Obwohl sich Ermittlungsverfahrenen zur Bekämpfung von Geldwäsche (AML) ständig weiterentwickeln, bleibt eine Hauptquelle für illegale Erlöse auf internationaler Ebene weitgehend unbekannt—der Handel mit Wildtieren. Der Handel mit Wildtieren ist ein bedeutender Schwarzmarkt1 und ein Umweltverbrechen, das jährlich schätzungsweise zwischen sieben und 23 Milliarden US-Dollar generiert.2...

In 2008, the pseudonymous Satoshi Nakamoto published the bitcoin white paper describing a cryptocurrency free from the control of governments or banks.1 Twelve years later, there are over 2,000 cryptocurrencies, but Nakamoto’s libertarian vision has collided with the realities of regulation. According to Chainalysis, a...

The application of big data and machine learning in anti-money laundering (AML) transaction monitoring (TM) programs is undeniably vast. Over the past five years, financial institutions (FIs) have assessed how they could implement and benefit from machine learning capabilities. Some FIs have already leveraged machine...

Identifying beneficial owners with a satisfactory level of certainty has been a manual and often fastidious task for know your customer analysts and compliance officers. Issues vary from deciphering poorly scanned articles of association, to the design, collection and verification of beneficial ownership statement forms...

Although anti-money laundering (AML) investigations are ever evolving, one major source of illegal profit internationally remains largely underreported—wildlife trafficking. Wildlife trafficking is a major illegal trade1 and an environmental crime that is estimated to generate between seven billion US dollars and 23 billion US dollars...