CN116777140A - Enterprise business management method, device, equipment and medium - Google Patents
Enterprise business management method, device, equipment and medium Download PDFInfo
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Abstract
The embodiment of the specification discloses an enterprise business management method, device, equipment and medium, comprising the following steps: establishing an information base of an enterprise according to related information of the enterprise; constructing a portrait of the enterprise according to the business of the enterprise and the information base of the enterprise; constructing a business processing module by combining the portrait of the enterprise with the approval flow and the demand of the business of the enterprise so as to fully cover the business processing of each business block and business chain of the enterprise; and carrying out risk analysis on each business plate and business chain business process of the enterprise through a risk analysis module constructed through big data in advance. The embodiment of the specification has the characteristics of management visualization, data base intellectualization, marketing system datamation, business management informatization, flow standardization, risk monitoring automation and the like, realizes full coverage of each operation plate and business chain, further improves the business management informatization level of a gold control enterprise, effectively improves the risk prevention and control capability, reduces the operation cost and the like.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method, an apparatus, a device, and a medium for enterprise business management.
Background
At present, an enterprise has a plurality of independent parts in service processing, which may cause that the enterprise service management is not communicated, thereby affecting the processing efficiency of the enterprise service. Therefore, how to better manage business of enterprises is a problem to be solved at present.
Disclosure of Invention
One or more embodiments of the present disclosure provide a method, an apparatus, a device, and a medium for enterprise business management, which are used to solve the technical problems set forth in the background art.
One or more embodiments of the present disclosure adopt the following technical solutions:
one or more embodiments of the present disclosure provide an enterprise business management method, including:
establishing an information base of an enterprise according to related information of the enterprise;
constructing a portrait of the enterprise according to the business of the enterprise and the information base of the enterprise;
constructing a business processing module by combining the portrait of the enterprise with the approval flow and the demand of the business of the enterprise so as to fully cover the business processing of each business block and business chain of the enterprise;
and carrying out risk analysis on each business plate and business chain business process of the enterprise through a risk analysis module constructed through big data in advance.
One or more embodiments of the present specification provide an enterprise business management apparatus, the apparatus comprising:
the information base establishing unit establishes an information base of the enterprise according to the related information of the enterprise;
a portrait construction unit for constructing a portrait of the enterprise according to the business of the enterprise and the information base of the enterprise;
the business processing module construction unit is used for constructing a business processing module by combining the portrait of the enterprise with the approval flow and the requirement of the business of the enterprise so as to fully cover the business processing of each business plate and business chain of the enterprise;
and the risk analysis unit is used for carrying out risk analysis on each business plate and business chain business process of the enterprise through a risk analysis module constructed through big data in advance.
One or more embodiments of the present specification provide an enterprise business management apparatus, including:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
establishing an information base of an enterprise according to related information of the enterprise;
constructing a portrait of the enterprise according to the business of the enterprise and the information base of the enterprise;
constructing a business processing module by combining the portrait of the enterprise with the approval flow and the demand of the business of the enterprise so as to fully cover the business processing of each business block and business chain of the enterprise;
and carrying out risk analysis on each business plate and business chain business process of the enterprise through a risk analysis module constructed through big data in advance.
One or more embodiments of the present description provide a non-volatile computer storage medium storing computer-executable instructions that, when executed by a computer, enable:
establishing an information base of an enterprise according to related information of the enterprise;
constructing a portrait of the enterprise according to the business of the enterprise and the information base of the enterprise;
constructing a business processing module by combining the portrait of the enterprise with the approval flow and the demand of the business of the enterprise so as to fully cover the business processing of each business block and business chain of the enterprise;
and carrying out risk analysis on each business plate and business chain business process of the enterprise through a risk analysis module constructed through big data in advance.
The above-mentioned at least one technical scheme that this description embodiment adopted can reach following beneficial effect:
the embodiment of the specification has the characteristics of management visualization, data base intellectualization, marketing system datamation, business management informatization, flow standardization, risk monitoring automation and the like, realizes full coverage of each operation plate and business chain, further improves the business management informatization level of a gold control enterprise, effectively improves the risk prevention and control capability, reduces the operation cost and the like.
Drawings
In order to more clearly illustrate the embodiments of the present description or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some of the embodiments described in the present description, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. In the drawings:
FIG. 1 is a flow diagram of an enterprise business management method according to one or more embodiments of the present disclosure;
FIG. 2 is a schematic diagram of an enterprise business management device according to one or more embodiments of the present disclosure;
fig. 3 is a schematic structural diagram of an enterprise service management device according to one or more embodiments of the present disclosure.
Detailed Description
The embodiment of the specification provides an enterprise business management method, device, equipment and medium.
In order to make the technical solutions in the present specification better understood by those skilled in the art, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present specification, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present disclosure.
FIG. 1 is a flow diagram of an enterprise business management method, which may be implemented by an enterprise business management system, in accordance with one or more embodiments of the present disclosure. Some input parameters or intermediate results in the flow allow for manual intervention adjustments to help improve accuracy.
The method flow steps of the embodiment of the present specification are as follows:
s102, establishing an information base of the enterprise according to the related information of the enterprise.
In this embodiment of the present disclosure, identity information, operation information, and credit information of an enterprise may be obtained according to a preset government affair data sharing platform, and after the enterprise logs in the government affair data sharing platform, corresponding enterprise information may be supplemented to the government affair data sharing platform to form an information base of the enterprise.
It should be noted that, in the embodiment of the present disclosure, an information base of an enterprise is obtained according to a preset government affair data sharing platform, which specifically includes:
logging in a government affair data sharing platform: the enterprise needs to log in the government affair data sharing platform and uses the provided identity verification mode for authentication.
Acquiring enterprise information: after successful login, the related data such as identity information, business information, credit information and the like of the enterprise can be obtained through the government affair data sharing platform. Such information may come from various government agencies or organizations, including tax authorities, business authorities, human resource social security authorities, and the like.
Supplementing enterprise information: an enterprise may provide more enterprise information to the government data sharing platform through the platform to better demonstrate the condition and development plan of the enterprise. Such information may include product or service introduction of the business, market analysis reports, annual financial statements, and the like.
Forming an enterprise information base: and integrating the information provided by the enterprises and the existing government data by the government data sharing platform to form an enterprise information base. Enterprises can access and update this information at any time to better manage and utilize their own data assets.
In a word, the government affair data sharing platform can provide a convenient and quick way for enterprises to acquire, share and manage enterprise information, and has important supporting function for the development and decision of the enterprises.
S104, constructing the portrait of the enterprise according to the business of the enterprise and the information base of the enterprise.
In the embodiment of the present specification, statistical analysis may be performed on the information base of the enterprise to obtain an enterprise information tag; carrying out service modeling analysis on the service of the enterprise to obtain a service model label; and finally, constructing the portrait of the enterprise according to the enterprise information tag and the service model tag.
In the embodiment of the present specification, when constructing an enterprise portrait, the following may be specifically included:
and (5) statistically analyzing an enterprise information base: in performing statistical analysis on enterprise information bases, data mining tools and techniques can be used to identify and extract important information tags. For example, information on industry classification, market share, customer characteristics and the like of enterprises can be found through means of cluster analysis, association rule mining and the like.
And carrying out business modeling analysis: through business modeling analysis, information on the aspects of operation modes, value chains, core competitiveness and the like of enterprises can be deeply known. The business processes and corresponding information flows of the enterprise can be visually described using tools such as UML model or BPMN model.
Building an enterprise portrait: and constructing the enterprise portraits according to the enterprise information labels and the business model labels. The enterprise portrayal is a comprehensive information file, which includes basic information of enterprises, management conditions, client demands, market trends, future development plans and other information. The method can use technologies such as big data analysis, machine learning and the like to fuse data from different sources and generate a report or chart with a visual effect, so that enterprises can better understand own conditions and decisions.
By constructing enterprise portraits, enterprises can better understand own advantages and disadvantages, find market opportunities, formulate more effective business strategies and realize sustainable growth
S106, constructing a business processing module by combining the portrait of the enterprise with the approval flow and the demand of the business of the enterprise so as to fully cover the business processing of each business block and business chain of the enterprise.
In the embodiment of the present specification, when the business processing module is constructed by combining the enterprise portrait with the approval process and the requirement, the following specific contents may be included:
determining an approval process: and determining approval flows of various businesses according to the specific conditions of the enterprises. For example, the approval process of the sales order may include customer confirmation, product inventory check, price audit, etc.
Defining a service requirement: for the requirements of each business tile, a corresponding requirements document is defined. For example, to meet the semi-finished product inventory management needs of the production department, a semi-finished product warehouse-in, warehouse-out and scrapped management module needs to be established.
Designing a service processing module: based on enterprise portraits and combining approval flows and service requirements, a corresponding service processing module is designed. For example, a Business Process Management (BPM) tool may be used to integrate different approval links, business logic, and data flows to implement automated business processes.
Realizing a service processing module: and developing corresponding software or system according to the designed business processing module. This needs to involve different technical fields such as front-end interface development, back-end service interface design, database design, etc.
Testing and optimizing: before being on-line, the service processing module needs to be fully tested, and performance optimization and security check are performed to ensure that it can meet the requirements and can operate in a stable operating environment.
Through the steps, an enterprise can construct a comprehensive business processing system to realize the full-coverage management of each business plate and business chain. This may help businesses increase efficiency, reduce costs, and better cope with market changes and competitive pressures.
S108, performing risk analysis on each business plate and business chain business process of the enterprise through a risk analysis module which is constructed through big data in advance.
In the embodiment of the present disclosure, when risk analysis is performed on each business block and business chain of an enterprise, the following specific contents may be included:
collecting data: the required data is collected from enterprise information stores and other reliable data sources. Such data may include enterprise financial reports, vendor assessment reports, market research reports, public opinion monitoring data, and the like.
Risk identification: and processing and analyzing the collected data by utilizing a big data technology and algorithm, and identifying possible risk points in each business plate and business chain. For example, it may be found that there is a single dependency on the sales channel, an increase in production costs, and the like.
Risk assessment: for the identified risk points, risk assessment is performed to determine their importance and scope of influence. Different evaluation methods and tools may be used, such as sensitivity analysis, simulation, etc.
Risk management: and according to the risk assessment result, corresponding risk management measures are formulated. These measures may include improving internal control, optimizing supply chain management, formulating emergency plans, and the like. Meanwhile, a monitoring mechanism needs to be established, risks are tracked and fed back, and measures are taken timely.
Risk reporting: and generating a corresponding risk report according to the risk analysis result. The risk report should include information in terms of risk identification, assessment, and management, so that the business decision maker knows the current risk situation and takes the necessary actions.
Through a pre-constructed risk analysis module, enterprises can carry out comprehensive risk analysis on each operation plate and service chain, and corresponding measures are formulated to reduce risks and improve efficiency. This helps the enterprise better cope with market changes and competitive pressures and achieves sustainable development.
Further, in the embodiment of the present disclosure, when risk analysis is performed on each business board and business chain business process of the enterprise, risk admittance, tag anti-fraud, credit score model establishment, credit score measurement model establishment, post-credit risk early warning and risk evaluation report may be performed on each business board and business chain business process of the enterprise, where the risk admittance includes blacklist screening, policy condition admittance judgment and admittance risk scoring.
It should be noted that, the policy condition admittance judgment may set up admittance rules for the policy condition admittance model according to the self risk positioning of the financial institution, where the admittance rules are used for applying for admittance conditions of individual/individual qualification, and the policy admittance rules help the financial institution to screen out target groups meeting the standard; the policy condition access model is based on the judgment of rule items, and is used for checking whether a client meets the access qualification through specific conditions, and establishing an applied access model according to big data and financial wind control service requirements so as to evaluate whether a controlled individual meets the specified application conditions.
The label anti-fraud is subjected to anti-fraud detection based on a relation map anti-fraud detection mode, association relations in the multi-source data are mined, a relation map is established according to the association relations in the multi-source data, user map features are extracted based on the relation map by using a map algorithm and a map embedding technology, anti-fraud detection modeling is performed by using a supervised, unsupervised and semi-supervised machine learning algorithm in machine learning, and anti-fraud probability of a user is predicted.
It should be noted that, the credit score model establishment may include:
establishing a credit scoring model according to client layering, client property and liability assessment, repayment willingness assessment, each dimension assessment result, each dimension index set and user behavior data of loan individuals, establishing a credit scoring model by adopting an AHP (advanced high performance analysis) hierarchical analysis method and a rule scoring model, establishing a comprehensive credit assessment system covering two layers of dimensions, wherein the bottom layer is a secondary index set corresponding to four dimensions of loan individual basic properties, property and liability assessment, repayment willingness assessment and user behavior assessment, and each dimension respectively establishes a dimensionality credit assessment model according to each dimension index set; and taking the credit evaluation value obtained by the dimension calculation as a first-level index set, establishing an upper evaluation model by combining the weight of each dimension, and calculating the loan individual comprehensive credit evaluation.
It should be noted that, with the rapid development of the capital market and the wide application of the modern information technology, the capital market is coming into the development period of gold, but the rapid development of enterprises still has a plurality of blocking points. Firstly, the enterprise has a plurality of business scenes and is difficult to overall manage. Based on financial business scenes of multiple legal persons and multiple license plates of enterprises, interconnection and data sharing of all edition data still cannot be realized at present, and overall management and visual analysis of the data cannot be realized. Secondly, each business plate of the enterprise is independent and easy to form a data island. The management of the clients of each subsidiary company of the enterprise is independent, and the related business and the related risk cannot be effectively identified in time, so that the business approval progress and the real-time acquisition of business data have difficulties. Thirdly, enterprises lack a set of low-risk wind control systems. Based on the aspect of enterprise risk prevention and control, support application of big data, enterprise history data and the like is lacking, and centralized and unified wind control system construction at the enterprise level is lacking. Fourth, the information asymmetric enterprises can not reach the standardization of internal business behaviors. Based on the consideration of service due-job investigation behavior specification, the quality of an adjustment link is difficult to be effectively ensured due to the existence of financial distortion, information asymmetry and the like of partial enterprises at present, and a relatively standard adjustment system is lacked to be used as a service support.
From the practical business perspective of enterprises, a unified feeding system and an adjustment system are built. The unified feeding system realizes the effect that the clients can go out more than one, enhances the use experience of the clients, and improves the processing efficiency of enterprise business. Establishing a standardized complete system and establishing investigation standards based on different business plates of enterprises.
Based on the approval flows of the characteristics of different business plates, an independent business processing system is constructed, the full coverage of each business plate and business chain is realized, and the informatization level of business management is further improved.
And a basic supporting system is constructed to cover the skills, data processing capacity, overall management capacity and the like of the financial department, so that good support is provided for upper-layer application. And establishing an enterprise wind control system foundation by means of big data in the aspect of financial department skills. And building a relevant data analysis processing model by means of the platform. In the aspect of overall management, the digital management cockpit of the enterprise level is customized and developed by combining the characteristics of the gold-controlled enterprise and the business characteristics of each business plate, and the business dynamics are monitored in real time through the construction of a rich index system, so that the enterprise data is visualized, visualized and embodied.
The technical scheme of the embodiment of the specification is as follows:
business process
1) And establishing an enterprise information base. Basic information, operation information, credit information and the like of enterprises in jurisdictions are collected by using a government affair data sharing platform, and when the enterprises log in a system, the enterprises can supplement and perfect data parameters by themselves, and finally an enterprise database is formed for subsequent business management in the enterprises.
2) And constructing an enterprise portrait. And (5) accurately portraying the enterprise by applying a big data technology and a knowledge graph technology according to business requirements. The once complete enterprise portrait construction process is as follows: data collection, data cleaning, data modeling and portrait construction. The key of enterprise portraits is to output labels, carry out statistical analysis from the original data of a data warehouse to obtain fact labels, then carry out business modeling analysis to obtain model labels, and then carry out model prediction to obtain prediction labels. And confirming that enterprise portrait modeling is carried out by adopting a cluster analysis method according to service requirements, and finally outputting enterprise portrait labels which comprise three categories of enterprise own labels, model labels after enterprise portrait modeling and final forecast labels, wherein all fields obtained by screening conditions enter a subsequent data modeling flow.
3) And (5) service management. After the client applies for the gold control, based on the approval flows of the characteristics of different business plates, an independent business processing system is constructed, the full coverage of each business plate and business chain is realized, and the informatization level of business management is further improved.
4) Risk analysis. And establishing an enterprise unified wind control system by means of big data. By effectively docking with a big data bureau, a wind control decision engine platform is built, and a relevant data analysis processing model is built by means of the platform. The establishment of the model system can objectively and accurately form a risk screening report of the client, and is respectively applied to pre-loan auditing, loan stroke control and post-loan monitoring, so as to enable the auxiliary decision-making of each edition business.
Detailed description of the examples
1. Marketing system
The marketing system is a product application interface of a user, and functions of product application, order viewing, online signing, message reminding and the like of the user are realized. Helping customers to realize online applications for financial products.
The client part feeding channel is a WeChat end and a PC end, and can also be connected with a third party platform in a butt joint manner, so that the expansion of a marketing entrance is realized.
2. Adjustment system
The system is arranged at the Pad end, so that the system is convenient to adjust in a down-line manner. The information filling operation can also be directly carried out by using the PC end to fill in the basic information of the client due-job investigation link, the information of the bottom layer asset and the like, the informatization, paperless and standardization of the due-job investigation link are realized, the labor cost is reduced, the working efficiency is improved, and the information backfilling can be directly carried out without repeated operation.
And the client manager completes the collection and confirmation of information such as the operation condition, financial data, social credibility and the like of the client through the built-in adjustment template. The interface adjusting part adopts a selection mode, so that the working efficiency of a business manager is conveniently improved.
The debug interface is divided into a fixed information interface and a field investigation information interface. The fixed information interface is mainly aimed at the fixed information of the client, such as business license pictures, legal identity card pictures, registration information and the like, and the system pre-fills the fixed information according to the third party information and the client library and verifies the fixed information by a client manager. The system can automatically identify and judge the valid period of the related certificates, and remind a business manager of modifying the certificates exceeding the valid period.
After finishing verification and modification and confirmation aiming at the fixed information interface, the business manager clicks the field investigation information interface.
For key information such as financial data, the system can automatically generate a financial data inspection interface after completing on-site adjustment. The key information is conveniently checked by a business manager.
By interfacing with third party data and analyzing customer data, a risk report is formed. And reporting and displaying contents such as basic information, credit investigation information, risk information and the like of the client, and grading the credit condition of the client by utilizing a big data analysis technology to help a business manager to make full judgment on the credit condition of the client.
3. Service system
Through the application of the client products of the marketing system, the application information of the client business is displayed in a list form, and the management and the viewing of the system are facilitated. By clicking the data for checking, the network third party data can be called to check the basic information of the clients except the financing application information, so that business personnel can primarily judge the clients. In addition, the third party data can be called to form a credit risk evaluation report of the client, so that the business personnel can primarily judge the credit risk condition of the client.
And clicking agreements for business applications passing the initial examination to enter the debugging program. The data generated by the prior service application is synchronously given to the modulating system, so that the workload of a modulating service manager is reduced.
The platform forms a credit report according to the user authorization application, and gives corresponding analysis basis, conclusion and suggestion for the financial institution to refer.
And evaluating the fraud risk and the credit risk of the clients through the credit report, and eliminating the fraudulent clients and clients with higher credit risk. Generating an enterprise pre-examination risk evaluation report according to the credit risk level of the client; and displaying the generated enterprise pre-review risk evaluation report in the form of a platform page and structured data.
And (3) reviewing and investigating business data (adjustment report and the like) submitted by sponsors, verifying relevant contents of the investigation report, indicating risks possibly generated in the business handling process, providing handling comments, and reporting to a company wind control part for auditing.
And (3) completing a business approval process, generating a contract by the system according to the prefabricated template, and sending the contract to a client application end to complete online signing. The system is used for interfacing with third party software (seal manager, electronic signature system and the like), sending generated contract materials to a client, completing on-line signing of the contract after signing and company signing by a client, and carrying out system record.
The contract signed offline supports uploading in the form of images or files as a record keeping.
4. Wind control system
The wind control system is a core module for providing financial department skill support for the business, and builds model support capability for covering the whole business flow through big data modeling technology, wherein the model support capability comprises risk admittance, label anti-fraud, credit scoring model, limit measuring and calculating model, post-credit risk early warning, risk evaluation report and the like.
4.1 Risk Admission
The method comprises the steps of constructing a fusion scoring method, a peer labeling five-division method, a numerical interval method, a classification method and other evaluation methods aiming at products, making a targeted admittance model aiming at finely divided passenger gas, and carrying out sub-division to three-level indexes on a plurality of primary indexes such as a passenger group management environment, management quality, business and management and risk management, and constructing the admittance model through different scoring modes.
4.1.1 blacklist screening
The blacklist screening data mainly originates from individual industrial and commercial operators and small micro-business owners with serious illegal beliefs and serious tax violations. And integrating negative information in the blacklist screening process, taking the weight and influence factors into consideration, applying the negative information to the applicant, the common borrower (spouse), family members and individuals according to different rules, and performing one-ticket overrule on the crowd triggering the blacklist.
4.1.2 policy conditional Access model
And setting up an admission rule according to the self risk positioning of the financial institution, namely, for applying for admission conditions of individual/individual qualification, helping the financial institution to screen out target groups meeting the standard through the policy admission rule.
The admission model is based on the judgment of the rule items, and the client is checked whether the client meets the admission qualification or not through specific conditions. The admission model is established according to big data and financial wind control business requirements and is used for evaluating whether a controlled individual meets specified application conditions, the admission model is mainly based on a rule method to check whether the individual meets admission qualification or not through specific conditions, the setting of admission indexes can be continuously and iteratively increased according to requirements of management departments, and the method of supervision learning or semi-supervision learning in machine learning can be introduced to judge whether the admission characteristics are added or not along with continuous expansion of data and continuous richness of dimensions in the later period.
4.1.3 Admission risk scoring model
The admission risk score is mainly established for two major types of negative list data, namely fact risk data which occur to the user, and non-fact risk data which possibly cause risk occurrence such as loss of business, social security accumulation and collection, marital status change, industrial injury and the like. When the customer stock data is absent or the stock data is smaller, an AHP scoring or rule scoring method is adopted to establish an admission risk rule scoring model, and the admission risk rule scoring model is mainly realized through the processes of extracting admission risk assessment indexes, index value grading, index grading, index weighting, risk grading calculation and the like. Firstly, extracting corresponding risk indexes aiming at risk data, such as total times of illegal and illegal infraction occurring in the last year, score of traffic infraction score of six months, total times of traffic accidents occurring in six months, tax punishment amount, overdue loan count, divorce, loss of business, labor contract termination time and the like, wherein the extraction of the risk indexes is required to be formed on the basis of fully researching a risk admittance policy and a product admittance condition, and the effectiveness of the risk indexes is fully ensured; determining index grading according to the extracted indexes, assigning each index grading, and assigning indexes and grading according to service policies by combining accumulated data of constructors and service experience of modelers when the stock data is absent.
After the admission risk rule scoring model is established, the index grading and grading assignment are verified and optimized according to the continuous expansion of the data; along with the accumulation of data, a customer training sample can be extracted, a customer positive training sample is extracted based on a class A taxpayer, a red list and an internal rating class A, a customer negative training sample is extracted based on a class D data of a tax rating class D and a credit rating class D of a credit rating is executed, and an admission risk machine learning assessment model is established by adopting supervised learning modes such as logistic regression, integrated learning and the like; and cross-verifying the rule scoring model through the machine learning model, or establishing a fusion strategy to perform fusion modeling on the two models, so that the on-line admission model pre-judging effect is fully ensured. The admission risk scoring model pre-judges the risk score of the client, establishes a risk threshold for the client, and when the client triggers the admission risk threshold, the online flow can perform admission interception on the client to reject the application requirement of the client.
4.2 tag anti-fraud
The anti-fraud detection is one of important links in financial wind control, the platform adopts an anti-fraud detection method based on a relationship map to carry out anti-fraud detection, the relationship map is established by mining the intricate and complex association relationship in multi-source data covered by the platform, the user map features are extracted based on the relationship map by using a map algorithm and a map embedding technology, and anti-fraud detection modeling is carried out by using a supervised, unsupervised and semi-supervised machine learning method in machine learning, community detection, label propagation and other algorithms to predict the anti-fraud probability of the user. In the construction process, a blacklist label library and a relation map are firstly established, and anti-fraud detection is carried out on users based on the blacklist label library and the relation map.
4.3 Credit scoring model
The platform establishes a comprehensive credit assessment model by combining each dimension assessment result, each dimension index set and user behavior data of loan individuals on the platform on the basis of client layering, client property and liability assessment and repayment willingness assessment. The method mainly comprises the steps of establishing a comprehensive credit assessment model by adopting an AHP and rule scoring model, establishing a comprehensive credit assessment system covering two dimensions, wherein the bottom layer is a secondary index set corresponding to four dimensions of loan individual basic attribute, asset and liability assessment, repayment willingness assessment and user behavior assessment, and each dimension respectively establishes a dimensionality credit assessment model according to each dimension index set; on the basis, the credit evaluation value obtained by the dimension calculation is used as a first-level index set, an upper evaluation model is built by combining the weight of each dimension, and the loan individual comprehensive credit evaluation is calculated. The construction of each subdivision model carries out credit assessment on loan individuals from each dimensionality, can carry out multidimensional and multi-angle credit analysis on the loan individuals, has adaptability to data, can construct subdivision models of aggregated data in the form of subdivision models according to continuous expansion of data, and constructs subdivision models of new data after new data are aggregated, so that the new data are flexibly integrated into the comprehensive credit assessment model in the form of flexible component configuration, and the assessment effect of the credit assessment model is fully ensured.
After credit evaluation calculates credit scores of loans, the credit score results of individuals are classified into five grades or ten grades of A, B, C, D, E by selecting specific scores as classification standards of credit grades, the credit grades of the individuals are classified, and the credit score results of the individuals are adjusted and calibrated by methods such as a score difference maximization function between grades, a performance rate increment test, a standard calibration and the like, so that an individual credit rating model meeting business requirements is finally formed.
The credit assessment model can predict the default risk of loan individuals after being paid, so that institutions can combine business indexes such as risk preference, passing rate and the like to formulate flexible processing strategies; meanwhile, the manager is assisted to rapidly judge the default risk of the potential client, and the worthless cost of acquiring the client is avoided.
4.4 post-loan risk early warning
4.4.1 real-time Risk early warning
Any risk situation of the loan individual can lead to overdue risk, real-time risk monitoring can be carried out aiming at the loan individual platform, and warning is sent out on the basis of monitoring, analyzing and distinguishing the financial factors and the non-financial factors of the loan individual.
4.4.2 stock risk Pre-alarm
The monitoring of the real-time risk of the loan individual is real-time risk monitoring aiming at financial or non-financial factors of the loan individual, the risk of real-time monitoring of the loan individual along with the change of the loan individual data and the restoration of the risk also disappears, the early warning signal also pauses, the temporary risk of the loan individual often is restored, but the occurrence of some financial or non-financial risk factors can cause the potential or secondary overdue risk of the loan individual, aiming at the situation, the platform establishes a stock risk pre-judging model according to three-party risk stock data gathered by the loan individual, user behavior data of the loan individual on the platform and all recorded historical risk events by adopting a supervised and semi-supervised machine learning algorithm, forms a risk monitoring index through index extraction, trains the stock risk pre-judging model through processes such as feature pre-processing, feature screening, model parameter iterative optimization, model verification and adjustment, and the like, and periodically updates the stock risk pre-judging model by running the three-party data of a full-volume loan customer.
5. Overall analysis
Combines the characteristics of alloy control enterprises and the business characteristics of each business plate, customizes and develops the digital management cockpit of enterprises and industry unit layers, builds through rich index systems, monitors business dynamics in real time, and visualizes, visualizes and embodies data.
6. Client system
The client library takes a single client as a dimension, performs multidimensional analysis and management on the client through external big data and delivery conditions, and can check the full-link delivery association condition of the client to realize hierarchical management of the client.
And for the users who have applied for the business, displaying all the client data and client portraits applying for the loan. The customer portrait is to make multidimensional judgment and drawing on the customer by calling the portrait model, and after clicking the detail page, all detail service fields of the loan applied by the customer are displayed.
It should be noted that, the embodiment of the specification has the characteristics of management visualization, data base wisdom, marketing system datamation, business management informatization, adjustment flow standardization, risk monitoring automation and the like, realizes full coverage of each operation plate and business chain, further improves the business management informatization level of a gold control enterprise, effectively improves the risk prevention and control capability, reduces the operation cost and the like.
Fig. 2 is a schematic structural diagram of an enterprise business management apparatus according to one or more embodiments of the present disclosure, where the apparatus includes: an information base building unit 202, a portrait building unit 204, a business processing module building unit 206 and a risk analysis unit 208.
An information base establishing unit 202 for establishing an information base of an enterprise according to related information of the enterprise;
a portrait construction unit 204 for constructing a portrait of the enterprise based on the business of the enterprise and the information base of the enterprise;
a business processing module construction unit 206, which combines the portrait of the enterprise with the approval flow and the requirement of the business of the enterprise to construct a business processing module so as to fully cover the business processes of each business block and business chain of the enterprise;
and the risk analysis unit 208 performs risk analysis on each business plate and business chain business process of the enterprise through a risk analysis module constructed through big data in advance.
Fig. 3 is a schematic structural diagram of an enterprise service management device according to one or more embodiments of the present disclosure, including:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
establishing an information base of an enterprise according to related information of the enterprise;
constructing a portrait of the enterprise according to the business of the enterprise and the information base of the enterprise;
constructing a business processing module by combining the portrait of the enterprise with the approval flow and the demand of the business of the enterprise so as to fully cover the business processing of each business block and business chain of the enterprise;
and carrying out risk analysis on each business plate and business chain business process of the enterprise through a risk analysis module constructed through big data in advance.
One or more embodiments of the present description provide a non-volatile computer storage medium storing computer-executable instructions that, when executed by a computer, enable:
establishing an information base of an enterprise according to related information of the enterprise;
constructing a portrait of the enterprise according to the business of the enterprise and the information base of the enterprise;
constructing a business processing module by combining the portrait of the enterprise with the approval flow and the demand of the business of the enterprise so as to fully cover the business processing of each business block and business chain of the enterprise;
and carrying out risk analysis on each business plate and business chain business process of the enterprise through a risk analysis module constructed through big data in advance.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for apparatus, devices, non-volatile computer storage medium embodiments, the description is relatively simple, as it is substantially similar to method embodiments, with reference to the section of the method embodiments being relevant.
The foregoing describes specific embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can 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 are also possible or may be advantageous.
The foregoing is merely one or more embodiments of the present description and is not intended to limit the present description. Various modifications and alterations to one or more embodiments of this description will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, or the like, which is within the spirit and principles of one or more embodiments of the present description, is intended to be included within the scope of the claims of the present description.
Claims (10)
1. A method for enterprise business management, the method comprising:
establishing an information base of an enterprise according to related information of the enterprise;
constructing a portrait of the enterprise according to the business of the enterprise and the information base of the enterprise;
constructing a business processing module by combining the portrait of the enterprise with the approval flow and the demand of the business of the enterprise so as to fully cover the business processing of each business block and business chain of the enterprise;
and carrying out risk analysis on each business plate and business chain business process of the enterprise through a risk analysis module constructed through big data in advance.
2. The method of claim 1, wherein the establishing an information base of the business based on the related information of the business comprises:
and acquiring identity information, management information and credit information of the enterprise according to a preset government affair data sharing platform, and supplementing corresponding enterprise information to the government affair data sharing platform after the enterprise logs in the government affair data sharing platform to form an information base of the enterprise.
3. The method of claim 1, wherein constructing the representation of the business from the business of the business and the information base of the business comprises:
carrying out statistical analysis on the information base of the enterprise to obtain an enterprise information tag;
carrying out service modeling analysis on the service of the enterprise to obtain a service model label;
and constructing the portrait of the enterprise according to the enterprise information tag and the service model tag.
4. The method of claim 1, wherein said risk analysis of each business segment and business chain business process of said enterprise comprises:
and performing risk admittance, label anti-fraud, credit scoring model establishment, credit measuring and calculating model establishment, post-loan risk early warning and risk evaluation reporting on each business plate and business chain business processing of the enterprise, wherein the risk admittance comprises blacklist screening, policy condition admittance judgment and admittance risk scoring.
5. The method according to claim 4, wherein the policy condition admittance determination is that a policy condition admittance model establishes admittance rules according to self risk positioning of the financial institution, the admittance rules are used for admittance conditions for applying individual/individual qualification, and the policy admittance rules help the financial institution to screen out target groups meeting standards; wherein, the liquid crystal display device comprises a liquid crystal display device,
the policy condition access model is based on the judgment of rule items, and is used for checking whether a client meets the access qualification through specific conditions, establishing an applied access model according to big data and financial wind control service requirements, and evaluating whether a controlled individual meets the specified application conditions.
6. The method of claim 4, wherein the tag anti-fraud is based on anti-fraud detection mode of a relation map, the association relation in the multi-source data is mined, the relation map is established according to the association relation in the multi-source data, the user map features are extracted based on the relation map by using a map algorithm and a map embedding technology, anti-fraud detection modeling is performed by using a supervised, unsupervised and semi-supervised machine learning algorithm in machine learning, and the anti-fraud probability of the user is predicted.
7. The method of claim 4, wherein the credit scoring model building comprises:
establishing a credit scoring model according to client layering, client property and liability assessment, repayment willingness assessment, each dimension assessment result, each dimension index set and user behavior data of loan individuals, establishing a credit scoring model by adopting an AHP (advanced high performance analysis) hierarchical analysis method and a rule scoring model, establishing a comprehensive credit assessment system covering two layers of dimensions, wherein the bottom layer is a secondary index set corresponding to four dimensions of loan individual basic properties, property and liability assessment, repayment willingness assessment and user behavior assessment, and each dimension respectively establishes a dimensionality credit assessment model according to each dimension index set; and taking the credit evaluation value obtained by the dimension calculation as a first-level index set, establishing an upper evaluation model by combining the weight of each dimension, and calculating the loan individual comprehensive credit evaluation.
8. An enterprise business management apparatus, the apparatus comprising:
the information base establishing unit establishes an information base of the enterprise according to the related information of the enterprise;
a portrait construction unit for constructing a portrait of the enterprise according to the business of the enterprise and the information base of the enterprise;
the business processing module construction unit is used for constructing a business processing module by combining the portrait of the enterprise with the approval flow and the requirement of the business of the enterprise so as to fully cover the business processing of each business plate and business chain of the enterprise;
and the risk analysis unit is used for carrying out risk analysis on each business plate and business chain business process of the enterprise through a risk analysis module constructed through big data in advance.
9. An enterprise business management apparatus, comprising:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
establishing an information base of an enterprise according to related information of the enterprise;
constructing a portrait of the enterprise according to the business of the enterprise and the information base of the enterprise;
constructing a business processing module by combining the portrait of the enterprise with the approval flow and the demand of the business of the enterprise so as to fully cover the business processing of each business block and business chain of the enterprise;
and carrying out risk analysis on each business plate and business chain business process of the enterprise through a risk analysis module constructed through big data in advance.
10. A non-transitory computer storage medium storing computer executable instructions that when executed by a computer enable:
establishing an information base of an enterprise according to related information of the enterprise;
constructing a portrait of the enterprise according to the business of the enterprise and the information base of the enterprise;
constructing a business processing module by combining the portrait of the enterprise with the approval flow and the demand of the business of the enterprise so as to fully cover the business processing of each business block and business chain of the enterprise;
and carrying out risk analysis on each business plate and business chain business process of the enterprise through a risk analysis module constructed through big data in advance.
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| CN117314163A (en) * | 2023-09-27 | 2023-12-29 | 吉贝克信息技术（北京）有限公司 | Social security data processing method and system based on big data |
| CN117314163B (en) * | 2023-09-27 | 2024-04-12 | 吉贝克信息技术（北京）有限公司 | Social security data processing method and system based on big data |
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