Fighting Crime with AI
The pandemic has exacerbated the risks of these crimes in the past two years. There has been an explosion of new risks and challenges as fraudsters and traffickers have become increasingly skilled at falsifying documents, submitting false insurance claims, and finding funding to carry out crimes wherever they can.
Organizations large and small are hard at work trying to root out crime across their systems. Unfortunately, with data growing at exponential rates, it has become an even more difficult task.
The Data Challenge
One of the greatest challenges? A lack of accuracy and context in data. With data disorganized, standing alone in siloes without context surrounding the individuals involved in carrying out crimes, criminals have become more sophisticated, flying under the radar and working around current monitoring systems.
The results range from still damaging but smaller crimes such as individual insurance claim fraud, to the devastating effects of underground trading and trafficking across the world.
In a world where nefarious actors excel at carrying out crimes under the cover of poor financial crime detection systems, companies must find new ways to prevent these activities. Fortunately, AI has given organizations the tools to not just catch criminals, but to prevent crimes before they take place.
Few companies suffer from a lack of data. Instead, problems arise when that data lives in siloes, disconnected from crucial information that can help prevent fraud. AI takes a frustrating issue—massive amounts of disorganized data—and turns it into insight that is more accessible, valuable, and easy to use.
AI provides much-needed context and sheds light on patterns that may indicate fraud and instances of trafficking. For example, it was recently reported that Americans consume more than $2 billion worth of seafood caught in illegal or unregulated waters each year. If technology had been implemented in a way to monitor data across the different shipping carriers, fishing boats, ports and more, it may have been possible to see this nefarious activity as it was happening.
This implementation is not easy to achieve, but critical to disrupting criminal activity. Individual actions may not spell out anything harmful or insidious—but together in context, companies can quickly detect troubling patterns to track down and thwart bad actors.
Connecting the Dots
Contextual intelligence in data is ultimately about connecting the dots between people and companies who need financing. AI has the power to bring in what once felt like insurmountable amounts of information and leverage that data, instead of leaving it in a disorganized, disconnected state, ideal for criminals to exploit.
If the world wants to make a difference and prevent these crimes from happening, organizations have to approach the supply chain and finance industry holistically, bringing together financial institutions, shipping companies, and law enforcement with a shared goal of catching criminals and ending illegal trade and trafficking.
With the right AI in place, companies can take a huge step forward to achieving just that.