CN115587701A

CN115587701A - Enterprise risk assessment processing method and device and electronic equipment

Info

Publication number: CN115587701A
Application number: CN202211253733.7A
Authority: CN
Inventors: 刘聪聪
Original assignee: Beijing Shangyin Microchip Technology Co ltd
Current assignee: Beijing Shangyin Microchip Technology Co ltd
Priority date: 2022-10-13
Filing date: 2022-10-13
Publication date: 2023-01-10

Abstract

According to the enterprise risk assessment processing method and device and the electronic equipment, a risk assessment request initiated by a user to a target enterprise is obtained, the risk assessment request comprises a user identifier, an enterprise identifier and a risk assessment identifier, and the risk assessment identifier comprises a risk inquiry identifier and/or a risk assessment identifier; determining a preset risk query rule corresponding to the risk query identifier, and performing risk data query on the target enterprise according to the preset risk query rule by using the user identifier and the enterprise identifier to obtain a first risk data query result corresponding to the target enterprise; and determining a preset risk assessment strategy corresponding to the risk assessment identification, and performing risk assessment on the target enterprise according to the preset risk assessment strategy by using the user identification and the enterprise identification to obtain a first risk assessment result corresponding to the target enterprise. The risk assessment method and the risk assessment system adopt the risk query rule and the risk assessment strategy which can be configured in advance, and can more efficiently, accurately and objectively carry out risk assessment processing on enterprises.

Description

Enterprise risk assessment processing method and device and electronic equipment

Technical Field

The present disclosure relates to the field of data processing technologies, and in particular, to an enterprise risk assessment processing method and apparatus, and an electronic device.

Background

With the rise of supply chain finance, evaluation and decision of core enterprises, dealers and suppliers in a supply chain depend on related wind control personnel to manually inquire enterprise information, and the problems of high manual investment, low efficiency and manual operation errors exist, so that the method is a technical problem which needs to be solved by technical personnel in the field and is used for more efficiently, accurately and objectively evaluating and processing risks of the enterprises and helping the customers to avoid the risks in advance.

Disclosure of Invention

In view of the foregoing problems, the present disclosure provides an enterprise risk assessment processing method, apparatus, and electronic device that overcome the foregoing problems or at least partially solve the foregoing problems, and the technical solutions are as follows:

an enterprise risk assessment processing method comprises the following steps:

obtaining a risk assessment request initiated by a user to a target enterprise, wherein the risk assessment request comprises a user identifier corresponding to the user, an enterprise identifier corresponding to the target enterprise and a risk assessment identifier input by the user, and the risk assessment identifier comprises a risk query identifier and/or a risk assessment identifier;

under the condition that the risk assessment request comprises the risk query identification, determining a preset risk query rule corresponding to the risk query identification, and performing risk data query on the target enterprise according to the preset risk query rule by using the user identification and the enterprise identification to obtain a first risk data query result corresponding to the target enterprise;

and under the condition that the risk assessment request comprises the risk assessment identifier, determining a preset risk assessment strategy corresponding to the risk assessment identifier, and performing risk assessment on the target enterprise according to the preset risk assessment strategy by using the user identifier and the enterprise identifier to obtain a first risk assessment result corresponding to the target enterprise.

Optionally, the preset risk query rule is configured with a score calculation manner, at least one first threshold interval, at least one data product, and at least one conditional expression corresponding to the data product.

Optionally, the performing, by using the user identifier and the enterprise identifier, a risk data query on the target enterprise according to the preset risk query rule to obtain a first risk data query result corresponding to the target enterprise includes:

before any data product in the preset risk query rule is called, whether the user has the authority of calling the data product is determined according to the user identification, if yes, the data product is called to query first enterprise associated data corresponding to the enterprise identification, the matching number of the conditional expressions matched with the first enterprise associated data is determined, and under the condition that the matching number is 1, a first data product query result of the target enterprise under the data product is obtained based on the first enterprise associated data and the matched conditional expressions;

performing data statistics on the query result of each first data product by using the score calculation mode to obtain a data statistical result;

and determining the first threshold interval matched with the data statistical result, and outputting a first risk data query result corresponding to the target enterprise.

Optionally, the preset risk assessment policy is configured with at least one preset risk query rule, at least one risk assessment model, and a preset risk assessment policy tree.

Optionally, the performing risk assessment on the target enterprise according to the preset risk assessment policy by using the user identifier and the enterprise identifier to obtain a first risk assessment result corresponding to the target enterprise includes:

respectively querying risk data of the target enterprise according to each preset risk query rule in the preset risk assessment strategy by using the user identification and the enterprise identification to obtain a second risk data query result which is queried under each preset risk query rule and corresponds to the target enterprise;

respectively calling each risk assessment model in the preset risk assessment strategy to carry out risk assessment on the target enterprise by using the user identification and the enterprise identification, and obtaining a first model assessment result which is inquired by each risk assessment model and corresponds to the target enterprise;

analyzing each second risk data query result and the first model evaluation result to obtain node data corresponding to a plurality of node objects in the preset risk evaluation strategy tree;

and sequentially determining a second threshold interval matched with the node data corresponding to each node object from the root node of the preset risk assessment strategy tree until a first risk assessment result corresponding to the target enterprise is obtained after each node object in the preset risk assessment strategy tree is traversed.

Optionally, the using the user identifier and the enterprise identifier to respectively call each risk assessment model in the preset risk assessment policy to perform risk assessment on the target enterprise, and obtaining a first model assessment result corresponding to the target enterprise and output by each risk assessment model, includes:

before any one of the risk assessment models of the preset risk assessment strategies is called, whether the user has the authority of calling the risk assessment model is determined according to the user identification, and if the user has the authority, the risk assessment model is called to inquire a first model assessment result corresponding to the enterprise identification.

Optionally, the data product includes a red blacklist query, a judicial data query, an industrial and commercial change data query, and an external investment data query.

Optionally, the risk assessment model includes an enterprise credit scoring model and an enterprise business data scoring model.

An enterprise risk assessment processing apparatus, comprising: a risk assessment request obtaining unit, a rule determining unit, a risk data inquiring unit, a strategy determining unit and a risk assessment unit,

the risk assessment request obtaining unit is configured to obtain a risk assessment request initiated by a user for a target enterprise, where the risk assessment request includes a user identifier corresponding to the user, an enterprise identifier corresponding to the target enterprise, and a risk assessment identifier input by the user, where the risk assessment identifier includes a risk query identifier and/or a risk assessment identifier;

the rule determining unit is configured to determine a preset risk query rule corresponding to the risk query identifier when the risk assessment request includes the risk query identifier;

the risk data query unit is used for performing risk data query on the target enterprise according to the preset risk query rule by using the user identifier and the enterprise identifier to obtain a first risk data query result corresponding to the target enterprise;

the policy determining unit is configured to determine a preset risk assessment policy corresponding to the risk assessment identifier when the risk assessment request includes the risk assessment identifier;

and the risk evaluation unit is used for carrying out risk evaluation on the target enterprise according to the preset risk evaluation strategy by utilizing the user identifier and the enterprise identifier to obtain a first risk evaluation result corresponding to the target enterprise.

An electronic device comprising at least one processor, and at least one memory connected to the processor, a bus; the processor and the memory complete mutual communication through the bus; the processor is configured to call program instructions in the memory to perform any of the above-described enterprise risk assessment processing methods.

By means of the technical scheme, the enterprise risk assessment processing method, the enterprise risk assessment processing device and the electronic equipment, provided by the disclosure, can obtain a risk assessment request initiated by a user to a target enterprise, wherein the risk assessment request comprises a user identifier corresponding to the user, an enterprise identifier corresponding to the target enterprise and a risk assessment identifier input by the user, and the risk assessment identifier is a risk query identifier and/or a risk assessment identifier; under the condition that the risk evaluation request comprises a risk query identifier, determining a preset risk query rule corresponding to the risk query identifier, and performing risk data query on a target enterprise according to the preset risk query rule by using a user identifier and an enterprise identifier to obtain a first risk data query result corresponding to the target enterprise; and under the condition that the risk assessment request comprises a risk assessment identifier, determining a preset risk assessment strategy corresponding to the risk assessment identifier, and performing risk assessment on the target enterprise according to the preset risk assessment strategy by using the user identifier and the enterprise identifier to obtain a first risk assessment result corresponding to the target enterprise. By adopting the risk query rule and the risk assessment strategy which can be configured in advance, the risk assessment processing can be carried out on the enterprise more efficiently, accurately and objectively, and a client is helped to avoid risks in advance.

The foregoing description is only an overview of the technical solutions of the present disclosure, and the embodiments of the present disclosure are described below in order to make the technical means of the present disclosure more clearly understood and to make the above and other objects, features, and advantages of the present disclosure more clearly understandable.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the disclosure. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:

fig. 1 is a schematic flow chart diagram illustrating an implementation manner of an enterprise risk assessment processing method according to an embodiment of the present disclosure;

FIG. 2 is a flow chart diagram illustrating another implementation of an enterprise risk assessment processing method according to an embodiment of the present disclosure;

FIG. 3 is a flow chart diagram illustrating another implementation of an enterprise risk assessment processing method according to an embodiment of the present disclosure;

FIG. 4 is an illustration of a preset risk assessment policy tree provided by an embodiment of the disclosure;

fig. 5 is a schematic structural diagram of an enterprise risk assessment processing apparatus provided in an embodiment of the present disclosure;

fig. 6 shows a schematic structural diagram of an electronic device provided by an embodiment of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

As shown in fig. 1, a schematic flow diagram of an implementation manner of an enterprise risk assessment processing method according to an embodiment of the present disclosure may include:

s100, obtaining a risk assessment request initiated by a user to a target enterprise, wherein the risk assessment request comprises a user identifier corresponding to the user, an enterprise identifier corresponding to the target enterprise and a risk assessment identifier input by the user, and the risk assessment identifier comprises a risk inquiry identifier and/or a risk assessment identifier.

The user can log in a preset risk assessment request submitting interface, and enterprise query information of the target enterprise and a risk assessment identifier which needs to carry out risk assessment processing on the target enterprise are input in the preset risk assessment request submitting interface. For example: the user can check the risk assessment identifier for performing risk assessment processing on the target enterprise in the preset risk assessment request submitting interface, and can also select the risk assessment identifier for performing risk assessment processing on the target enterprise in the drop-down box. The enterprise query information may include the enterprise name, the unified social credit code, the legal name, and the query time interval of the target enterprise.

The method and the device for generating the risk assessment request can respond to submission operation of a user in a preset risk assessment request submission interface and generate the risk assessment request according to content input by the user in the preset risk assessment request submission interface.

It can be understood that, in the embodiment of the present disclosure, after the user logs in the preset risk assessment request submission interface, the user identifier corresponding to the user may be obtained. Alternatively, the user identifier may be a unique user number for managing a user login account.

Alternatively, the business identification may be the name of the target business, a uniform social credit code, or a pre-configured unique business number.

Optionally, the risk query identifier may be a unique rule number corresponding to a preset risk query rule, and the risk assessment identifier may be a unique policy number corresponding to a preset risk assessment policy.

S200, under the condition that the risk assessment request comprises a risk inquiry identification, determining a preset risk inquiry rule corresponding to the risk inquiry identification.

The embodiment of the disclosure can identify the risk query identifier in the risk assessment request, thereby determining the preset risk query rule corresponding to the risk query identifier.

Optionally, the preset risk query rule may be configured with a score calculation manner, at least one first threshold interval, at least one data product, and at least one conditional expression corresponding to the data product.

The embodiment of the disclosure can provide a function of creating and configuring a risk query rule in advance. Optionally, in the embodiment of the present disclosure, at least one data product may be configured for the risk query rule, at least one conditional expression may be configured for the data product, and a plurality of data indicator fields such as a variable condition, a variable judgment value, a logical connection word, a rule score, and a weight may be configured for the conditional expression. After the conditional expressions are configured for the data products, a score calculation mode is configured for the risk query rule. Optionally, the score calculation method may include summation, weighted summation, average, maximum and minimum. After the score calculation mode is configured, setting a threshold maximum value and a threshold minimum value for the risk query rule according to the score calculation mode, and setting the interval name and the boundary threshold value of each threshold interval within the threshold maximum value and the threshold minimum value, so that the risk query rule finally outputs a score and a result.

It can be understood that, in the embodiment of the present disclosure, the risk query rule may be configured according to a series of configuration instructions input by a risk query rule configurator on a preset risk query rule configuration page, so as to obtain the configured risk query rule.

Wherein the data product can be an embeddable functional component having the capability to query third party data related to the enterprise principal and enterprise business. Optionally, the data product may include a red blacklist query, a judicial data query, a business change data query, and an external investment data query. It will be appreciated that the specific query content provided by the data product may be configured in configuring the data product for risk query rules based on the query functionality that the data product may provide. For example: based on the risk query rule configured in the preset risk query rule configuration page shown in fig. 3, when the configured data product is "business change query", the specific query content may be selected as "business change times" in the field name column. In the case where the configured data product is "judicial data query", the specific query content may be selected as "number of executed distrusted data" in the field name column.

The method and the device for risk query of the enterprise provide a universal risk query rule for identifying enterprise risks based on historical experience of supply chain financial business, the risk query rule can support custom configuration by combining risk requirements and preferences of users, and online query of enterprise risk conditions is achieved based on multidimensional third-party enterprise data.

The preset risk query rule provided by the embodiment of the disclosure can be independently used as a tool for evaluating enterprise risk, and can also be used as one of configuration items of a risk evaluation strategy.

S300, carrying out risk data query on the target enterprise according to a preset risk query rule by using the user identifier and the enterprise identifier, and obtaining a first risk data query result corresponding to the target enterprise.

Optionally, based on the method shown in fig. 1, as shown in fig. 2, a flowchart of another implementation of the enterprise risk assessment processing method provided in the embodiment of the present disclosure is schematically shown, and step S300 may include:

s310, before any data product in the preset risk inquiry rules is called, whether the user has the authority of calling the data product is determined according to the user identification, and if yes, the step S320 is executed.

Specifically, the embodiment of the present disclosure may query the data product invocation permission corresponding to the user identifier, determine whether the data product invocation permission includes a permission to use the data product, and if so, determine that the user corresponding to the user identifier has the permission to use the data product.

Optionally, the embodiment of the present disclosure may obtain the query result of the second data product when it is determined that the user does not have the right to use the data product. Optionally, the second data product result includes description information of the unauthorized product.

S320, calling the data product to inquire first enterprise associated data corresponding to the enterprise identification, determining the matching number of the conditional expressions matched with the first enterprise associated data, and executing the step S330 under the condition that the matching number is 1.

Optionally, after obtaining the first enterprise related data queried by the data product, the embodiment of the present disclosure obtains, according to the variable condition field in each condition expression corresponding to the data product, a field value corresponding to the variable condition field in the first enterprise related data. And if the variable condition fields in any conditional expression can be matched with the field values in the first enterprise associated data, determining that the first enterprise associated data is matched with the conditional expression.

Optionally, in the embodiment of the present disclosure, a third data product query result of the target enterprise under the data product may be obtained when the matching number of the conditional expression matched by the first enterprise-related data is not 1.

It will be appreciated that since the data product may correspond to a plurality of conditional expressions, the first enterprise-related data may or may not match a plurality of conditional expressions.

Optionally, in the embodiment of the present disclosure, when the first enterprise related data is matched to multiple conditional expressions, the third data product query result of the target enterprise under the data product may be obtained to include description information matched to the multiple conditional expressions.

Optionally, in the embodiment of the present disclosure, when the first enterprise related data is not matched to the conditional expression, the third data product query result of the target enterprise under the data product may be obtained to include the description information that is not matched to the conditional expression.

S330, obtaining a first data product query result of the target enterprise under the data product based on the first enterprise associated data and the matched conditional expression.

Specifically, the embodiment of the present disclosure substitutes a field value corresponding to a variable condition field in the matched condition expression in the first enterprise-related data into the condition expression for calculation, so as to obtain a calculated query result of the first data product.

S340, performing data statistics on the query results of the first data products by using a score calculation mode to obtain data statistics results.

According to the embodiment of the disclosure, under the condition that the target enterprise outputs the first data product query result under each data product in each threshold risk query rule, the score calculation mode is utilized to perform data statistics on each first data product query result, and the data statistics result is obtained.

It should be noted that, the target enterprise may output one or more second data product query results and/or third data product query results under each data product in each threshold risk query rule, in this case, the embodiment of the present disclosure may not perform step S340, but directly output the second risk data query results. Optionally, the second risk data query result includes description information of the abnormal risk data query result.

And S350, determining a first threshold interval matched with the data statistical result, and outputting a first risk data query result corresponding to the target enterprise.

It is understood that the data statistic is a numerical value. The embodiment of the disclosure may determine, in each first threshold interval configured by preset risk query rules, a first threshold interval corresponding to the value, and output the data statistical result and the first threshold interval corresponding to the value of the data statistical result as a first risk data query result.

It should be noted that, if there is no first threshold interval corresponding to the numerical value of the data statistical result in each first threshold interval configured by the preset risk query rule, the embodiment of the present disclosure may directly output the third risk data query result corresponding to the target enterprise. Optionally, the third risk data query result includes the data statistics result and the description information that is not matched to the threshold interval.

For ease of understanding, this is illustrated here by way of example: the preset risk query rule is assumed to comprise data products of 'red blacklist query' and 'judicial data query', and the specific query contents are 'historical blacklist quantity' and 'number of executed lost letters'. Assuming that "the number of history blacklists" is 5, the corresponding conditional expression is "condition: less than or equal to 10, the rule is divided into 80 ″, and the weight is: 50 percent. Assuming that "the number of times of loss of trust is executed" is 20, the corresponding conditional expression is "condition: >10 and ≤ 50, rule is divided into 20, weight: 50% ". If the score is calculated by weighted summation, the statistical result of the obtained data is 50. If the first threshold interval includes the threshold interval a "[70, 90]", the threshold interval B "[40, 70]", and the threshold interval C "[15, 40]", the first threshold interval corresponding to the data statistical result is the threshold interval B.

S400, under the condition that the risk assessment request comprises a risk assessment identifier, determining a preset risk assessment strategy corresponding to the risk assessment identifier.

The embodiment of the disclosure can identify the risk assessment identifier in the risk assessment request, so as to determine the preset risk assessment policy corresponding to the risk assessment identifier.

Optionally, the preset risk assessment policy may be configured with at least one preset risk query rule, at least one risk assessment model, and a preset risk assessment policy tree.

The embodiment of the disclosure can provide a function of creating and configuring a risk assessment policy in advance. Optionally, in the embodiment of the present disclosure, at least one preset risk query rule and/or at least one preset risk assessment model may be configured for the risk assessment policy, and then the risk assessment policy tree is configured according to the preset risk query rule and/or the preset risk assessment model, so that the risk assessment policy tree finally outputs a risk assessment result. Specifically, in the configuration process of the risk assessment policy tree, a preset risk query rule or a risk assessment model may be selected at a root node of the risk assessment policy tree, a default interval corresponding to the preset risk query rule or the risk assessment model is displayed, and the default interval is edited or interval branches are increased or decreased according to an editing instruction input by a configurator. The next node of each interval branch may select a condition node, an interval node, or a result node. The condition nodes are used for checking preset risk query rules or risk assessment models. The interval node is used for setting a preset risk query rule or a threshold interval of a risk evaluation model. The result node is used for setting a risk result. And completing the configuration of the risk assessment strategy tree until the final of all branches in the risk assessment strategy tree is the end node.

It can be understood that, in the embodiment of the present disclosure, the risk assessment policy may be configured according to a series of configuration instructions input by a risk assessment policy configurator on a preset risk assessment policy configuration page, so as to obtain a configured risk assessment policy.

Optionally, the configuration page of the risk assessment policy tree may be implemented by adopting a flex layout. Each node in the risk assessment strategy tree is a box, node gaps are realized by setting the inner edge distance of a node container, the middle transverse line of the tree is realized by setting an upper frame from the node container, and branch connection vertical lines are realized through pseudo elements. A series of operations such as deleting, editing and storing are carried out on the nodes on the box, and the internal layout is realized according to the specific node type condition. The node type includes a condition node, an interval node, or a result node.

Optionally, the interaction operation in the configuration process of the risk assessment policy tree mainly involves the interaction of adding nodes, editing and saving various nodes, switching prompts when switching condition nodes to select preset risk query rules or risk assessment models, and the like. When a node is added, the data structure of the node type of the node is immediately stored in the tree data tree, and the data of the corresponding node is stored when the node data is updated (such as model or rule replacement, click storage in an editing interval, defocusing of an editing result and the like).

Optionally, in the configuration process of the risk assessment policy tree, when the preset risk query rule or the risk assessment model is switched, the backend data needs to be requested according to the identifier corresponding to the preset risk query rule or the risk assessment model, format conversion is performed on the returned data, the data is mounted to the corresponding branch in the tree, and then re-rendering of the tree is performed.

Optionally, the embodiment of the present disclosure may perform logical verification on the risk assessment policy tree. The logic verification mainly comprises the following steps: 1. the interval nodes cannot be null check, integer check and threshold range check. 2. And (4) performing multi-interval mutual exclusion verification on the rule or the model. 3. Integrity check of each branch path of the tree, i.e., each branch path must have a result node. 4. And monitoring the state of the preset risk query rule or the risk evaluation model selected by each condition node in the tree, and prompting a configurator to replace other preset risk query rules or risk evaluation models if the preset risk query rule or the permission of the risk evaluation model of the condition node is monitored to be lost in the state editing.

Optionally, after the risk assessment policy tree is built, the risk assessment policy tree is stored in the database in a JSON string manner, and when the data of the back-end tree is returned to the front end during query, each node in the tree needs to be converted into a corresponding DOM node; and when the tree is refreshed, the response data is firstly subjected to data structure conversion and then the corresponding branch nodes are mounted. And when the risk assessment strategy tree is stored, traversing the use times of the rules and/or models selected by the condition nodes in the tree, so that when the risk assessment strategy tree is edited, the unused rules and/or models can be cancelled and checked.

The risk assessment model can be a pre-configured enterprise risk scoring model, and can respond to the calling of a preset risk inquiry rule through an interface to evaluate the admission, credit and the like of enterprises such as core enterprises, suppliers, distributors and the like. Optionally, the risk assessment model may include an enterprise credit scoring model and an enterprise business data scoring model.

According to the embodiment of the invention, decision flow configuration is carried out by combining specific business scenes and depending on preset risk query rules and a risk evaluation model, so that risk decision on the whole flow line is realized.

S500, performing risk assessment on the target enterprise according to a preset risk assessment strategy by using the user identification and the enterprise identification to obtain a first risk assessment result corresponding to the target enterprise.

Optionally, based on the method shown in fig. 1, as shown in fig. 3, a flowchart of another implementation of the enterprise risk assessment processing method provided in the embodiment of the present disclosure is schematically shown, and step S500 may include:

and S510, respectively querying risk data of the target enterprise according to each preset risk query rule in the preset risk assessment strategy by using the user identifier and the enterprise identifier, and obtaining a second risk data query result which is queried under each preset risk query rule and corresponds to the target enterprise.

It should be noted that, the process of the risk data query may refer to the description at step S300, and is not described herein again.

S520, by means of the user identification and the enterprise identification, the risk assessment models in the preset risk assessment strategy are called respectively to conduct risk assessment on the target enterprise, and first model assessment results which are inquired by the risk assessment models and correspond to the target enterprise are obtained.

Optionally, in the embodiment of the present disclosure, before any risk assessment model of the preset risk assessment policy is called, it may be determined whether the user has an authority to call the risk assessment model according to the user identifier, and if so, the risk assessment model is called to query the first model assessment result corresponding to the enterprise identifier.

Specifically, the embodiment of the present disclosure may query a model invoking permission corresponding to a user identifier, determine whether the model invoking permission includes a permission of the risk assessment model, and if so, determine that a user corresponding to the user identifier has a permission to use the risk assessment model.

Optionally, the embodiment of the present disclosure may obtain the second model evaluation result in a case where it is determined that the user does not have a right to use the risk evaluation model. Optionally, the second model evaluation result includes description information of the unauthorized use model.

S530, analyzing each second risk data query result and each first model evaluation result to obtain node data corresponding to a plurality of node objects in the preset risk evaluation strategy tree.

And S540, sequentially determining a second threshold interval matched with the node data corresponding to each node object from the root node of the preset risk assessment strategy tree until each node object in the preset risk assessment strategy tree is traversed, and obtaining a first risk assessment result corresponding to the target enterprise.

It can be understood that, according to the second threshold interval matched with the node data corresponding to the end node, the risk evaluation content corresponding to the second threshold interval is determined, and the risk evaluation content is output as the first risk evaluation result.

It should be noted that if the node data corresponding to any node object is not matched to the second threshold interval, the second risk assessment result corresponding to the target enterprise is output. Optionally, the second risk assessment result includes description information that is not matched to the model threshold interval or the rule threshold interval.

For ease of understanding, the description is made herein by way of example: with reference to the preset risk assessment policy tree shown in fig. 4, it is assumed that the root node is a preset risk query rule "enterprise test rule", and corresponds to interval nodes [70, 90], [40, 70] and [15, 40], if a second risk data query result corresponding to a target enterprise queried by the "enterprise test rule" is 80, a condition node under the interval nodes [70, 90] is called, the condition node is a risk assessment model "enterprise credit scoring model", and corresponds to interval nodes [22, 222], [333, 336] and [338, 390], and if a first model assessment result corresponding to the target enterprise queried by the "enterprise credit scoring model" is 168, it is determined that a risk assessment content "high risk" of an end node corresponding to the interval node [22, 222] is a first risk assessment result.

The enterprise risk assessment processing method provided by the embodiment of the disclosure can be applied to tool type wind control platforms. The wind control platform has the advantages that the visual configuration function of the risk query rule and the risk assessment strategy is provided, a configurator can conveniently configure the risk query rule and the risk assessment strategy, multidimensional selection of risk query and assessment is provided for a user, the user can be helped to comprehensively know the risk information of an enterprise, and related risks are avoided in advance.

According to the enterprise risk assessment processing method provided by the disclosure, a risk assessment request initiated by a user to a target enterprise can be obtained, wherein the risk assessment request comprises a user identifier corresponding to the user, an enterprise identifier corresponding to the target enterprise and a risk assessment identifier input by the user, and the risk assessment identifier is a risk query identifier and/or a risk assessment identifier; under the condition that the risk evaluation request comprises a risk query identifier, determining a preset risk query rule corresponding to the risk query identifier, and performing risk data query on a target enterprise according to the preset risk query rule by using a user identifier and an enterprise identifier to obtain a first risk data query result corresponding to the target enterprise; and under the condition that the risk assessment request comprises a risk assessment identifier, determining a preset risk assessment strategy corresponding to the risk assessment identifier, and performing risk assessment on the target enterprise according to the preset risk assessment strategy by using the user identifier and the enterprise identifier to obtain a first risk assessment result corresponding to the target enterprise. By adopting the risk query rule and the risk assessment strategy which can be configured in advance, the risk assessment processing can be carried out on the enterprise more efficiently, accurately and objectively, and a client is helped to avoid risks in advance.

Although the operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous.

It should be understood that the various steps recited in method embodiments of the present disclosure may be performed in a different order, and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.

Corresponding to the foregoing method embodiment, an embodiment of the present disclosure further provides an enterprise risk assessment processing apparatus, which has a structure as shown in fig. 5, and may include: a risk assessment request obtaining unit 100, a rule determining unit 200, a risk data querying unit 300, a policy determining unit 400, and a risk assessment unit 500.

A risk assessment request obtaining unit 100, configured to obtain a risk assessment request initiated by a user for a target enterprise, where the risk assessment request includes a user identifier corresponding to the user, an enterprise identifier corresponding to the target enterprise, and a risk assessment identifier input by the user, where the risk assessment identifier includes a risk query identifier and/or a risk assessment identifier.

A rule determining unit 200, configured to determine a preset risk query rule corresponding to the risk query identifier if the risk assessment request includes the risk query identifier.

And the risk data query unit 300 is configured to perform risk data query on the target enterprise according to a preset risk query rule by using the user identifier and the enterprise identifier, and obtain a first risk data query result corresponding to the target enterprise.

A policy determining unit 400, configured to determine a preset risk assessment policy corresponding to the risk assessment identifier if the risk assessment request includes the risk assessment identifier.

And the risk assessment unit 500 is configured to perform risk assessment on the target enterprise according to a preset risk assessment policy by using the user identifier and the enterprise identifier, and obtain a first risk assessment result corresponding to the target enterprise.

Optionally, the risk data querying unit 300 is specifically configured to determine, before any data product in the preset risk querying rules is called, whether a user has a right to invoke the data product according to a user identifier, if yes, invoke the data product to query first enterprise-related data corresponding to the enterprise identifier, determine a matching number of conditional expressions matching the first enterprise-related data, and obtain, in a case that the matching number is 1, a first data product querying result of the target enterprise under the data product based on the first enterprise-related data and the matched conditional expression; carrying out data statistics on the query results of the first data products by using a score calculation mode to obtain data statistics results; and determining a first threshold interval matched with the data statistical result, and outputting a first risk data query result corresponding to the target enterprise.

Optionally, the risk assessment unit 500 is specifically configured to perform, by using the user identifier and the enterprise identifier, risk data query on the target enterprise according to each preset risk query rule in the preset risk assessment policy, and obtain a second risk data query result corresponding to the target enterprise, which is queried under each preset risk query rule; respectively calling each risk evaluation model in a preset risk evaluation strategy to carry out risk evaluation on the target enterprise by using the user identification and the enterprise identification, and obtaining a first model evaluation result which is inquired by each risk evaluation model and corresponds to the target enterprise; analyzing each second risk data query result and each first model evaluation result to obtain node data corresponding to a plurality of node objects in a preset risk evaluation strategy tree; and sequentially determining a second threshold interval matched with the node data corresponding to each node object from the root node of the preset risk assessment strategy tree until all the node objects in the preset risk assessment strategy tree are traversed, and then obtaining a first risk assessment result corresponding to the target enterprise.

Optionally, the risk assessment unit 500 is specifically configured to, before any risk assessment model of the preset risk assessment policy is called, determine whether the user has an authority to call the risk assessment model according to the user identifier, and if so, call the risk assessment model to query a first model assessment result corresponding to the enterprise identifier.

Optionally, the data product includes a red black list query, a judicial data query, an industrial and commercial change data query, and an external investment data query.

The enterprise risk assessment processing device provided by the disclosure can obtain a risk assessment request initiated by a user to a target enterprise, wherein the risk assessment request comprises a user identifier corresponding to the user, an enterprise identifier corresponding to the target enterprise and a risk assessment identifier input by the user, and the risk assessment identifier is a risk query identifier and/or a risk assessment identifier; under the condition that the risk evaluation request comprises a risk query identifier, determining a preset risk query rule corresponding to the risk query identifier, and performing risk data query on a target enterprise according to the preset risk query rule by using a user identifier and an enterprise identifier to obtain a first risk data query result corresponding to the target enterprise; and under the condition that the risk assessment request comprises a risk assessment identifier, determining a preset risk assessment strategy corresponding to the risk assessment identifier, and performing risk assessment on the target enterprise according to the preset risk assessment strategy by using the user identifier and the enterprise identifier to obtain a first risk assessment result corresponding to the target enterprise. By adopting the risk query rule and the risk assessment strategy which can be configured in advance, the risk assessment processing can be carried out on the enterprise more efficiently, accurately and objectively, and a client is helped to avoid risks in advance.

With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.

The enterprise risk assessment processing device comprises a processor and a memory, wherein the risk assessment request obtaining unit 100, the rule determining unit 200, the risk data querying unit 300, the policy determining unit 400, the risk assessment unit 500 and the like are stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions.

The processor comprises a kernel, and the kernel calls the corresponding program unit from the memory. The kernel can be set to be one or more, a risk assessment request initiated by a user to a target enterprise is obtained by adjusting kernel parameters, the risk assessment request comprises a user identifier, an enterprise identifier and a risk assessment identifier, and the risk assessment identifier comprises a risk inquiry identifier and/or a risk assessment identifier; determining a preset risk query rule corresponding to the risk query identifier, and performing risk data query on the target enterprise according to the preset risk query rule by using the user identifier and the enterprise identifier to obtain a first risk data query result corresponding to the target enterprise; and determining a preset risk assessment strategy corresponding to the risk assessment identification, and performing risk assessment on the target enterprise according to the preset risk assessment strategy by using the user identification and the enterprise identification to obtain a risk assessment result corresponding to the target enterprise.

The disclosed embodiments provide a computer-readable storage medium on which a program is stored, which when executed by a processor implements the enterprise risk assessment processing method.

The embodiment of the disclosure provides a processor, which is used for running a program, wherein the program executes the enterprise risk assessment processing method during running.

As shown in fig. 6, an embodiment of the present disclosure provides an electronic device 1000, where the electronic device 1000 includes at least one processor 1001, and at least one memory 1002 and a bus 1003 connected to the processor 1001; the processor 1001 and the memory 1002 complete communication with each other through the bus 1003; the processor 1001 is configured to call the program instructions in the memory 1002 to execute the enterprise risk assessment processing method described above. The electronic device herein may be a server, a PC, a PAD, a mobile phone, etc.

The present disclosure also provides a computer program data product adapted to perform a program of initializing an enterprise risk assessment processing method step when executed on an electronic device.

The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus, electronic devices (systems), and computer program data products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, an electronic device includes one or more processors (CPUs), memory, and a bus. The electronic device may also include input/output interfaces, network interfaces, and the like.

The memory may include volatile memory in a computer readable medium, random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip. The memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

In the description of the present disclosure, it is to be understood that the directions or positional relationships indicated as referring to the terms "upper", "lower", "front", "rear", "left" and "right", etc., are based on the directions or positional relationships shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the positions or elements referred to must have specific directions, be constituted and operated in specific directions, and thus, are not to be construed as limitations of the present disclosure.

It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.

As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, system, or computer program data product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program data product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.

The foregoing is merely exemplary of the present disclosure and is not intended to limit the same. Various modifications and variations of this disclosure will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure should be included in the scope of the claims of the present disclosure.

Claims

1. An enterprise risk assessment processing method is characterized by comprising the following steps:

2. The method of claim 1, wherein the preset risk query rule is configured with a score computation manner, at least one first threshold interval, at least one data product, and at least one conditional expression corresponding to the data product.

3. The method of claim 2, wherein the performing, by using the user identifier and the enterprise identifier, a risk data query on the target enterprise according to the preset risk query rule to obtain a first risk data query result corresponding to the target enterprise comprises:

performing data statistics on the query result of each first data product by using the score calculation mode to obtain a data statistics result;

4. The method of claim 1, wherein the preset risk assessment policy is configured with at least one of the preset risk query rules, at least one risk assessment model, and a preset risk assessment policy tree.

5. The method of claim 4, wherein performing risk assessment on the target enterprise according to the preset risk assessment policy by using the user identifier and the enterprise identifier to obtain a first risk assessment result corresponding to the target enterprise comprises:

respectively querying risk data of the target enterprise according to each preset risk query rule in the preset risk assessment strategy by using the user identifier and the enterprise identifier to obtain a second risk data query result which is queried under each preset risk query rule and corresponds to the target enterprise;

6. The method according to claim 5, wherein the using the user identifier and the enterprise identifier to respectively invoke each risk assessment model in the preset risk assessment policy to perform risk assessment on the target enterprise, and obtaining a first model assessment result corresponding to the target enterprise and output by each risk assessment model, includes:

7. The method of claim 2, wherein the data products include red blacklist queries, judicial data queries, business alteration data queries, and investments data queries.

8. The method of claim 4, wherein the risk assessment model comprises an enterprise credit scoring model and an enterprise business data scoring model.

9. An enterprise risk assessment processing apparatus, comprising: a risk assessment request obtaining unit, a rule determining unit, a risk data inquiring unit, a strategy determining unit and a risk assessment unit,

10. An electronic device comprising at least one processor, and at least one memory connected to the processor, a bus; the processor and the memory complete mutual communication through the bus; the processor is configured to invoke program instructions in the memory to perform the enterprise risk assessment processing method of any of claims 1-8.