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Borrowing amount prediction method and device, server and storage medium

A prediction method and server technology, applied in the field of big data, can solve problems such as large errors, achieve the effect of improving randomness, optimizing user borrowing experience, and improving user borrowing efficiency

Inactive Publication Date: 2019-05-07
SHENZHEN LEXIN SOFTWARE TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] At present, the difficulty of directly predicting the user's loan amount is: predicting the amount of each loan of the user is different from predicting the total amount of the user's monthly loan, quarterly total, and annual total, which has great randomness and volatility, and the prediction results often have errors. very big

Method used

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  • Borrowing amount prediction method and device, server and storage medium
  • Borrowing amount prediction method and device, server and storage medium
  • Borrowing amount prediction method and device, server and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0056] figure 1 It is a flow chart of the loan amount prediction method provided in Embodiment 1 of the present invention. This embodiment is applicable to the situation of predicting the loan amount. This method can be executed by the loan amount prediction device provided in the embodiment of the present invention. The device can use software and and / or implemented in hardware, and integrated into a device that executes the method. In this embodiment, the device that executes the method may be any smart terminal or server that supports online services. refer to figure 1 , the method specifically includes the following steps:

[0057] Step 110, generating user loan characteristic data according to the user's loan information;

[0058] Specifically, the user's loan information includes, but is not limited to, the borrower's loan order data, data related to user identity information, user historical consumption habit data, and user historical loan record data as sample data. S...

Embodiment 2

[0111] The loan amount prediction device provided in the embodiments of the present invention can execute the loan amount prediction method provided in any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method. Figure 4 It is a schematic structural diagram of a loan amount prediction device provided in Embodiment 2 of the present invention. Such as Figure 4 As shown, the device may include:

[0112] A data generating unit 410, configured to generate user loan characteristic data according to the user's loan information;

[0113] The model input unit 420 is used to input the loan feature data into the pre-trained loan proportion prediction model, and output multiple probability values ​​corresponding to different loan proportions of the user. the percentage of the available borrowing amount;

[0114] A ratio confirmation unit 430, configured to confirm the optimal loan ratio according to the multiple p...

Embodiment 3

[0147] Figure 5 A schematic structural diagram of a server provided by Embodiment 3 of the present invention, such as Figure 5 As shown, the server includes a processor 510, a memory 520, an input device 530, and an output device 540; the number of processors 510 in the server can be one or more, Figure 5 Take a processor 510 as an example; the processor 510, memory 520, input device 530 and output device 540 in the server can be connected by bus or other methods, Figure 5 Take connection via bus as an example.

[0148] The memory 520, as a computer-readable storage medium, can be used to store software programs, computer-executable programs and modules, such as the program instructions / modules corresponding to the loan amount prediction method in the embodiment of the present invention (for example, the loan amount prediction device in the data generation unit 410, model input unit 420, proportion confirmation unit 430, amount confirmation unit 440). The processor 510 ...

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Abstract

The invention discloses a borrowing amount prediction method and device, a server and a storage medium. The method comprises the steps of generating user borrowing characteristic data according to borrowing information of a user; Inputting the user borrowing characteristic data into a pre-trained borrowing proportion prediction model, and outputting a plurality of probability values correspondingto different borrowing proportions of the user, the borrowing proportion being the proportion of the user borrowing amount in the remaining available borrowing amount of the user; Determining an optimal borrowing proportion according to the plurality of probability values, wherein the optimal borrowing proportion is a user borrowing proportion corresponding to the maximum probability value; And determining the current borrowing amount of the user according to the optimal borrowing proportion. According to the borrowing amount prediction method, the problem that single borrowing amount prediction has great randomness and volatility is improved, the user borrowing experience is optimized, the user borrowing efficiency is improved, and single borrowing earnings are increased.

Description

technical field [0001] Embodiments of the present invention relate to big data technology, and in particular to a loan amount prediction method, device, server, and storage medium. Background technique [0002] Users generate a large amount of user behavior data on the Internet, how to make user data generate value is currently a hot topic in the industry. By using data analysis, data modeling, data operation, and data-driven methods, the purpose of optimizing business and improving business benefits can be achieved. [0003] In the Internet financial platform, users need to fill in the amount of borrowing by themselves, resulting in poor borrowing experience for users. At the same time, in order to obtain higher returns, it is hoped that the user's single loan amount should be as high as possible. In order to provide better services to users, the enterprise will predict the user's loan amount, based on the predicted user loan amount, recommend the user's loan amount, impr...

Claims

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Application Information

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IPC IPC(8): G06Q40/02G06Q10/04
Inventor 雒航通程佳宇
Owner SHENZHEN LEXIN SOFTWARE TECH CO LTD
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