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BBD is the first domestic publisher of commercial big data industrial standard “COSR” in China.            This standard is dedicated to optimizing the efficiency and effectiveness of decision-making,            by standardizing data service and improving service levels.



In the purchase or use of data services, organizations and individuals need a proper data service framework to estimate what they are paying for.

A “proper framework” must: be unbiased; able to measure data services properly both in quantity and quality; be holistic and comprehensive, to avoid the missing of any relevant elements which may affect the effectiveness of a decision.

COSR Data Service Framework meets all criteria above. It standardizes the reliability, relevance to decision-making, and timeliness of data services and has made clear the compliance with relevant rules and regulations in the collection, storage, and analysis of data. What’s more, it has defined standards for data environment, data source, data technology, data application, and data security, strictly controlling the input and output of data servers entering data market, building a fortress for safe data usage and value iteration.

What is COSR?

COSR stands for “Council of Strategy Research”, a non-profit organization. This organization is dedicated to optimizing the efficiency and effectiveness of decision-making, by standardizing data services and raising service levels.

COSR Data Service Framework applies to all data-related industries, including asset evaluation, credit investigation services, credit rating, information platform, loan grading, industrial analysis, etc. Data service framework applies not only to the evaluation of data service companies, but also to data service units in a company.


How COSR works?

COSR data service framework provides data users with standards to estimate data services in three dimensions:

Dimension One: Objectives

Data services are designed to ensure the fulfillment of the following objectives:

  • Reliability of data report
                       including reliability, relevance to decision-making, and timeliness

  • Compliance with rules and regulations
                       in the collection, storage, and analysis of data

Dimension Two: Levels

Data service must be estimated on two levels:Data services must be appraised on two levels:

  • Organizational Level
                       a company or a data service unit.

  • Product Level

Dimension Three comprises five components of data service:
  • Data Environment

  • Data Source

  • Data Technology

  • Data Application

  • Data Security

*Data Environment

Data environment refers to the service awareness of a data service provider. Data environment defines the attitude of the management in a data service company, and affects employees’ data service awareness. This component is the basis for all other components of data services, and it sets the rules and structures.

*Data Source

Data sources provide the basic data for data services. This part is mainly concerned with the collection of data. The filtering, selection, elimination of privacy, estimation, storage and quality management of data are all necessary for a data service provider to ensure the accuracy, effectiveness, regulatory compliance of the data sources.

*Data Technology

Data technology talks about the basic data technologies for a data service provider to deliver data services. These technologies cover data collection, cleaning, storage, and analysis. These technologies guarantee the quality of data services in data quantity, data literacy, database extendibility, data extensibility and data reliability.

*Data Application

Data application refers to the presentation forms of data results. The forms should be designed according to clients’ usage patterns, including but not limited to written reports, data documents, computer applications, mobile apps, and web apps, etc.

*Data Security

The objective of data security is to establish a scientific standard system in identifying, estimating, and reducing the overall data security risk level of data service companies. This will lead to the standardization of industrial business operations and minimize the risk of information leakage and thus the loss of clients for a data service provider.