Fraudsters are using the fear caused by the COVID19 pandemic. Phishing emails have increased by over 600% since the end of February. Read the article here.
Felix Steinmann – Managing Director
The fraud prevention methods we use to determine fraudulent cases in motor vehicle financing include pattern recognition, the exchange of data from credit agencies and the control of reactions to suspicious cases. Because the damage to individual cases is usually too high to collect enough for analysis and the number of cases by different fraudsters is usually too low, machine learning processes can only be used to a limited extent for fraud management in vehicle financing. Therefore, expert knowledge that can be skillfully translated into rules is necessary.
If you, as a bank or financing service provider, don’t have the ability to carry out complete document review prior to application approval, then other parameters can be used to identify problematic points, including: trends in sales figures, information from previous decisions and data from previous payment disruptions. The response to suspicious cases can be automated or controlled manually using risk score values. In the case of manual measures, however, the goal should be to minimize customer disturbance as much as possible. Quick checks are made possible by ensuring that your employees have all relevant information in one interface and can directly initiate any necessary fraud prevention measures.
RISK IDENT has a data pool that provides information on devices that have previously been used for fraud, and we can use this information to suss out whether or not those devices are being used for transactions on your site. In addition, the end devices themselves can often provide useful clues, for instance when their information does not match the customer data or customer behavior on file.
In order to prevent losses, it’s important to respond to suspicious cases effectively. In the complete chain of online purchase to delivery, for example, you have the ability to offer a secure payment method — and later, retailers and logistics can prevent dispatch and delivery. This entire process is based on a broad exchange of information, which feeds our software with the data necessary to quickly detect and halt ever-changing fraud patterns.
For large retailers who have an abundance of data, we can configure individual rule sets that are optimized in accordance with attack patterns. But we also offer best practice rule sets for smaller businesses. In both cases, fraud prevention benefits your customers and gives your business a competitive advantage. Everyone wins — except for scammers.
Reactions to suspicious cases can be largely automated in order to ensure a smooth customer experience. For example, questionable applications can be temporarily paused until the customer provides additional documentation, identification or account information that can help you determine if the application is fraudulent. (As a rule, fraudsters will not respond to your request for further information.) Risk scores and service levels can then be examined in manual processing.
The post-processing of any suspicious cases is particularly important, as recognized fraud attempts can be incorporated into the analysis and will help with the quick detection of new fraud patterns in the future. The knowledge gained will be shared with the entire DEVICE IDENT community, which enables your business to actively contribute to better fraud management (link to “What is Fraud”) for all participating companies — fraud prevention is not about competitive advantages.