This paper surveys the existing academic literature on artificial intelligence (AI) technologies
for anti-money laundering (AML). We review the state-of-the-art AI methods for AML and …

Despite an emerging international consensus on principles of AI governance, lawmakers
have so far failed to translate those principles into regulations in the financial sector …

In the financial sectors like banking, anti-money laundering (AML) is a very challenging
issue. To prevent the money laundering, various set of procedures, government policies …

Over the last decade, the international community has become more aware of the danger
and harm caused by the practice of the crime of Money Laundering (ML). Organizations to …

The paper overviews the AVS video standard (developed by the Audio Video Coding
Standard Working Group of China) in terms of basic features, adopted major techniques and …

Money laundering (ML) is a critical source of extracting the money illegally from the financial
system. It is linked to various types of crimes, including corruption, exploitation of a specific …

In many real‐world applications of AI, the set of actors and tasks are not constant, but
instead change over time. Robots tasked with suppressing wildfires eventually run out of …

Most of the current anti money laundering (AML) systems, using handcrafted rules, are
heavily reliant on existing structured databases, which are not capable of effectively and …

Criminal analysis is a complex process involving information gathered from different
sources, mainly of quantitative character, such as billings or bank account transactions, but …

Money laundering (ML) is a serious crime which makes it necessary to develop detection
methods in transactions. Some researches have been carried on, but the problem is not …