal sale of drugs into an apparently legal source. 121 The United Nations (UN) Convention Against Illicit Traffic in Narcotic Drugs and Psychotropic Substances 1988 (Narcotic Drugs Convention) was adopted to curb drug abuse and related money laundering activities. 122 Zimbabwe became a member state of the Narcotic Drugs Convention in 1993, in a bid to align its money laundering regulatory regime with international best practices. However, it is submitted that the Narcotic Drugs Convention is too old and appears not to have been updated to align with the recent trends in drug crimes and related financial crimes such as money laundering globally. Furthermore, the Narcotic Drugs Convention does not expressly provide for the use of technological measures by regulatory authorities to effectively curb money laundering and other financial crimes in all member countries.

United Nations Convention Against Transnational Organised Crime 2000 (UNTOC)
The United Nations General Assembly adopted the UNTOC in a bid to curb transnational organised crime such as money laundering 123 in all countries and jurisdictions. To date, about 147 countries have signed UNTOC, including Zimbabwe, which became a member state in 2007. 124 The UNTOC was established in conjunction with its three protocols on human trafficking, migrant smuggling, and firearms in a bid to provide a more unified and comprehensive protection in all countries against related transnational organised crimes like money laundering. 125 The UNTOC empowers member countries to utilise modern technology and other technologically related methods when dealing with transnational organised crime. 126 Although there is no express mention of the use of AI to curb money laundering and other related crimes in the UNTOC, it could be inferred from article 27(3) of the UNTOC, which envisages the use of AI and other modern technologies to curb financial crimes such as money laundering in its member countries.

Political Declaration and Action Plan Against Money Laundering 1998
The Political Declaration and Action Plan Against Money Laundering 1998 (Action Plan Against Money Laundering) was established by the General Assembly after the internationalisation of criminal activities and the globalisation of money laundering increased. 127 The Action Plan Against Money Laundering was adopted in 1998 in order to identify future priorities and areas requiring further action, goals and targets to be established for drug control in all member countries. 128  a result of the sophistication of the techniques employed by the offenders. 129 In other words, offenders were taking advantage of weaknesses in the national regulatory frameworks of most countries by utilising flexible and rapid transfers as well as moving assets across national boundaries. 130 Additionally, offenders exploited the diversity of business regulations in national systems and utilised unregulated professional persons in some countries to commit money laundering activities. The Action Plan Against Money Laundering does not expressly require member states to use modern technologies such as AI and machine learning to detect and curb money laundering.

Naples Political Declaration and Global Action Plan against Organised Transnational Crime 1995
The Naples Political Declaration and Global Action Plan against Organised Transnational Crime (Naples Political Declaration) was established in 1995 by the General Assembly of the UN. 131 It emphasised the need for urgent global action against organised transnational crime, focussing on the structural characteristics of criminal organisations. 132 The Naples Political Declaration requires member countries to harmonise their legislation so as to ensure that their criminal justice systems have the capacity to prevent and control organised transnational crime in all its types and manifestations. 133 However, it does not expressly provide for the use of AI, machine learning and other technological measures to detect and timeously curb money laundering and other financial crimes in all member countries.

The effects of corona virus (covid-19) on money laundering and financial markets in Zimbabwe
Covid-19 is an acute respiratory disease which began in China and has spread to all parts of the world. 134 The negative impact of covid-19 has been felt by most countries globally. 135 It has affected most global economies. 136 Declarations/Political-Declarations_Index.html; Anon "Implementation of a Comprehensive, Integrated and Balanced Approach" 1-2; see related discussion by Narayan 2019 Stat LR 230. 129 Chang 1998 Int J Comp Appl Crim Justice 5. 130 Chang 1998 Int J Comp Appl Crim Justice 5. 131 Neudek, Zyhlarz-Shaw and Lovell 1995 ECCL 91. 132 Neudek, Zyhlarz-Shaw and Lovell 1995 ECCL 91. 133 Neudek In this regard, Zimbabwe too has grappled to boost its economy due to covid-19, political instability and related factors. The Zimbabwean economy was expected to decline by 6.5 per cent in 2019 owing inter alia to the negative effects of covid-19 on the formal and informal sectors of the economy. 137 Moreover, the economy was expected to decline by approximately 3 to 8 per cent at the end of 2020 due to a lack of fiscal stimulus from the government. This was the result inter alia of low productivity in the manufacturing sector and the closure of border entries for imported goods due to covid-19. This affected the economy since Zimbabwe relies mostly on imported goods and services. 138 Corruption has also played a negative role in during the covid-19 pandemic and a lot of covid-19-related relief was looted by government officials. For example, the former Minister of Health (Mr Obadiah Moyo) was dismissed from office after the criminal abuse of office though inflating the prices of covid-19 relief material and funds in Zimbabwe. 139 Additionally, greed and corruption amongst government officials, prominent business figures and state security agents deployed to enforce the covid-19 preventative measures also affected the economy at the expense of the poor ordinary people in Zimbabwe. 140 Corruption and money launderingrelated cases in Zimbabwe have manifested in shady deals between government officials and those in the private sector providing medical equipment for covid-19. 141 Government officials and business people set high profit mark-ups on coronavirus-related material and personal protective equipment (PPE) and abused loans allocated for economic relief and food aid parcels meant for the poor and economically vulnerable people. 142 Furthermore, the bribery of police and the military officers deployed to enforce covid-19 lockdown regulations worsened corruption. 143 The effects of covid-19 have been worse for the poor and vulnerable members of the Zimbabwean society as travel restrictions barred most informal traders from travelling to their places of trade while food parcels were diverted from the 137 UNDP 2020 https://reliefweb.int/sites/reliefweb.int/files/resources/UNDP_ZW_ Briefs_Socioeconomic_impact_of_Corona_virus_01_2020.pdf 7. 138 UNDP 2020 https://reliefweb.int/sites/reliefweb.int/files/resources/ UNDP_ZW_Briefs_Socioeconomic_impact_of_Corona_virus_01_2020.pdf 7. 139 Chingono 2020 https://www.theguardian.com/global-development/2020/jul/09/ zimbabwe-health-minister-facing-coronavirus-corruption-charge-sacked; Ndlovu 2020 https://www.thearticle.com/covid-19-corruption-and-stealing-the-recovery. poor by corrupt government officials. 144 It is submitted that corruption and money laundering have been rampant in Zimbabwe during the covid-19 pandemic.

The use of technology in combating money laundering in Zimbabwe
There has been a rapid increase in AI-related measures to curb money laundering in many countries, since they more efficient than human intelligence. 145 It appears that AI has been valuable in the fields of engineering, telecommunications, aerospace, physics and humanities due inter alia to reduced errors, its speedy completion of tasks and its constant availability, unlike humans. 146 Machine learning, 147 graph deep learning, 148 natural language processing, 149 chatbots 150 and social network analysis 151 are being devised and improved by information technology specialists to curb money laundering in some countries. 152 In Singapore, 153 Italy, 154 the 144 UNDP 2020 https://reliefweb.int/sites/reliefweb.int/files/resources/UNDP_ZW_Briefs _Socioeconomic_impact_of_Corona_virus_01_2020.pdf 5. 145 Bellomarini, Laurenza and Sallinger "Rule-Based Anti-Money Laundering" 1-2. 146 Jamshidi et al "Novel Multiobjective Approach" 454-458. 147 Machine learning is an application of AI that provides computer systems with the ability to automatically learn from past experiences. 148 Chami et al 2020 https://arxiv.org/pdf/2005.03675.pdf 1; Bacciu et al 2020 Neural Networks 204, Wagner 2019 Gesellschaft für Informatik 3. Graphs are generally data structures that can represent complex relational data. On the other hand, deep learning is an AI function that imitates the functioning of the human brain in processing data for detecting objects, recognising speech, translating languages and making decisions. In AML, graph deep learning enables regulators to detect and identify a recurrent pattern in money laundering. 149 Han et al 2020 Digital Finance 6. Natural language processing relates to a field of AI which strives to improve the ability of computers to process and analyse large amounts of data emanating from human languages. As a result, natural language processing may help curb money laundering through the timeous detection of strange or suspicious and/or illegitimate banking transactions. 150 Singh, Ramasubramanian and Shivam Building an Enterprise Chatbot 9. Chatbots are AI software that can have a conversation with a user in natural language through messaging applications, websites, mobile applications or through the telephone. In banking, chatbots can manage communications on behalf of the bank with millions of banking products and service users, at a low cost.

151
Colladon and Remondi 2017 Expert Syst Appl 51. Social network analysis refers to the study of trends between online social network accounts. In social network analysis, relevant role-players for money laundering usually utilise network metrics (which relates to the amount of "traffic") in a specific social network account held by a suspected money launderer. 152 Bellomarini, Laurenza and Sallinger "Rule-Based Anti-Money Laundering" 2. USA, the United Kingdom (UK) 155 and Germany, AI has been employed in one way or the other to curb money laundering in the banking sectors. 156 The use of AI has some notable benefits for the banking community globally. Firstly, it enables better access to credit through the greater accuracy of the mechanisms used for credit risk assessments, which reduces the risks of inaccurate results. 157 Secondly, the advanced analytics employed by AI may help banks to offer contextualised, personalised banking products and experiences to financial consumers. 158 Thirdly, AI may afford financial consumers better protection from fraud and other money laundering-related practices, since AI measures may automatically analyse massive amounts of data to detect anomalies which may be threats to banking institutions. 159 It is generally accepted that Zimbabwean banks have adopted online banking in their operations. However, there appears to be a very low rate of the adoption of AI-related measures by banks and other financial institutions to curb money laundering and related practices. 160

Conclusion
Money laundering is a complex global phenomenon which has been exacerbated by the extensive use of computers, the Internet and other digital devices by the offenders. As a result, various countries have enacted some laws and regulations to curb financial crimes such as money laundering and the financing of terrorist activities. As indicated above, most countries have enacted laws in accordance with the recommendations from the FATF and other role-players such as the UN and the ESAAMLG. In this regard, Zimbabwe has also enacted legislation such as the https://www.insaonline.org/wpcontent/uploads/2020/05/INSA_WP_TBML.pdf 8. In the United States of America (USA), the Financial Crimes Enforcement Network (FINCEN) reviews all Trade-Based Money-Laundering (TBML)-related Suspicious Activity Reports (SARs) that are filed by financial institutions. Additionally, FINCEN can also utilise Geographic Targeting Orders (GTOs), which requires any USA financial institution which operates within a certain geographic area to report on transactions greater than a specified amount. FINCEN has the ability to analyse this data and detect and identify typologies, patterns and trends, which could serve as vital information for tracing suspicious and money laundering-related practices to both law enforcement and the private sector in the USA. In other countries like Canada, AI is used in the form of algorithm-related measures in order to timeously detect illicit practices in the financial markets. This information was obtained from Mr Topham from the Financial Service Conduct Authority in South Africa during the 2 nd Corporate and Financial Markets Law Annual Colloquium held on the 29 th -30 th of October 2020 at the North-West University. 165 Section 3 of the Proceeds of Crime Act must be amended to include the use of AI, machine learning and other related technologies to curb money laundering, bank fraud and other financial crimes in Zimbabwe.