Identity theft: How machine learning protects against online fraud.
When goods are ordered under a false name, retailers are often left with the costs. RISK IDENT has developed a software that uses artificial intelligence to put a stop to identity fraud in e-commerce.
- With the increasing digitization, the number of fraud cases in e-commerce is also growing. A strong increase is also expected in the financial sector.
- RISK IDENT's software offers companies protection against fraudsters on the Internet.
- A self-learning algorithm determines the fraud probability of an order within milliseconds and thus provides merchants with a basis for decision-making.
Online trade in Europe has seen double digit growth for years. The pandemic only added to the rapid increase in digital interactions between companies and customers. The number and use of digital payment methods have soared and in everyday life, we reach for the smartphone more often to show a vaccination certificate or train ticket. The downside to all this convenience is the opening it gives cybercriminals.
Losses from online fraud are growing rapidly.
To find out how companies can protect themselves against online fraud, we conducted a video interview with Frank Heisel. Frank is Managing Director of RISK IDENT. Like EOS, the company, which is headquartered in Hamburg’s Hafencity , is part of the Otto Group. According to Frank, it is market leader for anti-fraud software in the German speaking countries. The diversified customer base includes retail corporations like Otto and Breuninger, Deutsche Telekom and Vodafone, the car rental company Sixt, and Deutsche Bahn. In the financial sector, banks and payment providers protect themselves with RISK IDENT software. EOS clients also benefit (see the interview on page 31). Around the world, RISK IDENT secures annual revenue of 80 billion euros for its clients, according to Frank.
Our algorithms predict in a matter of milliseconds the likelihood that an order is fraudulent.
Battle against organized crime
The best chance of preventing fraud is to recognize attempts early on. Frank explains how it works: “Criminals typically place more than one order. They use different identities or e-mail addresses, but don’t have an infinite number of devices. We see with device fingerprinting that we are getting an order from Anna, one from Jay, another one from Paula, but all of them use the same device. When we recognize that, we can identify and predict fraud attempts better.”
The tool against online fraud is called FRIDA.
Greater protection thanks to machine learning.
Frank says fraudsters are remarkably persistent. “Even if they run into a brick wall a number of times, they do succeed eventually. The point is to make sure they do not succeed twenty times by using the same method.” So, the goal is damage control. Complete protection is impossible. That is the harsh reality.
To the decision in milliseconds.
Companies trying to defend themselves have to ask how inconvenient they want to make things from the criminals’ point of view, says Frank. The higher the firewalls to minimize fraud, the more steps are required. Having too many steps obviously clashes with the online shop’s goal of offering its “good” customers the fastest possible shopping experience, ideally with many payment options.
Fraud prevention under the radar.
As an anti-fraud software provider, RISK IDENT does not want to impede ordering processes or financial transactions and prefers to “fly under the radar,” says Frank. “Our algorithms predict in a matter of milliseconds the likelihood that an order is fraudulent.” Banks or retailers base their risk decisions on these predictions.
AI is not a solo act
Currently, e-commerce and telecommunications make up more than half of RISK IDENT’s revenue. Frank predicts that the financial sector in particular will have to make major investments in cybersecurity. After all, most financial institutions keep pushing the digitalization of their processes so consumers can transfer and receive money within seconds. “Instant payment is the vision all credit institutions are working on.” The amounts involved in lending differ greatly from those in online retailing. “In Germany, an installment loan of EUR 80,000 may be issued without any collateral,” Frank says. So a great deal more money could quickly fall into the wrong hands.
Even digital ID cards do not offer full protection.
In India, for example, a central database was hacked last year. “That is worst case.” In central databases, the damage is in all likelihood even greater, as the personal data volume is larger and, above all, the data have been verified.
A never-ending cat-and-mouse game.
Thanks to the pandemic, we communicate online and via mobile channels, transfer money and shop online more than ever before. Annual damage caused by cyberattacks around the world is estimated to be in the trillions of dollars. Online fraud has evolved into a serious cost factor for companies. To put it differently: If you lower fraud expenses, you gain a competitive edge. In an ideal world, according to Frank, a business such as RISK IDENT would not even exist. “We really are an unnecessary industry,” he says. “However, data security is not and never will be an obsolete issue.”