Business data detection method and device, equipment, storage medium and program product

Abstract

The invention relates to a business data detection method and device, equipment, a storage medium and a program product. The method comprises the following steps: acquiring business data associated with a target business; converting the service data into structured data according to a data type and a data format indicated by preset data specification information; according to the business type of the target business, determining a target business rule corresponding to the target business, the target business rule being used for indicating key risk data in structured data corresponding to the target business and a risk triggering condition corresponding to the key risk data; and identifying the structured data corresponding to the target business according to the target business rule to obtain a risk detection result. By adopting the method, the detection efficiency of the business data can be improved.

Description

Technical Field

[0001] The present application relates to the field of information technology, and in particular to a method, device, equipment, storage medium and program product for detecting business data. Background Art

[0002] With the development of information technology, more and more businesses are beginning to use information systems to collect and process business data. Due to the continuous growth of business scale and the continuous increase of business lines, in the process of handling business, there may be a phenomenon of taking non-compliant business operations in order to complete performance appraisals and other reasons.

[0003] In the related art, by testing business data, non-compliant business operations in the business can be discovered in a timely manner. Usually, the auditor can manually test the business data from the perspective of the business itself and the business operation. However, the efficiency of manual testing of business data is low. Summary of the invention

[0004] Based on this, it is necessary to provide a business data detection method, device, equipment, storage medium and program product that can improve the detection efficiency of business data in response to the above technical problems.

[0005] In a first aspect, the present application provides a method for detecting business data, comprising:

[0006] Obtain business data associated with the target business;

[0007] Convert the business data into structured data according to the data type and data format indicated by the preset data specification information;

[0008] Determine, according to the business type of the target business, a target business rule corresponding to the target business, wherein the target business rule is used to indicate key risk data in the structured data corresponding to the target business and a risk trigger condition corresponding to the key risk data;

[0009] According to the target business rules, the structured data corresponding to the target business is identified to obtain a risk detection result.

[0010] In one embodiment, the key risk data includes execution location data of the target business; and the structured data corresponding to the target business is identified according to the target business rule to obtain a risk detection result, including:

[0011] Determining a maximum execution distance difference of the target service according to the execution position data of the target service;

[0012] If the maximum execution distance difference of the target business is greater than the distance difference threshold, it is determined that the target business meets the risk trigger condition, and a first risk detection result is generated, where the first risk detection result is used to indicate that the target business has a risk;

[0013] If the maximum execution distance difference of the target business is less than or equal to the distance difference threshold, it is determined that the target business does not meet the risk trigger condition, and a second risk detection result is generated, where the second risk detection result is used to indicate that there is no risk for the target business.

[0014] In one embodiment, the key risk data includes execution object data of the target business; and the structured data corresponding to the target business is identified according to the target business rules to obtain the risk detection result, including:

[0015] If the execution object data of the target business includes a risk warning object, determining that the target business meets the risk trigger condition, and generating a first risk detection result, the first risk detection result is used to indicate that the target business has a risk;

[0016] If the execution object data of the target business does not include the risk warning object, it is determined that the target business does not meet the risk trigger condition, and a second risk detection result is generated, where the second risk detection result is used to indicate that there is no risk in the target business.

[0017] In one of the embodiments, after identifying the structured data corresponding to the target business according to the target business rule to obtain the risk detection result, the method further includes:

[0018] According to the business type of the target business and the risk detection result, the target business is classified and counted to obtain a compliant business classification statistical chart and a risky business classification statistical chart;

[0019] A chart display instruction is sent to a terminal device, wherein the chart display instruction is used to instruct the terminal device to display the compliance business classification statistical chart and the risk business classification statistical chart.

[0020] In one embodiment, the acquiring the service data associated with the target service includes:

[0021] Determine the data sources corresponding to the multiple business operations of the target business respectively;

[0022] The business data associated with the target business is obtained from data sources corresponding to the multiple business operations respectively.

[0023] In one of the embodiments, the data format includes data length and data precision.

[0024] In a second aspect, the present application also provides a device for detecting business data, including:

[0025] An acquisition module is used to acquire business data associated with a target business;

[0026] A conversion module, used to convert the business data into structured data according to the data type and data format indicated by the preset data specification information;

[0027] A determination module, used to determine a target business rule corresponding to the target business according to the business type of the target business, wherein the target business rule is used to indicate key risk data in the structured data corresponding to the target business and a risk trigger condition corresponding to the key risk data;

[0028] The identification module is used to identify the structured data corresponding to the target business according to the target business rules to obtain risk detection results.

[0029] In one embodiment, the key risk data includes execution location data of the target business; the identification module is further used to determine the maximum execution distance difference of the target business based on the execution location data of the target business; if the maximum execution distance difference of the target business is greater than the distance difference threshold, it is determined that the target business meets the risk trigger condition, and a first risk detection result is generated, and the first risk detection result is used to indicate that the target business is at risk; if the maximum execution distance difference of the target business is less than or equal to the distance difference threshold, it is determined that the target business does not meet the risk trigger condition, and a second risk detection result is generated, and the second risk detection result is used to indicate that the target business is not at risk.

[0030] In one embodiment, the key risk data includes execution object data of the target business; the identification module is also used to determine that the target business meets the risk trigger condition if the execution object data of the target business includes a risk warning object, and generate a first risk detection result, the first risk detection result is used to indicate that the target business is at risk; if the execution object data of the target business does not include the risk warning object, it is determined that the target business does not meet the risk trigger condition, and a second risk detection result is generated, the second risk detection result is used to indicate that the target business is not at risk.

[0031] In one of the embodiments, the identification module is further used to classify and count the target business according to the business type of the target business and the risk detection result, to obtain a compliant business classification statistical chart and a risky business classification statistical chart; and to send a chart display instruction to the terminal device, wherein the chart display instruction is used to instruct the terminal device to display the compliant business classification statistical chart and the risky business classification statistical chart.

[0032] In one of the embodiments, the acquisition module is used to determine data sources corresponding to multiple business operations of the target business; and acquire business data associated with the target business from the data sources corresponding to the multiple business operations.

[0033] In one of the embodiments, the data format includes data length and data precision.

[0034] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the above-mentioned business data detection method when executing the computer program.

[0035] In a fourth aspect, the present application also provides a computer-readable storage medium having a computer program stored thereon, and the computer program implements the above-mentioned business data detection method when executed by a processor.

[0036] In a fifth aspect, the present application also provides a computer program product, including a computer program, which implements the above-mentioned business data detection method when executed by a processor.

[0037] The above-mentioned business data detection method, device, equipment, storage medium and program product first obtain the business data associated with the target business; secondly, convert the business data into structured data according to the data type and data format indicated by the preset data specification information; thirdly, determine the target business rules corresponding to the target business according to the business type of the target business, and the target business rules are used to indicate the key risk data in the structured data corresponding to the target business and the risk trigger conditions corresponding to the key risk data; finally, according to the target business rules, identify the structured data corresponding to the target business to obtain the risk detection result. By converting the business data into structured data and then identifying the structured data based on the target business rules, the automatic detection of business data can be realized, which improves the detection efficiency of business data. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0039] Figure 1 An application environment diagram of a business data detection method provided in an embodiment of the present application;

[0040] Figure 2 A flowchart of a method for detecting business data provided in an embodiment of the present application;

[0041] Figure 3 A flowchart of another method for detecting business data provided in an embodiment of the present application;

[0042] Figure 4 A flowchart of another method for detecting business data provided in an embodiment of the present application;

[0043] Figure 5 A structural block diagram of a device for detecting business data provided in an embodiment of the present application;

[0044] Figure 6 An internal structure diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0045] 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.

[0046] The method for detecting business data provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown, the terminal 102 communicates with the server 104 through a network. The data storage system can store data that the server 104 needs to process. The data storage system can be integrated on the server 104, or placed on the cloud or other network servers.

[0047] The terminal 102 sends a target business detection request to the server 104, and the target business detection request includes the business data associated with the target business. Secondly, after the server 104 obtains the business data associated with the target business from the target business detection request, it can convert the business data into structured data according to the data type and data format indicated by the preset data specification information. Thirdly, the server 104 determines the target business rules corresponding to the target business according to the business type of the target business. The target business rules are used to indicate the key risk data in the structured data corresponding to the target business and the risk trigger conditions corresponding to the key risk data. Finally, the server 104 identifies the structured data corresponding to the target business according to the target business rules to obtain the risk detection results.

[0048] 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 devices, projection devices, etc. Portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. Head-mounted devices may be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc. The server 104 may be an independent physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server that provides cloud computing services.

[0049] In an exemplary embodiment, Figure 2 As shown, a method for detecting business data is provided, and the method is applied to Figure 1 Taking the server in as an example, the detection of the business data includes: S201-S204:

[0050] S201. Obtain business data associated with a target business.

[0051] In this application, when compliance verification of a target business is required, business data associated with the target business can be obtained.

[0052] Among them, the above-mentioned target business includes any type of business, including marketing business, after-sales business, production business, etc., and the embodiments of the present application do not limit this.

[0053] In some embodiments, business data may include business execution data and business execution object data. Business execution data includes execution location data of the target business, vehicle usage information during the execution of the target business, etc. Business execution object data includes identity information of the business execution object.

[0054] In some embodiments, for the same target business, there may be multiple different business operations, and the data sources of the business data generated by different business operations are different. Accordingly, the server may determine the data sources corresponding to the multiple business operations of the target business, and then obtain the business data associated with the target business from the data sources corresponding to the multiple business operations.

[0055] For example, in the process of executing the target business, business execution operations such as authorization operations, voice verification operations, and data collection operations can be implemented through the business terminal. Accordingly, the business terminal can serve as the data source of the business data; query operations and data upload operations can be implemented through the data warehouse or data lake in the server. Accordingly, the data warehouse or data lake in the server can also serve as the data source of the business data.

[0056] Accordingly, the embodiments of the present application do not limit how to obtain the business data associated with the target business. In some embodiments, the terminal device can send a target business detection request to the server, and the target business detection request includes the business data associated with the target business, and the server then obtains the business data associated with the target business from the target business detection request. In other embodiments, the server can obtain the business data associated with the target business from a data warehouse or a data lake.

[0057] S202: Convert the business data into structured data according to the data type and data format indicated by the preset data specification information.

[0058] In this step, after the server obtains the business data associated with the target business, it can convert the business data into structured data according to the data type and data format indicated by the preset data specification information.

[0059] Among them, data types include date type, amount type, integer type, etc. Data types are used to standardize the character standard style of structured data. Data format includes data length and data precision.

[0060] Exemplarily, if the business data includes the occurrence date data of the business event, the data type of the occurrence date data of the business event is date type; if the business data includes the transaction amount data generated by the business event, the data type of the transaction amount data is amount type.

[0061] For example, for structured data of monetary amount, the data format may set the data length to 24 bits and the data precision to 2 digits.

[0062] It should be understood that different types of business data correspond to different data specification information, and the data specification information corresponding to various types of business data can be updated or set through the terminal device.

[0063] The embodiments of the present application do not limit how to convert business data into structured data according to the data type and data format indicated by the preset data specification information. In some embodiments, a corresponding data template can be generated in advance based on the data type and data format indicated by the data specification information. After the server cleans the business data and identifies the business data to be converted, it can extract valid characters from the business data to be converted and fill them into the data template to form the corresponding structured data.

[0064] In this application, by converting business data into structured data, the integrity, standardization, validity and accuracy of the data can be guaranteed, thereby completing the integration and cleaning of business data.

[0065] S203: Determine a target business rule corresponding to the target business according to the business type of the target business.

[0066] In this step, after the server converts the business data into structured data according to the data type and data format indicated by the preset data specification information, the target business rule corresponding to the target business can be determined according to the business type of the target business.

[0067] The target business rules are used to indicate key risk data in the structured data corresponding to the target business and risk triggering conditions corresponding to the key risk data.

[0068] Exemplarily, the target business rules may include distance rules, execution object rules, business type rules, execution location rules, business amount rules, etc. Different target business rules identify different key risk data and risk triggering conditions.

[0069] The above-mentioned key risk data may include the execution location data of the target business, the execution object data of the target business, etc. Accordingly, for the execution location data of the target business, the risk trigger condition may be that the maximum execution distance difference is greater than the distance difference threshold; for the execution object data of the target business, the risk trigger condition may be that the execution object data includes a risk warning object.

[0070] S204: According to the target business rules, the structured data corresponding to the target business is identified to obtain risk detection results.

[0071] In this step, after the server determines the target business rule corresponding to the target business according to the business type of the target business, it can identify the structured data corresponding to the target business according to the target business rule to obtain the risk detection result.

[0072] In some embodiments, for the case where the key risk data in the target business rule is the execution location data of the target business, the server can determine the maximum execution distance difference of the target business based on the execution location data of the target business. If the maximum execution distance difference of the target business is greater than the distance difference threshold, the server determines that the target business meets the risk trigger condition and generates a first risk detection result, which is used to indicate that the target business is at risk. If the maximum execution distance difference of the target business is less than or equal to the distance difference threshold, the server determines that the target business does not meet the risk trigger condition and generates a second risk detection result, which is used to indicate that the target business is not at risk.

[0073] Exemplarily, the above-mentioned execution location data may be longitude and latitude data, and the distance difference threshold may be a maximum number of kilometers. Accordingly, during the execution of the service, the service terminal may collect longitude and latitude data of multiple execution locations along the way, and determine the number of kilometers between the two farthest execution locations through the longitude and latitude data of multiple execution locations. When the number of kilometers between the two farthest execution locations is greater than the maximum number of kilometers, the risk trigger condition is met, and a first risk detection result is generated. When the number of kilometers between the two farthest execution locations is less than or equal to the maximum number of kilometers, the risk trigger condition is not met, and a second risk detection result is generated.

[0074] In some embodiments, for the case where the key risk data in the target business rule is the execution object data of the target business, if the execution object data of the target business includes a risk warning object, the server determines that the target business meets the risk trigger condition and generates a first risk detection result, which is used to indicate that the target business has a risk. If the execution object data of the target business does not include a risk warning object, the server determines that the target business does not meet the risk trigger condition and generates a second risk detection result, which is used to indicate that the target business does not have a risk.

[0075] It should be noted that if there are multiple target business rules, the structured data can be identified according to each target business rule. When all target business rules do not meet the risk triggering conditions, it can be determined that the target business does not have risks. When any target business rule meets the risk triggering conditions, it can be determined that the target business has risks.

[0076] In other embodiments, after obtaining the risk detection result, the server can also classify and count the target business according to the business type and risk detection result of the target business, and obtain a compliant business classification statistical chart and a risk business classification statistical chart. Subsequently, the server sends a chart display instruction to the terminal device.

[0077] Among them, the chart display instruction is used to instruct the terminal device to display the compliance business classification statistical chart and the risk business classification statistical chart.

[0078] For example, the compliant business classification statistics chart may include the number of target businesses without risks classified by each business type, and the risk business classification statistics chart may include the number of target businesses with risks classified by each business type. The compliant business classification statistics chart and the risk business classification statistics chart may be presented in the form of a bar chart, a pie chart, or the like.

[0079] For example, after the terminal device displays the compliance business classification statistical chart and the risk business classification statistical chart, the terminal device can interact with the server to obtain the business data of the target business with risks for the user to verify and determine the responsibility, thus forming a closed processing loop.

[0080] In this application, by collecting, integrating and cleaning business data and screening and identifying business data in multiple dimensions through business rule screening, behaviors and businesses with compliance risks can be intelligently identified. Therefore, the business data detection method provided in the embodiment of this application can improve the detection efficiency of business data and reduce the detection cost.

[0081] The method for detecting business data provided in the embodiment of the present application first obtains the business data associated with the target business. Secondly, the business data is converted into structured data according to the data type and data format indicated by the preset data specification information. Thirdly, according to the business type of the target business, the target business rules corresponding to the target business are determined, and the target business rules are used to indicate the key risk data in the structured data corresponding to the target business and the risk trigger conditions corresponding to the key risk data. Finally, according to the target business rules, the structured data corresponding to the target business is identified to obtain the risk detection result. By converting the business data into structured data and then identifying the structured data based on the target business rules, the automatic detection of the business data can be achieved, thereby improving the detection efficiency of the business data.

[0082] The following describes how to identify structured data. Figure 3 A flow chart of another method for detecting business data provided in an embodiment of the present application is shown as follows: Figure 3 As shown, the business data detection method includes S301-S308:

[0083] S301: Acquire business data associated with a target business.

[0084] S302: Convert the business data into structured data according to the data type and data format indicated by the preset data specification information.

[0085] S303: Determine a target business rule corresponding to the target business according to the business type of the target business.

[0086] The target business rules are used to indicate key risk data in the structured data corresponding to the target business and risk triggering conditions corresponding to the key risk data.

[0087] S304: Determine whether the structured data includes execution location data of the target service.

[0088] S305: Determine the maximum execution distance difference of the target service according to the execution position data of the target service.

[0089] S306: Determine whether the maximum execution distance difference of the target service is greater than a distance difference threshold.

[0090] If yes, execute S307, if no, execute S308.

[0091] S307: Determine whether the target business meets the risk triggering condition, and generate a first risk detection result, where the first risk detection result is used to indicate that the target business has a risk.

[0092] S308: Determine that the target business does not meet the risk triggering condition, and generate a second risk detection result, where the second risk detection result is used to indicate that the target business does not have any risk.

[0093] Figure 4 A flow chart of another method for detecting business data provided in an embodiment of the present application is shown as follows: Figure 4 As shown, the business data detection method includes S401-S407:

[0094] S401: Acquire business data associated with a target business.

[0095] S402: Convert the business data into structured data according to the data type and data format indicated by the preset data specification information.

[0096] S403: Determine a target business rule corresponding to the target business according to the business type of the target business.

[0097] The target business rules are used to indicate key risk data in the structured data corresponding to the target business and risk triggering conditions corresponding to the key risk data.

[0098] S404: Determine whether the structured data includes execution object data of the target business.

[0099] S405: Whether the execution object data of the target business includes a risk warning object.

[0100] If yes, execute S406, if no, execute S407.

[0101] S406: Determine whether the target business meets the risk triggering condition, and generate a first risk detection result, where the first risk detection result is used to indicate that the target business has a risk.

[0102] S407: Determine that the target business does not meet the risk triggering condition, and generate a second risk detection result, where the second risk detection result is used to indicate that the target business does not have any risk.

[0103] The method for detecting business data provided in the embodiment of the present application first obtains the business data associated with the target business. Secondly, the business data is converted into structured data according to the data type and data format indicated by the preset data specification information. Thirdly, according to the business type of the target business, the target business rules corresponding to the target business are determined, and the target business rules are used to indicate the key risk data in the structured data corresponding to the target business and the risk trigger conditions corresponding to the key risk data. Finally, according to the target business rules, the structured data corresponding to the target business is identified to obtain the risk detection result. By converting the business data into structured data and then identifying the structured data based on the target business rules, the automatic detection of the business data can be achieved, thereby improving the detection efficiency of the business data.

[0104] It should be understood that, although the steps in the flowcharts involved in the above 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 is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may 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 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.

[0105] Based on the same inventive concept, the embodiment of the present application also provides a detection device for business data for implementing the above-mentioned detection method for business data. 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 embodiments of the detection device for one or more business data provided below can refer to the limitations of the detection method for business data above, and will not be repeated here.

[0106] In an exemplary embodiment, Figure 5 As shown, a detection device 500 for business data is provided, comprising: an acquisition module 501, a conversion module 502, a determination module 503 and an identification module 504, wherein:

[0107] An acquisition module 501 is used to acquire business data associated with a target business;

[0108] The conversion module 502 is used to convert the business data into structured data according to the data type and data format indicated by the preset data specification information;

[0109] A determination module 503 is used to determine a target business rule corresponding to the target business according to the business type of the target business, where the target business rule is used to indicate key risk data in the structured data corresponding to the target business and a risk trigger condition corresponding to the key risk data;

[0110] The identification module 504 is used to identify the structured data corresponding to the target business according to the target business rules to obtain the risk detection result.

[0111] In one embodiment, the key risk data includes execution location data of the target business; the identification module 504 is also used to determine the maximum execution distance difference of the target business based on the execution location data of the target business; if the maximum execution distance difference of the target business is greater than the distance difference threshold, it is determined that the target business meets the risk trigger condition, and a first risk detection result is generated, and the first risk detection result is used to indicate that there is a risk in the target business; if the maximum execution distance difference of the target business is less than or equal to the distance difference threshold, it is determined that the target business does not meet the risk trigger condition, and a second risk detection result is generated, and the second risk detection result is used to indicate that there is no risk in the target business.

[0112] In one embodiment, the key risk data includes the execution object data of the target business; the identification module 504 is also used to determine that the target business meets the risk trigger condition if the execution object data of the target business includes a risk warning object, and generate a first risk detection result, the first risk detection result is used to indicate that there is a risk in the target business; if the execution object data of the target business does not include a risk warning object, it is determined that the target business does not meet the risk trigger condition, and a second risk detection result is generated, the second risk detection result is used to indicate that there is no risk in the target business.

[0113] In one of the embodiments, the identification module 504 is also used to classify and count the target business according to the business type and risk detection results of the target business, to obtain a compliance business classification statistical chart and a risk business classification statistical chart; and to send a chart display instruction to the terminal device, the chart display instruction is used to instruct the terminal device to display the compliance business classification statistical chart and the risk business classification statistical chart.

[0114] In one embodiment, the acquisition module is used to determine data sources corresponding to multiple business operations of the target business; and acquire business data associated with the target business from the data sources corresponding to the multiple business operations.

[0115] In one of the embodiments, the data format includes data length and data precision.

[0116] Each module in the above-mentioned business data detection device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0117] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 6 As shown. 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 through a system bus, and the communication interface is connected to the system bus through 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 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, a method for detecting business data is implemented.

[0118] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the 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 those shown in the figure, or combine certain components, or have a different arrangement of components.

[0119] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0120] Obtain business data associated with the target business;

[0121] Convert business data into structured data according to the data type and data format indicated by the preset data specification information;

[0122] According to the business type of the target business, determine the target business rules corresponding to the target business, where the target business rules are used to indicate the key risk data in the structured data corresponding to the target business and the risk trigger conditions corresponding to the key risk data;

[0123] According to the target business rules, the structured data corresponding to the target business is identified to obtain risk detection results.

[0124] In one embodiment, the key risk data includes execution location data of the target business; when the processor executes the computer program, the following steps are also implemented:

[0125] Determine the maximum execution distance difference of the target business according to the execution location data of the target business;

[0126] If the maximum execution distance difference of the target business is greater than the distance difference threshold, it is determined that the target business meets the risk trigger condition, and a first risk detection result is generated, where the first risk detection result is used to indicate that the target business has a risk;

[0127] If the maximum execution distance difference of the target business is less than or equal to the distance difference threshold, it is determined that the target business does not meet the risk trigger condition, and a second risk detection result is generated, the second risk detection result is used to indicate that there is no risk for the target business.

[0128] In one embodiment, the key risk data includes execution object data of the target business; when the processor executes the computer program, the following steps are also implemented:

[0129] If the execution object data of the target business includes a risk warning object, it is determined that the target business meets the risk triggering condition, and a first risk detection result is generated, where the first risk detection result is used to indicate that the target business has a risk;

[0130] If the execution object data of the target business does not include a risk warning object, it is determined that the target business does not meet the risk triggering condition, and a second risk detection result is generated, the second risk detection result is used to indicate that there is no risk in the target business.

[0131] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0132] According to the business type and risk detection results of the target business, the target business is classified and counted to obtain the statistical charts of compliance business classification and risk business classification;

[0133] A chart display instruction is sent to the terminal device, where the chart display instruction is used to instruct the terminal device to display a compliance business classification statistical chart and a risk business classification statistical chart.

[0134] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0135] Determine the data sources corresponding to multiple business operations of the target business;

[0136] The business data associated with the target business is obtained from the data sources corresponding to the multiple business operations.

[0137] In one embodiment, the data format includes data length and data precision.

[0138] 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 following steps are implemented:

[0139] Obtain business data associated with the target business;

[0140] Convert business data into structured data according to the data type and data format indicated by the preset data specification information;

[0141] According to the business type of the target business, determine the target business rules corresponding to the target business, where the target business rules are used to indicate the key risk data in the structured data corresponding to the target business and the risk trigger conditions corresponding to the key risk data;

[0142] According to the target business rules, the structured data corresponding to the target business is identified to obtain risk detection results.

[0143] In one embodiment, the key risk data includes execution location data of the target business; when the computer program is executed by the processor, the following steps are also implemented:

[0144] Determine the maximum execution distance difference of the target business according to the execution location data of the target business;

[0145] If the maximum execution distance difference of the target business is greater than the distance difference threshold, it is determined that the target business meets the risk trigger condition, and a first risk detection result is generated, where the first risk detection result is used to indicate that the target business has a risk;

[0146] If the maximum execution distance difference of the target business is less than or equal to the distance difference threshold, it is determined that the target business does not meet the risk trigger condition, and a second risk detection result is generated, the second risk detection result is used to indicate that there is no risk for the target business.

[0147] In one embodiment, the key risk data includes execution object data of the target business; when the computer program is executed by the processor, the following steps are also implemented:

[0148] If the execution object data of the target business includes a risk warning object, it is determined that the target business meets the risk triggering condition, and a first risk detection result is generated, where the first risk detection result is used to indicate that the target business has a risk;

[0149] If the execution object data of the target business does not include a risk warning object, it is determined that the target business does not meet the risk triggering condition, and a second risk detection result is generated, the second risk detection result is used to indicate that there is no risk in the target business.

[0150] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0151] According to the business type and risk detection results of the target business, the target business is classified and counted to obtain the statistical charts of compliance business classification and risk business classification;

[0152] A chart display instruction is sent to the terminal device, where the chart display instruction is used to instruct the terminal device to display a compliance business classification statistical chart and a risk business classification statistical chart.

[0153] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0154] Determine the data sources corresponding to multiple business operations of the target business;

[0155] The business data associated with the target business is obtained from the data sources corresponding to the multiple business operations.

[0156] In one embodiment, the data format includes data length and data precision.

[0157] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0158] Obtain business data associated with the target business;

[0159] Convert business data into structured data according to the data type and data format indicated by the preset data specification information;

[0160] According to the business type of the target business, determine the target business rules corresponding to the target business, where the target business rules are used to indicate the key risk data in the structured data corresponding to the target business and the risk trigger conditions corresponding to the key risk data;

[0161] According to the target business rules, the structured data corresponding to the target business is identified to obtain risk detection results.

[0162] In one embodiment, the key risk data includes execution location data of the target business; when the computer program is executed by the processor, the following steps are also implemented:

[0163] Determine the maximum execution distance difference of the target business according to the execution location data of the target business;

[0164] If the maximum execution distance difference of the target business is greater than the distance difference threshold, it is determined that the target business meets the risk trigger condition, and a first risk detection result is generated, where the first risk detection result is used to indicate that the target business has a risk;

[0165] If the maximum execution distance difference of the target business is less than or equal to the distance difference threshold, it is determined that the target business does not meet the risk trigger condition, and a second risk detection result is generated, the second risk detection result is used to indicate that there is no risk for the target business.

[0166] In one embodiment, the key risk data includes execution object data of the target business; when the computer program is executed by the processor, the following steps are also implemented:

[0167] If the execution object data of the target business includes a risk warning object, it is determined that the target business meets the risk triggering condition, and a first risk detection result is generated, where the first risk detection result is used to indicate that the target business has a risk;

[0168] If the execution object data of the target business does not include a risk warning object, it is determined that the target business does not meet the risk triggering condition, and a second risk detection result is generated, the second risk detection result is used to indicate that there is no risk in the target business.

[0169] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0170] According to the business type and risk detection results of the target business, the target business is classified and counted to obtain the statistical charts of compliance business classification and risk business classification;

[0171] A chart display instruction is sent to the terminal device, where the chart display instruction is used to instruct the terminal device to display a compliance business classification statistical chart and a risk business classification statistical chart.

[0172] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0173] Determine the data sources corresponding to multiple business operations of the target business;

[0174] The business data associated with the target business is obtained from the data sources corresponding to the multiple business operations.

[0175] In one embodiment, the data format includes data length and data precision.

[0176] 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.

[0177] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments 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 memory 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), magnetic 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, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0178] 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 application.

[0179] The above 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. A method for detecting business data, characterized in that: The method comprises: Obtain business data associated with the target business; Convert the business data into structured data according to the data type and data format indicated by the preset data specification information; Determine, according to the business type of the target business, a target business rule corresponding to the target business, wherein the target business rule is used to indicate key risk data in the structured data corresponding to the target business and a risk trigger condition corresponding to the key risk data; According to the target business rules, the structured data corresponding to the target business is identified to obtain a risk detection result.

2. The method according to claim 1, characterized in that: The key risk data includes the execution location data of the target business; the structured data corresponding to the target business is identified according to the target business rules to obtain the risk detection result, including: Determining a maximum execution distance difference of the target service according to the execution position data of the target service; If the maximum execution distance difference of the target business is greater than the distance difference threshold, it is determined that the target business meets the risk trigger condition, and a first risk detection result is generated, where the first risk detection result is used to indicate that the target business has a risk; If the maximum execution distance difference of the target business is less than or equal to the distance difference threshold, it is determined that the target business does not meet the risk trigger condition, and a second risk detection result is generated, where the second risk detection result is used to indicate that there is no risk for the target business.

3. The method according to claim 1, characterized in that The key risk data includes the execution object data of the target business; the structured data corresponding to the target business is identified according to the target business rules to obtain the risk detection result, including: If the execution object data of the target business includes a risk warning object, determining that the target business meets the risk trigger condition, and generating a first risk detection result, the first risk detection result is used to indicate that the target business has a risk; If the execution object data of the target business does not include the risk warning object, it is determined that the target business does not meet the risk trigger condition, and a second risk detection result is generated, where the second risk detection result is used to indicate that there is no risk in the target business.

4. The method according to claim 1, characterized in that After identifying the structured data corresponding to the target business according to the target business rule and obtaining the risk detection result, the method further includes: According to the business type of the target business and the risk detection result, the target business is classified and counted to obtain a compliant business classification statistical chart and a risky business classification statistical chart; A chart display instruction is sent to a terminal device, wherein the chart display instruction is used to instruct the terminal device to display the compliance business classification statistical chart and the risk business classification statistical chart.

5. The method according to claim 1, characterized in that The acquiring of the business data associated with the target business includes: Determine the data sources corresponding to the multiple business operations of the target business respectively; The business data associated with the target business is obtained from data sources corresponding to the multiple business operations respectively.

6. The method according to any one of claims 1 to 5, characterized in that: The data format includes data length and data precision.

7. A device for detecting business data, characterized in that: The device comprises: An acquisition module is used to acquire business data associated with a target business; A conversion module, used to convert the business data into structured data according to the data type and data format indicated by the preset data specification information; A determination module, used to determine a target business rule corresponding to the target business according to the business type of the target business, wherein the target business rule is used to indicate key risk data in the structured data corresponding to the target business and a risk trigger condition corresponding to the key risk data; The identification module is used to identify the structured data corresponding to the target business according to the target business rules to obtain risk detection results.

8. 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.

9. 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.

10. 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.

Images