Innovative Tech-enabled

economic crime

In partnership with:

This session offers a deep dive into the transformative potential of Fourth Industrial Revolution (4IR) technologies like AI and blockchain in both enabling and combating economic crime, with a special focus on addressing corruption and promoting ethical practices.

 

Through expert insights and real-world examples, our guests explore how digital tools can enhance transparency, accountability, and governance while also understanding the risks of tech-enabled economic crime.

Background information

The webinar, held in partnership with BEN-Africa, explores how Fourth Industrial Revolution (4IR) technologies like AI, blockchain, and other digital tools are reshaping the fight against economic crime while also presenting new risks.

 

With a special focus on combating corruption, particularly in sectors like water governance, the session highlights how these innovations can enhance transparency, accountability, and ethical practices. At the same time, it addresses the darker side of tech — how these same tools can be misused to enable sophisticated economic crimes.

 

Bringing together experts and thought leaders, this webinar provides an in-depth discussion on the opportunities and challenges posed by tech-enabled economic crime and valuable insights into the ethical implications of emerging technologies and explore practical strategies for strengthening governance and risk management.

Short Explainer Video

Questions and Answers

Corruption is not easily defined and is constantly evolving. Traditionally, it was perceived to occur in secrecy, “behind closed doors.” However, in poorly governed or highly corrupt states, corruption can happen “in broad daylight” and may even be seen as a necessary “grease that oils the wheels of industry and commerce.” The advent of technology, like Facebook and AI, has made it easier to connect and move money, adding a layer of complexity. This highlights that corruption is not solely a clandestine activity but can be overt and even justified under certain conditions.

The “triple challenge” encompasses structural inequality, heightened issues around poverty (including extreme poverty), and unemployment. These conditions, often exacerbated by conflict and war, create an environment where economic crime flourishes. Despite receiving significant aid (e.g., USD 30-50 billion from the UN), illicit financial flows (around USD 90 billion exiting the continent) far exceed this, prompting questions about the necessity of aid and the need to leverage internal resources.

Blockchain offers a highly transparent and difficult-to-manipulate ledger system, which can bolster governance and procurement processes, making it harder for corruption to occur. It can also facilitate anonymous whistleblowing, protecting individuals who disclose corrupt activities, particularly in contexts where whistleblowers face threats. AI, when viewed through a human rights-based approach, can aid in demanding accountability and transparency. Instead of solely relying on law enforcement to pursue criminals, a human rights approach enables a broader societal role in fighting corruption, utilising AI to monitor and expose suspicious activities, such as unexplained wealth displayed on social media.

Criminals are constantly innovating and are often a step ahead of law enforcement. Emerging technologies provide enhanced anonymity, making it difficult to identify perpetrators. This includes using fake names in emails for scams (like inheritance scams) and hiding behind shell companies or legitimate businesses. Money laundering is also facilitated by the internet, allowing illicit profits to be moved rapidly and reinvested into further criminal activities, creating a “virtuous cycle” for criminals. The rise of deepfakes and voice cloning further blurs the lines between reality and deception, enabling new forms of fraud.

It is crucial to categorise corruption to offer appropriate solutions. “Grand corruption” involves large sums of money and occurs at high-level decision-making points (e.g., government contracts), often driven by greed or systemic capture. “Petty corruption” (or administrative corruption) occurs at the administrative level, involving smaller bribes for services (e.g., access to water), often driven by the individual’s lack of adequate salary. Different solutions are required for each: improving salaries might curb petty corruption, while tackling grand corruption requires addressing greed and systemic issues, potentially through international mechanisms. This classification helps in applying appropriate technological and policy interventions.

Combating corruption ethically is vital to prevent the politicisation and instrumentalisation of anti-corruption mechanisms. It requires adhering to due process of law and respecting the rights of the accused. There is a risk of “corruption of anti-corruption,” where mechanisms are twisted to target political opponents. A key ethical dilemma arises with information leaks (e.g., Panama Papers) where illegally acquired evidence, while useful for public opinion, may not be admissible in a court of law due to privacy rights and surveillance concerns. Striking a balance between aggressive anti-corruption measures and upholding human rights is a constant challenge.

Policymakers and regulators must actively engage with civil society and researchers to inform policy, ensuring that empirical research is considered rather than shelved. There’s a need for a “multi-pronged approach” involving different sectors. While some question whether the private sector is better equipped than governments to fight corruption, it’s acknowledged that corruption exists in both. Ultimately, a fundamental shift in societal culture and ethics is required. Individuals must also take responsibility by refusing to engage in corrupt practices (e.g., paying bribes) and inculcating ethical awareness in future generations, moving away from a sole focus on material wealth. Support for international mechanisms, such as an International Anti-corruption Court, is also proposed to provide a neutral and effective means of tackling corruption beyond domestic political influence.

Key Concepts and Themes

  • Definition Challenges: Economic crime, particularly corruption, is difficult to define definitively and is constantly evolving.
  • Traditional Misconceptions: Corruption is not always secret; in poorly governed states, it can occur openly and even be perceived as necessary (“grease that oils the wheels”).
  • Categorisation of Corruption:Grand Corruption: Involves large sums of money, occurs at decision-making levels (e.g., awarding government contracts), and is often driven by greed or systemic capture. Solutions are complex and require addressing powerful actors.
  • Petty/Administrative Corruption: Involves smaller amounts, occurs at the administrative/service delivery level (e.g., bribing a village officer for water access), and can be driven by inadequate salaries or desperate circumstances. Solutions might include fair pay and accessible reporting mechanisms.
  • Impact of Corruption: It is not a victimless crime; it is an “extra tax on the poor” and harms society as a whole.
  • Enabler of Crime:Anonymity: Technology, particularly AI, allows criminals to operate anonymously (e.g., fake emails for scams, deepfakes, voice cloning).
  • Speed of Money Movement: The internet facilitates rapid money laundering and movement of illicit profits globally.
  • Diversification: Criminals can use technology to diversify into legitimate businesses.
  • Undetectable Wealth Transfer: Cryptocurrencies and blockchain can be used for untraceable movement of vast amounts of money.
  • Questioning Authenticity: Deepfakes and voice cloning make it difficult to distinguish reality from fabrication, aiding deception.
  • Tool for Combating Crime:Transparency and Accountability: Blockchain, as an immutable ledger system, can enhance transparency in governance and acquisition processes (e.g., government procurement).
  • Whistleblowing Protection: Blockchain can provide anonymous and secure channels for whistleblowers, protecting them from retaliation. Incentivising disclosures could further boost this.
  • Evidence Collection: AI and other technologies can monitor social media and other data sources to identify unexplained wealth, leading to investigations and convictions.
  • Data Analysis: Technologies can help analyse large datasets to identify patterns and anomalies indicative of corrupt activities.
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  • Policy and Implementation Gap: Research findings often remain “shelved,” with policymakers failing to consult or implement recommendations.
  • Cultural Shift: Technology alone is insufficient; a fundamental shift in culture, ethics, and “humanity” is required to combat corruption effectively (e.g., instilling a “first-world culture” in developing nations, promoting Ubuntu/Unhu).
  • Moral Bankruptcy: A focus on material wealth and conspicuous consumption contributes to corruption, indicating a loss of societal values.
  • Instrumentalisation of Anti-Corruption: Anti-corruption mechanisms (courts, commissions) can be corrupted and used for political ends.
  • Legal vs. Ethical Evidence: Information obtained illegally (e.g., data leaks like Panama Papers) may not be admissible in court, despite revealing significant corruption. This highlights a tension between human rights (privacy) and the fight against corruption.
  • Multi-pronged Approach:Cross-Sector Collaboration: Requires cooperation between government, business, civil society, and academia.
  • Human Rights-Based Approach: Fighting corruption should uphold fundamental rights like transparency and accountability, ensuring due process and fair representation for the accused. This also places duties on those in power and businesses.
  • International Cooperation: Domestic efforts are often insufficient; international mechanisms (e.g., an International Anti-Corruption Court) are needed.
  • Public Awareness: Educating communities on the long-term impact of corruption can motivate public participation in the fight.
  • Professional Responsibility: Gatekeepers (professionals in various sectors) have a crucial role in preventing and reporting corruption.
  • Self-Regulation vs. External Control for Tech Companies: The debate on whether tech companies should self-regulate or be subject to hybrid models involving local communities and government agencies, especially given their profit-driven focus and the rapid evolution of technology.

Our guests

Key terms used during the event

  • AI (Artificial Intelligence): The simulation of human intelligence processes by machines, especially computer systems. In the context of the transcript, it can be used both to perpetrate (e.g., deepfakes, voice cloning) and combat (e.g., data analysis) economic crime.
  • Anonymity: The state of being unknown to others. In the context of economic crime, criminals exploit anonymity provided by technology (e.g., fake emails, hidden identities) to avoid detection.
  • Anti-Corruption Court (International): A proposed international judicial body designed to prosecute cases of grand corruption, aiming to provide a neutral and effective platform for accountability beyond domestic political influence.
  • Blockchain: A decentralised, distributed, and often public digital ledger that records transactions across many computers so that the record cannot be altered retroactively without the alteration of all subsequent blocks and the consensus of the network. Used for transparency and secure whistleblowing.
  • Corruption of Anti-Corruption: A phenomenon where mechanisms intended to fight corruption (e.g., courts, anti-corruption commissions, laws) are themselves manipulated or politicised to target opponents or serve specific interests.
  • Cryptocurrency: A digital or virtual currency that is secured by cryptography, making it nearly impossible to counterfeit or double-spend. Many cryptocurrencies are decentralised networks based on blockchain technology, enabling untraceable movement of wealth for criminals.
  • Deepfakes: Synthetic media in which a person in an existing image or video is replaced with someone else’s likeness. These are created using AI and can be used for fraudulent or deceptive purposes in economic crime.
    Economic Crime: A broad category of illegal activities committed for financial gain, including fraud, money laundering, and corruption. The focus of the webinar is on crimes enabled by innovative technology.
  • Gatekeepers: Professionals (e.g., lawyers, accountants, financial advisors) who have a professional duty to prevent and report illegal activities, but who sometimes collude with criminals.
  • Global South: Refers to countries often described as developing, less developed, or developing, primarily located in Africa, Asia, and Latin America. Characterised by challenges like structural inequality, poverty, and unemployment, which can exacerbate economic crime.
  • Grand Corruption: Corruption involving high-level officials and large sums of money, typically at the policy-making or decision-making levels (e.g., procurement contracts). Often driven by greed or systemic political capture.
  • Human Rights-Based Approach to Corruption: An approach that views corruption not just as a criminal act but as a violation of fundamental human rights (e.g., the right to transparency, accountability, clean water), thereby empowering individuals and broadening the scope of the fight against it.
  • Illicit Financial Flows (IFFs): Money illegally earned, transferred, or used. In the context of Africa, the outflow of illicit funds significantly exceeds the inflow of aid, highlighting the scale of economic crime.
  • Internet of Things (IoT): A network of physical objects embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the internet.
  • Money Laundering: The process of concealing the origins of illegally obtained money, typically by passing it through a complex sequence of banking transfers or commercial transactions. Technology speeds up this process.
  • Panama Papers/Luanda Leaks: Examples of large-scale data leaks that exposed vast networks of offshore financial accounts and tax evasion, often facilitated by technology. The legal admissibility of such illegally acquired evidence is a debated ethical challenge.
  • Petty Corruption (Administrative Corruption): Lower-level, routine corruption involving smaller sums of money, often occurring at the administrative or service delivery level where individuals interact directly with public officials.
  • Procurement: The process of obtaining goods or services. Government procurement is often highlighted as an area vulnerable to corruption, which blockchain technology could help to make more transparent.
  • Social Justice Activist: An individual who advocates for fairness and equality in society, often working to address systemic issues like poverty, inequality, and corruption.
  • State Capture: A type of systemic corruption where private interests significantly influence a state’s decision-making processes to their own advantage, often at the expense of the public good.
  • Transparency International Corruption Perceptions Index (CPI): An annual index that ranks countries by their perceived levels of public sector corruption, as determined by expert assessments and opinion surveys.
  • Triple Challenge: A concept introduced by Anthony Kaziboni, referring to the interconnected issues of structural inequality, poverty (including extreme poverty), and unemployment, particularly prevalent in the Global South.
  • Ubuntu/Unhu: African philosophical concepts emphasising interconnectedness, community, and humanity. Anthony Kaziboni suggests a return to these values is crucial for combating corruption and fostering responsible behaviour.
  • Whistleblower: An individual who exposes information about illegal or unethical activities within a private or public organisation. Technology, like blockchain, can offer secure and anonymous channels for whistleblowers.

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