Financial crime is multi-faceted, multinational and very often invisible, making it hard to identify, measure and combat. Its impact is felt in many ways.
For those forced into slave labour by criminals infiltrating supply chains, or the victims of sex trafficking gangs who launder their profits through the financial system, the cost is catastrophic.
Organizations are paying a heavy financial cost, collectively spending billions trying to prevent financial crime, yet they are seeing ever greater amounts disappear from their businesses as a result of money laundering, fraud, theft and corruption.
It is widely believed that up to $2 trillion of illicit proceeds from financial crimes such as human trafficking, bribery and fraud are flowing through the financial system. And up to half of multinational companies have been victims of fraud in the last 12 months, according to our own survey of more than 2,300 companies. In addition, there are an estimated 40 million people who are the victims of modern day slavery. And yet slavery is illegal everywhere.
The figures tell us that financial crime is depressingly common and widespread. Its prevalence is made possible by our inability to disrupt and dismantle the crime networks that support it – networks that attack weaknesses in the international financial system every year.
Its global nature means we need collective action if we are to combat it effectively and that requires regulators, law enforcement agencies, data providers and financial institutions to place an increasingly high priority on tackling it.
At Davos last year we formed a unique coalition together with Europol and the World Economic Forum to open up the conversation across corporates, financial institutions, governments and think tanks on how to tackle financial crime at a coordinated, global level. The need to promote more effective information sharing between public and private entities is widely accepted as key to success.
At the heart of possible solutions is the ability to harness data and new technology to create new insight at the network level, moving away from tracking financial crime at the transaction level. After 18 years of providing risk intelligence data, we now maintain more than 4 million records – and this is an amazing foundation on which to use big data techniques to map connections and spot patterns in the data.
Network mapping is a really interesting emerging discipline that can help us combat crime more effectively. Understanding where criminal networks operate, or what types of criminal activity a country is connected to or vulnerable to will help yield better intelligence and ultimately better outcomes for organisations.
For companies that operate globally, this type of analysis and relationship mapping can be instrumental in understanding the illicit activities that they may be exposed to, but it doesn’t stop there.
Mapping out criminal relationships for human trafficking for example, can act as a valuable addition to the existing focus placed on suspicious financial transactions, which are often the first indication of money laundering from illicit activities such as trafficking.
Network mapping can be further improved when we work with charities and NGOs to obtain information they have gathered on trafficking activities, particularly in countries where underreporting is known to exist or where information is simply not published. Our recent work with Liberty Shared is one such example, where we have taken information and data collated by them on the ground in certain countries.
When displayed visually, networks provide a much clearer picture about the connections to criminal activity such as human trafficking. In the example below the visualisation offers a powerful commentary on the global nature of human trafficking with human trafficking affecting developing and developed countries alike.
Gathering and sharing information at the intersection of global financial systems and supply chains and moving away from a transaction by transaction approach is crucial when it comes to uncovering and preventing crimes such as human trafficking and modern day slavery. Using this intelligence, businesses can look to further strengthen their own corporate due diligence programmes and ensure their employees are appropriately educated and trained.
New technology offers new solutions and, as we incorporate machine learning and artificial intelligence with data, we see the potential to uncover additional hidden risks in business relationships and human networks.
Better data and smarter techniques are making it easier to shine a light on the dark places in which the traffickers like to operate. In turn, this enables us to form a more complete picture of risk across global supply chains.
In the case of financial crime, good data can be the beginning of a better world.