Data verification method and device based on insurance service and medium

Abstract

The invention provides a data verification method and device based on insurance business and a medium, and relates to the technical field of computer technology and information processing. The insurance service-based data verification method comprises the following steps: in response to a service number and a service scene input by a user, matching a target data model, and determining a data verification rule; and based on the total business data, performing data verification through a data verification rule, and determining matching information of the data verification rule. Through the technical scheme provided by the invention, the problems that the accuracy of data completely depends on the ability of a tester and the objectivity and accuracy of data verification are not easy to guarantee in the related technology are solved, and the efficiency and accuracy of insurance service data testing are improved.

Description

Technical Field

[0001] The present disclosure relates to the fields of computer technology and information processing, and in particular to a data verification method, device, electronic equipment and medium based on insurance business. Background Art

[0002] In the related technology, testers directly query and calculate the data under test by connecting to the database, which requires a high business background of the testers. There are data risks when conducting data testing without understanding the business. In addition, manual calculations and cross-table queries and comparisons are required, and test data verification is time-consuming. The accuracy of the data depends entirely on the ability of the testers, and the objectivity and accuracy of the data verification are not easy to guarantee. Summary of the invention

[0003] The present disclosure provides a data verification method, device, electronic device and medium based on insurance business, so as to solve the problem that the accuracy of data in related technologies completely depends on the ability of testers, and the objectivity and accuracy of data verification are not easy to guarantee, by organizing data models according to business scenarios and configuring data verification rules. According to the entered business order number to be tested and the corresponding business scenario, the data model and verification rules can be automatically matched, the full data verification is completed, and the matching information of each verification rule is output.

[0004] A first aspect of the present disclosure provides a data verification method based on insurance business, the method comprising:

[0005] In response to the user entering the business order number and business scenario, matching the target data model and determining the data validation rules;

[0006] Based on the full amount of business data, data verification is performed using the data verification rules to determine matching information of the data verification rules.

[0007] In one embodiment of the present disclosure, before responding to the user inputting the business order number and business scenario, matching the target data model, and determining the data calculation rule, the method further includes:

[0008] The business scenario is constructed according to the preconfigured data model, and the business scenario is composed of at least two of the data models.

[0009] In one embodiment of the present disclosure, in response to the user entering the business order number and business scenario, matching the target data model, and determining the data validation rule include:

[0010] In response to entering the business order number and selecting the business scenario, matching the target data model from a preset data model set;

[0011] The data validation rules are defined according to the business scenario and the target data model.

[0012] In one embodiment of the present disclosure, performing data verification based on the full amount of business data by using the data verification rule to determine matching information of the data verification rule includes:

[0013] Based on the business order number, filter the data to be verified from the full amount of business data;

[0014] The data to be verified is encapsulated into the target data model, and the matching information is calculated according to the data verification rule.

[0015] In an embodiment of the present disclosure, after calculating the matching information according to the data verification rule, the method further includes:

[0016] For the target data model, generate and output a verification result of the target data model;

[0017] If the verification result is abnormal, the verification result is highlighted.

[0018] A second aspect of the present disclosure provides a data verification device based on insurance business, the device comprising:

[0019] The first determination module is used to match the target data model and determine the data validation rules in response to the business order number and business scenario entered by the user;

[0020] The second determination module is used to perform data verification based on the full amount of business data through the data verification rules to determine the matching information of the data verification rules.

[0021] The third aspect embodiment of the present disclosure proposes an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute any one of the methods in the first aspect embodiment of the present disclosure.

[0022] The fourth aspect embodiment of the present disclosure proposes a non-transitory computer-readable storage medium storing computer instructions, characterized in that the computer instructions are used to enable a computer to execute the method in the first aspect embodiment of the present disclosure.

[0023] The fifth aspect embodiment of the present disclosure proposes a computer program product, characterized in that it includes a computer program, and the computer program implements any method in the first aspect embodiment of the present disclosure when executed by a processor.

[0024] The sixth aspect embodiment of the present disclosure proposes a chip, comprising at least one processor and a communication interface; the communication interface is used to receive signals input into the chip or signals output from the chip, the processor communicates with the communication interface and implements any one of the methods in the first aspect embodiment of the present disclosure through logic circuits or execution code instructions.

[0025] In summary, according to the data verification method based on insurance business proposed in the present invention, in response to the user entering the business order number and business scenario, matching the target data model, and determining the data verification rules, the test data verification can be easily completed even if the tester does not understand the business. At the same time, the execution process does not require the intervention of the tester, thereby ensuring the objectivity of the data verification process. Based on the full amount of business data, data verification is performed through the data verification rules, and the matching information of the data verification rules is determined, thereby improving the efficiency and accuracy of insurance business data testing.

[0026] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute improper limitations on the present disclosure.

[0028] Figure 1 It is a flow chart of a data verification method based on insurance business according to an embodiment of the present disclosure;

[0029] Figure 2 A flowchart of constructing a business scenario according to an embodiment of the present disclosure;

[0030] Figure 3 A schematic diagram of building a business scenario using different data models according to an embodiment of the present disclosure;

[0031] Figure 4 A flowchart of an embodiment of the present disclosure for responding to a user inputting a business order number and a business scenario, matching a target data model, and determining a data validation rule;

[0032] Figure 5 This is a flow chart of an embodiment of the present disclosure, which performs data verification based on full business data through data verification rules to determine matching information of the data verification rules;

[0033] Figure 6 A schematic diagram of data validation rules corresponding to a data model in an embodiment of the present disclosure;

[0034] Figure 7 A flowchart of verifying a target data model according to an embodiment of the present disclosure;

[0035] Figure 8 It is a structural schematic diagram of a data verification device based on insurance business according to an embodiment of the present disclosure;

[0036] Fig. 9 is a block diagram of an electronic device for implementing the data verification method based on insurance business disclosed in the present invention according to an exemplary embodiment;

[0037] Fig.10 It is a schematic diagram of the structure of the chip of the embodiment of the present disclosure. DETAILED DESCRIPTION

[0038] Embodiments of the present disclosure are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout identify the same or similar originals or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be construed as limiting the present disclosure.

[0039] In related technologies, data verification involving insurance business requires testers to query and compare data by directly connecting to the database. Due to the large number of insurance business data models, the data storage rules are relatively complex, and various business scenarios are superimposed, which requires covering more than 180 rules, checking more than 30 data tables, and more than 500 fields, including various data configuration item storage, data identification storage, and total insured amount, total premium, total taxes, sub-item insured amount, sub-item premium, sub-item tax, and tax splitting of co-insured business. All data calculations need to be manually verified. At the same time, some data verification involves the horizontal and vertical consistency of data in the data table. The verification process is time-consuming and inefficient, and data accuracy is not easy to guarantee.

[0040] This proposal can shield the business background of testers and the data relationship between multiple tables, reduce the subjective data verification problems caused by testers when performing data calculation and verification, and ensure the consistency and accuracy of the data to be tested. At the same time, it supports dynamic configuration of business scenarios, dynamic organization of data models, and customized data calculation and verification rules, which improves the flexibility of testers' data verification and testing efficiency.

[0041] The method proposed in this disclosure is applied to data verification tasks based on insurance business. Its application has a wide range of scenarios and is mainly applied to data model verification in the insurance industry to ensure the accuracy and consistency of business data such as insurance policies, batch orders and claims. In addition, it can also be extended to financial services, data analysis and mining, software testing and quality assurance, compliance auditing and business process optimization, etc., to help improve data processing efficiency and reduce manual intervention, thereby supporting more efficient business decisions and operations. The application scenarios are not limited in the embodiments of this disclosure.

[0042] The data verification method based on insurance business provided by the present disclosure is described in detail below with reference to the accompanying drawings.

[0043] Figure 1 Flow chart of a data verification method based on insurance business according to an embodiment of the present disclosure. This method is executed on the server side. Figure 1 In the embodiment shown, the data verification method based on insurance business includes:

[0044] Step 101, in response to the user entering the business order number and business scenario, matching the target data model and determining the data validation rules.

[0045] In this embodiment, the business order number refers to a unique identifier generated during the insurance transaction process, which is used to track and manage specific insurance business or policies. Business scenarios refer to the specific business activities and environments involved in the operation of an insurance company, such as life insurance, property insurance, disease insurance, etc. The target data model refers to the data model corresponding to the currently input business order number and business scenario. The data validation rule refers to the rule for verifying whether the target data model is correct. When the business order number and business scenario entered by the user are received, the closest target data model is matched according to the business order number and business scenario, and the data validation rule for verifying this target data model is determined.

[0046] Step 102: Based on the full amount of business data, data verification is performed using data verification rules to determine matching information of the data verification rules.

[0047] In this embodiment, the full amount of business data refers to all relevant data collected by the insurance company during the operation process, including customer information, policy details, claims records, marketing activities, risk assessment and other information. The matching information of the data validation rule refers to the uniformity information between the various form data recorded in the full amount of business data. The fewer the anomalies of each form data after passing the data validation rule, the higher the matching degree of the business data under the data validation rule, and the more accurate and reliable the business data. On the contrary, the less reliable the data, the poorer the accuracy.

[0048] Specifically, the present disclosure uses springboot, jep and testNG to implement all functions, wherein the jep component is used to parse calculation formulas, and the testNG test component is used for data verification. It can realize the definition of test business scenarios, personalized organization of data models, and customized data calculation and data verification rules. According to the generated business order number and business rules, it automatically matches the data model, calculates and verifies the data rules, and then determines the verification conclusion.

[0049] In summary, according to the data verification method based on insurance business proposed in the present invention, in response to the user entering the business order number and business scenario, matching the target data model, and determining the data verification rules, the test data verification can be easily completed even if the tester does not understand the business. At the same time, the execution process does not require the intervention of the tester, thereby ensuring the objectivity of the data verification process. Based on the full amount of business data, data verification is performed through the data verification rules, and the matching information of the data verification rules is determined, thereby improving the efficiency and accuracy of insurance business data testing.

[0050] Figure 2 The present invention is a flowchart of a business scenario. Figure 2 Yes Figure 1 Further explanation of step 101 before, based on Figure 2 The embodiment shown comprises the following steps:

[0051] Step 201: construct a business scenario according to a preconfigured data model, where the business scenario is composed of at least two data models.

[0052] In this embodiment, before matching the target data model based on the business order number and the business scenario, a business scenario is constructed according to a pre-configured data model. The business scenario is usually composed of at least two data models.

[0053] Specifically, the present disclosure has a relatively complete data model built in. In the rule configuration module, testers can customize business scenarios according to test requirements, including underwriting, modification, cancellation, individual group business, summary / fee summary business, short-term insurance business, joint insurance business, etc. At the same time, mutually exclusive settings can be added to the business scenarios. For example, if you choose underwriting, you cannot choose modification or cancellation, but you can still choose joint insurance business.

[0054] In one implementation of this embodiment,

[0055] Figure 3 FIG. 1 is a schematic diagram of using different data models to construct a business scenario according to an embodiment of the present disclosure. Figure 3 As shown, discrete data models are personalized and organized in different business scenarios. For example, business scenario 1 includes data models A, B, and C, business scenario 2 includes data models B, C, and D, and business scenario 3 includes data models A, B, C, and D.

[0056] In this embodiment, different business scenarios are constructed through multiple data models, providing verification models and evaluation scenarios for the verification of insurance business data.

[0057] Figure 4 This is a flowchart of an embodiment of the present disclosure for responding to a user entering a business order number and a business scenario, matching a target data model, and determining data validation rules. Figure 4 Yes Figure 1 Further explanation of step 101 is based on Figure 4 The embodiment shown comprises the following steps:

[0058] Step 401 , in response to entering a business order number and selecting a business scenario, matching a target data model from a preset data model set.

[0059] In this embodiment, after the user enters the business order number and selects the business scenario, the data model closest to the business order number and the business scenario is matched from the preset data model set as the target data model.

[0060] Step 402: define data validation rules according to the business scenario and the target data model.

[0061] In this embodiment, according to the business scenario and the target data model, data validation rules that can meet the requirements of the business scenario and the target data model are defined.

[0062] In this embodiment, data verification of insurance business does not require testers to directly connect to the database for query. A complete data model is pre-made, and multiple business scenarios can be customized. At the same time, the data model can be personalized and organized according to the scenario, and the data verification rules can be flexibly configured according to the business scenario and data model. Even if the tester does not understand the business, the verification of test data can be easily completed. At the same time, the execution process does not require the intervention of the tester, which ensures the objectivity of the data verification process.

[0063] Figure 5 This is a flowchart of an embodiment of the present disclosure, which performs data verification based on full business data through data verification rules to determine matching information of the data verification rules. Figure 5 Yes Figure 1 Further explanation of step 102 is based on Figure 5 The embodiment shown comprises the following steps:

[0064] Step 501, based on the business order number, filter the data to be verified from the full amount of business data.

[0065] In this embodiment, the data to be verified refers to the data in the business data form that needs to be verified to see if it is correct. The data to be verified is screened out from the full amount of business data according to the business order number.

[0066] Step 502: encapsulate the data to be verified into the target data model, and calculate the matching information according to the data verification rules.

[0067] In this embodiment, the data to be verified is automatically queried according to the business order number, and the data to be verified is encapsulated into the corresponding data model, that is, the data to be verified is encapsulated into the target data model, and the target data model is verified using data verification rules to obtain matching information.

[0068] In one implementation of this embodiment,

[0069] Figure 6 FIG. 1 is a schematic diagram of data validation rules corresponding to a data model in an embodiment of the present disclosure. Figure 6 As shown, business scenario 3 includes data models A, B, C, and D. For data model A, data validation rule 1 is A.field1 i =A.field3 i *A.field4 i *A.field5 i Specifically, this formula can mean that the first column of form A satisfies the product of the third, fourth, and fifth columns of form A. It can also mean that the first row of form A satisfies the product of the third, fourth, and fifth rows of form A. Data validation rule 2 is Specifically, this formula can indicate that the second column of form A is the same as the second column of form B and form C, and is equal to the sum of all elements in the second column of form D. Similar to data validation rule 1, data validation rule 2 can also indicate the rules satisfied between specific rows of a form. For data model B, the data validation rule is that the 7th row or column of form B is the specific identifier "0010". For data model C, the data validation rule is that the 6th row or column of form C is greater than the 7th row or column of form C. For data model D, the data validation rule is that the first row or column of form D is not empty.

[0070] In this embodiment, through dynamic and flexible configuration of rules, the calculation and verification rules can be quickly modified according to the test results, thereby improving the efficiency and accuracy of data verification.

[0071] Figure 7 The present invention is a flowchart of verifying a target data model according to an embodiment of the present invention. Figure 7 Yes Figure 5 The specific description after step 502 is based on Figure 7 The embodiment shown comprises the following steps:

[0072] Step 701: Generate and output a verification result of the target data model for the target data model.

[0073] In this embodiment, for the target data model, the data to be verified is verified using the data verification model of the target data model, and a verification result is generated and output.

[0074] Step 702: If the verification result is abnormal, the verification result is highlighted.

[0075] In this embodiment, if the verification result is an abnormal result, it means that there is abnormal data in the insurance business data that does not comply with the data verification rules. The abnormal result will be highlighted and the abnormal data that produces the result will be identified.

[0076] As shown in the following validation result table, when the check item is data model A, according to the validation results of the two data validation rules shown, the validation result is displayed as FAIL, indicating that the validation failed. For data models B and C, according to the data validation rule information shown in the validation results, the validation result is displayed as PASS, indicating that the validation passed. For data model D, according to the information shown in the validation results, the first row or column of form D is not empty, but an empty result is found, so the validation result is displayed as FAIL to indicate failure. In this example, the visualization of data validation results is achieved, and the validation rules and error data are displayed intuitively.

[0077] Verification results table

[0078]

[0079] The present disclosure proposes a data verification method based on insurance business. In response to the user inputting the business order number and business scenario, the target data model is matched and the data verification rules are determined. Even if the tester does not understand the business, the verification of the test data can be easily completed. At the same time, the execution process does not require the intervention of the tester, which ensures the objectivity of the data verification process; based on the full amount of business data, data verification is performed through the data verification rules, and the matching information of the data verification rules is determined, which improves the efficiency and accuracy of insurance business data testing. Corresponding to the methods provided in the above-mentioned embodiments, the present disclosure also provides a data verification device based on insurance business. Since the device provided in the embodiments of the present disclosure corresponds to the methods provided in the above-mentioned embodiments, the implementation method of the method is also applicable to the device provided in this embodiment, and will not be described in detail in this embodiment.

[0080] Figure 8 FIG. 8 is a schematic diagram of a data verification device 800 based on insurance business according to an embodiment of the present disclosure. Figure 8 As shown, the data verification device based on insurance business includes:

[0081] The first determination module 810 is used to match the target data model and determine the data validation rules in response to the business order number and business scenario entered by the user;

[0082] The second determination module 820 is used to perform data verification based on the full amount of business data through the data verification rules to determine the matching information of the data verification rules.

[0083] In some embodiments, before responding to the user inputting the business order number and business scenario, matching the target data model, and determining the data calculation rule, the first determination module 810 is further configured to:

[0084] A business scenario is constructed according to the preconfigured data model. The business scenario consists of at least two data models.

[0085] In some embodiments, the first determination module 810 is used to:

[0086] In response to entering a business order number and selecting a business scenario, matching a target data model from a preset data model set;

[0087] Define data validation rules based on business scenarios and target data models.

[0088] In some embodiments, the second determination module 820 is used to:

[0089] Based on the business order number, filter the data to be verified from the entire business data;

[0090] Encapsulate the data to be verified into the target data model and calculate the matching information according to the data verification rules.

[0091] In some embodiments, after calculating the matching information according to the data verification rule, the second determination module is further configured to:

[0092] For the target data model, generate and output the verification result of the target data model;

[0093] If the verification result is abnormal, the verification result will be highlighted.

[0094] In summary, through the data verification device based on insurance business, in response to the business order number and business scenario entered by the user, the target data model is matched and the data verification rules are determined; based on the full amount of business data, data verification is performed through the data verification rules to determine the matching information of the data verification rules. This device solves the problem in related technologies that the accuracy of data completely depends on the ability of the tester, and the objectivity and accuracy of data verification are not easy to guarantee, thereby improving the efficiency and accuracy of insurance business data testing.

[0095] In the above embodiments provided by the present disclosure, the methods and devices provided by the embodiments of the present disclosure are introduced. In order to implement the functions in the methods provided by the above embodiments of the present disclosure, the electronic device may include a hardware structure and a software module, and implement the above functions in the form of a hardware structure, a software module, or a hardware structure plus a software module. One of the above functions may be executed in the form of a hardware structure, a software module, or a hardware structure plus a software module.

[0096] Fig. 9 It is a block diagram of an electronic device 900 for implementing the above-mentioned data verification method based on insurance business according to an exemplary embodiment.

[0097] For example, the electronic device 900 may be a mobile phone, a computer, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0098] Reference Fig. 9 , the electronic device 900 may include one or more of the following components: a processing component 902 , a memory 904 , a power component 906 , a multimedia component 908 , an audio component 910 , an input / output (I / O) interface 912 , a sensor component 914 , and a communication component 916 .

[0099] The processing component 902 generally controls the overall operation of the electronic device 900, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 902 may include one or more processors 920 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 902 may include one or more modules to facilitate the interaction between the processing component 902 and other components. For example, the processing component 902 may include a multimedia module to facilitate the interaction between the multimedia component 908 and the processing component 902.

[0100] The memory 904 is configured to store various types of data to support operations on the electronic device 900. Examples of such data include instructions for any application or method operating on the electronic device 900, contact data, phone book data, messages, pictures, videos, etc. The memory 904 may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0101] The power supply component 906 provides power to the various components of the electronic device 900. The power supply component 906 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the electronic device 900.

[0102] The multimedia component 908 includes a screen that provides an output interface between the electronic device 900 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 908 includes a front camera and / or a rear camera. When the electronic device 900 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0103] The audio component 910 is configured to output and / or input audio signals. For example, the audio component 910 includes a microphone (MIC), and when the electronic device 900 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 904 or sent via the communication component 916. In some embodiments, the audio component 910 also includes a speaker for outputting audio signals.

[0104] I / O interface 912 provides an interface between processing component 902 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: a home button, a volume button, a start button, and a lock button.

[0105] The sensor assembly 914 includes one or more sensors for providing various aspects of status assessment for the electronic device 900. For example, the sensor assembly 914 can detect the open / closed state of the electronic device 900, the relative positioning of components, such as the display and keypad of the electronic device 900, and the sensor assembly 914 can also detect the position change of the electronic device 900 or a component of the electronic device 900, the presence or absence of user contact with the electronic device 900, the orientation or acceleration / deceleration of the electronic device 900, and the temperature change of the electronic device 900. The sensor assembly 914 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 914 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 914 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0106] The communication component 916 is configured to facilitate wired or wireless communication between the electronic device 900 and other devices. The electronic device 900 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, 4G LTE, 5G NR (NewRadio) or a combination thereof. In an exemplary embodiment, the communication component 916 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 916 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0107] In an exemplary embodiment, the electronic device 900 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above methods.

[0108] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 904 including instructions, and the instructions can be executed by the processor 920 of the electronic device 900 to complete the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0109] The embodiments of the present disclosure further provide a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute the data verification method based on insurance business described in the above embodiments of the present disclosure.

[0110] The embodiments of the present disclosure further provide a computer program product, including a computer program, which executes the data verification method based on insurance business described in the above embodiments of the present disclosure when a processor is used to execute the computer program.

[0111] Fig.10 It is a schematic diagram of the structure of a chip 1000 for implementing the above-mentioned data verification method based on insurance business according to an exemplary embodiment.

[0112] Reference Fig.10The chip 1000 includes at least one communication interface 1001 and a processor 1002; the communication interface 1001 is used to receive a signal input to the chip 1000 or a signal output from the chip 1000, and the processor 1002 communicates with the communication interface 1001 and implements the data verification method based on the insurance business described in the above embodiment through a logic circuit or executing code instructions.

[0113] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0114] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiments or examples are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0115] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present disclosure includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present disclosure belong.

[0116] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processing module, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (control method), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing in a suitable manner if necessary, and then stored in a computer memory.

[0117] It should be understood that the various parts of the embodiments of the present disclosure can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0118] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0119] In addition, each functional unit in each embodiment of the present disclosure may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium. The above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0120] Although the embodiments of the present disclosure have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present disclosure. A person skilled in the art may make changes, modifications, substitutions and variations to the above embodiments within the scope of the present disclosure.

Claims

1. A data verification method based on insurance business, characterized in that: The method comprises: In response to the user entering the business order number and business scenario, matching the target data model and determining the data validation rules; Based on the full amount of business data, data verification is performed using the data verification rules to determine matching information of the data verification rules.

2. The method according to claim 1, characterized in that Before responding to the user inputting the business order number and business scenario, matching the target data model, and determining the data calculation rule, the method further includes: The business scenario is constructed according to the preconfigured data model, and the business scenario is composed of at least two of the data models.

3. The method according to claim 1, characterized in that In response to the user entering the business order number and business scenario, matching the target data model, and determining the data validation rules include: In response to entering the business order number and selecting the business scenario, matching the target data model from a preset data model set; The data validation rules are defined according to the business scenario and the target data model.

4. The method according to claim 1, characterized in that: The performing data verification based on the full amount of business data by using the data verification rule to determine the matching information of the data verification rule includes: Based on the business order number, filter the data to be verified from the full amount of business data; The data to be verified is encapsulated into the target data model, and the matching information is calculated according to the data verification rule.

5. The method according to claim 4, characterized in that After calculating the matching information according to the data verification rule, the method further includes: For the target data model, generate and output a verification result of the target data model; If the verification result is abnormal, the verification result is highlighted.

6. A data verification device based on insurance business, characterized in that: The device comprises: The first determination module is used to match the target data model and determine the data validation rules in response to the business order number and business scenario entered by the user; The second determination module is used to perform data verification based on the full amount of business data through the data verification rules to determine the matching information of the data verification rules.

7. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 6.

8. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-6.

9. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 6.

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