Information processing method and device, computer equipment and storage medium

Abstract

The invention relates to an information processing method and device, computer equipment, a storage medium and a computer program product, and relates to the technical field of big data. The method comprises the steps of obtaining statistical parameters configured for state change operations, the statistical parameters comprising a statistical period, a statistical dimension and a risk early warning condition matched with the statistical dimension, obtaining respective record information of a plurality of state change operations occurring in the current statistical period, comprising the following steps: counting the changed state of each account according to a statistical dimension to obtain a change operation statistical result corresponding to the statistical dimension according to the changed state of the account corresponding to the state change operation, and by adopting the method, compared with a single statistical dimension, the statistical result under a plurality of statistical dimensions is higher in accuracy, and the accuracy of the change operation statistical result under a plurality of statistical dimensions is improved. And under the condition that the difference between the change operation statistical result and the historical statistical result meets the risk early warning condition, the accuracy of the output risk prompt information is higher.

Description

Technical Field

[0001] The present application relates to the field of big data technology, and in particular to an information processing method, apparatus, computer equipment, storage medium and computer program product. Background Art

[0002] With the development of financial technology, the digitalization of banking business is also advancing. Bank account counter business is gradually replaced by online business. The number of online accounts is increasing. At the same time, a large number of online accounts have not been used for a long time and are inactive. Such accounts are not conducive to banks' analysis of online accounts.

[0003] In the traditional way, business rules are configured in advance for various online accounts. When an online account meets the business rules, the account status is switched, for example, the account status is set to sleep. In this way, multiple accounts are divided into sleep accounts and non-sleep accounts, and prompt information is generated to prompt developers to make subsequent business adjustments based on the number of sleep accounts and non-sleep accounts. The currently generated prompt information still has the problem of low accuracy. Summary of the invention

[0004] Based on this, it is necessary to provide an information processing method, apparatus, computer device, computer-readable storage medium and computer program product that can improve the accuracy of prompt information in response to the above technical problems.

[0005] In a first aspect, the present application provides an information processing method. The method comprises:

[0006] Obtain statistical parameters configured for state change operations; the statistical parameters include a statistical period, a statistical dimension, and a risk warning condition matching the statistical dimension; obtain record information of each of multiple state change operations occurring in the current statistical period; the record information includes the changed state of the account targeted by the state change operation; for each state change operation, determine the expected state of the account targeted by the state change operation; perform matching analysis on each of the changed states and each of the expected states to determine the matching between the changed state and the expected state of each of the accounts; perform statistics on the matching of each of the accounts according to the statistical dimension to obtain the statistical result of the change operation corresponding to the statistical dimension; if the difference between the statistical result of the change operation and the historical statistical result of the historical statistical period meets the risk warning condition, output risk warning information.

[0007] In one of the embodiments, the statistical dimension is the change success rate; the matching status of each of the accounts is counted according to the statistical dimension to obtain the change operation statistical result corresponding to the statistical dimension, including: for each of the accounts, when the changed state of the account matches the expected state, determining the account as a successfully changed account; and determining the proportion of successfully changed accounts in each of the accounts as the change operation statistical result corresponding to the change success rate.

[0008] In one of the embodiments, the statistical dimension is a failure cause dimension; the matching status of each of the accounts is counted according to the statistical dimension to obtain a change operation statistical result corresponding to the statistical dimension, including: for each of the accounts, when the changed status of the account does not match the expected status, extracting the failure cause of the status change failure from the record information belonging to the account; and counting each of the failure causes to obtain a change operation statistical result corresponding to the failure cause dimension.

[0009] In one embodiment, the historical statistical period includes multiple candidate periods before the current statistical period; the method also includes: obtaining the candidate statistical results of each candidate period; determining the weight corresponding to each candidate period according to the time interval between each candidate period and the current period; the weight is inversely correlated with the time interval; and weighting each candidate statistical result according to each weight to obtain the historical statistical result of the historical statistical period.

[0010] In one of the embodiments, the method further includes: obtaining a table template configured for the statistical dimension; filling the risk warning information, the historical statistical results and the change operation statistical results into the to-be-filled position of the table template, and obtaining and outputting a result report for the statistical dimension.

[0011] In one of the embodiments, the risk warning condition includes a first warning condition configured for a statistical period and a second warning condition configured for a batch status change operation; the method also includes: when multiple target accounts meet the status change condition, triggering a batch status change operation for each of the target accounts; in response to the batch status change operation, obtaining the changed state of each of the target accounts; determining the match between the changed state of each of the target accounts and the expected state corresponding to the batch status change operation; counting the matching conditions of each of the target accounts according to the statistical dimension to determine the statistical results of the batch status change operation; and outputting risk warning information when the statistical results meet the second warning condition.

[0012] In a second aspect, the present application also provides an information processing device. The device comprises:

[0013] A parameter acquisition module is used to obtain statistical parameters configured for state change operations; the statistical parameters include a statistical period, a statistical dimension, and risk warning conditions matching the statistical dimension; an information acquisition module is used to obtain record information of each of multiple state change operations occurring in the current statistical period; the record information includes the changed state of the account targeted by the state change operation; a state statistics module is used to count the changed state of each of the accounts according to the statistical dimension to obtain a change operation statistical result corresponding to the statistical dimension; a first information output module is used to output risk warning information when the difference between the change operation statistical result and the historical statistical result of the historical statistical period meets the risk warning condition.

[0014] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0015] Obtain statistical parameters configured for state change operations; the statistical parameters include a statistical period, a statistical dimension, and a risk warning condition matching the statistical dimension; obtain record information of each of multiple state change operations occurring in the current statistical period; the record information includes the changed state of the account targeted by the state change operation; for each state change operation, determine the expected state of the account targeted by the state change operation; perform matching analysis on each of the changed states and each of the expected states to determine the matching between the changed state and the expected state of each of the accounts; perform statistics on the matching of each of the accounts according to the statistical dimension to obtain the statistical result of the change operation corresponding to the statistical dimension; if the difference between the statistical result of the change operation and the historical statistical result of the historical statistical period meets the risk warning condition, output risk warning information.

[0016] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0017] Obtain statistical parameters configured for state change operations; the statistical parameters include a statistical period, a statistical dimension, and a risk warning condition matching the statistical dimension; obtain record information of each of multiple state change operations occurring in the current statistical period; the record information includes the changed state of the account targeted by the state change operation; for each state change operation, determine the expected state of the account targeted by the state change operation; perform matching analysis on each of the changed states and each of the expected states to determine the matching between the changed state and the expected state of each of the accounts; perform statistics on the matching of each of the accounts according to the statistical dimension to obtain the statistical result of the change operation corresponding to the statistical dimension; if the difference between the statistical result of the change operation and the historical statistical result of the historical statistical period meets the risk warning condition, output risk warning information.

[0018] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0019] Obtain statistical parameters configured for state change operations; the statistical parameters include a statistical period, a statistical dimension, and a risk warning condition matching the statistical dimension; obtain record information of each of multiple state change operations occurring in the current statistical period; the record information includes the changed state of the account targeted by the state change operation; for each state change operation, determine the expected state of the account targeted by the state change operation; perform matching analysis on each of the changed states and each of the expected states to determine the matching between the changed state and the expected state of each of the accounts; perform statistics on the matching of each of the accounts according to the statistical dimension to obtain the statistical result of the change operation corresponding to the statistical dimension; if the difference between the statistical result of the change operation and the historical statistical result of the historical statistical period meets the risk warning condition, output risk warning information.

[0020] The above-mentioned information processing method, device, computer equipment, storage medium and computer program product obtain statistical parameters configured for state change operations, the statistical parameters include statistical period, statistical dimension, and risk warning conditions matching the statistical dimension, obtain the record information of each of the multiple state change operations occurring in the current statistical period, the record information includes the changed state of the account targeted by the state change operation, the record information reflects the state before and after the account change, each state change operation corresponds to a record information, which is conducive to the subsequent statistics of each change state and improves the accuracy of the statistical results. For each state change operation, determine the expected state of the account targeted by the state change operation, perform matching analysis on each changed state and each expected state, determine the matching between each changed state and the expected state of each account, perform statistics on each matching situation of each account according to the statistical dimension, and obtain the statistical results of the change operation corresponding to the statistical dimension. The obtained change statistical results are statistical results under multiple statistical dimensions. Compared with a single statistical dimension, the statistical results under multiple statistical dimensions are more accurate. By adopting the above method, the obtained change operation statistical results are more accurate. When the difference between the change operation statistical results and the historical statistical results of the historical statistical period meets the risk warning condition, the output risk warning information is more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] FIG1 is a diagram of an application environment of an information processing method in one embodiment;

[0022] FIG2 is a schematic diagram of a flow chart of an information processing method in one embodiment;

[0023] FIG3 is a schematic diagram of a flow chart of a method for determining risk warning information in one embodiment;

[0024] FIG4 is a flow chart of an automatic analysis method based on distributed core bank account status in one embodiment;

[0025] FIG5 is a block diagram of an information processing device in one embodiment;

[0026] FIG. 6 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application 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 application and are not used to limit the present application.

[0028] It should be noted that in the embodiments of the present application, certain software, groups, models and other existing solutions in the industry may be mentioned, which should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0029] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations. The acquisition, storage, use, and processing of data in the technical solution of this application are in compliance with relevant provisions of national laws and regulations.

[0030] The information processing method provided in the embodiment of the present application can be applied in the application environment shown in FIG1 . In which, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers.

[0031] The server 104 obtains statistical parameters configured for the state change operation, and the statistical parameters include a statistical period, a statistical dimension, and a risk warning condition matching the statistical dimension. The server 104 obtains the record information of each of the multiple state change operations occurring in the current statistical period, and the record information includes the changed state of the account targeted by the state change operation. The server 104 determines the expected state of the account targeted by the state change operation for each of the state change operations. The server 104 determines the matching between the changed state and the expected state of each of the accounts. The server 104 counts the matching of each of the accounts according to the statistical dimension, and obtains the statistical result of the change operation corresponding to the statistical dimension. When the difference between the statistical result of the change operation and the historical statistical result of the historical statistical period meets the risk warning condition, the server 104 outputs the risk warning information to the terminal 102.

[0032] The terminal 102 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. The portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers.

[0033] In one embodiment, as shown in FIG. 2 , an information processing method is provided, which is described by taking the method applied to the server 104 in FIG. 1 as an example, including:

[0034] S202: Obtain statistical parameters configured for the state change operation.

[0035] Among them, the state change operation refers to the operation of changing the state of the account, for example, the operation of switching the account to the sleep state, the operation of switching the account to the non-operating state, the operation of switching the account to the frozen state, etc. The state change operation can be triggered automatically or manually. Taking the state change operation of switching to the sleep state as an example, when the account has no actual transactions for more than a preset period of time, the state of the account can be automatically switched to the sleep state, or the account can be manually switched to the sleep state.

[0036] Statistical parameters represent parameters configured for state change operations. Specifically, statistical parameters include statistical period, statistical dimension, and risk warning conditions matched by statistical dimension.

[0037] The statistical period indicates the period configured for the operation time of the state change operation. For example, the statistical period can be monthly statistics, daily statistics, etc. Taking the monthly statistics as an example, the server can extract the record information corresponding to the account that has the state change operation in the month.

[0038] The statistical dimension represents the dimension of information extraction for the configuration of the state change operation. For example, the statistical dimension includes the change success rate and the change failure reason.

[0039] The risk warning condition represents a condition that matches the statistical dimension, and is used to determine whether it is necessary to output a prompt message for prompting the user. Specifically, when the statistical dimension is the change success rate, the risk warning condition is a condition that matches the change success rate. The risk warning condition may, for example, be that the change success rate is less than or equal to the success rate threshold. Similarly, when the statistical dimension is the cause of failure, the risk warning condition is a condition for the cause of failure. The risk warning condition may, for example, include that the number of causes of failure is greater than or equal to the quantity threshold, and / or that the proportion of change failure operations corresponding to the cause of failure is greater than or equal to the proportion threshold.

[0040] Specifically, the server can obtain the statistical parameters configured for the state change operation from the data storage system; or the staff can initiate the configuration operation for the state change operation through the terminal, so that the server can obtain the real-time configured statistical parameters from the terminal. Furthermore, the specific way for the server to obtain the statistical parameters can be active acquisition or passive reception, which is not limited here.

[0041] S204, obtaining record information of each of the multiple state change operations occurring in the current statistical period.

[0042] The recorded information includes the changed status of the account targeted by the status change operation.

[0043] The current statistical period indicates the time range to be counted, for example, from January 1 to February 1.

[0044] The multiple status change operations may represent status change operations occurring in each account, for example, sleep state transition operations occurring in a preset number of accounts within a month.

[0045] The recorded information may be information generated after a state change operation is performed on an account. For example, after the server performs a sleep state change operation on an account, the server generates a sleep state change-related file for the account. The sleep state change-related file records information such as when the sleep state change operation was initiated and whether the sleep state change operation was successful.

[0046] The relationship between the state change operation and the record information may be a one-to-one correspondence, that is, each time a state change operation occurs, there is a piece of record information corresponding to the state change operation.

[0047] The changed status indicates the status of the account after the status change operation is performed on the account. The changed status may include the sleep state, the sleep state, the non-operating state, the non-operating state, the frozen state, the frozen state, etc. Among them, the sleep state indicates that after the account is changed to the sleep state (status change operation), the status of the account is the sleep state. The sleep state indicates that after the account is changed to the sleep state (status change operation), the status of the account is the non-sleep state.

[0048] Specifically, the server can obtain the record information of each of the multiple state change operations occurring in the current statistical period from the data storage system. The record information includes the changed state of the account targeted by the state change operation.

[0049] In one embodiment, before obtaining the statistical parameters configured for the state change operation, the server may perform a state change operation on each account to obtain the changed state of each account.

[0050] In one embodiment, the state change operation is a sleep state operation. In this embodiment, the server performs a sleep state operation on each account to obtain a changed state of each account. The changed state includes a sleep state success state and a sleep state failure state.

[0051] S206: For each state change operation, determine the expected state of the account targeted by the state change operation.

[0052] The statistical dimension represents an information extraction dimension for the configuration of the state change operation. For example, the statistical dimension includes the change success rate and the failure reason.

[0053] The change operation statistical result indicates the statistical result corresponding to the statistical dimension. Specifically, when the statistical dimension is the change success rate, the change operation statistical result is the change operation statistical result corresponding to the change success rate. When the change dimension is the failure cause, the change operation statistical result is the change operation statistical result corresponding to the failure cause dimension.

[0054] Specifically, when the statistical dimension is the change success rate, the server can count the status of each account after the change, and obtain the number of accounts corresponding to the successful change and the number of accounts corresponding to the failed change. The server can obtain the change operation statistical result corresponding to the change success rate based on the two numbers obtained above.

[0055] Specifically, when the statistical dimension is the reason for change failure, the server can count the failure reasons corresponding to the accounts corresponding to the change failure, and obtain the change operation statistical results corresponding to the failure reason dimension. Among them, the statistical result can be the number of failure types corresponding to the change failure. Exemplarily, the server performs a sleep state operation on each account, obtains multiple accounts that fail to sleep, and the server counts the failure reasons corresponding to the accounts that fail to sleep, and obtains the number of failure types corresponding to the change failure.

[0056] The expected state indicates the preset state when the state change operation does not have any abnormality. For example, if the state change operation is a sleep state operation, the expected state may be that the account is switched to the sleep state. For another example, if the state change operation is a non-operating state operation, the expected state may be that the account is switched to the non-operating state. The expected state may also be a preset state among multiple candidate states.

[0057] S208, performing matching analysis on each changed state and each expected state to determine the matching status between each changed state and the expected state of each account.

[0058] The matching condition between the changed state and the expected state of the account may indicate the similarity between the changed state and the expected state, and whether the changed state and the expected state are successfully matched.

[0059] Specifically, the server may perform similarity matching between the changed state of each account and the expected state, and obtain the similarity between each changed state and the expected state, and a matching identifier indicating whether the changed state successfully matches the expected state.

[0060] S210, performing statistics on the matching status of each account according to the statistical dimension to obtain a statistical result of the change operation corresponding to the statistical dimension.

[0061] Specifically, the server may collect statistics on the matching conditions of each account according to the similarity between each changed state and the expected state, and the matching identifier, to obtain the change operation statistical result corresponding to the statistical dimension.

[0062] In one of the embodiments, the matching identifier indicates that the changed state of the account successfully matches the expected state. For each account, the server determines that the account is a successfully changed account when the changed state of the account matches the expected state. The server can determine the proportion of successfully changed accounts in each account as the change operation statistical result corresponding to the change success rate.

[0063] In one of the embodiments, the matching identifier indicates that the changed state of the account fails to match the expected state. For each account, when the changed state of the account does not match the expected state, the failure reason for the failed state change is extracted from the record information belonging to the account. The server can collect statistics on each failure reason to obtain the change operation statistics corresponding to the failure reason dimension.

[0064] In this embodiment, for each state change operation, the expected state of the account targeted by the state change operation is determined, the matching between the changed state of each account and the expected state is determined, and the matching of each account is counted according to the statistical dimension to obtain the statistical result of the change operation corresponding to the statistical dimension. The statistical results of the change operation of each of the multiple statistical dimensions are counted to obtain multiple statistical results of the change operation, which is conducive to the subsequent statistical results of different change operations. Compared with a single statistical dimension, the statistical results under multiple statistical dimensions are more accurate, thereby improving the accuracy of the output risk warning information.

[0065] S212: When the difference between the statistical result of the change operation and the historical statistical result of the historical statistical period meets the risk warning condition, output risk warning information.

[0066] The historical statistical period may be the statistical period before the current statistical period. For example, if the current statistical period is within the current month, the historical statistical period may be the previous month or the previous two months. The historical statistical period may also be a statistical period that partially overlaps with the current statistical period, the end time of the historical statistical period is later than the start time of the current statistical period and earlier than the end time of the current statistical period, and the start time of the historical statistical period is earlier than the start time of the current statistical period. The period length of the historical statistical period is not limited here, and it can be flexibly selected according to the actual situation.

[0067] The historical statistical result may be a historical operation statistical result corresponding to each of the different statistical dimensions. The historical operation statistical result is a result obtained by statistically analyzing the record information of each of the multiple state change operations occurring in the historical statistical period.

[0068] The risk warning information can be used to remind the user that the state change operation has risks. For example, when the state change operation is a sleep state operation, if the difference between the change operation statistics and the historical statistics meets the risk warning condition, the risk warning information indicating the sleep state operation is output, so as to remind the user to handle it immediately.

[0069] Risk warning information can also be used to indicate that there are risks in the statistical dimension. For example, when the statistical dimension is the change success rate, if the difference between the change operation statistical result and the historical statistical result meets the risk warning condition, the risk warning information indicating the change success rate is output. The risk warning information can be that the change success rate is reduced, so as to remind the user to handle it immediately.

[0070] The risk warning condition may be a first warning condition configured for a statistical period, and the risk warning condition may also be a second warning condition configured for a batch status change operation.

[0071] Specifically, when the risk warning condition is the first warning condition configured for the statistical period, the server outputs risk warning information when the difference between the statistical result of the change operation and the historical statistical result of the historical statistical period meets the first warning condition.

[0072] Specifically, when the risk warning condition is the second warning condition configured for the batch status change operation, the server can trigger the batch status change operation for each target account when multiple target accounts meet the status change condition. The server obtains the changed state of each target account in response to the batch status change operation. The server determines the match between the changed state of each target account and the expected state corresponding to the batch status change operation. The server counts the matching conditions of each target account according to the statistical dimension and determines the statistical results of the batch status change operation. When the statistical results meet the second warning condition, the server outputs risk warning information.

[0073] In the above information processing method, the statistical parameters configured for the state change operation are obtained, and the statistical parameters include the statistical period, the statistical dimension, and the risk warning conditions matching the statistical dimension. The record information of each of the multiple state change operations occurring in the current statistical period is obtained. The record information includes the changed state of the account targeted by the state change operation. The record information reflects the state before and after the account change. Each state change operation corresponds to a record information, which is conducive to the subsequent statistics of each change state and improves the accuracy of the statistical results. For each state change operation, the expected state of the account targeted by the state change operation is determined, and the matching analysis of each changed state and each expected state is performed to determine the matching between the changed state and the expected state of each account. The matching of each account is counted according to the statistical dimension to obtain the change operation statistical results corresponding to the statistical dimension. The obtained change statistical results are statistical results under multiple statistical dimensions. Compared with a single statistical dimension, the statistical results under multiple statistical dimensions are more accurate. Using the above method, the obtained change operation statistical results are more accurate. When the difference between the change operation statistical results and the historical statistical results of the historical statistical period meets the risk warning conditions, the output risk warning information is more accurate.

[0074] In one embodiment, the statistical dimension is the change success rate, and the matching status of each account is counted according to the statistical dimension to obtain the change operation statistical result corresponding to the statistical dimension, including: for each account, when the post-change status of the account matches the expected status, the account is determined to be a successfully changed account, and the proportion of successfully changed accounts in each account is determined as the change operation statistical result corresponding to the change success rate.

[0075] The changed state of the account matches the expected state, which can mean that the changed state of the account and the expected state are the same state, for example, both are in the sleeping state. The changed state of the account matches the expected state, which can also mean that the changed state of the account and the expected state are similar states, for example, the changed state is the waiting state for activation, the expected state is the sleeping state, and the waiting state for activation and the sleeping state are similar states.

[0076] A successfully changed account means that the changed status of the account is the same or similar to the expected status.

[0077] Specifically, for each account, the server can determine that the account is a successfully changed account if the changed status of the account matches the expected status. The server can determine the proportion of successfully changed accounts in each account as the change operation statistical result corresponding to the change success rate.

[0078] In one embodiment, the changed state may be a waiting state, a sleeping state, a failed state, etc. The server may determine the accounts corresponding to the waiting state and the sleeping state as successfully changed accounts, and the server may determine the change operation statistics corresponding to the change success rate according to the proportion of successfully changed accounts in each account.

[0079] In this embodiment, for each account, when the post-change status of the account matches the expected status, the account is determined to be a successfully changed account, and the proportion of successfully changed accounts in each account is determined as the change operation statistical result corresponding to the change success rate, so as to obtain accurate change operation statistical results, which is conducive to improving the accuracy of the output risk warning information.

[0080] In one embodiment, the statistical dimension is a failure cause dimension, and statistics are performed on the matching status of each account according to the statistical dimension to obtain a change operation statistical result corresponding to the statistical dimension, including: for each account, when the changed status of the account does not match the expected status, extract the failure reason of the status change failure from the record information belonging to the account, and perform statistics on each failure reason to obtain a change operation statistical result corresponding to the failure cause dimension.

[0081] The record information includes the failure reason of the status change failure. The failure reason indicates the reason that caused the status change failure. There may be multiple failure reasons. For example, if an account is switched to sleep mode, but the account is frozen, the corresponding failure reason is that the account is frozen (cannot be switched to sleep mode successfully). The failure reason can also be that the account is closed, the account is overdrawn, etc.

[0082] The change operation statistics result of the failure reason dimension may indicate the ratio of the number of failure reasons to the number of accounts in the current statistical period, and may also indicate the number corresponding to the type of failure reason in the current statistical period.

[0083] Specifically, for each account, if the changed status of the account does not match the expected status, the server can extract the failure reason for the status change from the record information belonging to the account. The server can count the failure reasons to obtain the ratio of the number of failure reasons to the number of accounts in the current statistical period and / or the number corresponding to the type of failure reasons in the current statistical period.

[0084] In this embodiment, for each account, when the changed state of the account does not match the expected state, the failure reason of the failed state change is extracted from the record information to which the account belongs, and each failure reason is counted to obtain the change operation statistics corresponding to the failure reason dimension. Obtaining accurate change operation statistics is conducive to improving the accuracy of the output risk warning information.

[0085] In one embodiment, the historical statistical period includes multiple candidate periods before the current statistical period, and the information processing method also includes: obtaining the candidate statistical results of each candidate period, determining the weight corresponding to each candidate period according to the time interval between each candidate period and the current period, the weight is inversely correlated with the time interval, and weighting each candidate statistical result according to each weight to obtain the historical statistical result of the historical statistical period.

[0086] The candidate periods may represent statistical periods between current statistical periods, the candidate periods may be complementary and overlapping statistical periods, or the candidate periods may be statistical periods with partially overlapping time periods.

[0087] The candidate statistical result representation may be a historical operation statistical result corresponding to each of the different statistical dimensions. The historical operation statistical result is a result obtained by statistically analyzing the record information of each of the multiple state change operations occurring in the candidate period.

[0088] The time interval represents the time difference between the candidate cycle and the current cycle. Specifically, the time difference may be the difference between the end time of the candidate cycle and the start time of the current cycle. The larger the time interval, the smaller the weight. Conversely, the smaller the time interval, the greater the weight.

[0089] The weight indicates the importance of each candidate period. The candidate statistical result of the candidate period with a smaller time interval is more important than the candidate statistical result of the candidate period with a larger time interval.

[0090] Specifically, the server may weight each candidate statistical result according to each weight to obtain the historical statistical result of the historical statistical period.

[0091] In one of the embodiments, the server may perform mean processing on each candidate statistical result to obtain a historical statistical result of a historical statistical period.

[0092] In one embodiment, the server may also weight each candidate statistical result according to the period length of each candidate period to obtain the historical statistical result of the historical statistical period, wherein the weight is positively correlated with the period length.

[0093] In this embodiment, the candidate statistical results of each candidate period are obtained, and the weights corresponding to each candidate period are determined according to the time intervals between each candidate period and the current period. The weights are inversely correlated with the time intervals. The candidate statistical results are weighted according to the weights to obtain the historical statistical results of the historical statistical period.

[0094] In one embodiment, the information processing method also includes: obtaining a table template configured for a statistical dimension, filling risk warning information, historical statistical results, and change operation statistical results into the to-be-filled position of the table template, and obtaining and outputting a result report for the statistical dimension.

[0095] The table template refers to a preset template for displaying statistical results and prompt information. The preset template has preset positions for filling different information and statistical results.

[0096] The position to be filled indicates the preset filling position in the table template.

[0097] The result report refers to the report containing risk warning information, historical statistical results and change operation statistical results under the statistical dimension.

[0098] Specifically, the server can fill the risk warning information, historical statistical results and change operation statistical results into the to-be-filled positions of the table template. The server can mark the differences between the historical statistical results and the change operation statistical results in the table template, obtain the marked results, fill the marked results into the to-be-filled positions of the table template, and obtain and output the result report for the statistical dimension.

[0099] In one of the embodiments, the server may render the result report in a preset rendering manner to obtain a line graph, a pie chart, a detail table, etc. containing the result report.

[0100] In this embodiment, a table template configured for a statistical dimension is obtained, risk warning information, historical statistical results, and change operation statistical results are filled into the to-be-filled position of the table template, and a result report for the statistical dimension is obtained and output to facilitate display to users and provide users with a comprehensive reference.

[0101] In one embodiment, as shown in FIG3 , the risk warning condition includes a first warning condition configured for a statistical period and a second warning condition configured for a batch state change operation, and the information processing method further includes:

[0102] S302: When multiple target accounts meet the status change condition, trigger a batch status change operation for each target account.

[0103] It should be noted that the target account refers to the account for batch status change operations, and the account in the aforementioned embodiment refers to the account for status change operations.

[0104] Among them, the state change condition represents the trigger condition for the state change configured for the account. For example, the trigger condition may be that the account has not been used for a preset period of time, and the account is considered to meet the state change condition, that is, the account is the target account. The trigger condition may also be that the account has not been used for a preset period of time, and the number of such accounts reaches a preset value, and such accounts are considered to meet the state change condition.

[0105] For example, if the target account has not been used for more than 3 years, when the number of target accounts reaches the preset value, a batch status change operation for each target account is triggered. This can make up for the lag of periodic statistics, improve the real-time nature of statistics, further improve the accuracy of statistical results, and improve the accuracy of subsequent output risk warning information.

[0106] Batch status change operations mean performing status change operations on multiple target accounts at the same time.

[0107] S304, in response to the batch status change operation, obtaining the changed status of each target account.

[0108] Among them, the batch change operation can be actively triggered or automatically triggered.

[0109] Specifically, the server may obtain the changed state of each target account in response to a batch state change operation actively triggered by a user. The server may obtain the changed state of each target account in response to an automatically triggered batch state change operation.

[0110] In one of the embodiments, for the automatic triggering scenario, the server may trigger a batch status change operation for each target account when the number of target accounts that meet the status change condition reaches a preset value, and obtain the changed status of each target account.

[0111] S306: Determine the matching status between the changed status of each target account and the expected status corresponding to the batch status change operation.

[0112] The matching condition between the changed state and the expected state of the target account may indicate the similarity between the changed state and the expected state, and whether the changed state and the expected state are successfully matched.

[0113] Specifically, the server may perform similarity matching between the changed state of each target account and the expected state, and obtain the similarity between each changed state and the expected state, and a matching identifier indicating whether the changed state successfully matches the expected state.

[0114] S308, performing statistics on the matching status of each target account according to the statistical dimension to determine the statistical result of the batch status change operation.

[0115] The statistical results of batch state change operations may represent statistical results corresponding to statistical dimensions. Specifically, when the statistical dimension is change success rate, the statistical results of batch state change operations are statistical results of change operations corresponding to change success rate. When the change dimension is failure cause, the statistical results of batch state change operations are statistical results of change operations corresponding to failure cause dimension.

[0116] Specifically, the server can count the matching conditions of each target account according to the change success rate to obtain the statistical results corresponding to the change success rate, and the server can count the matching conditions of each target account according to the failure reason to obtain the statistical results corresponding to the failure reason. The statistical results of the batch status change operation include the statistical results corresponding to the change success rate and the statistical results corresponding to the failure reason.

[0117] S310: When the statistical result meets the second warning condition, output risk warning information.

[0118] The second warning condition represents a warning condition configured for batch state change operations. The second warning condition may be a threshold value configured for each of the different preset dimensions. When the difference between the statistical result and the historical statistical result is greater than the threshold value, the statistical result is considered to meet the second warning condition. When the difference between the statistical result and the historical statistical result is less than or equal to the threshold value, the statistical result is considered not to meet the second warning condition.

[0119] The risk warning information indicates information used to warn the user that a state change operation involves risks.

[0120] In this embodiment, when multiple target accounts meet the status change condition, a batch status change operation is triggered for each target account. In response to the batch status change operation, the changed status of each target account is obtained, and the match between the changed status of each target account and the expected status corresponding to the batch status change operation is determined. The matching status of each target account is counted according to the statistical dimension, and the statistical result of the batch status change operation is determined. When the statistical result meets the second warning condition, risk warning information is output, which can make up for the lag of periodic statistics, improve the real-time performance of statistics, further improve the accuracy of the statistical results, and improve the accuracy of the subsequent output risk warning information.

[0121] In one embodiment, as shown in FIG4 , an automatic analysis method based on distributed core bank account status is provided, including:

[0122] S402: Obtain statistical parameters configured for the state change operation.

[0123] Among them, the statistical parameters include the statistical period, statistical dimension, and risk warning conditions matching the statistical dimension.

[0124] S404, obtaining record information of each of multiple state change operations occurring in the current statistical period.

[0125] The recorded information includes the changed status of the account targeted by the status change operation.

[0126] S406: For each state change operation, determine the expected state of the account targeted by the state change operation.

[0127] S408, performing matching analysis on each changed state and each expected state to determine the matching status between each changed state and the expected state of each account.

[0128] S410, for each account, if the changed state of the account matches the expected state, determine that the account is a successfully changed account.

[0129] Among them, the statistical dimension is the change success rate.

[0130] S412, determining the proportion of successfully changed accounts in each account as a change operation statistical result corresponding to the change success rate.

[0131] Exemplarily, the proportion of accounts with successful changes in each account is shown in the following table.

[0132] Table 1

[0133] Business Functions total success fail Success rate Switch to sleep 100 100 0 100% Transfer to other business 200 100 100 50%

[0134] Among them, "Go to Sleep" means that the account status change operation is a "Go to Sleep" operation. The field corresponding to "Go to Sleep" indicates that the proportion of successfully changed accounts in each account is 100%.

[0135] Transfer to non-operating means that the account status change operation is a non-operating status operation. The corresponding field of Transfer to non-operating indicates that the proportion of successfully changed accounts in all accounts is 50%.

[0136] S414, for each account, when the changed state of the account does not match the expected state, extract the failure reason of the state change failure from the record information belonging to the account.

[0137] Among them, the statistical dimension is the failure reason dimension.

[0138] S416, performing statistics on each failure reason to obtain a statistical result of the change operation corresponding to the failure reason dimension.

[0139] S418, obtaining the candidate statistics results of each candidate period.

[0140] The historical statistical period includes multiple candidate periods before the current statistical period.

[0141] S420: Determine the weight corresponding to each candidate period according to the time interval between each candidate period and the current period.

[0142] Among them, the weight is inversely correlated with the time interval.

[0143] S422, weighting each candidate statistical result according to each weight to obtain a historical statistical result of a historical statistical period.

[0144] S424: When the difference between the statistical result of the change operation and the historical statistical result of the historical statistical period meets the risk warning condition, output risk warning information.

[0145] Exemplarily, the risk warning condition also includes a first warning condition configured for a statistical period and a second warning condition configured for a batch status change operation.

[0146] Specifically, the server may output risk warning information when the difference between the statistical result of the change operation and the historical statistical result of the historical statistical period meets the first warning condition.

[0147] Specifically, the server may trigger a batch state change operation for each target account when multiple target accounts meet the state change condition. The server may obtain the changed state of each target account in response to the batch state change operation. The server may determine the match between the changed state of each target account and the expected state corresponding to the batch state change operation. The server may count the matching conditions of each target account according to the statistical dimension and determine the statistical results of the batch state change operation. The server may output risk warning information when the statistical results meet the second warning condition.

[0148] Exemplarily, a method for automatically processing sleep transition is also provided, including:

[0149] Step 1, program start; Step 2, read the specified directory file through the scheduled task; Step 3, for the convenience of long-term use, write the configuration file to the library; Step 4, download the sleep file in HDFS according to the configuration file; Step 5, process the past sleep file and the current sleep file to obtain the processing business data summary; Step 6, compare the sleep results, and issue an early warning for the sleep results that do not meet the expected conditions; Step 7, output multiple report data based on the processed business data summary for front-end use.

[0150] Among them, step 4 includes downloading the sleep file in HDFS according to the configuration file (input into the Java hdfs api).

[0151] Among them, "putting the card into dormancy" means that according to the bank's regulations, if no transactions have occurred on the bank card within a certain period of time, the bank card will be put into dormancy according to relevant business conditions (such as zero balance). After the card is put into dormancy, you will not be able to withdraw money and need to go to the business hall to activate it.

[0152] In the traditional way, you need to log in to the database server - enter the ISB library - find the file index table - find the desired index data according to the batch number and job or batch number and file name, copy the index file name, log in to the HDFS server - enter the HDFS script directory - enter the statistical command and the specific file path - execute the command to view the results. Due to the cumbersome operation, only one file can be checked each time, and some jobs will generate a large number of files, which brings great inconvenience to the reviewers. At present, there is no good method, strategy or invention to support this business.

[0153] HDFS is a distributed file system and a highly fault-tolerant system that can provide high-throughput data access and is often used in large-scale data set applications.

[0154] Java HDFS API: Java HDFS API interface, which can perform a series of operations on HDFS files through the HDFS API.

[0155] File index table: The specific paths of files generated by all jobs will be recorded in this table.

[0156] ISB library: connects to the upper layer Luban to initiate requests, parses job metadata, builds job step context, manages job flow, distributes job steps to the queue to be scheduled, the queue is consumed by DSB, and returns the result to Luban after the job is processed.

[0157] S426, obtaining a table template configured for the statistical dimension.

[0158] S428, fill the risk warning information, historical statistical results and change operation statistical results into the to-be-filled position of the table template, and obtain and output the result report for the statistical dimension.

[0159] In this embodiment, the statistical parameters configured for the state change operation are obtained, and the statistical parameters include the statistical period, the statistical dimension, and the risk warning conditions matching the statistical dimension. The record information of each of the multiple state change operations occurring in the current statistical period is obtained. The record information includes the changed state of the account targeted by the state change operation. The record information reflects the state before and after the account change. Each state change operation corresponds to a record information, which is conducive to the subsequent statistics of each change state and improves the accuracy of the statistical results. The changed state of each account is counted according to the statistical dimension to obtain the statistical result of the change operation corresponding to the statistical dimension. The obtained change statistical result is the statistical result under multiple statistical dimensions. Compared with a single statistical dimension, the statistical result under multiple statistical dimensions has higher accuracy. Using the above method, the obtained change operation statistical result is more accurate. When the difference between the change operation statistical result and the historical statistical result of the historical statistical period meets the risk warning condition, the output risk warning information is more accurate. In this method, on the one hand, the checker does not need to manually download-merge-manually parse the file-statistics, and the checker only needs to focus on the result itself to improve the check efficiency. On the other hand, the checker does not need to perform complex and cumbersome manual data processing, which can greatly reduce the statistical error rate.

[0160] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0161] Based on the same inventive concept, the embodiment of the present application also provides an information processing device for implementing the above-mentioned information processing method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above-mentioned method, so the specific limitations in the one or more information processing device embodiments provided below can refer to the limitations on the information processing method above, and will not be repeated here.

[0162] In one embodiment, as shown in FIG5 , an information processing device is provided, including:

[0163] The parameter acquisition module 502 is used to acquire statistical parameters configured for the state change operation; the statistical parameters include a statistical period, a statistical dimension, and a risk warning condition matching the statistical dimension;

[0164] The information acquisition module 504 is used to acquire the record information of each of the multiple status change operations occurring in the current statistical period; the record information includes the changed status of the account targeted by the status change operation;

[0165] A state determination module 506, configured to determine, for each state change operation, an expected state of the account targeted by the state change operation;

[0166] A matching determination module 508, for performing matching analysis on each changed state and each expected state, and determining a matching condition between each changed state and the expected state of each account;

[0167] A statistical result determination module 510 is used to count the matching conditions of each of the accounts according to the statistical dimension to obtain a statistical result of the change operation corresponding to the statistical dimension;

[0168] The first information output module 512 is used to output risk warning information when the difference between the change operation statistical result and the historical statistical result of the historical statistical period meets the risk warning condition.

[0169] In one embodiment, the statistical dimension is the change success rate; the statistical result determination module 510 includes:

[0170] An account change unit, for each account, determining that the account is a successfully changed account when the changed state of the account matches the expected state;

[0171] The statistical result determination unit is used to determine the proportion of successfully changed accounts in each account as a change operation statistical result corresponding to the change success rate.

[0172] In one embodiment, the statistical dimension is the failure cause dimension; the statistical result determination module 510 includes:

[0173] A reason extraction unit is used to extract the failure reason of the state change failure from the record information belonging to the account for each account when the state after the change of the account does not match the expected state;

[0174] The cause statistics unit is used to collect statistics on each failure cause and obtain the change operation statistics result corresponding to the failure cause dimension.

[0175] In one embodiment, the historical statistical period includes a plurality of candidate periods before the current statistical period; the information processing device 600 further includes:

[0176] A result acquisition module is used to obtain the candidate statistical results of each candidate period;

[0177] A weight determination module, used to determine the weight corresponding to each candidate period according to the time interval between each candidate period and the current period; the weight is inversely correlated with the time interval;

[0178] The statistical result determination module is used to weight each candidate statistical result according to each weight to obtain the historical statistical result of the historical statistical period.

[0179] In one embodiment, the information processing device 600 further includes:

[0180] The template acquisition module is used to obtain the table template configured for the statistical dimension;

[0181] The report output module is used to fill the risk warning information, historical statistical results and change operation statistical results into the to-be-filled position of the table template, and obtain and output the result report for the statistical dimension.

[0182] In one embodiment, the risk warning condition includes a first warning condition configured for a statistical period and a second warning condition configured for a batch status change operation;

[0183] The information processing device 500 further includes:

[0184] A trigger operation module is used to trigger a batch status change operation for each target account when multiple target accounts meet the status change conditions;

[0185] A status acquisition module, used to respond to the batch status change operation and obtain the changed status of each target account;

[0186] A matching status determination module, used to determine the matching status between the changed status of each target account and the expected status corresponding to the batch status change operation;

[0187] The matching situation statistics module is used to count the matching situation of each target account according to the statistical dimension and determine the statistical results of batch status change operations;

[0188] The second information output module is used to output risk warning information when the statistical results meet the second warning condition.

[0189] Each module in the above information processing device can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0190] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be shown in FIG6. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store statistical parameters and record information data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an information processing method is implemented.

[0191] Those skilled in the art will understand that the structure shown in FIG. 6 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0192] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the above method steps are implemented when the processor executes the computer program.

[0193] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the above method steps are implemented.

[0194] In one embodiment, a computer program product is provided, comprising a computer program, which implements the above method steps when executed by a processor.

[0195] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. In addition, the acquisition, storage, processing, and transmission of data are in compliance with relevant laws and regulations.

[0196] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0197] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0198] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. An information processing method, characterized in that: The method comprises: Obtain statistical parameters configured for the state change operation; the statistical parameters include a statistical period, a statistical dimension, and a risk warning condition matching the statistical dimension; Obtaining record information of each of multiple status change operations occurring in the current statistical period; the record information includes the changed status of the account targeted by the status change operation; For each of the state change operations, determining an expected state of the account targeted by the state change operation; Performing matching analysis on each of the changed states and each of the expected states to determine the matching status between the changed state and the expected state of each of the accounts; According to the statistical dimension, statistics are collected on the matching situations of the respective accounts to obtain statistical results of the change operations corresponding to the statistical dimension; When the difference between the statistical result of the change operation and the historical statistical result of the historical statistical period meets the risk warning condition, risk warning information is output.

2. The method according to claim 1, characterized in that The statistical dimension is the change success rate; The performing statistics on the matching situations of the respective accounts according to the statistical dimension to obtain the statistical result of the change operation corresponding to the statistical dimension includes: For each of the accounts, if the changed state of the account matches the expected state, determining the account as a successfully changed account; The proportion of accounts with successful changes in each of the accounts is determined as a change operation statistical result corresponding to the change success rate.

3. The method according to claim 1, characterized in that The statistical dimension is the failure cause dimension; The performing statistics on the matching situations of the respective accounts according to the statistical dimension to obtain the statistical result of the change operation corresponding to the statistical dimension includes: For each of the accounts, if the changed state of the account does not match the expected state, extracting the failure reason for the failed state change from the record information to which the account belongs; Statistics are collected for each of the failure reasons to obtain a statistical result of the change operation corresponding to the failure reason dimension.

4. The method according to claim 1, characterized in that: The historical statistical period includes a plurality of candidate periods before the current statistical period; The method further comprises: Obtaining candidate statistical results for each of the candidate periods; Determine the weight corresponding to each of the candidate cycles according to the time interval between each of the candidate cycles and the current cycle; the weight is inversely correlated with the time interval; The candidate statistical results are weighted according to the weights to obtain the historical statistical results of the historical statistical period.

5. The method according to claim 1, characterized in that The method further comprises: Obtaining a table template configured for the statistical dimension; The risk warning information, the historical statistical results and the change operation statistical results are filled into the to-be-filled position of the table template to obtain and output a result report for the statistical dimension.

6. The method according to any one of claims 1 to 5, characterized in that The risk warning conditions include a first warning condition configured for a statistical period and a second warning condition configured for a batch status change operation; The method further comprises: When multiple target accounts meet the status change condition, triggering a batch status change operation for each of the target accounts; In response to the batch status change operation, obtaining the changed status of each of the target accounts; Determine a match between the changed state of each of the target accounts and the expected state corresponding to the batch state change operation; Performing statistics on the matching status of each of the target accounts according to the statistical dimension to determine the statistical result of the batch status change operation; When the statistical result meets the second warning condition, risk warning information is output.

7. An information processing device, characterized in that: The device comprises: A parameter acquisition module, used to acquire statistical parameters configured for the state change operation; the statistical parameters include a statistical period, a statistical dimension, and a risk warning condition matching the statistical dimension; An information acquisition module, used to acquire the record information of each of the multiple status change operations occurring in the current statistical period; the record information includes the changed status of the account targeted by the status change operation; A state determination module, configured to determine, for each state change operation, an expected state of the account targeted by the state change operation; A matching determination module, used to perform matching analysis on each of the changed states and each of the expected states, and determine the matching between the changed state and the expected state of each of the accounts; A statistical result determination module, used for performing statistics on the matching conditions of each of the accounts according to the statistical dimension, and obtaining a statistical result of the change operation corresponding to the statistical dimension; The first information output module is used to output risk warning information when the difference between the statistical result of the change operation and the historical statistical result of the historical statistical period meets the risk warning condition.

8. The device according to claim 7, characterized in that The statistical dimension is the change success rate; the statistical result determination module includes: An account changing unit, configured to determine, for each of the accounts, that the account is a successfully changed account if the changed state of the account matches the expected state; The statistical result determination unit is used to determine the proportion of successfully changed accounts in each of the accounts as a change operation statistical result corresponding to the change success rate.

9. The device according to claim 7, characterized in that The statistical dimension is the failure cause dimension; the statistical result determination module includes: a reason extraction unit, configured to extract, for each of the accounts, a failure reason for the failure of the state change from the record information to which the account belongs, when the changed state of the account does not match the expected state; The cause statistics unit is used to collect statistics on the failure causes to obtain the change operation statistics results corresponding to the failure cause dimension.

10. The device according to claim 7, characterized in that The historical statistical period includes a plurality of candidate periods before the current statistical period; the device further includes: A result acquisition module, used to obtain the candidate statistical results of each candidate period; A weight determination module, used to determine the weight corresponding to each of the candidate cycles according to the time interval between each of the candidate cycles and the current cycle; the weight is inversely correlated with the time interval; The statistical result determination module is used to weight the candidate statistical results according to the weights to obtain the historical statistical results of the historical statistical period.

11. The device according to claim 7, characterized in that The information processing device further includes: A template acquisition module, used to acquire a table template configured for the statistical dimension; The report output module is used to fill the risk warning information, the historical statistical results and the change operation statistical results into the to-be-filled position of the table template, and obtain and output the result report for the statistical dimension.

12. The device according to any one of claims 7 to 11, characterized in that The risk warning conditions include a first warning condition configured for a statistical period and a second warning condition configured for a batch status change operation; The information processing device further includes: A trigger operation module, used for triggering a batch status change operation for each of the target accounts when the multiple target accounts meet the status change condition; A status acquisition module, configured to acquire the changed status of each of the target accounts in response to the batch status change operation; A matching status determination module, used to determine the matching status between the changed status of each of the target accounts and the expected status corresponding to the batch status change operation; A matching situation statistics module, used to count the matching situation of each of the target accounts according to the statistical dimension, and determine the statistical result of the batch status change operation; The second information output module is used to output risk warning information when the statistical result meets the second warning condition.

13. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

15. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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