Bobbie Dimitrova
Bobbie Dimitrova Dec 5, 2018

The future of fighting cyberfraud, today

Living in a fast-developing digital world has its undeniable advantages. In the last few decades, we confidently entered and mastered the personal computing era. Technologies have enhanced our lives as never before and make handling our day-to-day responsibilities much easier.

But rapid digitalization has its drawbacks: Hackers are becoming overly inventive and already nothing seems completely safe. Just days ago, Marriott revealed that its reservation system suffered a data breach that compromised the personal information of up to 500 million customers.

Financial services organizations are no less vulnerable. Even fintechs brandishing one of their stronger weapons—machine learning—are facing their biggest enemy in the form of super creative fraudsters. This is a recipe for a war of technologies.

As a result of the pervasive digital landscape, the times when a criminal stole your credit card and partied with it at the nearest store are long gone. Due in part to the implementation of EMV, this method poses less of a problem today, the financial industry now faces a fraudster network working with tools that help them successfully acquire valuable information without leaving the comfort of their own homes (or den of thieves, if you prefer).

Today, all institutions keep their customers’ information digitally. Though they store data under strong security measurements, many of them can do little when someone decides to produce their own. A well-versed techie with a little data science knowledge can generate thousands of credit card numbers. By using a simple binary tree algorithm based on the trial-and-error tactic on a powerful machine, the hacker can acquire all the information they need.

Fake people, real damage: synthetic fraud

Advanced cybercriminals have gone even further. Instead of using freshly acquired credit card data on the black market, they work towards creating a synthetic identity by using a combination of a real and manufactured information. It takes them years to convince a bank system that this is a real existing person, but it works. In fact, financial institutions overwhelmed by other security concerns too often devote their resources elsewhere, as this BAI Banking Strategies podcast reveals.

Eventually, synthetic fraudsters open a bank account and a credit card, which they keep in a good standing. Outwitting the system, the scammers then acquire multiple credit cards and buy merchandise with no intention to pay for it, often repeating the cycle with another synthetic identity. And another.

The above pattern, while common across the prepaid market space, represents but one challenge. Prepaid credit cards are not based on a credit check but only a simple Know Your Customer (KYC) check, which enables skillful cybercriminals to easily apply for and obtain a card with stolen personal information such as Social Security numbers and addresses.  

The payments and banking sectors stand out as the most frequent targets of cybercriminals. Financial services institutions now struggle to keep customers information out of the sight from hackers but often to little avail. This is where advanced technology comes in.

Fighting cybercrime with machine learning and artificial intelligence

As scammers get more creative, the IT sector rapidly rises to meet new digital world challenges. Machine learning and AI have been around for a while but offer new promise for financial services organizations. The former can be successfully used to identify unusual customer behavior patterns and catch fraud even before it happens. And with AI, computers can make their own decisions as they continuously react to newly ingested data.

Predictive algorithms can utilize thousands of data points to recognize and prevent fraudulent activity and with the help of proprietary algorithms, banks can prevent fraud and protect customers from unexpected risk. Companies can do this by monitoring hundreds of thousands of accounts simultaneously instead of focusing on a queue-based system. These algorithms help identify potential money laundering and catch activity that’s invisible to the naked eye.

Artificial intelligence and machine learning are here to change our world forever. And while many of the headlines center on driverless cars, Alexa-type chatbots and computers that can process hundreds of thousands of documents in seconds, computers can be used as weapons as well. Cybercriminals know this. But so do the high-tech innovators developing digital arsenals to fight fraud—and perhaps win that war someday. 

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Bobbie Dimitrova is a marketing assistant at DataSeers.

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