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A cluster storage and analysis method for financial industry risk early warning

A cluster storage and risk early warning technology, applied in finance, data processing applications, instruments, etc., can solve the problems of overdue loans and non-performing loan ratios, excessive manual operations, deviation of credit investigation results, etc., to reduce redundant credit investigation Additional steps, expanded capacity, and reduced hardware pressure

Active Publication Date: 2022-08-09
JIANGSU UNIV +1
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  • Abstract
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  • Application Information

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Problems solved by technology

[0003] The study found that another reason for the double increase in overdue loans and non-performing loan ratios in the banking industry is that after obtaining credit data, there are too many manual operations, which leads to deviations in credit results and greatly reduces efficiency

Method used

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  • A cluster storage and analysis method for financial industry risk early warning
  • A cluster storage and analysis method for financial industry risk early warning

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Embodiment Construction

[0038] The present invention will be further described below in conjunction with the accompanying drawings.

[0039] The cluster storage module of the present invention is composed of three parts: an application server cluster, an intelligent storage server cluster, and a metadata server cluster.

[0040] Application server cluster: a cluster that runs client applications, performs cluster analysis and calculation, queries historical credit data in real time, and provides credit results for credit data with the same rating.

[0041]Intelligent storage server cluster: consists of 10 Gigabit storage servers. It stores the actual data of credit reporting users and is the storage resource provider of the entire distributed storage system. When the application server accesses data, the storage server cluster provides the actual data I / O service. The data I / O pressure can be very evenly distributed among the storage server clusters.

[0042] Metadata server cluster: consists of 1...

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Abstract

The invention discloses a cluster storage and analysis method for financial industry risk early warning. According to the analysis method set by the module, the result of credit investigation is obtained, which is pushed to the front desk for final confirmation, and the result of credit investigation is sent to the cluster storage module to generate historical information. When sending credit data of the same rating, the data analysis module does not need to analyze the newly sent credit data, and can quickly obtain credit results through the historical credit information in the storage module, effectively improving credit efficiency. The invention is a risk early warning processing method integrating cluster storage and cluster analysis. It can quickly process hundreds of millions of data, and provide comprehensive analysis to quickly obtain final analysis results.

Description

technical field [0001] The invention relates to the field of risk early warning and computer cluster analysis and storage, and is a new data processing mode that integrates data analysis and data storage, and directly feeds back analysis conclusions. Background technique [0002] In the era of the explosive development of big data, the amount of data in all walks of life has doubled, especially the development of big data led by the financial industry, which has subverted the working mode of the traditional financial industry. The study found that most banks have serious asset quality problems, with overdue loan balances and non-performing loan ratios both rising. In the final analysis, single credit data and backward risk management are the main reasons. Therefore, it is imperative to improve the existing risk early warning mechanism. At present, due to the pressure of excessive data volume, the financial industry has to lower the evaluation criteria of credit data, so as ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q40/02
CPCG06Q40/03
Inventor 王天宝孙昊王玉龙
Owner JIANGSU UNIV
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