In an era where digital transactions move at the speed of light and financial systems stretch across continents, transnational financial crimes have become more complex, elusive, and dangerous.
From cross-border money laundering and cryptocurrency scams to AI-assisted fraud, financial criminals are increasingly exploiting the slow pace of international law enforcement and outdated legal frameworks.
But as the challenge grows, so does the potential of Artificial Intelligence (AI).
Experts and cybersecurity professionals argue that integrating AI into financial oversight, law enforcement, and legal frameworks could become a game-changer, if governments are willing to embrace both its power and its risks.
Legal scholar and cybersecurity law expert, Amarachi Ndubuisi, based in the United States said transnational financial crimes are not new.
“What is new is the scale, speed, and sophistication with which they now occur. Cybercriminal syndicates routinely target banks, payment processors, cryptocurrency platforms, and even government systems, often operating from jurisdictions with little regulatory oversight.
“According to the United Nations Office on Drugs and Crime (UNODC), money laundering alone moves an estimated $1.6 trillion annually, much of it across borders and via digital channels. Law enforcement agencies, however, are often confined by national laws and slow bureaucratic processes.
“Today’s financial criminals are no longer just individuals, they are networks operating with precision technology, and often with support from weak institutions,” She said.
Artificial intelligence, with its ability to detect patterns and anomalies across massive data sets, is already being deployed by some financial institutions to flag suspicious activity. But its broader integration into anti-crime systems remains limited.
AI can track transactions in real-time, identify hidden connections between accounts across jurisdictions, and even predict fraudulent behavior before it occurs. For example, machine learning algorithms can spot abnormal financial flows that deviate from a customer’s normal behavior, alerting compliance teams instantly.
“AI doesn’t just react—it learns. That makes it ideal for identifying emerging fraud schemes that traditional systems might miss,” she said.
Yet, while the technology offers immense promise, its deployment raises serious legal and ethical questions. Who is accountable if AI systems make an error? What happens to due process if algorithms drive arrests or seizures? And how do we ensure AI doesn’t become a tool for surveillance or discrimination?
Ndubuisi’s recent legal publication, “Analyzing the Impact of Artificial Intelligence on National Security’, warns that without clear legal frameworks, the integration of AI into law enforcement could violate rights and undermine trust in justice systems.
“We must design laws for the technology we’re using, not try to fit emerging threats into outdated rules,” she argues.
Another major hurdle is the lack of international cooperation. Even when financial crimes are identified, differing legal systems, lack of treaties, and data privacy rules often make cross-border investigations nearly impossible.
AI alone cannot fix these gaps, experts caution. It must be supported by updated treaties, harmonized digital evidence protocols, and international legal institutions that can respond quickly to cyber-financial threats.
Some have proposed the creation of international cybercrime courts or task forces with shared AI infrastructure. While such ideas remain largely aspirational, global forums, including the UN and African Union, are beginning to discuss how AI could be part of cross-border legal reform.
For countries like Nigeria, Kenya, and South Africa, emerging digital hubs but also hotspots for online fraud, the need to modernise is urgent. A lack of enforcement capacity, combined with weak data laws, has made many African states vulnerable targets and unwilling hosts for global financial crime syndicates.
Organisations such as Privacy Hub Africa are now calling on governments to not only invest in AI tools but also train prosecutors, judges, and regulators to understand how technology is changing crime and how law must change too.