CN118154333B - Intelligent electronic policy service management system based on Internet - Google Patents
Intelligent electronic policy service management system based on Internet Download PDFInfo
- Publication number
- CN118154333B CN118154333B CN202410589363.7A CN202410589363A CN118154333B CN 118154333 B CN118154333 B CN 118154333B CN 202410589363 A CN202410589363 A CN 202410589363A CN 118154333 B CN118154333 B CN 118154333B
- Authority
- CN
- China
- Prior art keywords
- electronic
- service
- time
- business
- data analysis
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000008901 benefit Effects 0.000 claims abstract description 41
- 238000007405 data analysis Methods 0.000 claims description 102
- 238000004458 analytical method Methods 0.000 claims description 32
- 238000005457 optimization Methods 0.000 claims description 27
- 230000004044 response Effects 0.000 claims description 14
- 238000013178 mathematical model Methods 0.000 claims description 11
- 238000011156 evaluation Methods 0.000 claims description 10
- 230000006872 improvement Effects 0.000 claims description 6
- 238000002360 preparation method Methods 0.000 claims description 6
- PCHJSUWPFVWCPO-UHFFFAOYSA-N gold Chemical compound [Au] PCHJSUWPFVWCPO-UHFFFAOYSA-N 0.000 claims description 5
- 239000010931 gold Substances 0.000 claims description 5
- 229910052737 gold Inorganic materials 0.000 claims description 5
- 238000012545 processing Methods 0.000 claims description 5
- 238000011161 development Methods 0.000 abstract description 3
- 230000008676 import Effects 0.000 description 6
- 238000013480 data collection Methods 0.000 description 4
- 230000000694 effects Effects 0.000 description 4
- 238000000034 method Methods 0.000 description 3
- 238000012544 monitoring process Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 2
- 238000009826 distribution Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000013486 operation strategy Methods 0.000 description 2
- 230000002265 prevention Effects 0.000 description 2
- 238000007418 data mining Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/08—Insurance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/018—Certifying business or products
- G06Q30/0185—Product, service or business identity fraud
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Accounting & Taxation (AREA)
- General Physics & Mathematics (AREA)
- Finance (AREA)
- Economics (AREA)
- Marketing (AREA)
- Theoretical Computer Science (AREA)
- Strategic Management (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Development Economics (AREA)
- Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Entrepreneurship & Innovation (AREA)
- Human Resources & Organizations (AREA)
- General Health & Medical Sciences (AREA)
- Technology Law (AREA)
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses an intelligent electronic policy service management system based on the Internet, and particularly relates to the technical field of electronic policy service management. The invention realizes the comprehensive intelligent management of the electronic security service, can improve the electronic security transaction efficiency, optimize the user behavior, improve the service benefit, reduce the service risk, provides a more efficient, convenient and safe solution for the electronic security service management, can effectively promote the development of the electronic security service, and provides higher-quality and efficient financial services for enterprises and individuals.
Description
Technical Field
The invention relates to the technical field of electronic warranty service management, in particular to an intelligent electronic warranty service management system based on the Internet.
Background
The electronic insurance is a novel guaranty certificate in the information age, the legal effectiveness of the electronic guaranty is realized through a computer network by adopting a CA certificate electronic signature technology, and the electronic guaranty is opened, transmitted and stored in the whole process.
The existing electronic warranty service management system firstly collects and integrates service data, including information of various links such as warranty application, issuing, cashing and the like, then, through data mining and algorithm analysis, the system performs deep analysis on the service data, identifies potential risks, generates a monitoring report, and can timely adjust service strategies and optimize service flows according to the report by a manager.
However, when the system is actually used, some disadvantages still exist, such as the existing electronic warranty service management system mainly focuses on some basic service indexes and data, and for more complex service modes and potential risks, deep mining and analysis may be lacking, which may cause some potential problems and risks to be ignored, so that the safety and stability of the service are affected, and the algorithm is too simple or single and cannot fully mine and utilize the acquired data, and the existing management system may mainly rely on traditional statistical methods and simple machine learning models for analysis, and the algorithm may not look at the heart when complex and variable data are processed, so that the analysis result is inaccurate or deep.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, an embodiment of the present invention provides an intelligent electronic policy service management system based on the internet, which solves the problems set forth in the above-mentioned background art through the following scheme.
In order to achieve the above purpose, the present invention provides the following technical solutions: an internet-based intelligent electronic policy service management system, comprising:
Management time dividing module: the management time of the target electronic policy service is determined to be a target time area, and the target time area is divided into sub-time areas in an equal time division mode and is marked as 1 and 2 … … n in sequence;
Service operation data acquisition module: operating and collecting transaction data, user behavior data and service benefit data of each sub-time region, and transmitting the collected data to a service operation data analysis module;
And a business operation data analysis module: the system comprises a transaction data analysis unit, a user behavior data analysis unit and a service benefit data analysis unit, and transmits the analyzed data to a service comprehensive analysis module;
The business risk data acquisition module: the system comprises a service risk data analysis module, a risk early warning module, a payment data acquisition module, a service operation error data acquisition module and a risk early warning module, wherein the service risk data acquisition module is used for acquiring the payment data, the service operation error data and the risk early warning data of each sub-time region;
business risk data analysis module: the system comprises a pay data analysis unit, a business operation error data analysis unit and a risk early warning data analysis unit, and transmits the analyzed data to a business comprehensive analysis module;
And a business comprehensive analysis module: the system comprises a business operation data analysis module, a business risk data analysis module, a business comprehensive analysis module, a management module and a management module, wherein the business operation data analysis module is used for establishing a business comprehensive analysis model, importing data transmitted by the business operation data analysis module and the business risk data analysis module into the business comprehensive analysis model, calculating a comprehensive optimization index of a target electronic warranty business, and transmitting the comprehensive optimization index to the management module;
and a management module: and the system is used for managing the target electronic warranty business according to the comprehensive optimization index target value.
Preferably, the transaction data includes an electronic policy issuing amount, an electronic policy average issuing duration, an electronic policy online application duty ratio, and an electronic policy instant effective duty ratio, which are respectively marked as Ls, lt, lr, and Lm, the user behavior data includes a user number, a frequency of accessing the electronic policy platform by the user, a number of times the user consults with the electronic policy service, and a renewal rate, which are respectively marked as Us, uf, uc, and Ur, and the service benefit data includes an average saving deposit amount, a cash flow improvement rate brought by the electronic policy service, an enterprise financing cost saved by the electronic policy service, and an enterprise bidding success rate increased by the electronic policy service, which are respectively marked as Bd, bc, bs, and Bu.
Preferably, the transaction data analysis unit is configured to establish a transaction data analysis model, import transaction data transmitted by the service operation data acquisition module into the transaction data analysis model, and calculate an electronic warranty transaction efficiency value of each sub-time region, where the specific digital model is: OL i represents the electronic warranty transaction efficiency value of the ith sub-time area, LS i represents the electronic warranty issue quantity of the ith sub-time area, lt i represents the average electronic warranty issue duration of the ith sub-time area, lr i represents the electronic warranty online application duty ratio of the ith sub-time area, and Lm i represents the electronic warranty instant effective duty ratio of the ith sub-time area.
Preferably, the user behavior data analysis unit is configured to establish a user behavior data analysis model, import the user behavior data transmitted by the service operation data acquisition module into the user behavior data analysis model, and calculate a user behavior feature value of each sub-time region, where the specific digital model is: OU i represents the user behavior characteristic value of the ith sub-time area, us i represents the number of users of the ith sub-time area, uf i represents the frequency of access to the electronic policy platform by the users of the ith sub-time area, uc i represents the number of times the users of the ith sub-time area consult the electronic policy service, and Ur i represents the renewal rate of the ith sub-time area.
Preferably, the service benefit data analysis unit is configured to establish a service benefit data analysis model, import service benefit data transmitted by the service operation data acquisition module into the service benefit data analysis model, and calculate an electronic protection service benefit evaluation value of each sub-time region, where the specific digital model is: OB i represents an electronic policy service benefit evaluation value of the i-th sub-time region, bd i represents an average saving guarantee amount of the i-th sub-time region, bc i represents a cash flow improvement rate by the electronic policy service of the i-th sub-time region, bs i represents an enterprise financing cost of the electronic policy service saving of the i-th sub-time region, and Bu i represents an enterprise bidding success rate of the electronic policy service increase of the i-th sub-time region.
Preferably, the payable data includes an electronic policy payable rate, an electronic policy violation number, an electronic policy risk preparation balance, and an electronic policy payable duration, which are respectively marked as Sr, su, sb, and St, the service operation error data includes a service interruption number, an electronic policy generation or decryption failure number, an electronic policy service operation error number, and an electronic policy service average response time, which are respectively marked as Md, ml, mr, and Mt, and the risk early-warning data includes a risk early-warning event number, a risk early-warning processing time, and a risk early-warning resolution, which are respectively marked as Ew, et, and Er.
Preferably, the claim data analysis unit is configured to establish a claim data analysis model, import the claim data transmitted by the business risk data acquisition module into the claim data analysis model, and calculate an electronic protection function claim efficiency value of each sub-time region, where the specific mathematical model is: LS i represents the electronic warranty payoff efficacy value of the ith sub-time zone, sr i represents the electronic warranty payoff rate of the ith sub-time zone, su i represents the number of electronic warranty default cases of the ith sub-time zone, sb i represents the electronic warranty risk preparation gold balance of the ith sub-time zone, st i represents the electronic warranty payoff duration of the ith sub-time zone, and Δt represents the time difference between the ith sub-time zone and the ith-1 sub-time zone.
Preferably, the business operation error data analysis unit is configured to establish a business operation error data analysis model, import the business operation error data transmitted by the business risk data acquisition module into the business operation error data analysis model, and calculate an electronic policy operation error feature value of each sub-time region, where the specific mathematical model is: LM i represents the electronic warranty operation error characteristic value of the ith sub-time area, md i represents the service interruption times caused by the failure of the electronic warranty system of the ith sub-time area, ml i represents the electronic warranty generation or decryption failure times of the ith sub-time area, mr i represents the electronic warranty service operation error number of the ith sub-time area, mt i represents the average response time of the electronic warranty service of the ith sub-time area, mt max represents the maximum response time of the electronic warranty service of the target time area, and Mt min represents the minimum response time of the electronic warranty service of the target time area.
Preferably, the risk early-warning data analysis unit is configured to establish a risk early-warning data analysis model, import risk early-warning data transmitted by the business risk data acquisition module into the risk early-warning data analysis model, and calculate an electronic protection risk early-warning efficacy value of each sub-time region, where the specific mathematical model is: LE i represents the electronic warranty risk early warning efficacy value of the ith sub-time region, ew i represents the number of risk early warning events of the ith sub-time region, et i represents the risk early warning processing time of the ith sub-time region, and Er i represents the risk early warning release rate of the ith sub-time region.
Preferably, the business risk data analysis module calculates an electronic warranty risk optimization index of the ith sub-time region according to the electronic warranty pay efficiency value of the ith sub-time region, the electronic warranty operation error feature value of the ith sub-time region and the electronic warranty risk early warning efficiency value of the ith sub-time region, and the specific mathematical model is as follows: σ i represents the electronic warranty risk optimization index of the ith sub-time region, where [ mu ] represents other influencing factors of the electronic warranty risk optimization index.
Preferably, the service comprehensive analysis model specifically represents: η represents a comprehensive optimization index of the target electronic policy service, OL i represents an electronic policy transaction efficiency value of the ith sub-time area, OU i represents a user behavior characteristic value of the ith sub-time area, us i represents the number of users of the ith sub-time area, OB i represents an electronic policy service benefit evaluation value of the ith sub-time area, σ i represents an electronic policy risk optimization index of the ith sub-time area, and λ represents other influencing factors of the comprehensive optimization index.
Preferably, the comprehensive optimization index target value is marked as eta tar, when eta tar is smaller than eta, the operation effect of the target electronic warranty service is good, the collection and analysis of service operation data and service risk data are kept, when eta tar is larger than eta, the operation effect of the target electronic warranty service is poor, the data transmitted by the service operation data collection module and the service risk data collection module are stored, and abnormal signals are sent to a manager.
The invention has the technical effects and advantages that:
According to the invention, the management time of the target electronic policy service can be accurately divided by the management time division module to form a plurality of sub-time areas, so that enterprises can better grasp the time distribution of the service, and more targeted management and optimization are performed for different time periods; transaction data, user behavior data and service benefit data of each sub-time region can be comprehensively collected through the service operation data collection module, so that not only is service operation conditions reflected, but also the use habit and preference of a user are revealed, enterprises can know the service operation conditions in depth, potential problems and opportunities are found, and powerful support is provided for decision making; the collected business operation data is subjected to deep analysis through the business operation data analysis module, so that the enterprise can be helped to find out bottlenecks and advantages in operation, key factors influencing business benefits are identified, the enterprise is helped to formulate a more scientific and reasonable operation strategy, the business process is optimized, and the business benefits are improved; the business risk data acquisition module is used for acquiring data related to business risks, including factors possibly causing risks, probability of risk occurrence, loss possibly caused by risks and the like, and enterprises can timely know business risk conditions through the acquisition of the data, so that data support is provided for risk prevention and response; the business risk data is subjected to deep analysis through the business risk data analysis module, so that the intrinsic law and characteristics of risks can be revealed, the enterprises are helped to identify main risk sources and potential risk points, the enterprises are helped to formulate targeted risk precautionary measures, the business risks are reduced, and the steady development of the business is ensured; the business comprehensive analysis module is used for comprehensively analyzing business operation data and business risk data to form comprehensive evaluation on the overall business condition, so that enterprises can know the business condition from multiple angles, advantages and disadvantages in business are found, and powerful support is provided for formulating a more comprehensive and scientific business management strategy; the management module is used for realizing comprehensive monitoring and management of service operation, finding and solving problems in time and ensuring smooth service operation.
Drawings
Fig. 1 is a schematic diagram of the overall structure of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, an intelligent electronic policy service management system based on the internet includes a management time dividing module, a service operation data acquisition module, a service operation data analysis module, a service risk data acquisition module, a service risk data analysis module, a service comprehensive analysis module, and a management module.
The management time dividing module is used for determining the management time of the target electronic policy service as a target time region, dividing the target time region into sub-time regions in an equal time dividing mode, and marking the sub-time regions as 1 and 2 … … n in sequence.
The business operation data acquisition module is used for acquiring transaction data, user behavior data and business benefit data of each sub-time region in an operation mode, and transmitting acquired numbers to the business operation data analysis module.
The transaction data comprises an electronic policy issuing amount, an electronic policy average issuing duration, an electronic policy online application duty ratio and an electronic policy instant effective duty ratio, which are respectively marked as Ls, lt, lr and Lm, the user behavior data comprises the number of users, the frequency of users accessing an electronic policy platform, the number of times users consult electronic policy services and the renewal rate, which are respectively marked as Us, uf, uc and Ur, the service benefit data comprises an average saving and guarantee amount, a cash flow improvement rate brought by an electronic policy service, an enterprise financing cost saved by the electronic policy service and an enterprise bidding success rate increased by the electronic policy service, which are respectively marked as Bd, bc, bs and Bu.
The business operation data analysis module comprises a transaction data analysis unit, a user behavior data analysis unit and a business benefit data analysis unit, and transmits the analyzed data to the business comprehensive analysis module.
The transaction data analysis unit is used for establishing a transaction data analysis model, importing transaction data transmitted by the business operation data acquisition module into the transaction data analysis model, and calculating the electronic warranty transaction efficiency value of each sub-time region, wherein the specific digital model is as follows: OL i represents the electronic warranty transaction efficiency value of the ith sub-time area, LS i represents the electronic warranty issue quantity of the ith sub-time area, lt i represents the average electronic warranty issue duration of the ith sub-time area, lr i represents the electronic warranty online application duty ratio of the ith sub-time area, and Lm i represents the electronic warranty instant effective duty ratio of the ith sub-time area.
The user behavior data analysis unit is used for establishing a user behavior data analysis model, importing the user behavior data transmitted by the business operation data acquisition module into the user behavior data analysis model, and calculating the user behavior characteristic value of each sub-time region, wherein the specific digital model is as follows: OU i represents the user behavior characteristic value of the ith sub-time area, us i represents the number of users of the ith sub-time area, uf i represents the frequency of access to the electronic policy platform by the users of the ith sub-time area, uc i represents the number of times the users of the ith sub-time area consult the electronic policy service, and Ur i represents the renewal rate of the ith sub-time area.
The service benefit data analysis unit is used for establishing a service benefit data analysis model, importing service benefit data transmitted by the service operation data acquisition module into the service benefit data analysis model, and calculating an electronic protection service benefit evaluation value of each sub-time region, wherein the specific digital model is as follows: OB i represents an electronic policy service benefit evaluation value of the i-th sub-time region, bd i represents an average saving guarantee amount of the i-th sub-time region, bc i represents a cash flow improvement rate by the electronic policy service of the i-th sub-time region, bs i represents an enterprise financing cost of the electronic policy service saving of the i-th sub-time region, and Bu i represents an enterprise bidding success rate of the electronic policy service increase of the i-th sub-time region.
The business risk data acquisition module is used for acquiring the pay data, the business operation error data and the risk early warning data of each sub-time region and transmitting the acquired data to the business risk data analysis module.
The payable data comprises electronic insurance payable rate, electronic insurance default case number, electronic insurance risk preparation gold balance and electronic insurance payable duration, which are respectively marked as Sr, su, sb and St, the business operation error data comprises business interruption times, electronic insurance generation or decryption failure times, electronic insurance business operation error numbers and electronic insurance service average response time caused by electronic insurance system faults, which are respectively marked as Md, ml, mr and Mt, and the risk early warning data comprises risk early warning event number, risk early warning processing time and risk early warning release rate, which are respectively marked as Ew, et and Er.
The business risk data analysis module comprises a pay data analysis unit, a business operation error data analysis unit and a risk early warning data analysis unit, and transmits the analyzed data to the business comprehensive analysis module.
The claim data analysis unit is used for establishing a claim data analysis model, importing the claim data transmitted by the business risk data acquisition module into the claim data analysis model, and calculating the electronic protection function claim efficiency value of each sub-time region, wherein the specific mathematical model is as follows: LS i represents the electronic warranty payoff efficacy value of the ith sub-time zone, sr i represents the electronic warranty payoff rate of the ith sub-time zone, su i represents the number of electronic warranty default cases of the ith sub-time zone, sb i represents the electronic warranty risk preparation gold balance of the ith sub-time zone, st i represents the electronic warranty payoff duration of the ith sub-time zone, and Δt represents the time difference between the ith sub-time zone and the ith-1 sub-time zone.
The business operation error data analysis unit is used for establishing a business operation error data analysis model, importing business operation error data transmitted by the business risk data acquisition module into the business operation error data analysis model, and calculating the electronic warranty operation error characteristic value of each sub-time region, wherein the specific mathematical model is as follows: LM i represents the electronic warranty operation error characteristic value of the ith sub-time area, md i represents the service interruption times caused by the failure of the electronic warranty system of the ith sub-time area, ml i represents the electronic warranty generation or decryption failure times of the ith sub-time area, mr i represents the electronic warranty service operation error number of the ith sub-time area, mt i represents the average response time of the electronic warranty service of the ith sub-time area, mt max represents the maximum response time of the electronic warranty service of the target time area, and Mt min represents the minimum response time of the electronic warranty service of the target time area.
The risk early warning data analysis unit is used for establishing a risk early warning data analysis model, importing risk early warning data transmitted by the business risk data acquisition module into the risk early warning data analysis model, and calculating an electronic protection risk early warning efficiency value of each sub-time region, wherein the specific mathematical model is as follows: LE i represents the electronic warranty risk early warning efficacy value of the ith sub-time region, ew i represents the number of risk early warning events of the ith sub-time region, et i represents the risk early warning processing time of the ith sub-time region, and Er i represents the risk early warning release rate of the ith sub-time region.
The business risk data analysis module calculates an electronic warranty risk optimization index of the ith sub-time zone according to the electronic warranty pay efficiency value of the ith sub-time zone, the electronic warranty operation error characteristic value of the ith sub-time zone and the electronic warranty risk early warning efficiency value of the ith sub-time zone, and the specific mathematical model is as follows: σ i represents the electronic warranty risk optimization index of the ith sub-time region, where [ mu ] represents other influencing factors of the electronic warranty risk optimization index.
The business comprehensive analysis module is used for establishing a business comprehensive analysis model, importing the data transmitted by the business operation data analysis module and the business risk data analysis module into the business comprehensive analysis model, calculating the comprehensive optimization index of the target electronic warranty business, and transmitting the comprehensive optimization index to the management module.
The service comprehensive analysis model specifically comprises the following steps: η represents a comprehensive optimization index of the target electronic policy service, OL i represents an electronic policy transaction efficiency value of the ith sub-time area, OU i represents a user behavior characteristic value of the ith sub-time area, us i represents the number of users of the ith sub-time area, OB i represents an electronic policy service benefit evaluation value of the ith sub-time area, σ i represents an electronic policy risk optimization index of the ith sub-time area, and λ represents other influencing factors of the comprehensive optimization index.
And the management module is used for managing the target electronic warranty business according to the comprehensive optimization index target value.
And when eta tar is larger than eta, the operation effect of the target electronic policy service is poor, and data transmitted by the service operation data acquisition module and the service risk data acquisition module are saved and abnormal signals are sent to management staff.
According to the invention, the management time of the target electronic policy service can be accurately divided by the management time division module to form a plurality of sub-time areas, so that enterprises can better grasp the time distribution of the service, and more targeted management and optimization are performed for different time periods; transaction data, user behavior data and service benefit data of each sub-time region can be comprehensively collected through the service operation data collection module, so that not only is service operation conditions reflected, but also the use habit and preference of a user are revealed, enterprises can know the service operation conditions in depth, potential problems and opportunities are found, and powerful support is provided for decision making; the collected business operation data is subjected to deep analysis through the business operation data analysis module, so that the enterprise can be helped to find out bottlenecks and advantages in operation, key factors influencing business benefits are identified, the enterprise is helped to formulate a more scientific and reasonable operation strategy, the business process is optimized, and the business benefits are improved; the business risk data acquisition module is used for acquiring data related to business risks, including factors possibly causing risks, probability of risk occurrence, loss possibly caused by risks and the like, and enterprises can timely know business risk conditions through the acquisition of the data, so that data support is provided for risk prevention and response; the business risk data is subjected to deep analysis through the business risk data analysis module, so that the intrinsic law and characteristics of risks can be revealed, the enterprises are helped to identify main risk sources and potential risk points, the enterprises are helped to formulate targeted risk precautionary measures, the business risks are reduced, and the steady development of the business is ensured; the business comprehensive analysis module is used for comprehensively analyzing business operation data and business risk data to form comprehensive evaluation on the overall business condition, so that enterprises can know the business condition from multiple angles, advantages and disadvantages in business are found, and powerful support is provided for formulating a more comprehensive and scientific business management strategy; the management module is used for realizing comprehensive monitoring and management of service operation, finding and solving problems in time and ensuring smooth service operation.
Secondly: in the drawings of the disclosed embodiments, only the structures related to the embodiments of the present disclosure are referred to, and other structures can refer to the common design, so that the same embodiment and different embodiments of the present disclosure can be combined with each other under the condition of no conflict;
finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (3)
1. An intelligent electronic policy service management system based on the internet, which is characterized by comprising:
Management time dividing module: the management time of the target electronic policy service is determined to be a target time area, and the target time area is divided into sub-time areas in an equal time division mode and is marked as 1 and 2 … … n in sequence;
Service operation data acquisition module: operating and collecting transaction data, user behavior data and service benefit data of each sub-time region, and transmitting the collected data to a service operation data analysis module;
And a business operation data analysis module: the system comprises a transaction data analysis unit, a user behavior data analysis unit and a service benefit data analysis unit, and transmits the analyzed data to a service comprehensive analysis module;
The transaction data analysis unit is used for establishing a transaction data analysis model, importing transaction data transmitted by the business operation data acquisition module into the transaction data analysis model, and calculating the electronic warranty transaction efficiency value of each sub-time region, wherein the specific digital model is as follows: OL i represents the electronic warranty transaction efficiency value of the ith sub-time area, LS i represents the electronic warranty issue quantity of the ith sub-time area, lt i represents the average electronic warranty issue duration of the ith sub-time area, lr i represents the electronic warranty online application duty ratio of the ith sub-time area, and Lm i represents the electronic warranty instant effective duty ratio of the ith sub-time area;
the user behavior data analysis unit is used for establishing a user behavior data analysis model, importing the user behavior data transmitted by the business operation data acquisition module into the user behavior data analysis model, and calculating the user behavior characteristic value of each sub-time region, wherein the specific digital model is as follows: OU i represents the user behavior characteristic value of the ith sub-time area, us i represents the number of users of the ith sub-time area, uf i represents the frequency of access to the electronic policy platform by the users of the ith sub-time area, uc i represents the number of times the users of the ith sub-time area consult the electronic policy service, and Ur i represents the renewal rate of the ith sub-time area;
The service benefit data analysis unit is used for establishing a service benefit data analysis model, importing service benefit data transmitted by the service operation data acquisition module into the service benefit data analysis model, and calculating an electronic protection service benefit evaluation value of each sub-time region, wherein the specific digital model is as follows: OB i represents an electronic policy service benefit evaluation value of the ith sub-time area, bd i represents an average saving guarantee amount of the ith sub-time area, bc i represents a cash flow improvement rate brought by the electronic policy service of the ith sub-time area, bs i represents an enterprise financing cost saved by the electronic policy service of the ith sub-time area, and Bu i represents an enterprise bidding success rate increased by the electronic policy service of the ith sub-time area;
The business risk data acquisition module: the system comprises a service risk data analysis module, a risk early warning module, a payment data acquisition module, a service operation error data acquisition module and a risk early warning module, wherein the service risk data acquisition module is used for acquiring the payment data, the service operation error data and the risk early warning data of each sub-time region;
business risk data analysis module: the system comprises a pay data analysis unit, a business operation error data analysis unit and a risk early warning data analysis unit, and transmits the analyzed data to a business comprehensive analysis module;
The claim data analysis unit is used for establishing a claim data analysis model, importing the claim data transmitted by the business risk data acquisition module into the claim data analysis model, and calculating the electronic protection function claim efficiency value of each sub-time region, wherein the specific mathematical model is as follows: LS i represents the electronic warranty payoff efficiency value of the ith sub-time zone, sr i represents the electronic warranty payoff rate of the ith sub-time zone, su i represents the number of electronic warranty default cases of the ith sub-time zone, sb i represents the electronic warranty risk preparation gold balance of the ith sub-time zone, st i represents the electronic warranty payoff duration of the ith sub-time zone, and Deltat represents the time difference between the ith sub-time zone and the ith-1 sub-time zone;
the business operation error data analysis unit is used for establishing a business operation error data analysis model, importing business operation error data transmitted by the business risk data acquisition module into the business operation error data analysis model, and calculating the electronic warranty operation error characteristic value of each sub-time region, wherein the specific mathematical model is as follows: LM i represents the electronic warranty operation error characteristic value of the ith sub-time area, md i represents the service interruption times caused by the failure of the electronic warranty system of the ith sub-time area, ml i represents the electronic warranty generation or decryption failure times of the ith sub-time area, mr i represents the electronic warranty service operation error number of the ith sub-time area, mt i represents the average response time of the electronic warranty service of the ith sub-time area, mt max represents the maximum response time of the electronic warranty service of the target time area, and Mt min represents the minimum response time of the electronic warranty service of the target time area;
And a business comprehensive analysis module: the system comprises a business operation data analysis module, a business risk data analysis module, a business comprehensive analysis module, a management module and a management module, wherein the business operation data analysis module is used for establishing a business comprehensive analysis model, importing data transmitted by the business operation data analysis module and the business risk data analysis module into the business comprehensive analysis model, calculating a comprehensive optimization index of a target electronic warranty business, and transmitting the comprehensive optimization index to the management module;
The business risk data analysis module calculates an electronic warranty risk optimization index of the ith sub-time zone according to the electronic warranty pay efficiency value of the ith sub-time zone, the electronic warranty operation error characteristic value of the ith sub-time zone and the electronic warranty risk early warning efficiency value of the ith sub-time zone, and the specific mathematical model is as follows: σ i represents the electronic warranty risk optimization index of the ith sub-time region, wherein [ mu ] represents other influencing factors of the electronic warranty risk optimization index;
and a management module: and the system is used for managing the target electronic warranty business according to the comprehensive optimization index target value.
2. The internet-based intelligent electronic policy service management system according to claim 1, wherein: the transaction data comprises an electronic policy issuing amount, an electronic policy average issuing duration, an electronic policy online application duty ratio and an electronic policy instant effective duty ratio, which are respectively marked as Ls, lt, lr and Lm, the user behavior data comprises the number of users, the frequency of users accessing an electronic policy platform, the number of times users consult electronic policy services and the renewal rate, which are respectively marked as Us, uf, uc and Ur, the service benefit data comprises an average saving and guarantee amount, a cash flow improvement rate brought by an electronic policy service, an enterprise financing cost saved by the electronic policy service and an enterprise bidding success rate increased by the electronic policy service, which are respectively marked as Bd, bc, bs and Bu.
3. The internet-based intelligent electronic policy service management system according to claim 1, wherein: the payable data comprises electronic insurance payable rate, electronic insurance default case number, electronic insurance risk preparation gold balance and electronic insurance payable duration, which are respectively marked as Sr, su, sb and St, the business operation error data comprises business interruption times, electronic insurance generation or decryption failure times, electronic insurance business operation error numbers and electronic insurance service average response time caused by electronic insurance system faults, which are respectively marked as Md, ml, mr and Mt, and the risk early warning data comprises risk early warning event number, risk early warning processing time and risk early warning release rate, which are respectively marked as Ew, et and Er.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410589363.7A CN118154333B (en) | 2024-05-13 | 2024-05-13 | Intelligent electronic policy service management system based on Internet |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410589363.7A CN118154333B (en) | 2024-05-13 | 2024-05-13 | Intelligent electronic policy service management system based on Internet |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN118154333A CN118154333A (en) | 2024-06-07 |
| CN118154333B true CN118154333B (en) | 2024-07-12 |
Family
ID=91299462
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410589363.7A Active CN118154333B (en) | 2024-05-13 | 2024-05-13 | Intelligent electronic policy service management system based on Internet |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN118154333B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118552327A (en) * | 2024-07-29 | 2024-08-27 | 深圳市熙盛恒科技有限公司 | A data analysis method, system and storage medium for automobile insurance business |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113159568A (en) * | 2021-04-19 | 2021-07-23 | 福建万川信息科技股份有限公司 | System and method for estimating insurance risk |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102903056A (en) * | 2011-07-27 | 2013-01-30 | 刘金衢 | Method and system for debit and credit guarantee based on e-commerce platform |
| CN109903175A (en) * | 2019-03-26 | 2019-06-18 | 众安在线财产保险股份有限公司 | A kind of Insurance core system monitor supervision platform |
| CN113034267A (en) * | 2021-03-26 | 2021-06-25 | 广东中盈盛达数字科技有限公司 | Electronic letter protection system based on supply chain |
| CN114155093B (en) * | 2022-02-08 | 2022-04-19 | 一方函互联网有限公司 | Block chain-based electronic insurance full-flow management and risk management and control system |
| CN115630375A (en) * | 2022-09-08 | 2023-01-20 | 工保保函(北京)科技有限公司 | Electronic insurance risk management and control method, system and electronic equipment |
| CN115760437A (en) * | 2022-09-27 | 2023-03-07 | 深圳先进技术研究院 | Insurance applicant recommendation method based on safety management measures and insurance letters |
| CN115841370A (en) * | 2022-11-04 | 2023-03-24 | 辽宁省网联数字科技产业有限公司 | Electronic bidding insurance letter full-flow public service system |
| CN117172937B (en) * | 2023-09-11 | 2024-04-19 | 深圳市融锋科技有限公司 | Intelligent electronic policy service management system based on Internet |
| CN117252673B (en) * | 2023-09-19 | 2024-08-30 | 深圳市腾晴科技有限公司 | Electronic warranty management system based on multiparty security calculation |
-
2024
- 2024-05-13 CN CN202410589363.7A patent/CN118154333B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113159568A (en) * | 2021-04-19 | 2021-07-23 | 福建万川信息科技股份有限公司 | System and method for estimating insurance risk |
Also Published As
| Publication number | Publication date |
|---|---|
| CN118154333A (en) | 2024-06-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zhang et al. | Sok: blockchain decentralization | |
| Jackson et al. | Auditors and earnings management | |
| KR102032924B1 (en) | Security System for Cloud Computing Service | |
| JP6978551B2 (en) | Patent evaluation system | |
| CN118154333B (en) | Intelligent electronic policy service management system based on Internet | |
| Hacioglu et al. | Crafting performance-based cryptocurrency mining strategies using a hybrid analytics approach | |
| CN113434575B (en) | Data attribution processing method, device and storage medium based on data warehouse | |
| KR20180060005A (en) | Security System for Cloud Computing Service | |
| CN117195292B (en) | Power business evaluation method based on data fusion and edge calculation | |
| TW202230233A (en) | Method, computing device and system for profit sharing | |
| CN113256324A (en) | Data asset pricing method, device, computer equipment and storage medium | |
| Ma et al. | Early warning for internet finance industry risk: an empirical investigation of the P2P companies in the coastal regions of China | |
| CN113298637B (en) | User diversion method, device and system of service platform | |
| CN114066624A (en) | Method and System for Mining Blacklist Association Graph Based on Graph Computing | |
| CN113220447A (en) | Financial wind control system and method based on edge calculation | |
| CN116739722A (en) | Financing lease quotation method and system based on risk assessment | |
| CN113592499B (en) | Internet money laundering countermeasure method and device | |
| Bagourd et al. | Quantifying MEV On Layer 2 Networks | |
| CN117252678A (en) | Agricultural loan request processing method, device, equipment and readable storage medium | |
| CN114880369B (en) | Risk credit granting method and system based on weak data technology | |
| TWI792101B (en) | Data Quantification Method Based on Confirmed Value and Predicted Value | |
| CN115630375A (en) | Electronic insurance risk management and control method, system and electronic equipment | |
| CN115760363A (en) | Interest rate measuring and calculating method and device based on pedestrian credit report | |
| KR101078868B1 (en) | Method and system for providing service of financial consulting | |
| CN112669087A (en) | Financial transaction strategy paid sharing method based on block chain |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |