CN117611355A - Policy quality evaluation method, device, equipment and medium - Google Patents
Policy quality evaluation method, device, equipment and medium Download PDFInfo
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- G—PHYSICS
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- 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
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Abstract
The invention relates to an artificial intelligence technology, and discloses a policy quality evaluation method, which comprises the following steps: acquiring historical policy data from a preset policy database, and analyzing and clustering the historical policy data to obtain policy clustering data; extracting the policy data characteristics of each policy cluster data; acquiring quality information of the historical policy data, and training a preset policy scoring model according to the quality information and the characteristics of the policy data to obtain a standard policy scoring model; and acquiring the pre-signed data of the pre-signed policy, calculating the quality score of the pre-signed data of the policy by using the standard policy scoring model, and outputting the quality evaluation result of the pre-signed policy according to the quality score. The invention also provides a policy quality evaluation device, electronic equipment and a storage medium. The invention can realize intelligent evaluation of the policy, and improve the efficiency and accuracy of the policy evaluation.
Description
Technical Field
The present invention relates to the field of artificial intelligence technologies, and in particular, to a policy quality evaluation method, a policy quality evaluation device, an electronic device, and a computer readable storage medium.
Background
The risk prevention and control takes an increasingly important role in enterprises, such as the more important the insurance risk prevention and control is in the development of insurance business of insurance companies, a good insurance risk prevention and control scheme can evaluate and monitor the quality of insurance policies, and help the insurance companies to change to intelligent wind control.
The existing method for evaluating the quality of the insurance policy is mainly based on manual screening, and a large gap exists between the management and control system, the quantization technology, the monitoring and early warning and other aspects for realizing the fine risk management and control of the insurance policy, so that an intelligent evaluation method for the quality of the insurance policy is needed, and the prepositive management and control of the insurance policy is carried out, so that the smooth signing of the policy with the quality which does not meet the requirements is avoided.
Disclosure of Invention
The invention provides a policy quality evaluation method, a policy quality evaluation device and a computer readable storage medium, which mainly aim to realize intelligent evaluation of a policy and improve the efficiency and accuracy of policy evaluation.
In order to achieve the above object, the present invention provides a policy quality evaluation method, including:
acquiring historical policy data from a preset policy database, and analyzing and clustering the historical policy data to obtain policy clustering data;
extracting the policy data characteristics of each policy cluster data;
acquiring quality information of the historical policy data, and training a preset policy scoring model according to the quality information and the characteristics of the policy data to obtain a standard policy scoring model;
and acquiring the pre-signed data of the pre-signed policy, calculating the quality score of the pre-signed data of the policy by using the standard policy scoring model, and outputting the quality evaluation result of the pre-signed policy according to the quality score.
Optionally, the analyzing and clustering the historical policy data to obtain policy clustering data includes:
acquiring the data type of the historical policy data based on a big data technology, and analyzing the historical policy data by using a data analysis method according to the data type to obtain standard policy data;
carrying out information filtering on the standard policy data to obtain filtered policy data;
and clustering the filtering policy data to obtain policy clustering data.
Optionally, the filtering the information of the standard policy data to obtain filtered policy data includes:
carrying out data cleaning on the standard data by an outlier processing method to obtain cleaning policy data;
and carrying out information filtering on the cleaning policy data according to a preset standard policy database by a preset character string matching algorithm to obtain the filtering policy data.
Optionally, the extracting the policy data feature of each policy cluster data includes:
the policy clustering data are subjected to word segmentation through a preset word segmentation component, so that policy segmentation is obtained;
converting the policy segmentation into a character string form to obtain a policy segmentation character string;
constructing an empty array, and receiving the policy segmentation character string by using the empty array;
and extracting the characteristics in the policy segmentation character string by using a preset text characteristic extraction function to obtain the policy data characteristics.
Optionally, the acquiring the quality information of the historical policy data includes:
acquiring a policy payment state according to the historical policy data;
if the policy payment state is timely payment, confirming the quality information of the historical policy data as a first type of quality;
if the policy payment state is not timely payment, acquiring the renewal time from the historical policy data;
judging whether the duration is within a preset duration range or not;
if the duration is within the duration range, confirming the quality information of the historical policy data as a second class of quality;
and if the renewal time is not in the renewal time range, confirming the quality information of the historical policy data as third class quality.
Optionally, the historical policy data in the policy database is stored in the form of a message queue.
Optionally, the policy data features include policy information, product information, customer information agent information, agent and buyer behavior features.
In order to solve the above problems, the present invention also provides a policy quality evaluation device, the device comprising:
the policy data acquisition module: the method comprises the steps of obtaining historical policy data from a preset policy database, analyzing and clustering the historical policy data to obtain policy clustering data, and extracting policy data characteristics of each policy clustering data;
model training module: the method comprises the steps of obtaining quality information of historical policy data, training a preset policy scoring model according to the quality information and the characteristics of the policy data, and obtaining a standard policy scoring model;
and the policy quality assessment module: and the method is used for acquiring the pre-signed data of the pre-signed policy, calculating the quality score of the pre-signed data of the policy by using the standard policy scoring model, and outputting the quality evaluation result of the pre-signed policy according to the quality score.
In order to solve the above-mentioned problems, the present invention also provides an electronic apparatus including:
at least one processor;
and a memory communicatively coupled to the at least one processor;
wherein the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to perform the policy quality assessment method described above.
In order to solve the above-described problems, the present invention also provides a computer-readable storage medium having stored therein at least one computer program that is executed by a processor in an electronic device to implement the policy quality evaluation method described above.
According to the embodiment of the invention, the policy scoring model can be trained according to the historical policy data, and the quality score of the pre-signed policy is analyzed based on the policy scoring model, so that intelligent evaluation of the policy instructions is realized, and the efficiency and accuracy of policy evaluation are improved.
Drawings
FIG. 1 is a flowchart of a policy quality evaluation method according to an embodiment of the present invention;
FIG. 2 is a functional block diagram of a policy quality evaluation device according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device for implementing the policy quality evaluation method according to an embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The embodiment of the application provides a policy quality evaluation method. The execution subject of the policy quality evaluation method includes, but is not limited to, at least one of a server, a terminal, and the like, which can be configured to execute the method provided by the embodiment of the application. In other words, the policy quality evaluation method may be performed by software or hardware installed in a terminal device or a server device, and the software may be a blockchain platform. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.
Referring to fig. 1, a flow chart of a policy quality evaluation method according to an embodiment of the invention is shown. In this embodiment, the policy quality evaluation method includes:
s1, acquiring historical policy data from a preset policy database, and analyzing and clustering the historical policy data to obtain policy clustering data.
In the embodiment of the invention, the policy database can be used for storing all databases of completed policy data, namely databases of historical policy data, for a company providing insurance service to develop policy business service.
Further, the historical policy data in the policy database is stored in a form of a message queue, and the specific storage form may be that the historical policy data is stored according to a time sequence of the historical policy data, that is, the historical policy data with a time sequence earlier than a preset time is stored in a first storage location of the message queue, and the historical policy data with a time sequence later than the preset time is stored in a second storage location of the message queue, where the second storage location is distributed behind the first storage location in the message queue.
When the embodiment of the invention acquires the history policy data from the policy database, the history policy data of the second storage position in the message queue is acquired, namely the history policy data newly added into the policy database is acquired.
In the embodiment of the invention, the history policy data is stored in the form of the message queue, and the history policy data newly added into the policy database is preferentially acquired when the history policy data is acquired, so that the timeliness of the acquired history policy data can be improved, the long-term storage time of the acquired policy data is avoided, and the use value is not provided.
In the embodiment of the invention, the historical policy data is analyzed, information is filtered, and clustering, automatic classification and the like are carried out through a big data technology, so that policy clustering data is obtained.
Further, the analyzing and clustering the historical policy data to obtain policy clustering data includes:
acquiring the data type of the historical policy data based on a big data technology, and analyzing the historical policy data by using a data analysis method according to the data type to obtain standard policy data;
carrying out information filtering on the standard policy data to obtain filtered policy data;
and clustering the filtering policy data to obtain policy clustering data.
In the embodiment of the invention, the data analysis method is a method for converting the format of the historical policy data, so that the historical policy data can be converted from a data format convenient for transmission into a data format convenient for reading, and the standard policy data is the historical policy data convenient for reading after the data format conversion. For example, commonly used data parsing methods are JOSN data parsing and XML data parsing.
In the embodiment of the invention, the filtering policy data can be clustered through a K-Means algorithm or a K-media algorithm, wherein the clustered policy clustering data can facilitate feature extraction and acquire the features of the history policy data. In the embodiment of the invention, through analyzing and filtering the historical policy data, the terms and the important information in the policy data can be extracted from the obscure insurance terms and the policy data of the policy and displayed to the user, and the obtained policy terms can be converted into the policy terms which can be read by the user.
Further, the filtering the standard policy data to obtain filtered policy data includes:
carrying out data cleaning on the standard data by an outlier processing method to obtain cleaning policy data;
and carrying out information filtering on the cleaning policy data according to a preset standard policy database by a preset character string matching algorithm to obtain the filtering policy data.
In the embodiment of the present invention, the standard policy database is a database for defining a term specification of a policy, and further, an algorithm for filtering the cleaning policy data may be a regular expression matching algorithm, a finite automaton (Deterministic Finite Automaton, DFA) determining algorithm, or the like, in addition to the character string matching algorithm.
In the embodiment of the invention, the abnormal value processing method comprises the steps of supplementing missing data, replacing an average value of the abnormal data, deleting repeated data and the like, wherein the abnormal value in the abnormal value processing method comprises but not limited to an abnormally large or small data value, and also comprises the missing data value, the repeated data value and the like.
In the embodiment of the invention, the standard policy data is filtered to screen the policy, and the data which does not meet the requirements in the analysis policy data is removed.
Further, the policy cluster data is text data.
S2, extracting the policy data characteristics of each policy clustering data.
In the embodiment of the invention, the data characteristics of the policy include data characteristics of various aspects such as policy information, product information, customer information agent information, agent and buyer behavior characteristics and the like.
Further, the extracting the policy data feature of each policy cluster data includes:
the policy clustering data are subjected to word segmentation through a preset word segmentation component, so that policy segmentation is obtained;
converting the policy segmentation into a character string form to obtain a policy segmentation character string;
constructing an empty array, and receiving the policy segmentation character string by using the empty array;
and extracting the characteristics in the policy segmentation character string by using a preset text characteristic extraction function to obtain the policy data characteristics.
In the embodiment of the invention, the word segmentation component is a Jieba word segmentation component, is a Chinese word segmentation component based on python, and can determine the association probability between Chinese characters by means of a Chinese word stock so as to realize word segmentation.
In the embodiment of the invention, the text feature extraction function is a countvector function.
In another embodiment of the present invention, the policy data feature of the policy data may also be extracted by a random forest algorithm.
In the embodiment of the invention, the data characteristics of the policy clustering data are extracted, so that the characteristics of each type of policy can be obtained, and the relationship between the data characteristics of the policy and the quality of the policy can be conveniently determined later.
And S3, acquiring quality information of the historical policy data, and training a preset policy scoring model according to the quality information and the characteristics of the policy data to obtain a standard policy scoring model.
In the embodiment of the invention, the quality information can be obtained according to the payment condition of the historical policy, namely, the user of one policy pays timely, and the quality information of the policy is determined to meet the requirement.
In the embodiment of the present invention, the obtaining the quality information of the historical policy data includes:
acquiring a policy payment state according to the historical policy data;
if the policy payment state is timely payment, confirming the quality information of the historical policy data as a first type of quality;
if the policy payment state is not timely payment, acquiring the renewal time from the historical policy data;
judging whether the duration is within a preset duration range or not;
if the duration is within the duration range, confirming the quality information of the historical policy data as a second class of quality;
and if the renewal time is not in the renewal time range, confirming the quality information of the historical policy data as third class quality.
In the embodiment of the invention, the first class quality is better than the second class quality, and the second class quality is better than the third class quality.
In the embodiment of the invention, the preset policy scoring model is trained according to the quality information and the policy data characteristics, so that the relation between the quality information and the policy data characteristics is established, and then the weight of each policy data characteristic in evaluating the quality of the policy can be determined when the policy is scored, namely, each policy data characteristic has different influences on the quality of the policy.
In another embodiment of the present invention, the quality information of the policy may be determined to meet the requirement according to the application range of the history policy, that is, the number of subscribers to one policy is large.
S4, acquiring the pre-signed data of the pre-signed policy, calculating the quality score of the pre-signed data of the policy by using a standard policy scoring model, and outputting the quality evaluation result of the pre-signed policy according to the quality score.
In the embodiment of the invention, the policy pre-signing data is the policy data to be evaluated, and the policy pre-signing data can be the data of pre-signing the policy before the insurance agent and the applicant formally sign up the policy.
In the embodiment of the invention, the quality score is the quality evaluation of the pre-endorsement policy.
Further, if the quality score of the pre-signed policy is a score of a first class quality and a score of a second class quality, the pre-signed policy may be signed formally, and if the quality score of the pre-signed policy is a score of a third class quality, the pre-signed policy may be discarded and an early warning notification may be sent to an insurance agent.
According to the embodiment of the invention, the policy scoring model can be trained according to the historical policy data, and the quality score of the pre-signed policy is analyzed based on the policy scoring model, so that the intelligent evaluation of the policy instructions is realized.
Fig. 2 is a functional block diagram of a policy quality evaluation device according to an embodiment of the present invention.
The policy quality evaluation device 100 of the present invention may be mounted in an electronic apparatus. The policy quality evaluation device 100 may include a policy data acquisition module 101, a model training module 102, and a policy quality evaluation module 103 according to the implemented functions. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.
In the present embodiment, the functions concerning the respective modules/units are as follows:
the policy data acquisition module 101: the method comprises the steps of obtaining historical policy data from a preset policy database, analyzing and clustering the historical policy data to obtain policy clustering data, and extracting policy data characteristics of each policy clustering data;
the model training module 102: the method comprises the steps of obtaining quality information of historical policy data, training a preset policy scoring model according to the quality information and the characteristics of the policy data, and obtaining a standard policy scoring model;
the policy quality assessment module 103: and the method is used for acquiring the pre-signed data of the pre-signed policy, calculating the quality score of the pre-signed data of the policy by using the standard policy scoring model, and outputting the quality evaluation result of the pre-signed policy according to the quality score.
In detail, each module in the policy quality evaluation device 100 in the embodiment of the present invention adopts the same technical means as the policy quality evaluation method described in fig. 1 and can produce the same technical effects when in use, and will not be described herein.
Fig. 3 is a schematic structural diagram of an electronic device for implementing a policy quality evaluation method according to an embodiment of the present invention.
The electronic device 1 may comprise a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may further comprise a computer program, such as a policy quality evaluation program, stored in the memory 11 and executable on the processor 10.
The processor 10 may be formed by an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be formed by a plurality of integrated circuits packaged with the same function or different functions, including one or more central processing units (Central Processing unit, CPU), a microprocessor, a digital processing chip, a graphics processor, a combination of various control chips, and so on. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various parts of the entire electronic device using various interfaces and lines, executes or executes programs or modules (for example, executes policy quality evaluation programs or the like) stored in the memory 11, and invokes data stored in the memory 11 to perform various functions of the electronic device and process data.
The memory 11 includes at least one type of readable storage medium including flash memory, a removable hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device, such as a mobile hard disk of the electronic device. The memory 11 may in other embodiments also be an external storage device of the electronic device, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the electronic device. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device. The memory 11 may be used not only for storing application software installed in an electronic device and various types of data, such as codes of policy quality evaluation programs, but also for temporarily storing data that has been output or is to be output.
The communication bus 12 may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus, or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. The bus is arranged to enable a connection communication between the memory 11 and at least one processor 10 etc.
The communication interface 13 is used for communication between the electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), typically used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a Display (Display), an input unit such as a Keyboard (Keyboard), or alternatively a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the electronic device and for displaying a visual user interface.
Only an electronic device having components is shown, and it will be understood by those skilled in the art that the structures shown in the figures do not limit the electronic device, and may include fewer or more components than shown, or may combine certain components, or a different arrangement of components.
For example, although not shown, the electronic device may further include a power source (such as a battery) for supplying power to the respective components, and preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management, and the like are implemented through the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The electronic device may further include various sensors, bluetooth modules, wi-Fi modules, etc., which are not described herein.
It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.
The policy quality evaluation program stored in the memory 11 in the electronic device 1 is a combination of instructions that, when executed in the processor 10, may implement:
acquiring historical policy data from a preset policy database, and analyzing and clustering the historical policy data to obtain policy clustering data;
extracting the policy data characteristics of each policy cluster data;
acquiring quality information of the historical policy data, and training a preset policy scoring model according to the quality information and the characteristics of the policy data to obtain a standard policy scoring model;
and acquiring the pre-signed data of the pre-signed policy, calculating the quality score of the pre-signed data of the policy by using the standard policy scoring model, and outputting the quality evaluation result of the pre-signed policy according to the quality score.
In particular, the specific implementation method of the above instructions by the processor 10 may refer to the description of the relevant steps in the corresponding embodiment of the drawings, which is not repeated herein.
Further, the modules/units integrated in the electronic device 1 may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as separate products. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM).
The present invention also provides a computer readable storage medium storing a computer program which, when executed by a processor of an electronic device, can implement:
acquiring historical policy data from a preset policy database, and analyzing and clustering the historical policy data to obtain policy clustering data;
extracting the policy data characteristics of each policy cluster data;
acquiring quality information of the historical policy data, and training a preset policy scoring model according to the quality information and the characteristics of the policy data to obtain a standard policy scoring model;
and acquiring the pre-signed data of the pre-signed policy, calculating the quality score of the pre-signed data of the policy by using the standard policy scoring model, and outputting the quality evaluation result of the pre-signed policy according to the quality score.
In the several embodiments provided in the present invention, it should be understood that the disclosed apparatus, device 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 modules is merely a logical function division, and there may be other manners of division when actually implemented.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm and the like. The Blockchain (Blockchain), which is essentially a decentralised database, is a string of data blocks that are generated by cryptographic means in association, each data block containing a batch of information of network transactions for verifying the validity of the information (anti-counterfeiting) and generating the next block. The blockchain may include a blockchain underlying platform, a platform product services layer, an application services layer, and the like.
The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.
Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. A plurality of units or means recited in the system claims can also be implemented by means of software or hardware by means of one unit or means. The terms first, second, etc. are used to denote a name, but not any particular order.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (10)
1. A policy quality assessment method, the method comprising:
acquiring historical policy data from a preset policy database, and analyzing and clustering the historical policy data to obtain policy clustering data;
extracting the policy data characteristics of each policy cluster data;
acquiring quality information of the historical policy data, and training a preset policy scoring model according to the quality information and the characteristics of the policy data to obtain a standard policy scoring model;
and acquiring the pre-signed data of the pre-signed policy, calculating the quality score of the pre-signed data of the policy by using the standard policy scoring model, and outputting the quality evaluation result of the pre-signed policy according to the quality score.
2. The policy quality evaluation method of claim 1, wherein said performing analytical clustering on said historical policy data to obtain policy clustered data comprises:
acquiring the data type of the historical policy data based on a big data technology, and analyzing the historical policy data by using a data analysis method according to the data type to obtain standard policy data;
carrying out information filtering on the standard policy data to obtain filtered policy data;
and clustering the filtering policy data to obtain policy clustering data.
3. The policy quality evaluation method of claim 2, wherein said filtering the standard policy data to obtain filtered policy data comprises:
carrying out data cleaning on the standard data by an outlier processing method to obtain cleaning policy data;
and carrying out information filtering on the cleaning policy data according to a preset standard policy database by a preset character string matching algorithm to obtain the filtering policy data.
4. The policy quality evaluation method according to claim 1, wherein said extracting policy data features of each of said policy cluster data comprises:
the policy clustering data are subjected to word segmentation through a preset word segmentation component, so that policy segmentation is obtained;
converting the policy segmentation into a character string form to obtain a policy segmentation character string;
constructing an empty array, and receiving the policy segmentation character string by using the empty array;
and extracting the characteristics in the policy segmentation character string by using a preset text characteristic extraction function to obtain the policy data characteristics.
5. The policy quality evaluation method according to claim 1, wherein said obtaining quality information of said history policy data includes:
acquiring a policy payment state according to the historical policy data;
if the policy payment state is timely payment, confirming the quality information of the historical policy data as a first type of quality;
if the policy payment state is not timely payment, acquiring the renewal time from the historical policy data;
judging whether the duration is within a preset duration range or not;
if the duration is within the duration range, confirming the quality information of the historical policy data as a second class of quality;
and if the renewal time is not in the renewal time range, confirming the quality information of the historical policy data as third class quality.
6. A policy quality assessment method according to any one of claims 1 to 5, wherein the historical policy data in said policy database is stored in the form of a message queue.
7. The policy quality assessment method according to any one of claims 1 to 5, wherein said policy data features include policy information, product information, customer information agent information, agent and buyer behavior features.
8. A policy quality evaluation device, the device comprising:
the policy data acquisition module: the method comprises the steps of obtaining historical policy data from a preset policy database, analyzing and clustering the historical policy data to obtain policy clustering data, and extracting policy data characteristics of each policy clustering data;
model training module: the method comprises the steps of obtaining quality information of historical policy data, training a preset policy scoring model according to the quality information and the characteristics of the policy data, and obtaining a standard policy scoring model;
and the policy quality assessment module: and the method is used for acquiring the pre-signed data of the pre-signed policy, calculating the quality score of the pre-signed data of the policy by using the standard policy scoring model, and outputting the quality evaluation result of the pre-signed policy according to the quality score.
9. An electronic device, the electronic device comprising:
at least one processor;
and a memory communicatively coupled to the at least one processor;
wherein the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the policy quality assessment method according to any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the policy quality evaluation method according to any one of claims 1 to 7.
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