CN113159915A - Intelligent financial credit dynamic evaluation method and system based on big data - Google Patents
Intelligent financial credit dynamic evaluation method and system based on big data Download PDFInfo
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Abstract
The embodiment of the application provides an intelligent financial credit dynamic evaluation method and system based on big data, and the problems of low accuracy and low evaluation efficiency of credit evaluation results can be solved. The method comprises the following steps: receiving an interaction request of a user to a target user terminal device, and acquiring target indication information generated based on the user interaction request, wherein the target indication information comprises running information of a target type interaction application; and obtaining a target indication financial credit score according to the type and the corresponding quantity of the running information of the target type interactive application, and performing dynamic assessment on the financial credit according to the target indication financial credit score.
Description
Technical Field
The application relates to the technical field of data processing, in particular to an intelligent financial credit dynamic evaluation method and system based on big data.
Background
Currently, credit market ratings are mainly classified into internal ratings and external ratings, the internal ratings are credit evaluation systems initiated inside banks and set up for preventing loan risks, and main influence indexes include past financial data of enterprises, the operational capacity of clients, the development prospects of the enterprises, industry prospects, internal operation management, the repayment capacity, the profitability, the performance conditions and the like of the clients. External credit ratings are independent of third party rating agencies outside of bank ratings, which achieve high confidence according to uniform standards, procedures and methods. However, the existing credit evaluation method is mainly based on the reported data of the evaluated object to evaluate, so that the data is hard to distinguish, the data samples are good and bad, it is difficult to obtain a more accurate evaluation result, and the evaluation efficiency is low.
Disclosure of Invention
The embodiment of the application provides an intelligent financial credit dynamic evaluation method and system based on big data, and the problems of low accuracy and low evaluation efficiency of credit evaluation results can be solved.
A first aspect of an embodiment of the present application provides an intelligent financial credit dynamic assessment method based on big data, which is used for a user terminal device, and includes:
receiving an interaction request of a user to a target user terminal device,
acquiring target indication information generated based on the user interaction request, wherein the target indication information comprises running information of a target type interaction application;
and obtaining a target indication financial credit score according to the type and the corresponding quantity of the running information of the target type interactive application, and performing dynamic assessment on the financial credit according to the target indication financial credit score.
Optionally, the target type interactive application is a post application interactive application, and the operation information of the target type interactive application includes access action information, operation duration, forwarding action information, and downloading action information.
Optionally, the number of the target user terminal devices is multiple, and the operation information of the target type interactive application further includes an operation concentration of the target type interactive application, where the operation concentration is the number of the target user terminal devices generating the target indication information in the multiple target user terminal devices within a preset range around the same time;
and calculating the first user concentration ratio of the plurality of target user terminal devices in a preset range before and after the same moment.
Optionally, the obtaining a target indication financial credit score according to the type and the corresponding quantity of the running information of the target type interactive application specifically includes:
counting the running information of the target type interactive application, and analyzing through SPSS software to obtain the weight of each running information;
and calculating to obtain a financial credit score of the target indication according to the weight and the corresponding quantity of each item of running information in the running information of the target type interactive application included in the target indication information.
Optionally, acquiring target indication sample information of a target field in the whole network or a field to which the user belongs through a web crawler process;
and training the neural network through the target indication sample information, and predicting a second user concentration ratio within a preset range before and after the same moment based on the trained neural network model.
Optionally, the first user concentration ratio and the second user concentration ratio are compared to obtain a comparison result.
The step of obtaining a target indication financial credit score according to the type and the corresponding quantity of the running information of the target type interactive application and performing dynamic assessment on the financial credit according to the target indication financial credit score comprises the following steps:
and performing dynamic assessment of financial credit according to the comparison result and the target indication financial credit score.
Optionally, the terminal devices serving as a calculation basis in the first user concentration ratio and the second user concentration ratio are counted into the number of the terminal devices only when the running information of the target type interactive application reaches the preset activity.
A second aspect of the embodiments of the present application provides a big data intelligent financial credit dynamic evaluation system, including:
the receiving unit is used for receiving an interaction request of a user to the target user terminal equipment;
the acquisition unit is used for acquiring target indication information generated based on the user interaction request, and the target indication information comprises running information of a target type interaction application;
and the evaluation unit is used for obtaining a target indication financial credit score according to the type and the corresponding quantity of the running information of the target type interactive application and carrying out dynamic evaluation on the financial credit according to the target indication financial credit score.
A third aspect of the embodiments of the present application provides an electronic device, which includes a memory and a processor, where the processor is configured to implement the steps of the above-mentioned intelligent dynamic financial credit assessment method based on big data when executing a computer program stored in the memory.
A fourth aspect of the present embodiment provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the above-mentioned intelligent dynamic assessment method for financial credit based on big data.
In summary, the intelligent financial credit dynamic evaluation method based on big data provided by the embodiment of the present application is used for a user terminal device, and includes: receiving an interaction request of a user to a target user terminal device, and acquiring target indication information generated based on the user interaction request, wherein the target indication information comprises running information of a target type interaction application; and obtaining a target indication financial credit score according to the type and the corresponding quantity of the running information of the target type interactive application, and performing dynamic assessment on the financial credit according to the target indication financial credit score. By recording the interaction request and the operation information which are related to the target indication information of the terminal equipment of the staff in the operation subject to be evaluated, for example, the operation information can be the operation information in job application, and finally determining the flow condition of the staff in the operation subject to be evaluated according to the type and the quantity of the operation information, or predicting the future flow condition, the problem of low evaluation accuracy rate caused by data counterfeiting or report missing condition which may occur in the financial credit evaluation is avoided, and the evaluation efficiency of the financial credit evaluation can be improved because large data dynamic monitoring is adopted in the whole process.
Accordingly, the system, the electronic device and the computer-readable storage medium provided by the embodiment of the invention also have the technical effects.
Drawings
FIG. 1 is a schematic flow chart of a possible big data-based intelligent dynamic assessment method for financial credit according to an embodiment of the present disclosure;
FIG. 2 is a block diagram illustrating a schematic structure of a possible big data-based intelligent dynamic financial credit evaluation system according to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of a hardware structure of a possible big data-based intelligent dynamic financial credit evaluation system according to an embodiment of the present application;
fig. 4 is a schematic structural block diagram of a possible electronic device provided in an embodiment of the present application;
fig. 5 is a schematic structural block diagram of a possible computer-readable storage medium provided in an embodiment of the present application.
Detailed Description
The embodiment of the application provides an intelligent financial credit dynamic evaluation method based on big data and related equipment, and can solve the problems of low accuracy rate and low evaluation efficiency of credit evaluation results.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present application and in the drawings described above, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments.
Referring to fig. 1, a flowchart of an intelligent financial credit dynamic evaluation method based on big data according to an embodiment of the present application is used for a user terminal device, and specifically may include: S110-S130.
S110, receiving an interactive request of a user to the target user terminal equipment.
The user here may be all employees in the subject range of the evaluated object, and the target user terminal may be all employee terminal devices in the subject range of the evaluated object, and is not limited to a mobile phone, a tablet computer and a smart wearable device.
The interactive request may be an interactive request sent by a user touching the terminal panel, for example, an interactive request for operating an application program in the terminal device.
And S120, acquiring target indication information generated based on the user interaction request, wherein the target indication information comprises running information of a target type interaction application.
In some examples, the target indication information may be indication information indicating fluidity of all employees within the subject range of the subject to be evaluated and possible fluidity.
In some examples, the target-type interactive application may be various job-seeking applications, forum applications, and the like, and is not limited herein.
The target type interactive application is a post application interactive application, and the running information of the target type interactive application comprises access action information, running duration, forwarding action information and downloading action information.
In some examples, the downloading action may be a downloading action of the target application, or a downloading action of some content in the target application.
In some examples, the number of the target user terminal devices is multiple, and the running information of the target type interactive application further includes a running concentration of the target type interactive application, where the running concentration is the number of the target user terminal devices generating the target indication information in the multiple target user terminal devices within a preset range around the same time;
and calculating the first user concentration ratio of the plurality of target user terminal devices in a preset range before and after the same moment.
It should be noted that, employees in the subject scope of the evaluated object may have the running concentration of the target type interactive application in the preset scope before and after the same time, because it can indicate whether there is a sudden activity of a certain interactive action of a large number of employees in the subject scope of the evaluated object in the same time scope. This may be considered to be an important factor that indicates mobility of the person or that indicates the presence of a significant risk or occurrence of a significant adverse event within the subject being evaluated.
In addition, it can be understood that the data acquisition is carried out on the target terminal equipment within the range of the evaluated object subject in the above manner, so that the authenticity and predictability of the data can be guaranteed to the maximum extent.
And S130, obtaining a target indication financial credit score according to the type and the corresponding quantity of the running information of the target type interactive application, and performing dynamic assessment on the financial credit according to the target indication financial credit score.
In some examples, the obtaining a target indication financial credit score according to the type and the corresponding amount of the running information of the target type interactive application specifically includes:
counting the running information of the target type interactive application, and analyzing through SPSS software to obtain the weight of each running information;
and calculating to obtain a financial credit score of the target indication according to the weight and the corresponding quantity of each item of running information in the running information of the target type interactive application included in the target indication information.
According to the embodiment, the running information is dynamically counted and analyzed through an intelligent algorithm, so that the financial credit score of the target indication is obtained, and the efficiency of credit evaluation can be further improved.
In some examples, target indication sample information of a target field in the whole network or the field to which the user belongs is obtained through a web crawler process;
in some examples, the method further comprises:
and comparing the first user concentration ratio with the second user concentration ratio to obtain a comparison result.
The step of obtaining a target indication financial credit score according to the type and the corresponding quantity of the running information of the target type interactive application and performing dynamic assessment on the financial credit according to the target indication financial credit score comprises the following steps:
and performing dynamic assessment of financial credit according to the comparison result and the target indication financial credit score.
And training the neural network through the target indication sample information, and predicting a second user concentration ratio within a preset range before and after the same moment based on the trained neural network model. The big data can be used for transversely comparing the analysis indexes, and the accuracy of evaluation is improved.
In some examples, the terminal devices serving as a basis for calculation in the first user concentration ratio and the second user concentration ratio are counted in the number of terminal devices only when the running information of the target type interactive application reaches a preset activity. This may further improve the accuracy, universality and usability of the data.
In summary, the intelligent financial credit dynamic evaluation method based on big data provided in the foregoing embodiments is applied to a user terminal device, and includes: receiving an interaction request of a user to a target user terminal device, and acquiring target indication information generated based on the user interaction request, wherein the target indication information comprises running information of a target type interaction application; and obtaining a target indication financial credit score according to the type and the corresponding quantity of the running information of the target type interactive application, and performing dynamic assessment on the financial credit according to the target indication financial credit score. By recording the interaction request and the operation information which are related to the target indication information of the terminal equipment of the staff in the operation subject to be evaluated, for example, the operation information can be the operation information in job application, and finally determining the flow condition of the staff in the operation subject to be evaluated according to the type and the quantity of the operation information, or predicting the future flow condition, the problem of low evaluation accuracy rate caused by data counterfeiting or report missing condition which may occur in the financial credit evaluation is avoided, and the evaluation efficiency of the financial credit evaluation can be improved because large data dynamic monitoring is adopted in the whole process.
The above describes the intelligent financial credit dynamic evaluation method based on big data in the embodiment of the present application, and the following describes the intelligent financial credit dynamic evaluation system based on big data in the embodiment of the present application.
Referring to fig. 2, an embodiment of a big data based intelligent dynamic financial credit evaluation system is described in the embodiment of the present application, which may include:
a receiving unit 201, configured to receive an interaction request from a user to a target user terminal device;
an obtaining unit 202, configured to obtain target indication information generated based on the user interaction request, where the target indication information includes running information of a target type interaction application;
and the evaluation unit 203 is used for obtaining a target indication financial credit score according to the type and the corresponding quantity of the running information of the target type interactive application and performing dynamic financial credit evaluation according to the target indication financial credit score.
The target type interactive application is a post application interactive application, and the running information of the target type interactive application comprises access action information, running duration, forwarding action information and downloading action information.
The target user terminal devices are multiple, the running information of the target type interactive application further comprises running concentration of the target type interactive application, and the running concentration is the number of the target user terminal devices generating the target indication information in the multiple target user terminal devices within a preset range before and after the same moment;
and calculating the first user concentration ratio of the plurality of target user terminal devices in a preset range before and after the same moment.
The evaluation unit 203 may be specifically configured to:
counting the running information of the target type interactive application, and analyzing through SPSS software to obtain the weight of each running information;
and calculating to obtain a financial credit score of the target indication according to the weight and the corresponding quantity of each item of running information in the running information of the target type interactive application included in the target indication information.
The evaluation unit 203 may be specifically configured to:
acquiring target indication sample information of a target field in the whole network or the field to which the user belongs through a web crawler process;
and training the neural network through the target indication sample information, and predicting a second user concentration ratio within a preset range before and after the same moment based on the trained neural network model.
The evaluation unit 203 may be specifically configured to:
and comparing the first user concentration ratio with the second user concentration ratio to obtain a comparison result.
The step of obtaining a target indication financial credit score according to the type and the corresponding quantity of the running information of the target type interactive application and performing dynamic assessment on the financial credit according to the target indication financial credit score comprises the following steps:
and performing dynamic assessment of financial credit according to the comparison result and the target indication financial credit score.
In some examples, the terminal devices serving as a basis for calculation in the first user concentration ratio and the second user concentration ratio are counted in the number of terminal devices only when the running information of the target type interactive application reaches a preset activity.
In summary, the intelligent financial credit dynamic evaluation system based on big data provided in the foregoing embodiments is used for a user terminal device, and includes: receiving an interaction request of a user to a target user terminal device, and acquiring target indication information generated based on the user interaction request, wherein the target indication information comprises running information of a target type interaction application; and obtaining a target indication financial credit score according to the type and the corresponding quantity of the running information of the target type interactive application, and performing dynamic assessment on the financial credit according to the target indication financial credit score. By recording the interaction request and the operation information which are related to the target indication information of the terminal equipment of the staff in the operation subject to be evaluated, for example, the operation information can be the operation information in job application, and finally determining the flow condition of the staff in the operation subject to be evaluated according to the type and the quantity of the operation information, or predicting the future flow condition, the problem of low evaluation accuracy rate caused by data counterfeiting or report missing condition which may occur in the financial credit evaluation is avoided, and the evaluation efficiency of the financial credit evaluation can be improved because large data dynamic monitoring is adopted in the whole process.
In some examples, the staff inside the operation subject of the evaluated object, especially the qualified staff capable of embodying the qualification of the operation subject of the evaluated object, may be subjected to job data collection by an intelligent means, so as to further improve the accuracy of evaluation and avoid data cheating during evaluation. In some examples, the location of the qualified employee's work device and the degree of match of the job data may be located, e.g., by a web crawler process obtaining a sample of job data for a target domain within the entire network or a domain to which the user belongs;
and training the neural network through the operation data sample, predicting operation contents matched with the qualified staff based on the trained neural network model, and matching the operation contents with the real-time operation contents of the qualified staff, so that the number of the user equipment which accords with the operation contents in the evaluated main body is judged, and is checked with the reported number, and the evaluation accuracy is further improved.
Fig. 2 above describes the intelligent financial credit dynamic evaluation system based on big data in the embodiment of the present application from the perspective of modular functional entities, and the following describes the intelligent financial credit dynamic evaluation system based on big data in the embodiment of the present application in detail from the perspective of hardware processing, please refer to fig. 3, in which an embodiment of the intelligent financial credit dynamic evaluation system 300 based on big data in the embodiment of the present application includes:
an input device 301, an output device 302, a processor 303 and a memory 304, wherein the number of the processor 303 may be one or more, and one processor 303 is taken as an example in fig. 5. In some embodiments of the present application, the input device 301, the output device 502, the processor 303, and the memory 304 may be connected by a bus or other means, wherein fig. 5 illustrates the connection by the bus.
Wherein, by calling the operation instruction stored in the memory 304, the processor 303 is configured to perform the following steps:
receiving an interaction request of a user to a target user terminal device,
acquiring target indication information generated based on the user interaction request, wherein the target indication information comprises running information of a target type interaction application;
and obtaining a target indication financial credit score according to the type and the corresponding quantity of the running information of the target type interactive application, and performing dynamic assessment on the financial credit according to the target indication financial credit score.
The processor 303 is also configured to perform any of the methods in the corresponding embodiments of fig. 1 by calling the operation instructions stored in the memory 304.
Referring to fig. 4, fig. 4 is a schematic view of an embodiment of an electronic device according to an embodiment of the present disclosure.
As shown in fig. 4, an electronic device provided in the embodiment of the present application includes a memory 410, a processor 420, and a computer program 411 stored in the memory 420 and executable on the processor 420, where the processor 420 executes the computer program 411 to implement the following steps:
receiving an interaction request of a user to a target user terminal device,
acquiring target indication information generated based on the user interaction request, wherein the target indication information comprises running information of a target type interaction application;
and obtaining a target indication financial credit score according to the type and the corresponding quantity of the running information of the target type interactive application, and performing dynamic assessment on the financial credit according to the target indication financial credit score.
In a specific implementation, when the processor 420 executes the computer program 411, any of the embodiments corresponding to fig. 1 may be implemented.
Since the electronic device described in this embodiment is a device used for implementing the intelligent financial credit dynamic evaluation system based on big data in this embodiment, based on the method described in this embodiment, a person skilled in the art can understand the specific implementation manner of the electronic device of this embodiment and various variations thereof, so that how to implement the method in this embodiment by the electronic device is not described in detail herein, and as long as the person skilled in the art implements the device used for implementing the method in this embodiment, the scope of protection intended by this application is included.
Referring to fig. 5, fig. 5 is a schematic diagram illustrating an embodiment of a computer-readable storage medium according to the present application.
As shown in fig. 5, the present embodiment provides a computer-readable storage medium 500 having a computer program 511 stored thereon, the computer program 511 implementing the following steps when executed by a processor:
receiving an interaction request of a user to a target user terminal device,
acquiring target indication information generated based on the user interaction request, wherein the target indication information comprises running information of a target type interaction application;
and obtaining a target indication financial credit score according to the type and the corresponding quantity of the running information of the target type interactive application, and performing dynamic assessment on the financial credit according to the target indication financial credit score.
In a specific implementation, the computer program 511 may implement any of the embodiments corresponding to fig. 1 when executed by a processor.
It should be noted that, in the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to relevant descriptions of other embodiments for parts that are not described in detail in a certain embodiment.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Embodiments of the present application further provide a computer program product, where the computer program product includes computer software instructions, when the computer software instructions are run on a processing device, the processing device is caused to execute the flow in the intelligent dynamic financial credit assessment method based on big data in the corresponding embodiment of fig. 1.
The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the application to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can store or a data storage device, such as a server, a data center, etc., that is integrated with one or more available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (10)
1. The intelligent financial credit dynamic evaluation method based on big data is used for user terminal equipment, and is characterized by comprising the following steps:
receiving an interactive request of a user to a target user terminal device;
acquiring target indication information generated based on the user interaction request, wherein the target indication information comprises running information of a target type interaction application;
and obtaining a target indication financial credit score according to the type and the corresponding quantity of the running information of the target type interactive application, and performing dynamic assessment on the financial credit according to the target indication financial credit score.
2. The method of claim 1, wherein the target-type interactive application is a post application interactive application, and the operation information of the target-type interactive application comprises access action information, operation duration, forwarding action information, and downloading action information.
3. The method according to claim 2, wherein the number of the target user terminal devices is multiple, the running information of the target type interactive application further includes a running concentration of the target type interactive application, and the running concentration is the number of the target user terminal devices generating the target indication information in the multiple target user terminal devices within a preset range around the same time;
and calculating the first user concentration ratio of the plurality of target user terminal devices in a preset range before and after the same moment.
4. The method according to claim 3, wherein obtaining a target indicated financial credit score according to the type and corresponding amount of the run information of the target type interactive application specifically comprises:
counting the running information of the target type interactive application, and analyzing through SPSS software to obtain the weight of each running information;
and calculating to obtain a financial credit score of the target indication according to the weight and the corresponding quantity of each item of running information in the running information of the target type interactive application included in the target indication information.
5. The method of claim 4, further comprising:
acquiring target indication sample information of a target field in the whole network or the field to which the user belongs through a web crawler process;
and training the neural network through the target indication sample information, and predicting a second user concentration ratio within a preset range before and after the same moment based on the trained neural network model.
6. The method of claim 5, further comprising:
comparing the first user concentration ratio with the second user concentration ratio to obtain a comparison result;
the step of obtaining a target indication financial credit score according to the type and the corresponding quantity of the running information of the target type interactive application and performing dynamic assessment on the financial credit according to the target indication financial credit score comprises the following steps:
and performing dynamic assessment of financial credit according to the comparison result and the target indication financial credit score.
7. The method according to claim 6, wherein the terminal devices of the first and second user concentration ratios serving as a basis for calculation are counted into the number of terminal devices only when the operation information of the target type interactive application reaches a preset activity.
8. An intelligent financial credit dynamic assessment system based on big data, comprising:
the receiving unit is used for receiving an interaction request of a user to the target user terminal equipment;
the acquisition unit is used for acquiring target indication information generated based on the user interaction request, and the target indication information comprises running information of a target type interaction application;
and the evaluation unit is used for obtaining a target indication financial credit score according to the type and the corresponding quantity of the running information of the target type interactive application and carrying out dynamic evaluation on the financial credit according to the target indication financial credit score.
9. An electronic device comprising a memory, a processor, wherein the processor is configured to implement the steps of the big data based intelligent dynamic assessment method of financial credit of any one of claims 1 to 7 when executing a computer program stored in the memory.
10. A computer-readable storage medium having stored thereon a computer program, characterized in that: the computer program when executed by a processor implements the steps of the big data based intelligent dynamic assessment method of financial credits of any one of claims 1 to 7.
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