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The AI revolution affects us all, starting from the tools we use every day for mundane tasks to the security of our workplace. However, one area where artificial intelligence is having a significant effect, both positive and negative, is in credit card fraud detection. On the one hand, fraud detection and credit card protection AI programs have advanced significantly in recent years, and today, their detection rate of financial anomalies exceeds 98%. However, on the other hand, the methods and tools available to everyday fraudsters have become increasingly complex.
Are you a business operating in a competitive industry, looking to improve the performance and profitability of your services? Then, investing in fraud detection and credit card protection tools will be essential for the proper development of your enterprise. Credit card fraud is the main factor that can lead to financial and reputational losses for American companies. So, the use of professional solutions with AI capabilities is the only way to stay one step ahead of fraudsters and make their job harder.
Are fraud detection programs infallible? No, nothing is. However, their success rate is significant, with their main advantage being that they allow the automation of a good part of the security systems necessary for the monitoring of financial data. What does this mean for your employees? Reduced workload and more time to focus on core competencies. Fraud detection AI tools can analyze real-time anomalies in transactions performed on your website’s platform, make use of neural nets for continuous improvements, and are always one step ahead of bad actors, thanks to their unrivaled predictive analysis algorithms.
How Will AI Be of Use?
Artificial intelligence is developing at a dizzying pace. So, in a few years, it may force us to ask some difficult questions about the definition of sentience and how we can control a technology that is beginning to copy the defining elements of humanity. But until then, AI is a tool, and like any tool, it can be used for both positive and not-so-legal purposes. How can AI help in credit card fraud detection? For one thing, algorithms will analyze and establish patterns for each customer who has accessed your services. A deviation from the standard pattern interpreted by the program you are using could cause the transaction to be flagged and investigated further.
How do these algorithms work? Through machine learning. What can we understand from this term? In short, machine learning is the use of large data sets whereby computers can improve their performance and accuracy without human input. In machine learning, through complex computational logic, computers repeat the same task over and over again until they arrive at a suitable solution to the chosen problem. The more intricate the datasheet, the better the fraud detection and credit card protection program will be at its selected job.
To make an analogy, machine learning is like a child learning to ride a bike. It fails and fails again, but with each failure, it gets better until, at some point, it learns to use it without external intervention. Machine learning can be operated in conjunction with natural language processing, crucial for the prevention of phishing attempts, or with behavioral biometrics that can analyze the subtle motions of peripherals. Behavioral biometrics analysis is, for example, used in CAPTCHA tests, and it’s an essential element in the prevention of fraud attempts when unusual usage patterns are detected.
How Does It Work?
Are you one of the more than six million employers active in the United States? In that case, you are most likely interested in finding out how fraud detection and credit card protection work. The process itself is pretty simple, but its accuracy will be influenced by the algorithms of the software solution deployed. Once the customer initiates a transaction for the services or products you offer, the credit card fraud detection application will perform a pre-analysis of the card data used and examine the accuracy of the information processed. What is in this data? Everything from the card expiration number to the customer’s name.
The transaction is registered in the name of John Doe from England, but is the operation carried out from Thailand under an unregistered name? Then, something is probably wrong. Sure, in most cases, fraud is less evident than that, so methods like fingerprinting and behavioral analysis will be needed. The program you use will perform a geographic analysis of the transaction based on the device’s IP and will calculate, in just a few seconds, the likelihood that the transaction is fraudulent based on the rules system implemented by your company.
If the system detects anomalies, then the customer may be asked to prove their identity by two-factor authentication or biometrics. If this is not possible, then the transaction can be automatically canceled. Professional credit card fraud detection applications are helpful because they enable real-time system monitoring without intervention, analyze data from multiple sources at the same time, and have a higher detection rate of fraudulent transactions than is possible with the exclusive use of human staff.
What Methods Do Fraudsters Use?
First, fraudsters may attempt to make transactions on your site using stolen credit card information, which can then be subsequently voided by banks. Did the user of that credit card perform a chargeback of the transaction once they regained access to their account? Then, what happens if the purchased product has already been delivered? Once fraudsters gain access to stolen credit cards, they will probably perform a large number of transactions in a short time, and this will alert the algorithms of the fraud detection and credit card protection application, which will block the transaction and potentially IP ban the customer.
But things are not always so simple. Suppose fraudsters gain access to your users’ credit card information by ATO methods. In that case, they will probably use automatic scripts to perform small transactions designed to bypass the algorithm of your preferred AI detection tool. The machine learning of the utilized software will be crucial in this case since automated scripts can only be stopped by state-of-the-art pattern recognition algorithms that have been modeled with an appropriately sized data sheet.
Concrete Actions for Complex Attacks
Credit card fraud detection programs score a consistently high detection rate of over 98% for organizations operating internationally. But how they work depends on your field of activity and the turnover of your business. Are you a business active in retail? In that case, the majority of breach incidents you will face will test the vigilance of your credit card fraud prevention systems. Are you, instead, a company active in healthcare or IT? If that’s the case, the majority of the challenges you’ll encounter will manifest as phishing attempts.
The fraud detection and credit card protection tool you use must ensure a multichannel approach for the security of your venture and incorporate AI algorithms in the fraud prevention techniques you utilize. From pattern analysis to IP geolocation, the success of the software you deploy will be determined by the flexibility of the detection methods and the ability of the application to be updated in line with market requirements. AI fraud detection programs are essential for companies operating internationally. And their use can be synonymous with the long-term success of your organization
