Disclosure of Invention
The embodiment of the application aims to provide a transaction risk monitoring method, device, electronic equipment, storage medium and program product for a pay-through claim service, which are used for reducing the influence of manual intervention and subjective judgment, monitoring individual and clustered risks in time and improving the reliability and efficiency of pay-through claim service risk monitoring.
The application provides a transaction risk monitoring method of a pay-through claim service, which comprises the steps of obtaining target service data, calculating at least one risk field corresponding to a risk identification main body according to the target service data, judging whether the risk identification main body hits a preset wind control rule corresponding to the risk field according to each risk field to obtain a corresponding hit judgment result, and calculating whether the risk identification main body hits a wind control strategy according to the hit judgment result, wherein the wind control strategy comprises at least one preset wind control rule.
In the scheme, the potential risk of the risk identification main body can be comprehensively identified by comprehensively analyzing the target business data including the attribute data, the transaction consumption data, the action track data and the operation behavior data of the risk identification main body, and the automatic risk field calculation and the preset wind control rule matching can accurately judge whether the risk identification main body triggers the wind control strategy, so that the effective risk monitoring is realized, the influence of manual intervention and subjective judgment is reduced, and the reliability and the efficiency of the direct payment settlement business risk monitoring are improved.
As an alternative, the risk field further includes an intrinsic attribute corresponding to the risk identification body. In the scheme, the risk indexes of the risk identification main body can be combined or not combined with the inherent attribute of the risk identification main body to carry out hit judgment of the preset wind control rule, so that the situations of misjudgment and missed judgment are reduced, and the robust development of the service is supported.
As an optional mode, the wind control strategy further comprises a weight corresponding to each preset wind control rule, and the calculation of whether the risk identification main body hits the wind control strategy according to the hit judgment result comprises the steps of calculating products between the preset wind control rules of each hit and the weights corresponding to the preset wind control rules, calculating a sum of a plurality of products, and determining whether the risk identification main body hits the wind control strategy according to the sum. In the scheme, the contribution degree of each preset wind control rule in the whole wind control strategy is estimated by introducing a weight mechanism, so that risk estimation is not simply matching the preset wind control rules, but is weighted according to the importance of each rule, thereby optimizing the wind control strategy and improving the accuracy of risk estimation.
As an optional mode, after the calculation of whether the risk identification subject hits the wind control strategy according to the hit judgment result, basic information of the risk identification subject, a risk subject index, a risk analysis result of the risk identification subject and a risk detail of the risk analysis result are output, wherein the risk subject index is a visual index for an administrator generated according to the risk field.
In the scheme, by providing the basic information of the risk identification subject, the risk subject index, the risk analysis result and the risk detail, a user and a decision maker can more clearly understand the basis and the result of risk assessment, and the data is used for supporting business decision and risk management.
As an alternative way, before the target service data is obtained, the method further comprises the step of cleaning the bottom data from different sources to obtain the target service data. In the scheme, the data can be cleaned, so that errors or inconsistencies in the data set can be identified and corrected, the data quality is improved, the operation risk caused by the errors or inconsistencies of the data is reduced, and the overall business process efficiency is improved.
As an alternative way, the calculating at least one risk field corresponding to the risk identification subject according to the target service data includes calculating at least one risk field corresponding to the risk identification subject within a time node. In the scheme, the risk field is calculated in the specific time node, so that the risk assessment can be connected with the historical service condition, the timeliness and the relativity of the risk assessment are improved, and the dynamic monitoring capability of the risk is enhanced.
The application provides a transaction risk monitoring device of a pay-through claim service, which comprises an acquisition module, a risk field calculation module and a judgment module, wherein the acquisition module is used for acquiring target service data, the target service data comprises attribute data, transaction consumption data, action track data and operation behavior data of a risk identification main body, the risk field calculation module is used for calculating at least one risk field corresponding to the risk identification main body according to the target service data, the risk field comprises a risk index corresponding to the risk identification main body, the judgment module is used for judging whether the risk identification main body hits a preset wind control rule corresponding to the risk field according to each risk field to obtain a corresponding hit judgment result, and the wind control strategy calculation module is used for calculating whether the risk identification main body hits a wind control strategy according to the hit judgment result, wherein the wind control strategy comprises at least one preset wind control rule.
In the scheme, the potential risk of the risk identification main body can be comprehensively identified by comprehensively analyzing the target business data including the attribute data, the transaction consumption data, the action track data and the operation behavior data of the risk identification main body, and the automatic risk field calculation and the preset wind control rule matching can accurately judge whether the risk identification main body triggers the wind control strategy, so that the effective risk monitoring is realized, the influence of manual intervention and subjective judgment is reduced, and the reliability and the efficiency of the direct payment settlement business risk monitoring are improved.
The wind control strategy further comprises a weight corresponding to each preset wind control rule, and the wind control strategy calculation module is used for calculating products of the preset wind control rules of each hit and the weights corresponding to the preset wind control rules and calculating a sum of a plurality of products, and determining whether the risk identification main body hits the wind control strategy according to the sum.
The device further comprises an output module, wherein the output module is used for outputting basic information of the risk identification subject, risk subject indexes, risk analysis results of the risk identification subject and risk details of the risk analysis results, and the risk subject indexes are visual indexes which are generated according to the risk fields and used by an administrator.
As an optional mode, the device further comprises a data cleaning module, which is used for cleaning the bottom data of different sources to obtain target business data.
As an optional manner, the risk field calculation module is specifically configured to calculate at least one risk field corresponding to the risk identification body within a time node.
In a third aspect, the present application provides an electronic device comprising a processor, a memory and a bus, wherein the processor and the memory communicate with each other via the bus, the memory storing machine-readable instructions executable by the processor, which when executed by the processor, perform the method steps of the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the method steps as in the first aspect.
In a fifth aspect, the present application provides a computer program product comprising a computer program which, when run by a processor, performs the method steps of the first aspect.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the embodiments of the application.
Detailed Description
Embodiments of the technical scheme of the present application will be described in detail below with reference to the accompanying drawings. The following examples are only for more clearly illustrating the technical aspects of the present application, and thus are merely examples, and are not intended to limit the scope of the present application.
It should be noted that all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs, that the terms used herein are for the purpose of describing particular embodiments only and are not intended to limit the application, and that the terms "comprising" and "having" and any variations thereof in the description of the application and the claims and the above description of the drawings are intended to cover non-exclusive inclusions.
It can be appreciated that the transaction risk monitoring method for pay-through-payment claim service provided by the embodiment of the application can be applied to terminal equipment (also referred to as electronic equipment) or a server, wherein the terminal equipment can be a smart phone, a tablet computer, a Personal digital assistant (Personal DIGITAL ASSISTANT, PDA) or the like, and the server can be an application server or a Web server.
In order to facilitate understanding, the technical solution provided by the embodiments of the present application is described below by taking a server as an execution body as an example, and an application scenario of the transaction risk monitoring method for pay-through claims service provided by the embodiments of the present application is described.
Referring to fig. 1, fig. 1 is a flow chart of a transaction risk monitoring method for pay-through claim service according to an embodiment of the present application. The method comprises the following steps:
And S10, acquiring target business data, wherein the target business data comprises attribute data, transaction consumption data, action track data and operation behavior data of a risk identification main body.
The targeted business data is used to assess and monitor transaction risk, and by analyzing such data, the system can identify possible risk behaviors such as theft, illegal cashing, etc. The target business data includes attribute data, transaction consumption data, action trace data, and operational behavior data of the risk identification subject.
Risk identification subjects refer to individuals or entities that may be involved in a pay-through-payment claim service. For example, risk identification principals in transactions of pay-through-payment claims service may include customer side, insurance side, and consumption institution side, among others. It should be noted that, the user side refers to an individual who can conduct a pay-through claim business transaction, the policy side refers to a group associated with the same policy, and the consumption mechanism side refers to a trade shop for providing goods or services.
Taking a supplementary medical fund recharging service as an example, the supplementary medical fund can be recharged into a pay-through claim card of a corresponding user, and the user can consume the supplementary medical fund by swiping the card, wherein in the pay-through claim service, a consumption mechanism side is a trade shop for providing medical services or medicines, a user side is a person consuming by using the pay-through claim card at the consumption mechanism side, and a guarantee side is a group associated with the guarantee.
The attribute data of the risk identification subject may include user information, account information, card information, policy-side information, consumption institution-side information, and the like. The transaction consumption data of the risk identification principal may include transaction log data, item detail data, consumption type data, refund data of the cash payment module, online purchase related data, and the like. The operational behavior data of the risk identification agent may include card operational data, application (APP) operational data, hardware device data for use in transactions, and the like.
As one implementation, the targeted business data may be from individual insurers.
And step S20, calculating at least one risk field corresponding to the risk identification main body according to the target service data, wherein the risk field comprises a risk index corresponding to the risk identification main body.
The risk index refers to a series of quantitative indexes for evaluating risks that risk identification subjects may face in pay-through claims service, and is obtained by pre-calculating target service data of each risk identification subject. For example, the risk field may be a transaction amount, a number of transactions, a longest number of consecutive transactions, a number of abnormal time transactions, a number of off-site transactions, etc., and the transactions may also be classified, with different grades of transactions being set according to the transaction amount. Data integration is then performed, such as maximum number of consecutive transaction days, number of times, maximum consecutive transaction amount, etc. The calculation of the above risk fields may be implemented by logical execution of SQL statements.
Step S30, judging whether the risk identification main body hits a preset wind control rule corresponding to the risk field according to the risk field aiming at each risk field, and obtaining a corresponding hit judgment result.
The preset wind control rules are a series of predefined criteria or conditions used in the risk monitoring process to identify, evaluate and address potential risks. It should be noted that, the specific implementation manner of determining the preset wind control rule is not specifically limited in the embodiment of the present application, and those skilled in the art may perform appropriate adjustment according to actual situations. For example, the preset wind control rules may be determined based on statistical analysis of historical data and training of machine learning algorithms, or may be formulated based on experience and business logic of those skilled in the art, or may be dynamically adjusted according to new data and market changes, etc. For example, one preset wind control rule formulated based on attribute data of the risk identification subject may be to determine whether the card holding user is older than 90 years old.
In addition, the number of the preset wind control rules corresponding to each risk field is not particularly limited in the embodiment of the present application, and a person skilled in the art can also perform appropriate adjustment according to actual situations. For example, the risk field may correspond to one preset wind control rule, or the risk field may correspond to two preset wind control rules, or the like.
There are two kinds of outputs of the hit determination result, i.e., hit or miss, alternatively, hit may be represented by output 1 and miss may be represented by output 0.
The risk identification main body hits a certain preset wind control rule, which indicates that the risk identification main body meets the certain preset wind control rule, and correspondingly, the risk identification main body does not hit the certain preset wind control rule, which indicates that the risk identification main body does not meet the certain preset wind control rule. For example, when the preset wind control rule determines whether the user age of the card holding user is greater than 90 years old, the user age greater than 90 years old indicates that the risk identification subject hits the preset wind control rule.
And S40, calculating whether the risk identification main body hits the wind control strategy according to the hit judgment result, wherein the wind control strategy comprises at least one preset wind control rule.
The wind control strategy is a set of at least one preset wind control rule in the risk monitoring process and is used for capturing risks so as to protect the fund safety of enterprises and users and ensure the compliance and stability of the business. In the risk monitoring process, only hitting a single preset wind control rule cannot indicate that the user really has risks, and the preset wind control rules can offset each other. Therefore, the risk type is preset according to the actual scene and the service requirement by the wind control strategy, and the risks of different situations are captured by configuring different wind control strategies.
As one implementation, the configuration of the air control strategy may be static, and the air control strategy may not be changed after the air control strategy is determined in advance. As another implementation, the configuration of the air control strategy may also be dynamic, constantly optimized and adjusted according to new data, machine learning algorithms, market conditions, and business needs.
Taking the ex-situ transaction service as an example, the risk field may include transaction location, transaction amount, transaction store, and card attribute, so that the ex-situ transaction policy may select related preset policy rules related to the transaction location, transaction amount, transaction store, and card attribute to form a rule set. The wind control strategy can comprise related preset wind control rules related to transaction places and transaction amounts in a period of time, and the wind control strategy can be updated to comprise related preset wind control rules related to transaction places, transaction amounts and card attributes in a next period of time.
Taking a risk identification subject as an example, the wind control strategy comprises two preset wind control rules, wherein the first is that whether the user is older than 55 years old or not, and the second is that whether the user has continuously transacted three times or more in the last week or not. If the user hits the first preset wind control rule but does not hit the second preset wind control rule, as a first embodiment, when all the preset wind control rules in the wind control policy are hit, the user is considered to hit the wind control policy, and the user is not hit the wind control policy, and is judged to be a low risk user, as a second embodiment, the first preset wind control rule is set with a weight coefficient of 0.3, the second preset wind control rule is set with a weight coefficient of 0.7, and when the calculated wind control policy output value is greater than or equal to 0.5, the wind control policy is considered to be hit, and the wind control policy output value is 1×0.3+0×0.7=0.3 <0.5, and therefore the user is not hit the wind control policy, and is judged to be a low risk user.
In the scheme, the potential risk of the risk identification main body can be comprehensively identified by comprehensively analyzing the target business data including the attribute data, the transaction consumption data and the operation behavior data of the risk identification main body, and the automatic risk field calculation and the preset wind control rule matching can accurately judge whether the risk identification main body triggers the wind control strategy, so that the effective risk monitoring is realized, the influence of manual intervention and subjective judgment is reduced, the individual and cluster risks are monitored in time, and the reliability and the efficiency of the risk monitoring of the pay-through claim business are improved.
In some embodiments, the risk field may also include an inherent attribute corresponding to the risk identification subject.
The inherent properties of a risk identification principal refer to the fundamental features that are directly related to the risk identification principal and generally do not change over time or behavior. For example, the inherent attribute of the risk identification body may include the user sex, the attribution, the mobile phone number, the policy type, whether one person has multiple cards, whether real names, the attribution policy, etc. of the card, the inherent attribute of the risk identification body may include the insurance company, the claim settlement limit claim settlement proportion, the face recognition rate, etc. of the policy identification body, and the inherent attribute of the risk identification body may include the class of store, the consumption limit, the attribution, etc. of the store.
When judging whether the risk identification main body hits the preset wind control rule, the risk identification main body can only judge the risk index in the risk field, and can also judge whether the risk identification main body hits the preset wind control rule according to the risk index and the inherent attribute.
Taking the risk identification main body as the user side as an example, the risk index of the card held by the user side is transaction amount, one inherent attribute of the card is the attribution of the cardholder, and the preset wind control rule corresponding to the risk field combining the risk index and the inherent attribute can be whether the user side has transaction behavior with the transaction amount greater than 1000 yuan in Sichuan province.
In the scheme, the risk indexes of the risk identification main body can be combined or not combined with the inherent attribute of the risk identification main body to carry out hit judgment of the preset wind control rule, so that the situations of misjudgment and missed judgment are reduced, and the robust development of the service is supported.
In some embodiments, the wind control strategy further comprises a weight corresponding to each preset wind control rule, and step S40 comprises calculating the product of each hit preset wind control rule and the corresponding weight, calculating the sum of the products, and determining whether the risk identification main body hits the wind control strategy according to the sum.
In this embodiment, weights are assigned to each preset wind control rule to help identify which preset wind control rules are more critical, and the weight ratio of the more critical preset wind control rules is set higher, otherwise, the weight ratio of the more critical preset wind control rules is lower, so that unnecessary wind control intervention can be reduced, and the false alarm rate is reduced. For example, if a preset wind control rule, while triggered, is weighted lower, it may not immediately result in the risk identification principal being determined to be high risk, thereby reducing unnecessary interference to low risk users.
In the scheme, the contribution degree of each preset wind control rule in the whole wind control strategy is estimated by introducing a weight mechanism, so that risk estimation is not simply matching the preset wind control rules, but is weighted according to the importance of each rule, thereby optimizing the wind control strategy and improving the accuracy of risk estimation.
In some embodiments, after step S40, the transaction risk monitoring method for a pay-through-payment claim service provided in the embodiment of the present application further includes:
And outputting basic information of the risk identification subject, risk subject indexes, risk analysis results of the risk identification subject and risk details of the risk analysis results, wherein the risk subject indexes are visual indexes which are generated according to the risk fields and used by an administrator.
The embodiment of the present application does not specifically limit the specific implementation manner of outputting each data in the above steps, and those skilled in the art may perform appropriate adjustment according to actual situations. For example, each data may be output by means of text, pictures, tables, or the like, or each data may be output by means of voice.
When basic information of the risk identification main body is output, all conditions corresponding to the current risk identification main body can be displayed, for example, when the risk identification main body is a card, user conditions, famous cards, association user relations and the like are displayed, for example, when the risk identification main body is a security terminal or a consumption mechanism terminal, corresponding main body information is also displayed.
When the risk subject indexes are output, different risk subject index modules can be configured for display according to different risk identification subjects, and the risk subject indexes are visual displays which are made after the risk fields are read and are easy to be understood by an administrator.
When the risk analysis result of the risk identification main body is output, the risk points of the risk identification main body can be further revealed, and classified display is performed according to different main bodies. Such as card bodies, show daily trends, consumer type conditions, store conditions, location and distribution of consumption, abnormal timelines, etc. The display at the consumer and warranty ends is relatively more complex.
When the risk detail of the risk analysis result is output, the corresponding risk detail condition is provided more deeply and more specifically on the basis of the risk analysis result, so that the business processing and the docking are convenient, for example, in the output of the risk analysis result, a card consumption path can be seen, a user consumes in certain two provinces, but only the consumption provinces and the amount of money are output, and in the output of the risk detail, what the urban area of a store is consumed in certain day, the specific consumption time, the consumed amount of money and the consumed articles can be also checked. The risk details may include risk transaction items of the risk identification subject, risk lists involved in the policy, risk consuming users at the location of the consumption institution, abnormal transaction items, and so forth.
In the scheme, by providing the basic information of the risk identification subject, the risk subject index, the risk analysis result and the risk detail, a user and a decision maker can more clearly understand the basis and the result of risk assessment, and the data is used for supporting business decision and risk management.
In some embodiments, before the target service data is acquired, the method further comprises cleaning the underlying data from different sources to obtain the target service data.
The underlying data from different insurance companies may be provided in different manners, for example, by an applet, or by a data sharing platform, or by a cloud service, etc.
Data cleansing can correct or remove problems with errors, duplicates, anomalies, or missing values in the data. And the data quality and accuracy are improved. And the data can be standardized and normalized in the data cleaning process, and the data can be converted into a uniform format.
In the scheme, the data can be cleaned, so that errors or inconsistencies in the data set can be identified and corrected, the data quality is improved, the operation risk caused by the errors or inconsistencies of the data is reduced, and the overall business process efficiency is improved.
In some embodiments, step S20 includes calculating at least one risk field corresponding to the risk identification principal within the time node.
The risk field includes a time attribute. For example, with day, week, month, year as time nodes, the risk field is calculated within the time nodes, specifically the risk field may be the longest consecutive transaction days within a month, etc.
In the scheme, the risk field is calculated in the specific time node, so that the risk assessment can be connected with the historical service condition, the timeliness and the relativity of the risk assessment are improved, and the dynamic monitoring capability of the risk is enhanced.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a transaction risk monitoring device for pay-through-payment claim service according to an embodiment of the present application, including:
The acquiring module 100 is configured to acquire target business data, where the target business data includes attribute data, transaction consumption data, action track data, and operation behavior data of the risk identification subject.
And a risk field calculation module 200, configured to calculate, according to the target service data, at least one risk field corresponding to the risk identification subject, where the risk field includes a risk indicator corresponding to the risk identification subject.
The judging module 300 is configured to judge, according to each risk field, whether the risk identification body hits a preset wind control rule corresponding to the risk field, so as to obtain a corresponding hit judgment result.
And the wind control strategy calculation module 400 is configured to calculate, according to the hit determination result, whether the risk identification subject hits the wind control strategy, where the wind control strategy includes at least one preset wind control rule.
It should be understood that, corresponding to the transaction risk monitoring method embodiment of the pay-through-payment claim service, the apparatus can perform the steps related to the method embodiment, and specific functions of the apparatus may be referred to the above description, and detailed descriptions are omitted herein as appropriate to avoid repetition. The device includes at least one software functional module that can be stored in memory in the form of software or firmware (firmware) or cured in an Operating System (OS) of the device.
The wind control strategy further comprises a weight corresponding to each preset wind control rule, and the wind control strategy calculation module is used for calculating products of the preset wind control rules of each hit and the weights corresponding to the preset wind control rules and calculating a sum of a plurality of products, and determining whether the risk identification main body hits the wind control strategy according to the sum.
In some embodiments, the device further comprises an output module, wherein the output module is used for outputting the basic information of the risk identification subject, the risk subject index, the risk analysis result of the risk identification subject and the risk detail of the risk analysis result, and the risk subject index is a visual index for an administrator generated according to the risk field.
In some embodiments, the device further comprises a data cleaning module for cleaning the bottom data from different sources to obtain the target business data.
In some embodiments, the risk field calculation module is specifically configured to calculate at least one risk field corresponding to the risk identification body within a time node.
Referring to fig. 3, fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application, where the electronic device includes a processor 301, a processor 302, and a bus 303, where the processor 301 and the memory 302 complete communication with each other through the bus 303, and the processor 302 stores machine-readable instructions executable by the processor 301, where the machine-readable instructions execute the methods provided in the foregoing method embodiments when executed by the processor 301.
The processor 301 includes one or more (only one shown) which may be an integrated circuit chip having signal processing capabilities. The Processor 301 may be a general-purpose Processor including a central processing unit (Central Processing Unit, CPU), a micro control unit (Micro Controller Unit, MCU), a network Processor (Network Processor, NP) or other conventional Processor, or may be a special-purpose Processor including a neural network Processor (Neural-network Processing Unit, NPU), a graphics Processor (Graphics Processing Unit, GPU), a digital signal Processor (DIGITAL SIGNAL Processor, DSP), an Application SPECIFIC INTEGRATED Circuits (ASIC), a field programmable gate array (Field Programmable GATE ARRAY, FPGA) or other programmable logic device, discrete gate or transistor logic device, or discrete hardware components. Also, when the processor 301 is plural, some of them may be general-purpose processors, and another may be special-purpose processors.
The processor 302 includes one or more (Only one shown in the figure) which may be, but is not limited to, a random access processor (Random Access Memory, RAM for short), a Read Only Memory (ROM for short), a programmable Read Only Memory (Programmable Read-Only Memory for short, PROM) an erasable programmable Read Only Memory (Erasable Programmable Read-Only Memory for short, EPROM for short), an electrically erasable programmable Read Only Memory (Electric Erasable Programmable Read-Only Memory for short, EEPROM for short), and the like. Processor 301 and other possible components may access, read, and/or write data to processor 302.
In particular, one or more computer program instructions may be stored in the processor 302, which may be read and executed by the processor 301 to implement the weak password scan behavior recognition method provided by the embodiments of the present application.
Bus 303 includes one or more (only one shown) that may be used to communicate directly or indirectly with other devices for data interaction. The bus 303 may include devices for wired and wireless communication, such as an optical fiber, a serial peripheral interface (SERIAL PERIPHERAL INTERFACE, abbreviated as SPI) module, an integrated circuit bus (Inter-INTEGRATED CIRCUIT, abbreviated as I2C), etc., and may include devices for wireless communication, such as a bluetooth module, a Wi-Fi module, a mobile communication module (e.g., 4G, 5G module), etc.
It will be appreciated that the configuration shown in fig. 3 is merely illustrative, and that the electronic device may also include more or fewer components than shown in fig. 3, or have a different configuration than shown in fig. 3. The components shown in fig. 3 may be implemented in hardware, software, or a combination thereof. The electronic device may be a physical device, such as a switch, router, server, PC, etc., or a virtual device, such as a virtual machine, virtualized container, etc. The electronic device is not limited to a single device, and may be a combination of a plurality of devices or an integrated environment formed by a large number of devices.
The present application provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the methods provided by the above-described method embodiments.
The present application provides a computer program product comprising a computer program which, when run by a processor, performs the methods provided by the method embodiments described above.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
Further, the units described as separate units may or may not be physically separate, and units displayed as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
Furthermore, functional modules in various embodiments of the present application may be integrated together to form a single portion, or each module may exist alone, or two or more modules may be integrated to form a single portion.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and variations will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.