Financial data intelligent analysis method and system

Abstract

The invention relates to the technical field of data analysis, and particularly discloses a financial data intelligent analysis method and system, and the method comprises the steps: receiving work data which is inputted by a worker and contains personnel information, and constructing a work database; receiving personnel information input by personnel, matching the data items in the work database according to the personnel information, reading the workload in the data items, and converting the workload into financial data; performing statistics on financial data of all workers, judging the anomaly degree of the financial data according to the overall data, and determining a rechecking sequence of each worker according to the anomaly degree, the workload item and the worker feature item; verifying the financial data based on the rechecking sequence; according to the invention, a common database is established, a worker automatically uploads work data, automatically identifies the work data, intelligently generates a re-checking work order and sends the work order to a manager, and the distribution process of an accounting task can be realized only by inputting some basic information by personnel.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and in particular to a method and system for intelligent analysis of financial data. Background Art

[0002] There are many types of financial data, and one special type of financial data is wages. The wage accounting process is actually the responsibility of the human resources department, and the personnel requirements of the human resources department do not require financial capabilities, which makes the wage accounting process very difficult. In addition, during the accounting, it is necessary to connect with multiple parties and a lot of communication work is required, which makes the company's wage payment process relatively late. How to provide a wage financial data analysis solution that is easy for non-professional personnel to use and simplify the accounting work is the technical problem that the technical solution of the present invention wants to solve. Summary of the invention

[0003] The purpose of the present invention is to provide a financial data intelligent analysis method and system to solve the problems raised in the above background technology.

[0004] To achieve the above object, the present invention provides the following technical solutions: A financial data intelligent analysis method, the method comprising: Receive work data containing personnel information input by staff and construct a work database; the work database includes personnel information items, workload items and personnel feature items; the personnel features are used to characterize the work status and work changes of staff; Receive personnel information input by HR personnel, match data items in the work database according to the personnel information, read the workload in the data item, and convert the workload into financial data; Collect financial data of all staff members, determine the abnormality of the financial data based on the overall data, and determine the review order of each staff member based on the abnormality, workload items and personnel characteristics items; The data items of the staff members are read in sequence based on the review order, the floating space is determined according to the staff members' personal characteristics, a review task sheet containing the floating space is generated, and the financial data is verified.

[0005] As a further solution of the present invention: the step of receiving the work data containing personnel information input by the staff and constructing the work database includes: Receive the staff member's work number, and query the staff information in the staff information database according to the work number; the staff information includes work number, work type, education level and length of service; Receive the workload with time periods input by the staff, perform longitudinal comparison on the workload to obtain the variation, perform transverse comparison on the workload to obtain the prominence, and use the variation and the prominence as the personnel characteristics with time periods; The personnel information, workload and personnel characteristics of each staff member in the same time period are counted to obtain a work database with time periods as labels; the work database is a table, each row corresponds to a staff member, and each column corresponds to an indicator; The longitudinal comparison process is the comparison of the workload of the same staff member in different time periods, including: ; In the formula, Indicates the amount of change, is the total number of time periods within the preset cycle, Indicates the first The workload in each time period; ; The horizontal comparison process is a comparison of the workload of different staff members in the same period of time, including: ; In the formula, Indicates abruptness, Indicates the total number of other staff members selected in the same time period, which is a preset value. is a preset constant, Indicates the current staff member and The similarity of each staff member is based on the similarity of personnel information. Indicates the current staff member and The difference in workload between staff members.

[0006] As a further solution of the present invention: the steps of receiving the personnel information input by the personnel personnel, matching the data items in the work database according to the personnel information, reading the workload in the data items, and converting the workload into financial data include: Receive the personnel information input by the personnel personnel, traverse the personnel information items in the work database according to the input personnel information, and when a match is successful, read the corresponding row of data as the data item; Read the workload in the data item, query the preset conversion model according to the type of work, input the workload into the queried conversion model, and obtain the financial data.

[0007] As a further solution of the present invention: the steps of collecting financial data of all staff members, judging the abnormality of the financial data according to the overall data, and determining the review order of each staff member according to the abnormality, workload items and staff characteristic items include: Query the total sales in the same time period, multiply the total sales by the ratio range to obtain the financial data range; the ratio range is determined by the historical total sales and its verified financial data; Assess the abnormality of financial data based on the financial data range; Determine the workload standard value and the personnel characteristic standard value according to the abnormality degree; Calculate the priority of each staff member based on the standard value of workload and the standard value of personnel characteristics, and determine the composite order of each staff member based on the descending order of priority; The calculation process of the abnormality degree is: ; In the formula, is the abnormality, is the preset correction factor, is the left endpoint of the financial data range, is the right endpoint of the financial data range; The relationship between the abnormality and the standard value of workload and the relationship between the abnormality and the standard value of personnel characteristics are both preset relationships; The process of calculating the priority of each staff member based on the workload standard value and the staff characteristic standard value is as follows: ; In the formula, For priority, and is the preset correction factor, is the difference between the workload and the standard workload value, It is the difference between the personnel characteristic and the standard value of the personnel characteristic.

[0008] As a further solution of the present invention: the steps of reading the data items of the staff members in sequence based on the review order, determining the floating space according to the staff members' personal characteristics, generating a review task list containing the floating space, and verifying the financial data include: Read the data items of the staff members in sequence based on the review order, and query the staff features in the data items; Reading the change amount and prominence of the personnel characteristics, and determining the floating space according to the change amount and prominence; Generate a review task sheet with floating space to verify financial data; The floating space is directly proportional to the change amount and inversely proportional to the protrusion.

[0009] As a further solution of the present invention: the step of generating a review task list containing floating space and verifying the financial data includes: Reading the workload in the data item, generating a review task form according to the workload, and inserting a floating space in the generated review task form; At least one manager of the query personnel is randomly selected and a review task form is sent to verify the financial data; The review task volume of each manager is queried, and the selection probability in the random selection process is adjusted according to the review task volume.

[0010] The technical solution of the present invention also provides a financial data intelligent analysis system, the system comprising: A database construction module is used to receive work data containing personnel information input by the staff and construct a work database; the work database includes personnel information items, workload items and personnel feature items; the personnel features are used to characterize the work status and work changes of the staff; The workload conversion module is used to receive the personnel information input by the personnel personnel, match the data items in the work database according to the personnel information, read the workload in the data items, and convert the workload into financial data; A review order determination module is used to collect statistics on the financial data of all staff members, determine the abnormality of the financial data based on the overall data, and determine the review order of each staff member based on the abnormality, workload items and personnel characteristics items; The data verification module is used to read the data items of the staff in sequence based on the review order, determine the floating space according to the personnel characteristics of the staff, generate a review task sheet containing the floating space, and verify the financial data.

[0011] As a further solution of the present invention: the database construction module includes: A personnel information query unit, used to receive the work number of a staff member, and query the personnel information in the personnel information database according to the work number; the personnel information includes the work number, type of work, education level and length of service; A personnel characteristic determination unit, for receiving the workload with time periods input by the staff, performing a longitudinal comparison on the workload to obtain a change, performing a transverse comparison on the workload to obtain a prominence, and using the change and the prominence as personnel characteristics with time periods; A data statistics unit is used to count the personnel information, workload and personnel characteristics of each staff member in the same time period, and obtain a work database with time periods as labels; the work database is a table, each row corresponds to a staff member, and each column corresponds to an indicator; The longitudinal comparison process is the comparison of the workload of the same staff member in different time periods, including: ; In the formula, Indicates the amount of change, is the total number of time periods within the preset cycle, Indicates the first The workload in each time period; ; The horizontal comparison process is a comparison of the workload of different staff members in the same period of time, including: ; In the formula, Indicates abruptness, Indicates the total number of other staff members selected in the same time period, which is a preset value. is a preset constant, Indicates the current staff member and The similarity of each staff member is based on the similarity of personnel information. Indicates the current staff member and The difference in workload between staff members.

[0012] As a further solution of the present invention: the workload conversion module includes: An information matching unit is used to receive personnel information input by a personnel staff, traverse the personnel information items in the work database according to the input personnel information, and when a match is successful, read a corresponding row of data as a data item; The conversion execution unit is used to read the workload in the data item, query the preset conversion model according to the type of work, input the workload into the queried conversion model, and obtain financial data.

[0013] As a further solution of the present invention: the review order determination module includes: A range determination unit, used to query the total sales in the same time period, and multiply the total sales by the ratio range to obtain the financial data range; the ratio range is determined by the historical total sales and the verified financial data; An abnormality evaluation unit, used to evaluate the abnormality of financial data according to the financial data range; A standard value determination unit, used to determine a workload standard value and a personnel characteristic standard value according to the abnormality degree; A priority application unit, used to calculate the priority of each staff member according to the workload standard value and the staff characteristic standard value, and determine the composite order of each staff member according to the descending order of priority; The calculation process of the abnormality degree is: ; In the formula, is the abnormality, is the preset correction factor, is the left endpoint of the financial data range, is the right endpoint of the financial data range; The relationship between the abnormality and the standard value of workload and the relationship between the abnormality and the standard value of personnel characteristics are both preset relationships; The process of calculating the priority of each staff member based on the workload standard value and the staff characteristic standard value is as follows: ; In the formula, For priority, and is the preset correction factor, is the difference between the workload and the standard workload value, It is the difference between the personnel characteristic and the standard value of the personnel characteristic.

[0014] Compared with the prior art, the beneficial effects of the present invention are: the present invention establishes a common database, and the staff uploads the work data by themselves, automatically identifies the work data, intelligently generates review work orders, and sends them to the management personnel. This process only requires the personnel to input some basic information to realize the distribution process of accounting tasks, and during the distribution process, some floating space can be set according to the work status of each staff member, and the level of intelligence is extremely high. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention.

[0016] Figure 1 This is a flowchart of the intelligent analysis method of financial data.

[0017] Figure 2 This is a structural block diagram of the financial data intelligent analysis system. DETAILED DESCRIPTION

[0018] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0019] Figure 1 The flowchart of the financial data intelligent analysis method is as follows. In an embodiment of the present invention, a financial data intelligent analysis method is provided, and the method includes: Step S100: receiving work data containing personnel information input by a staff member, and constructing a work database; the work database includes personnel information items, workload items, and personnel feature items; the personnel features are used to characterize the work status and work changes of the staff member; As the name suggests, staff members are those who work in the course of work. At the beginning of each month, each staff member will upload one month's work data for salary settlement. The work data is the quantification of their work. Regardless of the type of work, there will be a certain quantitative indicator. The work data containing staff information input by all staff members is received to build a work database. The role of staff information is to indicate which staff member's work data belongs to. The obtained work database includes staff information items, workload items and staff feature items. The workload is how much labor the staff member has put in, such as working hours. The staff feature is an indicator determined based on the workload, which is used to characterize the staff member's work situation and work changes. In addition, regarding the staff information item, it may include multiple sub-items, and the same is true for the staff feature item, which may also include multiple sub-items.

[0020] It is worth mentioning that the work database is generally a table, and each column corresponds to an indicator, such as each sub-item in personnel information, workload, and each sub-item in personnel characteristics.

[0021] Step S200: receiving personnel information input by personnel personnel, matching data items in the work database according to the personnel information, reading the workload in the data items, and converting the workload into financial data; HR personnel are the ones who count workload. In layman's terms, they are the ones who calculate wages. They need to perform a calculation for each staff member, receive the personnel information input by the HR personnel, directly locate the corresponding data item in the work database based on the personnel information, read the workload in the data item, and convert the workload into financial data. The correspondence between workload and financial data is a default known mapping relationship. Every company has a fixed salary calculation plan, which is the mapping relationship mentioned above.

[0022] It is worth mentioning that human resources personnel are also staff members, and they also need to upload their own workload. Correspondingly, there are data items corresponding to human resources personnel in the work database. In addition, there are many known mapping relationships that are fixed mapping relationships. No matter how much the input is, the output is the same. This actually corresponds to a fixed salary. For human resources personnel, a fixed salary is generally used. Therefore, the data items corresponding to human resources personnel in the work database are generally simpler.

[0023] Step S300: Counting the financial data of all staff members, judging the abnormality of the financial data based on the overall data, and determining the review order of each staff member based on the abnormality, workload items and staff characteristic items; After each staff member's work data is converted into financial data, the financial data of all staff members are counted, and the overall data of the company is queried. The overall data includes total turnover, total number of orders and total shipments, etc., which are actually related to the staff's wages. If the total turnover increases, it means that the staff's workload also increases. There is a corresponding relationship between total turnover and workload. By collecting multiple total turnovers and staff workloads, a relationship can be fitted. When the relationship is fitted, whenever new financial data is obtained, it can be judged whether there is an abnormality in the financial data based on the overall data. In layman's terms, it is to judge whether the salary payment is roughly correct based on the total turnover. The more normal, the lower the abnormality.

[0024] The above-mentioned abnormality degree only indicates the probability of abnormality, and further judgment is needed to determine the possibility of abnormality of each staff member in combination with the abnormality degree, workload and personnel characteristics, and then determine the review order and review the staff; it should be noted that the above-mentioned abnormality degree refers to the abnormal situation of the entire staff, and the determined possibility of abnormality of each staff member refers to the abnormal situation of each staff member.

[0025] Step S400: Read the data items of the staff members in turn based on the review order, determine the floating space according to the staff members' personal characteristics, generate a review task list containing the floating space, and verify the financial data; After the review order is determined, the data items of the staff are read in sequence based on the review order, the floating space is determined according to the personnel characteristics of the staff, and a review task sheet containing the floating space is generated to verify the financial data; the review task sheet is to generate a review task table, which is equivalent to a work order, and is handed over to the reviewer. It is preset known data, and tells the reviewer what information to check, such as business screenshots and work videos; when the order is known, how to check the work of the staff (generate a review task sheet) belongs to the prior art and will not be repeated in this application.

[0026] The focus of the above content is the parameter of floating space, which represents a range. The working status of the staff is determined according to the personnel characteristics of the staff. If the working status is good, the floating space will be larger. During the review, if the staff's salary is a little higher, it is also considered that the corresponding account data meets the standards and can pass the verification. This is actually a hidden benefit for the staff, equivalent to a reward. The excess salary may be misreported by the staff, or it may be deliberately overreported. The above verification method takes a tacit attitude towards this process, which can bring great emotional value to the staff. In layman's terms, suppose a staff member is in a very good working state, and then he is very tired at work in a certain month. When reporting his workload, he overreported by 1%. At this time, the reviewer will acquiesce to this behavior within the range of the floating space, which can bring great joy to the staff, and his work will be more serious, which has a positive impact on both the staff and the company.

[0027] Regarding step S100, the step of receiving work data containing personnel information input by the staff and constructing a work database includes: Receive the staff member's work number, and query the staff information in the staff information database according to the work number; the staff information includes work number, work type, education level and length of service; Receive the workload with time periods input by the staff, perform longitudinal comparison on the workload to obtain the variation, perform transverse comparison on the workload to obtain the prominence, and use the variation and the prominence as the personnel characteristics with time periods; The personnel information, workload and personnel characteristics of each staff member in the same time period are counted to obtain a work database with time periods as labels; the work database is a table, each row corresponds to a staff member, and each column corresponds to an indicator.

[0028] In an example of the technical solution of the present invention, the construction process of the work database is explained, the work number of the staff member is received, and the personnel information is queried in the personnel information database according to the work number. The personnel information is data that is counted when joining the company and can be directly queried according to the work number; the workload containing the time period input by the staff member is received. The workload of this application is uploaded by the staff member voluntarily, and a vertical comparison is performed on the workload uploaded by the staff member to obtain the change amount, and a horizontal comparison is performed on the workload uploaded by the staff member to obtain the prominence, and the change amount and the prominence are used as personnel characteristics containing the time period; finally, the personnel information, workload and personnel characteristics of each staff member are counted to obtain a work database.

[0029] It should be noted that the data in this application are all data within a preset period of time, such as a month, and wages are basically settled monthly. Therefore, the constructed work database is also a work database for a period of time, containing time period labels.

[0030] The longitudinal comparison process is the comparison of the workload of the same staff member in different time periods, including: ; In the formula, Indicates the amount of change, is the total number of time periods within the preset cycle, Indicates the first The workload in each time period; .

[0031] The longitudinal comparison process is to compare the workload of the staff with their historical workload. The preset period can be one year, and the time period can be one month. It represents the increase in workload between two consecutive months. The average of all increases is calculated to get the change, which represents the staff's progress speed.

[0032] The horizontal comparison process is a comparison of the workload of different staff members in the same period of time, including: ; In the formula, Indicates abruptness, Indicates the total number of other staff members selected in the same time period, which is a preset value. is a preset constant, Indicates the current staff member and The similarity of each staff member is based on the similarity of personnel information. Indicates the current staff member and The difference in workload between staff members.

[0033] The horizontal comparison process compares the differences between a staff member and other staff members. If a staff member is compared with all other staff members, the amount of calculation will be very large. Therefore, the above content sets a total number M to limit the number of comparisons. Of course, M can be selected to be very large so that all staff members will be compared once. For the two compared parties, the absolute value of the difference in their workload is calculated and then multiplied by the similarity to obtain the difference between the other staff member and the current staff member. The differences between M staff members and the current staff member are accumulated and multiplied by a preset constant. The resulting parameter is called abruptness, which indicates the degree of difference between a staff member and other staff members.

[0034] Regarding step S200, the steps of receiving personnel information input by a personnel staff, matching data items in a work database according to the personnel information, reading the workload in the data items, and converting the workload into financial data include: Receive the personnel information input by the personnel personnel, traverse the personnel information items in the work database according to the input personnel information, and when a match is successful, read the corresponding row of data as the data item; Read the workload in the data item, query the preset conversion model according to the type of work, input the workload into the queried conversion model, and obtain the financial data.

[0035] In an example of the technical solution of the present invention, the personnel personnel and the staff share the same work database. The execution subject of this method receives the personnel information input by the personnel personnel (the personnel personnel need to process the staff one by one), and traverses the personnel information items in the work database according to the input personnel information. When the corresponding data item is found, the match is successful, and the corresponding row of data is read as the data item; the workload in the data item is read, and the preset conversion model is queried according to the type of work, and the workload is input into the queried conversion model to obtain financial data; it can be known from the foregoing content that the relationship between the workload and salary of each type of work is pre-equipped, and the preset conversion model is queried according to the type of work. After the workload is read, the workload is input into the queried conversion model to obtain financial data.

[0036] Regarding step S300, the steps of collecting financial data of all staff members, judging the abnormality of the financial data according to the overall data, and determining the review order of each staff member according to the abnormality, workload items and staff characteristic items include: Query the total sales in the same time period, multiply the total sales by the ratio range to obtain the financial data range; the ratio range is determined by the historical total sales and its verified financial data; Assess the abnormality of financial data based on the financial data range; Determine the workload standard value and the personnel characteristic standard value according to the abnormality degree; The priority of each staff member is calculated based on the standard value of workload and the standard value of personnel characteristics, and the composite order of each staff member is determined in descending order of priority.

[0037] In an example of the technical solution of the present invention, the process of determining the review order is explained, the overall data is limited to the total sales, and a proportion range is determined by the historical total sales and the reviewed financial data, indicating the range of wages and total sales under normal conditions. When the new total sales is obtained, the total sales is multiplied by the proportion range to obtain the financial data range.

[0038] When the financial data is determined, it can be judged whether the financial data is abnormal based on the financial data range. The workload standard value and personnel characteristic standard value can be determined based on the abnormality. The priority of each staff member is calculated based on the workload standard value and personnel characteristic standard value. The composite order of each staff member can be determined based on the priority.

[0039] The calculation process of the abnormality degree is: ; In the formula, is the abnormality, is the preset correction factor, is the left endpoint of the financial data range, The right endpoint of the financial data range.

[0040] The calculation principle of abnormality is very simple. If the financial data is closer to the center of the range, the smaller the abnormality is. On the contrary, the abnormality is greater. It is worth mentioning that if C is less than or C is greater than , directly set the abnormality to the maximum value.

[0041] The relationship between the abnormality degree and the standard value of the workload, as well as the relationship between the abnormality degree and the standard value of the personnel characteristics, are both preset relationships; these two relationships can be represented by a table. When the abnormality degree is a certain value, what kind of workload is the most standard, and what kind of personnel characteristics are the most standard. This is determined by the management personnel of the subject executing this method. For this application, the default is known data.

[0042] The process of calculating the priority of each staff member based on the workload standard value and the staff characteristic standard value is as follows: ; In the formula, For priority, and is the preset correction factor, is the difference between the workload and the standard workload value, It is the difference between the personnel characteristic and the standard value of the personnel characteristic.

[0043] Priority is essentially a numerical value. The difference between the workload of the staff and the standard value is calculated, and the difference between the personnel characteristics of the staff and the standard value is calculated. The total value obtained by adding the corresponding weights can be used as the priority. In this application, there are two personnel characteristics to be considered, namely, the change amount and the abruptness. Therefore, Can be split into and , representing the amount of change and abruptness respectively.

[0044] Regarding step S400, the steps of reading the data items of the staff members in sequence based on the review order, determining the floating space according to the staff members' personal characteristics, generating a review task list containing the floating space, and verifying the financial data include: Read the data items of the staff members in turn based on the review order, and query the personnel characteristics in the data items; Reading the change amount and prominence of the personnel characteristics, and determining the floating space according to the change amount and prominence; Generate a review task sheet with floating space to verify financial data; The floating space is directly proportional to the change amount and inversely proportional to the protrusion.

[0045] In one example of the technical solution of the present invention, data items of staff members are read in sequence based on the review order, personnel characteristics in the data items are queried, the change amount and prominence of the personnel characteristics are read, the floating space is determined based on the change amount and prominence, and after a review task sheet is generated based on the financial data, the floating space is inserted to obtain a review task sheet containing the floating space; the financial data is verified through the review task sheet containing the floating space.

[0046] As a preferred embodiment of the technical solution of the present invention, the step of generating a review task list containing floating space and verifying the financial data includes: Reading the workload in the data item, generating a review task form according to the workload, and inserting a floating space in the generated review task form; At least one manager of the query personnel is randomly selected and a review task form is sent to verify the financial data; The review task volume of each manager is queried, and the selection probability in the random selection process is adjusted according to the review task volume.

[0047] In an example of the technical solution of the present invention, a specific solution for verifying financial data is provided, which reads the workload in a data item, generates a review task form based on the workload, and inserts a floating space in the generated review task form; wherein, the process of generating a review task form based on the workload is a conventional task order generation solution, which can be achieved by using existing technologies.

[0048] Then, for the staff reviewer, query at least one manager of the staff, the managers include team leaders, deputy managers and managers, etc., randomly select at least one manager from the managers, send the review task form containing floating space to the manager, and receive the verification results fed back by the manager, which is collectively referred to as verification of financial data.

[0049] Furthermore, for each manager, the amount of review tasks of each manager is queried. The higher the level of the manager, the more staff members he or she faces and the greater the amount of review tasks. The selection probability in the random selection process is adjusted according to the amount of review tasks. The selection probability is inversely proportional to the amount of review tasks. Its actual meaning is that the more staff members a manager needs to review, the smaller the probability of being selected when encountering new staff members.

[0050] Specifically, for each staff member, the total number of managers is queried, the selection probability is determined based on the amount of review tasks of each manager, all selection probabilities are added up, and then the selection probability of each manager relative to the staff member is calculated. After the calculation is completed, whether each manager is selected is determined based on the selection probability. When only one alternative manager is left, the probability of his selection is set to 100% to ensure that at least one manager is selected.

[0051] Figure 2 : is a structural block diagram of a financial data intelligent analysis system. In an embodiment of the present invention, a financial data intelligent analysis system, the system 10 includes: The database construction module 11 is used to receive work data containing personnel information input by the staff and construct a work database; the work database includes personnel information items, workload items and personnel feature items; the personnel features are used to characterize the work status and work changes of the staff; The workload conversion module 12 is used to receive the personnel information input by the personnel personnel, match the data items in the work database according to the personnel information, read the workload in the data items, and convert the workload into financial data; The review order determination module 13 is used to collect the financial data of all staff members, determine the abnormality of the financial data based on the overall data, and determine the review order of each staff member based on the abnormality, workload items and personnel characteristic items; The data verification module 14 is used to read the data items of the staff in sequence based on the review order, determine the floating space according to the personnel characteristics of the staff, generate a review task list containing the floating space, and verify the financial data.

[0052] Furthermore, the database construction module 11 includes: A personnel information query unit, used to receive the work number of a staff member, and query the personnel information in the personnel information database according to the work number; the personnel information includes the work number, type of work, education level and length of service; A personnel characteristic determination unit, for receiving the workload with time periods input by the staff, performing a longitudinal comparison on the workload to obtain a change, performing a transverse comparison on the workload to obtain a prominence, and using the change and the prominence as personnel characteristics with time periods; A data statistics unit is used to count the personnel information, workload and personnel characteristics of each staff member in the same time period, and obtain a work database with time periods as labels; the work database is a table, each row corresponds to a staff member, and each column corresponds to an indicator; The longitudinal comparison process is the comparison of the workload of the same staff member in different time periods, including: ; In the formula, Indicates the amount of change, is the total number of time periods within the preset cycle, Indicates the first The workload in each time period; ; The horizontal comparison process is a comparison of the workload of different staff members in the same period of time, including: ; In the formula, Indicates abruptness, Indicates the total number of other staff members selected in the same time period, which is a preset value. is a preset constant, Indicates the current staff member and The similarity of each staff member is based on the similarity of personnel information. Indicates the current staff member and The difference in workload between staff members.

[0053] Specifically, the workload conversion module 12 includes: An information matching unit is used to receive personnel information input by a personnel staff, traverse the personnel information items in the work database according to the input personnel information, and when a match is successful, read a corresponding row of data as a data item; The conversion execution unit is used to read the workload in the data item, query the preset conversion model according to the type of work, input the workload into the queried conversion model, and obtain financial data.

[0054] Furthermore, the review order determination module 13 includes: A range determination unit, used to query the total sales in the same time period, and multiply the total sales by the ratio range to obtain the financial data range; the ratio range is determined by the historical total sales and the verified financial data; An abnormality evaluation unit, used to evaluate the abnormality of financial data according to the financial data range; A standard value determination unit, used to determine a workload standard value and a personnel characteristic standard value according to the abnormality degree; A priority application unit, used to calculate the priority of each staff member according to the workload standard value and the staff characteristic standard value, and determine the composite order of each staff member according to the descending order of priority; The calculation process of the abnormality degree is: ; In the formula, is the abnormality, is the preset correction factor, is the left endpoint of the financial data range, is the right endpoint of the financial data range; The relationship between the abnormality and the standard value of workload and the relationship between the abnormality and the standard value of personnel characteristics are both preset relationships; The process of calculating the priority of each staff member based on the workload standard value and the staff characteristic standard value is as follows: ; In the formula, For priority, and is the preset correction factor, is the difference between the workload and the standard workload value, It is the difference between the personnel characteristic and the standard value of the personnel characteristic.

[0055] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A financial data intelligent analysis method, characterized in that: The method comprises: Receive work data containing personnel information input by staff and construct a work database; the work database includes personnel information items, workload items and personnel feature items; the personnel features are used to characterize the work status and work changes of staff; Receive personnel information input by HR personnel, match data items in the work database according to the personnel information, read the workload in the data item, and convert the workload into financial data; Collect financial data of all staff members, determine the abnormality of the financial data based on the overall data, and determine the review order of each staff member based on the abnormality, workload items and personnel characteristics items; The data items of the staff members are read in sequence based on the review order, the floating space is determined according to the staff members' personal characteristics, a review task sheet containing the floating space is generated, and the financial data is verified.

2. The financial data intelligent analysis method according to claim 1, characterized in that: The step of receiving work data containing personnel information input by the staff and constructing a work database comprises: Receive the staff member's work number, and query the staff information in the staff information database according to the work number; the staff information includes work number, work type, education level and length of service; Receive the workload with time periods input by the staff, perform longitudinal comparison on the workload to obtain the variation, perform transverse comparison on the workload to obtain the prominence, and use the variation and the prominence as the personnel characteristics with time periods; The personnel information, workload and personnel characteristics of each staff member in the same time period are counted to obtain a work database with time periods as labels; the work database is a table, each row corresponds to a staff member, and each column corresponds to an indicator; The longitudinal comparison process is the comparison of the workload of the same staff member in different time periods, including: ; In the formula, Indicates the amount of change, is the total number of time periods within the preset cycle, Indicates the first The workload in each time period; ; The horizontal comparison process is a comparison of the workload of different staff members in the same period of time, including: ; In the formula, Indicates abruptness, Indicates the total number of other staff members selected in the same time period, which is a preset value. is a preset constant, Indicates the current staff member and The similarity of each staff member is based on the similarity of personnel information. Indicates the current staff member and The difference in workload between staff members.

3. The financial data intelligent analysis method according to claim 1, characterized in that: The steps of receiving personnel information input by personnel personnel, matching data items in a work database according to the personnel information, reading the workload in the data items, and converting the workload into financial data include: Receive the personnel information input by the personnel personnel, traverse the personnel information items in the work database according to the input personnel information, and when a match is successful, read the corresponding row of data as the data item; Read the workload in the data item, query the preset conversion model according to the type of work, input the workload into the queried conversion model, and obtain the financial data.

4. The financial data intelligent analysis method according to claim 1, characterized in that: The steps of collecting financial data of all staff members, judging the abnormality of the financial data according to the overall data, and determining the review order of each staff member according to the abnormality, workload items and staff characteristic items include: Query the total sales in the same time period, multiply the total sales by the ratio range to obtain the financial data range; the ratio range is determined by the historical total sales and its verified financial data; Assess the abnormality of financial data based on the financial data range; Determine the workload standard value and the personnel characteristic standard value according to the abnormality degree; Calculate the priority of each staff member based on the standard value of workload and the standard value of personnel characteristics, and determine the composite order of each staff member based on the descending order of priority; The calculation process of the abnormality is: ; In the formula, is the abnormality, is the preset correction factor, is the left endpoint of the financial data range, is the right endpoint of the financial data range; The relationship between the abnormality and the standard value of workload and the relationship between the abnormality and the standard value of personnel characteristics are both preset relationships; The process of calculating the priority of each staff member based on the workload standard value and the staff characteristic standard value is as follows: ; In the formula, For priority, and is the preset correction factor, is the difference between the workload and the standard workload value, It is the difference between the personnel characteristic and the standard value of the personnel characteristic.

5. The financial data intelligent analysis method according to claim 2, characterized in that: The steps of sequentially reading the data items of the staff members based on the review order, determining the floating space according to the staff members' personal characteristics, generating a review task sheet containing the floating space, and verifying the financial data include: Read the data items of the staff members in turn based on the review order, and query the personnel characteristics in the data items; Reading the change amount and prominence of the personnel characteristics, and determining the floating space according to the change amount and prominence; Generate a review task sheet with floating space to verify financial data; The floating space is directly proportional to the change amount and inversely proportional to the protrusion.

6. The financial data intelligent analysis method according to claim 5, characterized in that: The steps of generating a review task sheet containing floating space and verifying the financial data include: Reading the workload in the data item, generating a review task form according to the workload, and inserting a floating space in the generated review task form; At least one manager of the query personnel is randomly selected and a review task form is sent to verify the financial data; The review task volume of each manager is queried, and the selection probability in the random selection process is adjusted according to the review task volume.

7. A financial data intelligent analysis system, characterized in that: The system comprises: A database construction module is used to receive work data containing personnel information input by the staff and construct a work database; the work database includes personnel information items, workload items and personnel feature items; the personnel features are used to characterize the work status and work changes of the staff; The workload conversion module is used to receive the personnel information input by the personnel personnel, match the data items in the work database according to the personnel information, read the workload in the data items, and convert the workload into financial data; A review order determination module is used to collect statistics on the financial data of all staff members, determine the abnormality of the financial data based on the overall data, and determine the review order of each staff member based on the abnormality, workload items and personnel characteristics items; The data verification module is used to read the data items of the staff in sequence based on the review order, determine the floating space according to the personnel characteristics of the staff, generate a review task sheet containing the floating space, and verify the financial data.

8. The financial data intelligent analysis system according to claim 7, characterized in that: The database construction module includes: A personnel information query unit, used to receive the work number of a staff member, and query the personnel information in the personnel information database according to the work number; the personnel information includes the work number, type of work, education level and length of service; A personnel characteristic determination unit, for receiving the workload with time periods input by the staff, performing a longitudinal comparison on the workload to obtain a change, performing a transverse comparison on the workload to obtain a prominence, and using the change and the prominence as personnel characteristics with time periods; A data statistics unit is used to count the personnel information, workload and personnel characteristics of each staff member in the same time period, and obtain a work database with time periods as labels; the work database is a table, each row corresponds to a staff member, and each column corresponds to an indicator; The longitudinal comparison process is the comparison of the workload of the same staff member in different time periods, including: ; In the formula, Indicates the amount of change, is the total number of time periods within the preset cycle, Indicates the first The workload in each time period; ; The horizontal comparison process is a comparison of the workload of different staff members in the same period of time, including: ; In the formula, Indicates abruptness, Indicates the total number of other staff members selected in the same time period, which is a preset value. is a preset constant, Indicates the current staff member and The similarity of each staff member is based on the similarity of personnel information. Indicates the current staff member and The difference in workload between staff members.

9. The financial data intelligent analysis system according to claim 7, characterized in that: The workload conversion module includes: An information matching unit is used to receive personnel information input by a personnel staff, traverse the personnel information items in the work database according to the input personnel information, and when a match is successful, read a corresponding row of data as a data item; The conversion execution unit is used to read the workload in the data item, query the preset conversion model according to the type of work, input the workload into the queried conversion model, and obtain financial data.

10. The financial data intelligent analysis system according to claim 7, characterized in that: The review order determination module comprises: A range determination unit, used to query the total sales in the same time period, and multiply the total sales by the ratio range to obtain the financial data range; the ratio range is determined by the historical total sales and the verified financial data; An abnormality evaluation unit, used to evaluate the abnormality of financial data according to the financial data range; A standard value determination unit, used to determine a workload standard value and a personnel characteristic standard value according to the abnormality degree; A priority application unit, used to calculate the priority of each staff member according to the workload standard value and the staff characteristic standard value, and determine the composite order of each staff member according to the descending order of priority; The calculation process of the abnormality is: ; In the formula, is the abnormality, is the preset correction factor, is the left endpoint of the financial data range, is the right endpoint of the financial data range; The relationship between the abnormality and the standard value of workload and the relationship between the abnormality and the standard value of personnel characteristics are both preset relationships; The process of calculating the priority of each staff member based on the workload standard value and the staff characteristic standard value is as follows: ; In the formula, For priority, and is the preset correction factor, is the difference between the workload and the standard workload value, It is the difference between the personnel characteristic and the standard value of the personnel characteristic.

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