Fighting fraud with machine learning

Machine learning can be used in many ways today and scientists are just limited by their imagination. Can the power of technology be strong enough to fight fraud?

Machine learning technique uses historical and live data to create patterns for customers’ behaviour. These patterns allow the system to make accurate fraud predictions.

Want to learn more? Read the in-depth article: Payment trends in 2017: Fighting fraud using machines

The system is now used to prevent, or at least limit, fraud attempts. It works similar to our brain, but using technology. It isn’t perfect, but, in many cases could solve lots of problems. And it’s one of the best methods you can leverage to grow your loyal customer base. It’s extremely helpful with multi channel payments when your customers pay on your website and via mobile devices.

Advanced algorithms evaluate every transaction for fraud risk and take appropriate action. The system creates deep profiles based on gathered data and analyses it to make the most accurate predictions and prevent fraud attempts.

A machine can check larger amounts of data in no time.

Machine learning integrates historical data with streaming information and is able to make the analysis in real-time. When a machine has more data, its accuracy will improve. To imagine how useful the machine-based process is, consider that a person could check just one transaction in about 5 minutes. A machine can check larger amounts of data in no time.

Sometimes genuine orders may be rejected because they aren’t tailored to the typical behaviour pattern. But, keep in mind that a machine learns from every transaction so it could be more accurate in the coming weeks.

Machine learning is a great solution, especially for large e-commerce businesses when speed and scale are paramount. The speed of fraud detection should also come with a high accuracy level.

The machine-based approach comes with smart automation and in the payment industry, it can be used to lower fraud attempts and make analyst’s life much easier. It also allows a look at more granular information a human being might miss when checking transactions manually.

The promise of machine learning is huge and, when done properly, could really help businesses grow and meet their goals. Computers are extremely precise, and with the larger number of patterns, the fraud detection will be more accurate.

The more data that is collected across historical transactions of many clients and industries, the better precision in fraud detecting. In all, it comes with lower costs by minimizing the expenses of manual reviews.

Learn more: Payment trends in 2017: Fighting fraud using machines

Originally published at on October 26, 2016.