Data processing method and device based on difference correction model, equipment and medium

Abstract

The invention relates to the technical field of data processing, and provides a data processing method based on a difference correction model, and the method comprises the steps: carrying out the format unification of transaction data and corresponding income data through a transaction data model and an income data model, and carrying out the modeling of key fields of the transaction data and the income data. And checking the transaction data model and the income data model to check the transaction data of each transaction order and the income data of the transaction order, and when the checking result is that the checking is abnormal, realizing the processing automation of the checking difference through the difference correction model according to the type of the checking abnormality. Therefore, automatic identification and automatic processing of the difference between the transaction and the income are realized, low account checking efficiency and accuracy caused by manual account checking are avoided, the identification efficiency and processing efficiency of the account checking difference are improved, the identification accuracy of the account checking difference and the accuracy of a processing result are improved, and the user experience is further improved.

Description

Technical Field

[0001] The present invention relates to the fields of data processing and financial technology, and in particular to a data processing method, device, computer equipment and computer-readable storage medium based on a difference correction model. Background Art

[0002] With the popularization and rapid development of Internet technology, mobile payment has increasingly become an important payment method in people's work and life. Mobile payment can not only greatly reduce the premium payment cost of the insurance industry, but also provide convenient fund reconciliation and settlement services. Therefore, mobile payment accounts for an increasing proportion of premium payment methods. The business reconciliation differences between the funds and business transactions on the insurance company side need to be handled by themselves. The current method of handling reconciliation differences is generally to reconcile and determine the difference transaction information through the system, and then manually verify and handle the difference transaction information. This processing method is very heavy when the transaction base is large. As a result, the reconciliation difference processing is not only inefficient, but also has a low accuracy rate.

[0003] Therefore, how to solve the current low efficiency in handling reconciliation differences and the low accuracy of processing results has become a technical problem that needs to be solved urgently. Summary of the invention

[0004] The main purpose of the present invention is to provide a data processing method, device, equipment and computer-readable storage medium based on a difference correction model, aiming to solve the current technical problems of low efficiency in reconciliation difference processing and low accuracy of processing results.

[0005] To achieve the above object, the present invention provides a data processing method based on a difference correction model, and the reconciliation difference processing method comprises the following steps:

[0006] Modeling the transaction data based on the transaction modeling data to obtain a transaction data model, wherein the transaction modeling data includes a first transaction serial number, a transaction amount, and a transaction time;

[0007] Modeling the income data based on the income modeling data to obtain an income data model, wherein the income modeling data includes the second transaction serial number, the income amount, and the income time;

[0008] Based on the transaction data model and the account data model, reconciling the transaction data with the account data;

[0009] When the reconciliation result is an abnormal reconciliation, the reconciliation difference type is obtained, and the reconciliation difference correction is performed based on the difference correction model and the reconciliation difference type.

[0010] In addition, to achieve the above-mentioned purpose, the present invention further provides a data processing device based on a difference correction model, the data processing device based on a difference correction model comprising:

[0011] A transaction data modeling module, used to model the transaction data based on the transaction modeling data to obtain a transaction data model, wherein the transaction modeling data includes a first transaction serial number, a transaction amount, and a transaction time;

[0012] An income data modeling module, used to model the income data based on the income modeling data to obtain an income data model, wherein the income modeling data includes the second transaction serial number, the income amount and the income time;

[0013] A transaction account reconciliation module, used for reconciling the transaction data with the account data based on the transaction data model and the account data model;

[0014] The reconciliation difference correction module is used to obtain the reconciliation difference type when the reconciliation result is an abnormal reconciliation, and perform reconciliation difference correction based on the difference correction model and the reconciliation difference type.

[0015] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer device, which includes a processor, a memory, and a data processing program based on a difference correction model stored in the memory and executable by the processor, wherein when the data processing program based on the difference correction model is executed by the processor, the steps of the data processing method based on the difference correction model as described above are implemented.

[0016] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, on which a data processing program based on a difference correction model is stored, wherein when the data processing program based on the difference correction model is executed by a processor, the steps of the data processing method based on the difference correction model as described above are implemented.

[0017] The present application provides a data processing method based on a difference correction model, the method models the transaction data based on the transaction modeling data to obtain a transaction data model, wherein the transaction modeling data includes a first transaction serial number, a transaction amount and a transaction time; based on the account modeling data, the account data is modeled to obtain an account data model, wherein the account modeling data includes a second transaction serial number, an account amount and an account time; based on the transaction data model and the account data model, the transaction data and the account data are reconciled; when the reconciliation result is an abnormal reconciliation, the reconciliation difference type is obtained, and the reconciliation difference correction is performed based on the difference correction model and the reconciliation difference type. Through the above method, the present application first models the transaction data and the account data, and through the transaction data model and the account data model, the transaction data of each transaction order and the account data of the corresponding reconciliation file are formatted in a unified manner, and the key fields of the transaction data and the account data are modeled. The transaction data model and the account data model are proofread to reconcile the transaction data of each transaction order with its account data. When the reconciliation result is an exception, the difference correction model is used to automate the processing of the reconciliation difference according to the type of reconciliation exception. This achieves automatic identification and processing of the differences between transactions and accounts, avoiding low reconciliation efficiency and accuracy caused by manual reconciliation. It not only improves the identification efficiency and processing efficiency of reconciliation differences, but also improves the identification accuracy of reconciliation differences and the accuracy of processing results, and further improves the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flow chart of a first embodiment of a data processing method based on a difference correction model of the present invention;

[0019] Figure 2 It is a flow chart of a second embodiment of a data processing method based on a difference correction model of the present invention;

[0020] Figure 3 It is a flow chart of a third embodiment of a data processing method based on a difference correction model of the present invention;

[0021] Figure 4 A schematic diagram of a correction process for reconciliation differences according to the present invention;

[0022] Figure 5 It is a schematic diagram of a data processing device based on a difference correction model of the present invention;

[0023] Figure 6 The figure is a schematic diagram of the hardware structure of a computer device involved in an embodiment of the present invention.

[0024] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0026] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0027] It should be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0028] It should be further understood that the term “and / or” used in the specification and appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0029] The data processing method based on the difference correction model involved in the embodiment of the present invention is mainly applied to computer equipment. The data processing and generating device based on the difference correction model can be a PC, a portable computer, a mobile terminal or other equipment with display and processing functions.

[0030] In conjunction with the accompanying drawings, some embodiments of the present application are described in detail below. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0031] Reference Figure 1 , Figure 1 It is a flowchart diagram of the first embodiment of the data processing method based on the difference correction model of the present invention.

[0032] like Figure 1 As shown, an embodiment of the present invention provides a data processing method based on a difference correction model, and the data processing method based on the difference correction model includes steps S10 to S30.

[0033] Step S10: Modeling the transaction data based on the transaction modeling data to obtain a transaction data model, wherein the transaction modeling data includes a first transaction serial number, a transaction amount, and a transaction time;

[0034] After analysis, it was found that manual verification and processing of difference transaction information would make the workload of manual review and processing of differences very heavy when the transaction base is large, resulting in not only inefficiency but also low accuracy in reconciliation difference processing.

[0035] In order to solve the above problems, this embodiment first models the transaction data and the account data. Through the transaction data model and the account data model, the transaction data of each transaction order and the account data of the corresponding reconciliation file are formatted in a unified manner, and the key fields of the transaction data and the account data are modeled. The transaction data model and the account data model are proofread to reconcile the transaction data of each transaction order with its account data, and when the reconciliation result is an abnormal reconciliation, the difference correction model is used to realize the automation of the processing of the reconciliation difference according to the abnormal reconciliation type, thereby realizing the automatic identification and automatic processing of the difference between the transaction and the account, avoiding the low reconciliation efficiency and accuracy caused by manual reconciliation, not only improving the identification efficiency and processing efficiency of the reconciliation difference, but also improving the identification accuracy of the reconciliation difference and the accuracy of the processing result, and further improving the user experience.

[0036] Specifically, the premium transaction data is modeled, and the transaction data modeling includes the first transaction serial number that can accurately correspond to the business (i.e., the payee transaction serial number), the transaction amount that can accurately correspond to the funds, and the transaction time that can accurately record the time when the funds are received (i.e., the payee payment time). The key parameters of the transaction data are shown in Table 1:

[0037] Transaction data model describe Payer transaction serial number That is, the transaction code used by the payment company to identify each transaction Payment time of the payer That is, the time when the funds are received after each transaction payment is confirmed Payment order number That is, the transaction order numbers recorded in the insurance company's trading platform Business document number list A list of unique document numbers for code businesses Transaction amount The specific amount of each transaction Delivery Methods The payer's code Reconciliation result flag If the reconciliation balance or the transaction side is too Correction method Such as system correction and manual correction

[0038] Table 1

[0039] Among them, the payer's transaction serial number is used to determine the funds corresponding to each transaction paid by the payer, the business document number is used to associate with the corresponding transaction business information, and the payer's payment time is used to accurately record the time when the payer's funds are received.

[0040] Furthermore, key parameters of the transaction data are collected in advance through the first data collection module, so that the transaction data is formatted uniformly through the first data collection module to determine a standard transaction data format.

[0041] Step S20: Modeling the payment data based on the payment modeling data to obtain a payment data model, wherein the payment modeling data includes the second transaction serial number, the payment amount, and the payment time;

[0042] In this embodiment, the data on the funding side is modeled. The data on the funding side is used to truly feedback the actual receipt of funds. It serves as the basis for premium reconciliation, is the most trusted data in transaction reconciliation, is the detailed data of the third-party payment to settle funds to the policy company, and is the data that has been confirmed by financial personnel. Among them, the receipt modeling data includes the second transaction serial number (i.e. the transaction serial number of the receiving party), the receipt amount (i.e. the transaction amount) and the receipt time (i.e. the time when the funds are received). Because, when the receipt amount is greater than the transaction amount, manual processing requires cross-departmental confirmation of the business transaction situation corresponding to the funds, and the need to refund the excess funds, etc.; if there is more data on the business side (i.e. the transaction amount is greater than the receipt amount), it is necessary to follow up on the withdrawal of the insurance policy across departments, etc. Therefore, this embodiment realizes the automation of the processing flow of reconciliation differences through the transaction data model, the receipt data model and the difference correction model. The key parameters of the receipt data model (i.e. the funding side data model) are shown in Table 2:

[0043] Funding side data model describe Transaction serial number of the recipient The transaction code used by the receiving company to identify each transaction Funds received time The time when the funds are received after payment confirmation Order Number The order number on the insurance company's trading platform Transaction amount The specific amount of each transaction Delivery Methods The payer's code

[0044] Table 2

[0045] Among them, the transaction serial number of the payee is used to determine the incoming funds corresponding to each transaction of the payee, and the fund receipt time is used to accurately record the fund receipt time of the payee.

[0046] Furthermore, the key parameters of the account-in data are collected in advance through the second data collection module, so that the format of the account-in data is unified through the second data collection module to determine the standard transaction data format.

[0047] Step S30: reconcile the transaction data with the account data based on the transaction data model and the account data model;

[0048] In this embodiment, determining that there is a reconciliation difference between the transaction data and the income data is a prerequisite for processing the reconciliation difference between the transaction data and the income data. Before determining the reconciliation difference between the transaction data and the income data, the transaction data needs to be compared with the income data (or the reconciliation file). In the case of inconsistent comparison results, after the financial personnel confirm the funds on the specified date, in the detailed data in the reconciliation file, the premium transaction details are matched according to the payee's transaction serial number. If the data of the two parties matches and the amounts on both sides are consistent, it means that the reconciliation result is a reconciliation balance. The reconciliation result information can be further recorded in the reconciliation result data model, and the reconciliation result can be marked as reconciliation balance; if the fund reconciliation file cannot be found in the premium transaction details data according to the payee transaction serial number, it means that the reconciliation result is that the fund transaction (i.e., the amount of money received) is too much, and the reconciliation result information is recorded in the reconciliation result data model, and the reconciliation result is marked as too much money received; if the premium transaction details data cannot find the fund transaction according to the payee transaction serial number, it means that the reconciliation result is too much on the transaction side, and the funds corresponding to the transaction have not been received, and the reconciliation result information is recorded in the reconciliation result data model, and the reconciliation result is marked as too much on the transaction side. Thus, the modeling of the reconciliation result data is completed, and the data model is used to record the reconciliation results of transaction data and fund side data, i.e., 1) reconciliation balance 2) more on the fund side 3) more on the transaction side. The reconciliation result data model is shown in Table 3.

[0049] Reconciliation result data model describe Payer transaction serial number The serial number of the payment company transaction Funds received time The time when the funds are received after payment confirmation Order Number The order number of the insurance company's trading platform Reconciliation result flag Generally, it is account balance, more on the transaction side, more on the capital side

[0050] Furthermore, after reconciling the transaction data with the income data based on the transaction data model and the income data model, the method further includes:

[0051] When the transaction data matches the account receipt data, it is determined that the reconciliation result is a reconciliation balance.

[0052] In this embodiment, in the detailed data in the reconciliation file, the premium transaction detailed data is matched according to the payee's transaction serial number. If the two data match and the amounts on both sides are consistent, it means that the reconciliation result is balanced.

[0053] Step S40: When the reconciliation result is abnormal, obtain the reconciliation difference type, and perform reconciliation difference correction based on the difference correction model and the reconciliation difference type.

[0054] In this embodiment, when it is determined that the reconciliation result is abnormal, a corresponding difference correction rule is further determined according to the reconciliation difference type, and the reconciliation difference correction is performed according to the corresponding difference correction rule to achieve automated processing of the reconciliation difference.

[0055] The difference correction process corresponding to each reconciliation difference type, that is, the difference correction rule corresponding to each reconciliation difference type, is prepared in advance, and a difference correction model is generated based on each reconciliation difference type and its corresponding difference correction rule.

[0056] Specifically, the types of reconciliation differences include: more on the fund side and more on the transaction side. The correction process for reconciliation differences is as follows: Figure 2 As shown:

[0057] 1. The solutions for dealing with differences in funds include:

[0058] 1) Determine the order number of the transaction with abnormal reconciliation in the fund reconciliation file, and send the order number to the trading platform to perform supplementary underwriting operations on the business data corresponding to all business document numbers under the transaction in the trading platform;

[0059] 2) If the order data cannot be found on the trading platform, the system will automatically generate payable data and notify the accounting system to generate a payable accounting voucher for the refund, and then call the fund refund interface service to generate actual payment data. In this way, the funds are automatically returned to the customer through the original refund method.

[0060] Second, the solution for dealing with differences on the trading side. If such differences are found, it means that the funds have not been received and the insurance policies that have been insured need to be cancelled. The system implements the fund system to call the trading platform, and the trading platform notifies the insurance policy system to cancel the insurance policy.

[0061] The present embodiment provides a data processing method based on a difference correction model, the method models the transaction data based on the transaction modeling data to obtain a transaction data model, wherein the transaction modeling data includes a first transaction serial number, a transaction amount and a transaction time; based on the account modeling data, models the account data to obtain an account model, wherein the account modeling data includes a second transaction serial number, an account amount and an account time; based on the transaction data model and the account data model, reconciles the transaction data with the account data; when the reconciliation result is an abnormal reconciliation, obtains the reconciliation difference type, and performs reconciliation difference correction based on the difference correction model and the reconciliation difference type. In the above manner, the present embodiment first models the transaction data and the account data, and through the transaction data model and the account data model, unifies the format of the transaction data of each transaction order and the account data of the corresponding reconciliation file, and models the key fields of the transaction data and the account data. The transaction data model and the account data model are proofread to reconcile the transaction data of each transaction order with its account data. When the reconciliation result is an exception, the difference correction model is used to automate the processing of the reconciliation difference according to the type of reconciliation exception. This achieves automatic identification and processing of the differences between transactions and accounts, avoiding low reconciliation efficiency and accuracy caused by manual reconciliation. It not only improves the identification efficiency and processing efficiency of reconciliation differences, but also improves the identification accuracy of reconciliation differences and the accuracy of processing results, and further improves the user experience.

[0062] Reference Figure 3 , Figure 3 It is a flowchart diagram of the second embodiment of the data processing method based on the difference correction model of the present invention.

[0063] Based on the above Figure 1 In the embodiment shown, in this embodiment, the step S40 specifically includes:

[0064] Step S41, when the reconciliation anomaly type is a first type, determining a first difference correction rule corresponding to the first type based on the difference correction model, wherein the first type is a reconciliation anomaly type in which the incoming amount is greater than the transaction amount;

[0065] Step S42: Based on the first difference correction rule, a supplementary underwriting operation or a refund operation is performed on the transaction data.

[0066] Furthermore, performing a supplementary underwriting operation or a refund operation on the transaction data based on the first difference correction rule specifically includes:

[0067] Determine the transaction order number corresponding to the transaction data based on the first difference correction rule, and send the transaction order number to the trading platform;

[0068] If the transaction information corresponding to the transaction number does not exist in the transaction platform, generating a refund voucher corresponding to the transaction data based on the transaction amount;

[0069] Through the refund interface service, the refund amount corresponding to the refund voucher is refunded to the corresponding account according to the original payment method to complete the refund operation.

[0070] Furthermore, after determining the transaction order number corresponding to the transaction data based on the first difference correction rule and sending the transaction order number to the trading platform, the method further includes:

[0071] If the transaction information corresponding to the transaction number exists in the transaction platform, all transaction information corresponding to the transaction number is obtained from the transaction platform;

[0072] Based on all transaction information corresponding to the transaction order number, supplementary insurance reminder information is generated to perform supplementary insurance operations on all transaction information corresponding to the transaction data.

[0073] In this embodiment, when the reconciliation anomaly type is a reconciliation anomaly type in which the amount of money received is greater than the transaction amount, that is, the reconciliation anomaly type is a multi-type on the fund side. The first difference correction rule corresponding to this anomaly type includes two solutions: transactions with reconciliation anomalies and transactions without reconciliation anomalies:

[0074] 1) Determine the order number of the transaction with abnormal reconciliation in the fund reconciliation file, and send the order number to the trading platform to perform supplementary underwriting operations on the business data corresponding to all business document numbers under the transaction in the trading platform;

[0075] It can be understood that the transaction information corresponding to the transaction order number can be one transaction, that is, there is only one business under the transaction, and the transaction information corresponding to the transaction order number can also be multiple transactions, that is, there are multiple business document numbers under the transaction, then the business data corresponding to all business document numbers under the transaction will be supplemented by underwriting operations.

[0076] 2) If the order data corresponding to the order number cannot be found in the trading platform, the payable data is generated according to the order number, and the payable accounting voucher for the refund is generated through the accounting system, and then the fund refund interface service is called to generate the actual payment data corresponding to the payable data. According to the actual payment data and the original refund method, the funds corresponding to the transaction are automatically refunded to the paying customer account.

[0077] Through the above method, this embodiment proofreads the transaction data model and the account data model to reconcile the transaction data of each transaction order with its account data, automatically identify differences and automatically process reconciliation differences, improve the systematization of manual business processes, and when the reconciliation result is a reconciliation exception, through the difference correction model, according to the reconciliation exception type, realize the automation of the processing of reconciliation differences, thereby realizing automatic identification and automatic processing of differences between transactions and accounts, avoiding low reconciliation efficiency and accuracy caused by manual reconciliation, not only improving the identification efficiency and processing efficiency of reconciliation differences, but also greatly reducing manual processing costs, reducing manual processing errors, greatly reducing manual accounts, improving the identification accuracy of reconciliation differences and the accuracy of processing results, and further improving user experience.

[0078] Reference Figure 4 , Figure 4 It is a flowchart diagram of a third embodiment of a data processing method based on a difference correction model of the present invention.

[0079] Based on the above Figure 1 In the embodiment shown, in this embodiment, the step S40 specifically further includes:

[0080] Step S43, when the reconciliation anomaly type is the second type, determining a second difference correction rule corresponding to the second type based on the difference correction model, wherein the second type is the reconciliation anomaly type in which the incoming amount is less than the transaction amount;

[0081] Step S44, determining the historical transaction information corresponding to the transaction data, and based on the historical transaction information, sending payment reminder information and / or contract cancellation reminder information to the transaction platform to make additional payment or contract cancellation for the historical transaction information.

[0082] Furthermore, the sending of payment reminder information and / or contract withdrawal reminder information to the transaction platform based on the historical transaction information specifically includes:

[0083] Sending payment reminder information corresponding to the historical transaction information to the policy user through the transaction platform;

[0084] When no payment instruction corresponding to the historical transaction information is received within a preset time period, a policy cancellation is sent to the policy system through the transaction platform to cancel the policy corresponding to the historical transaction information.

[0085] In this embodiment, the reconciliation exception type is the reconciliation exception type in which the incoming amount is less than the transaction amount, that is, the difference type on the transaction side. The difference processing solution corresponding to this difference type is: when the funds corresponding to the transaction are not received, the insured policy must be cancelled, that is, the transaction platform is called through the fund system, and the policy cancellation operation is initiated to the policy system through the transaction platform, so as to cancel the policy corresponding to the historical transaction information.

[0086] Furthermore, before sending the policy withdrawal operation to the policy system, the transaction platform may send payment reminder information corresponding to the historical transaction information to the policy user, so that the user who missed the payment can make up the payment. If the payment instruction corresponding to the historical transaction information is not received within the preset time period, the policy withdrawal operation is sent to the policy system through the transaction platform.

[0087] Through the above method, this embodiment proofreads the transaction data model and the account data model to reconcile the transaction data of each transaction order with its account data, automatically identify differences and automatically process reconciliation differences, improve the systematization of manual business processes, and when the reconciliation result is an account reconciliation exception, through the difference correction model, according to the type of reconciliation exception, realize the automation of the processing of reconciliation differences, thereby realizing automatic identification and automatic processing of differences between transactions and accounts, avoiding low reconciliation efficiency and accuracy caused by manual reconciliation, not only improving the identification efficiency and processing efficiency of reconciliation differences, but also greatly reducing manual processing costs, reducing manual processing errors, and greatly reducing manual accounts, realizing fully automated processing from policy transactions to funds to corresponding accounting, improving the identification accuracy of reconciliation differences and the accuracy of processing results, and further improving user experience.

[0088] See also Figure 5 , Figure 5 It is a functional module diagram of a data processing device based on a difference correction model provided in an embodiment of the present application.

[0089] like Figure 5 As shown, the data processing device 500 based on the difference correction model includes:

[0090] A transaction data modeling module 10 is used to model the transaction data based on the transaction modeling data to obtain a transaction data model, wherein the transaction modeling data includes a first transaction serial number, a transaction amount, and a transaction time;

[0091] An income data modeling module 20 is used to model the income data based on the income modeling data to obtain an income data model, wherein the income modeling data includes the second transaction serial number, the income amount and the income time;

[0092] A transaction account reconciliation module 30, configured to reconcile the transaction data with the account data based on the transaction data model and the account data model;

[0093] The reconciliation difference correction module 40 is used to obtain the reconciliation difference type when the reconciliation result is abnormal, and perform reconciliation difference correction based on the difference correction model and the reconciliation difference type.

[0094] Furthermore, the reconciliation difference correction module 40 specifically includes:

[0095] A first rule determination unit is used to determine, when the reconciliation anomaly type is a first type, a first difference correction rule corresponding to the first type based on the difference correction model, wherein the first type is a reconciliation anomaly type in which the incoming amount is greater than the transaction amount;

[0096] The first difference correction unit is used to perform a supplementary underwriting operation or a refund operation on the transaction data based on the first difference correction rule.

[0097] Furthermore, the first difference correction unit specifically includes:

[0098] a first order number determination subunit, configured to determine a transaction order number corresponding to the transaction data based on the first difference correction rule, and send the transaction order number to a trading platform;

[0099] A refund voucher generating subunit, configured to generate a refund voucher corresponding to the transaction data based on the transaction amount if the transaction information corresponding to the transaction order number does not exist in the transaction platform;

[0100] The payment amount refund sub-unit, through the refund interface service, refunds the refund amount corresponding to the refund voucher to the corresponding account in accordance with the original payment method, thereby completing the refund operation.

[0101] Furthermore, the first difference correction unit specifically includes:

[0102] a transaction information acquisition unit, configured to acquire all transaction information corresponding to the transaction number from the transaction platform if the transaction information corresponding to the transaction number exists in the transaction platform;

[0103] The supplementary underwriting operation unit is used to generate supplementary underwriting reminder information based on all transaction information corresponding to the transaction order number, so as to perform supplementary underwriting operations on all transaction information corresponding to the transaction data.

[0104] Furthermore, the reconciliation difference correction module 40 specifically includes:

[0105] A second rule determination unit is used to determine, when the reconciliation anomaly type is a second type, based on the difference correction model, a second difference correction rule corresponding to the second type, wherein the second type is a reconciliation anomaly type in which the incoming amount is less than the transaction amount;

[0106] The second difference correction unit is used to determine the historical transaction information corresponding to the transaction data, and based on the historical transaction information, send payment reminder information and / or contract cancellation reminder information to the transaction platform to make additional payment or contract cancellation for the historical transaction information.

[0107] Furthermore, the second difference correction unit specifically includes:

[0108] A payment information reminder subunit, used to send payment reminder information corresponding to the historical transaction information to the policy user through the transaction platform;

[0109] The insurance policy withdrawal operation subunit is used to send an insurance policy withdrawal to the insurance policy system through the transaction platform when no payment instruction corresponding to the historical transaction information is received within a preset time period, so as to withdraw the insurance policy corresponding to the historical transaction information.

[0110] Furthermore, the data processing device 500 based on the difference correction model further includes:

[0111] The reconciliation balance determination module is used to determine that the reconciliation result is a reconciliation balance when the transaction data matches the income data.

[0112] It should be noted that those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described device and each module can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0113] The above-mentioned device can be implemented in the form of a computer program. Figure 6 Runs on the computer device shown.

[0114] See also Figure 6 , Figure 6 1 is a schematic block diagram of a computer device provided in an embodiment of the present application. The computer device may be a server.

[0115] See also Figure 6 The computer device includes a processor, a memory and a network interface connected through a system bus, wherein the memory may include a non-volatile storage medium and an internal memory.

[0116] The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions, and when the program instructions are executed, the processor can execute any data processing method based on the difference correction model.

[0117] The processor is used to provide computing and control capabilities and support the operation of the entire computer equipment.

[0118] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor, the processor can execute any data processing method based on the difference correction model.

[0119] The network interface is used for network communication, such as sending assigned tasks, etc. 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.

[0120] It should be understood that the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0121] In one embodiment, the processor is used to run a computer program stored in the memory to implement the following steps:

[0122] Modeling the transaction data based on the transaction modeling data to obtain a transaction data model, wherein the transaction modeling data includes a first transaction serial number, a transaction amount, and a transaction time;

[0123] Modeling the income data based on the income modeling data to obtain an income data model, wherein the income modeling data includes the second transaction serial number, the income amount, and the income time;

[0124] Based on the transaction data model and the account data model, reconciling the transaction data with the account data;

[0125] When the reconciliation result is an abnormal reconciliation, the reconciliation difference type is obtained, and the reconciliation difference correction is performed based on the difference correction model and the reconciliation difference type.

[0126] In one embodiment, the processor is used to run a computer program stored in the memory to implement the following steps:

[0127] In the case where the reconciliation anomaly type is the first type, determining a first difference correction rule corresponding to the first type based on the difference correction model, wherein the first type is the reconciliation anomaly type in which the incoming amount is greater than the transaction amount;

[0128] Based on the first difference correction rule, a supplementary underwriting operation or a refund operation is performed on the transaction data.

[0129] In one embodiment, the processor is used to run a computer program stored in the memory to implement the following steps:

[0130] Determine the transaction order number corresponding to the transaction data based on the first difference correction rule, and send the transaction order number to the trading platform;

[0131] If the transaction information corresponding to the transaction number does not exist in the transaction platform, generating a refund voucher corresponding to the transaction data based on the transaction amount;

[0132] Through the refund interface service, the refund amount corresponding to the refund voucher is refunded to the corresponding account according to the original payment method to complete the refund operation.

[0133] In one embodiment, the processor is used to run a computer program stored in the memory to implement the following steps:

[0134] If the transaction information corresponding to the transaction number exists in the transaction platform, all transaction information corresponding to the transaction number is obtained from the transaction platform;

[0135] Based on all transaction information corresponding to the transaction order number, supplementary insurance reminder information is generated to perform supplementary insurance operations on all transaction information corresponding to the transaction data.

[0136] In one embodiment, the processor is used to run a computer program stored in the memory to implement the following steps:

[0137] In the case where the reconciliation anomaly type is the second type, determining a second difference correction rule corresponding to the second type based on the difference correction model, wherein the second type is a reconciliation anomaly type in which the incoming amount is less than the transaction amount;

[0138] Determine the historical transaction information corresponding to the transaction data, and based on the historical transaction information, send payment reminder information and / or contract cancellation reminder information to the transaction platform to make additional payment or contract cancellation for the historical transaction information.

[0139] In one embodiment, the processor is used to run a computer program stored in the memory to implement the following steps:

[0140] Sending payment reminder information corresponding to the historical transaction information to the policy user through the transaction platform;

[0141] When no payment instruction corresponding to the historical transaction information is received within a preset time period, a policy cancellation is sent to the policy system through the transaction platform to cancel the policy corresponding to the historical transaction information.

[0142] In one embodiment, the processor is used to run a computer program stored in the memory to implement the following steps:

[0143] When the transaction data matches the account receipt data, it is determined that the reconciliation result is a reconciliation balance.

[0144] A computer-readable storage medium is also provided in an embodiment of the present application, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and the processor executes the program instructions to implement any one of the data processing methods based on the difference correction model provided in the embodiments of the present application.

[0145] The computer-readable storage medium may be an internal storage unit of the computer device described in the above embodiment, such as a hard disk or memory of the computer device. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the computer device.

[0146] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A data processing method based on a difference correction model, characterized in that: The method for processing reconciliation differences comprises the following steps: Modeling the transaction data based on the transaction modeling data to obtain a transaction data model, wherein the transaction modeling data includes a first transaction serial number, a transaction amount, and a transaction time; Modeling the income data based on the income modeling data to obtain an income data model, wherein the income modeling data includes the second transaction serial number, the income amount, and the income time; Based on the transaction data model and the account data model, reconciling the transaction data with the account data; When the reconciliation result is an abnormal reconciliation, the reconciliation difference type is obtained, and the reconciliation difference correction is performed based on the difference correction model and the reconciliation difference type.

2. The data processing method based on the difference correction model according to claim 1, characterized in that: The reconciliation difference correction based on the difference correction model and the reconciliation difference type specifically includes: In the case where the reconciliation anomaly type is the first type, determining a first difference correction rule corresponding to the first type based on the difference correction model, wherein the first type is the reconciliation anomaly type in which the incoming amount is greater than the transaction amount; Based on the first difference correction rule, a supplementary underwriting operation or a refund operation is performed on the transaction data.

3. The data processing method based on the difference correction model according to claim 1, characterized in that: The performing of a supplementary underwriting operation or a refund operation on the transaction data based on the first difference correction rule specifically includes: Determine the transaction order number corresponding to the transaction data based on the first difference correction rule, and send the transaction order number to the trading platform; If the transaction information corresponding to the transaction number does not exist in the transaction platform, generating a refund voucher corresponding to the transaction data based on the transaction amount; Through the refund interface service, the refund amount corresponding to the refund voucher is refunded to the corresponding account according to the original payment method to complete the refund operation.

4. The data processing method based on the difference correction model according to claim 1, characterized in that: After determining the transaction order number corresponding to the transaction data based on the first difference correction rule and sending the transaction order number to the trading platform, the method further includes: If the transaction information corresponding to the transaction order number exists in the transaction platform, all transaction information corresponding to the transaction order number is obtained from the transaction platform; Based on all transaction information corresponding to the transaction order number, supplementary insurance reminder information is generated to perform supplementary insurance operations on all transaction information corresponding to the transaction data.

5. The data processing method based on the difference correction model according to claim 1, characterized in that: The reconciliation difference correction based on the difference correction model and the reconciliation difference type specifically includes: In the case where the reconciliation anomaly type is the second type, determining a second difference correction rule corresponding to the second type based on the difference correction model, wherein the second type is a reconciliation anomaly type in which the incoming amount is less than the transaction amount; Determine the historical transaction information corresponding to the transaction data, and based on the historical transaction information, send payment reminder information and / or contract cancellation reminder information to the transaction platform to make additional payment or contract cancellation for the historical transaction information.

6. The data processing method based on the difference correction model according to claim 5, characterized in that: The sending of payment reminder information and / or contract withdrawal reminder information to the transaction platform based on the historical transaction information specifically includes: Sending payment reminder information corresponding to the historical transaction information to the policy user through the transaction platform; When no payment instruction corresponding to the historical transaction information is received within a preset time period, a policy cancellation is sent to the policy system through the transaction platform to cancel the policy corresponding to the historical transaction information.

7. The data processing method based on the difference correction model according to any one of claims 1 to 6, characterized in that: After reconciling the transaction data with the account data based on the transaction data model and the account data model, the method further includes: When the transaction data matches the account receipt data, it is determined that the reconciliation result is a reconciliation balance.

8. A data processing device based on a difference correction model, characterized in that: The data processing device based on the difference correction model includes: A transaction data modeling module, used to model the transaction data based on the transaction modeling data to obtain a transaction data model, wherein the transaction modeling data includes a first transaction serial number, a transaction amount, and a transaction time; An income data modeling module, used to model the income data based on the income modeling data to obtain an income data model, wherein the income modeling data includes the second transaction serial number, the income amount and the income time; A transaction account reconciliation module, used for reconciling the transaction data with the account data based on the transaction data model and the account data model; The reconciliation difference correction module is used to obtain the reconciliation difference type when the reconciliation result is an abnormal reconciliation, and perform reconciliation difference correction based on the difference correction model and the reconciliation difference type.

9. A computer device, characterized in that: The computer device includes a processor, a memory, and a data processing program based on a difference correction model stored in the memory and executable by the processor, wherein when the data processing program based on the difference correction model is executed by the processor, the steps of the data processing method based on the difference correction model as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a data processing program based on a difference correction model, wherein when the data processing program based on a difference correction model is executed by a processor, the steps of the data processing method based on a difference correction model as described in any one of claims 1 to 7 are implemented.

Images