CN111582643A - Method, device and equipment for collecting enterprise risk information - Google Patents

Method, device and equipment for collecting enterprise risk information Download PDF

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Publication number
CN111582643A
CN111582643A CN202010269228.6A CN202010269228A CN111582643A CN 111582643 A CN111582643 A CN 111582643A CN 202010269228 A CN202010269228 A CN 202010269228A CN 111582643 A CN111582643 A CN 111582643A
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enterprise
information
enterprise risk
entity
risk information
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张�杰
于皓
邓礼志
吴信东
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Beijing Mininglamp Software System Co ltd
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Beijing Mininglamp Software System Co ltd
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    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/03—Credit; Loans; Processing thereof

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Abstract

A method, apparatus, device and computer-readable storage medium for enterprise risk information collection, wherein the method comprises: acquiring data of an enterprise to be researched and researched from various heterogeneous data sources; extracting enterprise risk information from the data of the enterprise to be researched and researched according to a preset template, wherein the enterprise risk information comprises entity information and event information; and carrying out entity fusion and association on the enterprise risk information to generate an enterprise risk knowledge graph. The method and the device integrate data of various heterogeneous data sources in an entity and event mode, can display the data in a visual mode, and are convenient for a user to make risk decisions.

Description

Method, device and equipment for collecting enterprise risk information
Technical Field
The present disclosure relates to the field of risk research, and more particularly, to a method, an apparatus, a device, and a computer-readable storage medium for enterprise risk information collection.
Background
Along with the increase of the economic quantity of China, the credit requirements of medium and small enterprises in various industries are rapidly developed, and financial institutions generally pay attention to how to effectively identify the credit risk of the medium and small enterprises.
The related technology mainly collects registration information, share right information, operation and flow information and the like of the enterprises in a mode of dispatching a special person to the location of the enterprises for full-time investigation, the data scale is limited, the data type is fixed, and decision judgment depends on subjective experience of wind control experts.
Disclosure of Invention
A method, apparatus, device and computer-readable storage medium for enterprise risk information collection are provided to collect enterprise risk information through multiple data sources.
The embodiment of the application provides a method for collecting enterprise risk information, which comprises the following steps:
acquiring data of an enterprise to be researched and researched from various heterogeneous data sources;
extracting enterprise risk information from the data of the enterprise to be researched and researched according to a preset template, wherein the enterprise risk information comprises entity information and event information;
and carrying out entity fusion and association on the enterprise risk information to generate an enterprise risk knowledge graph.
The embodiment of the present application further provides a device for collecting enterprise risk information, including:
the acquisition module is used for acquiring data of an enterprise to be investigated from various heterogeneous data sources;
the extraction module is used for extracting enterprise risk information from the data of the enterprise to be researched according to a preset template, wherein the enterprise risk information comprises entity information and event information;
and the fusion association module is used for performing entity fusion and association on the enterprise risk information to generate an enterprise risk knowledge graph.
The embodiment of the present application further provides an enterprise risk information collecting device, including: memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the method of enterprise risk information collection when executing the program.
Embodiments of the present application further provide a computer-readable storage medium storing computer-executable instructions for performing the method for collecting enterprise risk information.
Compared with the related art, the embodiment of the application comprises the following steps: acquiring data of an enterprise to be researched and researched from various heterogeneous data sources; extracting enterprise risk information from the data of the enterprise to be researched and researched according to a preset template, wherein the enterprise risk information comprises entity information and event information; and carrying out entity fusion and association on the enterprise risk information to generate an enterprise risk knowledge graph. The method and the device integrate data of various heterogeneous data sources in an entity and event mode, can display the data in a visual mode, and are convenient for a user to make risk decisions.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the application. Other advantages of the present application may be realized and attained by the instrumentalities and combinations particularly pointed out in the specification and the drawings.
Drawings
The accompanying drawings are included to provide an understanding of the present disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the examples serve to explain the principles of the disclosure and not to limit the disclosure.
FIG. 1 is a flow chart of a method of enterprise risk information collection according to an embodiment of the present application;
fig. 2 is a schematic composition diagram of an enterprise risk information collecting apparatus according to an embodiment of the present application.
Detailed Description
The present application describes embodiments, but the description is illustrative rather than limiting and it will be apparent to those of ordinary skill in the art that many more embodiments and implementations are possible within the scope of the embodiments described herein. Although many possible combinations of features are shown in the drawings and discussed in the detailed description, many other combinations of the disclosed features are possible. Any feature or element of any embodiment may be used in combination with or instead of any other feature or element in any other embodiment, unless expressly limited otherwise.
The present application includes and contemplates combinations of features and elements known to those of ordinary skill in the art. The embodiments, features and elements disclosed in this application may also be combined with any conventional features or elements to form a unique inventive concept as defined by the claims. Any feature or element of any embodiment may also be combined with features or elements from other inventive aspects to form yet another unique inventive aspect, as defined by the claims. Thus, it should be understood that any of the features shown and/or discussed in this application may be implemented alone or in any suitable combination. Accordingly, the embodiments are not limited except as by the appended claims and their equivalents. Furthermore, various modifications and changes may be made within the scope of the appended claims.
Further, in describing representative embodiments, the specification may have presented the method and/or process as a particular sequence of steps. However, to the extent that the method or process does not rely on the particular order of steps set forth herein, the method or process should not be limited to the particular sequence of steps described. Other orders of steps are possible as will be understood by those of ordinary skill in the art. Therefore, the particular order of the steps set forth in the specification should not be construed as limitations on the claims. Further, the claims directed to the method and/or process should not be limited to the performance of their steps in the order written, and one skilled in the art can readily appreciate that the sequences may be varied and still remain within the spirit and scope of the embodiments of the present application.
The related art does not fully utilize or even completely ignore massive information from the internet, and public opinion information about a business or high management of the business can expose the default risk of the business credit in advance. And the related art lacks an effective utilization means for the above information.
As shown in fig. 1, an embodiment of the present application provides a method for collecting enterprise risk information, including:
step 101, obtaining data of an enterprise to be researched and researched from various heterogeneous data sources.
The data of the enterprise to be researched may include the following three types of data of the enterprise to be researched and its high administration:
1. internet information:
news portal sites and social self-media sites can periodically acquire news and public opinion information about enterprises and high governance thereof every day.
2. Three-party information:
and acquiring enterprise share relations, supply chain relations, fund traffic relations and high-management social relations from an authoritative third-party data company.
3. Internal information:
the information held by the financial institution and the investigated enterprise may include: historical overdue bad account information, enterprise registration information, industry properties, industry competitive products, market share, capital exchange, human resources, fixed assets, customer relations, business conditions, and the like.
In this step, data cleaning may be performed on the acquired data, that is, data is rechecked and verified, which is used to delete duplicate information, correct existing errors, and provide data consistency, which may include checking data consistency, processing invalid values and missing values, and the like.
Step 102, enterprise risk information is extracted from the data of the enterprise to be researched and researched according to a preset template, wherein the enterprise risk information comprises entity information and event information.
The step realizes information extraction, and extracts corresponding segments according to a preset template.
In an embodiment, the preset template includes an entity class template and an event class template, in this step, entity information is extracted from the data of the enterprise to be researched according to the entity class template, and event information is extracted from the data of the enterprise to be researched according to the event class template.
In an embodiment, the template may include:
1. entity class template:
(1) enterprise template
Wherein, the enterprise template can include: enterprise name, registered capital fund, registered place, legal representative, affiliated industry, operation range, financing round, current valuation and the like;
(2) high pipe formwork
Wherein, the high pipe template can include: name, job title, academic calendar, working year, company of business once offered, etc.;
2. event class template:
(1) administrative penalty events
Wherein, the administrative penalty event may include: jurisdictions, penalty reasons, penalty amounts, and the like.
(2) Financing and purchasing event
Among other things, financing and purchasing events may include: enterprise name, financing amount, financing turn, financing share ratio, investor, etc.
(3) Bid winning event
Wherein, the bid winning event may include: bidding enterprises, bidding projects, bidding quota, bidding enterprises, etc.
(4) Risk liability identification event
Wherein the risk liability determination event may include: enterprise name, involved amount, examiner, guarantor, region, industry, etc.
And 103, carrying out entity fusion and association on the enterprise risk information to generate an enterprise risk knowledge graph.
The step realizes information fusion, and the enterprise information can be uniformly stored in a graph database and subjected to entity fusion and association.
Where "fusion" refers to two or more entities extracted from different data sources, if referring to the same entity, they are merged.
In this embodiment, "fusing" includes identifying the enterprise risk information and merging the same entities in the enterprise risk information.
"associated" refers to two elements contained in two different entities or events, which are associated if the two elements are associated.
In this embodiment, "associating" includes identifying the enterprise risk information, and recording an association relationship between different entities in the enterprise risk information.
In one embodiment, the identifying the enterprise risk information may include:
1. accurate identification
And determining a corresponding entity according to the elements in the enterprise risk information.
Wherein, a certain element can accurately locate a certain entity, such as: the corresponding enterprise can be determined according to the organization code of the enterprise, and the corresponding high management can be determined according to the identification number of the personnel.
2. Fuzzy recognition
And calculating the similarity among the entities in the enterprise risk information, and determining whether the entities are the same entities according to the similarity.
And calculating the similarity between the two entities according to a preset algorithm, and determining that the two entities are the same entity after the similarity is higher than a preset similarity threshold.
For example, the similarity between two entities can be calculated using decision trees, conditional random fields, neural networks, and the like.
And generating an enterprise risk knowledge graph according to the entity and the incidence relation.
The enterprise risk information after entity fusion and association may be stored in an enterprise risk database.
In an embodiment, after step 103, the method further includes:
and displaying all or part of the enterprise risk knowledge graph according to the acquired display instruction.
The step can realize map visualization, and the enterprise risk database (also called a risk-to-public database) can be embedded into a risk-to-public examination and approval system of a financial institution in a visualized form and is used by risk examination and approval personnel in a man-machine interaction mode.
Wherein, can adopt the show mode to include:
1. only see a certain relation diagram
And displaying a relation diagram appointed in the enterprise risk knowledge graph according to relation selection information carried in a display instruction. Such as a equity relationship graph, a fund-to-business relationship graph, an event relationship graph, etc.
The relationship selection information includes information on a selected relationship, such as a equity relationship, a money-to-and-go relationship, an event relationship, and the like.
2. An overlay relationship chart showing two or more relationships overlaid together
And displaying a plurality of relation superposed graphs appointed in the enterprise risk knowledge graph according to the relation selection information carried in the display instruction. For example, the stock right relationship diagram and the fund to-and-fro relationship diagram are superposed for displaying.
The relationship selection information includes information of two or more selected relationships.
3. Rule cutting picture
And displaying a cutting graph of the specified rule in the enterprise risk knowledge graph according to the query rule information carried in the display instruction.
Under the condition of the display mode, an approver inputs a certain query rule, and the map only displays the result meeting the requirement, such as: the method comprises the steps of "a fund relationship graph with the amount larger than 500 ten thousand in one month", "credit enterprises with share right relationship approved by the same examiner in the past half year", and the like.
The embodiment of the application integrates data of various heterogeneous data sources in a mode of entity and event, can display various relation data in an interactive and visual mode, and is convenient for a user to make risk decision.
As shown in fig. 2, an embodiment of the present application further provides an apparatus for collecting enterprise risk information, including:
the acquisition module 21 is configured to acquire data of an enterprise to be investigated from multiple heterogeneous data sources;
an extraction module 22, configured to extract enterprise risk information from the data of the enterprise to be researched according to a preset template, where the enterprise risk information includes entity information and event information;
and the fusion association module 23 is configured to perform entity fusion and association on the enterprise risk information to generate an enterprise risk knowledge graph.
In an embodiment, the preset templates include an entity class template and an event class template, and the extraction module 22 is configured to:
and extracting entity information from the data of the enterprise to be researched according to the entity type template, and extracting event information from the data of the enterprise to be researched according to the event type template.
In one embodiment, the entity class template comprises at least one of an enterprise template and a high-management template, and the event class template comprises at least one of an administrative penalty event, a financing and buying event, a bid inviting event, and a risk liability identification event.
In an embodiment, the fusion association module 23 is configured to:
identifying the enterprise risk information, combining the same entities in the enterprise risk information, and recording the incidence relation between different entities in the enterprise risk information.
In an embodiment, the fusion association module 23 is configured to:
determining a corresponding entity according to elements in the enterprise risk information; and/or
And calculating the similarity among the entities in the enterprise risk information, and determining whether the entities are the same entities according to the similarity.
In one embodiment, the apparatus further comprises:
and the display module is used for displaying all or part of the enterprise risk knowledge graph according to the acquired display instruction.
In one embodiment, the display module is configured to display in at least one of the following ways:
displaying a relation graph appointed in the enterprise risk knowledge graph according to relation selection information carried in a display instruction;
displaying a plurality of relation superimposed graphs appointed in the enterprise risk knowledge graph according to relation selection information carried in a display instruction;
and displaying a cutting graph of the specified rule in the enterprise risk knowledge graph according to the query rule information carried in the display instruction.
The embodiment of the application integrates data of various heterogeneous data sources in a mode of entity and event, can display various relation data in an interactive and visual mode, and is convenient for a user to make risk decision.
The embodiment of the present application further provides an enterprise risk information collecting device, including: memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the method of enterprise risk information collection when executing the program.
Embodiments of the present application further provide a computer-readable storage medium storing computer-executable instructions for performing the method for collecting enterprise risk information.
In this embodiment, the storage medium may include, but is not limited to: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
It will be understood by those of ordinary skill in the art that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation. Some or all of the components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.

Claims (10)

1. A method of enterprise risk information collection, comprising:
acquiring data of an enterprise to be researched and researched from various heterogeneous data sources;
extracting enterprise risk information from the data of the enterprise to be researched and researched according to a preset template, wherein the enterprise risk information comprises entity information and event information;
and carrying out entity fusion and association on the enterprise risk information to generate an enterprise risk knowledge graph.
2. The method according to claim 1, wherein the preset templates include an entity class template and an event class template, and the extracting enterprise risk information from the data of the enterprise to be researched according to the preset templates includes:
and extracting entity information from the data of the enterprise to be researched according to the entity type template, and extracting event information from the data of the enterprise to be researched according to the event type template.
3. The method of claim 2,
the entity class template comprises at least one of an enterprise template and a high management template, and the event class template comprises at least one of an administration penalty event, a financing and purchasing event, a bid inviting event and a risk liability identification event.
4. The method of claim 1, wherein the entity fusing and associating the enterprise risk information comprises:
identifying the enterprise risk information, combining the same entities in the enterprise risk information, and recording the incidence relation between different entities in the enterprise risk information.
5. The method of claim 4, wherein the identifying the business risk information comprises:
determining a corresponding entity according to elements in the enterprise risk information; and/or
And calculating the similarity among the entities in the enterprise risk information, and determining whether the entities are the same entities according to the similarity.
6. The method of claim 1, wherein after the entity fusing and associating the enterprise risk information to generate an enterprise risk knowledge graph, the method further comprises:
and displaying all or part of the enterprise risk knowledge graph according to the acquired display instruction.
7. The method according to claim 1, wherein the displaying part of the enterprise risk knowledge graph according to the obtained display instruction comprises at least one of the following manners:
displaying a relation graph appointed in the enterprise risk knowledge graph according to relation selection information carried in a display instruction;
displaying a plurality of relation superimposed graphs appointed in the enterprise risk knowledge graph according to relation selection information carried in a display instruction;
and displaying a cutting graph of the specified rule in the enterprise risk knowledge graph according to the query rule information carried in the display instruction.
8. An apparatus for enterprise risk information collection, comprising:
the acquisition module is used for acquiring data of an enterprise to be investigated from various heterogeneous data sources;
the extraction module is used for extracting enterprise risk information from the data of the enterprise to be researched according to a preset template, wherein the enterprise risk information comprises entity information and event information;
and the fusion association module is used for performing entity fusion and association on the enterprise risk information to generate an enterprise risk knowledge graph.
9. An apparatus for enterprise risk information collection, comprising: memory, processor and computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 7 when executing the program.
10. A computer-readable storage medium storing computer-executable instructions for performing the method of any one of claims 1-7.
CN202010269228.6A 2020-04-08 2020-04-08 Method, device and equipment for collecting enterprise risk information Pending CN111582643A (en)

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CN112037043A (en) * 2020-09-02 2020-12-04 中国银行股份有限公司 Method and device for determining high-quality loan enterprise based on knowledge graph
CN112559774A (en) * 2021-03-01 2021-03-26 北京金睛云华科技有限公司 Extended knowledge graph for information security risk assessment and construction method and system
CN112700218A (en) * 2020-12-31 2021-04-23 新奥数能科技有限公司 Energy enterprise information expansion method and system
CN112837148A (en) * 2021-03-03 2021-05-25 中央财经大学 Risk logical relationship quantitative analysis method fusing domain knowledge
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