Training method and device of customer contact loss identification model, customer contact loss identification method and device, electronic equipment and computer program product

By training the customer missing contact recognition model, using multi-stage missing contact confirmation strategies and multi-dimensional feature data, we automatically identify and mark missing customers, solving the problems of low efficiency and high cost of customer missing contact recognition in the existing technology, and achieving more efficient collection resource use and identification efficiency.

CN119919222APending Publication Date: 2025-05-02中国邮政储蓄银行股份有限公司
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Patent Information

Application Number
CN202411828452.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-12
Publication Date
2025-05-02

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Abstract

The invention discloses a training method and device of a customer contact loss identification model, a customer contact loss identification method and device, electronic equipment and a computer program product. The training method comprises the steps that information such as contact information of a to-be-confirmed contact loss customer is acquired; according to the contact way of the to-be-confirmed lost customer and the multi-stage lost confirmation strategy, determining the lost customer and marking a corresponding lost tag; obtaining multi-dimensional feature data of a lost customer and a non-lost customer; and according to the multi-dimensional feature data of the lost clients and the non-lost clients and the corresponding labels, training a client lost identification model. According to the method, the lost customer can be automatically identified and marked by using the multi-stage lost confirmation strategy, the customer lost identification model is trained according to the accumulation of the marking data in combination with the multi-dimensional feature information of the customer, whether the customer has the lost risk or not is predicted in advance by using the model, the lost identification efficiency is improved, and the user experience is improved. And timely contact with the customer who may lose contact is facilitated, and the utilization rate of collection resources in post-loan management is improved.
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