Law enforcement works tirelessly around the world to combat the scourge of online fraud and is now warning of organized gangs increasingly gravitating to fraud.
Enterprises must match these efforts with improvements of their own. That means supporting risk teams with highly usable, data-centric fraud prevention platforms that leverage the power of machine learning to stop scams in their tracks.
Criminals Cash In
Yet there’s no time to be complacent, as organized crime gangs previously involved in drug trafficking and firearms offenses are increasingly turning to online fraud. They’re helped in this by the recruitment of money mules, who provide bank accounts for fraudsters to launder their illegally obtained funds.
There are even romance scammers who trawl dating sites looking for vulnerable middle-aged and elderly victims often recruit their marks as money mules. They apparently convince them to open new bank accounts and, in some cases, register a limited liability company, in order to cash in on a ‘lucrative business opportunity’ which turns out to be anything but.
The Right Tools
The truth is that, despite the best efforts of police, online fraud is thriving. E-commerce firms alone are expected to lose billions in online card not present (CNP) fraud over the next few years. In addition, over a third (34%) of global retailers in 2018 saw between 11% and 20% of their cross-border orders rejected because of fraud or suspected scams, according to Statista.1
Fraud impacts enterprises in numerous ways. There is the headline hit to the bottom line that comes from chargebacks. But legacy anti-fraud solutions can also add to the problem, by creating additional administrative overheads such as flagging too many cases for manual review. If efforts to block suspected fraud attempts are too rigorous then the extra friction this generates could lead to abandoned baskets that cost the company more than predicted fraud itself.
It’s a fine balancing act, and one which fraud teams can only achieve with the right tools. Simility’s Adaptive Decisioning Platform is one such tool. It’s built on large volumes of data from disparate sources, manual rules written by teams in plain English, and machine learning models which can spot complex fraud patterns. These are designed to adapt, strengthen and evolve over time, no matter what the bad guys have up their sleeves.
That’s the reassurance organizations need as they continue to leverage the power of digital transformation to get closer to their customers.
To learn more about how Simility’s Adaptive Decisioning Platform can help your business strike a balance between fraud detection and customer friction, schedule a demo today.