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Implementation and Delivery
Case details

Intelligence Big Data Analysis Platform of an Urban Commercial Bank

With the transformation and development of the big retail in the banking industry, the data-based operation capability will become the core competitiveness of credit card risk management and customer operations. Building a business-oriented data base and a comprehensive data system architecture is a basic task, the solid foundation for the bank’s strategic decisions, operation management and risks control and also an important prerequisite for supporting banks to achieve the data-based intelligence operations.

Intelligence Big Data Analysis Platform of an Urban Commercial Bank

With the transformation and development of the big retail in the banking industry, the data-based operation capability will become the core competitiveness of credit card risk management and customer operations. Building a business-oriented data base and a comprehensive data system architecture is a basic task, the solid foundation for the bank’s strategic decisions, operation management and risks control and also an important prerequisite for supporting banks to achieve the data-based intelligence operations.
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Target Demands

An all-process data indicator system should be constructed based on the big data platform of the bank.

The data indicators should be flexibly configured and managed, and the indicators of the bank should be processed through the business configuration to improve the accessibility of rules configuration and process efficiency.
The business indicator design should be standardized.
The indicators should be uniformly managed by classification, and the indicator system based on different dimensions such as risk, marketing, customers and products should be uniformly arranged.
Reasonable hierarchical division; indicator data with different time granularity and period in the model should be saved.

Target Demands

An all-process data indicator system should be constructed based on the big data platform of the bank.

The data indicators should be flexibly configured and managed, and the indicators of the bank should be processed through the business configuration to improve the accessibility of rules configuration and process efficiency.
The business indicator design should be standardized.
The indicators should be uniformly managed by classification, and the indicator system based on different dimensions such as risk, marketing, customers and products should be uniformly arranged.
Reasonable hierarchical division; indicator data with different time granularity and period in the model should be saved.
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Solutions

Based on Rivere’s AnyAST real-time big data intelligence analysis work platform and the credit card core data model, the credit card data indicator system was uniformly planned and designed, and the overall logical structure centering on the credit card data model was established to achieve the unification and integration of credit card data indicators and effectively support relevant data such as data report, modeling and regulatory submission.
Through data structure design, the data application scenes were established, and the data was deeply mined, analyzed and processed to develop a data application system, and process and layer the results of the analyzed data. The processed theme data was applied to data application platforms such as big data decision service, big data user portrait, intelligence data report and big data intelligence modeling.

Solutions

Based on Rivere’s AnyAST real-time big data intelligence analysis work platform and the credit card core data model, the credit card data indicator system was uniformly planned and designed, and the overall logical structure centering on the credit card data model was established to achieve the unification and integration of credit card data indicators and effectively support relevant data such as data report, modeling and regulatory submission.
Through data structure design, the data application scenes were established, and the data was deeply mined, analyzed and processed to develop a data application system, and process and layer the results of the analyzed data. The processed theme data was applied to data application platforms such as big data decision service, big data user portrait, intelligence data report and big data intelligence modeling.
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Value and Significance

The practical application value of financial data was improved, and the bank’s digital operation was enhanced, boosting the improvement of risk control, operation capabilities and efficiency.
The key to the construction of business-oriented data indicator system is to achieve the logical concentration, integration, sharing and use of business data, which can quickly improve the efficiency and learning speed of risk and market analysis, and strengthen the data operation capability so as to improve the risk control and marketing capabilities, optimize resource allocation and achieve the sustainable scientific development.
For the refined operation of data, the complete and detailed basic data support is provided to drive the rapid iteration of business with data.

Value and significance

The practical application value of financial data was improved, and the bank’s digital operation was enhanced, boosting the improvement of risk control, operation capabilities and efficiency.
The key to the construction of business-oriented data indicator system is to achieve the logical concentration, integration, sharing and use of business data, which can quickly improve the efficiency and learning speed of risk and market analysis, and strengthen the data operation capability so as to improve the risk control and marketing capabilities, optimize resource allocation and achieve the sustainable scientific development.
For the refined operation of data, the complete and detailed basic data support is provided to drive the rapid iteration of business with data.
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联系方式

邮箱地址:
market@riveretech.com
公司地址:
北京市朝阳区望京北路16号中材国际大厦三层

北京江融信科技 2014-2022 © 版权所有 京ICP备15040770号