User electricity arrearage risk assessment method, device and equipment and storage medium

Abstract

The invention discloses a user electricity arrearage risk assessment method and device, equipment and a storage medium. Obtaining an area type of an area to which a target user belongs, a user type of the target user, a current arrearage length of the target user and an event problem element of the target user, and determining an object attribute risk coefficient of the target user based on the area type of the area to which the target user belongs and the user type of the target user, determining an arrearage length risk coefficient from an arrearage length and arrearage length risk coefficient relation table based on the current arrearage length of the target user, and determining an event problem element risk coefficient from an event problem element and event problem element risk coefficient relation table based on the event problem element, the arrearage risk value of the target user is calculated based on the object attribute risk coefficient, the arrearage long risk coefficient and the event problem element risk coefficient, errors caused by risk research and judgment depending on manual working experience are solved, and the risk assessment accuracy is improved.

Description

Technical Field

[0001] The present invention relates to power grid technology, and in particular to a method, device, equipment and storage medium for assessing the risk of user electricity arrears. Background Art

[0002] The risk prevention and control of user arrears plays a very important role in improving the electricity bill recovery rate. As the types of electricity users become more and more complex, the account managers' assessment of user types and arrears risks is based solely on work experience, lacking scientific algorithms and data support, and having no reference standards for solutions and strategies to prevent risks, which can lead to delayed and inappropriate risk handling, or even missing the best time to handle the risks. Summary of the invention

[0003] The present invention provides a method, device, equipment and storage medium for assessing the risk of user electricity arrears, so as to improve the accuracy of risk assessment.

[0004] In a first aspect, the present invention provides a method for assessing the risk of a user's electricity arrears, comprising:

[0005] Obtaining the area type of the area to which the target user belongs, the user type of the target user, the current arrears duration of the target user, and the event problem element of the target user, wherein the event problem element is used to characterize whether the target user currently has electricity and whether the user can be contacted;

[0006] Determining an object attribute risk coefficient of the target user based on the area type of the area to which the target user belongs and the user type of the target user;

[0007] Determine the arrears duration risk coefficient from the arrears duration and arrears duration risk coefficient relationship table based on the current arrears duration of the target user;

[0008] Determine the event problem element risk coefficient from the event problem element and the event problem element risk coefficient relationship table based on the event problem element;

[0009] The arrears risk value of the target user is calculated based on the object attribute risk coefficient, the arrears duration risk coefficient and the event problem element risk coefficient.

[0010] Optionally, determining the object attribute risk coefficient of the target user based on the area type of the area to which the target user belongs and the user type of the target user includes:

[0011] The object attribute risk coefficient of the target user is searched from a relationship table of object attribute risk coefficients with respect to area types and user types based on the area type of the area to which the target user belongs and the user type of the target user.

[0012] Optionally, a calculation formula for calculating the target user's arrears risk value based on the object attribute risk coefficient, the arrears duration risk coefficient, and the event problem element risk coefficient is as follows:

[0013] R=β T ×β Z ×β S

[0014] Among them, R is the default risk value of the target user, β T is the risk coefficient of the duration of arrears, β Z is the object attribute risk coefficient, β S is the risk factor of the event problem factor.

[0015] Optionally, the arrears duration risk coefficient is positively correlated with the user's current arrears duration.

[0016] Optionally, after calculating the arrears risk value of the target user based on the object attribute risk coefficient, the arrears duration risk coefficient and the event problem element risk coefficient, the method further includes:

[0017] Determining the risk level based on the arrears risk value;

[0018] Determine risk response measures based on the risk level described.

[0019] Optionally, determining the risk level based on the arrears risk value includes:

[0020] Determining whether the arrears risk value is greater than or equal to a first preset value;

[0021] If yes, determining the risk level to be the first risk level;

[0022] If not, determining whether the arrears risk value is greater than or equal to a second preset value;

[0023] If yes, determining that the risk level is the second risk level;

[0024] If not, it is determined that the risk level is a third risk level, wherein the first preset value is greater than the second preset value.

[0025] Optionally, risk response measures are determined according to the risk level, including:

[0026] If the risk level is the first risk level, determining the risk response measure to be power outage collection;

[0027] If the risk level is the second risk level, determining the risk response measure to be door-to-door collection;

[0028] If the risk level is the third risk level, the risk response measure is determined to be telephone collection.

[0029] In a second aspect, the present invention further provides a user electricity arrears risk assessment device, comprising:

[0030] An information acquisition module, used to acquire the area type of the area to which the target user belongs, the user type of the target user, the current arrears duration of the target user, and the event problem element of the target user, wherein the event problem element is used to characterize whether the target user currently has electricity and whether the user can be contacted;

[0031] An object attribute risk coefficient determination module, configured to determine the object attribute risk coefficient of the target user based on the area type of the area to which the target user belongs and the user type of the target user;

[0032] A module for determining a risk coefficient of arrears duration, for determining a risk coefficient of arrears duration from a relationship table of arrears duration and arrears duration risk coefficient based on the current arrears duration of the target user;

[0033] An event problem element risk coefficient determination module, used to determine the event problem element risk coefficient from a table of event problem element and event problem element risk coefficient relationships based on the event problem element;

[0034] The arrears risk value calculation module is used to calculate the arrears risk value of the target user based on the object attribute risk coefficient, the arrears duration risk coefficient and the event problem element risk coefficient.

[0035] In a third aspect, the present invention further provides an electronic device, comprising:

[0036] one or more processors;

[0037] A storage device for storing one or more programs;

[0038] When the one or more programs are executed by the one or more processors, the one or more processors implement the user electricity arrears risk assessment method as provided in the first aspect of the present invention.

[0039] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the user electricity arrears risk assessment method provided in the first aspect of the present invention.

[0040] The method for assessing the risk of arrears in electricity consumption provided by the present invention comprises: obtaining the area type of the area to which the target user belongs, the user type of the target user, the current arrears duration of the target user and the event problem element of the target user, wherein the event problem element is used to characterize whether the target user currently uses electricity and whether the user can be contacted; determining the object attribute risk coefficient of the target user based on the area type of the area to which the target user belongs and the user type of the target user; determining the arrears duration risk coefficient from a table of relationships between arrears duration and arrears duration risk coefficients based on the current arrears duration of the target user; determining the event problem element risk coefficient from a table of relationships between event problem elements and event problem element risk coefficients based on the event problem element; and calculating the arrears risk value of the target user based on the object attribute risk coefficient, the arrears duration risk coefficient and the event problem element risk coefficient, thereby solving the errors caused by relying on manual work experience for risk assessment and improving the accuracy of risk assessment.

[0041] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0043] Figure 1 A flow chart of a method for assessing the risk of electricity arrears provided by the present invention;

[0044] Figure 2 A schematic diagram of the structure of a device for assessing the risk of electricity arrears provided by the present invention;

[0045] Figure 3 The present invention provides a schematic structural diagram of an electronic device.

[0046] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0047] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0048] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0049] Figure 1 This is a flow chart of a method for assessing the risk of electricity arrears provided by the present invention. This embodiment can be used to assess the risk of electricity arrears of power grid users. The method can be performed by a device for assessing the risk of electricity arrears provided by the present invention. The device can be implemented in software and / or hardware and is usually configured in an electronic device, such as Figure 1 As shown, the method for assessing the risk of user electricity arrears includes the following steps:

[0050] S101. Obtain the area type of the area to which the target user belongs, the user type of the target user, the current arrears duration of the target user, and event problem elements of the target user.

[0051] In an embodiment of the present invention, when it is necessary to conduct an arrears risk assessment on a target user, the area type of the target user's area, the target user's user type, the target user's current arrears duration, and the target user's event problem elements are obtained through the target user's previous registration information and historical electricity usage data in the power grid.

[0052] In the embodiment of the present invention, the area type of the area to which the user belongs includes self-built houses, co-built houses, residential areas, commercial entities, industrial parks, government agencies, etc., which are not described in detail in the embodiment of the present invention. User types include residential users, non-residential users, commercial users, ordinary industrial users, large industrial users, etc., which are not described in detail in the embodiment of the present invention. The event problem element is used to characterize whether the target user currently has electricity and whether the user can be contacted, including: the user currently has electricity and can be contacted by phone, the user currently has electricity, but cannot be contacted by phone, the user currently has electricity and can be found at home, the user currently has electricity, but cannot be found at home, the user currently has no electricity, but can be contacted by phone, the user currently has no electricity, and cannot be contacted by phone, the user currently has no electricity, but can be found at home, the user currently has no electricity, but can be contacted by phone, the user currently has no electricity, and cannot be contacted by phone, the user currently has no electricity, but can be found at home, the user currently has no electricity, and cannot be found at home, etc. The embodiment of the present invention will not be described in detail here.

[0053] S102: Determine an object attribute risk coefficient of the target user based on the region type of the region to which the target user belongs and the user type of the target user.

[0054] In an embodiment of the present invention, a mapping relationship between the object attribute risk coefficient and the area type and the user type is pre-established based on the user's arrears history, the area type of the area to which the user belongs, and the user type. After obtaining the area type of the area to which the target user belongs and the user type of the target user, the object attribute risk coefficient is determined based on the above mapping relationship. Exemplarily, in a specific embodiment of the present invention, the object attribute risk coefficient of the target user is searched from a relationship table of the object attribute risk coefficient and the area type and the user type based on the area type of the area to which the target user belongs and the user type of the target user. Exemplarily, the mapping relationship table of the object attribute risk coefficient and the area type and the user type is shown in Table 1, and the value range of the object attribute risk coefficient is 1≤β Z ≤10, β Z is an integer, β Z The larger the number, the greater the risk.

[0055] Table 1

[0056]

[0057] S103: Determine the arrears duration risk coefficient from the arrears duration and arrears duration risk coefficient relationship table based on the current arrears duration of the target user.

[0058] In the embodiment of the present invention, a mapping relationship table of the arrears duration risk coefficient and the arrears duration is constructed in advance according to the user's arrears history and the arrears duration. After obtaining the current arrears duration of the target user, the arrears duration risk coefficient is determined from the arrears duration and arrears duration risk coefficient relationship table based on the current arrears duration of the target user.

[0059] In some embodiments of the present invention, the arrears duration risk coefficient is positively correlated with the current arrears duration of the user. For example, the mapping relationship table of the arrears duration risk coefficient and the arrears duration is shown in Table 2:

[0060] Table 2

[0061] Time T many months February Current month Risk factor of arrears duration 4 2 1

[0062] S104. Determine the event problem element risk coefficient from the event problem element and the event problem element risk coefficient relationship table based on the event problem element.

[0063] In an embodiment of the present invention, a mapping relationship table of event problem element risk coefficients on event problem elements is constructed in advance based on the user's arrears history and event problem elements. After the event problem elements of the target user are acquired, the event problem element risk coefficient is determined from the event problem element and event problem element risk coefficient relationship table based on the event problem element. Exemplarily, the mapping relationship table of event problem element risk coefficients on event problem elements is shown in Table 3.

[0064] Risk factor of event problem elements Event Problem Element S 1 If you need electricity, you can contact the user by phone. 2 There is electricity demand but the user cannot be contacted by phone. 3 If there is electricity demand, we can go to the customer's door to find the electricity user. 4 No electricity consumption, can contact the electricity user by phone 5 No electricity, unable to contact electricity users by phone

[0065] 6 No electricity consumption, we can find electricity users at their doorsteps 10 There is no electricity and no electricity users can be found at their doorsteps …… ……

[0066] S105. Calculate the target user's arrears risk value based on the object attribute risk coefficient, the arrears duration risk coefficient, and the event problem factor risk coefficient.

[0067] In the embodiment of the present invention, the arrears risk value of the target user is calculated based on the above-mentioned target user's object attribute risk coefficient, arrears duration risk coefficient and event problem element risk coefficient. Exemplarily, the calculation formula of the arrears risk value is as follows:

[0068] R=β T ×β Z ×β S

[0069] Among them, R is the default risk value of the target user, β T is the risk coefficient of the duration of arrears, β Z is the object attribute risk coefficient, β S is the risk factor of the event problem factor.

[0070] The method for assessing the risk of arrears in electricity consumption provided by the present invention comprises: obtaining the area type of the area to which the target user belongs, the user type of the target user, the current arrears duration of the target user and the event problem element of the target user, wherein the event problem element is used to characterize whether the target user currently uses electricity and whether the user can be contacted; determining the object attribute risk coefficient of the target user based on the area type of the area to which the target user belongs and the user type of the target user; determining the arrears duration risk coefficient from a table of relationships between arrears duration and arrears duration risk coefficients based on the current arrears duration of the target user; determining the event problem element risk coefficient from a table of relationships between event problem elements and event problem element risk coefficients based on the event problem element; and calculating the arrears risk value of the target user based on the object attribute risk coefficient, the arrears duration risk coefficient and the event problem element risk coefficient, thereby solving the errors caused by relying on manual work experience for risk assessment and improving the accuracy of risk assessment.

[0071] In some embodiments of the present invention, after calculating the arrears risk value of the target user based on the object attribute risk coefficient, the arrears duration risk coefficient and the event problem element risk coefficient, the method further includes:

[0072] 1. Determine the risk level based on the arrears risk value.

[0073] In some embodiments of the present invention, the risk level is determined based on the default risk value.

[0074] Exemplarily, determining whether the arrears risk value is greater than or equal to a first preset value (80);

[0075] If yes, the risk level is determined to be the first risk level (significant risk);

[0076] If not, determining whether the arrears risk value is greater than or equal to a second preset value (40);

[0077] If yes, the risk level is determined to be the second risk level (higher risk);

[0078] If not, the risk level is determined to be the third risk level (general risk), wherein the first preset value is greater than the second preset value.

[0079] 2. Determine risk response measures based on risk levels.

[0080] After determining the risk level, the risk response measures are determined according to the risk level. For example, if the risk level is the first risk level, the risk response measures are determined to be power outage collection, that is, power outage for the target user and door-to-door collection; if the risk level is the second risk level, the risk response measures are determined to be door-to-door collection; if the risk level is the third risk level, the risk response measures are determined to be telephone collection.

[0081] Figure 2 A schematic diagram of a device for assessing the risk of electricity arrears provided by the present invention is shown in FIG. Figure 2 As shown, the user electricity arrears risk assessment device includes:

[0082] The information acquisition module 201 is used to acquire the area type of the area to which the target user belongs, the user type of the target user, the current arrears duration of the target user, and the event problem element of the target user, wherein the event problem element is used to indicate whether the target user currently uses electricity and whether the user can be contacted;

[0083] An object attribute risk coefficient determination module 202, configured to determine the object attribute risk coefficient of the target user based on the area type of the area to which the target user belongs and the user type of the target user;

[0084] The arrears duration risk coefficient determination module 203 is used to determine the arrears duration risk coefficient from the arrears duration and arrears duration risk coefficient relationship table based on the current arrears duration of the target user;

[0085] An event problem element risk coefficient determination module 204 is used to determine the event problem element risk coefficient from a table of event problem element and event problem element risk coefficient relationships based on the event problem element;

[0086] The arrears risk value calculation module 205 is used to calculate the arrears risk value of the target user based on the object attribute risk coefficient, the arrears duration risk coefficient and the event problem element risk coefficient.

[0087] In some embodiments of the present invention, the object attribute risk coefficient determination module 202 includes:

[0088] The object attribute risk coefficient determination submodule is used to find the object attribute risk coefficient of the target user from the relationship table of object attribute risk coefficients on area type and user type based on the area type of the area to which the target user belongs and the user type of the target user.

[0089] In some embodiments of the present invention, the calculation formula for calculating the arrears risk value of the target user based on the object attribute risk coefficient, the arrears duration risk coefficient and the event problem element risk coefficient is as follows:

[0090] R=β T ×β Z ×β S

[0091] Among them, R is the default risk value of the target user, β T is the risk coefficient of the duration of arrears, β Z is the object attribute risk coefficient, β Sis the risk factor of the event problem factor.

[0092] In some embodiments of the present invention, the arrears duration risk coefficient is positively correlated with the user's current arrears duration.

[0093] In some embodiments of the present invention, the user electricity arrears risk assessment device further includes:

[0094] A risk level determination module, configured to determine the risk level based on the arrears risk value after calculating the arrears risk value of the target user based on the object attribute risk coefficient, the arrears duration risk coefficient and the event problem element risk coefficient;

[0095] The response measure determination module is used to determine the risk response measures according to the risk level.

[0096] In some embodiments of the present invention, the risk level determination module includes:

[0097] A first judgment submodule is used to judge whether the arrears risk value is greater than or equal to a first preset value;

[0098] A first determination submodule, configured to determine that if yes, the risk level is a first risk level;

[0099] A second judgment submodule is used to judge whether the arrears risk value is greater than or equal to a second preset value if no;

[0100] A second determination submodule, configured to, if yes, determine that the risk level is a second risk level;

[0101] The third determination submodule is configured to determine that the risk level is a third risk level if no, wherein the first preset value is greater than the second preset value.

[0102] In some embodiments of the present invention, the countermeasure determination module includes:

[0103] A first measure determination submodule, configured to determine that the risk response measure is power outage collection if the risk level is the first risk level;

[0104] A second measure determination submodule, for determining that the risk response measure is door-to-door collection if the risk level is the second risk level;

[0105] The third measure determination submodule is used to determine that the risk response measure is telephone collection if the risk level is the third risk level.

[0106] The above-mentioned user electricity arrears risk assessment device can execute the user electricity arrears risk assessment method provided by the aforementioned embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the user electricity arrears risk assessment method.

[0107] Figure 3 A schematic diagram of the structure of an electronic device provided by the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0108] like Figure 3 As shown, the electronic device includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0109] A number of components in the electronic device are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0110] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a method for assessing the risk of arrears in electricity consumption by a user.

[0111] In some embodiments, the method for assessing the risk of arrears in electricity bills for a user may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for assessing the risk of arrears in electricity bills for a user described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the method for assessing the risk of arrears in electricity bills for a user in any other appropriate manner (e.g., by means of firmware).

[0112] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0113] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0114] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0115] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0116] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0117] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0118] An embodiment of the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the user electricity arrears risk assessment method provided in any embodiment of the present application.

[0119] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0120] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0121] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for assessing the risk of arrears in electricity bills for users, characterized in that: include: Obtaining the area type of the area to which the target user belongs, the user type of the target user, the current arrears duration of the target user, and the event problem element of the target user, wherein the event problem element is used to characterize whether the target user currently has electricity and whether the user can be contacted; Determining an object attribute risk coefficient of the target user based on the area type of the area to which the target user belongs and the user type of the target user; Determine the arrears duration risk coefficient from the arrears duration and arrears duration risk coefficient relationship table based on the current arrears duration of the target user; Determine the event problem element risk coefficient from the event problem element and the event problem element risk coefficient relationship table based on the event problem element; The arrears risk value of the target user is calculated based on the object attribute risk coefficient, the arrears duration risk coefficient and the event problem element risk coefficient.

2. The method for assessing the risk of user electricity arrears according to claim 1, characterized in that: Determining the object attribute risk coefficient of the target user based on the area type of the area to which the target user belongs and the user type of the target user includes: The object attribute risk coefficient of the target user is searched from a relationship table of object attribute risk coefficients with respect to area types and user types based on the area type of the area to which the target user belongs and the user type of the target user.

3. The method for assessing the risk of user electricity arrears according to claim 1, characterized in that: The calculation formula for calculating the arrears risk value of the target user based on the object attribute risk coefficient, the arrears duration risk coefficient and the event problem element risk coefficient is as follows: R＝β T ×β Z ×β S Among them, R is the default risk value of the target user, β T is the risk coefficient of the duration of arrears, β Z is the object attribute risk coefficient, β S is the risk factor of the event problem factor.

4. The method for assessing the risk of user electricity arrears according to claim 1, characterized in that: The arrears duration risk coefficient is positively correlated with the user's current arrears duration.

5. The method for assessing the risk of user electricity arrears according to claim 1, characterized in that: After calculating the arrears risk value of the target user based on the object attribute risk coefficient, the arrears duration risk coefficient and the event problem element risk coefficient, the method further includes: Determining the risk level based on the arrears risk value; Determine risk response measures based on the risk level described.

6. The method for assessing the risk of user electricity arrears according to claim 5, characterized in that: Determining the risk level based on the arrears risk value includes: Determining whether the arrears risk value is greater than or equal to a first preset value; If yes, determining the risk level to be the first risk level; If not, determining whether the arrears risk value is greater than or equal to a second preset value; If yes, determining that the risk level is the second risk level; If not, it is determined that the risk level is a third risk level, wherein the first preset value is greater than the second preset value.

7. The method for assessing the risk of user electricity arrears according to claim 6, characterized in that: Determine risk response measures based on the risk level, including: If the risk level is the first risk level, determining the risk response measure to be power outage collection; If the risk level is the second risk level, determining the risk response measure to be door-to-door collection; If the risk level is the third risk level, the risk response measure is determined to be telephone collection.

8. A device for assessing the risk of arrears in electricity bills for users, characterized in that: include: An information acquisition module, used to acquire the area type of the area to which the target user belongs, the user type of the target user, the current arrears duration of the target user, and the event problem element of the target user, wherein the event problem element is used to characterize whether the target user currently has electricity and whether the user can be contacted; An object attribute risk coefficient determination module, configured to determine the object attribute risk coefficient of the target user based on the area type of the area to which the target user belongs and the user type of the target user; A module for determining a risk coefficient of arrears duration, for determining a risk coefficient of arrears duration from a relationship table of arrears duration and arrears duration risk coefficient based on the current arrears duration of the target user; An event problem element risk coefficient determination module, used to determine the event problem element risk coefficient from a table of event problem element and event problem element risk coefficient relationships based on the event problem element; The arrears risk value calculation module is used to calculate the arrears risk value of the target user based on the object attribute risk coefficient, the arrears duration risk coefficient and the event problem element risk coefficient.

9. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the user electricity arrears risk assessment method as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for assessing the risk of electricity arrears of a user as described in any one of claims 1 to 7 is implemented.

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