Bank customer data processing method and device

A technology of customer data and processing methods, applied in the field of data analysis, can solve problems such as complex customer consumption behavior, poor classification accuracy and reliability, and achieve the effects of improving feature learning ability, improving accuracy and reliability, and cost efficiency

CN111984842APending Publication Date: 2020-11-24BANK OF CHINA
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2020-11-24

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Abstract

The invention discloses a bank customer data processing method and device. The method comprises the following steps: obtaining bank customer data which comprises one or any combination of personal data, transaction data and behavior data; and classifying the bank customer data according to the bank customer data and a pre-established classification model, wherein the classification model is pre-established according to a plurality of trained machine learning models, the plurality of trained machine learning models are selected from a machine learning model set by using a genetic algorithm, each trained machine learning model in the machine learning model set is provided with different hyper-parameters, and each machine learning model is trained according to historical data of bank customers. According to the invention, bank customer data can be processed conveniently, and high-accuracy and high-reliability customer data classification is realized.
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Description

technical field

[0001] The invention relates to the technical field of data analysis, in particular to a bank customer data processing method and device. Background technique

[0002] Commercial banks have a large number of customers, and different customers have huge differences in consumption habits, consumption behaviors, and consumption capabilities. In order to provide each customer with more targeted and personalized services, commercial banks need to conduct customer analysis based on customer behavior, value and other data. Classification and refined management.

[0003] With the increase in the number of commercial bank customers, customer consumption behavior is extremely complex, and the amount of data is increasing over time. The existing clustering algorithm or manual classification method can no longer meet the requirements of commercial banking for customer data classification results. , there is a problem of poor classification accuracy and reliability. [...

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Embodiment Construction

[0018] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings. Here, the exemplary embodiments and descriptions of the present invention are used to explain the present invention, but not to limit the present invention.

[0019] First of all, the nouns involved in the embodiments of this application are introduced:

[0020] lightgbm model: The lightgbm model is a gradient boosting framework proposed by Microsoft, using a tree-based learning algorithm. The model is fast, accurate and can handle large-scale data.

[0021] Customer group classification: Customer group classification refers to the behavior of classifying customers with similar behavior characteristics and value characteristics into the same group according to certain standards.

[0022] xgboost model: The xgboost model i...