CN111582763A - Insurance achievement data monitoring method and device - Google Patents
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Abstract
The invention discloses an insurance achievement data monitoring method and device, wherein the method comprises the following steps: acquiring insurance performance data and corresponding monitoring types, wherein the monitoring types comprise: monitoring for T +1 day and monitoring in real time; determining monitoring index data according to the insurance performance data and the corresponding monitoring type; monitoring insurance performance data according to the monitoring index data and a preset index threshold, wherein if the monitoring type is monitoring for T +1 day, the index threshold is preset according to an insurance type label; and if the monitoring type is real-time monitoring, the index threshold value is preset according to the timeliness grade label. The invention can effectively monitor the abnormal condition of the insurance performance data, saves manpower and material resources and improves the efficiency of monitoring the performance data and the accuracy of the result.
Description
Technical Field
The invention relates to the technical field of data monitoring, in particular to an insurance performance data monitoring method and device.
Background
The development of the current mobile network provides a rapid channel for the high-speed development of information, data informatization is a huge task and mission of a data department, the stability and the reliability of data are ensured, and the foundation for realizing digital informatization is provided.
The performance data of the internet scenarized insurance is important data and is the final data export. The internet scene insurance is not only a traditional core system, but also an external cooperation access system, a cloud system and the like, and has complex scenes, which means that the data of the core system, the data of the peripheral system and the data of the cloud server resources exist, and the stability and the reliability of the performance data are influenced to a great extent by the existence of the data. Therefore, there is a need for effective monitoring of performance data for internet scenic insurance.
In the prior art, an operation and maintenance team usually monitors machine performance and task flow, wherein the monitoring of the machine performance includes monitoring of hardware such as a CPU, an IO, and a disk of the machine, the monitoring of the task flow is to write a normal log after the task flow is normally operated, and to push a data error mail to related personnel when the task flow is abnormal. And then, judging whether the performance data of the internet scene insurance is accurate and reliable or not according to the monitoring results of the machine performance and the task flow by combining experience values of data personnel, but the method needs the data personnel to carry out experience value judgment on each machine performance and task flow monitoring result one by one, so that not only is a large amount of manpower and material resources consumed, but also the accuracy of the obtained performance data monitoring result is not high, and the problem cannot be checked and fed back in time.
Disclosure of Invention
The embodiment of the invention provides an insurance performance data monitoring method, which is used for monitoring the abnormal condition of insurance performance data, saving manpower and material resources and improving the monitoring efficiency and the result accuracy of the insurance performance data, and comprises the following steps:
acquiring insurance performance data and corresponding monitoring types, wherein the insurance performance data comprises: one or any combination of insurance performance data of different risk categories, insurance performance data of different cause departments and insurance performance data of different scenes, wherein the monitoring types comprise: monitoring for T +1 day and monitoring in real time;
determining monitoring index data according to the insurance performance data and the corresponding monitoring type;
monitoring insurance performance data according to the monitoring index data and a preset index threshold, wherein if the monitoring type is monitoring for T +1 day, the index threshold is preset according to an insurance type label; and if the monitoring type is real-time monitoring, the index threshold value is preset according to the timeliness grade label.
The embodiment of the invention provides an insurance achievement data monitoring device, which is used for monitoring the abnormal condition of insurance achievement data, saving manpower and material resources and improving the efficiency of monitoring the insurance achievement data and the accuracy of results, and comprises:
the acquisition module is used for acquiring insurance performance data and corresponding monitoring types, wherein the insurance performance data comprises: one or any combination of insurance performance data of different risk categories, insurance performance data of different cause departments and insurance performance data of different scenes, wherein the monitoring types comprise: monitoring for T +1 day and monitoring in real time;
the data determination module is used for determining monitoring index data according to the insurance performance data and the corresponding monitoring type;
the monitoring module is used for monitoring insurance performance data according to the monitoring index data and a preset index threshold, wherein if the monitoring type is T +1 day monitoring, the index threshold is preset according to an insurance type label; and if the monitoring type is real-time monitoring, the index threshold value is preset according to the timeliness grade label.
The embodiment of the invention also provides computer equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor realizes the insurance performance data monitoring method when executing the computer program.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer program for executing the insurance performance data monitoring method is stored in the computer-readable storage medium.
Compared with the scheme of judging whether the insurance performance data is accurate and reliable or not according to the monitoring results of the machine performance and the task flow and by combining experience values of data personnel in the prior art, the embodiment of the invention acquires the insurance performance data and the corresponding monitoring types, wherein the insurance performance data comprises the following steps: one or any combination of insurance performance data of different risk categories, insurance performance data of different cause departments and insurance performance data of different scenes, wherein the monitoring types comprise: monitoring for T +1 day and monitoring in real time; determining monitoring index data according to the insurance performance data and the corresponding monitoring type; monitoring insurance performance data according to the monitoring index data and a preset index threshold, wherein if the monitoring type is monitoring for T +1 day, the index threshold is preset according to an insurance type label; and if the monitoring type is real-time monitoring, the index threshold value is preset according to the timeliness grade label. According to the embodiment of the invention, a data worker is not required to judge experience values of each machine performance and task flow monitoring result one by one, only an index threshold value is set in advance according to the monitoring type and historical insurance performance data, the monitoring index data is determined according to the insurance performance data and the corresponding monitoring type, and then the insurance performance data can be monitored according to the monitoring index data and the preset index threshold value, so that the abnormal condition of the insurance performance data is effectively monitored, manpower and material resources are saved, and the performance data monitoring efficiency and the result accuracy are improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:
FIG. 1 is a schematic diagram of a method for monitoring insurance performance data in accordance with an embodiment of the present invention;
FIG. 2 is a schematic diagram of insurance performance data in accordance with an embodiment of the present invention;
FIG. 3 is a diagram illustrating runtime data for a program in an embodiment of the present invention;
FIG. 4 is a schematic illustration of a time effectiveness level tag in an embodiment of the present invention;
FIG. 5 is a block diagram of an insurance performance data monitoring apparatus in accordance with an embodiment of the present invention;
FIG. 6 is a schematic diagram of an exemplary method for monitoring insurance performance data for indicator thresholds according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
In order to monitor abnormal situations of insurance performance data, save manpower and material resources, and improve performance data monitoring efficiency and result accuracy, an embodiment of the present invention provides an insurance performance data monitoring method, as shown in fig. 1, the method may include:
102, determining monitoring index data according to the insurance performance data and the corresponding monitoring type;
103, monitoring insurance performance data according to the monitoring index data and a preset index threshold, wherein if the monitoring type is T +1 day monitoring, the index threshold is preset according to an insurance type label; and if the monitoring type is real-time monitoring, the index threshold value is preset according to the timeliness grade label.
As can be seen from fig. 1, the embodiment of the present invention obtains insurance performance data and corresponding monitoring types, where the insurance performance data includes: one or any combination of insurance performance data of different risk categories, insurance performance data of different cause departments and insurance performance data of different scenes, wherein the monitoring types comprise: monitoring for T +1 day and monitoring in real time; determining monitoring index data according to the insurance performance data and the corresponding monitoring type; monitoring insurance performance data according to the monitoring index data and a preset index threshold, wherein if the monitoring type is monitoring for T +1 day, the index threshold is preset according to an insurance type label; and if the monitoring type is real-time monitoring, the index threshold value is preset according to the timeliness grade label. According to the embodiment of the invention, a data worker is not required to judge experience values of each machine performance and task flow monitoring result one by one, only an index threshold value is set in advance according to the monitoring type and historical insurance performance data, the monitoring index data is determined according to the insurance performance data and the corresponding monitoring type, and then the insurance performance data can be monitored according to the monitoring index data and the preset index threshold value, so that the abnormal condition of the insurance performance data is effectively monitored, manpower and material resources are saved, and the performance data monitoring efficiency and the result accuracy are improved.
In specific implementation, insurance performance data and a corresponding monitoring type are obtained, wherein the insurance performance data comprises: one or any combination of insurance performance data of different risk categories, insurance performance data of different cause departments and insurance performance data of different scenes, wherein the monitoring types comprise: monitoring for T +1 day and monitoring in real time.
In an embodiment, as shown in FIG. 2, the insurance performance data may include: the system comprises insurance performance data of different risk categories, insurance performance data of different departments and insurance performance data of different scenes, wherein the risk categories can comprise vehicle insurance, health insurance, accident insurance, comprehensive insurance, family insurance, enterprise insurance, responsibility insurance, freight insurance, credit guarantee insurance and the like, the departments can comprise health departments, Internet departments, vehicle insurance departments, direct operation departments and the like, and the scenes can comprise micro-insurance, easy planning, Ali and the like.
And in specific implementation, determining monitoring index data according to the insurance performance data and the corresponding monitoring type. Monitoring insurance performance data according to the monitoring index data and a preset index threshold, wherein if the monitoring type is monitoring for T +1 day, the index threshold is preset according to an insurance type label; and if the monitoring type is real-time monitoring, the index threshold value is preset according to the timeliness grade label.
In an embodiment, determining the monitoring index data according to the insurance performance data and the corresponding monitoring type includes: if the monitoring type is monitoring for T +1 day, extracting the program running time data of the insurance achievement data from a database, and determining monitoring index data according to the program running time data of the insurance achievement data; the insurance category label is determined from historical insurance performance data.
In the present embodiment, as shown in fig. 3, the program runtime data includes: program operation start time data and program operation completion time data. And if the monitoring type is T +1 day monitoring, extracting program operation starting time data and program operation finishing time data of the insurance achievement data from the database, calculating a difference value between the program operation finishing time data and the program operation starting time data, and obtaining a time metric value as monitoring index data.
In the present embodiment, insurance type tags corresponding to different types of insurance performance data, that is, different insurance performance data, different department insurance performance data, and different scene insurance performance data, are determined from the historical insurance performance data. The index threshold is preset according to the insurance type label. For example, the index threshold value of the tag corresponding to the insurance performance data of different insurance types and the index threshold value of the tag corresponding to the insurance performance data of different departments are set to 1 hour, and the index threshold value of the tag corresponding to the insurance performance data of different scenes is set to 30 minutes. Further, insurance performance data is monitored based on the monitoring index data and a preset index threshold. For example, when the difference between the program operation completion time data and the program operation start time data is smaller than the set index threshold, an alarm is given.
In an embodiment, determining the monitoring index data according to the insurance performance data and the corresponding monitoring type includes: if the monitoring type is real-time monitoring, extracting program running time data of the insurance achievement data from a database, and determining monitoring index data according to the program running time data of the insurance achievement data; the timeliness rating label is determined from historical insurance performance data.
In this embodiment, the program runtime data includes: program operation start time data and program operation completion time data. And if the monitoring type is real-time monitoring, extracting the program operation starting time data and the program operation finishing time data of the insurance achievement data from a database, calculating the difference value of the program operation finishing time data and the program operation starting time data, and obtaining a time measurement value as monitoring index data.
In this embodiment, as shown in fig. 4, the timeliness level tags are determined from the historical insurance performance data, and are divided into: high timeliness label, medium timeliness label, low timeliness label. The timeliness grade label can be determined through one or any combination of the number of times of accessing the presentation layer report in the historical insurance performance data, the access frequency and the calculated daily average access amount. And then setting an index threshold according to the timeliness grade label. For example, the high timeliness tab index threshold is set to 1 minute, the medium timeliness tab index threshold is set to 5 minutes, and the low timeliness tab index threshold is set to 15 minutes, and insurance performance data is monitored based on the monitoring index data and the preset index threshold. For example, when the difference between the program operation completion time data and the program operation start time data is smaller than the set index threshold, an alarm is given.
In an embodiment, determining the monitoring index data according to the insurance performance data and the corresponding monitoring type includes: if the monitoring type is T +1 day monitoring, KPI assessment data of the insurance performance data are extracted from a database, and the KPI assessment data comprise: a KPI current value and a KPI target value; determining monitoring index data according to the KPI current value and the KPI target value of the insurance performance data; the insurance performance data monitoring method further comprises the following steps: and monitoring insurance performance data according to the monitoring index data and a preset index threshold, wherein if the monitoring type is T +1 day monitoring, the index threshold is preset according to time sequence progress data, and the time sequence progress data is determined according to historical insurance performance data.
In this embodiment, a ratio of a current KPI value to a target KPI value of the insurance performance data is calculated to obtain a target KPI achievement value as monitoring indicator data. Determining the current days and the total days according to the historical insurance performance data, calculating the ratio of the days of the day to the total days to obtain time sequence progress data, comparing the KPI goal achievement value with the time sequence progress data, and giving an alarm when the KPI goal achievement value is lower than the time sequence progress data.
In this embodiment, determining the monitoring index data according to the insurance performance data and the corresponding monitoring type includes: determining monitoring index data according to the current value of KPI of the insurance performance data and the current days; the insurance performance data monitoring method further comprises the following steps: and monitoring insurance performance data according to the monitoring index data and a preset index threshold, wherein if the monitoring type is T +1 day monitoring, the index threshold is preset according to KPI target mean value data, and the KPI target mean value data is determined according to historical insurance performance data.
In this embodiment, the ratio of the current KPI value of the insurance performance data to the current day is calculated, and a KPI daily average is obtained as the monitoring indicator data. Determining total days according to historical insurance performance data, calculating the ratio of KPI target value to total days to obtain KPI target mean value, comparing KPI daily mean value with KPI target mean value, for example, when KPI daily mean value is lower than KPI target mean value, alarming.
In an embodiment, determining the monitoring index data according to the insurance performance data and the corresponding monitoring type includes: if the monitoring type is real-time monitoring, extracting the loading time data and the system time data of the insurance achievement data from a database, and determining monitoring index data according to the loading time data and the system time data of the insurance achievement data; the timeliness rating label is determined from historical insurance performance data.
In this embodiment, the difference between the loading time data of the insurance performance data and the system time data is calculated to obtain a time scale data as the monitoring index data. And determining a timeliness grade label according to the historical insurance performance data, wherein the index threshold is preset according to the timeliness grade label. For example, a database result table T is set, a timestamp field loadTime is added to the table to indicate the loading time data of the insurance performance data, and after the insurance performance data is calculated, the loading time data and related information are written into the database result table T. The timeliness level label of the historical insurance performance data is set according to the actual business scene, and can be divided into high-level, middle-level and low-level, wherein when the index threshold value is preset according to the timeliness level label, if the timeliness level label is high, the index threshold value is set to be 15 minutes, if the timeliness level label is middle, the index threshold value is set to be 30 minutes, if the timeliness level label is low, the index threshold value is set to be 60 minutes, and the index threshold value can be adjusted at any time according to the update frequency of the actual business scene data.
In this embodiment, monitoring insurance performance data according to the monitoring index data and a preset index threshold includes: and if the monitoring index data exceeds the index threshold value, sending an abnormal alarm signal. For example, the difference between the loading time of the insurance performance data and the system time is compared with an index threshold, if the difference between the loading time of the insurance performance data and the system time is greater than or equal to the set index threshold, the situation is defined as an abnormal situation, and an abnormal alarm signal is sent out. And setting a timing big data platform calling interface, and executing difference calculation of the loading time of the insurance achievement data and the system time once within 5 minutes.
In the embodiment, if abnormal conditions exist, the abnormal information can be pushed to the mobile terminal, and the information is not pushed when no abnormal conditions exist. When real-time monitoring content needs to be added newly, a new monitoring index needs to be configured first, the index is written into a database table, and the difference and the threshold are calculated to realize monitoring.
In an embodiment, determining the monitoring index data according to the insurance performance data and the corresponding monitoring type includes: and if the monitoring type is T +1 day monitoring, calculating the same ratio of the insurance performance data according to the insurance performance data. Day I parity was calculated as follows: day I iso-ratio (current day I insurance performance data-last year day I insurance performance data)/last year day I insurance performance data. The index threshold is preset as follows: if the monitoring type is monitoring for T +1 day, calculating the same-ratio values of a plurality of historical insurance achievement data to obtain a same-ratio value sequence; and presetting an index threshold according to the maximum value, the minimum value and the mean value of the comparation value sequence. For example, if the geometric value of a plurality of historical insurance performance data is calculated, and the minimum value is 0.74 and the maximum value is 1.49, the approximate interval is [0.7,1.5], and then the average value of the geometric value series of X consecutive days is taken, so that the index threshold value can be set in advance according to the maximum value, the minimum value and the average value of the geometric value series as follows: index threshold (mean of sequence of homologous values for X consecutive days) X [0.7,1.5 ].
In an embodiment, determining the monitoring index data according to the insurance performance data and the corresponding monitoring type includes: and if the monitoring type is T +1 day monitoring, calculating the ring ratio of the insurance performance data according to the insurance performance data. The ring ratio on day I was calculated as follows: day I ring ratio ═ day I insurance performance data- (day I-1 insurance performance data))/(day I-1 insurance performance data). The index threshold is preset as follows: if the monitoring type is monitoring for T +1 day, calculating ring ratio values of a plurality of historical insurance performance data to obtain a ring ratio value sequence; and presetting an index threshold according to the maximum value, the minimum value and the mean value of the ring ratio sequence. For example, when the loop ratio of a plurality of historical insurance performance data is calculated, and the minimum value is-0.47 and the maximum value is 1.81, the approximate interval is [ -0.5,1.9] can be obtained, and then the average value of the loop ratio sequence of X consecutive days is taken, so that the index threshold value can be preset according to the maximum value, the minimum value and the average value of the loop ratio sequence as follows: index threshold (mean of a sequence of loop ratios for X consecutive days) X [ -0.5,1.9 ].
In an embodiment, determining the monitoring index data according to the insurance performance data and the corresponding monitoring type includes: and if the monitoring type is T +1 day monitoring, calculating the mean value of the insurance achievement data according to the insurance achievement data. The mean of the insurance performance data is calculated as follows: and the average value of the insurance performance data is the sum of the insurance performance data for X consecutive days/X. The index threshold is preset as follows: if the monitoring type is T +1 day monitoring, calculating the average value of a plurality of groups of historical insurance performance data to obtain an average value sequence; and presetting an index threshold according to the maximum value and the minimum value of the mean value sequence. For example, the insurance performance data of this year is calculated by taking week as a unit, the average value of the historical insurance performance data of each week is obtained, the ratio of the maximum value and the minimum value of the average value sequence to the average value of the current year is about [0.6,0.8], and therefore, the index threshold value can be preset according to the maximum value and the minimum value of the average value sequence according to the following modes: the index threshold value is (sum of insurance performance data/X for X consecutive days) × [0.6,0.8 ].
In an embodiment, determining the monitoring index data according to the insurance performance data and the corresponding monitoring type includes: and if the monitoring type is T +1 day monitoring, taking the insurance achievement data as monitoring index data. The index threshold is preset as follows: if the monitoring type is monitoring for T +1 day, determining the maximum value and the minimum value in the plurality of historical insurance achievement data; and presetting an index threshold according to the maximum value and the minimum value in the plurality of historical insurance performance data. For example, when the maximum value and the minimum value in the historical insurance day performance data are obtained, the average value X of the maximum value and the minimum value is taken, and the index threshold value is preset, the range of the index threshold value is more than or equal to X.
In this embodiment, monitoring insurance performance data according to the monitoring index data and a preset index threshold includes: and if the monitoring index data exceeds the index threshold value, sending an abnormal alarm signal. For example, comparing the same ratio of the insurance performance data with the corresponding index threshold, the ring ratio with the corresponding index threshold, the mean value with the corresponding index threshold, and the insurance performance data with the corresponding index threshold, if the ratio exceeds the set index threshold, defining as an abnormal condition, sending an abnormal alarm signal, and writing the abnormal data into the abnormal value log information table.
In this embodiment, when there is an abnormality, the performance information of the WeChat is not pushed, and when there is no abnormality, the performance is pushed at regular time. Meanwhile, the visual page can be customized to display the monitoring index data, and the early warning font color is set for the monitoring index data with abnormity, so that the abnormal condition is prompted. When T +1 day monitoring content needs to be newly added, a new monitoring index needs to be configured at first, a risk model is established for the index, and a monitoring mechanism automatically operates every day.
Based on the same inventive concept, the embodiment of the present invention further provides an insurance performance data monitoring apparatus, as described in the following embodiments. Since the principles of these solutions are similar to the insurance performance data monitoring method, the implementation of the device can be referred to the implementation of the method, and the repeated details are not repeated.
Fig. 5 is a block diagram of an insurance performance data monitoring apparatus according to an embodiment of the present invention, as shown in fig. 5, the apparatus including:
an obtaining module 501, configured to obtain insurance performance data and a corresponding monitoring type, where the insurance performance data includes: one or any combination of insurance performance data of different risk categories, insurance performance data of different cause departments and insurance performance data of different scenes, wherein the monitoring types comprise: monitoring for T +1 day and monitoring in real time;
a data determining module 502, configured to determine monitoring index data according to the insurance performance data and the corresponding monitoring type;
the monitoring module 503 is configured to monitor insurance performance data according to the monitoring index data and a preset index threshold, where if the monitoring type is T +1 day monitoring, the index threshold is preset according to an insurance type label; and if the monitoring type is real-time monitoring, the index threshold value is preset according to the timeliness grade label.
A specific embodiment is given below to illustrate a specific application of the insurance performance data monitoring method in the embodiment of the present invention. In this specific embodiment, a monitoring type is first determined, and for an internet scene insurance T +1 day monitoring type, such as a newly added key scene service "mei qu", this scene service is currently from external system docking, and the controllable range of stability to the external system is small, so that a powerful monitoring measure is required to ensure the stability of data, and specific implementation steps are as follows: firstly, identifying a scene service 'Mei Gong' configuration item, belonging to a channel service, and identifying the configuration item according to a channel code, wherein the fromid code is 61326. As shown in fig. 6, the mei-agglomerant index threshold is calculated:
index threshold corresponding to the ratio: the time points were 2019, 6 months and 30 days, and the values of the beauty groups were 0.81, 0.85, 1.11, 1.01 and 0.92, respectively, and the index threshold was 0.7 × [0.7,1.5] ═ 0.49,1.05 ].
Index threshold corresponding to ring ratio: the time points are 30/6 in 2019 and 5 consecutive days, the ring ratio of the beauty mass is 4.35%, -16.67%, 13.00%, 9.73% and 2.42%, so that the average ring ratio of 5 consecutive days is 2.57%, and the index threshold value corresponding to the ring ratio is 0.0257 × [ -0.5,1.9] ═ 0.01285, 0.04883.
Index threshold corresponding to the mean value: the time points are 2019, 6 and 30 days, and the performance of the American group is 120 ten thousand, 100 ten thousand, 113 ten thousand, 124 ten thousand and 127 ten thousand respectively, so the average value of the continuous 5 days is 116.8 ten thousand, and the index threshold value corresponding to the average value is 116.8 x [0.6,0.8] ═ [70.08,93.44 ].
The index threshold corresponding to the insurance achievement data is as follows: the daily performance of the highest point in the year is 70 thousands, the daily performance of the lowest point in the history is 30 thousands, and a threshold value is set to be 50 thousands.
Comparing the same ratio, the ring ratio, the average value and the achievement of each item with corresponding index thresholds respectively, defining the items as abnormal when the values of the items are not in the threshold range, and writing an abnormal pool log information table for the abnormal items. When abnormal information exists in the log information table, the performance WeChat is not pushed to leaders and service personnel, the abnormal information is pushed to the mobile phones of the related personnel at the moment, and the performance WeChat can be pushed only when the related personnel confirm and process the information in the abnormal information table. Visual show can be carried out at any time, and configuration graceful group channel in the channel control page shows graceful group's actual achievement condition to output same ratio, ring ratio, mean value, and through visual colour early warning, whether suggestion index threshold value is normal, to having unusual identification item, set up early warning typeface colour green, the suggestion is unusual.
For the real-time monitoring type of internet scene insurance, such as the real-time monitoring of dental service of newly increased health service department, the requirement for the scene service invalidation is slightly low, and the scene service invalidation is loaded once in 60 minutes, and the specific implementation steps are as follows: the identification item is dental service of a major health cause department, the timeliness level label is low-level, the index threshold S is set to be 60 minutes, the difference value H minutes between a data writing timestamp (loading time) and system time in a result table is set, a timing big data platform calling interface is set, a calling calculation module is executed once in 5 minutes, and the threshold S is compared with the difference value H. When S is less than or equal to H, outputting an abnormal message to the mobile phone of the relevant personnel, wherein the time for dental service delay (H-S) of the major health department is 'in the mobile phone of the relevant personnel'; and when S is larger than H, no information is prompted.
The embodiment of the invention solves the problem that the current cost is not checked or manually checked according to experience, reduces the working complexity of data personnel, ensures the stability and reliability of data, improves the identification capability of data risks, can quickly position once abnormity is found, improves the stability of the data, enhances the systematic construction of company data, and better supports the business development of companies by the data. Aiming at the monitoring type of the scene insurance T +1 day, abnormity is automatically identified, page visual output is carried out on the abnormity, green risk early warning is carried out by applying, meanwhile, the abnormity information is written into a log sheet, active micro-letter performance timing pushing can not be carried out when the abnormity information exists, the micro-letter performance pushing can be carried out only after an abnormity pool is cleared, the risk is automatically identified through the early warning device, and the micro-letter performance timing pushing is automatically cancelled before the risk is not confirmed. Aiming at the real-time monitoring type of the scene insurance, the difference value between the result loading time and the system time is compared with an index threshold value, a timing big data platform calling interface is set, a calling calculation module is executed once in 5 minutes, when abnormal conditions exist, abnormal information is pushed to a related contact person mobile phone, and when the abnormal conditions do not exist, the information is not output.
In summary, in the embodiments of the present invention, insurance performance data and a corresponding monitoring type are obtained, where the insurance performance data includes: one or any combination of insurance performance data of different risk categories, insurance performance data of different cause departments and insurance performance data of different scenes, wherein the monitoring types comprise: monitoring for T +1 day and monitoring in real time; determining monitoring index data according to the insurance performance data and the corresponding monitoring type; monitoring insurance performance data according to the monitoring index data and a preset index threshold, wherein if the monitoring type is monitoring for T +1 day, the index threshold is preset according to an insurance type label; and if the monitoring type is real-time monitoring, the index threshold value is preset according to the timeliness grade label. According to the embodiment of the invention, a data worker does not need to judge experience values of each machine performance and task flow monitoring result one by one, the monitoring index data is determined only according to the insurance performance data and the corresponding monitoring type, and then the insurance performance data monitoring can be realized according to the monitoring index data and the preset index threshold, so that the abnormal condition of the insurance performance data is effectively monitored, manpower and material resources are saved, and the performance data monitoring efficiency and the result accuracy are improved.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. An insurance performance data monitoring method, comprising:
acquiring insurance performance data and corresponding monitoring types, wherein the insurance performance data comprises: one or any combination of insurance performance data of different risk categories, insurance performance data of different cause departments and insurance performance data of different scenes, wherein the monitoring types comprise: monitoring for T +1 day and monitoring in real time;
determining monitoring index data according to the insurance performance data and the corresponding monitoring type;
monitoring insurance performance data according to the monitoring index data and a preset index threshold, wherein if the monitoring type is monitoring for T +1 day, the index threshold is preset according to an insurance type label; and if the monitoring type is real-time monitoring, the index threshold value is preset according to the timeliness grade label.
2. The insurance performance data monitoring method of claim 1, wherein determining monitoring indicator data based on the insurance performance data and corresponding monitoring types comprises: if the monitoring type is monitoring for T +1 day, extracting the program running time data of the insurance achievement data from a database, and determining monitoring index data according to the program running time data of the insurance achievement data; the insurance category label is determined from historical insurance performance data.
3. The insurance performance data monitoring method of claim 1, wherein determining monitoring indicator data based on the insurance performance data and corresponding monitoring types comprises: if the monitoring type is real-time monitoring, extracting program running time data of the insurance achievement data from a database, and determining monitoring index data according to the program running time data of the insurance achievement data; the timeliness rating label is determined from historical insurance performance data.
4. The insurance performance data monitoring method of any one of claims 2 or 3, wherein the program runtime data includes: program operation start time data and program operation completion time data.
5. The insurance performance data monitoring method of claim 1, wherein determining monitoring indicator data based on the insurance performance data and corresponding monitoring types comprises:
if the monitoring type is T +1 day monitoring, KPI assessment data of the insurance performance data are extracted from a database, and the KPI assessment data comprise: a KPI current value and a KPI target value; determining monitoring index data according to the KPI current value and the KPI target value of the insurance performance data;
the insurance performance data monitoring method further comprises the following steps: and monitoring insurance performance data according to the monitoring index data and a preset index threshold, wherein if the monitoring type is T +1 day monitoring, the index threshold is preset according to time sequence progress data, and the time sequence progress data is determined according to historical insurance performance data.
6. The insurance performance data monitoring method of claim 5, wherein determining monitoring indicator data based on the insurance performance data and corresponding monitoring types comprises:
determining monitoring index data according to the current value of KPI of the insurance performance data and the current days;
the insurance performance data monitoring method further comprises the following steps: and monitoring insurance performance data according to the monitoring index data and a preset index threshold, wherein if the monitoring type is T +1 day monitoring, the index threshold is preset according to KPI target mean value data, and the KPI target mean value data is determined according to historical insurance performance data.
7. The insurance performance data monitoring method of claim 1, wherein determining monitoring indicator data based on the insurance performance data and corresponding monitoring types comprises: if the monitoring type is real-time monitoring, extracting the loading time data and the system time data of the insurance achievement data from a database, and determining monitoring index data according to the loading time data and the system time data of the insurance achievement data; the timeliness rating label is determined from historical insurance performance data.
8. An insurance performance data monitoring apparatus, comprising:
the acquisition module is used for acquiring insurance performance data and corresponding monitoring types, wherein the insurance performance data comprises: one or any combination of insurance performance data of different risk categories, insurance performance data of different cause departments and insurance performance data of different scenes, wherein the monitoring types comprise: monitoring for T +1 day and monitoring in real time;
the data determination module is used for determining monitoring index data according to the insurance performance data and the corresponding monitoring type;
the monitoring module is used for monitoring insurance performance data according to the monitoring index data and a preset index threshold, wherein if the monitoring type is T +1 day monitoring, the index threshold is preset according to an insurance type label; and if the monitoring type is real-time monitoring, the index threshold value is preset according to the timeliness grade label.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1 to 7.
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Application publication date: 20200825 |