CN112991049A - Loan information processing method and electronic device - Google Patents
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Abstract
The embodiment of the application provides a loan information processing method and electronic equipment. The method comprises the following steps: the loan information of the user with overdue behaviors is input into a complaint probability information prediction model to obtain complaint probability information of the user, whether the user is a high complaint risk user is determined based on the complaint probability information, a target collection urging strategy is obtained when the user is the high complaint risk user, the target collection urging strategy is used for indicating at least one of frequency, mode and telephone art of collection urging the user, corresponding operation is executed according to the target collection urging strategy, and the user experience is improved while the refund rate is guaranteed.
Description
Technical Field
The embodiment of the application relates to the technical field of artificial intelligence, in particular to a loan information processing method and an electronic device.
Background
At present, the user is often urged to receive to realize the withdrawal after the loan is overdue through Artificial Intelligence (AI), however, because the user is different in the receiving degree of the urging, the non-differentiated urging mode will reduce the user experience and bring more user complaints, so how to reduce the user complaints and realize the effective urging is a problem to be solved urgently at present.
Disclosure of Invention
The embodiment of the application provides a loan information processing method and electronic equipment, which can carry out differentiated collection urging according to the acceptance degree of different users to the collection urging so as to improve the user experience.
In a first aspect, a method for processing loan information is provided, including:
inputting loan information of a user with overdue behaviors into a complaint probability information prediction model to obtain complaint probability information of the user; determining whether the user is a high complaint risk user based on the complaint probability information; when the user is a high complaint risk user, acquiring a target collection urging strategy, wherein the target collection urging strategy is used for indicating at least one of frequency, mode and dialect for urging collection of the user; and executing corresponding operation according to the target collection strategy.
In a second aspect, an electronic device is provided, comprising:
the processing unit is used for inputting loan information of the user with overdue behavior into the complaint probability information prediction model to obtain complaint probability information of the user; the processing unit is further used for determining whether the user is a high complaint risk user or not based on the complaint probability information; the system comprises an acquisition unit, a display unit and a management unit, wherein the acquisition unit is used for acquiring a target collection urging strategy when the user is a high complaint risk user, and the target collection urging strategy is used for indicating at least one of frequency, mode and dialect for urging the user to collect; the processing unit is further configured to execute a corresponding operation according to the target collection policy.
In a third aspect, an electronic device is provided, including: a processor and a memory, the memory being configured to store a computer program, the processor being configured to invoke and execute the computer program stored in the memory to perform a method as in the first aspect or its implementations.
In a fourth aspect, there is provided a computer readable storage medium for storing a computer program for causing a computer to perform the method as in the first aspect or its implementations.
In a fifth aspect, there is provided a computer program product comprising computer program instructions to cause a computer to perform the method as in the first aspect or its implementations.
A sixth aspect provides a computer program for causing a computer to perform a method as in the first aspect or implementations thereof.
According to the method and the device, the complaint risk of the user can be identified according to the loan information of the user who asks for the complaint, the user with high complaint risk adopts a target asking for collection strategy to carry out customized asking for collection, the money return rate is guaranteed, the user experience is improved, and the complaint of the user is reduced.
Drawings
Fig. 1 is a schematic diagram illustrating an application scenario 100 of loan information processing according to an embodiment of the present disclosure;
fig. 2 is a flowchart illustrating a method 200 for processing loan information according to an embodiment of the disclosure;
fig. 3 is a schematic block diagram of an electronic device 300 provided in an embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device 400 according to an embodiment of the present application.
Detailed Description
Technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments obtained by a person of ordinary skill in the art without making any creative effort with respect to the embodiments in the present application belong to the protection scope of the present application.
For the sake of understanding, technical terms mentioned in the embodiments of the present application will be first explained:
overdue stage M1: the payment is not paid, and the overdue days are 1-31 days, namely within one month.
Urging a user: the user is required to be charged due to overdue behavior.
With the continuous progress of the intelligent robot, the intelligent collection robot can be gradually used for replacing manpower in the collection process, so that the labor is saved. However, the same collection method and collection intensity are adopted for collecting different users, which results in poor experience of some users, and thus the complaint rate of users is continuously increased, and the complaints of users need to be solved with a large investment.
Based on the problems, the application provides a differentiated urging scheme, which can identify the complaint risk of the user according to the loan information of the urging user, and urge the user with high complaint risk to adopt a target urging strategy, for example, to reduce the urging strength, and to adopt a milder urging word technique, etc., so as to improve the user experience and reduce the complaint of the user.
It should be noted that the loan information in the present application may include any user characteristics related to the loan transaction, and may include at least one of the following: the user's history loan record, history collection record, history customer service communication record, history behavior record, etc.
The main implementation body of the present application is an electronic device, and it should be understood that the electronic device may be a terminal device, such as a Mobile Phone (Mobile Phone), a tablet computer (Pad), a computer, and so on. In some embodiments, the electronic device may also be a server.
Fig. 1 is a schematic diagram of an application scenario 100 of loan information processing according to an embodiment of the present disclosure. As shown in fig. 1, the electronic device 110 for processing loan information is connected to the plurality of user terminals 120 by wire or wireless, the electronic device 110 is connected to the service terminal 130 by wire or wireless, and the service terminal 130 is connected to the plurality of user terminals 120 by wire or wireless.
Wherein, each user terminal 120 logs in an account number of the user to be prompted; the service terminal 130 registers an account number of a requester who pays for a loan. Optionally, the number of the service terminals 130 is one to more.
Alternatively, the service terminal 130 may be integrated with the electronic device 110.
Based on the application scenario, in this embodiment, the electronic device 110 may perform an operation of hastening the receipt on the at least one user terminal 120 according to the target hastening the receipt policy, and in some embodiments, the electronic device 110 may notify the service terminal 130, so that the service terminal 130 performs an operation of hastening the receipt on the at least one user terminal 120 according to the determined hastening the receipt policy.
The technical solution of the present application is described in detail by specific examples below.
Fig. 2 is a flowchart illustrating a method 200 for processing loan information according to an embodiment of the disclosure. As shown in fig. 2, an execution subject of the embodiment of the present application may be the electronic device 110, and the method specifically includes:
s201: inputting loan information of a user with overdue behaviors into a complaint probability information prediction model to obtain complaint probability information of the user;
s202: determining whether the user is a high complaint risk user based on the complaint probability information;
s203: when the user is a high complaint risk user, acquiring a target collection urging strategy, wherein the target collection urging strategy is used for indicating at least one of frequency, mode and dialect for urging collection of the user;
s204: and executing corresponding operation according to the target collection strategy.
The embodiment of the present application may be applied to loan collection for overdue users in any overdue period, for example, the overdue period M1.
Illustratively, the complaint probability information identified by the complaint probability information prediction model can be the complaint probability, or can be the complaint probability score, for example, the score can be 1-99, and the higher the score, the higher the complaint probability.
The target collection urging strategy is a collection urging strategy predetermined by a user with high complaint risk, and the target collection urging strategy aims at remarkably reducing the complaint rate and has small influence on the rate of refund. The complaints in the general urging process mainly include complaint urging attitude, urging mode, and the like. For people with high complaint risk, a more moderate hastening attitude and a proper hastening mode are needed. The target collection policy may include: the call collection strategy comprises at least one of a frequency of call collection, a call collection mode and a call collection skill template, wherein the frequency of call collection of a target call collection strategy is smaller than the frequency of call collection of a general call collection strategy, the call collection mode can be a contact mode without dialing an emergency contact and/or a third party, the call collection skill template can be a call collection and service technology, and optionally the call collection strategy can further comprise attitude prompt information which is used for prompting the adoption of a mild call collection attitude. The specific strategy can be formulated and adjusted according to the specific form of the product and the historical complaint information in the collection process.
In some embodiments, the electronic device may send a call request to the user terminal according to the target collection policy, so that the demander who collects the loan according to the collection call in the target collection policy; or, the electronic device may send an induced receipt message to the user terminal according to the target induced receipt policy, and optionally, the induced receipt message may be generated based on an induced receipt in the target induced receipt policy.
In other embodiments, the electronic device may send the target collection policy to the service terminal, so that the service terminal sends the call request and/or the collection message to the user terminal according to the target collection policy.
It should be noted that the call request and the message for collection are both used to prompt the user to perform a payment operation.
In some embodiments, the electronic device may determine a complaint probability information grade to which the complaint probability information belongs, and determine that the user is a high complaint risk user when a complaint rate corresponding to the complaint probability information grade is greater than a preset value.
The complaint rate is the proportion of the number of users with complaint behaviors in the complaint probability information grading to the total number of users.
In some embodiments, a plurality of complaint probability information grades may be determined based on the user sample set and a complaint risk grade corresponding to each complaint probability grade is determined, the complaint risk grades including a high risk and a low risk, or a plurality of complaint probability information grades may be determined based on the user sample set and a preset value may be determined based on the complaint rate of each complaint probability information grade and the complaint rate corresponding to the user sample set, a complaint probability grade greater than the preset value corresponding to a high risk, and a complaint probability grade less than the preset value corresponding to a low risk.
The user sample set described above is the third sample set in the embodiment of the present application.
Illustratively, the complaint probability information grade to which the complaint probability information belongs is determined, and when the complaint rate corresponding to the complaint probability information grade is greater than a preset value, the user is determined to be a high-complaint risk user, wherein the complaint rate is the proportion of the number of users with complaint behaviors in the complaint probability information grade to the total number of users.
For example, in this embodiment, the complaint probability information corresponding to each sample in the third sample set may be determined, a plurality of complaint probability information grades are obtained by dividing based on the complaint probability information corresponding to each sample in the third sample set, a complaint rate corresponding to each complaint probability information grade is obtained, and the preset value is determined based on the complaint rate corresponding to each complaint probability information grade and the complaint rate corresponding to the third sample set.
Optionally, each complaint probability grade may correspond to one or more complaint probability information, for example, the complaint probability information is a grade with a complaint probability grade of 1 and the corresponding complaint probability grade is a grade with a grade of 1, and for example, the complaint probability information is a grade with a complaint probability grade of 0.5% to 1.5% and the corresponding complaint probability grade is a grade with a grade of 1.
Illustratively, as shown in table 1, the complaint probability ratings include 1 to 99 ratings, wherein the complaint rates corresponding to 1 to 85 ratings are all less than 1%, not shown in the table. Illustratively, complaint probability ratings 93-99 correspond to high risk, and complaint probability ratings 92 and below correspond to low risk. For example, the complaint rate corresponding to the complaint probability grade with the ratio of the complaint rate to the complaint rate corresponding to the third sample set being greater than 5 may be determined as a preset value, that is, the complaint probability grade 93, i.e., the complaint probability grade above, corresponds to a high risk.
In some embodiments, for a user corresponding to each test sample in a test set, a call request and/or a collection urging message is sent to a terminal of the user according to a preset initial collection urging strategy to obtain a complaint rate and a collection rate corresponding to the test set, and the initial collection urging strategy is adjusted based on the complaint rate and the collection rate corresponding to the test set, and a predetermined complaint rate threshold and a collection rate threshold to obtain a target collection urging strategy.
Note that the complaint rate threshold and the refund rate threshold are determined based on the control group. For example, the comparison set is urged to be collected according to a general urging strategy, for example, any conventional urging method is adopted to obtain urging results, the complaint rate in the urging results is used as a complaint rate threshold, and the refund rate in the urging results is used as a refund rate threshold.
In some embodiments, the first sample set is input into the complaint probability information prediction model to obtain a second sample set, complaint rates of complaint probability grades corresponding to the complaint probability information of the samples in the second sample set are all larger than the preset value, and the second sample set is divided into a test set and a comparison set according to a preset proportion.
Illustratively, the first sample set includes a plurality of filtered user samples, such as M1 overdue users who selected the most recent 2 months of history that experienced a 1 month inducement of a full performance period. Each user sample carries a complaint parameter, e.g., the user has a complaint of 1 and no complaint of 0 within 1 month after M1 is overdue.
Alternatively, the complaint probability prediction model may be a machine learning model, such as the integrated learning algorithm xgboost.
Exemplary, test set: the control set may be 2: 8 or 5: and 5, ensuring that the number of people in the test set reaches an evaluable number (more than one hundred grades). And (4) carrying out collection urging on the test set by using a target collection urging strategy, and carrying out no other intervention on the control set. The complaint rate and the refund rate of the test set and the control set are continuously observed. The complaint rate and the refund rate are combined to adjust the collection strategy, as shown in table 2. The desired goal is finally achieved by continuous optimization: the complaint rate is obviously reduced, and the money withdrawal rate is unchanged or improved.
Therefore, the method and the device for prompting the user to pay the credit can identify the complaint risk of the user according to the loan information of the user who is prompted, and carry out customized submission on the user with high complaint risk by adopting a target submission prompting strategy, so that the user experience is improved and the complaint of the user is reduced while the cash withdrawal rate is ensured.
While method embodiments of the present application are described in detail above with reference to fig. 2, apparatus embodiments of the present application are described in detail below with reference to fig. 3-4, it being understood that apparatus embodiments correspond to method embodiments and that similar descriptions may refer to method embodiments.
Fig. 3 is a schematic block diagram of an electronic device 300 according to an embodiment of the present application. As shown in fig. 3, the electronic device 300 includes:
the processing unit 310 is used for inputting loan information of a user with overdue behavior into the complaint probability information prediction model to obtain complaint probability information of the user;
the processing unit 310 is further configured to determine whether the user is a high complaint risk user based on the complaint probability information;
an obtaining unit 320, configured to obtain a target collection urging strategy when the user is a user with a high complaint risk, where the target collection urging strategy is used to indicate at least one of a frequency, a mode, and a talk skill of urging collection for the user;
the processing unit 310 is further configured to execute a corresponding operation according to the target charging policy.
In some embodiments, the processing unit is specifically configured to:
determining the grade of the complaint probability information to which the complaint probability information belongs;
and when the complaint rate corresponding to the complaint probability information grading is larger than a preset value, determining that the user is a high-complaint risk user, wherein the complaint rate is the proportion of the number of the users with complaint behaviors in the complaint probability information grading to the total number of the users.
In some embodiments, the processing unit 310 is further configured to:
aiming at a user corresponding to each test sample in the test set, sending a call request and/or a call receiving message to a terminal of the user according to a preset initial receiving strategy to obtain a complaint rate and a refund rate corresponding to the test set;
adjusting the initial collection urging strategy based on the complaint rate and the refund rate corresponding to the test set and a predetermined complaint rate threshold and a predetermined refund rate threshold to obtain the target collection urging strategy;
wherein the complaint rate threshold and the refund rate threshold are determined based on a control set.
In some embodiments, the processing unit 310 is specifically configured to:
inputting the first sample set into the complaint probability information prediction model to obtain a second sample set, wherein the complaint rates of complaint probability grades corresponding to the complaint probability information of the samples in the second sample set are all larger than the preset value;
and dividing the second sample set into a test set and a control set according to a preset proportion.
In some embodiments, the processing unit 310 is further configured to:
determining complaint probability information corresponding to each sample in the third sample set;
dividing to obtain a plurality of complaint probability information grades based on the complaint probability information corresponding to each sample in the third sample set, and obtaining the complaint rate corresponding to each complaint probability information grade;
and determining the preset value based on the complaint rate corresponding to each complaint probability information grade and the complaint rate corresponding to the third sample set.
In some embodiments, the processing unit 310 is specifically configured to:
sending a call request and/or a collection urging message to the user terminal according to the target collection urging strategy; or the like, or, alternatively,
sending the target collection strategy to a service terminal, and enabling the service terminal to send a call request and/or a collection message to a user terminal according to the target collection strategy;
wherein, the calling request and the message are both used to prompt the user to pay.
The electronic device provided by the above embodiment may execute the technical solution of the above method embodiment, and the implementation principle and the technical effect are similar, which are not described herein again.
Fig. 4 is a schematic structural diagram of an electronic device 400 according to an embodiment of the present application. The electronic device 400 shown in fig. 4 includes a processor 410, and the processor 410 can call and run a computer program from a memory to implement the method in the embodiment of the present application.
Optionally, as shown in fig. 4, the electronic device 400 may also include a memory 420. From the memory 420, the processor 410 can call and run a computer program to implement the method in the embodiment of the present application.
The memory 420 may be a separate device from the processor 410, or may be integrated into the processor 410.
Optionally, as shown in fig. 4, the electronic device 400 may further include a transceiver 430, and the processor 410 may control the transceiver 430 to communicate with other devices, and in particular, may transmit information or data to the other devices or receive information or data transmitted by the other devices.
The transceiver 430 may include a transmitter and a receiver, among others. The transceiver 430 may further include antennas, and the number of antennas may be one or more.
Optionally, the electronic device 400 may implement corresponding processes in the methods of the embodiments of the present application, and for brevity, details are not described here again.
It should be understood that the processor of the embodiments of the present application may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method embodiments may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, or discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
It will be appreciated that the memory in the embodiments of the subject application can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. The non-volatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash Memory. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of example, but not limitation, many forms of RAM are available, such as Static random access memory (Static RAM, SRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic random access memory (Synchronous DRAM, SDRAM), Double Data Rate Synchronous Dynamic random access memory (DDR SDRAM), Enhanced Synchronous SDRAM (ESDRAM), Synchronous link SDRAM (SLDRAM), and Direct Rambus RAM (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to comprise, without being limited to, these and any other suitable types of memory.
It should be understood that the above memories are exemplary but not limiting illustrations, for example, the memories in the embodiments of the present application may also be Static Random Access Memory (SRAM), dynamic random access memory (dynamic RAM, DRAM), Synchronous Dynamic Random Access Memory (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (enhanced SDRAM, ESDRAM), Synchronous Link DRAM (SLDRAM), Direct Rambus RAM (DR RAM), and the like. That is, the memory in the embodiments of the present application is intended to comprise, without being limited to, these and any other suitable types of memory.
The embodiment of the application also provides a computer readable storage medium for storing the computer program.
Optionally, the computer-readable storage medium may be applied to the electronic device in the embodiment of the present application, and the computer program enables a computer to execute corresponding processes in each method in the embodiment of the present application, which is not described herein again for brevity.
Embodiments of the present application also provide a computer program product comprising computer program instructions.
Optionally, the computer program product may be applied to the electronic device in the embodiment of the present application, and the computer program instructions enable the computer to execute corresponding processes in each method in the embodiment of the present application, which is not described herein again for brevity.
The embodiment of the application also provides a computer program.
Optionally, the computer program may be applied to the electronic device in the embodiment of the present application, and when the computer program runs on a computer, the computer is enabled to execute corresponding processes in each method in the embodiment of the present application, and for brevity, details are not described here again.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses, devices and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus, device and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. With regard to such understanding, the technical solutions of the present application may be essentially implemented or contributed to by the prior art, or may be implemented in a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A method for processing loan information, comprising:
inputting loan information of a user with overdue behaviors into a complaint probability information prediction model to obtain complaint probability information of the user;
determining whether the user is a high complaint risk user based on the complaint probability information;
when the user is a high complaint risk user, acquiring a target collection urging strategy, wherein the target collection urging strategy is used for indicating at least one of frequency, mode and talk operation of collection urging of the user;
and executing corresponding operation according to the target collection strategy.
2. The method of claim 1, wherein the determining whether the user is a high complaint risk user based on the complaint probability information comprises:
determining the grade of the complaint probability information to which the complaint probability information belongs;
and when the complaint rate corresponding to the complaint probability information grading is larger than a preset value, determining that the user is a high-complaint risk user, wherein the complaint rate is the proportion of the number of users with complaint behaviors in the complaint probability information grading to the total number of users.
3. The method according to claim 1 or 2, characterized in that the method further comprises:
aiming at a user corresponding to each test sample in a test set, sending a call request and/or a collection prompting message to a terminal of the user according to a preset initial collection prompting strategy to obtain a complaint rate and a refund rate corresponding to the test set;
adjusting the initial collection urging strategy based on the complaint rate and the refund rate corresponding to the test set and a predetermined complaint rate threshold and a predetermined refund rate threshold to obtain the target collection urging strategy;
wherein the complaint rate threshold and the refund rate threshold are determined based on a control set.
4. The method according to claim 3, wherein before the user corresponding to each test sample in the test set sends a call request and/or a collection message to the terminal of the user according to a preset initial collection policy, the method further comprises:
inputting the first sample set into the complaint probability information prediction model to obtain a second sample set, wherein the complaint rates of complaint probability grades corresponding to the complaint probability information of the samples in the second sample set are all larger than the preset value;
and dividing the second sample set into a test set and a control set according to a preset proportion.
5. The method according to claim 1 or 2, characterized in that the method further comprises:
determining complaint probability information corresponding to each sample in the third sample set;
dividing to obtain a plurality of complaint probability information grades based on the complaint probability information corresponding to each sample in the third sample set, and obtaining the complaint rate corresponding to each complaint probability information grade;
and determining the preset value based on the complaint rate corresponding to each complaint probability information grade and the complaint rate corresponding to the third sample set.
6. The method according to claim 1 or 2, wherein the performing corresponding operations according to the target collection policy includes:
sending a call request and/or a collection urging message to the user terminal according to the target collection urging strategy; or the like, or, alternatively,
sending the target collection strategy to a service terminal, and enabling the service terminal to send a call request and/or a collection message to a user terminal according to the target collection strategy;
and the calling request and the collection prompting message are used for prompting the user to carry out payment operation.
7. An electronic device, comprising:
the processing unit is used for inputting loan information of the user with overdue behavior into the complaint probability information prediction model to obtain complaint probability information of the user;
the processing unit is further used for determining whether the user is a high complaint risk user based on the complaint probability information;
the system comprises an acquisition unit, a display unit and a management unit, wherein the acquisition unit is used for acquiring a target collection urging strategy when the user is a high complaint risk user, and the target collection urging strategy is used for indicating at least one of frequency, mode and dialect for urging the user to collect;
and the processing unit is also used for executing corresponding operation according to the target collection strategy.
8. The device according to claim 7, wherein the processing unit is specifically configured to:
determining the grade of the complaint probability information to which the complaint probability information belongs;
and when the complaint rate corresponding to the complaint probability information grading is larger than a preset value, determining that the user is a high-complaint risk user, wherein the complaint rate is the proportion of the number of users with complaint behaviors in the complaint probability information grading to the total number of users.
9. An electronic device, comprising: a processor and a memory for storing a computer program, the processor being configured to invoke and execute the computer program stored in the memory to perform the method of any of claims 1 to 8.
10. A computer-readable storage medium for storing a computer program which causes a computer to perform the method of any one of claims 1 to 6.
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| CN202110395748.6A CN112991049B (en) | 2021-04-13 | 2021-04-13 | Loan information processing method and electronic equipment |
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| CN202110395748.6A CN112991049B (en) | 2021-04-13 | 2021-04-13 | Loan information processing method and electronic equipment |
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