CN113537574B - Service processing aging pushing method and device, storage medium and computer equipment - Google Patents

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

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CN113537574B
CN113537574B CN202110700507.8A CN202110700507A CN113537574B CN 113537574 B CN113537574 B CN 113537574B CN 202110700507 A CN202110700507 A CN 202110700507A CN 113537574 B CN113537574 B CN 113537574B
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service
processed
aging
processing
timeliness
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CN113537574A (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 Shuidi Technology Group Co ltd
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    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract

The invention discloses a pushing method, a pushing device, a storage medium and computer equipment for service processing timeliness, which relate to the technical field of information and mainly can predict the processing timeliness of a service handled by a user and timely push the service processing timeliness to the user, so that the user can clearly learn the processing timeliness of the service 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 to obtain aging labels corresponding to the service to be processed; determining service processing timeliness corresponding to the service to be processed based on the timeliness label; and pushing the service processing time to the user. The method and the device are suitable for pushing service processing timeliness.

Description

Service processing aging pushing method and device, storage medium and computer equipment
Technical Field
The present invention relates to the field of information technologies, and in particular, to a service processing aging pushing method, device, storage medium, and computer equipment.
Background
With the continuous development of information technology, users can transact services in an online mode without going out, and the service platform processes the services according to the service data provided by the users and feeds back the service processing results to the users in an online mode.
At present, after a user applies for service handling on a service platform, the processing timeliness of the service handled by the user is generally presumed according to service clauses. However, the specificity of the terms of the business is strong, and the user is likely to erroneously analyze the contents of the terms of the business, thereby causing the user to be unable to clearly learn about the processing timeliness of the transacted business.
Disclosure of Invention
In view of the above, the present invention provides a pushing method, device, storage medium and computer device for service processing timeliness, which are mainly capable of predicting the processing timeliness of a service handled by a user and timely pushing the service processing timeliness to the user, so that the user can clearly learn the processing timeliness of the service handled by the user.
According to one aspect of the present invention, there is provided a push method for service processing aging, 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 to obtain aging labels corresponding to the service to be processed;
Determining service processing timeliness corresponding to the service to be processed based on the timeliness label;
and pushing the service processing time to the user.
Optionally, the step of inputting the service information into a plurality of preset service processing aging prediction models to perform aging prediction to obtain aging labels corresponding to the to-be-processed service includes:
inputting the service information into a target preset service processing timeliness prediction model in the plurality of 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 or not;
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, service processing aging corresponding to the service to be processed includes:
and determining service processing aging corresponding to the aging label as service processing aging corresponding to the service to be processed.
Optionally, before the obtaining the service information corresponding to the service to be processed, the method further includes:
Determining a plurality of risk conditions according to the risk points in the business processing process;
predicting the accuracy and recall rate corresponding to the multiple risk conditions respectively by using the processed history service;
screening a plurality of target risk conditions from the plurality of risk conditions based on the accuracy rate and recall rate;
and combining the target risk conditions based on service processing timeliness of the historical service corresponding to the target risk conditions respectively, and constructing a plurality of preset service processing timeliness prediction models.
Optionally, the step of combining the plurality of target risk conditions based on service processing aging of the historical service corresponding to the plurality of target risk conditions respectively, and constructing the plurality of preset service processing aging prediction models includes:
based on service processing timeliness of the historical service respectively corresponding to the target risk conditions, statistics is carried out on historical service volumes under different service processing timeliness;
according to the historical traffic under the different traffic treatment timelines, determining the traffic treatment timelines corresponding to the highest historical traffic;
determining service processing timeliness suitable for the target risk conditions respectively based on the service processing timeliness corresponding to the highest historical service volume;
And combining the target risk conditions based on service processing timeliness respectively applicable to the target risk conditions to construct the preset service processing timeliness prediction models.
Optionally, after determining that the service corresponding to the service to be processed is aged based on the aging label, the method further includes:
determining service priority corresponding to the service to be processed based on 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 the service priority corresponding to the service to be processed is determined based on 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, carrying out lifting treatment on the service priority corresponding to the service to be treated.
Optionally, 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.
Optionally, after determining that the service corresponding to the service to be processed is aged 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 constructed in advance, and determining a target service node where the service to be processed is currently located according to a matching result;
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 into a plurality of preset service processing aging prediction models to perform aging prediction to obtain aging labels corresponding to the service to be processed;
the determining unit is used for determining 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 time to the user.
Optionally, the prediction unit includes: the judging module and the marking module are used for judging whether the marking is performed on the marking paper,
the judging module is used for inputting the service information into a target preset service processing timeliness prediction model in the plurality of preset service processing timeliness prediction models and judging whether the service information meets the risk condition corresponding to the target preset service processing timeliness prediction model or not;
and the marking module is used for marking the service to be processed with an aging label matched with the target preset service processing aging prediction model if the service information meets the risk condition.
Optionally, the determining unit is specifically configured to determine service processing aging corresponding to the aging label as 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 used for determining a plurality of risk conditions according to the risk points in the business processing process;
the prediction unit is further used for predicting the accuracy and recall rate corresponding to the multiple risk conditions respectively by using the processed history service;
the screening unit is used for screening a plurality of target risk conditions from the plurality of risk conditions based on the accuracy rate and the recall rate;
The construction unit is configured to combine the plurality of target risk conditions based on service processing timeliness of the historical service corresponding to the plurality of target risk conditions, and construct the plurality of preset service processing timeliness prediction models.
Optionally, the building unit comprises: the statistics module, the determination module and the construction module,
the statistics module is used for counting the historical traffic under different service treatment timeouts based on service treatment timeouts of the historical services respectively corresponding to the target risk conditions;
the determining module is used for determining service processing timeliness corresponding to the highest historical service volume according to the historical service volumes under different service processing timeliness;
the determining module is further configured to determine service processing timeliness that the plurality of target risk conditions are respectively applicable based on service processing timeliness corresponding to the highest historical service volume;
the construction module is configured to combine the plurality of target risk conditions based on service processing timeliness that the plurality of target risk conditions are respectively applicable, and construct the plurality of preset service processing timeliness prediction models.
Optionally, the apparatus further comprises: the dispensing unit is configured to dispense the liquid,
The determining unit is further configured to determine a service priority corresponding to the service to be processed based on service processing timeliness corresponding to the service to be processed;
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 unit is lifted up and the air conditioner is moved up,
the determining unit is further configured to determine a service retention time length corresponding to the service to be processed;
and the lifting unit is used for lifting the service priority corresponding to the service to be processed if the service retention time exceeds the preset service retention time.
Optionally, the acquiring unit is further configured to acquire a processing duration of the service personnel for the to-be-processed case currently;
the pushing unit is further configured to send alarm information to a terminal of the service personnel if the processing duration exceeds a preset processing duration.
Optionally, the apparatus further comprises: the receiving unit is configured to receive the received signal,
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 built in advance, and determine, according to a matching result, a target service node where the service to be processed is currently located;
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 to obtain aging labels corresponding to the service to be processed;
determining service processing timeliness corresponding to the service to be processed based on the timeliness label;
and pushing the service processing time to the 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 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 to obtain aging labels corresponding to the service to be processed;
determining service processing timeliness corresponding to the service to be processed based on the timeliness label;
And pushing the service processing time to the user.
Compared with the current method that a user presumes the processing timeliness of the processed business according to business clauses, the method and the device can acquire the business information corresponding to the business to be processed; the service information is respectively input into a plurality of preset service processing aging prediction models to conduct aging prediction, and an aging label corresponding to the service to be processed is obtained; meanwhile, based on the aging label, determining service processing aging corresponding to the service to be processed; and finally pushing the service processing timeliness 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 is pushed to the user, the user can clearly learn the processing timeliness of the case handled by the user, the user experience can be further enhanced, and the satisfaction degree of the user is improved.
The technical scheme of the invention is further described in detail through the drawings and the 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 may be more clearly understood from the following detailed description taken in conjunction with the accompanying drawings, in which:
fig. 1 shows a flowchart of a push method for service processing aging provided by an embodiment of the present invention;
fig. 2 shows a flowchart of another service processing aging push method provided by an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a push device for service processing aging according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of another service processing aging pushing device according to an embodiment of the present invention;
fig. 5 shows a schematic physical structure 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, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless it is specifically stated otherwise.
Meanwhile, it should be understood that the sizes of the respective parts shown in the drawings are not drawn in actual scale for convenience of description.
The following description of at least one exemplary embodiment is merely exemplary in nature and is in no way intended to limit the invention, its application, or uses.
Techniques, methods, and apparatus known to one 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 numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further discussion thereof is necessary 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, network personal computers, small computer systems, mainframe computer systems, and distributed cloud computing technology environments that include any of the foregoing, and the like.
A 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 implemented in a distributed cloud computing environment in which 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 computing system storage media including memory storage devices.
The embodiment of the invention provides a pushing method for service processing aging, as shown in fig. 1, which 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 an online platform, such as insurance claim service, the service information is data related to the service handled by the user, for example, when the service to be processed is the insurance claim service, the service information can be specific report information, reporting data, initial examination result, settlement conclusion and the like of the user. The embodiment of the invention is mainly applied to the scene of pushing service processing timeliness to the user. The execution main body of the embodiment of the invention is a device and equipment capable of predicting and pushing service processing timeliness, and can be particularly arranged at one side of a server.
For the embodiment of the invention, when the user applies for transacting the service at the user side, the service information required by transacting the service, including personal information, service type and the like of the user, is filled first, and according to the service requirement, the user can upload corresponding service data, such as corresponding reporting data, such as claim settlement documents, invoices and the like, in the claim settlement service. After the user completes 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, after receiving a service processing instruction triggered by the user, the server predicts service processing timeliness corresponding to the service to be processed according to the service information corresponding to the service to be processed and pushes the service processing timeliness to the user, so that the user can clearly learn the service processing timeliness of the applied service, the user is prevented from being in long-time unknown waiting, and 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 to obtain aging labels corresponding to the service to be processed.
The preset service treatment aging prediction model corresponds to a plurality of risk conditions, aging labels corresponding to different preset service treatment aging prediction models are different, if the aging label corresponding to the preset service treatment aging prediction model A is a 24-hour label, the aging label corresponding to the preset service treatment aging prediction model B is a 48-hour label, the aging label corresponding to the preset service treatment aging prediction model C is a 72-hour time mark, in addition, the number of the preset service treatment aging prediction models can be set according to actual service requirements, if 3 preset service treatment aging prediction models are built for the service A, and 5 preset service treatment aging prediction models are built for the service B, and the number of the preset service treatment aging prediction models is not limited in the embodiment of the invention.
For the embodiment of the present invention, in order to obtain the aging 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 plurality of 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 or not; 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 aging prediction model is any model in the preset service processing aging 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 time-efficiency prediction models, namely a preset service processing time-efficiency prediction model 1 and a preset service processing time-efficiency prediction model 2, wherein the preset service processing time-efficiency prediction model 1 is a model which can be set for 24 hours, the preset service processing time-efficiency prediction model 2 is a model which can be set for 48 hours, the preset service processing time-efficiency prediction model 1 comprises a risk condition a and a risk condition b, the preset service processing time-efficiency prediction model 2 comprises a risk condition d and a risk condition e, the service information corresponding to the service to be processed is input into the preset service processing time-efficiency prediction model 1, 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 is judged respectively, if the service information corresponding to the service to be processed meets the risk condition a, the risk condition b and the risk condition c, the service information corresponding to the service to be processed is marked for 24 hours, the service information corresponding to the service to be processed is input into the preset service processing time-efficiency prediction model 2, and if the service information corresponding to be processed meets the risk condition d, the risk condition e and the risk condition b and the risk condition c, and the risk condition f is small, and the risk condition 48 is judged if the label is small, and the label corresponding to the risk information is marked for the service to be processed is small.
103. And determining 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 service processing timeliness corresponding to the service to be processed, step 103 specifically includes: and determining service processing aging corresponding to the aging label as service processing aging corresponding to the service to be processed. If the service to be processed only meets the risk condition corresponding to the preset service processing aging prediction model, an aging label matched with the preset service processing aging prediction model is marked on the service to be processed, service processing aging corresponding to the service to be processed is determined according to service processing aging in the aging label, if the unique aging label corresponding to the service to be processed is a 24-time aging label, service processing aging corresponding to the service to be processed is determined to be 24 hours, namely the service is required to be processed after 24 hours, and a processing result is fed back to a user.
104. And pushing the service processing time to the 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 a plurality of preset service processing timeliness prediction models, and the service processing timeliness is pushed to the user, specifically, the service processing timeliness of the service processed by the user can be sent to the mobile phone of the user in a short message mode, and the predicted service processing timeliness can also be pushed to the user through WeChat or other APP (application) and the like, so that the user can clearly learn the processing timeliness of the service processed by the user, further the user experience can be enhanced, and the satisfaction degree of the user is improved.
Compared with the current method that a user presumes the processing timeliness of the processed business according to business clauses, the pushing method of the business processing timeliness provided by the embodiment of the invention can acquire the business information corresponding to the business to be processed; the service information is respectively input into a plurality of preset service processing aging prediction models to conduct aging prediction, and an aging label corresponding to the service to be processed is obtained; meanwhile, based on the aging label, determining service processing aging corresponding to the service to be processed; and finally pushing the service processing timeliness 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 is pushed to the user, the user can clearly learn the processing timeliness of the case handled by the user, the user experience can be further enhanced, and the satisfaction degree of the user is improved.
Further, in order to better explain the foregoing process of predicting service processing aging, as a refinement and extension to the foregoing embodiment, an embodiment of the present invention provides another pushing method of service processing aging, as shown in fig. 2, where the method includes:
201. and acquiring service information corresponding to the service to be processed.
For the embodiment of the present invention, before predicting service processing aging corresponding to a service to be processed by using a plurality of preset service processing aging prediction models, a preset service processing aging prediction model needs to be built in advance, and as an optional embodiment, the method includes: determining a plurality of risk conditions according to the risk points in the business processing process; predicting the accuracy and recall rate corresponding to the multiple risk conditions respectively by using the processed history service; screening a plurality of target risk conditions from the plurality of risk conditions based on the accuracy rate and recall rate; and combining the target risk conditions based on service processing timeliness of the historical service corresponding to the target risk conditions respectively, and constructing a plurality of preset service processing timeliness prediction models. Further, the service processing aging based on the history service corresponding to the target risk conditions respectively combines the target risk conditions to construct the preset service processing aging prediction models, which includes: based on service processing timeliness of the historical service respectively corresponding to the target risk conditions, statistics is carried out on historical service volumes under different service processing timeliness; according to the historical traffic under the different traffic treatment timelines, determining the traffic treatment timelines corresponding to the highest historical traffic; determining service processing timeliness suitable for the target risk conditions respectively based on the service processing timeliness corresponding to the highest historical service volume; and combining the target risk conditions based on service processing timeliness respectively applicable to the target risk conditions to construct the preset service processing timeliness prediction models.
The risk point may be determined according to a specific service type, for example, in a insurance claim service, the risk point may specifically refer to a settlement point, a refusal point, and the like, and further, according to the saving point and the risk point, a risk condition may be determined, for example, whether the primary review is labeled as the saving point, whether the primary review is labeled as the refusal point, and the like.
In a specific application scene, the accuracy and recall rate of a plurality of risk conditions can be tested by using the processed historical service, a plurality of target risk conditions are screened out from the plurality of risk conditions according to the accuracy and recall rate of each risk condition, and further, a plurality of preset service processing aging prediction models are constructed by combining the screened plurality of target risk conditions. For example, a plurality of target risk conditions selected from a plurality of risk conditions are a risk condition a, a risk condition b, a risk condition c, a risk condition d, a risk condition e and a risk condition f, further, service treatment timelines corresponding to the history service satisfying the risk condition a, service treatment timelines corresponding to the history service satisfying the risk condition b, service treatment timelines corresponding to the history service satisfying the risk condition c, service treatment timelines corresponding to the history service satisfying the risk condition d, service treatment timelines corresponding to the history service satisfying the risk condition e, and service treatment timelines corresponding to the history service satisfying the risk condition f are determined, then, the history service volumes under different service treatment timelines, such as the history service timelines corresponding to the risk condition a, are counted for 24 hours and 48 hours, and the history service volumes under different service treatment timelines, such as 300 pieces and 50 pieces for the risk condition b, 24 hours and 48 hours, are counted for each risk condition a, are determined; for the risk condition c, the historical traffic of 24 hours and 48 hours is counted to be 700 pieces and 200 pieces respectively; for the risk condition d, the historical traffic of 24 hours and 48 hours is counted to be 50 pieces and 400 pieces respectively; for the risk condition e, statistics is carried out on historical traffic of 100 pieces and 500 pieces in 24 hours and 48 hours respectively; for the risk condition f, the historical traffic of 24 hours and 48 hours is counted to be 200 and 700 respectively, so that the risk condition a, the risk condition b and the risk condition c can be determined to be more suitable for a model of 24 hours, the risk condition d, the risk condition e and the risk condition f are more suitable for a model of 48 hours, the risk condition a, the risk condition b and the risk condition c are further formed into a model of 24 hours, and the risk d, the risk condition e and the risk condition f are formed into a model of 48 hours.
202. And respectively inputting the service information into a plurality of preset service processing aging prediction models to perform aging prediction to obtain aging labels 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 an aging label corresponding to the service to be processed, and the specific process of aging prediction of the service to be processed is identical to that of step 102, which is not described herein.
203. And determining service treatment timeliness corresponding to the service to be treated based on the timeliness label, and pushing the service treatment timeliness to a user.
For the embodiment of the present invention, based on the aging label, the specific process of determining service aging corresponding to the service to be processed is identical to step 103, and will not be described in detail here.
204. And determining the service priority corresponding to the service to be processed based on service processing timeliness corresponding to the service to be processed.
The shorter the service treatment time, the higher the corresponding service priority, for example, the service priority corresponding to the service to be treated in 24 hours is higher than the service priority corresponding to the service to be treated in 48 hours. For the embodiment of the invention, after the service processing timeliness 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 timeliness 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, according to the service priority corresponding to the service to be processed, the processing sequence corresponding to the service to be processed is determined, the higher the service priority is, the earlier the corresponding processing sequence is, and then the service to be processed is distributed to corresponding service personnel for processing based on the determined processing sequence. For example, the service processing time corresponding to the service a to be processed is 24 hours, the service processing time corresponding to the service B to be processed is 48 hours, and according to the service processing time corresponding to the service a to be processed and the service processing time corresponding to the service B to be processed, 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 sequence of the service a to be processed is earlier than the processing sequence of the service B to be processed, so that the service a to be processed is preferentially allocated to corresponding service personnel for processing, and after the service a to be processed is allocated, 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 the service to be processed in the service pool is too long and is not allocated for a long time, the service priority corresponding to the service to be processed is raised so as to allocate the service to be processed to corresponding service personnel for timely processing, based on this, after 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 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, carrying out lifting treatment on the service priority corresponding to the service to be treated. The preset service retention time can be set according to service requirements.
For example, the service processing time corresponding to the service to be processed is 72 hours, the corresponding preset service retention time is 12 hours, if no special service personnel process the service to be processed for 14 hours, the service priority corresponding to the service to be processed can be increased, and in particular, the service priority corresponding to the service to be processed can be increased to the service priority corresponding to the service for 24 hours.
In a specific application scenario, if the 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 duration, the server sends an alarm message to a terminal of the service person to prompt the service person to grasp time for processing, based on which, after allocating the service to be processed 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 length can be set according to service requirements, for example, the preset processing time length is set to be 20 hours for the service completed in 24 hours; and setting the preset processing time length to be 44 hours for the service completed in 48 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 period exceeds the preset unprocessed time period, the server also sends alarm information to the terminal of the service personnel so as to remind the service personnel of processing the service as soon as possible.
In addition, in the process of processing the service, a plurality of service nodes may be involved, for example, in the process of protecting the claim settlement service, the service nodes such as initial examination, input and verification may be involved, if the processing time of the service on the corresponding service node exceeds the preset processing time, the server may also send alarm information to the terminal of the service personnel or the manager of the corresponding service node, so as to prompt the service personnel 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 be further pushed to a user, so that a service progress is displayed for the user at a client, so that a service flow is completely transparent, based on which, after determining that service processing corresponding to the service to be processed is aged 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 constructed in advance, and determining a target service node where the service to be processed is currently located according to a matching result; pushing the target service node to a user. The service nodes related to the insurance claim service comprise initial examination, input calculation, examination and the like, and 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, after the entry and the settlement are completed on the insurance claim service, the insurance claim service enters an audit service node, when the audit system receives the audit request of the insurance claim service, corresponding feedback information is sent to a server, for example, the audit of the insurance claim service is being performed, the server performs word segmentation processing on the feedback information after receiving the information fed back by the service system, and particularly, a preset natural language processing model can be used for word segmentation on the received feedback information, for example, the word segmentation result is that the insurance claim is being performed/is performed, further, each word segment corresponding to the feedback information is matched with each pre-constructed insurance claim service node, and the word segment 'audit' in the feedback information is matched with the audit service node, so that the insurance claim service can be determined to be currently in the audit node.
Further, after determining the service node where the service to be processed is currently located, the server may send the service node to the client, and the client may display the service node where the service to be processed is currently located to the user by means of a progress bar.
The following describes the process of pushing the insurance claim for the user to age, but not limited to this.
When a user applies for an insurance claim service, the user firstly fills corresponding report information, uploads the ticket data, and after the user confirms and submits the report information, the primary auditing system conducts primary auditing according to the report information filled by the user and the uploaded data and gives out a primary auditing conclusion, and then the insurance claim service enters an input claim service node, carries out input claim conclusion according to the report information, the data, the primary auditing conclusion and the like of the user and gives out corresponding auditing conclusion, and further, the report information, the data, the primary auditing conclusion and the input claim conclusion of the user are input into a preset claim ageing prediction model together to conduct prediction of claim ageing, wherein the number of the preset claim ageing prediction models can be a plurality of, such as a first claim ageing prediction model, a second claim ageing prediction model and a third claim ageing prediction model, the first claim ageing prediction model, the second claim ageing prediction model and the third claim ageing prediction model can be specific 24 hours, and 48 hours claim ageing prediction model and the claim ageing prediction model is not limited to the claim ageing prediction model.
Further, the report information, data, initial review conclusion and audit conclusion of the input settlement are respectively input into a first settlement aging prediction model, a second settlement aging prediction model and a third settlement aging prediction model are used for predicting the aging of the claims, whether the invoice amount corresponding to a bill Zhang Menzhen invoice in the data uploaded by the user is smaller than the first preset invoice amount or not is judged specifically, if so, a corresponding aging label is given to the bill, in the process of carrying out aging prediction on the insurance claim business by utilizing the first settlement aging prediction model, whether a setting mode corresponding to the insurance claim business meets the requirements of the setting mode is firstly judged, if yes, whether the initial review conclusion meets the corresponding initial review conclusion requirements is judged, if yes, whether the invoice amount corresponding to the insurance claim business meets the insurance responsibility requirements is judged, if yes, whether the invoice name corresponding to the insurance business is met, if yes, the invoice amount corresponding to the first settlement type is judged, and if yes, the invoice amount corresponding to the first settlement type is judged.
In the process of carrying out aging prediction on the insurance claim service by utilizing the third claim aging prediction model, firstly judging whether a case-setting mode corresponding to the insurance claim service meets the case-setting mode requirement, if so, judging whether the initial review conclusion meets the corresponding initial review conclusion requirement, if so, judging whether the insurance responsibility corresponding to the insurance claim service meets the insurance responsibility requirement, if so, judging whether the invoice amount corresponding to a bill Zhang Menzhen invoice in data uploaded by a user is smaller than a second preset invoice amount, if so, judging whether the disease name corresponding to the insurance claim service meets the disease name requirement, if so, judging whether the settlement conclusion corresponding to the insurance claim service meets the settlement conclusion requirement, if so, judging whether the total sum of the first settlement is smaller than the second preset settlement amount, and if so, marking the insurance claim service with an aging label corresponding to the third claim aging prediction model.
Meanwhile, in the process of processing the insurance claim service, the insurance claim service may involve service nodes such as initial examination, input and calculation, examination and rechecking, when the insurance claim service enters any service node, the server receives feedback information of the corresponding service node, determines the service node where the insurance claim service is currently located based on the feedback information, if it is determined that the insurance claim is in the examination service node, the examination service node is sent to the client, and the client can display the information in a mode of a progress bar, so that a user can know the processing progress of the insurance claim service in time. Furthermore, early warning can be performed at each service node, and when the service personnel on each service node does not process cases for a long time or processes cases for a long time, alarm information can be sent to the terminals of the corresponding service personnel or management personnel to remind the service personnel to process as soon as possible or remind the management personnel to assist the corresponding service personnel to process, and particularly, the service personnel or management personnel can be reminded in a mode of system interface, mail, social software, telephone, short message and the like.
According to the data processing method provided by the embodiment of the invention, when the service processing time is shortened, the service node where the service to be processed is currently located can be determined according to the feedback information of the system and is pushed 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 the corresponding service personnel to process the service as soon as possible, thereby improving the processing efficiency of the service.
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, as shown in fig. 3, where the device includes: an acquisition unit 31, a prediction unit 32, a determination unit 33 and a pushing unit 34.
The acquiring unit 31 may be configured to acquire service information corresponding to a service to be processed.
The prediction unit 32 may be configured to input 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 determining unit 33 may be configured to determine service processing timeliness corresponding to the service to be processed based on the timeliness label.
The pushing unit 34 may be configured to age-push the service processing to a user.
Further, as shown in fig. 4, in order to obtain the aging label corresponding to the service to be processed, the prediction unit 32 includes: a judging module 321 and a marking module 322.
The judging module 321 may be configured to input the service information to a target preset service processing aging prediction model of the multiple preset service processing aging prediction models, and judge 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 the service to be processed with an aging label that matches the target preset service processing aging prediction model if the service information meets the risk condition.
In a specific application scenario, the determining unit 33 may be specifically configured to determine service processing aging corresponding to the aging label as 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 device 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 risk points in the service processing procedure.
The prediction unit 32 may be further configured to predict an accuracy rate and a recall rate corresponding to the plurality of risk conditions respectively using the processed history service.
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 rate and recall rate.
The construction unit 36 may be configured to combine the plurality of target risk conditions based on service processing aging of the historical service corresponding to the plurality of target risk conditions, and construct the plurality of preset service processing aging prediction models.
Further, the construction unit 36 includes: statistics module 361, determination module 362, and construction module 363.
The statistics module 361 may be configured to count historical traffic under different service processing timeframes based on service processing timeframes of the historical services corresponding to the target risk conditions.
The determining module 362 may be configured to determine, according to the historical traffic under the different service processing ages, a service processing age corresponding to the highest historical traffic.
The determining module 362 may be further configured to determine service processing timeliness that the plurality of target risk conditions are respectively applicable based on the service processing timeliness corresponding to the highest historical traffic.
The construction module 363 may be configured to combine the plurality of target risk conditions based on service processing aging applicable to the plurality of target risk conditions, and construct the plurality of preset service processing aging prediction models.
In a specific application scenario, in order to distribute the service to be processed to the corresponding service personnel, 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 service processing timeliness corresponding to the service to be processed.
The allocation 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 elevating unit 38.
The determining unit 33 may be further configured to determine a service residence time duration corresponding to the service to be processed.
The raising unit 38 may be configured to raise the service priority corresponding to the service to be processed if the service residence time exceeds a preset service residence time.
Further, to remind the corresponding service personnel to process the service as soon as possible, the obtaining unit 31 may be further configured to obtain a processing duration of the service personnel for the to-be-processed case currently.
The pushing unit 34 may be further configured to send an alarm message to a terminal of the service personnel 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 under the corresponding service node in the service processing process.
The determining unit 33 may be further configured to match the feedback information with each service node that is previously constructed, and determine, according to a matching result, a target service node where the service to be processed is currently located.
The pushing unit 34 may be further configured to push the target service node to a user.
Based on the above-mentioned methods shown in fig. 1 and 2, correspondingly, the embodiment of the present 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 2.
Based on the embodiment of the method shown in fig. 1 and the device shown in fig. 3, the embodiment of the invention further provides a physical 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, the processor 41 implementing the method as shown in fig. 1-2 when executing the program.
By the technical scheme, the service information corresponding to the service to be processed can be obtained; the service information is respectively input into a plurality of preset service processing aging prediction models to conduct aging prediction, and an aging label corresponding to the service to be processed is obtained; meanwhile, based on the aging label, determining service processing aging corresponding to the service to be processed; and finally pushing the service processing timeliness 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 is pushed to the user, the user can clearly learn the processing timeliness of the case handled by the user, the user experience can be further enhanced, and the satisfaction degree of the user is improved.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different manner from other embodiments, so that the same or similar parts between the embodiments are mutually referred to. For system embodiments, the description is relatively simple as it essentially corresponds to method embodiments, and reference should be made to the description of method embodiments for relevant points.
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 by software, hardware, firmware, or any combination of software, hardware, firmware. The above-described sequence of steps for the method is for illustration only, and the steps of the method of the present invention are not limited to the sequence specifically described above unless specifically stated otherwise. Furthermore, in some embodiments, the present invention may also be embodied as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods 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 those of ordinary skill in the art. The embodiments were 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 (16)

1. A push device for service processing aging, comprising:
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 into a plurality of preset service processing aging prediction models to perform aging prediction to obtain aging labels corresponding to the service to be processed;
the determining unit is used for determining service processing timeliness corresponding to the service to be processed based on the timeliness label;
the pushing unit is used for pushing the service processing time effect to the user;
the apparatus further comprises: a screening unit and a construction unit,
the determining unit is further used for determining a plurality of risk conditions according to the risk points in the business processing process;
The prediction unit is further used for predicting the accuracy and recall rate corresponding to the multiple risk conditions respectively by using the processed history service;
the screening unit is used for screening a plurality of target risk conditions from the plurality of risk conditions based on the accuracy rate and the recall rate;
the construction unit is used for combining the target risk conditions based on service processing timeliness of the historical service corresponding to the target risk conditions respectively to construct the preset service processing timeliness prediction models;
the construction unit includes: the statistics module, the determination module and the construction module,
the statistics module is used for counting the historical traffic under different service treatment timeouts based on service treatment timeouts of the historical services respectively corresponding to the target risk conditions;
the determining module is used for determining service processing timeliness corresponding to the highest historical service volume according to the historical service volumes under different service processing timeliness;
the determining module is further configured to determine service processing timeliness that the plurality of target risk conditions are respectively applicable based on service processing timeliness corresponding to the highest historical service volume;
The construction module is configured to combine the plurality of target risk conditions based on service processing timeliness that the plurality of target risk conditions are respectively applicable, and construct the plurality of preset service processing timeliness prediction models.
2. The apparatus of claim 1, wherein the prediction unit comprises: the judging module and the marking module are used for judging whether the marking is performed on the marking paper,
the judging module is used for inputting the service information into a target preset service processing timeliness prediction model in the plurality of preset service processing timeliness prediction models and judging whether the service information meets the risk condition corresponding to the target preset service processing timeliness prediction model or not;
and the marking module is used for marking the service to be processed with an aging label matched with the target preset service processing aging prediction model if the service information meets the risk condition.
3. The apparatus of claim 2, wherein the device comprises a plurality of sensors,
the determining unit is specifically configured to determine service processing aging corresponding to the aging label as service processing aging corresponding to the service to be processed.
4. The apparatus of claim 1, wherein the apparatus further comprises: the dispensing unit is configured to dispense the liquid,
The determining unit is further configured to determine a service priority corresponding to the service to be processed based on service processing timeliness corresponding to the service to be processed;
the distribution unit is used for distributing the service to be processed to corresponding service personnel based on the service priority.
5. The apparatus of claim 4, wherein the apparatus further comprises: the unit is lifted up and the air conditioner is moved up,
the determining unit is further configured to determine a service retention time length corresponding to the service to be processed;
and the lifting unit is used for lifting the service priority corresponding to the service to be processed if the service retention time exceeds the preset service retention time.
6. The apparatus of claim 4, wherein the device comprises a plurality of sensors,
the obtaining unit is further configured to obtain a processing duration of the service personnel for the case to be processed currently;
the pushing unit is further configured to send alarm information to a terminal of the service personnel if the processing duration exceeds a preset processing duration.
7. The apparatus of claim 1, wherein the apparatus further comprises: the receiving unit is configured to receive the received signal,
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 built in advance, and determine, according to a matching result, a target service node where the service to be processed is currently located;
the pushing unit is further configured to push the target service node to a user.
8. The push 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 to obtain aging labels corresponding to the service to be processed;
determining service processing timeliness corresponding to the service to be processed based on the timeliness label;
pushing the service treatment time to a user;
before the service information corresponding to the service to be processed is obtained, the method further comprises the following steps:
determining a plurality of risk conditions according to the risk points in the business processing process;
predicting the accuracy and recall rate corresponding to the multiple risk conditions respectively by using the processed history service;
screening a plurality of target risk conditions from the plurality of risk conditions based on the accuracy rate and recall rate;
based on service processing timeliness of the historical service respectively corresponding to the target risk conditions, combining the target risk conditions, and constructing a plurality of preset service processing timeliness prediction models;
The service processing aging based on the history service corresponding to the target risk conditions respectively combines the target risk conditions to construct the preset service processing aging prediction models, including:
based on service processing timeliness of the historical service respectively corresponding to the target risk conditions, statistics is carried out on historical service volumes under different service processing timeliness;
according to the historical traffic under the different traffic treatment timelines, determining the traffic treatment timelines corresponding to the highest historical traffic;
determining service processing timeliness suitable for the target risk conditions respectively based on the service processing timeliness corresponding to the highest historical service volume;
and combining the target risk conditions based on service processing timeliness respectively applicable to the target risk conditions to construct the preset service processing timeliness prediction models.
9. The method of claim 8, wherein the step of inputting the service information into a plurality of preset service processing aging prediction models to perform aging prediction to obtain aging labels corresponding to the service to be processed includes:
inputting the service information into a target preset service processing timeliness prediction model in the plurality of 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 or not;
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.
10. The method of claim 9, wherein the determining, based on the aging tag, a service processing aging corresponding to the service to be processed comprises:
and determining service processing aging corresponding to the aging label as service processing aging corresponding to the service to be processed.
11. The method of claim 8, wherein after the determining, based on the aging tag, that the service corresponding to the service to be processed is aged, the method further comprises:
determining service priority corresponding to the service to be processed based on 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.
12. The method of claim 11, wherein after the determining the service priority corresponding to the pending service based on the service processing age corresponding to the pending service, the method further comprises:
determining a service retention time corresponding to the service to be processed;
And if the service retention time exceeds the preset service retention time, carrying out lifting treatment on the service priority corresponding to the service to be treated.
13. The method of claim 11, wherein after said assigning said pending service to a corresponding service person based on said service priority, said method further comprises:
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.
14. The method of claim 8, wherein after the determining, based on the aging tag, that the service corresponding to the service to be processed is aged, the method further comprises:
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 constructed in advance, and determining a target service node where the service to be processed is currently located according to a matching result;
pushing the target service node to a user.
15. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 8 to 14.
16. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the computer program when executed by the processor implements the steps of the method of any of claims 8 to 14.
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