TaxThemis: Interactive mining and exploration of suspicious tax evasion group

Tax evasion is a serious economic problem for many countries, as it can undermine the government' s tax system and lead to an unfair business competition environment. Recent research has applied data analytics techniques to analyze and detect tax evasion behaviors of individual taxpayers. However, they failed to support the analysis and exploration of the uprising related party transaction tax evasion (RPTTE) behaviors (e.g., transfer pricing), where a group of taxpayers is involved. In this paper, we present TaxThemis, an interactive visual analytics system to help tax officers mine and explore suspicious tax evasion groups through analyzing heterogeneous tax-related data. A taxpayer network is constructed and fused with the trade network to detect suspicious RPTTE groups. Rich visualizations are designed to facilitate the exploration and investigation of suspicious transactions between related taxpayers with profit and topological data analysis. Specifically, we propose a calendar heatmap with a carefully-designed encoding scheme to intuitively show the evidence of transferring revenue through related party transactions. We demonstrate the usefulness and effectiveness of TaxThemis through two case studies on real-world tax-related data, and interviews with domain experts.Comment: 11 pages, 7 figure

Combating Money Laundering and the Financing of Terrorism: A Survey

Policy programs on anti-money laundering and combating the financing of terrorism (AML/CFT) have largely called for preventive measures like keeping record of financial transactions and reporting suspicious ones. In this survey study, we analyze the extent of global money laundering and terrorist financing and discuss the preventive policies and their evaluations. Moreover, we investigate whether more effective tax information exchange would bolster AML/CFT policies in that it reduced tax evasion, thus the volume of transnational financial flows (i.e. to and from offshore financial centres) and thus in turn cover given to money laundering and terrorist financing. We conclude that such a strategy can reduce financial flows, yet due to a "weakest link problem" even a few countries not participating can greatly undo what others have achieved

Combining Network Visualization and Data Mining for Tax Risk Assessment

This paper presents a novel approach, called MALDIVE, to support tax administrations in the tax risk assessment for discovering tax evasion and tax avoidance. MALDIVE relies on a network model describing several kinds of relationships among taxpayers. Our approach suitably combines various data mining and visual analytics methods to support public officers in identifying risky taxpayers. MALDIVE consists of a 4-step pipeline: ( ${i}$ ) A social network is built from the taxpayers data and several features of this network are extracted by computing both classical social network indexes and domain-specific indexes; ( ii ) an initial set of risky taxpayers is identified by applying machine learning algorithms; ( iii ) the set of risky taxpayers is possibly enlarged by means of an information diffusion strategy and the output is shown to the analyst through a network visualization system; ( iv ) a visual inspection of the network is performed by the analyst in order to validate and refine the set of risky taxpayers. We discuss the effectiveness of the MALDIVE approach through both quantitative analyses and case studies performed on real data in collaboration with the Italian Revenue Agency

Money Laundering and criminal connected companies

This thesis is about the money laundering. It included 4 chapters. First chapter is about ML models. Second chapter is about 4th AML Directive and its role in center. ML activity. Third is about gaps of the Russian legislation. Fourth is about ML activity in modern spor

How Countries Should Share Tax Information

Offshore tax evasion, international money laundering, and aggressive international tax planning significantly reduce government revenues. In particular, for some low-income countries the amount of capital flight (where elites move and hide monies offshore in tax havens) exceeds foreign aid. Governments struggle to enforce their tax laws to constrain these actions, and they are inhibited by a lack of information concerning international capital flows. The main international policy response to these developments has been to promote global financial transparency through heightened cross-border exchanges of tax information. The Article examines elements of optimal cross-border tax information exchange laws and policies by focusing on three key challenges: information quality, taxpayer privacy, and enforcement. Relatedly, the Article discusses how the exchange of automatic big tax data combined with data analytics can help address these challenges. The recommended laws and policies will improve how countries share tax information, which in turn will help inhibit global financial crimes

Tracking Transnational Terrorist Resourcing Nodes and Networks

In light of persistent terrorist attacks in Europe and elsewhere, the study of terrorist resourcing and financing has attracted renewed attention. How are terrorists\u27 networks financed? Who raises the financial resources, and how do they transfer them across borders? How does the global financial industry facilitate or impede these transfers? Answers to these and other questions can help law enforcement investigate, disrupt, and neutralize cross-border terrorist resourcing. Evidence and data on this phenomenon is scarce, of questionable quality, irreplicable, and can be difficult to come by. This study is the first comprehensive effort to collect, code, analyze, and compare available open-source case law data on transnational terrorist resourcing networks. Under the study\u27s methodology, the conventional yet strict focus on financing is broadened to resources, which includes forms other than cash, including trade-based fraud and online social networks. The analysis reveals common crossborder resourcing patterns and usage of financial intermediaries such as banks. It thus contributes to the ongoing optimization of anti-terrorist resourcing laws, policies, and risk-management practices

A Critical Examination of the Multinational Companies Anti-corruption Policy in Nigeria

In contemporary enterprise and organisational culture, many companies are increasingly willing to increase their profits and to gain competitive advantages through indulgence in bribery, corruption, money laundering and other anti-social practices that shows little regard for social obligations and even laws. Companies cemented their social relations by claims of socially responsible and of ethical conduct, but the evidence in practice proves otherwise. The bourgeoning corporate social responsibility literature rarely examines predatory practices of MNCs even though the practices affect a variety of stakeholders. This paper draws attention to the gaps between corporate anti-corruption policy and acts. The paper used publicly available evidence to provide case studies to show that companies engaged in bribery, corruption and money laundering as against their claims of responsible social conduct. The paper argued that MNCs have used the political elite in developing countries to seek to advance their global earnings and competitive advantages by offering bribes and other inducements to secure government contracts in Nigeria. It also encourages reflections on endemic corrupt practices and offers some suggestions for reform