Vehicle mortgage task processing method and device, storage medium and computer equipment

Abstract

The invention discloses a vehicle mortgage task processing method and device, a storage medium and computer equipment, relates to the technical field of information and financial science and technology, and can improve the processing efficiency and processing effect of a vehicle mortgage task and improve the experience feeling of vehicle mortgage personnel. Comprising the following steps: in response to a mortgage task processing signal of a target vehicle, acquiring mortgage task data and vehicle feature data of the target vehicle, specialist feature data of a plurality of specialists to be distributed in a mortgage party, and user feature data of a mortgage party user; according to the mortgage task data, judging whether the mortgage task of the target vehicle meets a preset mortgage condition for continuous processing; and if the mortgage task accords with the mortgage preset condition, determining a target specialist for processing the mortgage task in the to-be-allocated specialists based on specialist feature data, user feature data and vehicle feature data, and allocating the target specialist to process the mortgage task of the target vehicle.

Description

Technical Field

[0001] The present invention relates to the fields of information technology and financial technology, and in particular to a method, device, storage medium and computer equipment for processing a vehicle mortgage task. Background Art

[0002] Car mortgage usually refers to the method of guarantee in which the mortgagor uses his / her car as collateral to obtain a loan from a financial institution (mortgagee). Car release usually refers to the act of canceling the car mortgage after the mortgagor has paid off the loan from the financial institution (mortgagee). The current market size of automobile financial leasing is expanding year by year. The annual financial leasing vehicles of the leading financial leasing companies have reached millions, and they need to handle thousands of vehicle mortgage and release procedures every day. Therefore, finding an effective way to handle vehicle mortgages or releases has become an urgent problem to be solved.

[0003] At present, a specialist is usually randomly assigned to handle vehicle mortgage tasks by the account manager of a financial institution. However, this random assignment of specialists may cause the assigned specialist to be currently processing a business, so another specialist needs to be reassigned to handle the vehicle mortgage task, resulting in low efficiency in handling the vehicle mortgage task. At the same time, the assigned specialist may not be able to effectively handle the mortgage task, resulting in poor handling of the vehicle mortgage task and reducing the experience of the vehicle mortgage personnel. Summary of the invention

[0004] The present invention provides a method, device, storage medium and computer equipment for processing a vehicle mortgage task, which are mainly capable of improving the processing efficiency and processing effect of the vehicle mortgage task and improving the experience of the vehicle mortgage personnel.

[0005] According to a first aspect of the present invention, a method for processing a vehicle mortgage task is provided, comprising:

[0006] In response to a mortgage task processing signal of a target vehicle, acquiring mortgage task information data of the target vehicle, vehicle feature data, specialist feature data of a plurality of specialists to be assigned in the mortgagee, and user feature data of a user of the mortgagee;

[0007] Determining whether the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing based on the mortgage task data;

[0008] If the mortgage task meets the mortgage preset conditions, a target specialist who handles the mortgage task is determined from among the specialists to be assigned based on the specialist characteristic data, the user characteristic data, and the vehicle characteristic data, and the target specialist is assigned to handle the mortgage task of the target vehicle.

[0009] Optionally, the mortgage task data includes: contract number, task type, user name, user address, user contact information of the mortgage party, frame number of the target vehicle, mortgage start time, and mortgage end time;

[0010] The step of judging whether the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing based on the mortgage task data includes:

[0011] Determine whether the contract number conforms to a preset number regular expression; and / or,

[0012] Determining whether the task type in the mortgage task information data matches the task type carried in the mortgage task processing signal of the target vehicle; and / or,

[0013] Determine whether the user name exists; and / or,

[0014] Determining whether the user address is correct, wherein the method for determining whether the user address is correct includes: converting the user address into geographic coordinates using a preset geocoding algorithm, and matching the geographic coordinates with a preset area corresponding to the user address, and determining whether the user address is correct based on the matching result; and / or,

[0015] Determine whether the user contact information conforms to a preset telephone number regular expression; and / or, based on the vehicle frame number, determine whether the target vehicle belongs to the mortgagee user; and / or,

[0016] Based on the mortgage start time and the mortgage end time, determining whether the mortgage time of the target vehicle is within a preset time range;

[0017] If the contract number conforms to the preset number regular expression, the task type matches the task type carried in the mortgage task processing signal, the user name exists, the user address is correct, the user contact information conforms to the preset telephone number regular expression, the target vehicle belongs to the mortgagee user, and the mortgage time of the target vehicle is within the preset time range, then it is determined that the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing.

[0018] Optionally, before determining a target specialist to handle the mortgage task from among the specialists to be assigned based on the specialist feature data, the user feature data, and the vehicle feature data, the method further includes:

[0019] Obtain the mortgage jurisdiction area corresponding to each of the specialists to be assigned and the task processing area of ​​the mortgage task;

[0020] Based on the mortgage jurisdiction area and the task processing area, determining a reserve specialist to be assigned from among the specialists to be assigned who can perform mortgage task processing in the task processing area;

[0021] The step of determining a target specialist who handles the mortgage task from among the specialists to be assigned based on the specialist feature data, the user feature data, and the vehicle feature data includes:

[0022] Based on the specialist characteristic data of each of the prepared specialists to be assigned, the user characteristic data, and the vehicle characteristic data, a target specialist who handles the mortgage task is determined from among the prepared specialists to be assigned.

[0023] Optionally, after assigning the target specialist to handle the mortgage task of the target vehicle, the method further includes:

[0024] Receive a response signal triggered by the target specialist for the mortgage task, determine the mortgage task status information corresponding to the response signal, and display the mortgage task status information on the terminal of the person who delegates the mortgage task, wherein the response signal includes a task receiving signal, a task processing signal, and a task ending signal, and the mortgage task status information includes a received status corresponding to the task receiving signal, a task processing status corresponding to the task processing signal, and a task review status corresponding to the task ending signal;

[0025] If the mortgage task status information is a task review status, obtaining in real time the review result of the mortgage task by the task assignor of the assignor terminal;

[0026] Based on the review result, change the mortgage task status information displayed on the terminal of the delegate;

[0027] Wherein, the response signal also includes a task processing rejection signal. When the response signal is a task processing rejection signal, a substitute specialist who handles the mortgage task is determined from the remaining specialists to be assigned, and the substitute specialist is assigned to handle the mortgage task of the target vehicle, wherein the specialists among the specialists to be assigned excluding the target specialist are defined as the remaining specialists to be assigned.

[0028] Optionally, after assigning the target specialist to handle the mortgage task of the target vehicle, the method further includes:

[0029] In response to the target vehicle's mortgage release task processing signal, obtaining the target vehicle's mortgage release task information data, vehicle feature data, mortgage release specialist feature data of multiple mortgage release specialists to be assigned in the mortgagee, and user feature data of the mortgagee's user;

[0030] Determining whether the mortgage release task of the target vehicle meets the mortgage release preset conditions for continued processing based on the mortgage release task data;

[0031] If the mortgage release task meets the preset conditions for mortgage release, a target mortgage release specialist who handles the mortgage release task is determined from among the mortgage release specialists to be assigned based on the mortgage release specialist characteristic data, the user characteristic data, and the vehicle characteristic data, and the target mortgage release specialist is assigned to handle the mortgage release task of the target vehicle.

[0032] Optionally, the determining a target specialist who handles the mortgage task from among the specialists to be assigned based on the specialist feature data, the user feature data, and the vehicle feature data includes:

[0033] Respectively determining a specialist feature vector corresponding to the specialist feature data, a user feature vector corresponding to the user feature data, and a vehicle feature vector corresponding to the vehicle feature data;

[0034] Cross-processing the specialist feature vector, the user feature vector, and the vehicle feature vector to obtain a mortgage cross feature vector;

[0035] Input the mortgage cross feature vector into a pre-trained scoring model for score prediction, and obtain a mortgage processing effect score of each of the to-be-assigned specialists corresponding to the mortgagee user;

[0036] Based on the mortgage processing effect score of each of the specialists to be assigned, a target specialist who handles the mortgage task is determined from among the specialists to be assigned.

[0037] Optionally, cross-processing the specialist feature vector, the user feature vector, and the vehicle feature vector to obtain a mortgage cross feature vector includes:

[0038] Performing feature-level cross processing on the specialist feature vector, the user feature vector, and the vehicle feature vector to obtain a feature cross vector;

[0039] Performing element-level cross processing on the specialist feature vector, the user feature vector, and the vehicle feature vector to obtain an element cross vector;

[0040] Performing low-order cross processing on the specialist feature vector, the user feature vector, and the vehicle feature vector to obtain a low-order cross vector;

[0041] The characteristic cross vector, element cross vector and low-order cross vector are transformed by using a preset transformation function to obtain the mortgage cross characteristic vector.

[0042] According to a second aspect of the present invention, there is provided a vehicle mortgage task processing device, comprising:

[0043] An acquisition unit, for acquiring, in response to a mortgage task processing signal of a target vehicle, mortgage task information data of the target vehicle, vehicle feature data, specialist feature data of a plurality of specialists to be assigned in the mortgagee, and user feature data of a user of the mortgagee;

[0044] A judgment unit, used to judge whether the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing based on the mortgage task data;

[0045] A task processing unit is used to determine a target specialist who handles the mortgage task from among the specialists to be assigned based on the specialist characteristic data, the user characteristic data, and the vehicle characteristic data if the mortgage task meets the mortgage preset conditions, and assign the target specialist to handle the mortgage task of the target vehicle.

[0046] According to a third aspect of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for processing the vehicle mortgage task.

[0047] According to a fourth aspect of the present invention, there is provided a computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for processing vehicle mortgage tasks when executing the program.

[0048] According to a vehicle mortgage task processing method, device, storage medium and computer equipment provided by the present invention, compared with the current method of arbitrarily assigning a specialist to handle vehicle mortgage tasks through the account manager of a financial institution, the present invention pre-determines whether the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing based on the mortgage task data of the target vehicle, and processes the mortgage task if it meets the mortgage preset conditions for continued processing, thereby avoiding the mortgage task processing error caused by incomplete or erroneous mortgage task data, and also avoiding the time wasted by re-processing the task after the task processing error, so that the present invention can improve the processing accuracy and processing efficiency of the vehicle mortgage task. Afterwards, the present invention determines the target specialist suitable for processing the mortgage task among each specialist to be assigned through the specialist feature data, user feature data and vehicle feature data, and assigns the target specialist to process the mortgage task of the target vehicle, and selects the target specialist who is better qualified for the mortgage task processing among multiple specialists by comprehensively analyzing the specialist feature data, user feature data and vehicle feature data, so as to ensure the smooth and rapid progress and accurate processing of the mortgage task, and improve the experience of the vehicle mortgagor in the vehicle mortgage process. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0050] Figure 1 A flow chart of a method for processing a vehicle mortgage task provided by an embodiment of the present invention is shown;

[0051] Figure 2 A flow chart of another method for processing a vehicle mortgage task provided by an embodiment of the present invention is shown;

[0052] Figure 3A A schematic diagram of a newly created state of a mortgage task provided by an embodiment of the present invention is shown;

[0053] Figure 3B A schematic diagram of a state of pending orders for a mortgage task provided by an embodiment of the present invention is shown;

[0054] Figure 3C A schematic diagram of an order-accepted state of a mortgage task provided by an embodiment of the present invention is shown;

[0055] Figure 3D A schematic diagram showing a processing state of a mortgage task provided by an embodiment of the present invention is shown;

[0056] Figure 3E A schematic diagram showing a completed state of a mortgage task provided by an embodiment of the present invention is shown;

[0057] Figure 3F A schematic diagram of the approval status of a mortgage task provided by an embodiment of the present invention is shown;

[0058] Figure 4 A schematic diagram showing the structure of a vehicle mortgage task processing device provided by an embodiment of the present invention;

[0059] Figure 5 A schematic diagram of the physical structure of a computer device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0060] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0061] At present, the method in which the account manager of a financial institution randomly assigns a specialist to handle a vehicle mortgage task may cause the assigned specialist to be currently in the process of handling the business, so the specialist needs to be reassigned, resulting in low efficiency in handling the vehicle mortgage task. At the same time, the randomly assigned specialist may not be competent for the mortgage task, which will lead to poor handling effect of the vehicle mortgage task and reduce the experience of the vehicle mortgage personnel.

[0062] In order to solve the above problems, an embodiment of the present invention provides a method for processing a vehicle mortgage task, such as Figure 1 As shown, the method includes:

[0063] 101. In response to a mortgage task processing signal of a target vehicle, obtain mortgage task information data of the target vehicle, vehicle feature data, specialist feature data of multiple specialists to be assigned in the mortgagee, and user feature data of the mortgagee user.

[0064] Among them, the target vehicle is the mortgaged vehicle; the mortgage task information data is all the information related to the mortgage task uploaded or filled in by the creator of the mortgage task in the mortgage system, such as the task number, the user name of the user (mortgagor) to whom the target vehicle belongs, the frame number of the target vehicle, the mortgage start time, the mortgage end time, the mortgage task processing area, the company entity of the mortgagee, the task creator and other information; the vehicle characteristic data includes: the vehicle type, mileage, brand, manufacturer, engine performance, transmission system, driving mode and other information of the target vehicle; the specialist characteristic data refers to the age, gender, interests and hobbies, work experience, educational background, number of mortgage tasks processed, number of mortgage tasks to be processed, customer satisfaction, complaint rate, etc. of the specialist to be assigned; the user characteristic data refers to the age, work experience, educational background, social income, family situation, interests and hobbies, etc. of the mortgagor user.

[0065] For the embodiment of the present invention, when the personnel under the task establishes a task in the mortgage system and fills in the task-related information, the mortgage task processing signal is triggered. When the mortgage task processing signal is received, the mortgage task information data of the target vehicle, the vehicle characteristic data, the specialist characteristic data of multiple specialists to be assigned in the mortgagee, the user characteristic data of the mortgagee user, etc. are obtained. Then, based on the above data, a suitable specialist is assigned to process the mortgage task of the target vehicle. Therefore, by comprehensively analyzing the mortgage task information data, vehicle characteristic data, specialist characteristic data, user characteristic data, etc., a suitable specialist is selected to process the mortgage task, which can ensure the mortgage task is carried out quickly and accurately, and enhance the user experience of the mortgagee.

[0066] It should be noted that the specialist characteristic data, user characteristic data, and vehicle characteristic data obtained in this embodiment are not private data, but data related to the mortgage task that can be obtained in the mortgage system (non-private data).

[0067] 102. Based on the mortgage task data, determine whether the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing.

[0068] For the embodiment of the present invention, when obtaining the mortgage task information data, it is first necessary to review whether the data in the mortgage task information data is comprehensive and accurate. When the data is comprehensive and accurate, the mortgage task processing can be continued, which can avoid mortgage task processing errors caused by incomplete or inaccurate information, or the problem of re-processing the mortgage task. Therefore, the embodiment of the present invention can improve the processing efficiency and accuracy of the mortgage task and avoid the waste of task processing resources.

[0069] 103. If the mortgage task meets the mortgage preset conditions, the target specialist who will handle the mortgage task is determined from among the specialists to be assigned based on the specialist characteristic data, user characteristic data, and vehicle characteristic data, and the target specialist is assigned to handle the mortgage task of the target vehicle.

[0070] For the embodiment of the present invention, when the mortgage task meets the mortgage preset conditions for continued processing, it is necessary to conduct a comprehensive analysis of the specialist characteristic data, user characteristic data, and vehicle characteristic data, and determine a target specialist who can better handle the mortgage task from multiple specialists to be assigned based on the analysis results, and assign the target specialist to handle the mortgage task of the target vehicle. Therefore, by conducting a comprehensive analysis of the specialist characteristic data, user characteristic data, and vehicle characteristic data, a target specialist who can better handle the mortgage task is selected from multiple specialists, thereby ensuring the smooth, rapid and accurate processing of the mortgage task, thereby improving the experience of the vehicle mortgagor during the vehicle mortgage process.

[0071] According to a method for processing a vehicle mortgage task provided by the present invention, compared with the current method of arbitrarily assigning a specialist to handle the vehicle mortgage task through the account manager of a financial institution, the present invention pre-determines whether the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing based on the mortgage task data of the target vehicle, and processes the mortgage task when it meets the mortgage preset conditions for continued processing, thereby avoiding the mortgage task processing error caused by incomplete or erroneous mortgage task data, and also avoiding the time wasted by re-processing the task after the task processing error, so that the present invention can improve the processing accuracy and processing efficiency of the vehicle mortgage task. Afterwards, the present invention determines the target specialist suitable for processing the mortgage task among the specialists to be assigned through the specialist feature data, user feature data, and vehicle feature data, and assigns the target specialist to process the mortgage task of the target vehicle, and selects the target specialist who is better qualified for the mortgage task processing among multiple specialists by comprehensively analyzing the specialist feature data, user feature data, and vehicle feature data, so as to ensure the smooth and rapid progress and accurate processing of the mortgage task, and improve the experience of the vehicle mortgagor in the vehicle mortgage process.

[0072] Further, in order to better illustrate the process of processing the vehicle mortgage task, as a refinement and extension of the above embodiment, the embodiment of the present invention provides another method for processing the vehicle mortgage task, such as Figure 2 As shown, the method includes:

[0073] 201. In response to a mortgage task processing signal of a target vehicle, obtain mortgage task information data of the target vehicle, vehicle feature data, specialist feature data of multiple specialists to be assigned in the mortgagee, and user feature data of the mortgagee user.

[0074] Specifically, data such as mortgage task information data, vehicle feature data, specialist feature data of multiple specialists to be assigned, and user feature data can be obtained in the database of the mortgage system.

[0075] 202. Based on the mortgage task data, determine whether the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing.

[0076] Among them, the mortgage task information data includes: contract number, task type, user name of the mortgagor user, user address, user contact information, frame number of the target vehicle, mortgage start time, mortgage end time and other data; a preset number regular expression is constructed in advance based on the standard contract number, and a preset phone number regular expression is constructed based on the standard phone number; the preset area is the expected area planned according to the user address; the preset time range is set according to actual needs.

[0077] For the embodiment of the present invention, after obtaining the mortgage task information data, it is first necessary to determine whether the mortgage task can continue to be processed based on the mortgage task information data. Based on this, step 202 specifically includes: determining whether the contract number conforms to a preset number regular expression; and / or determining whether the task type in the mortgage task information data matches the task type carried in the mortgage task processing signal of the target vehicle; and / or determining whether the user name exists; and / or determining whether the user address is correct, wherein the method for determining whether the user address is correct includes: using a preset geocoding algorithm to convert the user address into geographic coordinates, and matching the geographic coordinates with a preset area corresponding to the user address, and determining based on the matching result. Whether the user address is correct; and / or, whether the user contact information conforms to the preset telephone number regular expression; and / or, based on the vehicle frame number, whether the target vehicle belongs to the mortgagee user; and / or, based on the mortgage start time and mortgage end time, whether the mortgage time of the target vehicle is within the preset time range; if the contract number conforms to the preset number regular expression, the task type matches the task type carried in the mortgage task processing signal, the user name exists, the user address is correct, the user contact information conforms to the preset telephone number regular expression, the target vehicle belongs to the mortgagee user, and the mortgage time of the target vehicle is within the preset time range, then it is determined that the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing.

[0078] Specifically, first determine whether the mortgage task data contains information such as the contract number, task type, user name of the mortgagee, user address, user contact information, vehicle frame number of the target vehicle, mortgage start time, and mortgage end time. If all the above information is included, the above information needs to be reviewed, such as reviewing whether the contract number, telephone number, etc. conform to the corresponding preset regular expression, reviewing whether the task type, user address, user name, and vehicle frame number are filled in correctly, and reviewing whether the vehicle frame number belongs to the mortgagee user to avoid illegal mortgage by the user. In the process of user address review, the user address can be converted into spatial geographic coordinates using a preset geocoding algorithm, and then the user address is reviewed based on the spatial geographic coordinates. The preset geocoding algorithm can be a geographic grid algorithm, that is, the earth's surface is divided according to certain mathematical rules to form multiple polygons that are adjacent to each other and do not cross, and each polygon is given a unique identifier, that is, a geographic code, and then the geographic object and the address are used to establish a relative association through the grid, and the address attribute of the geographic object is established, so that the spatial position coordinates can be obtained. Further, it is also necessary to calculate the mortgage time of the target vehicle according to the mortgage start time and the mortgage end time, and conduct a compliance review on the mortgage time. The mortgage task of the target vehicle will only be processed if all the information in the above-mentioned mortgage task data has been reviewed and approved, so as to avoid mortgage task processing errors due to missing or incorrect information in the mortgage task data, and the need to waste time on re-processing the mortgage task. Therefore, the embodiment of the present invention can improve the processing efficiency and accuracy of the mortgage task.

[0079] 203. If the mortgage task meets the mortgage preset conditions, obtain the mortgage jurisdiction area corresponding to each specialist to be assigned and the task processing area of ​​the mortgage task.

[0080] 204. Based on the mortgage jurisdiction area and the task processing area, a reserve specialist to be assigned who can handle the mortgage task in the task processing area is determined from among the specialists to be assigned.

[0081] Specifically, after all the data in the mortgage task data are reviewed and approved, it is determined that the mortgage task meets the mortgage preset conditions for continued processing. At this time, in order to reduce the complexity of determining the target specialist, it is first necessary to determine the specialist who can process the mortgage task among the specialists to be classified, that is, to match the mortgage jurisdiction area of ​​each specialist to be assigned with the task processing area of ​​the mortgage task, and match the pre-assigned specialist whose mortgage jurisdiction area is the same as the task processing area. For example, if the task processing area of ​​the mortgage task is Suzhou, the mortgage jurisdiction area of ​​the specialist to be assigned A is Suzhou, the mortgage jurisdiction area of ​​the specialist to be assigned B is Shanghai, the mortgage jurisdiction area of ​​the specialist to be assigned C is Shandong, and the mortgage jurisdiction area of ​​the specialist to be assigned D is Suzhou, then the specialist to be assigned A and the specialist to be assigned D are determined as the pre-assigned specialists to be assigned. Therefore, before determining the target specialist who can better handle the mortgage task, the first round of screening is first performed on each specialist to be assigned, which can reduce the complexity of selecting the target specialist from the specialists to be assigned with a large amount of data, and can also avoid the mortgage specialist taking a long time to reach the mortgage task processing area when assigning a specialist far away from the mortgage task processing area to process the mortgage task, so that the embodiment of the present invention can improve the processing efficiency of the mortgage task.

[0082] 205. Based on the specialist characteristic data, user characteristic data, and vehicle characteristic data of each prepared specialist to be assigned, a target specialist to handle the mortgage task is determined from among the prepared specialists to be assigned, and the target specialist is assigned to handle the mortgage task of the target vehicle.

[0083] For the embodiment of the present invention, after determining the specialists to be assigned, it is necessary to conduct a comprehensive analysis of the specialist feature data, user feature data, and vehicle feature data of each specialist to be assigned, so as to select a target specialist who can better handle the mortgage task from each specialist to be assigned. Based on this, step 205 includes: respectively determining a specialist feature vector corresponding to the specialist feature data, a user feature vector corresponding to the user feature data, and a vehicle feature vector corresponding to the vehicle feature data; cross-processing the specialist feature vector, the user feature vector, and the vehicle feature vector to obtain a mortgage cross-feature vector; inputting the mortgage cross-feature vector into a pre-trained scoring model for score prediction to obtain a mortgage processing effect score of each specialist to be assigned corresponding to the mortgagee user; and determining a target specialist who can handle the mortgage task from each specialist to be assigned based on the mortgage processing effect score of each specialist to be assigned. Among them, the method for cross-processing the specialist feature vector, the user feature vector, and the vehicle feature vector includes: performing feature-level cross-processing on the specialist feature vector, the user feature vector, and the vehicle feature vector to obtain a feature cross-vector; performing element-level cross-processing on the specialist feature vector, the user feature vector, and the vehicle feature vector to obtain an element cross-vector; performing low-order cross-processing on the specialist feature vector, the user feature vector, and the vehicle feature vector to obtain a low-order cross-vector; and using a preset transformation function to transform the feature cross-vector, the element cross-vector, and the low-order cross-vector to obtain the mortgage cross-feature vector.

[0084] Specifically, since the specialist feature data, user feature data, and vehicle feature data are in different fields, the processing method is to embed the data of the three fields into vectors of the same latitude. For example, if the specialist feature vector is (a1, a2), the user feature vector is (b1, b2), and the vehicle feature vector is (c1, c2), the specific cross processing method includes: performing feature-level crossover between different feature vectors, that is, performing Hadamard product on all elements between vectors, and then performing convolution transformation under certain weights to obtain a feature crossover vector of f(w*(a1*b1*c1,a2*b2*c2,a3*b3*c3)); at the same time, performing element-level crossover on all feature vector data, that is, performing Hadamard product on each element between vectors, and giving each product The results are assigned different weight values, and then a linear transformation is performed, and the obtained element cross vector is f(w1*a1*b1*c1,w2*a2*b2*c2,w3*a3*b3*c3); in addition, all feature vectors are subjected to low-order cross processing, and weight coefficients are assigned to the results after the cross processing, and then a linear transformation is performed, and the obtained low-order cross vector is f(w2(a1,a2,b1,b2,c1,c2)); finally, the above feature cross vectors, element cross vectors, and low-order cross vectors are combined together, and the preset function is used for transformation processing to obtain the mortgage cross feature vector. The preset function here can be set according to the actual situation, and this embodiment does not limit this. It should be noted that the above examples are only illustrative and do not limit the embodiments of the present application. Therefore, by cross-processing the specialist feature vector, user feature vector, and vehicle feature vector, different features can be automatically or explicitly combined to generate new feature combinations. These combined features may contain complex nonlinear relationships between the original features, so that the model can capture more detailed and rich information in the data, that is, it can make full use of the relationship between various data, extract more implicit features, and take into account both high-order and low-order processing, so that data utilization is more complete, and the target specialist selection results obtained later are more accurate and meet the needs of actual application scenarios.

[0085] Furthermore, after determining the mortgage cross-feature vector, it is necessary to predict the mortgage processing effect score of each specialist based on the scoring model. Before the scoring prediction, in order to improve the prediction accuracy of the scoring model, it is necessary to first construct and train the scoring model. Based on this, the method includes: constructing at least one initial scoring model; or a sample data set, wherein the sample data set includes sample specialist feature data of sample specialists, sample user feature data of sample mortgagee users, sample vehicle feature data of sample mortgage vehicles, and actual mortgage processing effect scores corresponding to each sample specialist; based on the number of models of the initial scoring model, dividing the sample data set into multiple groups of training data sets and multiple groups of test data sets; using each group of training data sets to train the corresponding preset initial scoring model, and using each group of test data sets to test the corresponding trained initial scoring model, and finally determining the trained initial scoring model that meets the test conditions as the scoring model.

[0086] Furthermore, after training and constructing the scoring model, the mortgage cross-feature vector is input into the pre-trained scoring model for score prediction. The scoring model can output the mortgage processing effect score of each prepared specialist to be assigned corresponding to the mortgagee user, and finally select the target specialist with the highest mortgage processing effect score to process the mortgage task. The specialist selection through the model can improve the selection efficiency and accuracy of the task processing specialists, thereby improving the processing efficiency and accuracy of the mortgage tasks.

[0087] Furthermore, after the mortgage task is processed, it is necessary to continue to process the mortgage release task of the target vehicle. The processing flow of the mortgage release task is similar to the processing flow of the mortgage task. The method includes: in response to the mortgage release task processing signal of the target vehicle, obtaining the mortgage release task information data, vehicle characteristic data, mortgage release specialist characteristic data of multiple mortgage release specialists to be assigned in the mortgagee, and user characteristic data of the mortgagee user of the target vehicle; judging whether the mortgage release task of the target vehicle meets the mortgage release preset conditions for continued processing based on the mortgage release task information data; if the mortgage release task meets the mortgage release preset conditions, determining a target mortgage release specialist to process the mortgage release task from each of the mortgage release specialists to be assigned based on the mortgage release specialist characteristic data, the user characteristic data, and the vehicle characteristic data, and assigning the target mortgage release specialist to process the mortgage release task of the target vehicle.

[0088] Among them, the mortgage release task information data refers to all the information related to the mortgage release task uploaded or filled in by the creator of the mortgage release task in the mortgage release system, such as the task number, the user name of the user (mortgagor) to whom the target vehicle belongs, the frame number of the target vehicle, the mortgage start time, the mortgage end time, the mortgage release task processing area, the company entity of the mortgage release party, the task creator and other information; the vehicle characteristic data includes: the vehicle type, mileage, brand, manufacturer, engine performance, transmission system, driving mode and other information of the target vehicle (mortgage release); the specialist characteristic data refers to the age, gender, interests and hobbies, work experience, educational background, number of mortgage release tasks processed, number of mortgage release tasks to be processed, customer satisfaction, complaint rate, etc. of the mortgage release specialist to be assigned; the user characteristic data refers to the age, work experience, educational background, social income, family situation, interests and hobbies, etc. of the mortgage release party user.

[0089] Specifically, based on the mortgage release task information data, if it is determined that the mortgage release task of the target vehicle meets the preset conditions for continued mortgage release, the mortgage release specialist characteristic data, user characteristic data, and vehicle characteristic data are input into the preset score prediction model for score prediction, and the mortgage release effect score of each mortgage release specialist to be assigned for the mortgage release user is obtained. Finally, the specialist with the highest score is selected as the mortgage release task processing specialist, and the mortgage release task is processed. Therefore, through comprehensive analysis of the specialist characteristic data, user characteristic data, and vehicle characteristic data, the target specialist who is more competent for the mortgage release task processing is selected from multiple mortgage release specialists, which can ensure the smooth, rapid and accurate processing of the mortgage release task, thereby improving the experience of the vehicle mortgage releaser during the vehicle mortgage release process.

[0090] Furthermore, after determining the target specialist who is more competent for the mortgage task processing work and the mortgage task processing work, the task status needs to be displayed in real time throughout the entire process from task creation to task execution and finally to task completion, so that relevant personnel can understand the task processing progress in real time. Based on this, taking the mortgage task as an example, the method includes: receiving a response signal triggered by the target specialist for the mortgage task, determining mortgage task status information corresponding to the response signal, and displaying the mortgage task status information on the terminal of the person delegating the mortgage task, wherein the response signal includes a task reception signal, a task processing signal, and a task completion signal, and the mortgage task status information includes a received status corresponding to the task reception signal, a task processing signal, and a task completion signal. The mortgage task status information includes the task processing status corresponding to the task processing signal and the task review status corresponding to the task end signal; if the mortgage task status information is the task review status, obtaining the review result of the mortgage task by the task delegating personnel of the delegating personnel terminal in real time; based on the review result, changing the mortgage task status information displayed on the delegating personnel terminal; wherein, the response signal also includes a task processing rejection signal, and when the response signal is a task processing rejection signal, determining a substitute specialist for processing the mortgage task from the remaining specialists to be assigned, and assigning the substitute specialist to process the mortgage task of the target vehicle, wherein the specialists after removing the target specialist from the specialists to be assigned are defined as the remaining specialists to be assigned.

[0091] Specifically, the embodiment of the present invention is based on a mortgage / unmortgage system. The account manager creates a mortgage / unmortgage task in the mortgage / unmortgage system and fills in relevant information. The system dispatches the mortgage / unmortgage task according to the preset task dispatching rules. The mortgage / unmortgage specialist receives the mortgage / unmortgage task based on the task dispatched by the system. After receiving the mortgage / unmortgage task, the mortgage / unmortgage specialist handles the mortgage / unmortgage task and feedbacks the handling progress. The account manager can view the status of the mortgage / unmortgage task in real time on the mortgage / unmortgage system and track the mortgage / unmortgage task. The task status of the mortgage / unmortgage task is divided into new, pending order, received order, in process, completed, approved and other states. New status: the account manager creates and submits the mortgage task information, but the system does not assign the task; Waiting for order status: the system assigns the task, but the mortgage / mortgage release specialist does not accept the task; Accepted status: after the system assigns the task, the mortgage / mortgage release specialist accepts the task; Processing status: the mortgage / mortgage release specialist begins to process the mortgage / mortgage release task; Processing completed status: the mortgage / mortgage release task procedures are completed; Approved status: after the mortgage / mortgage release task procedures are completed, the account manager approves the task and the task is completed. Examples of pages corresponding to each status are as follows: Figure 3A , Figure 3B , Figure 3C , Figure 3D , Figure 3E , Figure 3F As shown, it respectively shows the status information of each mortgage task displayed on the task execution specialist terminal, and the status information of each mortgage task displayed on the task creator (account manager) terminal.

[0092] Further, the detailed description of the display of each mortgage task status information is as follows: the account manager creates a mortgage / mortgage release task in the mortgage / mortgage release system and submits mortgage / mortgage release related information. Figure 3A As shown. The system records the mortgage / unmortgage task data. Each data record contains fields such as contract number, task type (mortgage, unmortgage), customer name, customer mobile number, vehicle frame number, lease start date, settlement date, task area, company entity, account manager, etc. The mortgage / unmortgage task is assigned to the target specialist. After the task is assigned, the pages of the account manager and mortgage / unmortgage specialist in the mortgage / unmortgage system are as follows: Figure 3B The mortgage / demortgage specialist clicks the "Accept Order" button in the pending order task list to accept the order. After accepting the order, the task changes from pending order to accepted order. The pages of the account manager and mortgage / demortgage specialist in the mortgage / demortgage system are as follows: Figure 3C As shown; other mortgage / unmortgage specialists can no longer accept orders for this task, and the task will be handled by the mortgage / unmortgage specialist who accepted the order. The mortgage / unmortgage specialist handles the mortgage / unmortgage task until the mortgage / unmortgage task is completed. The mortgage / unmortgage specialist starts to handle the mortgage / unmortgage task. If you click the task "Start Handling" button, the mortgage / unmortgage task status in the system will change to "Processing". During the task handling process, the pages of the account manager and the mortgage / unmortgage specialist in the mortgage / unmortgage system are as follows Figure 3D After the mortgage / unmortgage specialist completes the task, click the task "Complete", the mortgage / unmortgage task status in the system changes to Completed, and the mortgage task processing ends. After the task is completed, the pages of the account manager and mortgage / unmortgage specialist in the mortgage / unmortgage system are as follows: Figure 3E The account manager will review the mortgage / unmortgage task according to the completion status of the mortgage / unmortgage task. If there is no objection to the mortgage / unmortgage task, the mortgage / unmortgage task will be completed. The page of the account manager and the mortgage / unmortgage specialist in the mortgage / unmortgage system is as follows: Figure 3F Otherwise, the process returns to step S4, and the mortgage / unmortgage specialist continues to handle the mortgage / unmortgage task. Finally, the account manager reviews the mortgage / unmortgage task and confirms that the task is completed, and the mortgage / unmortgage task ends.

[0093] Furthermore, if the target specialist temporarily has other urgent matters or is unable to handle the mortgage task due to other reasons, a task processing rejection signal will be triggered in the mortgage system. When the mortgage system receives the task processing rejection signal, it will re-select a substitute specialist who is better qualified for the mortgage task from the remaining specialists to be assigned, and assign the substitute specialist to handle the mortgage task, so as to avoid the problem of the mortgage task being shelved due to the target specialist's temporary affairs.

[0094] According to another method for processing vehicle mortgage tasks provided by the present invention, compared with the current method of arbitrarily assigning a specialist to handle vehicle mortgage tasks through the account manager of a financial institution, the present invention pre-determines whether the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing based on the mortgage task data of the target vehicle, and processes the mortgage task when it meets the mortgage preset conditions for continued processing, thereby avoiding the mortgage task processing error caused by incomplete or erroneous mortgage task data, and also avoiding the time wasted by re-processing the task after the task processing error, so that the present invention can improve the processing accuracy and processing efficiency of the vehicle mortgage task. Afterwards, the present invention determines the target specialist suitable for processing the mortgage task among the specialists to be assigned through the specialist feature data, user feature data, and vehicle feature data, and assigns the target specialist to process the mortgage task of the target vehicle, and selects the target specialist who is better qualified for the mortgage task processing among multiple specialists by comprehensively analyzing the specialist feature data, user feature data, and vehicle feature data, so as to ensure the smooth and rapid progress and accurate processing of the mortgage task, and improve the experience of the vehicle mortgagor in the vehicle mortgage process.

[0095] Further, as Figure 1 In a specific implementation, an embodiment of the present invention provides a processing device for a vehicle mortgage task, such as Figure 4 As shown, the device includes: an acquisition unit 31, a judgment unit 32, and a task processing unit 33.

[0096] The acquisition unit 31 can be used to respond to the mortgage task processing signal of the target vehicle to acquire the mortgage task information data, vehicle feature data, specialist feature data of multiple specialists to be assigned in the mortgagee, and user feature data of the mortgagee user.

[0097] The judgment unit 32 may be used to judge whether the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing based on the mortgage task information data.

[0098] The task processing unit 33 can be used to determine a target specialist who handles the mortgage task among the specialists to be assigned based on the specialist characteristic data, the user characteristic data, and the vehicle characteristic data if the mortgage task meets the mortgage preset conditions, and assign the target specialist to handle the mortgage task of the target vehicle.

[0099] In a specific application scenario, the mortgage task information data includes: contract number, task type, user name of the mortgagor user, user address, user contact information, frame number of the target vehicle, mortgage start time, and mortgage end time; in order to determine whether the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing, the judgment unit 32 includes a judgment module 321 and a determination module 322.

[0100] The judgment module 321 can be used to judge whether the contract number conforms to a preset number regular expression.

[0101] The judgment module 321 may also be used to judge whether the task type in the mortgage task information data matches the task type carried in the mortgage task processing signal of the target vehicle.

[0102] The determination module 321 may also be used to determine whether the user name exists.

[0103] The judgment module 321 can also be used to judge whether the user address is correct, wherein the method for judging whether the user address is correct includes: using a preset geocoding algorithm to convert the user address into geographic coordinates, and matching the geographic coordinates with a preset area corresponding to the user address, and judging whether the user address is correct based on the matching result.

[0104] The determination module 321 may also be used to determine whether the user contact information conforms to a preset telephone number regular expression.

[0105] The judgment module 321 may also be used to judge whether the target vehicle belongs to the mortgage user based on the vehicle frame number.

[0106] The judgment module 321 may also be used to judge whether the mortgage time of the target vehicle is within a preset time range based on the mortgage start time and the mortgage end time.

[0107] The determination module 322 can be used to determine that the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing if the contract number meets the preset number regular expression, the task type matches the task type carried in the mortgage task processing signal, the user name exists, the user address is correct, the user contact information meets the preset telephone number regular expression, the target vehicle belongs to the mortgagor user, and the mortgage time of the target vehicle is within the preset time range.

[0108] In a specific application scenario, in order to determine a ready-to-be-assigned specialist who can perform mortgage task processing in the task processing area, the device further includes a determining unit 34 .

[0109] The acquisition unit 31 may also be used to acquire the mortgage jurisdiction area corresponding to each of the specialists to be assigned and the task processing area of ​​the mortgage task.

[0110] The determining unit 34 may be configured to determine, based on the mortgage jurisdiction area and the task processing area, a reserve specialist to be assigned from among the specialists to be assigned who can perform mortgage task processing in the task processing area.

[0111] In a specific application scenario, in order to determine the target specialist to handle the mortgage task, the task processing unit 33 can be specifically used to determine the target specialist to handle the mortgage task among the prepared specialists to be assigned based on the specialist characteristic data of each of the prepared specialists to be assigned, the user characteristic data, and the vehicle characteristic data.

[0112] In a specific application scenario, in order to display the task processing status on the terminal, the device further includes: a display unit 35 and a changing unit 36 ​​.

[0113] The display unit 35 can be used to receive a response signal triggered by the target specialist for the mortgage task, determine the mortgage task status information corresponding to the response signal, and display the mortgage task status information on the terminal of the person assigned to the mortgage task, wherein the response signal includes a task reception signal, a task processing signal, and a task end signal, and the mortgage task status information includes a received status corresponding to the task reception signal, a task processing status corresponding to the task processing signal, and a task review status corresponding to the task end signal.

[0114] The acquisition unit 31 may also be used to acquire in real time the audit result of the mortgage task by the task assignor of the assignor terminal if the mortgage task status information is a task audit status.

[0115] The changing unit 36 ​​may be used to change the mortgage task status information displayed on the terminal of the delegate based on the audit result.

[0116] Wherein, the response signal also includes a task processing rejection signal. When the response signal is a task processing rejection signal, the task processing unit 33 can also be used to determine a substitute specialist who handles the mortgage task from the remaining specialists to be assigned, and assign the substitute specialist to handle the mortgage task of the target vehicle, wherein the specialists among the specialists to be assigned excluding the target specialist are defined as the remaining specialists to be assigned.

[0117] In a specific application scenario, in order to process a vehicle mortgage release task, the acquisition unit 31 can also be used to respond to a mortgage release task processing signal of the target vehicle to obtain mortgage release task information data, vehicle feature data, mortgage release specialist feature data of multiple mortgage release specialists to be assigned among the mortgagee, and user feature data of the mortgagee's users.

[0118] The judgment unit 32 may also be used to judge whether the mortgage release task of the target vehicle meets the preset mortgage release conditions for continued processing based on the mortgage release task data.

[0119] The task processing unit 33 can also be used to determine a target mortgage release specialist who handles the mortgage release task from among the mortgage release specialists to be assigned based on the mortgage release specialist characteristic data, the user characteristic data, and the vehicle characteristic data if the mortgage release task meets the preset mortgage release conditions, and assign the target mortgage release specialist to handle the mortgage release task of the target vehicle.

[0120] In a specific application scenario, in order to determine the target specialist who processes the mortgage task, the task processing unit 33 includes a determination module 331 , a cross-processing module 332 , and a prediction module 333 .

[0121] The determination module 331 may be used to respectively determine a specialist feature vector corresponding to the specialist feature data, a user feature vector corresponding to the user feature data, and a vehicle feature vector corresponding to the vehicle feature data.

[0122] The cross-processing module 332 may be used to perform cross-processing on the specialist feature vector, the user feature vector, and the vehicle feature vector to obtain a mortgage cross-feature vector.

[0123] The prediction module 333 can be used to input the mortgage cross-feature vector into a pre-trained scoring model for score prediction, so as to obtain the mortgage processing effect score of each of the specialists to be assigned corresponding to the mortgagee user.

[0124] The determination module 331 may be specifically configured to determine a target specialist who is to handle the mortgage task from among the specialists to be assigned based on the mortgage processing effect score of each specialist to be assigned.

[0125] In a specific application scenario, in order to perform cross-processing on the specialist feature vector, the user feature vector, and the vehicle feature vector, the cross-processing module 332 can be specifically used to perform feature-level cross-processing on the specialist feature vector, the user feature vector, and the vehicle feature vector to obtain a feature cross-vector; perform element-level cross-processing on the specialist feature vector, the user feature vector, and the vehicle feature vector to obtain an element cross-vector; perform low-order cross-processing on the specialist feature vector, the user feature vector, and the vehicle feature vector to obtain a low-order cross-vector; and use a preset transformation function to transform the feature cross-vector, the element cross-vector, and the low-order cross-vector to obtain the mortgage cross-feature vector.

[0126] It should be noted that for other corresponding descriptions of the functional modules involved in the vehicle mortgage task processing device provided in the embodiment of the present invention, reference can be made to Figure 1 The corresponding description of the method shown will not be repeated here.

[0127] Based on the above Figure 1 The method shown, accordingly, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the following steps are implemented: in response to a mortgage task processing signal of a target vehicle, the mortgage task information data, vehicle feature data, specialist feature data of multiple specialists to be assigned in the mortgagee, and user feature data of the mortgagee user of the target vehicle are obtained; based on the mortgage task information data, whether the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing is judged; if the mortgage task meets the mortgage preset conditions, then based on the specialist feature data, the user feature data, and the vehicle feature data, a target specialist to process the mortgage task is determined from among the specialists to be assigned, and the target specialist is assigned to process the mortgage task of the target vehicle.

[0128] Based on the above Figure 1 The method shown and Figure 4 The embodiment of the device shown in the figure, the embodiment of the present invention also provides a physical structure diagram of a computer device, such as Figure 5As shown, the computer device includes: a processor 41, a memory 42, and a computer program stored in the memory 42 and executable on the processor, wherein the memory 42 and the processor 41 are both arranged on a bus 43. When the processor 41 executes the program, the following steps are implemented: in response to a mortgage task processing signal of a target vehicle, the mortgage task information data, vehicle characteristic data, specialist characteristic data of a plurality of specialists to be assigned in the mortgagee, and user characteristic data of the mortgagee user of the target vehicle are obtained; based on the mortgage task information data, whether the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing is determined; if the mortgage task meets the mortgage preset conditions, a target specialist to process the mortgage task is determined from among the specialists to be assigned based on the specialist characteristic data, the user characteristic data, and the vehicle characteristic data, and the target specialist is assigned to process the mortgage task of the target vehicle.

[0129] Through the technical solution of the present invention, the present invention determines whether the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing in advance based on the mortgage task data of the target vehicle. When the mortgage preset conditions for continued processing are met, the mortgage task is processed to avoid the mortgage task processing errors caused by incomplete or erroneous mortgage task data, and can also avoid the time wasted in re-processing the task after the task processing error, so that the present invention can improve the processing accuracy and efficiency of the vehicle mortgage task. Afterwards, the present invention determines the target specialist suitable for processing the mortgage task among each specialist to be assigned through the specialist feature data, user feature data, and vehicle feature data, and assigns the target specialist to process the mortgage task of the target vehicle. By comprehensively analyzing the specialist feature data, user feature data, and vehicle feature data, the target specialist who is better qualified for the mortgage task processing is selected from multiple specialists, which can ensure the smooth and rapid progress and accurate processing of the mortgage task, and improve the experience of the vehicle mortgagor during the vehicle mortgage process.

[0130] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0131] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for processing a vehicle mortgage task, characterized in that: include: In response to a mortgage task processing signal of a target vehicle, acquiring mortgage task information data of the target vehicle, vehicle feature data, specialist feature data of a plurality of specialists to be assigned in the mortgagee, and user feature data of a user of the mortgagee; Determining whether the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing based on the mortgage task data; If the mortgage task meets the mortgage preset conditions, a target specialist who handles the mortgage task is determined from among the specialists to be assigned based on the specialist characteristic data, the user characteristic data, and the vehicle characteristic data, and the target specialist is assigned to handle the mortgage task of the target vehicle.

2. The method according to claim 1, characterized in that The mortgage task data includes: contract number, task type, user name, user address, user contact information of the mortgage party, frame number of the target vehicle, mortgage start time, and mortgage end time; The step of judging whether the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing based on the mortgage task data includes: Determine whether the contract number conforms to a preset number regular expression; and / or, Determining whether the task type in the mortgage task information data matches the task type carried in the mortgage task processing signal of the target vehicle; and / or, Determine whether the user name exists; and / or, Determining whether the user address is correct, wherein the method for determining whether the user address is correct includes: converting the user address into geographic coordinates using a preset geocoding algorithm, and matching the geographic coordinates with a preset area corresponding to the user address, and determining whether the user address is correct based on the matching result; and / or, Determining whether the user contact information conforms to a preset telephone number regular expression; and / or, Based on the vehicle frame number, determining whether the target vehicle belongs to the mortgage user; and / or, Based on the mortgage start time and the mortgage end time, determining whether the mortgage time of the target vehicle is within a preset time range; If the contract number conforms to the preset number regular expression, the task type matches the task type carried in the mortgage task processing signal, the user name exists, the user address is correct, the user contact information conforms to the preset telephone number regular expression, the target vehicle belongs to the mortgagee user, and the mortgage time of the target vehicle is within the preset time range, then it is determined that the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing.

3. The method according to claim 1, characterized in that Before determining a target specialist who handles the mortgage task from among the specialists to be assigned based on the specialist feature data, the user feature data, and the vehicle feature data, the method further includes: Obtain the mortgage jurisdiction area corresponding to each of the specialists to be assigned and the task processing area of ​​the mortgage task; Based on the mortgage jurisdiction area and the task processing area, determining a reserve specialist to be assigned from among the specialists to be assigned who can perform mortgage task processing in the task processing area; The step of determining a target specialist who handles the mortgage task from among the specialists to be assigned based on the specialist feature data, the user feature data, and the vehicle feature data includes: Based on the specialist characteristic data of each of the prepared specialists to be assigned, the user characteristic data, and the vehicle characteristic data, a target specialist who handles the mortgage task is determined from among the prepared specialists to be assigned.

4. The method according to claim 1, characterized in that: After assigning the target specialist to handle the mortgage task of the target vehicle, the method further includes: Receive a response signal triggered by the target specialist for the mortgage task, determine the mortgage task status information corresponding to the response signal, and display the mortgage task status information on the terminal of the person who delegates the mortgage task, wherein the response signal includes a task receiving signal, a task processing signal, and a task ending signal, and the mortgage task status information includes a received status corresponding to the task receiving signal, a task processing status corresponding to the task processing signal, and a task review status corresponding to the task ending signal; If the mortgage task status information is a task review status, obtaining in real time the review result of the mortgage task by the task assignor of the assignor terminal; Based on the review result, change the mortgage task status information displayed on the terminal of the delegate; Wherein, the response signal also includes a task processing rejection signal. When the response signal is a task processing rejection signal, a substitute specialist who handles the mortgage task is determined from the remaining specialists to be assigned, and the substitute specialist is assigned to handle the mortgage task of the target vehicle, wherein the specialists among the specialists to be assigned excluding the target specialist are defined as the remaining specialists to be assigned.

5. The method according to claim 1, characterized in that After assigning the target specialist to handle the mortgage task of the target vehicle, the method further includes: In response to the target vehicle's mortgage release task processing signal, obtaining the target vehicle's mortgage release task information data, vehicle feature data, mortgage release specialist feature data of multiple mortgage release specialists to be assigned in the mortgagee, and user feature data of the mortgagee's user; Determining whether the mortgage release task of the target vehicle meets the mortgage release preset conditions for continued processing based on the mortgage release task data; If the mortgage release task meets the preset conditions for mortgage release, a target mortgage release specialist who handles the mortgage release task is determined from among the mortgage release specialists to be assigned based on the mortgage release specialist characteristic data, the user characteristic data, and the vehicle characteristic data, and the target mortgage release specialist is assigned to handle the mortgage release task of the target vehicle.

6. The method according to claim 1, characterized in that The step of determining a target specialist who handles the mortgage task from among the specialists to be assigned based on the specialist feature data, the user feature data, and the vehicle feature data includes: Respectively determining a specialist feature vector corresponding to the specialist feature data, a user feature vector corresponding to the user feature data, and a vehicle feature vector corresponding to the vehicle feature data; Cross-processing the specialist feature vector, the user feature vector, and the vehicle feature vector to obtain a mortgage cross feature vector; Input the mortgage cross feature vector into a pre-trained scoring model for score prediction, and obtain a mortgage processing effect score of each of the to-be-assigned specialists corresponding to the mortgagee user; Based on the mortgage processing effect score of each of the specialists to be assigned, a target specialist who handles the mortgage task is determined from among the specialists to be assigned.

7. The method according to claim 6, characterized in that The cross-processing of the specialist feature vector, the user feature vector, and the vehicle feature vector to obtain the mortgage cross-feature vector includes: Performing feature-level cross processing on the specialist feature vector, the user feature vector, and the vehicle feature vector to obtain a feature cross vector; Performing element-level cross processing on the specialist feature vector, the user feature vector, and the vehicle feature vector to obtain an element cross vector; Performing low-order cross processing on the specialist feature vector, the user feature vector, and the vehicle feature vector to obtain a low-order cross vector; The characteristic cross vector, element cross vector and low-order cross vector are transformed by using a preset transformation function to obtain the mortgage cross characteristic vector.

8. A vehicle mortgage task processing device, characterized in that: include: An acquisition unit, for acquiring, in response to a mortgage task processing signal of a target vehicle, mortgage task information data of the target vehicle, vehicle feature data, specialist feature data of a plurality of specialists to be assigned in the mortgagee, and user feature data of a user of the mortgagee; A judgment unit, used to judge whether the mortgage task of the target vehicle meets the mortgage preset conditions for continued processing based on the mortgage task data; A task processing unit is used to determine a target specialist who handles the mortgage task from among the specialists to be assigned based on the specialist characteristic data, the user characteristic data, and the vehicle characteristic data if the mortgage task meets the mortgage preset conditions, and assign the target specialist to handle the mortgage task of the target vehicle.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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