Data and analytics: Protecting us against financial crime part 1
29 November 2017
The Chicago mobster Al Capone is famously (and perhaps erroneously) credited as the source of the phrase ‘money laundering’ in the 1940s, after his laundromat businesses were used to legitimise cash he gained through less salubrious means.
Even Capone might have been surprised at how the money laundering business has boomed since his days. Our Global Economic Crime Survey shows the scale of the problem: global money laundering transactions worldwide are estimated at between $1 and $2 trillion – that’s 2% to 5% of the world’s total GDP. Less than 1% of this money is ever recovered by the authorities.
Financial institutions have, naturally, been the target of the raft of regulation that the authorities have developed to tackle financial crime in recent years. And as regulation has increased, so has regulators’ willingness to fine institutions that don’t meet established standards. Our survey also shows that nearly one in five banks – a significant proportion – have recently experienced enforcement actions by a regulator.
Technology has much to do with the modern-day increase in financial crime, which encompasses anything from fraud and money laundering to the financing of terrorism and weapons proliferation. The globalisation of finance and the ease with which money can be moved around the world is a perfect breeding ground for dodgy dealings and opacity. But while the audacity and imagination of financial criminals has evolved over time, so too has our ability to use advanced technology to thwart and intercept them.
The human race produces somewhere in the region of 2.5 billion gigabytes of data every day – that’s equivalent to 150,000,000 iPhones. The beauty of data analysis technology is that it allows us to find patterns in vast amounts of data, and financial services institutions are making good use of what’s available to them. Unfortunately, fraudsters and criminals are sometimes one step ahead and the rapid introduction of new products and innovations (such as bitcoin) is adding to the challenge.
Financial crime regulations have placed a huge responsibility on banks and other financial institutions to gather and screen information about customers and transactions. They need much more information than ever before about who and where their customers are, and what they’re doing. It’s no longer enough to process a payment for goods that are shipped around the world; sanctions requirements mean that the bank or institution responsible for the money side of the equation needs to know what the goods are, what they could be used for, where they’re going - and even check that they don’t deviate towards a sanctioned jurisdiction, or are moved to a sanctioned vessel, during transit. That’s a lot of data to manage, with serious consequences if you get it wrong.
In spite of this, we’re not yet winning the fight against financial crime. This should be a story about the successful use of technology to shut down international criminals; instead it’s currently a story of burdensome compliance, soaring operational costs, and punishing fines.
But we can win. The good news is that technology is on our side; the problem is that too many organisations are not yet using the available technology in the most efficient way.
To give just one example, there are systems available that are designed to flag up suspicious transactions on customer accounts. The problem is that too many of these systems haven’t been configured correctly and newer more effective analytical solutions aren’t being used, resulting in hundreds of thousands of false-positive alerts, all of which have to be investigated. That takes a lot of people, and isn’t cheap.
Over the next few weeks we’re going to look in detail at how technology, data analytics and machine learning allows firms to efficiently and effectively meet their compliance obligations. Used well and wisely, with a focus on enhancing the data that’s available, technology can help us win the fight against financial crime.