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Risk model training method and device, computer equipment and readable storage medium

A training method and risk model technology, applied in computer parts, calculation, character and pattern recognition, etc., can solve problems such as poor accuracy, illegal user utilization, and strict risk rule formulation, to avoid hysteresis and risk identification. Efficient and accurate results

Pending Publication Date: 2021-07-20
PINGAN YIQIANBAO E COMMERCE CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a risk model training method, device, computer equipment and readable storage medium, which are used to solve the current identification of risk problems existing in the prior art. Not only the risk identification efficiency is low, the accuracy is poor, and it is very It is easy to become a loophole for illegal users to exploit. At the same time, because the risk rules are too strict, it is easy to identify normal users as risky users, which makes it difficult for the service system to operate normally.

Method used

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  • Risk model training method and device, computer equipment and readable storage medium
  • Risk model training method and device, computer equipment and readable storage medium
  • Risk model training method and device, computer equipment and readable storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0058] see figure 1 , a risk model training method of this embodiment, comprising:

[0059] S101: Obtain long-term historical data through preset long-term extraction rules, and obtain recent historical data through preset recent extraction rules.

[0060] S102: Summarize the long-term historical data and the recent historical data to obtain comprehensive training data.

[0061] S106: Adjust the data volume of the long-term historical data and the recent historical data in the comprehensive training data, and adjust the sum of the long-term positive samples and the recent positive samples in the comprehensive training data, and the long-term negative samples in the comprehensive training data. The positive and negative ratio between the sample and the sum of recent negative samples to obtain comprehensive adjusted data.

[0062] S107: Obtain an initial intelligent model, and train the initial intelligent model through the comprehensive adjustment data to obtain a mature mode...

Embodiment 2

[0071] This embodiment is a specific application scenario of the first embodiment above. Through this embodiment, the method provided by the present invention can be described more clearly and specifically.

[0072] Next, in the server running the risky model training method, the comprehensive adjustment data is obtained by obtaining the long-term historical data and the recent historical data and adjusting them, and then the mature model is obtained by training the initial intelligent model through the comprehensive adjustment data. An example is used to describe the method provided in this embodiment in detail. It should be noted that this embodiment is only exemplary, and does not limit the protection scope of the embodiment of the present invention.

[0073] figure 2 A schematic diagram of an environment application of the risk model training method according to Embodiment 2 of the present application is schematically shown.

[0074] In an exemplary embodiment, the serv...

Embodiment 3

[0252] see Figure 4 , a risk model training device 1 of this embodiment, comprising:

[0253] The data extraction module 11 is used to obtain long-term historical data through preset long-term extraction rules, and obtain recent historical data through preset recent extraction rules;

[0254] Data summary module 12, is used for collecting described long-term historical data and described short-term historical data to obtain comprehensive training data;

[0255]The data adjustment module 16 is used to adjust the data volume of the long-term historical data and the recent historical data in the comprehensive training data, and adjust the sum of the long-term positive samples and the recent positive samples in the comprehensive training data, which is consistent with the comprehensive training data. The positive and negative ratio between the sum of the long-term negative samples and the recent negative samples in the data, to obtain the comprehensive adjusted data;

[0256] T...

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Abstract

The invention relates to the field of business security of computer security, and discloses a risk model training method and device, computer equipment and a readable storage medium, and the method comprises the steps: obtaining long-term historical data through a long-term extraction rule, and obtaining recent historical data through a recent extraction rule; summarizing the long-term historical data and the recent historical data to obtain comprehensive training data; adjusting data volumes of long-term historical data and short-term historical data in the comprehensive training data, and adjusting a positive-negative proportion between a sum of a long-term positive sample and a short-term positive sample in the comprehensive training data and a sum of a long-term negative sample and a short-term negative sample in the comprehensive training data to obtain comprehensive adjustment data; and training the initial intelligent model through comprehensive adjustment data to obtain a mature model. The invention further relates to a block chain technology, and information can be stored in a block chain node. According to the invention, the risk identification efficiency is high, the accuracy is high, and the problems that experience and rules become vulnerabilities and normal users are identified as risk users are avoided.

Description

technical field [0001] The present invention relates to the technical field of computer security business security, in particular to a risk model training method, device, computer equipment and readable storage medium. Background technique [0002] With the continuous development of Internet technology, major financial and technology companies have launched Internet wealth management products through APPs that are closer to the lives of ordinary people. Compared with traditional stock funds and securities, Internet wealth management products have unique advantages and are especially suitable for this market. Young people with little money and high liquidity are deeply loved by young people. [0003] However, Internet wealth management products face some risks that cannot be ignored, such as: identity theft for registration, stealing other people’s account transactions, and users being cheated, etc. Since the operation of Internet wealth management products is generally only ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q40/06G06K9/62
CPCG06Q40/06G06F18/214
Inventor 胥嘉栋胡明荣傅群慧朱尧
Owner PINGAN YIQIANBAO E COMMERCE CO LTD
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