Data processing method and payment platform
A payment platform and data processing technology, applied in the field of communications, can solve the problems of fraudulently obtaining credit by falsifying data, difficult, and many restrictions.
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Embodiment 1
[0100] The embodiment of the present invention provides a data processing method, such as figure 1 As shown, the method is applied to the payment platform, and the method includes:
[0101] Step 101. Receive a first request from a first user, where the first request is generated based on a first payment required by the first user.
[0102] Here, the first user can refer to a user who applies for a loan, including two situations. 1) One is that the user needs to apply for a loan when the payment amount is not enough to participate in the actual transaction. 800 yuan, the debit card balance is not enough at this time, you need to apply for a loan to make up the difference of 800 yuan, the amount of the loan application is greater than or equal to 800 yuan; 2) The other is that the user also needs to apply when the user has nothing to do with the actual transaction For loans, for example, if you want to recharge your debit card or transfer money to other users, the transfer amou...
Embodiment approach 1
[0122] Step 201. Obtain a first data set f1 formed by mutual attention and / or interaction frequency between the associated user and the first user in at least one dimension.
[0123] Step 202. Detect whether the degree of mutual attention and / or interaction frequency in the first data set is higher than the preset first threshold, if yes, then satisfy the second preset condition, and execute step 203; otherwise, as an invalid user from the Deleted from the first data set f1 mentioned above.
[0124] Step 203: Determine associated users who meet the second preset condition as the valid users, update the first data set f1 to an updated data set f1', and the updated data set f1' is all valid users.
Embodiment approach 2
[0126] Step 301. Obtain a second data set f2 formed by the second credit value of the associated user. The second credit value is obtained according to the second behavior data of the associated user and the second cash flow record.
[0127] Step 302, detecting whether the second credit value in the second data set is higher than the preset second threshold value, if yes, satisfy the second preset condition, and execute step 303; otherwise, as an invalid user from the second Deleted from dataset f2.
[0128] Step 303: Determine the associated users satisfying the second preset condition as the valid users, update the second data set f2 to an updated data set f2', and the updated data set f2' is all valid users.
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