一种基于准实时效应的自动化模型框架及风险管控方法
本发明提供一种基于准实时效应的自动化模型框架及风险管控方法,属于风险管理技术领域,具体包括:变量池模块负责进行信贷用户的授信申请信息的信贷特征的提取得到变量池,准实时模型模块负责按照预设周期,基于变量池进行样本的准实时更新处理,并基于基础模型,利用对抗处理后的样本进行基础模型的增量训练,进行信贷模型的更新处理,当更新完成后,进行上线处理,数据监控模块负责在所述信贷模型中加入时间戳特征,利用时间戳特征分析信贷模型以及客群的变动趋势,提升了信贷模型的更新处理的及时性。 The invention provides an automatic model framework based on a qu...
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| Format | Patent |
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| Language | Chinese |
| Published |
26.08.2025
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| Subjects | |
| Online Access | Get full text |
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| Summary: | 本发明提供一种基于准实时效应的自动化模型框架及风险管控方法,属于风险管理技术领域,具体包括:变量池模块负责进行信贷用户的授信申请信息的信贷特征的提取得到变量池,准实时模型模块负责按照预设周期,基于变量池进行样本的准实时更新处理,并基于基础模型,利用对抗处理后的样本进行基础模型的增量训练,进行信贷模型的更新处理,当更新完成后,进行上线处理,数据监控模块负责在所述信贷模型中加入时间戳特征,利用时间戳特征分析信贷模型以及客群的变动趋势,提升了信贷模型的更新处理的及时性。
The invention provides an automatic model framework based on a quasi-real-time effect and a risk management and control method, and belongs to the technical field of risk management, and the method specifically comprises the steps: a variable pool module is responsible for carrying out the extraction of credit features of credit granting application information of credit users to obtain a variable pool, and a quasi-real-time model module is responsible for carrying out the extraction of credit granting application information according to a preset period; and the data monitoring module is responsible for carrying out quasi real-time updating processing on the samples based on the variable pool, carrying out incremental training on the basic model by utilizing the samples subject |
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| Bibliography: | Application Number: CN202510685946 |