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Financial atlas construction and analysis method for bank risk control

An analysis method and graph technology, applied in the field of data modeling of financial graphs, can solve problems such as exacerbated credit risk exposure, low efficiency, and huge time overhead for detecting guarantee rings, and achieve narrow traversal range, improve search efficiency, and improve analysis efficiency effect

Pending Publication Date: 2019-09-06
武汉观图信息科技有限公司
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Problems solved by technology

However, if the economy gradually declines, the negative impact of the guarantee ring will gradually be revealed, exacerbating the exposure of credit risks, and if it is not handled properly, it will easily lead to systemic financial risks
However, the traditional relational database management system (RDBMS) currently used by banks is not efficient in processing a large number of connection operations, and the time overhead in detecting guarantee rings is very huge, which cannot meet the needs of actual work

Method used

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  • Financial atlas construction and analysis method for bank risk control
  • Financial atlas construction and analysis method for bank risk control
  • Financial atlas construction and analysis method for bank risk control

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specific Embodiment approach

[0084] For the guarantee ring model, the most important thing is to find the guarantee ring. We can also use the graph query method described in 4.1 to search. The specific implementation is as follows:

[0085] Step 1: Understand the banking business and analyze the models it needs to find. As for the guarantee ring, what is reflected in the bank's business is the special interest body generated by mutual guarantee or chain guarantee between enterprises.

[0086] Step 2: According to the analysis in step 1, map each part of the analysis model with the graph data model. The main entities involved in the guarantee ring are the customer entity and the guarantee relationship, which correspond to the customer node and the guarantee relationship in the graph data model, and require that the starting point and the end point of the guarantee chain be consistent to form a guarantee ring. And the business is concerned with the length of the guarantee ring and the total guarantee amo...

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Abstract

The invention provides a bank financial atlas construction and analysis method. The method mainly comprises a financial atlas construction method and two typical analysis models based on financial atlass. The financial atlas construction method provides a universal bank data model with an atlas as a structure. The method mainly comprises three types of nodes of a bank, a client and a deposit account and five types of relations of transaction, guarantee, loan, correspondence and control among the nodes. The data in the bank relation database can be converted into the graph data, and a special graph database management system is adopted to store the graph data, so that the demand expression of associated data analysis is clearer, and the processing efficiency is greatly improved. The financial atlas analysis model comprises a consumer loan illegal entry real estate industry model and a guarantee ring model. According to the method, the analysis efficiency is effectively improved by usingtypical graph query and graph traversal modes respectively, required data can be quickly and accurately found out from massive bank data, and risk prevention of a bank and macroscopic decision of a bank supervision department are facilitated.

Description

technical field [0001] The invention belongs to the field of financial big data analysis, and in particular relates to data modeling of financial graphs and how to discover possible risks in massive bank data through financial graphs. Background technique [0002] The banking industry is a data-driven industry, and data has always been the key word in the development of bank informatization. The banking industry generates massive amounts of transaction data every day. According to research statistics, after years of development and accumulation, the data volume of domestic commercial banks has reached more than 100TB and is growing at a faster rate. [0003] Such a huge amount of data also brings great challenges to the data analysis departments of banks and their regulators. When the complexity of the data analysis task is relatively high, the calculation of massive data will lead to unbearable overhead. Taking the guarantee ring as an example, the guarantee ring refers ...

Claims

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Application Information

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IPC IPC(8): G06F16/36G06Q40/02
CPCG06Q40/02G06F16/367
Inventor 钟鸣
Owner 武汉观图信息科技有限公司
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