CN113537574A - Service processing timeliness pushing method and device, storage medium and computer equipment - Google Patents

Service processing timeliness pushing method and device, storage medium and computer equipment Download PDF

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CN113537574A
CN113537574A CN202110700507.8A CN202110700507A CN113537574A CN 113537574 A CN113537574 A CN 113537574A CN 202110700507 A CN202110700507 A CN 202110700507A CN 113537574 A CN113537574 A CN 113537574A
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service
processed
aging
service processing
timeliness
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CN113537574B (en
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杨拯
杨光
费竹青
崇爱甄
范琳
郭霄
李登峰
刘琪
刘琦
刘阳
孟驰鹏
史鑫
帅璐
苏畅
王翰卿
王琦栋
张璟
张频
张瑶
赵万里
赵伟华
沈鹏
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Beijing Absolute Health Ltd
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Abstract

The invention discloses a pushing method, a device, a storage medium and computer equipment for service processing timeliness, relates to the technical field of information, and mainly aims to predict the processing timeliness of services handled by a user and push the service processing timeliness to the user in time, so that the user can clearly learn the processing timeliness of the services handled by the user. The method comprises the following steps: acquiring service information corresponding to a service to be processed; respectively inputting the service information into a plurality of preset service processing aging prediction models to perform aging prediction, and obtaining aging labels corresponding to the services to be processed; determining service processing timeliness corresponding to the service to be processed based on the timeliness label; and pushing the service processing timeliness to a user. The invention is suitable for pushing the service processing timeliness.

Description

Service processing timeliness pushing method and device, storage medium and computer equipment
Technical Field
The invention relates to the technical field of information, in particular to a pushing method and device for service processing timeliness, a storage medium and computer equipment.
Background
With the continuous development of information technology, users can handle services in a mode on a line, and a service platform performs service processing according to service data provided by the users and feeds back service processing results to the users in a mode on the line.
At present, after a user applies for transaction of a service on a service platform, the processing timeliness of the transaction of the user is usually presumed according to service terms. However, the professional nature of the business terms is strong, and the user is likely to parse the content of the business terms by mistake, thereby causing the user to not clearly know the processing timeliness of the transacted business.
Disclosure of Invention
In view of this, the present invention provides a method, an apparatus, a storage medium, and a computer device for pushing service processing timeliness, which mainly can predict the processing timeliness of a service handled by a user, and push the service processing timeliness to the user in time, so that the user can clearly learn the processing timeliness of the service handled by the user.
According to an aspect of the present invention, a method for pushing service processing timeliness is provided, including:
acquiring service information corresponding to a service to be processed;
respectively inputting the service information into a plurality of preset service processing aging prediction models to perform aging prediction, and obtaining aging labels corresponding to the services to be processed;
determining service processing timeliness corresponding to the service to be processed based on the timeliness label;
and pushing the service processing timeliness to a user.
Optionally, the step of inputting the service information into a plurality of preset service processing aging prediction models respectively to perform aging prediction to obtain an aging label corresponding to the service to be processed includes:
inputting the service information into a target preset service processing timeliness prediction model in the preset service processing timeliness prediction models, and judging whether the service information meets a risk condition corresponding to the target preset service processing timeliness prediction model;
and if the service information meets the risk condition, marking an aging label matched with the target preset service processing aging prediction model for the service to be processed.
Optionally, the determining, based on the aging label, a service processing aging corresponding to the service to be processed includes:
and determining the service processing aging corresponding to the aging label as the service processing aging corresponding to the service to be processed.
Optionally, before the obtaining of the service information corresponding to the service to be processed, the method further includes:
determining a plurality of risk conditions according to risk points in the service processing process;
predicting the accuracy and the recall rate respectively corresponding to the plurality of risk conditions by using the processed historical services;
screening a plurality of target risk conditions from the plurality of risk conditions based on the accuracy and recall;
and combining the target risk conditions based on the service processing timeliness of the historical services corresponding to the target risk conditions respectively, and constructing the preset service processing timeliness prediction models.
Optionally, the step of combining the target risk conditions based on the service processing aging of the historical service corresponding to each of the target risk conditions to construct the preset service processing aging prediction models includes:
based on the service processing timeliness of the historical services respectively corresponding to the target risk conditions, the historical service volumes under different service processing timeliness are counted;
determining the service processing timeliness corresponding to the highest historical service quantity according to the historical service quantities under the different service processing timeliness;
determining service processing timeliness respectively applicable to the target risk conditions based on the service processing timeliness corresponding to the highest historical service volume;
and combining the target risk conditions based on the service processing timeliness respectively applicable to the target risk conditions to construct the preset service processing timeliness prediction models.
Optionally, after determining the service processing aging corresponding to the service to be processed based on the aging label, the method further includes:
determining the service priority corresponding to the service to be processed based on the service processing timeliness corresponding to the service to be processed;
and distributing the service to be processed to corresponding service personnel based on the service priority.
Optionally, after determining the service priority corresponding to the service to be processed based on the service processing aging corresponding to the service to be processed, the method further includes:
determining a service retention time corresponding to the service to be processed;
and if the service retention time exceeds the preset service retention time, raising the service priority corresponding to the service to be processed.
Optionally, after the allocating the service to be processed to the corresponding service personnel based on the service priority, the method further includes:
acquiring the current processing time of the business personnel aiming at the case to be processed;
and if the processing time length exceeds the preset processing time length, sending alarm information to the terminal of the service personnel.
Optionally, after determining the service processing aging corresponding to the service to be processed based on the aging label, the method further includes:
receiving feedback information of the service to be processed under the corresponding service node in the service processing process;
matching the feedback information with each service node which is constructed in advance, and determining a target service node where the service to be processed is located currently according to a matching result;
and pushing the target service node to a user.
According to a second aspect of the present invention, there is provided a push device for service processing aging, including:
the acquisition unit is used for acquiring service information corresponding to the service to be processed;
the prediction unit is used for respectively inputting the service information to a plurality of preset service processing aging prediction models for aging prediction to obtain aging labels corresponding to the services to be processed;
the determining unit is used for determining the service processing timeliness corresponding to the service to be processed based on the timeliness label;
and the pushing unit is used for pushing the service processing timeliness to a user.
Optionally, the prediction unit comprises: a judging module and a marking module, wherein the judging module is used for judging whether the marking module is used for marking the mark,
the judging module is used for inputting the service information into a target preset service processing aging prediction model in the plurality of preset service processing aging prediction models and judging whether the service information meets a risk condition corresponding to the target preset service processing aging prediction model;
and the marking module is used for marking an aging label matched with the target preset service processing aging prediction model for the service to be processed if the service information meets the risk condition.
Optionally, the determining unit is specifically configured to determine the service processing aging corresponding to the aging label as the service processing aging corresponding to the service to be processed.
Optionally, the apparatus further comprises: a screening unit and a construction unit,
the determining unit is further configured to determine a plurality of risk conditions according to the risk points in the service processing process;
the prediction unit is further configured to predict accuracy and recall rate corresponding to the plurality of risk conditions by using the processed historical services;
the screening unit is used for screening a plurality of target risk conditions from the plurality of risk conditions based on the accuracy and the recall rate;
the construction unit is configured to combine the multiple target risk conditions based on the service processing timeliness of the historical services respectively corresponding to the multiple target risk conditions, and construct the multiple preset service processing timeliness prediction models.
Optionally, the construction unit comprises: a statistic module, a determining module and a constructing module,
the statistical module is used for counting the historical service volume under different service processing timeliness based on the service processing timeliness of the historical services respectively corresponding to the target risk conditions;
the determining module is used for determining the service processing timeliness corresponding to the highest historical service quantity according to the historical service quantities under the different service processing timeliness;
the determining module is further configured to determine, based on the service processing timeliness corresponding to the highest historical service volume, service processing timeliness to which the plurality of target risk conditions are respectively applicable;
the construction module is used for combining the target risk conditions based on the service processing timeliness respectively applicable to the target risk conditions to construct the preset service processing timeliness prediction models.
Optionally, the apparatus further comprises: the distribution unit is used for distributing the data,
the determining unit is further configured to determine a service priority corresponding to the service to be processed based on the service processing timeliness corresponding to the service to be processed;
and the distribution unit is used for distributing the service to be processed to corresponding service personnel based on the service priority.
Optionally, the apparatus further comprises: the lifting unit is used for lifting the air conditioner,
the determining unit is further configured to determine a service retention time corresponding to the service to be processed;
and the raising unit is used for raising the service priority corresponding to the service to be processed if the service retention time exceeds the preset service retention time.
Optionally, the obtaining unit is further configured to obtain a processing duration of the business staff for the case to be processed currently;
and the pushing unit is also used for sending alarm information to the terminal of the service personnel if the processing time length exceeds the preset processing time length.
Optionally, the apparatus further comprises: a receiving unit for receiving the received data,
the receiving unit is used for receiving feedback information of the service to be processed under the corresponding service node in the service processing process;
the determining unit is further configured to match the feedback information with each service node that is pre-constructed, and determine a target service node where the service to be processed is currently located according to a matching result;
the pushing unit is further configured to push the target service node to a user.
According to a third aspect of the present invention, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:
acquiring service information corresponding to a service to be processed;
respectively inputting the service information into a plurality of preset service processing aging prediction models to perform aging prediction, and obtaining aging labels corresponding to the services to be processed;
determining service processing timeliness corresponding to the service to be processed based on the timeliness label;
and pushing the service processing timeliness to a user.
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 on the memory and executable on the processor, the processor implementing the following steps when executing the program:
acquiring service information corresponding to a service to be processed;
respectively inputting the service information into a plurality of preset service processing aging prediction models to perform aging prediction, and obtaining aging labels corresponding to the services to be processed;
determining service processing timeliness corresponding to the service to be processed based on the timeliness label;
and pushing the service processing timeliness to a user.
Compared with the mode that the user guesses the processing timeliness of the business handled by the user according to the business terms at present, the method and the device can acquire the business information corresponding to the business to be processed; respectively inputting the service information into a plurality of preset service processing aging prediction models to perform aging prediction, and obtaining aging labels corresponding to the services to be processed; meanwhile, determining the service processing timeliness corresponding to the service to be processed based on the timeliness label; and finally, the service processing timeliness is pushed to the user, so that the processing timeliness of the service to be processed can be predicted through a plurality of preset service processing timeliness prediction models, and the processing timeliness can be pushed to the user, so that the user can clearly learn the processing timeliness of the case handled by the user, the user experience can be enhanced, and the satisfaction degree of the user is improved.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description, serve to explain the principles of the invention.
The invention will be more clearly understood from the following detailed description, taken with reference to the accompanying drawings, in which:
fig. 1 shows a flowchart of a pushing method for service processing aging according to an embodiment of the present invention;
FIG. 2 is a flow chart of another pushing method for processing aging of a service according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a pushing device for processing aging of a service according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of a push apparatus for processing aging of another service according to an embodiment of the present invention;
fig. 5 shows a physical structure diagram of a computer device according to an embodiment of the present invention.
Detailed Description
Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, the numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.
Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description.
The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.
Embodiments of the invention are operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well known computing systems, environments, and/or configurations that may be suitable for use with the computer system/server include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, networked personal computers, minicomputer systems, mainframe computer systems, distributed cloud computing environments that include any of the above, and the like.
The computer system/server may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, etc. that perform particular tasks or implement particular abstract data types. The computer system/server may be practiced in distributed cloud computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computer system storage media including memory storage devices.
The embodiment of the invention provides a method for pushing service processing timeliness, as shown in fig. 1, the method comprises the following steps:
101. and acquiring service information corresponding to the service to be processed.
The service to be processed is various services processed through the online platform, such as an insurance claim settlement service, and the service information is data related to the service handled by the user, for example, when the service to be processed is an insurance claim settlement service, the service information may specifically be report information, declaration data, an initial review result, an adjustment conclusion, and the like of the user. The embodiment of the invention is mainly applied to the scene of pushing the service processing timeliness to the user. The execution subject of the embodiment of the invention is a device and equipment capable of predicting and pushing service processing timeliness, and the device and equipment can be specifically arranged on one side of a server.
For the embodiment of the invention, when a user applies for handling the service at a user end, the user can firstly fill in service information required by the service handling, including personal information, service types and the like of the user, and according to service requirements, the user can also upload corresponding service data at the same time, for example, in insurance claim settlement service, the user can upload corresponding declaration data, such as claim settlement documents, invoices and the like. After the user completes the filling and uploading of the service information, the user clicks to determine, at the moment, the user side can generate a corresponding service processing request and send the service processing request to the server, and after the server receives a service processing instruction triggered by the user, the server can predict the service processing timeliness corresponding to the service to be processed according to the service information corresponding to the service to be processed and push the service processing timeliness to the user, so that the user can clearly learn the processing timeliness of the service applied by the user, the user is prevented from being in long-time unknown waiting, and the user experience is enhanced.
102. And respectively inputting the service information into a plurality of preset service processing aging prediction models to perform aging prediction, so as to obtain an aging label corresponding to the service to be processed.
The preset service treatment aging prediction models correspond to a plurality of risk conditions, aging labels corresponding to different preset service treatment aging prediction models are different, for example, an aging label corresponding to the preset service treatment aging prediction model A is a 24-hour label, an aging label corresponding to the preset service treatment aging prediction model B is a 48-hour label, and an aging label corresponding to the preset service treatment aging prediction model C is a 72-hour label.
For the embodiment of the present invention, in order to obtain the age label corresponding to the service to be processed, step 102 specifically includes: inputting the service information into a target preset service processing timeliness prediction model in the preset service processing timeliness prediction models, and judging whether the service information meets a risk condition corresponding to the target preset service processing timeliness prediction model; and if the service information meets the risk condition, marking an aging label matched with the target preset service processing aging prediction model for the service to be processed. The target preset service processing timeliness prediction model is any one of the plurality of preset service processing timeliness prediction models.
For example, according to the service type corresponding to the service to be processed, determining that the service to be processed relates to two preset service processing aging prediction models, namely a preset service processing aging prediction model 1 and a preset service processing aging prediction model 2 respectively, wherein the preset service processing aging prediction model 1 is a model capable of being finalized in 24 hours, the preset service processing aging prediction model 2 is a model capable of being finalized in 48 hours, the preset service processing aging prediction model 1 comprises a risk condition a, a risk condition b and a risk condition c, the preset service processing aging prediction model 2 comprises a risk condition d, a risk condition e and a risk condition f, inputting the service information corresponding to the service to be processed into the preset service processing aging prediction model 1, respectively judging whether the service information corresponding to the service to be processed meets the risk condition a, the risk condition b and the risk condition c, if the service information meets the risk condition a, the risk condition b and the risk condition c, a 24-hour label is marked for the service to be processed, the service information corresponding to the service to be processed is input into a preset service processing aging prediction model 2 in the same way, whether the service information corresponding to the service to be processed meets the risk condition d, the risk condition e and the risk condition f is respectively judged, if the service information meets the risk condition d, the risk condition e and the risk condition f, a 48-hour label is marked for the service to be processed, and therefore the aging label corresponding to the service to be processed can be determined to comprise the 24-hour label and the 48-hour label.
103. And determining the service processing timeliness corresponding to the service to be processed based on the timeliness label.
For the embodiment of the present invention, in order to determine the service processing aging corresponding to the service to be processed, step 103 specifically includes: and determining the service processing aging corresponding to the aging label as the service processing aging corresponding to the service to be processed. And if the service to be processed only meets the risk condition corresponding to one preset service processing aging prediction model, marking an aging label matched with the preset service processing aging prediction model for the service to be processed, determining the service processing aging corresponding to the service to be processed according to the service processing aging in the aging label, and if the unique aging label corresponding to the service to be processed is a 24 aging label, determining the service processing aging corresponding to the service to be processed to be 24 hours, namely the service needs to be processed after 24 hours, and feeding back a processing result to a user.
104. And pushing the service processing timeliness to a user.
For the embodiment of the invention, after receiving the service processing request, the service processing timeliness corresponding to the service to be processed is determined by utilizing the plurality of preset service processing timeliness prediction models, and the service processing timeliness is pushed to the user.
Compared with the method for pushing the service processing timeliness provided by the embodiment of the invention, the method for pushing the service processing timeliness can acquire the service information corresponding to the service to be processed; respectively inputting the service information into a plurality of preset service processing aging prediction models to perform aging prediction, and obtaining aging labels corresponding to the services to be processed; meanwhile, determining the service processing timeliness corresponding to the service to be processed based on the timeliness label; and finally, the service processing timeliness is pushed to the user, so that the processing timeliness of the service to be processed can be predicted through a plurality of preset service processing timeliness prediction models, and the processing timeliness can be pushed to the user, so that the user can clearly learn the processing timeliness of the case handled by the user, the user experience can be enhanced, and the satisfaction degree of the user is improved.
Further, to better explain the above process of predicting the aging of business process, as a refinement and extension to the above embodiment, an embodiment of the present invention provides another pushing method for the aging of business process, as shown in fig. 2, the method includes:
201. and acquiring service information corresponding to the service to be processed.
For the embodiment of the present invention, before predicting the service treatment aging corresponding to the service to be treated by using a plurality of preset service treatment aging prediction models, the preset service treatment aging prediction model needs to be constructed in advance, and as an optional embodiment, a construction method of the preset service treatment aging prediction model is provided, where the method includes: determining a plurality of risk conditions according to risk points in the service processing process; predicting the accuracy and the recall rate respectively corresponding to the plurality of risk conditions by using the processed historical services; screening a plurality of target risk conditions from the plurality of risk conditions based on the accuracy and recall; and combining the target risk conditions based on the service processing timeliness of the historical services corresponding to the target risk conditions respectively, and constructing the preset service processing timeliness prediction models. Further, the step of combining the target risk conditions based on the service processing aging of the historical services corresponding to the target risk conditions, and constructing the preset service processing aging prediction models includes: based on the service processing timeliness of the historical services respectively corresponding to the target risk conditions, the historical service volumes under different service processing timeliness are counted; determining the service processing timeliness corresponding to the highest historical service quantity according to the historical service quantities under the different service processing timeliness; determining service processing timeliness respectively applicable to the target risk conditions based on the service processing timeliness corresponding to the highest historical service volume; and combining the target risk conditions based on the service processing timeliness respectively applicable to the target risk conditions to construct the preset service processing timeliness prediction models.
The risk points may be determined according to specific service categories, for example, in an insurance claim settlement service, the risk points may specifically refer to offer points, claim rejection points, and the like, and further, according to the saving points and the risk points, risk conditions may be determined, such as whether the initial review is labeled as a saving point, whether the initial review is labeled as a claim rejection point, and the like.
In a specific application scenario, the accuracy and the recall rate of a plurality of risk conditions can be tested by using the processed historical services, then a plurality of target risk conditions are screened out from the plurality of risk conditions according to the accuracy and the recall rate of each risk condition, and further, the screened target risk conditions are combined to construct a plurality of preset service processing aging prediction models. For example, the plurality of target risk conditions selected from the plurality of risk conditions are risk condition a, risk condition b, risk condition c, risk condition d, risk condition e and risk condition f, further, the service treatment timeliness corresponding to the historical service meeting risk condition a, the service treatment timeliness corresponding to the historical service meeting risk condition b, the service treatment timeliness corresponding to the historical service meeting risk condition c, the service treatment timeliness corresponding to the historical service meeting risk condition d, the service treatment timeliness corresponding to the historical service meeting risk condition e and the service treatment timeliness corresponding to the historical service meeting risk condition f are determined, then, the historical traffic under different service treatment timeliness is counted, for example, the service treatment timeliness corresponding to the historical service under risk condition a includes 24 hours and 48 hours, for risk condition a, the historical traffic volumes at 24 hours and 48 hours are counted respectively as 500 pieces and 100 pieces, so that the historical traffic volumes at different service treatment aging times for each risk condition can be determined, for example, the historical traffic volumes at 24 hours and 48 hours are counted respectively as 300 pieces and 50 pieces for the risk condition b; for risk condition c, the historical traffic volume at 24 hours and 48 hours is counted as 700 pieces and 200 pieces respectively; for the risk condition d, the historical traffic volumes at 24 hours and 48 hours are counted as 50 pieces and 400 pieces respectively; for the risk condition e, the historical traffic of 24 hours and 48 hours is counted to be 100 pieces and 500 pieces respectively; according to the risk condition f, the historical traffic volume in 24 hours and 48 hours is counted to be 200 pieces and 700 pieces respectively, so that a model that the risk condition a, the risk condition b and the risk condition c are more suitable for 24-hour case settlement can be determined, a model that the risk condition d, the risk condition e and the risk condition f are more suitable for 48-hour case settlement can be determined, the risk condition a, the risk condition b and the risk condition c form a model for 24-hour case settlement, and the risk condition d, the risk condition e and the risk condition f form a model for 48-hour case settlement in the same way.
202. And respectively inputting the service information into a plurality of preset service processing aging prediction models to perform aging prediction, so as to obtain an aging label corresponding to the service to be processed.
For the embodiment of the present invention, after a plurality of preset service processing aging prediction models are constructed, the service processing aging of the service to be processed is predicted by using the service processing aging prediction model, so as to obtain the aging label corresponding to the service to be processed, and the specific process of performing aging prediction on the service to be processed is completely the same as that in step 102, and is not described herein again.
203. And determining the service processing timeliness corresponding to the service to be processed based on the timeliness label, and pushing the service processing timeliness to a user.
For the embodiment of the present invention, the specific process of determining the service aging corresponding to the service to be processed based on the aging label is completely the same as step 103, and is not described herein again.
204. And determining the service priority corresponding to the service to be processed based on the service processing timeliness corresponding to the service to be processed.
The shorter the service processing time is, the higher the service priority corresponding to the service processing time is, for example, the service priority corresponding to the 24-hour service to be processed is higher than the service priority corresponding to the 48-hour service to be processed. For the embodiment of the invention, after the service processing aging corresponding to the service to be processed is determined, the service priority corresponding to the service to be processed is determined according to the service processing aging length corresponding to the service to be processed.
205. And distributing the service to be processed to corresponding service personnel based on the service priority.
For the embodiment of the invention, the processing sequence corresponding to the service to be processed is determined according to the service priority corresponding to the service to be processed, the higher the service priority is, the earlier the corresponding processing sequence is, and then the service to be processed is distributed to the corresponding service personnel for processing based on the determined processing sequence. For example, the service processing aging corresponding to the service a to be processed is 24 hours, the service processing aging corresponding to the service B to be processed is 48 hours, and according to the service processing aging corresponding to the service a to be processed and the service B to be processed respectively, it is determined that the service priority corresponding to the service a to be processed is higher than the service priority corresponding to the service B to be processed, that is, the processing order of the service a to be processed is higher than the processing order of the service B to be processed, so that the service a to be processed is preferentially allocated to the corresponding service personnel for processing, and after the allocation of the service a to be processed is completed, the service B to be processed is allocated to the corresponding service personnel for processing.
In a specific application scenario, if the retention time of a service to be processed in a service pool is too long and the service to be processed is not allocated for a long time, the service priority corresponding to the service to be processed is increased, so that the service to be processed is preferentially allocated to a corresponding service worker for processing in time, and based on this, after determining the service priority corresponding to the service to be processed based on the service processing aging corresponding to the service to be processed, the method further includes: determining a service retention time corresponding to the service to be processed; and if the service retention time exceeds the preset service retention time, raising the service priority corresponding to the service to be processed. The preset service detention duration can be set according to service requirements.
For example, the service processing aging corresponding to the service to be processed is 72 hours, the corresponding preset service retention time is 12 hours, if the service to be processed has 14 hours and no special service personnel are available for processing, the service priority corresponding to the service to be processed is increased, and specifically, the service priority corresponding to the service to be processed is increased to the service priority corresponding to the service of 24 hours.
In a specific application scenario, if a service to be processed is already allocated to a corresponding service person for processing, but the service person has not been processed within a corresponding time period, the server sends an alarm message to a terminal of the service person to prompt the service person to grasp time for processing, and based on this, after the service to be processed is allocated to the corresponding service person based on the service priority, the method further includes: acquiring the current processing time of the business personnel aiming at the case to be processed; and if the processing time length exceeds the preset processing time length, sending alarm information to the terminal of the service personnel. The preset processing time can be set according to service requirements, for example, the preset processing time is set to be 20 hours for a service finished in 24 hours; for the service finished in 48 hours, the preset processing time is set to be 44 hours.
Further, if the service to be processed is already allocated to the corresponding service personnel, but the service personnel does not process the service personnel within the corresponding time, if the unprocessed time length exceeds the preset unprocessed time length, the server also sends alarm information to the terminal of the service personnel to remind the service personnel to process the service personnel as soon as possible.
In addition, in the process of processing the service, a plurality of service nodes may be involved, for example, service nodes such as initial review, input adjustment, audit and the like may be involved in the insurance claim settlement service, and if the processing duration of the service on the corresponding service node exceeds the preset processing duration, the server may also send alarm information to a terminal of a service person or a manager of the corresponding service node to prompt the service person or the manager to complete the processing on the corresponding node as soon as possible.
In a specific application scenario, a service node where a service to be processed is currently located may also be pushed to a user, so as to show a service progress for the user at a client, so that a service flow is completely transparent, and based on this, after determining a service processing aging corresponding to the service to be processed based on the aging label, the method further includes: receiving feedback information of the service to be processed under the corresponding service node in the service processing process; matching the feedback information with each service node which is constructed in advance, and determining a target service node where the service to be processed is located currently according to a matching result; and pushing the target service node to a user. In addition, when the service to be processed enters the next service node from the current service node, the next service node sends feedback information to the server aiming at the service to be processed, so that the server determines the service node where the service to be processed is currently located according to the received feedback information.
For example, the service to be processed is an insurance claim service, when the insurance claim service is recorded and settled, the insurance claim service enters an audit service node, when an audit system receives an audit request of the insurance claim service, the audit system sends corresponding feedback information to the server, such as ' audit on the insurance claim service is currently performed ', and after receiving information fed back by the service system, the server performs word segmentation on the feedback information, specifically, a preset natural language processing model can be used to perform word segmentation on the received feedback information, such as that the word segmentation result is currently/correctly/insurance claim/service/currently/continuously/or continuously, and further, each word segmentation corresponding to the feedback information is matched with each pre-constructed insurance claim service node, because the word segmentation ' in the feedback information is matched with the audit service node, it can therefore be determined that insurance claim settlement services are currently at the audit node.
Furthermore, after determining the current service node of the service to be processed, the server may send the service node to the client, and the client may show the current service node of the service to be processed to the user in a progress bar manner, and may inform the user of the current service node of the service to be processed in a short message or a WeChat manner, so that the user can know the service progress in time and realize transparent display of the service processing flow.
The following describes the process of pushing the insurance claim aging for the user in detail by taking the insurance claim service as an example, but not limited thereto.
When a user applies for an insurance claim service at a user end, corresponding report information is firstly filled in, bill data is uploaded at the same time, after the user confirms and submits the report information and the uploaded data, a primary auditing system carries out primary auditing according to the report information and the uploaded data filled in by the user and gives a primary auditing conclusion, then the insurance claim service enters an accounting service node, entry and accounting are carried out according to the report information, the data, the primary auditing conclusion and the like of the user and corresponding auditing conclusion is given, further, the report information, the data, the primary auditing conclusion and the auditing conclusion of the entry and accounting of the user are input into a preset claim aging prediction model together for prediction of claim aging, wherein the number of the preset claim aging prediction models can be multiple, such as a first claim aging prediction model, a second claim aging prediction model and a third claim aging prediction model, the first claim aging prediction model, the second claim aging prediction model and the third claim aging prediction model may be specifically a 24-hour claim aging prediction model, a 48-hour claim aging prediction model and a 72-hour claim aging prediction model, but is not limited thereto.
Further, the application information, the data, the preliminary examination conclusion and the examination conclusion of the input settlement calculation of the user are respectively input into a first claim aging prediction model, a second claim aging prediction model and a third claim aging prediction model to predict the claim aging, specifically, whether the insurance claim service meets the risk condition of a preset claim aging prediction model is judged, if yes, a corresponding aging label is printed on the insurance claim service, in the process of performing aging prediction on the insurance claim service by using the first claim aging prediction model, whether the proposal mode corresponding to the insurance claim service meets the proposal mode requirement is firstly judged, if yes, whether the preliminary examination conclusion meets the corresponding preliminary examination conclusion requirement is judged, if yes, whether the insurance responsibility corresponding to the insurance claim service meets the insurance responsibility requirement is judged, if yes, the amount of money corresponding to a single invoice outpatient invoice in the data uploaded by the user is judged to be smaller than a first preset amount, if the sum of the first preset invoice is less than the sum of the first preset invoice, whether the disease name corresponding to the insurance claim service meets the requirement of the disease name is judged, if so, whether the settlement conclusion corresponding to the insurance claim service meets the requirement of the settlement conclusion is judged, if so, whether the first settlement total sum is less than the first preset settlement sum is judged, if so, whether the invoice type corresponding to the insurance claim service meets the requirement of the invoice type is judged, and if so, an aging label corresponding to the first claim aging prediction model is printed on the insurance claim service.
In the process of carrying out aging prediction on an insurance claim service by using a third claim aging prediction model, firstly, whether the scheme setting mode corresponding to the insurance claim service meets the scheme setting mode requirement is judged, if so, the primary review conclusion meets the corresponding primary review conclusion requirement is judged, if so, whether the insurance responsibility corresponding to the insurance claim service meets the insurance responsibility requirement is judged, if so, whether the invoice amount corresponding to a single outpatient invoice in the data uploaded by a user is smaller than the second preset invoice amount is judged, if so, the disease name corresponding to the insurance claim service meets the disease name requirement is judged, if so, whether the settlement conclusion corresponding to the insurance claim service meets the settlement conclusion requirement is judged, if so, whether the first total amount of settlement is smaller than the second preset amount is judged, and if the insurance claim settlement amount is less than the second preset settlement amount, marking an aging label corresponding to the third claim settlement aging prediction model for the insurance claim settlement service.
Meanwhile, in the process of insurance claim settlement service processing, the insurance claim settlement service may relate to service nodes such as initial review, input settlement, audit and recheck, when the insurance claim settlement service enters any service node, the server receives feedback information of the corresponding service node, determines the service node where the insurance claim settlement service is currently located based on the feedback information, and if the insurance claim settlement is determined to be in the audit service node, the audit service node is sent to the client, and the client can be displayed in a progress bar mode, so that a user can know the processing progress of the insurance claim settlement service in time. Furthermore, early warning can be performed at each service node, when the service personnel at each service node do not process the case for a long time or process the case for a long time, alarm information can be sent to the terminal of the corresponding service personnel or the terminal of the manager to remind the service personnel to process the case as soon as possible, or remind the manager to assist the corresponding service personnel to process the case, and the service personnel or the manager can be reminded in a system interface mode, a mail mode, social software mode, a telephone mode, a short message mode and the like.
The other data processing method provided by the embodiment of the invention can determine the current service node of the service to be processed according to the feedback information of the system while pushing the service processing timeliness to the user, and push the service node to the user, so that the user can know the processing progress of the service to be processed in time, and in addition, alarm information can be sent to service personnel on each service node to remind corresponding service personnel to process the service as soon as possible, thereby improving the service processing efficiency.
Further, as an implementation of the method shown in fig. 1, an embodiment of the present invention provides a pushing device for service processing aging, and as shown in fig. 3, the pushing device includes: an acquisition unit 31, a prediction unit 32, a determination unit 33, and a push unit 34.
The obtaining unit 31 may be configured to obtain service information corresponding to a service to be processed.
The prediction unit 32 may be configured to input the service information to a plurality of preset service processing aging prediction models respectively to perform aging prediction, so as to obtain an aging label corresponding to the service to be processed.
The determining unit 33 may be configured to determine, based on the aging label, a service processing aging corresponding to the service to be processed.
The pushing unit 34 may be configured to push the service processing timeliness to a user.
Further, as shown in fig. 4, in order to obtain the age label corresponding to the service to be processed, the predicting unit 32 includes: a determination module 321 and a marking module 322.
The determining module 321 may be configured to input the service information into a target preset service processing aging prediction model in the plurality of preset service processing aging prediction models, and determine whether the service information meets a risk condition corresponding to the target preset service processing aging prediction model.
The marking module 322 may be configured to mark an aging label matched with the target preset service processing aging prediction model for the service to be processed if the service information meets the risk condition.
In a specific application scenario, the determining unit 33 may be specifically configured to determine the service processing aging corresponding to the aging label as the service processing aging corresponding to the service to be processed.
In a specific application scenario, in order to construct a preset service processing aging prediction model, the apparatus further includes: a screening unit 35 and a construction unit 36.
The determining unit 33 may be further configured to determine a plurality of risk conditions according to the risk points in the business processing process.
The predicting unit 32 may be further configured to predict accuracy and recall rate corresponding to the plurality of risk conditions by using the processed historical services.
The screening unit 35 may be configured to screen a plurality of target risk conditions from the plurality of risk conditions based on the accuracy and the recall ratio.
The constructing unit 36 may be configured to combine the multiple target risk conditions based on the service processing timeliness of the historical services corresponding to the multiple target risk conditions, respectively, and construct the multiple preset service processing timeliness prediction models.
Further, the building unit 36 includes: a statistics module 361, a determination module 362 and a construction module 363.
The counting module 361 may be configured to count historical traffic volumes under different service processing timeliness based on the service processing timeliness of the historical services corresponding to the plurality of target risk conditions, respectively.
The determining module 362 may be configured to determine, according to the historical traffic volumes under the different service processing timeliness, a service processing timeliness corresponding to a highest historical traffic volume.
The determining module 362 may be further configured to determine, based on the service processing aging corresponding to the highest historical traffic volume, service processing aging applicable to each of the plurality of target risk conditions.
The constructing module 363 may be configured to combine the multiple target risk conditions based on the service processing timeliness respectively applicable to the multiple target risk conditions, and construct the multiple preset service processing timeliness prediction models.
In a specific application scenario, in order to allocate a service to be processed to a corresponding service person, the apparatus further includes: a dispensing unit 37.
The determining unit 33 may be further configured to determine a service priority corresponding to the service to be processed based on the service processing timeliness corresponding to the service to be processed.
The allocating unit 37 may be configured to allocate the service to be processed to a corresponding service person based on the service priority.
In a specific application scenario, in order to adjust the service priority corresponding to the service to be processed, the apparatus further includes an increasing unit 38.
The determining unit 33 may be further configured to determine a service retention time corresponding to the service to be processed.
The increasing unit 38 may be configured to increase the service priority corresponding to the service to be processed if the service retention time exceeds a preset service retention time.
Further, in order to remind the corresponding service staff to process the service as soon as possible, the obtaining unit 31 may be further configured to obtain a processing duration of the service staff for the case to be processed currently.
The pushing unit 34 may be further configured to send an alarm message to the terminal of the service staff if the processing duration exceeds a preset processing duration.
Further, in order to push the service node where the service to be processed is currently located to the user, the apparatus further includes: a receiving unit 39.
The receiving unit 39 may be configured to receive feedback information of the service to be processed in the service processing process under the corresponding service node.
The determining unit 33 may be further configured to match the feedback information with each service node that is constructed in advance, and determine a target service node where the service to be processed is currently located according to a matching result.
The pushing unit 34 may be further configured to push the target service node to a user.
Based on the methods shown in fig. 1 and fig. 2, correspondingly, the embodiment of the invention further provides a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the methods shown in fig. 1 to fig. 2.
Based on the above embodiments of the method shown in fig. 1 and the apparatus shown in fig. 3, an embodiment of the present invention further provides an entity structure diagram of a computer device, as shown in fig. 5, where the computer device includes: a processor 41, a memory 42, and a computer program stored on the memory 42 and executable on the processor, wherein the memory 42 and the processor 41 are both arranged on a bus 43 such that the processor 41 implements the method as shown in fig. 1-2 when executing the program.
By the technical scheme, the invention can acquire the service information corresponding to the service to be processed; respectively inputting the service information into a plurality of preset service processing aging prediction models to perform aging prediction, and obtaining aging labels corresponding to the services to be processed; meanwhile, determining the service processing timeliness corresponding to the service to be processed based on the timeliness label; and finally, the service processing timeliness is pushed to the user, so that the processing timeliness of the service to be processed can be predicted through a plurality of preset service processing timeliness prediction models, and the processing timeliness can be pushed to the user, so that the user can clearly learn the processing timeliness of the case handled by the user, the user experience can be enhanced, and the satisfaction degree of the user is improved.
In the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts in the embodiments are referred to each other. For the system embodiment, since it basically corresponds to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The method and system of the present invention may be implemented in a number of ways. For example, the methods and systems of the present invention may be implemented in software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order for the steps of the method is for illustrative purposes only, and the steps of the method of the present invention are not limited to the order specifically described above unless specifically indicated otherwise. Furthermore, in some embodiments, the present invention may also be embodied as a program recorded in a recording medium, the program including machine-readable instructions for implementing a method according to the present invention. Thus, the present invention also covers a recording medium storing a program for executing the method according to the present invention.
The description of the present invention has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to practitioners skilled in this art. The embodiment was chosen and described in order to best explain the principles of the invention and the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.

Claims (10)

1. The utility model provides a pusher of business processing ageing which characterized in that includes:
the acquisition unit is used for acquiring service information corresponding to the service to be processed;
the prediction unit is used for respectively inputting the service information to a plurality of preset service processing aging prediction models for aging prediction to obtain aging labels corresponding to the services to be processed;
the determining unit is used for determining the service processing timeliness corresponding to the service to be processed based on the timeliness label;
and the pushing unit is used for pushing the service processing timeliness to a user.
2. The apparatus of claim 1, wherein the prediction unit comprises: a judging module and a marking module, wherein the judging module is used for judging whether the marking module is used for marking the mark,
the judging module is used for inputting the service information into a target preset service processing aging prediction model in the plurality of preset service processing aging prediction models and judging whether the service information meets a risk condition corresponding to the target preset service processing aging prediction model;
and the marking module is used for marking an aging label matched with the target preset service processing aging prediction model for the service to be processed if the service information meets the risk condition.
3. The apparatus of claim 2,
the determining unit is specifically configured to determine the service processing aging corresponding to the aging label as the service processing aging corresponding to the service to be processed.
4. The apparatus of claim 1, further comprising: a screening unit and a construction unit,
the determining unit is further configured to determine a plurality of risk conditions according to the risk points in the service processing process;
the prediction unit is further configured to predict accuracy and recall rate corresponding to the plurality of risk conditions by using the processed historical services;
the screening unit is used for screening a plurality of target risk conditions from the plurality of risk conditions based on the accuracy and the recall rate;
the construction unit is configured to combine the multiple target risk conditions based on the service processing timeliness of the historical services respectively corresponding to the multiple target risk conditions, and construct the multiple preset service processing timeliness prediction models.
5. The apparatus of claim 4, wherein the building unit comprises: a statistic module, a determining module and a constructing module,
the statistical module is used for counting the historical service volume under different service processing timeliness based on the service processing timeliness of the historical services respectively corresponding to the target risk conditions;
the determining module is used for determining the service processing timeliness corresponding to the highest historical service quantity according to the historical service quantities under the different service processing timeliness;
the determining module is further configured to determine, based on the service processing timeliness corresponding to the highest historical service volume, service processing timeliness to which the plurality of target risk conditions are respectively applicable;
the construction module is used for combining the target risk conditions based on the service processing timeliness respectively applicable to the target risk conditions to construct the preset service processing timeliness prediction models.
6. The apparatus of claim 1, further comprising: the distribution unit is used for distributing the data,
the determining unit is further configured to determine a service priority corresponding to the service to be processed based on the service processing timeliness corresponding to the service to be processed;
and the distribution unit is used for distributing the service to be processed to corresponding service personnel based on the service priority.
7. The apparatus of claim 6, further comprising: the lifting unit is used for lifting the air conditioner,
the determining unit is further configured to determine a service retention time corresponding to the service to be processed;
and the raising unit is used for raising the service priority corresponding to the service to be processed if the service retention time exceeds the preset service retention time.
8. A pushing method for service processing aging is characterized by comprising the following steps:
acquiring service information corresponding to a service to be processed;
respectively inputting the service information into a plurality of preset service processing aging prediction models to perform aging prediction, and obtaining aging labels corresponding to the services to be processed;
determining service processing timeliness corresponding to the service to be processed based on the timeliness label;
and pushing the service processing timeliness to a user.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method as claimed in claim 8.
10. A computer arrangement comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the computer program realizes the steps of the method as claimed in claim 8 when executed by the processor.
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