CN114219199A - Supplier credit management method and supplier credit management system - Google Patents

Abstract

The invention relates to a supplier credit management method, which comprises the following steps: the supplier client sends a credit data reporting request to the web server and accesses the database; the database stores the credit data in a distributed manner; the enterprise client sends a supplier management request and accesses a database; the application server loads a visualization tool to process the credit data into one or more visual data of a credit portrait, a credit genealogy and a credit report, and the visualization tool is based on a browser/server mode. The method comprises the steps of processing and analyzing collected upstream and downstream supplier data based on a big data platform, constructing a supplier evaluation model, providing functions of supplier enterprise map, supplier association map, supplier credit analysis, supplier credit risk monitoring, monitoring report management and the like, judging the loyalty, performance capability and credit level of a supplier, and providing technical support for supplier management and bidding decision optimization.

Description

Supplier credit management method and supplier credit management system

Technical Field

The invention relates to the technical field of credit information management, in particular to a supplier credit management method and a supplier credit management system.

Background

In the equipment material purchasing management process, the credit management of the supplier is an important ring. With the development of an enterprise, the demand for credit management of suppliers is gradually increased, from the most basic loss avoidance demand to the stable increase of income, the maximization of income is further realized, and finally, the strategic goal of sustainable development is reached. As the roles and tasks to be undertaken for provider credit management continue to escalate, the complexity of the provider credit management system required varies. At present, the Chinese credit society is not completely established, the situation that information is not equal exists between a supplier and a purchasing party, and illegal violation information, punishment information and the like of the supplier have the problems of difficult collection, difficult recognition and the like.

Disclosure of Invention

Based on the above problems, the technical solution proposed by the present invention includes the following aspects:

in a first aspect, a supplier credit management method is provided, the method comprising the following steps: a supplier client sends a credit data reporting request to a web server, and the web server calls a relevant interface through a relevant IP address and token and accesses a database through an application server;

The database stores the credit data in a distributed manner;

the enterprise client sends a supplier management request to the web server, and the web server calls a relevant interface through a relevant IP address and token and accesses a database through an application server;

and the application server loads a visualization tool to process the credit data into one or more of credit portrait, credit genealogy and credit report, and sends the visual data to the web server through a corresponding interface, wherein the visualization tool is based on a browser/server mode.

In a second aspect, a supplier credit management system is provided, the system includes a plurality of servers in communication with each other to implement the supplier credit management method provided by the present invention.

In a third aspect. A credit service cloud platform is provided, and the credit service cloud platform supports the supplier credit management system provided by the invention.

The method is based on a big data platform to process and analyze the collected upstream and downstream supplier data, construct a supplier evaluation model, provide functions of supplier enterprise atlas, supplier association atlas, supplier credit analysis, supplier credit risk monitoring and monitoring report management and the like, judge the loyalty, performance capability and credit level of the supplier, and provide technical support for supplier management and bidding decision optimization.

Drawings

FIG. 1, a business flow diagram to which some embodiments are applied;

FIG. 2, a data structure diagram of a central region database of some embodiments;

fig. 3, a heartbeat transmission flow diagram of some embodiments.

Detailed Description

The supplier credit management method of some embodiments is applicable to the scenario of fig. 1, and includes the following steps:

the supplier client sends a credit data reporting request to the web server, and the web server calls a relevant interface through a relevant IP address and token and accesses the database through the application server;

the database stores the credit data in a distributed manner;

the enterprise client sends a supplier management request to the web server, and the web server calls a relevant interface through a relevant IP address and token and accesses the database through the application server;

the application server loads a visualization tool to process the credit data into one or more of credit portrait, credit genealogy and credit report, and sends the visual data to the web server through a corresponding interface, and the visualization tool is based on a browser/server mode.

Wherein the visualization tool is preferably a data analysis computer program product FineBI of sailsoftware ltd, which has a data processing module: preparing data, namely connecting a data source and carrying out ETL (extract transform and load) processing on certain data to establish a data service packet, wherein the process is finished by a system administrator; a visual analysis module: the metadata are processed in a self-service mode, the data are analyzed in a self-service mode, business personnel process and visually analyze the data through a dragging operation, a needed report is created, and the analysis appeal of the business personnel is achieved; sharing the shared module: sharing insight that people who accord with the authority can read reports shared by other people and conduct ad hoc analysis.

Some embodiments relate to a database structure comprising: the credit monitoring database comprises an enterprise registration information table, an enterprise master table, an enterprise tax data table and a change table which are connected on the right; the system also comprises a right-connected early warning item dictionary table, an industry group type dictionary table, an industry dictionary table, an enterprise evaluation word description dictionary table and a three-two-one industry dictionary table, wherein the early warning item dictionary table comprises date data; the enterprise registration information table comprises industrial group type data and industrial data, and the change table comprises three-two-one industrial data.

It should be noted that, the data layer forms a database from all data resources including credit data collected from the internal interface and the external interface, and is responsible for unified organization and management of data. The data layer is based on Spark analysis technology, Hbase, MongoDB, Redis database, Hive data warehouse and HDFS distributed file system, and is technically supported by a Hadoop big data platform.

The term "third-second-first industry" refers to structural relationships among third-third industry, the attributes of the first industry being taken from nature; the second industry is processing of products from nature; all the rest economic activities are integrated into the third industry.

Some embodiments relate more particularly to a database comprising a central region as in fig. 2, the central region comprising:

a basal region; pasting a source region; an atomic region; a common model region; sharing a summary area; collecting a city area; the basic area comprises main data, reference data and credit evaluation model data;

the method is based on a big data platform to realize a processing flow, and comprises the following steps:

the method comprises the steps that reported data are obtained through a supplier client and are accessed to a buffer base in a resource file mode;

acquiring acquired data through an external interface, and accessing the acquired data into a buffer library in a database form;

the loading buffer file system carries out structuralization processing on structured data and semi-structured and unstructured data in the reported data and/or the collected data and stores the structuralization data and the unstructured data into the source pasting area according to original semantics, structures and contents of the structuralization data;

processing the data stored in the pasting region through a zipper algorithm, a slicing algorithm and a distributed snapshot algorithm and then storing the data in an atomic region;

data stored in the atomic region are cleaned, converted, normalized and combined, organized according to a third normal model and stored in a public model region;

calculating data stored in the public model area through an application server to obtain a calculation result, and storing the calculation result in a public summary area;

And storing the data of the public summary area, the data of the public model area and the data of the atomic area into the urban area.

The term "source tile" primarily includes a data buffer that is consistent with the source system; the term "atomic region" encompasses a transaction that is a user-defined sequence of database operations that are either all done or not done, and that is an indivisible unit of work.

The data of the source data area enters the ground area through the data access function of the big data service platform, the data processing and circulation of the ground area and the center are realized through the data processing function of the big data service platform, the data of the center area is output through the service interface function of the big data service platform, and the whole process is carried out under the control of the data management and control system. The division enables the logic positioning of various data to be clearer, the flow direction and the relation to be more definite, and the whole data platform has better expandability, flexibility of theme release, diversified data analysis and safe data access control.

Relational databases are difficult to express by the requirement of a statement to enforce consistency on the data, and can only rely on transactions. However, because the embedded subdocuments can be designed in a denormalization mode, and the update specification can perform atomic operation on the subdocuments in a single record or the same record, the cloud development database does not need to use transactions under normal conditions.

The term "third paradigm" means that all data elements in the table must be uniquely identified by the primary key, and must be independent of each other without any other functional relationship; the third paradigm comprises a "BC" paradigm, which emphasizes that all attributes (including both primary and non-primary) in the relational schema R are completely dependent on the code or candidate key, and that there are no cases of transitive dependency.

Some embodiments relate to a database that uses MySQL-Proxy to implement database read-write separation. The MySQL master-slave cluster is constructed by adopting MySQL-Proxy, the Mysql master server is used for data writing operation through an Amoeba tool, and the Mysql slave server is used for data query operation.

The method according to some embodiments further monitors server conditions, task execution conditions, and enterprise client operation conditions, where the heartbeat transmission flow logic is as shown in fig. 3 (fig. is an embodiment adopting a Mina server architecture), and specifically includes the following steps: establishing timing heartbeats, collecting the running condition of a server corresponding to each heartbeat, and counting the execution condition of the current task, CPU occupation information, memory hard disk size information and system information; according to the corresponding configuration information, continuously sending a task request to the server; adjusting the frequency of the task request according to the result of the task request, if the acquisition task is sufficient, keeping the highest frequency to acquire the task, and if the acquisition task is insufficient, reducing the frequency of acquiring the task; and storing the configuration information to the local, and judging whether to acquire new text analysis configuration or not according to comparison between the configuration version of the locally stored configuration information and the configuration version in the acquisition task when analyzing the task information each time.

According to the method related to some embodiments, the size of the thread pool is dynamically allocated according to the number of the collection tasks, the running condition of the client and the control information of the server; and acquiring the thread by the single task, and releasing the thread after the execution is finished.

Some more specific embodiments develop a mobile phone application that includes an exemplary application system (vendor credit management system), a wechat applet to provide a vendor credit management system and a campus credit management system and a "credit loan" -financing delivery service system. The functional modules which can be realized by the designed application system and the mobile phone application comprise:

the function modules and menu functions of all subsystems are flexibly set through configuring a management module and a management system resource menu; configuring a management data dictionary and standardizing data entry; the system presets timing tasks of all functional modules and supports starting and stopping of project self-defined timing tasks; the interface style and elements of the project site self-defined platform are supported, interface logo pictures are uploaded through a system customization function, platform titles are modified, and the customization of the interface style and elements of the project site is achieved. Platform subsystems, modules, functions and resources are configured.

Data is divided into five regions according to the data flow direction and the served function:

1. Source data area

The method comprises various reported data (such as data reported by committee offices such as the government of Fujian province, the business office, the tax administration of the statistical office and the like) and external collected data. The source data area is not managed by the system, and data is accessed into the system through each subsystem. Wherein:

a. reporting data support interface mode and file mode, e.g. EXCEL data upload, webservice interface call

b. The collected data is not directly managed and is acquired by an interface or a database direct connection mode.

2. Floor area

Temporarily storing data obtained from a source data area through various system means, wherein the storage form comprises formatted data in a database and files (structured, semi-structured and unstructured) in a file system;

3. central zone

Is a core database (similar to a data warehouse structure) of the whole system, and can be divided into the following subareas:

c. basic area: data common to other sub-regions of the center, including main data, reference data (such as administrative divisions, industries, etc.), evaluation/evaluation models (model structures, indexes, parameters, etc.);

d. pasting a source region: directly carrying out necessary structural processing on structural data, semi-structural data and unstructured data of the floor area, storing the structural data, the semi-structural data and the unstructured data into the floor area as much as possible according to original semantics, structures and contents, and reorganizing the same semantic data in a pull chain table or a slice table mode;

e. Atomic region: carrying out necessary processing such as cleaning, conversion, normalization, combination and the like on the data of the source region, and organizing the data according to a normalized (basically, third normalized) model;

f. the common model area: according to a public service domain, processing such as splitting, merging and recombining atomic region data, and organizing and forming fact-dimension data of atomic granularity according to a star model of a classical data warehouse;

g. a common summary area: on the basis of the data of the public model area, carrying out statistics and summarization according to multiple dimensions such as company, region, industry, time, service type and the like to form a multi-level data cube;

h. urban area collection: aiming at different specific service applications, integrating relevant data of an atomic region, a public model region and a public summary region, and aiming at specific service application categories, forming a special data set through necessary processing such as merging, conversion, aggregation and the like, such as basic data mart, key industry mart, industry analysis mart and the like;

4. managing data area

The method is used for storing data for controlling data definition, acquisition, processing, storage, application and destruction of the whole life cycle, and specifically comprises the following steps:

i. data standard: defining the service domain/theme, classification, naming, semantics, format, value, management responsibility and the like of the data;

j. Metadata: i. service metadata: data sets, Chinese names, English names, standard classifications, business definitions, purposes, external reference definitions, topics to which data items belong, and the like of the data items; technical metadata: data sets, physical naming of data items, data type, length, precision, value range, reference data, etc.; managing metadata: origin, mouth, etc.;

k. data quality: the method comprises the steps of setting a universal quality rule, a task for checking by applying the quality rule, checking results and the like;

index system: the method comprises the steps of index definition, task generation definition and the like, wherein part of the content of the execution result of the index generation task enters a 'general index mart' in a central area;

5. a data service area:

and (3) organizing the data of the central area to form an exclusive data service area facing to a specific service scene, wherein the data in the area may or may not be overlapped with most of a certain centralized and urban area of the central area. In addition, the area is generally co-managed by the system and the service system. According to the requirements of the project of the current period, the local area may comprise public basic data, public supervision data, market public opinion data, enterprise evaluation, industry analysis, loss risk analysis and the like.

According to some embodiments, the cloud platform is built through the invention, and the cloud platform adopts a six-horizontal four-wing structure. From infrastructure, information resource, data level, service level, gateway level, show level, around the thread of "integration, analysis, application" with the credit, with the service intellectuality, management visualization, business coordination, resource centralization, information perception ization. Meanwhile, the platform provides various acquisition service interfaces, supports various data docking modes and calls data of all dimensions. Wherein, "six horizontal" refers to the layout of six levels as follows:

1. and (3) foundation construction: will be deployed on the platform.

2. Information resources: the information resources comprise basic information of enterprises, credit information, credit keeping information, loss information and other information. The system will construct a data layer based on the above information.

3. And (3) a data layer: the data layer forms a database with the information of the information resources, is responsible for unified organization and management of data, and provides data support for credit report management systems (credit evaluation management and automatic credit report systems), credit service systems, supplier credit management systems, park credit management systems, investment and financing systems and the like of the display layer.

4. And (3) a service layer: and the application scenes of the display layer are supported by a plurality of business micro-services of data processing, operation support, credit archives, credit evaluation, credit public sentiment and information management.

5. A gateway layer: the gateway layer provides API full-hosting service, rich API management functions and assists in managing large-scale APIs so as to reduce management cost and safety risks, and the gateway layer comprises functions of protocol adaptation, protocol forwarding, safety strategy, anti-brushing, flow, log monitoring and the like. And realizes the uniform authentication of the system through the filter.

6. A display layer: the construction comprises diversified service functions such as a credit information management system, an operation support system, a credit service system, a credit report management system (credit evaluation management and automatic credit report system), a supplier credit management system, a park credit management system, a credit loan-investment and financing service system and the like, and provides informatization application for development of credit service business. The platform can provide various credit services for users such as government departments, financial institutions, third-party institutions, enterprises and the like through access channels such as a credit portal hall, WeChat public numbers and the like.

Implementations and functional operations of the subject matter described in this specification can be implemented in: digital electronic circuitry, tangibly embodied computer software or firmware, computer hardware, including the structures disclosed in this specification and their structural equivalents, or combinations of more than one of the foregoing. Embodiments of the subject matter described in this specification can be implemented as one or more computer programs, i.e., one or more modules of computer program instructions encoded on one or more tangible, non-transitory program carriers, for execution by, or to control the operation of, data processing apparatus.

Alternatively or in addition, the program instructions may be encoded on an artificially generated propagated signal, e.g., a machine-generated electrical, optical, or electromagnetic signal, that is generated to encode information for transmission to suitable receiver apparatus for execution with a data processing apparatus. The computer storage medium may be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of one or more of the foregoing.

A computer program (which may also be referred to or described as a program, software application, module, software module, script, or code) can be written in any form of programming language, including compiled or interpreted languages, or declarative or procedural languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data, e.g., one or more scripts stored in: in a markup language document; in a single file dedicated to the relevant program; or in multiple coordinated files, such as files that store one or more modules, sub programs, or portions of code. A computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network.

Computers suitable for carrying out computer programs include, and illustratively may be based on, general purpose microprocessors, or special purpose microprocessors, or both, or any other kind of central processing unit. Typically, the central processing unit will receive instructions and data from a read-only memory or a random access memory or both. The essential elements of a computer are a central processing unit for executing or executing instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto optical disks, or optical disks. However, a computer need not have such a device. Further, the computer may be embedded in another apparatus, e.g., a mobile telephone, a Personal Digital Assistant (PDA), a mobile audio or video player, a game console, a Global Positioning System (GPS) receiver, or a removable storage device, e.g., a Universal Serial Bus (USB) flash drive, or the like. Computer readable media suitable for storing computer program instructions and data include all forms of non volatile memory, media and memory devices, including by way of example: semiconductor memory devices, such as EPROM, EEPROM, and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto-optical disks; CD-ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry. A computer may interact with a user by sending a document to a device used by the user and receiving the document from the device; for example, by sending a web page to a web browser on the user's client device in response to a request received from the web browser.

Implementations of the subject matter described in this specification can be implemented in a computing system that includes a back-end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front-end component, e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the subject matter described in this specification, or any combination of one or more such back-end, middleware, or front-end components. The components in the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network ("LAN") and a wide area network ("WAN"), e.g., the Internet. The computing system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

While this specification contains many specific implementation details, these should not be construed as limitations on the scope of any inventions or of what may be claimed, but rather as descriptions of features that may embody particular implementations of particular inventions. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination. Moreover, although features may be described above as acting in combination and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a subcombination or variation of a subcombination.

Similarly, while operations are depicted in the drawings in a particular order, this should not be understood as: such operations are required to be performed in the particular order shown, or in sequential order, or all illustrated operations may be performed, in order to achieve desirable results. In certain situations, multitasking and parallel processing may be advantageous. Moreover, the separation of various system modules and components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

Particular embodiments of the subject matter have been described. Other implementations are within the scope of the following claims. For example, the activities recited in the claims can be performed in a different order and still achieve desirable results. As one example, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In certain implementations, multitasking and parallel processing may be advantageous.

Claims (10)

1. A supplier credit management method, characterized in that it comprises the following steps: the supplier client reports the credit data to the web server, and the web server calls a relevant interface through a relevant IP address and token and accesses the database through the application server;

the database stores the credit data in a distributed manner;

the enterprise client sends a supplier management request to the web server, and the web server calls a relevant interface through a relevant IP address and token and accesses a database through an application server;

and the application server loads a visualization tool to process the credit data into one or more of credit portrait, credit genealogy and credit report, and sends the visual data to the web server through a corresponding interface, wherein the visualization tool is based on a browser/server mode.

2. The method of claim 1, wherein the database comprises a credit monitoring database comprising a right-connected business registry table, a business master table, a business tax data table, a change table; the system also comprises a right-connected early warning item dictionary table, an industry group type dictionary table, an industry dictionary table, an enterprise evaluation word description dictionary table and a three-two-one industry dictionary table, wherein the early warning item dictionary table comprises date data; the enterprise registration information table comprises industrial group type data and industrial data, and the change table comprises three-two-one industrial data.

3. The method of claim 2, wherein the database comprises a central region comprising:

a basal region; pasting a source region; an atomic region; a common model region; sharing a summary area; collecting a city area; the basic area comprises main data, reference data and credit evaluation model data.

4. The method of claim 3, further comprising the following steps implemented based on a big data platform:

acquiring reported data through the supplier client, wherein the reported data is accessed to a buffer library in a resource file form;

Acquiring collected data through an external interface, wherein the collected data is accessed to the buffer library in a database form;

a loading buffer file system carries out structuralization processing on structured data and semi-structured and unstructured data in the reported data and/or the acquired data and stores the structuralization processing into the source region according to original semantics, structure and content of the structuralization processing;

processing the data stored in the pasting region by a zipper algorithm, a slicing algorithm and a distributed snapshot algorithm and then storing the processed data in the atomic region;

data stored in the atomic region are cleaned, converted, normalized and combined, organized according to a third normal model and stored in the public model region;

calculating data stored in the public model area through the application server to obtain a calculation result, and storing the calculation result in the public summary area;

and storing the data of the public summary area, the data of the public model area and the data of the atomic area to the urban collection area.

5. The method of claim 3, further comprising the steps of: the MySQL master-slave cluster is constructed by adopting MySQL-Proxy, the Mysql master server is used for data writing operation through an Amoeba tool, and the Mysql slave server is used for data query operation.

6. The method of claim 4, wherein the database is based on a Hadoop technology framework, enabling distributed storage of data by using a HDFS component.

7. The method of claim 6, further comprising monitoring server conditions, task execution conditions, and the enterprise client operational conditions, including the steps of:

establishing timing heartbeats, collecting the running condition of a server corresponding to each heartbeat, and counting the execution condition of the current task, CPU occupation information, memory hard disk size information and system information; according to the corresponding configuration information, continuously sending a task request to the server;

adjusting the frequency of the task request according to the result of the task request, if the acquisition task is sufficient, keeping the highest frequency to acquire the task, and if the acquisition task is insufficient, reducing the frequency of acquiring the task;

and storing the configuration information to the local, and judging whether to acquire new text analysis configuration or not according to comparison between the configuration version of the locally stored configuration information and the configuration version in the acquisition task when analyzing the task information each time.

8. The method of claim 6, further comprising the steps of:

Dynamically allocating the size of a thread pool according to the number of the collection tasks, the running condition of the client and the control information of the server;

and acquiring the thread by the single task, and releasing the thread after the execution is finished.

9. A supplier credit management system, characterised in that it comprises a plurality of servers in communication with each other for carrying out all the steps of the method according to claims 1-8.

10. A credit services cloud platform, characterized in that the credit services cloud platform support comprises the system of claim 9.

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