Method and device for searching influence parameter of customer score, equipment and storage medium

Abstract

The application relates to a data processing technology and discloses a customer score influence parameter searching method, which comprises the following steps: obtaining a customer information table of a customer to be scored in a database, and reading customer field information in the customer information table; regularly analyzing the customer field information according to the level of the customer field information to obtain regular fields; inquiring about the superior-inferior relationship of the regular fields, and constructing a tree diagram according to the superior-inferior relationship of the regular fields to obtain a regular field tree diagram; obtaining a preset score calculation formula, and obtaining each score parameter according to the input parameter of the score calculation formula based on the regular field tree diagram; adding each score parameter into the score calculation formula to obtain a customer score, and performing control variable analysis on the score parameter to search for an influence parameter of the customer score. The application further discloses a customer score influence parameter searching device, an electronic device and a storage medium. The application can improve the searching efficiency of the influence parameter when scoring the customer.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to a customer score influence parameter searching method and device, electronic equipment and computer readable storage medium. BACKGROUND

[0002] Customer value is the profit paid by the customer to the enterprise when the customer exists a transaction relationship with the enterprise and is willing to bear a suitable price for the products and services provided by the enterprise. For the enterprise, there are both high-quality customers and poor-quality customers. In this case, effective evaluation of the customers can help the enterprise to distinguish different customers, which is beneficial to the better operation and development of the enterprise.

[0003] The existing customer scoring method can only obtain a scoring result when scoring the customer according to customer information, and cannot obtain which information in the customer information has a greater influence on the scoring result. For example, in the financial insurance business, the score of the insured person can be calculated according to the industry code, over-age coefficient and medical limit information in the insured person information, and it is not possible to obtain which information causes the insured person's score to fail. At this time, it is not possible to effectively feedback to the customer and improve the service quality, and it also hinders the development of potential customers of the enterprise. SUMMARY

[0004] The present application provides a customer score influence parameter searching method, device and computer readable storage medium, which mainly aims to solve the problem of low searching efficiency of influence parameters when scoring the customer.

[0005] To achieve the above-mentioned purpose, the present application provides a customer score influence parameter searching method, which comprises:

[0006] Obtain the customer information table of the customer to be scored in the database, and read the customer field information in the customer information table;

[0007] Regularly analyze the customer field information according to the level of the customer field information, and obtain the regular field;

[0008] Query the superior-inferior relationship of the regular field, and construct a tree diagram according to the superior-inferior relationship of the regular field to obtain a regular field tree diagram;

[0009] Obtain a preset scoring calculation formula, and obtain the input parameters of the scoring calculation formula according to the regular field tree diagram to obtain each scoring parameter;

[0010] Put the each scoring parameter into the scoring calculation formula to obtain the customer score, and perform control variable analysis on the scoring parameter to search for the influence parameter of the customer score.

[0011] Optionally, the control variable analysis on the score parameters is performed to find the influence parameter of the customer score, including:

[0012] Step A, obtaining the industry of the customer in the customer information table, and querying each standard parameter in the score calculation formula according to the industry of the customer;

[0013] Step B, collecting the score parameters to obtain a score parameter set;

[0014] Step C, obtaining a score parameter from the score parameter set, and replacing the score parameter with the corresponding standard parameter and the remaining score parameters in the score parameter set in the score calculation formula to obtain a parameter-adjusted score;

[0015] Step D, calculating the score difference between the parameter-adjusted score and the customer score, and taking the score parameter as the influence parameter when the score difference is greater than or equal to a preset threshold;

[0016] Step E, determining whether each score parameter in the score parameter set participates in replacement;

[0017] If each score parameter in the score parameter set does not participate in replacement, return to Step C;

[0018] If each score parameter in the score parameter set participates in replacement, Step F, statistics the influence parameter of the customer score.

[0019] Optionally, the regular analysis is performed on the customer field information according to the level of the customer field information to obtain a regular field, including:

[0020] Obtaining the nested relationship between the customer field information, and extracting the customer field information according to the nested relationship to obtain field data of a multi-level structure;

[0021] Finding the regularity of the field data of the multi-level structure to obtain a regular field.

[0022] Optionally, before the each score parameter is counted in the score calculation formula to obtain the customer score, the method further includes:

[0023] Determining whether all parameters of the score calculation formula exist in the each score parameter;

[0024] If all parameters of the score calculation formula exist in the each score parameter, the customer score is directly obtained;

[0025] If all parameters of the score calculation formula do not exist in the each score parameter, it is determined whether the remaining information table of the customer exists in the database.

[0026] If the rest information table of the customer exists in the database, the missing parameters of the score calculation formula are completed by the rest information table, and the customer score is calculated;

[0027] If the rest information table of the customer does not exist in the database, the missing parameters in the score calculation formula are counted as 0 value, and the customer score is calculated.

[0028] Optionally, the customer information table of the customer to be scored in the database is obtained, comprising:

[0029] The score task of scoring the customer to be scored is obtained, and the task time limit is queried;

[0030] The serial number of the customer to be scored is queried, and the data table with the largest data amount within the task time limit is selected from the database according to the serial number, and the data table is taken as the customer information table.

[0031] Optionally, the input parameter of the score calculation formula is obtained according to the regular field tree diagram, and each score parameter is obtained, comprising:

[0032] The node field of each node in the regular field tree diagram is obtained, and the node field attribute is obtained by attribute analysis of the node field through a preset dictionary;

[0033] The target data level of the score calculation formula in the regular field tree diagram is obtained according to the node field attribute;

[0034] The field data of the target data level in the regular field tree diagram is obtained through a recursive function, and the field data is taken as the input parameter of the score calculation formula, and the each score parameter is obtained.

[0035] Optionally, after the upper and lower relationship of the regular field is queried, and the tree diagram is constructed according to the upper and lower relationship of the regular field, the regular field tree diagram is obtained, the method further comprises:

[0036] The node field of each node in the regular field tree diagram is obtained by traversing the regular field tree diagram;

[0037] The node field is converted into josn data, and the josn data is parsed into a JavaScript object;

[0038] The JavaScript object is inserted into a preset HTML page, and displayed in the front end.

[0039] To solve the above problems, the application further provides a customer score influence parameter searching device, which comprises:

[0040] A customer information reading module is configured to obtain a customer information table of a customer to be scored in a database and read customer field information in the customer information table.

[0041] A tree diagram constructing module is configured to regularly parse the customer field information according to a level of the customer field information, obtain regular fields, query an upper and lower level relationship of the regular fields, and construct a tree diagram according to the upper and lower level relationship of the regular fields to obtain a regular field tree diagram.

[0042] A score parameter obtaining module is configured to obtain a preset score calculation formula and obtain input parameters of the score calculation formula according to the regular field tree diagram to obtain each score parameter.

[0043] An influence parameter searching module is configured to add the each score parameter into the score calculation formula to obtain a customer score, and perform a control variable analysis on the score parameter to search for an influence parameter of the customer score.

[0044] To solve the above problems, the application further provides an electronic device, which comprises:

[0045] at least one processor; and

[0046] a memory connected with the at least one processor; wherein

[0047] the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the customer score influence parameter searching method.

[0048] To solve the above problems, the application further provides a computer readable storage medium, which stores at least one computer program, and the at least one computer program is executed by a processor in an electronic device to implement the customer score influence parameter searching method.

[0049] This invention, through its embodiments, parses the fields in a customer information table to identify patterns, thus classifying the field information. A tree diagram of these patterns is then constructed based on their hierarchical relationships, visually representing the relationships between different fields. Finally, parameters from the tree diagram are obtained using the scoring formula, and a controllable variable analysis is performed to identify parameters that influence customer scoring results. This allows for the identification of parameters affecting customer ratings. Therefore, the method, apparatus, electronic device, and computer-readable storage medium for identifying customer scoring parameters proposed in this invention solve the problem of not being able to clearly identify the impact of different parameters on scoring results when rating customers. Attached Figure Description

[0050] Figure 1 This is a flowchart illustrating a method for finding parameters influencing customer ratings according to an embodiment of the present invention.

[0051] Figure 2 for Figure 1 The diagram shows a detailed implementation process for one step in the method for finding the parameters affecting customer ratings.

[0052] Figure 3 for Figure 1 The diagram shows a detailed implementation process for one step in the method for finding the parameters affecting customer ratings.

[0053] Figure 4 This is a functional block diagram of a customer rating influence parameter lookup device provided in an embodiment of the present invention;

[0054] Figure 5 This is a schematic diagram of the structure of an electronic device for implementing the customer rating influence parameter search method according to an embodiment of the present invention.

[0055] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0056] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0057] The embodiment of the present application provides a customer score influence parameter searching method. The execution subject of the customer score influence parameter searching method includes but is not limited to at least one of electronic devices such as a server, a terminal and the like which can be configured to execute the method provided by the embodiment of the present application. In other words, the customer score influence parameter searching method can be executed by software or hardware installed in a terminal device or a server device, and the software can be a blockchain platform. The server 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 can be a stand-alone server, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and basic cloud computing services such as big data and artificial intelligence platforms.

[0058] Referring to Figure 1 As shown in the figure, the embodiment of the present application provides a flowchart of a customer score influence parameter searching method.

[0059] In the embodiment, the customer score influence parameter searching method includes:

[0060] S1, obtaining a customer information table of a customer to be scored in a database, and reading customer field information in the customer information table.

[0061] In the embodiment of the present application, the database stores information of all customers in a certain business of an enterprise, and in the database, the information of the customers is stored in the form of a data table.

[0062] The enterprise can be a financial service enterprise, for example, the enterprise is a network credit enterprise, can provide network credit services for customers, or the enterprise is an insurance company, can provide insurance signing services for customers.

[0063] In the embodiment of the present application, the customer information table has field information of a customer to be scored, and the reading of the customer field information in the customer information table can split and refine the information from the table which is a larger carrier, which is beneficial to subsequent analysis of different influences of different information of the customer to be scored on the scoring result.

[0064] Further, the obtaining of the customer information table of the customer to be scored in the database includes:

[0065] obtaining a scoring task for scoring the customer to be scored, and querying a task time limit of the scoring task;

[0066] Query the serial number of the to-be-scored customer, and select the data table with the largest amount of data within the task time limit from the database according to the serial number, and take the data table as the customer information table.

[0067] Specifically, the scoring task is determined according to the business scope of the enterprise, for example, when the business scope of the enterprise is network credit, the scoring task is a customer credit qualification scoring task, and when the business scope of the enterprise is insurance signing, the scoring task is a customer insurance qualification scoring task.

[0068] Among them, the serial number is a unique identifier of numbers or letters, which is used to identify the to-be-scored customer, so as to avoid that the queried customer is not the target customer, and to realize the tracking of the target customer.

[0069] In another embodiment of the application, all data tables corresponding to the to-be-scored customer within the task time limit can also be selected according to the serial number, and the data in each data table is compared to select the data table with the highest quality as the customer information table. The quality of the data table can be determined by the effective date, offset, and publication time of the data in the data table, and the offset is the value of the data offset from the preset standard data.

[0070] S2, regular analysis is performed on the customer field information according to the level of the customer field information, and a regular field is obtained.

[0071] In the embodiment of the application, the level of the customer field information is used to represent different depths of the customer field information, for example, the level of the credit text information is deeper than the information depth of the finance text information, and the level of the loan text information is deeper than the information depth of the credit text information. The regular field is a field that distinguishes different levels and attributes after summarization.

[0072] Further, the regular analysis of the customer field information according to the level of the customer field information to obtain the regular field comprises:

[0073] Obtain the nested relationship between the customer field information, and extract the customer field information respectively according to the nested relationship to obtain field data of a multi-level structure;

[0074] Find the regularity of the field data of the multi-level structure to obtain the regular field.

[0075] Specifically, the nested relationship between the customer field information represents the progression between different customer field information, for example, there is a progressive relationship between the three fields of finance, credit, and loan.

[0076] In the embodiment of the present application, the rule of querying the field data of the multi-level structure can facilitate positioning information and improve the processing efficiency of data, for example, in the financial field, the occurrence frequency of field data, the master-slave relationship between different field data, etc., can be queried, and "bank", "credit product" and "loan amount" are taken as rule fields.

[0077] S3, querying the superior-inferior relationship of the rule field, and constructing a tree diagram according to the superior-inferior relationship of the rule field to obtain a rule field tree diagram.

[0078] In the embodiment of the present application, the superior-inferior relationship of the rule field refers to the parent-child or ancestor-descendant relationship between different field information, wherein the parent-child relationship is generally used to represent the relationship between a field information and its directly subordinate field information, and the ancestor-descendant relationship is used to represent a more extensive hierarchical structure. The rule field tree diagram is a tree diagram constructed by taking the rule field as a node according to the superior-inferior relationship. The tree diagram is a chart in a tree structure, wherein each branch represents a decision or category, and each node represents different field information.

[0079] Further, after the querying the superior-inferior relationship of the rule field, and constructing a tree diagram according to the superior-inferior relationship of the rule field to obtain a rule field tree diagram, the method can further include:

[0080] traversing the rule field tree diagram to obtain node fields of each node in the rule field tree diagram;

[0081] converting the node fields into josn data, and parsing the josn data into a JavaScript object;

[0082] inserting the JavaScript object into a preset HTML page for front-end display.

[0083] In the embodiment of the present application, the josn data is data converted from text data, and the josn data is a lightweight data exchange data commonly used for network communication, data storage and front-end display. The JavaScript object is data converted from the josn data for facilitating front-end display, and the HTML page is a page for displaying the rule field tree diagram.

[0084] In the embodiment of the present application, by displaying the rule field tree diagram, each parameter in the customer information can be clearly determined, which can help enterprises analyze the portrait of customers and provide better services for customers.

[0085] S4, acquire a preset score calculation formula, and acquire input parameters of the score calculation formula according to the rule field tree diagram, to obtain each score parameter.

[0086] In the embodiment of the application, the score calculation formula is a formula for calculating the customer score by taking the data in the customer information table as parameters.

[0087] Referring to Figure 2 Further, the acquiring of the input parameters of the score calculation formula according to the rule field tree diagram to obtain each score parameter comprises:

[0088] S401, acquire node fields of each node in the rule field tree diagram, and perform attribute analysis on the node fields by a preset dictionary to obtain node field attributes;

[0089] S402, acquire a target data level of the score calculation formula in the rule field tree diagram according to the node field attributes;

[0090] S403, acquire field data of the target data level in the rule field tree diagram by a recursive function, and take the field data as input parameters of the score calculation formula to obtain each score parameter.

[0091] S5, take each score parameter into the score calculation formula to obtain a customer score, and perform control variable analysis on the score parameter to find an influence parameter of the customer score.

[0092] In the embodiment of the application, the customer score is a score obtained by taking all parameters in the customer information table that can be taken into the score calculation formula into the score calculation formula.

[0093] In the embodiment of the application, before the taking of each score parameter into the score calculation formula to obtain a customer score, the method further comprises:

[0094] determining whether all parameters of the score calculation formula exist in each score parameter;

[0095] if all parameters of the score calculation formula exist in each score parameter, the customer score is directly obtained;

[0096] if all parameters of the score calculation formula do not exist in each score parameter, it is determined whether the remaining information table of the customer exists in the database;

[0097] If the rest information table of the customer exists in the database, the missing parameters of the score calculation formula are completed by the rest information table, and the customer score is calculated.

[0098] If the rest information table of the customer does not exist in the database, the missing parameters in the score calculation formula are counted as 0 values, and the customer score is calculated.

[0099] In another embodiment of the present application, if the missing parameters in the score calculation formula are necessary parameters, the missing parameters are not counted as 0 values, but the general numerical value of the industry to which the customer to be scored belongs is obtained, and the general numerical value is counted into the score calculation formula to score the customer to be scored.

[0100] Referring to Figure 3 In an embodiment of the present application, the control variable analysis of the score parameters and the search for the influence parameters of the customer score include:

[0101] S501, obtaining the industry to which the customer in the customer information table belongs, and querying each standard parameter in the score calculation formula according to the industry to which the customer belongs;

[0102] S502, collecting each score parameter to obtain a score parameter set;

[0103] S503, obtaining a score parameter from the score parameter set, and replacing the score parameter with the corresponding standard parameter and the rest of the score parameters in the score parameter set into the score calculation formula to obtain a parameter-adjusted score;

[0104] S504, calculating the score difference between the parameter-adjusted score and the customer score, and regarding the score parameter as an influence parameter when the score difference is greater than or equal to a preset threshold;

[0105] S505, determining whether each score parameter in the score parameter set participates in replacement;

[0106] If each score parameter in the score parameter set does not participate in replacement, return to S503;

[0107] If each score parameter in the score parameter set participates in replacement, S506, statistics of the influence parameters of the customer score.

[0108] Further, the influence parameters of the customer score include but are not limited to one, for example, when providing an insurance signing service for a customer, the age and industry code in the medical limit, age, industry code, and gender in the customer information table have greater influence on the score and can be regarded as influence parameters, and the medical limit and gender have smaller influence and can be regarded as non-influence factors.

[0109] The embodiment of the present application further comprises the following after searching the influence parameter of the customer score:

[0110] The influence parameter is marked in the HTML page.

[0111] The marking of the influence parameter in the HTML page can intuitively show which information of the customer to be scored will affect the score result.

[0112] The embodiment of the present application realizes the classification of field information by regularly parsing the fields in the customer information table to obtain regular fields, constructs a regular field tree diagram through the superior-inferior relationship of the regular fields, displays the relationship between different field information in the form of images, finally acquires the parameters in the regular field tree diagram according to the score calculation formula, and performs variable controllable analysis to find out the parameters affecting the customer score result, so that the parameters affecting the score result can be determined when scoring the customer. Therefore, the customer score influence parameter searching method, device, electronic equipment and computer readable storage medium provided by the present application can solve the problem that different parameters affecting the score result cannot be determined when scoring the customer.

[0113] As shown in Figure 4 FIG. 1 is a functional module diagram of a customer score influence parameter searching device according to an embodiment of the present application.

[0114] The customer score influence parameter searching device 100 can be installed in an electronic equipment. According to the functions to be realized, the customer score influence parameter searching device 100 can comprise a customer information reading module 101, a tree diagram constructing module 102, a score parameter acquiring module 103 and an influence parameter searching module 104. The modules of the present application can also be called units, which refer to a series of computer program segments capable of being executed by an electronic equipment processor and capable of completing fixed functions, and are stored in the memory of the electronic equipment.

[0115] In the embodiment, the functions of the modules / units are as follows:

[0116] The customer information reading module 101 is used to acquire the customer information table of the customer to be scored in the database, and read the customer field information in the customer information table.

[0117] The tree diagram constructing module 102 is used to regularly parse the customer field information according to the level of the customer field information, obtain regular fields, query the superior-inferior relationship of the regular fields, and construct a tree diagram according to the superior-inferior relationship of the regular fields to obtain a regular field tree diagram.

[0118] The scoring parameter obtaining module 103 is configured to obtain a preset scoring calculation formula, and obtain input parameters of the scoring calculation formula according to the rule field tree diagram, so as to obtain each scoring parameter.

[0119] The influence parameter searching module 104 is configured to put the each scoring parameter into the scoring calculation formula to obtain a customer score, and perform control variable analysis on the scoring parameter to search for an influence parameter of the customer score.

[0120] In detail, each module in the influence parameter searching device 100 of the customer score in the embodiment of the present application uses the same technical means as the influence parameter searching method of the customer score in the above Figures 1 to 3 , and can produce the same technical effects, which will not be described here.

[0121] As shown in Figure 5 , it is a structural schematic diagram of an electronic device for implementing the influence parameter searching method of the customer score according to an embodiment of the present application.

[0122] The electronic device 1 can include a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and can further include a computer program stored in the memory 11 and executable on the processor 10, such as the influence parameter searching program of the customer score.

[0123] In some embodiments, the processor 10 can be composed of an integrated circuit, for example, can be composed of a single packaged integrated circuit, or can be composed of multiple packaged integrated circuits with the same function or different functions, including one or more combinations of central processing units (CPU), microprocessors, digital processing chips, graphics processors and various control chips. The processor 10 is the control core of the electronic device, which connects each component of the electronic device through various interfaces and lines, executes or runs the program or module stored in the memory 11 (such as the influence parameter searching program of the customer score), and calls the data stored in the memory 11, so as to execute various functions of the electronic device and process data.

[0124] The memory 11 includes at least one type of readable storage medium, such as a flash memory, a mobile hard disk, a multimedia card, a card-type memory (e.g., an SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of an electronic device, such as a mobile hard disk of the electronic device. In other embodiments, the memory 11 can 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 card, etc. Further, the memory 11 can include both an internal storage unit and an external storage device of the electronic device. The memory 11 can be used to store application software installed in the electronic device and various data, such as a code of a customer score impact parameter lookup program, etc., and can also be used to temporarily store data that has been output or will be output.

[0125] The communication bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable connection and communication between the memory 11 and the at least one processor 10, etc.

[0126] The communication interface 13 is used for communication between the electronic device and other devices, and includes a network interface and a user interface. Optionally, the network interface can include a wired interface and / or a wireless interface (e.g., a WI-FI interface, a Bluetooth interface, etc.), and is typically used to establish a communication connection between the electronic device and other electronic devices. The user interface can be a display (Display), an input unit (such as a keyboard (Keyboard)), and optionally, the user interface can also be a standard wired interface, a wireless interface. Optionally, in some embodiments, the display can be an LED display, a liquid crystal display, a touch liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, etc. The display can also be appropriately referred to as a display screen or a display unit, and is used to display information processed in the electronic device and to display a visualized user interface.

[0127] Figure 5 Only the electronic device with components is shown, and those skilled in the art can understand that, Figure 5The illustrated structure does not constitute a limitation on the electronic device 1, and can include fewer or more components than illustrated, or combine certain components, or arrange different components.

[0128] For example, although not shown, the electronic device can also include a power supply (such as a battery) for powering individual components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, so that the power management device can implement functions such as charge management, discharge management, and power consumption management. The power supply can also include one or more direct current or alternating current power supplies, recharging devices, power supply fault detection circuits, power supply converters or inverters, power supply status indicators, and any other components. The electronic device can also include various sensors, Bluetooth modules, Wi-Fi modules, and the like, which are not described here.

[0129] It should be understood that the embodiments are only for illustration and are not limited in the scope of the patent application by this structure.

[0130] The influence parameter lookup program of the customer score stored in the memory 11 in the electronic device 1 is a combination of multiple instructions, which, when executed in the processor 10, can achieve:

[0131] Obtain a customer information table of a customer to be scored in a database, and read customer field information in the customer information table;

[0132] Regularly parse the customer field information according to the hierarchy of the customer field information to obtain regular fields;

[0133] Query the superior-inferior relationship of the regular fields, and construct a tree diagram according to the superior-inferior relationship of the regular fields to obtain a regular field tree diagram;

[0134] Obtain a preset score calculation formula, and obtain input parameters of the score calculation formula according to the regular field tree diagram to obtain various score parameters;

[0135] Enter the various score parameters into the score calculation formula to obtain a customer score, and perform control variable analysis on the score parameters to find the influence parameters of the customer score.

[0136] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to the description of the related steps in the corresponding embodiments of the accompanying drawings, which is not described here.

[0137] Further, the modules / units integrated in the electronic device 1 are stored in a computer readable storage medium if they are realized in the form of software function units and sold or used as independent products. The computer readable storage medium can be volatile or non-volatile. For example, the computer readable medium can include any entity or device capable of carrying the computer program code, a recording medium, a U disk, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM).

[0138] The application further provides a computer readable storage medium, which stores a computer program, and the computer program can realize the following when executed by a processor of an electronic device:

[0139] obtaining a customer information table of a customer to be scored in a database, and reading customer field information in the customer information table;

[0140] regularly parsing the customer field information according to a level of the customer field information, to obtain regular fields;

[0141] querying a superior-inferior relationship of the regular fields, and constructing a tree diagram according to the superior-inferior relationship of the regular fields, to obtain a regular field tree diagram;

[0142] obtaining a preset scoring calculation formula, and obtaining input parameters of the scoring calculation formula according to the regular field tree diagram, to obtain each scoring parameter;

[0143] adding the each scoring parameter into the scoring calculation formula, to obtain a customer score, and performing control variable analysis on the scoring parameter, to find an influence parameter of the customer score.

[0144] In the several embodiments of the application, it should be understood that the disclosed device, apparatus and method can be implemented in other ways. For example, the device embodiments described above are only illustrative, and the division of the modules is only a logical function division. In actual implementation, another division manner can be used.

[0145] The modules described as separate components can or can not be physically separated, and the components displayed as modules can or can not be physical units, i.e., they can be located in one place, or distributed on multiple network units. According to actual needs, some or all of the modules can be selected to achieve the purpose of the embodiment.

[0146] In addition, each of the functional modules in the various embodiments of the present application can be integrated in one processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware, or in the form of a hardware plus software function module.

[0147] It is obvious for those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and the present application can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application.

[0148] Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting, and the scope of the present application is defined by the appended claims rather than the above description, and therefore all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present application. Any additional reference signs in the claims should not be considered as limiting the claims involved.

[0149] The blockchain referred to in the present application is a new application mode of computer technologies such as distributed data storage, peer-to-peer transmission, verification mechanism, and encryption algorithm. Blockchain, in essence, is a decentralized database, which is a series of data blocks associated using cryptographic methods, each of which contains information of a batch of network transactions, for verifying the validity (anti-fake) of the information and generating the next block. The blockchain can include a blockchain underlying platform, a platform product service layer, and an application service layer, etc.

[0150] The embodiments of the present application can acquire and process related data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the use of digital computers or computer-controlled machines to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0151] In addition, it is obvious that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. The plurality of units or devices stated in the system claims can also be implemented by one unit or device through software or hardware. The words first, second, etc. are used to indicate names, not any particular order.

[0152] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A method for finding parameters influencing customer ratings, characterized in that, The method comprises: obtaining a customer information table of a customer to be scored in a database, and reading customer field information in the customer information table; regularly parsing the customer field information according to a level of the customer field information to obtain regular fields; inquiring an upper and lower level relationship of the regular fields, and constructing a tree diagram according to the upper and lower level relationship of the regular fields to obtain a regular field tree diagram; obtaining a preset scoring calculation formula, and obtaining input parameters of the scoring calculation formula according to the regular field tree diagram to obtain each scoring parameter; entering the each scoring parameter into the scoring calculation formula to obtain a customer score; controlling variable analysis on the scoring parameter to find an influence parameter of the customer score, comprising: step A, obtaining an industry to which a customer in the customer information table belongs, and inquiring each standard parameter in the scoring calculation formula according to the industry to which the customer belongs, step B, collecting the each scoring parameter to obtain a scoring parameter set, step C, obtaining one scoring parameter from the scoring parameter set, and replacing the scoring parameter with a corresponding standard parameter and the remaining scoring parameters in the scoring parameter set to enter the scoring calculation formula to obtain a parameter-adjusted score, step D, calculating a score difference between the parameter-adjusted score and the customer score, and taking the scoring parameter as an influence parameter when the score difference is greater than or equal to a preset threshold, step E, judging whether each scoring parameter in the scoring parameter set has participated in replacement, if not, returning to step C, and if so, executing step F, and counting the influence parameter of the customer score.

2. The method of claim 1, wherein the impact parameter lookup table is a function of the customer score. The regularly parsing the customer field information according to the level of the customer field information to obtain regular fields comprises: obtaining a nesting relationship between the customer field information, and extracting the customer field information respectively according to the nesting relationship to obtain field data of a multi-level structure; finding a rule of the field data of the multi-level structure to obtain regular fields.

3. The customer score impact parameter lookup of claim 1, wherein, Before the entering the each scoring parameter into the scoring calculation formula to obtain the customer score, the method further comprises: judging whether all parameters of the scoring calculation formula exist in the each scoring parameter; if all parameters of the scoring calculation formula exist in the each scoring parameter, directly obtaining the customer score; if all parameters of the scoring calculation formula do not exist in the each scoring parameter, inquiring whether remaining information tables of the customer exist in the database; if the remaining information tables of the customer exist in the database, completing missing parameters of the scoring calculation formula through the remaining information tables, and calculating the customer score; if the remaining information tables of the customer do not exist in the database, taking missing parameters in the scoring calculation formula as 0 values, and calculating the customer score.

4. The method of claim 1, wherein the impact parameter lookup table is a function of the customer score. The obtaining a customer information table of a customer to be scored in a database comprises: obtaining a scoring task of scoring the customer to be scored, and inquiring a task time limit of the scoring task; query the serial number of the customer to be scored, and select a data table with the largest amount of data within the task time limit from the database according to the serial number, and take the data table as the customer information table.

5. The customer score impact parameter lookup of claim 1, wherein, The input parameters of the score calculation formula are obtained according to the regular field tree diagram, and each score parameter is obtained. The node fields of each node in the regular field tree diagram are obtained, and the node field attributes are obtained by attribute analysis of the node fields through a preset dictionary. The target data level of the score calculation formula in the regular field tree diagram is obtained according to the node field attributes. The field data of the target data level in the regular field tree diagram is obtained through a recursive function, and the field data is taken as the input parameters of the score calculation formula to obtain the each score parameter.

6. The method for finding the influencing parameters of customer rating as described in claim 1, characterized in that, After the upper and lower level relationship of the regular field is queried and the tree diagram is constructed according to the upper and lower level relationship of the regular field to obtain the regular field tree diagram, the method further comprises: Each node field in the regular field tree diagram is obtained by traversing the regular field tree diagram. The node field is converted into josn data, and the josn data is parsed into a JavaScript object. The JavaScript object is inserted into a preset HTML page and displayed on the front end.

7. A client score influence parameter search device for executing the client score influence parameter search method according to any one of claims 1 to 6, characterized by The device comprises: A customer information reading module is configured to obtain a customer information table of a customer to be scored in a database, and read customer field information in the customer information table. A tree diagram construction module is configured to perform regular analysis on the customer field information according to the level of the customer field information to obtain regular fields, query the upper and lower level relationship of the regular fields, and construct a tree diagram according to the upper and lower level relationship of the regular fields to obtain a regular field tree diagram. A score parameter acquisition module is configured to obtain a preset score calculation formula, and obtain input parameters of the score calculation formula according to the regular field tree diagram to obtain each score parameter. An influence parameter finding module is configured to input the each score parameter into the score calculation formula to obtain a customer score, and perform control variable analysis on the score parameter to find an influence parameter of the customer score.

8. An electronic device, comprising: The electronic device comprises: at least one processor; and a memory connected to the at least one processor in communication; wherein The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the customer score influence parameter finding method of any one of claims 1 to 6.

9. A computer readable storage medium storing a computer program, characterized in that, The computer program is executed by the processor to implement the customer score influence parameter finding method of any one of claims 1 to 6.

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