CN111966716A - Data processing method and device - Google Patents
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Abstract
An embodiment of the present specification provides a data processing method and an apparatus, wherein the data processing method includes: receiving a service demand submitted by a user, determining a target service category according to the service demand, extracting a target entity attribute from to-be-audited service data of the target service category, determining audit reference information associated with the target service category, inquiring whether an audit rule matched with the audit reference information exists in a pre-constructed knowledge base, and if not, creating and storing the target service audit rule associated with the target entity attribute based on the audit reference information and the target entity attribute; the compliance self-check rule associated with the target entity attribute is created and stored for the target entity attribute, and in the process of performing compliance self-check on the service data to be checked at the later stage, the self-check rule does not need to be newly created, so that the efficiency of compliance checking is favorably improved.
Description
Technical Field
The embodiment of the specification relates to the field of compliance data management, in particular to a data processing method. One or more embodiments of the present specification also relate to a data processing apparatus, a computing device, and a computer-readable storage medium.
Background
With the development of internet technology, various services are developed online one after another, and although an online mode is more convenient for a user to service, in order to obtain a large sales market, more merchants or shops individually select to develop online services, or individually develop offline services, or simultaneously develop online services and offline services, thereby attracting more users.
However, as this phenomenon increases, the sales scenario becomes more complicated, and when some merchants or shops offer services to users, compliance self-check is required to determine whether their operation ranges or operation modes meet the specified compliance conditions. At present, the compliance of business is mainly analyzed and judged by the experience of supervising the professional manpower of compliance, the efficiency is low, the requirement on the experience of staff supervising the compliance industry is high, the information acquisition is delayed, the authenticity of the information is not easy to check, the equivalent rate is low, and great obstacles are caused to the timeliness and the effectiveness of supervision, so that an effective method is urgently needed to solve the problems.
Disclosure of Invention
In view of this, the embodiments of the present specification provide a data processing method. One or more embodiments of the present specification also relate to a data processing apparatus, a computing device, and a computer-readable storage medium to address technical deficiencies in the prior art.
According to a first aspect of embodiments herein, there is provided a data processing method including:
receiving a service requirement submitted by a user, and determining a target service category according to the service requirement;
extracting target entity attributes from the to-be-audited service data of the target service category;
determining audit reference information associated with the target business category, and inquiring whether an audit rule matched with the audit reference information exists in a pre-constructed knowledge base; wherein the auditing rule corresponds to the target entity attribute;
and if not, creating a target service auditing rule associated with the target entity attribute based on the auditing reference information and the target entity attribute and storing the target service auditing rule.
Optionally, after determining the target service category according to the service requirement, the method further includes:
acquiring a service table corresponding to the target service category, wherein the service table comprises the service data to be audited;
judging whether each field of the target entity attribute contained in the service table is associated with an auditing rule corresponding to the target entity attribute;
and if not, executing the checking rule which is inquired in the pre-constructed knowledge base whether the checking reference information is matched with the checking reference information.
Optionally, after determining the target service category according to the service requirement, the method further includes:
acquiring at least one knowledge graph corresponding to the target service category;
constructing at least one service table associated with the target service category based on the at least one knowledge graph, wherein a plurality of fields of the at least one service table are respectively used for storing target entity information and target entity attribute information associated with to-be-audited service data of the target service category;
judging whether each field of the target entity attribute contained in the service table is associated with an auditing rule corresponding to the target entity attribute;
and if not, executing the checking rule which is inquired in the pre-constructed knowledge base whether the checking reference information is matched with the checking reference information.
Optionally, if there is no audit rule corresponding to the target entity attribute in the knowledge base, the following operations are performed:
creating a target business auditing rule corresponding to the target entity attribute based on the auditing reference information and the target entity attribute;
and establishing and storing the association relationship between the target service auditing rule and the field to which the target entity attribute belongs.
Optionally, the knowledge base is constructed by:
acquiring historical audit reference information, historical audit rules and historical audit service data;
determining the incidence relation among the historical auditing reference information, the historical auditing rule and the historical auditing service data;
and constructing the knowledge base according to the incidence relation.
Optionally, the extracting the target entity attribute from the to-be-audited service data of the target service category includes:
performing word segmentation processing on the service data to be audited to obtain the target entity attribute; or the like, or, alternatively,
and extracting and identifying the target entity attribute contained in the service data to be audited through a named entity identification model and/or a preset keyword extraction rule.
Optionally, the querying whether there is an audit rule matching the audit reference information in a pre-constructed knowledge base includes:
reading an audit item from the knowledge base; wherein the audit item comprises audit reference information and an audit rule;
extracting keywords from the audit reference information and the audit rule respectively;
and determining whether the keywords contained in the extraction result are associated with the target entity attributes.
Optionally, the querying whether there is an audit rule matching the audit reference information in a pre-constructed knowledge base includes:
calculating a first association degree between the target entity attribute and the auditing reference information, and calculating a second association degree between the target entity attribute and the auditing rule; the knowledge base comprises a plurality of auditing reference information and a plurality of auditing rules;
and determining the auditing rule corresponding to the target entity attribute in the knowledge base based on the first association degree between the target entity attribute and the auditing reference information and the second association degree between the auditing rules.
Optionally, the querying whether there is an audit rule matching the audit reference information in a pre-constructed knowledge base includes:
inquiring whether an audit rule corresponding to the target entity attribute under each field in the service table exists in the knowledge base;
if yes, establishing the association relationship between the fields to which the target entity attributes belong and the auditing rule.
Optionally, after querying whether there is an audit rule matching the audit reference information in the pre-constructed knowledge base, the method further includes:
if yes, establishing and storing the association relationship between each target entity attribute and the auditing rule.
Optionally, the data processing method further includes:
receiving an audit request, wherein the audit request carries identification information of a target service category;
extracting target entity attributes from the to-be-audited service data of the target service category;
inquiring a target service auditing rule associated with the target entity attribute in a pre-constructed knowledge base according to the identification information;
and auditing the to-be-audited service data of the target service category based on the target service auditing rule and outputting an auditing result to respond to the auditing request.
According to a second aspect of embodiments herein, there is provided a data processing apparatus comprising:
the receiving module is configured to receive the service requirements submitted by the users and determine the target service categories according to the service requirements;
the extraction module is configured to extract the target entity attribute from the to-be-audited business data of the target business category;
the query module is configured to determine audit reference information associated with the target business category and query whether an audit rule matched with the audit reference information exists in a pre-constructed knowledge base; wherein the auditing rule corresponds to the target entity attribute;
if the operation result of the query module is negative, the creation module is operated;
the creating module is configured to create and store a target business auditing rule associated with the target entity attribute based on the auditing reference information and the target entity attribute.
According to a third aspect of embodiments herein, there is provided a computing device comprising:
a memory and a processor;
the memory is to store computer-executable instructions, and the processor is to execute the computer-executable instructions to:
receiving a service requirement submitted by a user, and determining a target service category according to the service requirement;
extracting target entity attributes from the to-be-audited service data of the target service category;
determining audit reference information associated with the target business category, and inquiring whether an audit rule matched with the audit reference information exists in a pre-constructed knowledge base; wherein the auditing rule corresponds to the target entity attribute;
and if not, creating a target service auditing rule associated with the target entity attribute based on the auditing reference information and the target entity attribute and storing the target service auditing rule.
According to a fourth aspect of embodiments herein, there is provided a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the data processing method.
One embodiment of the present specification receives a service requirement submitted by a user, determines a target service category according to the service requirement, extracts a target entity attribute from to-be-audited service data of the target service category, determines audit reference information associated with the target service category, and queries whether an audit rule matching the audit reference information exists in a pre-constructed knowledge base, where the audit rule corresponds to the target entity attribute, and if not, creates and stores a target service audit rule associated with the target entity attribute based on the audit reference information and the target entity attribute;
and establishing a target business auditing rule associated with the target entity attribute for the target entity attribute by the above mode, storing the target business auditing rule in a knowledge base, and using the target business auditing rule for compliance self-check, thereby being beneficial to improving the efficiency of compliance auditing.
Drawings
FIG. 1 is a process flow diagram of a data processing method provided in one embodiment of the present description;
FIG. 2 is a flow chart of a data processing method according to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of a data processing apparatus provided in one embodiment of the present description;
fig. 4 is a block diagram of a computing device according to an embodiment of the present disclosure.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present description. This description may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, as those skilled in the art will be able to make and use the present disclosure without departing from the spirit and scope of the present disclosure.
The terminology used in the description of the one or more embodiments is for the purpose of describing the particular embodiments only and is not intended to be limiting of the description of the one or more embodiments. As used in one or more embodiments of the present specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used in one or more embodiments of the present specification refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It will be understood that, although the terms first, second, etc. may be used herein in one or more embodiments to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, a first can also be referred to as a second and, similarly, a second can also be referred to as a first without departing from the scope of one or more embodiments of the present description. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
In the present specification, a data processing method is provided, and the present specification relates to a data processing apparatus, a computing device, and a computer-readable storage medium, which are described in detail one by one in the following embodiments.
Fig. 1 shows a process flow diagram of a data processing method provided according to an embodiment of the present specification, including steps 102 to 108.
Step 102, receiving a service requirement submitted by a user, and determining a target service category according to the service requirement.
When an enterprise provides services for users, most enterprises can carry out compliance self-check to determine whether the operation range or the operation mode of the enterprise meets the specified compliance conditions, and with the continuous emergence of new technologies, the traditional supervision compliance means cannot cope with the rapid development of various industries. At present, the compliance of business is mainly analyzed and judged by the experience of supervising the professional manpower of compliance, the efficiency is low, the requirement on the experience of staff supervising the compliance industry is high, the information acquisition is delayed, the authenticity of the information is not easy to check, the equivalent rate is low, and great obstacles are caused to the timeliness and the effectiveness of supervision, so that an effective method is urgently needed to solve the problems.
Based on this, in the embodiment of the present specification, a service requirement submitted by a user is received, a target service category is determined according to the service requirement, a target entity attribute is extracted from to-be-audited service data of the target service category, audit reference information associated with the target service category is determined, and whether an audit rule matching the audit reference information exists is queried in a pre-constructed knowledge base, wherein the audit rule corresponds to the target entity attribute, and if not, a target service audit rule associated with the target entity attribute is created based on the audit reference information and the target entity attribute and stored;
and establishing a target business auditing rule associated with the target entity attribute for the target entity attribute by the above mode, storing the target business auditing rule in a knowledge base, and using the target business auditing rule for compliance self-check, thereby being beneficial to improving the efficiency of compliance auditing.
Specifically, the user is a party to be audited, the party to be audited specifically refers to an enterprise, a merchant or a store that needs to perform business compliance audit on a target business, the target business described in the embodiment of the present specification is a target business of the party to be audited, and the target business includes, but is not limited to, a fund transaction business, a data resource transaction business, a calculation resource transaction business, a virtual resource transaction business and the like; compliance means that the business activities of the enterprise, merchant or store are in accordance with laws, rules and guidelines; the service compliance auditing range specifically refers to service data to be audited corresponding to the target service of the party to be audited; the service data to be audited includes but is not limited to the service data of the transaction services such as fund transaction service, data resource transaction service, computing resource transaction service, virtual resource transaction service and the like, the service category is the service category under the target service of the party to be audited, for example, the service category corresponding to the fund transaction service includes but is not limited to fund transaction service, loan service and the like; the service category corresponding to the virtual resource transaction service includes, but is not limited to, a purchase service of virtual currency, a gift service, and the like.
The business requirement is the requirement for performing compliance self-check on the business data to be checked, and the business data to be checked related to the new business can be subjected to compliance self-check in a mode of submitting the business requirement under the condition that a new business is developed by a party to be checked.
Because the business services provided by the party to be audited include a plurality of services, and the auditing rule corresponding to each business may have differences, after receiving the business requirement, the target business category can be determined according to the business requirement, so as to query the auditing rule according to the target business category.
And 104, extracting the target entity attribute from the to-be-audited business data of the target business category.
Specifically, after receiving the service requirement submitted by the user, the target entity attribute can be extracted from the service data to be audited of the target service category.
In practical application, the target entity attribute is an attribute corresponding to a target entity included in the service data to be audited.
Taking the target service category as a loan service as an example, the target entity is a user of the loan service, and the target entity attributes include but are not limited to gender, age, occupation, and the like of the user.
In specific implementation, the extracting of the target entity attribute from the to-be-audited service data of the target service category may be specifically implemented in the following manner:
performing word segmentation processing on the service data to be audited to obtain the target entity attribute; or the like, or, alternatively,
and extracting and identifying the target entity attribute contained in the service data to be audited through a named entity identification model and/or a preset keyword extraction rule.
Specifically, word segmentation processing is carried out on service data to be audited by adopting a word segmentation technology to obtain target entity attributes; the target entity attributes include, but are not limited to, information for characterizing specific attributes, such as attribute information for characterizing a territory, attribute information for characterizing an audience, attribute information for characterizing an applicable scene, and the like.
Performing word segmentation processing according to the service data to be audited to obtain one or more new words, for example, the service data to be audited is "a limiting condition for the age of the borrower", performing word segmentation processing on the service data to be audited, and obtaining a word segmentation result: the target entity attribute of "age" can be obtained according to the word segmentation processing result.
In addition, Named Entity Recognition (referred to as "near Recognition"), which is also called "proper name Recognition", refers to Recognition of entities having specific meanings in texts, mainly includes names of people, places, names of organizations, proper nouns, and the like, is a basic tool in application fields such as information extraction, question and answer systems, syntactic analysis, machine translation, and the like, and plays an important role in the process of putting natural language processing technology into practical use.
And extracting and identifying the target entity attribute contained in the service data to be audited through a named entity identification model, namely inputting the service data to be audited into the named entity identification model for target entity attribute identification, and acquiring a target entity attribute identification result output by the model.
In practical application, a model corresponding to the NER may be trained in advance, and the trained model may more accurately obtain entity attributes or concepts included in the service data to be audited, for example, based on the above example, the model corresponding to the NER may identify named entities including three major classes and seven minor classes. Each piece of information in the to-be-audited business data can be respectively input into the model corresponding to the NER, and the entity attribute contained in the to-be-audited business data is extracted and identified, so that the entity attribute or concept related information contained in each piece of information in the to-be-audited business data is obtained.
In addition, the keyword extraction rule may include multiple types, such as a natural language processing technique, a graph-based ranking algorithm (Text Rank algorithm) for Text, a TF-IDF (Term Frequency-Inverse Document Frequency), and the like, and the keyword extraction rule may be one or a combination of multiple types, and may be specifically set according to an actual situation, which is not limited in this specification.
After the target entity attribute contained in the to-be-audited business data is extracted and identified, the content, the context and the like of each piece of information in the to-be-audited business data can be analyzed, and the association relation information of the corresponding information is respectively extracted from each piece of information in the to-be-audited business data.
The word segmentation processing is carried out on the business data to be audited, or the word segmentation processing is carried out on the business data to be audited through a named entity recognition model and/or a preset keyword extraction rule, so that the extraction and recognition of the business data to be audited contained in the business data to be audited are carried out, and the accuracy of the obtained extraction and recognition results is improved.
Step 106, determining audit reference information associated with the target business category, and inquiring whether an audit rule matched with the audit reference information exists in a pre-constructed knowledge base; wherein the audit rule corresponds to the target entity attribute.
Specifically, the audit reference information, that is, the external supervision information, includes preset service audit rules and/or service environment data, the preset service audit rules, that is, the supervision rules, include but are not limited to regulatory provisions, policy and regulations, and the service environment data includes but is not limited to external operation environment data, external supervision environment data, external service feedback data, and the like.
The auditing rule is a rule which is created in advance and is used for performing compliance self-inspection on the service data to be audited, and because the compliance self-inspection rules corresponding to the service data to be audited of different service categories are different, after receiving service requirements and determining a target service category and auditing reference information associated with the target service category, whether the auditing rule matched with the auditing reference information exists can be inquired in a pre-constructed knowledge base.
And if the pre-constructed knowledge base does not have the auditing rule matched with the auditing reference information, creating and storing a target service auditing rule associated with the target entity attribute based on the auditing reference information and the target entity attribute.
And if an audit rule matched with the audit reference information exists in a pre-constructed knowledge base, establishing and storing an association relation between the target entity attribute and the audit rule.
During specific implementation, historical audit reference information, historical audit rules and historical audit service data can be obtained, the association relationship among the historical audit reference information, the historical audit rules and the historical audit service data is determined, and the knowledge base is constructed according to the association relationship.
And constructing a knowledge base based on the historical audit reference information, the historical audit rule and the incidence relation between the historical audit business data, wherein the construction of the whole knowledge base can be automatically carried out without consuming a large amount of labor cost, the constructed knowledge base can cover various audit reference information and audit rules, and the audit reference information and audit rule have high coverage rate in the application stage, so that the accuracy of the audit result is ensured.
In specific implementation, the querying whether an audit rule matching the audit reference information exists in the pre-constructed knowledge base may be specifically implemented in the following manner:
reading an audit item from the knowledge base; wherein the audit item comprises audit reference information and an audit rule;
extracting keywords from the audit reference information and the audit rule respectively;
and determining whether the keywords contained in the extraction result are associated with the target entity attributes.
Specifically, the knowledge base comprises audit reference information and audit rules, after receiving a service requirement and determining a target service category, the knowledge base can read audit items from the knowledge base, extract keywords from the audit items, and compare the extracted keywords with the target entity attribute to determine whether the extracted keywords are associated with the target entity attribute.
If the audit rules are not related, the fact that the audit rules are matched with the audit reference information do not exist in the pre-constructed knowledge base is determined.
Whether the audit rule matched with the audit reference information exists in the knowledge base or not is determined in the mode, and the query efficiency of querying the audit rule matched with the audit reference information in the knowledge base is improved.
In addition, the querying whether the pre-constructed knowledge base has the audit rule matched with the audit reference information can be realized by the following method:
calculating a first association degree between the target entity attribute and the auditing reference information, and calculating a second association degree between the target entity attribute and the auditing rule; the knowledge base comprises a plurality of auditing reference information and a plurality of auditing rules;
and determining the auditing rule corresponding to the target entity attribute in the knowledge base based on the first association degree between the target entity attribute and the auditing reference information and the second association degree between the auditing rules.
Specifically, a first degree of association between the target entity attribute and the review reference information and a second degree of association between the target entity attribute and the review rule are calculated, which may be implemented by Word vector-based document similarity algorithm (WMD), and before calculating the degree of similarity, Word segmentation may be performed on the review reference information and the review rule to obtain a first Word set corresponding to the review reference information and a second Word set corresponding to the review rule, and a first degree of association and a second degree of association of Word segmentation results in the target entity attribute, the first Word set and the second Word set are calculated respectively, and the review rule corresponding to the target entity attribute is determined in the knowledge base based on the first degree of association and the second degree of association.
And determining the auditing rule corresponding to the target entity attribute in the knowledge base by combining the first association degree between the target entity attribute and the auditing reference information and the second association degree between the target entity attribute and the auditing rule, so that the accuracy of the determined auditing rule corresponding to the target entity attribute is ensured.
And 108, creating a target business auditing rule associated with the target entity attribute based on the auditing reference information and the target entity attribute and storing the target business auditing rule.
Specifically, if there is no audit rule matching with the audit reference information of the target service category in the pre-created knowledge base, a target service audit rule associated with the target entity attribute needs to be created and stored based on the audit reference information and the target entity attribute.
For example, the target service category is loan service, the service data to be audited is "a restriction condition for the age of the borrower", and the word segmentation is performed on the service data, and the obtained word segmentation result is: "pair", "borrower", "age", "of", "restriction condition", the target entity attribute is "age" can be obtained according to the word segmentation processing result; one piece of auditing reference information related to the loan transaction is that the age of the borrower is greater than or equal to 18 years old, and in a pre-constructed knowledge base, in order to query an auditing rule matched with the auditing reference information, a target service auditing rule needs to be created based on the auditing reference information and the target entity attribute of age, and the created target service auditing rule can be that the age of the borrower is greater than or equal to 18 years old? ".
In specific implementation, after determining the target service category according to the service requirement, the method further includes:
acquiring a service table corresponding to the target service category, wherein the service table comprises the service data to be audited;
judging whether each field of the target entity attribute contained in the service table is associated with an auditing rule corresponding to the target entity attribute;
if not, inquiring whether an audit rule corresponding to the target entity attribute under each field in the service table exists in the knowledge base;
and if so, establishing the association relationship between the field to which each target entity attribute belongs and the auditing rule.
Specifically, since the service data to be audited is generally stored in the form of a service table, after receiving a service requirement and determining a target service category, a service table corresponding to the target service category may be obtained, after obtaining the service table, it is determined whether a field to which each attribute information belongs in the service table is associated with an audit rule corresponding to each attribute information, and if not, it is queried in a pre-established knowledge base whether an audit rule matching each attribute information and the audit reference information exists.
In addition, after determining the target service category according to the service requirement, the method further includes:
acquiring at least one knowledge graph corresponding to the target service category;
constructing at least one service table associated with the target service category based on the at least one knowledge graph, wherein a plurality of fields of the at least one service table are respectively used for storing target entity information and target entity attribute information associated with to-be-audited service data of the target service category;
judging whether each field of the target entity attribute contained in the service table is associated with an auditing rule corresponding to the target entity attribute;
and if not, executing the checking rule which is inquired in the pre-constructed knowledge base whether the checking reference information is matched with the checking reference information.
In particular, a Knowledge Graph (knowledgegraph) is a Knowledge base called semantic network (semantic network), i.e. a Knowledge base with a directed Graph structure, wherein nodes of the Graph represent entities (entries) or concepts (concepts), and edges of the Graph represent various semantic relationships between entities/concepts. The entities may have corresponding attribute information that may be used to characterize certain attributes of the entities (e.g., attributes such as categories, storage addresses, etc. of information characterized by the entities). The knowledge graph can be applied to various fields, such as information search, information recommendation and the like.
After receiving a service requirement and determining a target service category according to the service requirement, at least one knowledge graph corresponding to the target service category can be obtained, a service table is constructed based on entities contained in the at least one knowledge graph and attribute information corresponding to the entities, and the entities and the attribute information corresponding to the entities are used as fields to construct the service table.
After the business table is constructed, whether the field to which each attribute information belongs is associated with the auditing rule corresponding to each attribute information is determined, if not, whether the auditing rule matched with each attribute information and the auditing reference information exists is inquired in a pre-constructed knowledge base.
Further, if the knowledge base does not have the auditing rule corresponding to the target entity attribute, a target service auditing rule corresponding to the target entity attribute is created based on the auditing reference information and the target entity attribute, and the association relationship between the target service auditing rule and the field to which the target entity attribute belongs is established and stored.
For example, the target service category is loan service, the service data to be audited is "a restriction condition for the age of the borrower", and the word segmentation is performed on the service data, and the obtained word segmentation result is: "pair", "borrower", "age", "of", "restriction condition", the target entity attribute is "age" can be obtained according to the word segmentation processing result; one piece of auditing reference information related to the loan transaction is that the age of the borrower is greater than or equal to 18 years old, and in a pre-constructed knowledge base, in order to query an auditing rule matched with the auditing reference information, a target service auditing rule needs to be created based on the auditing reference information and the target entity attribute of age, and the created target service auditing rule can be that the age of the borrower is greater than or equal to 18 years old? After the creation is completed, the association relationship between the target business auditing rule and the field to which the age belongs is established and stored.
The method comprises the steps of constructing at least one service table associated with a target service category based on at least one knowledge graph corresponding to the target service category, being beneficial to ensuring the comprehensiveness and diversity of target entity attributes contained in the constructed service table, creating a target service auditing rule associated with the target entity attributes for the target entity attributes, storing the target service auditing rule in a knowledge base, using the target service auditing rule for compliance self-check, and being beneficial to improving the efficiency of compliance auditing.
In addition, after the target service auditing rule associated with the target entity attribute is created based on the auditing reference information and the target entity attribute, the compliance self-check can be performed on the service data to be audited of the target service category based on the target service auditing rule associated with the target entity attribute, and the method can be specifically realized by the following modes:
receiving an audit request, wherein the audit request carries identification information of a target service category;
extracting target entity attributes from the to-be-audited service data of the target service category;
inquiring a target service auditing rule associated with the target entity attribute in a pre-constructed knowledge base according to the identification information;
and auditing the to-be-audited service data of the target service category based on the target service auditing rule and outputting an auditing result to respond to the auditing request.
Specifically, the auditing request can be submitted by the party to be audited to perform compliance self-check on the business data to be audited, and the business data to be audited related to the new business can be subjected to compliance self-check in a mode of submitting the auditing requirement under the condition that the party to be audited develops the new business.
After receiving an audit request submitted by a party to be audited, acquiring business data to be audited of a target business category according to identification information of the target business category carried in the audit request, and extracting target entity attributes from the business data to be audited. In practical application, the target entity attribute is an attribute corresponding to a target entity included in the service data to be audited.
After the target entity attribute is extracted, a target service auditing rule associated with the target entity attribute can be inquired in a pre-constructed knowledge base according to the identification information, auditing is carried out on the service data to be audited of the target service category based on the target service auditing rule, and an auditing result is output to respond to the auditing request.
As described above, the target service category is a loan service, the service data to be audited is "a restriction condition for the age of the borrower", the service data is subjected to word segmentation, and the target entity attribute is "age" according to the word segmentation result; an age-related target service audit rule queried in the knowledge base according to the identification information of the lending service is "is the borrower age greater than or equal to 18 years? And if so, checking the age information in the to-be-checked service data of the loan service based on the target service checking rule, and outputting a checking result.
The compliance self-check rule associated with the target entity attribute is created and stored for the target entity attribute, and in the process of performing compliance self-check on the service data to be checked at the later stage, the self-check rule does not need to be newly created, so that the efficiency of compliance checking is favorably improved.
Receiving a service requirement submitted by a user, determining a target service category according to the service requirement, extracting a target entity attribute from service data to be audited of the target service category, determining audit reference information associated with the target service category, and querying whether an audit rule matched with the audit reference information exists in a pre-established knowledge base, wherein the audit rule corresponds to the target entity attribute, and if not, creating and storing the target service audit rule associated with the target entity attribute based on the audit reference information and the target entity attribute;
and establishing a target business auditing rule associated with the target entity attribute for the target entity attribute by the above mode, storing the target business auditing rule in a knowledge base, and using the target business auditing rule for compliance self-check, thereby being beneficial to improving the efficiency of compliance auditing.
The following description will further explain the data processing method by taking the application of the data processing method provided in this specification in a loan service scenario as an example, with reference to fig. 2. Fig. 2 shows a flowchart of a processing procedure of a data processing method according to an embodiment of the present specification, and specific steps include step 202 to step 218.
Step 202, receiving a service requirement submitted by a user, and determining a target service category according to the service requirement.
Specifically, the target service category is a loan service.
And 204, extracting and identifying the target entity attribute contained in the to-be-audited loan service data through a named entity identification model and/or a preset keyword extraction rule.
At step 206, audit reference information associated with the loan transaction is determined.
And step 208, acquiring a service table corresponding to the loan service.
Specifically, the service table includes the to-be-audited loan service data.
If not, go to step 212; if yes, the processing is not required.
Step 212, calculating a first association degree between the target entity attribute and the audit reference information, and calculating a second association degree between the target entity attribute and the audit rule.
Specifically, the knowledge base includes a plurality of audit reference information and a plurality of audit rules.
Step 214, querying whether an audit rule corresponding to the target entity attribute in each field in the service table exists in the knowledge base based on the first association between the target entity attribute and the audit reference information and the second association between the audit rules.
If the knowledge base has an audit rule corresponding to the target entity attribute under each field in the service table, establishing and storing an association relation between the target service audit rule and the field to which the target entity attribute belongs;
if the knowledge base does not have the auditing rule corresponding to the target entity attribute under each field in the service table, step 216 is executed.
Step 218, establishing and storing the association relationship between the target business audit rule and the field to which the target entity attribute belongs.
In the embodiment of the specification, the target business auditing rule associated with the target entity attribute is created for the target entity attribute, the target business auditing rule is stored in the knowledge base, the target business auditing rule is used for compliance self-check, and in the later process of performing compliance self-check on the business data to be audited, a self-check rule does not need to be created, so that the efficiency of compliance audit is improved.
Corresponding to the above method embodiment, the present specification further provides a data processing apparatus embodiment, and fig. 3 shows a schematic diagram of a data processing apparatus provided in an embodiment of the present specification. As shown in fig. 3, the apparatus includes:
a receiving module 302, configured to receive a service requirement submitted by a user, and determine a target service category according to the service requirement;
an extraction module 304, configured to extract a target entity attribute from the to-be-audited service data of the target service category;
a query module 306 configured to determine audit reference information associated with the target service category, and query whether an audit rule matching the audit reference information exists in a pre-constructed knowledge base; wherein the auditing rule corresponds to the target entity attribute;
if the operation result of the query module is no, the creating module 308 is operated;
the creating module 308 is configured to create and store a target business audit rule associated with the target entity attribute based on the audit reference information and the target entity attribute.
Optionally, the data processing apparatus further includes:
a service table obtaining module configured to obtain a service table corresponding to the target service category, wherein the service table includes the service data to be audited;
the first judging module is configured to judge whether each field to which the target entity attribute belongs in the service table is associated with an auditing rule corresponding to the target entity attribute;
and if the operation result of the first judgment module is negative, operating the query module.
Optionally, the data processing apparatus further includes:
a knowledge graph acquisition module configured to acquire at least one knowledge graph corresponding to the target business category;
a building module configured to build at least one service table associated with the target service category based on the at least one knowledge graph, where a plurality of fields of the at least one service table are respectively used to store target entity information and target entity attribute information associated with to-be-audited service data of the target service category;
the second judging module is configured to judge whether each field to which the target entity attribute belongs in the service table is associated with an auditing rule corresponding to the target entity attribute;
and if the operation result of the second judgment module is negative, operating the query module.
Optionally, if the operation result of the first determining module is yes, the following operations are performed:
creating a target business auditing rule corresponding to the target entity attribute based on the auditing reference information and the target entity attribute;
and establishing and storing the association relationship between the target service auditing rule and the field to which the target entity attribute belongs.
Optionally, if the operation result of the second determining module is yes, the following operations are performed:
creating a target business auditing rule corresponding to the target entity attribute based on the auditing reference information and the target entity attribute;
and establishing and storing the association relationship between the target service auditing rule and the field to which the target entity attribute belongs.
Optionally, the knowledge base is constructed by:
acquiring historical audit reference information, historical audit rules and historical audit service data;
determining the incidence relation among the historical auditing reference information, the historical auditing rule and the historical auditing service data;
and constructing the knowledge base according to the incidence relation.
Optionally, the extraction module 304 includes:
the word segmentation processing submodule is configured to perform word segmentation processing on the service data to be audited to obtain the target entity attribute; or the like, or, alternatively,
and the extraction submodule is configured to extract and identify the target entity attribute contained in the service data to be audited through a named entity identification model and/or a preset keyword extraction rule.
Optionally, the query module 306 includes:
a reading sub-module configured to read the audit entries from the knowledge base; wherein the audit item comprises audit reference information and an audit rule;
a keyword extraction sub-module configured to extract keywords from the review reference information and the review rule, respectively;
a determination sub-module configured to determine whether a keyword contained in the extraction result is associated with the target entity attribute.
Optionally, the query module 306 includes:
the calculation sub-module is configured to calculate a first association degree between the target entity attribute and the auditing reference information, and calculate a second association degree between the target entity attribute and the auditing rule; the knowledge base comprises a plurality of auditing reference information and a plurality of auditing rules;
and the rule determining submodule is configured to determine the auditing rule corresponding to the target entity attribute in the knowledge base based on a first association degree between the target entity attribute and the auditing reference information and a second association degree between the auditing rules.
Optionally, the query module 306 includes:
a rule query submodule configured to query whether an audit rule corresponding to the target entity attribute under each field in the service table exists in the knowledge base;
if the operation result of the rule query submodule is yes, the establishing submodule is operated;
the establishing submodule is configured to establish an association relationship between the fields to which the target entity attributes belong and the auditing rule.
Optionally, the data processing apparatus further includes:
if the operation result of the query module 306 is yes, the establishing module is operated;
the establishing module is configured to establish and store the association relationship between each target entity attribute and the auditing rule.
Optionally, the data processing apparatus further includes:
the request receiving module is configured to receive an audit request, wherein the audit request carries identification information of a target service category;
the target entity attribute extraction module is configured to extract target entity attributes from the to-be-audited business data of the target business category;
the auditing rule inquiry module is configured to inquire a target business auditing rule associated with the target entity attribute in a pre-constructed knowledge base according to the identification information;
and the auditing module is configured to audit the to-be-audited service data of the target service category based on the target service auditing rule and output an auditing result to respond to the auditing request.
The above is a schematic configuration of a data processing apparatus of the present embodiment. It should be noted that the technical solution of the data processing apparatus and the technical solution of the data processing method belong to the same concept, and details that are not described in detail in the technical solution of the data processing apparatus can be referred to the description of the technical solution of the data processing method.
FIG. 4 illustrates a block diagram of a computing device 400 provided in accordance with one embodiment of the present description. The components of the computing device 400 include, but are not limited to, a memory 410 and a processor 420. Processor 420 is coupled to memory 410 via bus 430 and database 450 is used to store data.
Computing device 400 also includes access device 440, access device 440 enabling computing device 400 to communicate via one or more networks 460. Examples of such networks include the Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the internet. The access device 440 may include one or more of any type of network interface (e.g., a Network Interface Card (NIC)) whether wired or wireless, such as an IEEE802.11 Wireless Local Area Network (WLAN) wireless interface, a worldwide interoperability for microwave access (Wi-MAX) interface, an ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a bluetooth interface, a Near Field Communication (NFC) interface, and so forth.
In one embodiment of the present description, the above-described components of computing device 400, as well as other components not shown in FIG. 4, may also be connected to each other, such as by a bus. It should be understood that the block diagram of the computing device architecture shown in FIG. 4 is for purposes of example only and is not limiting as to the scope of the present description. Those skilled in the art may add or replace other components as desired.
Computing device 400 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., tablet, personal digital assistant, laptop, notebook, netbook, etc.), mobile phone (e.g., smartphone), wearable computing device (e.g., smartwatch, smartglasses, etc.), or other type of mobile device, or a stationary computing device such as a desktop computer or PC. Computing device 400 may also be a mobile or stationary server.
Wherein the memory 410 is configured to store computer-executable instructions and the processor 420 is configured to execute the following computer-executable instructions:
receiving a service requirement submitted by a user, and determining a target service category according to the service requirement;
extracting target entity attributes from the to-be-audited service data of the target service category;
determining audit reference information associated with the target business category, and inquiring whether an audit rule matched with the audit reference information exists in a pre-constructed knowledge base; wherein the auditing rule corresponds to the target entity attribute;
and if not, creating a target service auditing rule associated with the target entity attribute based on the auditing reference information and the target entity attribute and storing the target service auditing rule.
The above is an illustrative scheme of a computing device of the present embodiment. It should be noted that the technical solution of the computing device and the technical solution of the data processing method belong to the same concept, and details that are not described in detail in the technical solution of the computing device can be referred to the description of the technical solution of the data processing method.
An embodiment of the present specification also provides a computer readable storage medium storing computer instructions which, when executed by a processor, are used for implementing the steps of the data processing method.
The above is an illustrative scheme of a computer-readable storage medium of the present embodiment. It should be noted that the technical solution of the storage medium belongs to the same concept as the technical solution of the data processing method, and details that are not described in detail in the technical solution of the storage medium can be referred to the description of the technical solution of the data processing method.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The computer instructions comprise computer program code which may be in the form of source code, object code, an executable file or some intermediate form, or the like. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
It should be noted that, for the sake of simplicity, the foregoing method embodiments are described as a series of acts, but those skilled in the art should understand that the present embodiment is not limited by the described acts, because some steps may be performed in other sequences or simultaneously according to the present embodiment. Further, those skilled in the art should also appreciate that the embodiments described in this specification are preferred embodiments and that acts and modules referred to are not necessarily required for an embodiment of the specification.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
The preferred embodiments of the present specification disclosed above are intended only to aid in the description of the specification. Alternative embodiments are not exhaustive and do not limit the invention to the precise embodiments described. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the embodiments and the practical application, to thereby enable others skilled in the art to best understand and utilize the embodiments. The specification is limited only by the claims and their full scope and equivalents.
Claims (14)
1. A method of data processing, comprising:
receiving a service requirement submitted by a user, and determining a target service category according to the service requirement;
extracting target entity attributes from the to-be-audited service data of the target service category;
determining audit reference information associated with the target business category, and inquiring whether an audit rule matched with the audit reference information exists in a pre-constructed knowledge base; wherein the auditing rule corresponds to the target entity attribute;
and if not, creating a target service auditing rule associated with the target entity attribute based on the auditing reference information and the target entity attribute and storing the target service auditing rule.
2. The data processing method of claim 1, after determining the target service category according to the service requirement, further comprising:
acquiring a service table corresponding to the target service category, wherein the service table comprises the service data to be audited;
judging whether each field of the target entity attribute contained in the service table is associated with an auditing rule corresponding to the target entity attribute;
and if not, executing the checking rule which is inquired in the pre-constructed knowledge base whether the checking reference information is matched with the checking reference information.
3. The data processing method of claim 1, after determining the target service category according to the service requirement, further comprising:
acquiring at least one knowledge graph corresponding to the target service category;
constructing at least one service table associated with the target service category based on the at least one knowledge graph, wherein a plurality of fields of the at least one service table are respectively used for storing target entity information and target entity attribute information associated with to-be-audited service data of the target service category;
judging whether each field of the target entity attribute contained in the service table is associated with an auditing rule corresponding to the target entity attribute;
and if not, executing the checking rule which is inquired in the pre-constructed knowledge base whether the checking reference information is matched with the checking reference information.
4. The data processing method according to claim 2 or 3, wherein if there is no audit rule corresponding to the target entity attribute in the knowledge base, the following operations are performed:
creating a target business auditing rule corresponding to the target entity attribute based on the auditing reference information and the target entity attribute;
and establishing and storing the association relationship between the target service auditing rule and the field to which the target entity attribute belongs.
5. The data processing method of claim 1, the knowledge base being constructed by:
acquiring historical audit reference information, historical audit rules and historical audit service data;
determining the incidence relation among the historical auditing reference information, the historical auditing rule and the historical auditing service data;
and constructing the knowledge base according to the incidence relation.
6. The data processing method according to claim 1, wherein extracting the target entity attribute from the to-be-audited service data of the target service category includes:
performing word segmentation processing on the service data to be audited to obtain the target entity attribute; or the like, or, alternatively,
and extracting and identifying the target entity attribute contained in the service data to be audited through a named entity identification model and/or a preset keyword extraction rule.
7. The data processing method according to claim 1, wherein the querying whether an audit rule matching the audit reference information exists in a pre-constructed knowledge base comprises:
reading an audit item from the knowledge base; wherein the audit item comprises audit reference information and an audit rule;
extracting keywords from the audit reference information and the audit rule respectively;
and determining whether the keywords contained in the extraction result are associated with the target entity attributes.
8. The data processing method according to claim 1, wherein the querying whether an audit rule matching the audit reference information exists in a pre-constructed knowledge base comprises:
calculating a first association degree between the target entity attribute and the auditing reference information, and calculating a second association degree between the target entity attribute and the auditing rule; the knowledge base comprises a plurality of auditing reference information and a plurality of auditing rules;
and determining the auditing rule corresponding to the target entity attribute in the knowledge base based on the first association degree between the target entity attribute and the auditing reference information and the second association degree between the auditing rules.
9. The data processing method according to claim 2, wherein the querying whether an audit rule matching the audit reference information exists in a pre-constructed knowledge base comprises:
inquiring whether an audit rule corresponding to the target entity attribute under each field in the service table exists in the knowledge base;
if yes, establishing the association relationship between the fields to which the target entity attributes belong and the auditing rule.
10. The data processing method according to claim 1, after querying whether there is an audit rule matching the audit reference information in a pre-constructed knowledge base, further comprising:
if yes, establishing and storing the association relationship between each target entity attribute and the auditing rule.
11. The data processing method of claim 1, further comprising:
receiving an audit request, wherein the audit request carries identification information of a target service category;
extracting target entity attributes from the to-be-audited service data of the target service category;
inquiring a target service auditing rule associated with the target entity attribute in a pre-constructed knowledge base according to the identification information;
and auditing the to-be-audited service data of the target service category based on the target service auditing rule and outputting an auditing result to respond to the auditing request.
12. A data processing apparatus comprising:
the receiving module is configured to receive the service requirements submitted by the users and determine the target service categories according to the service requirements;
the extraction module is configured to extract the target entity attribute from the to-be-audited business data of the target business category;
the query module is configured to determine audit reference information associated with the target business category and query whether an audit rule matched with the audit reference information exists in a pre-constructed knowledge base; wherein the auditing rule corresponds to the target entity attribute;
if the operation result of the query module is negative, the creation module is operated;
the creating module is configured to create and store a target business auditing rule associated with the target entity attribute based on the auditing reference information and the target entity attribute.
13. A computing device, comprising:
a memory and a processor;
the memory is to store computer-executable instructions, and the processor is to execute the computer-executable instructions to:
receiving a service requirement submitted by a user, and determining a target service category according to the service requirement;
extracting target entity attributes from the to-be-audited service data of the target service category;
determining audit reference information associated with the target business category, and inquiring whether an audit rule matched with the audit reference information exists in a pre-constructed knowledge base; wherein the auditing rule corresponds to the target entity attribute;
and if not, creating a target service auditing rule associated with the target entity attribute based on the auditing reference information and the target entity attribute and storing the target service auditing rule.
14. A computer readable storage medium storing computer instructions which, when executed by a processor, carry out the steps of the data processing method of any one of claims 1 to 11.
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| CN115145982A (en) * | 2022-08-03 | 2022-10-04 | 浙江网商银行股份有限公司 | Data processing method and device |
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