For mobile payment, both the transaction itself and the security and anti-fraud issues behind it cannot be separated from big data technology.
From the origin of big data and its current application in the United States, big data is just a type of technology, and data itself is a description of the development process of a thing. Take the growth process of tomatoes as an example. If we collect data at intervals from the time a seed is planted, we can try to grasp the data of all dimensions including water, light, biochemistry, etc. at each time point. At this time, if you want to know the details of a certain dimension at any time, just find the corresponding time slice directly. This kind of record and query itself will derive many functions and applications.
In the field of payment, using big data to realize anti-fraud behavior analysis is one of the commonly used technical means for payment risk prevention and control. Big data technology can help the system identify whether a payment card is owned by the owner of the card, and can easily detect fraud and other illegal activities, thereby greatly improving the security of payment transactions.
In addition, if the right entry point and method are found, the millions of seemingly ordinary transaction data generated by big data every day can become a treasure for merchants. With these data, not only can the anti-fraud and security of the payment business itself be improved, but they also play a huge role in optimizing products. Based on massive transaction data, system owners can also clearly know where the problem lies (payment platform or merchant).