Data verification method and device, electronic equipment, storage medium and program product

Abstract

The embodiment of the invention discloses a data verification method and device, electronic equipment, a storage medium and a program product, and the method comprises the steps: obtaining the current to-be-recognized payment record related image data; performing image recognition on a target reference image element in the current to-be-recognized payment record associated image data to obtain a target image recognition result; wherein the target reference image element comprises an image text, payment amount data, a payment date, an order number and bar code data; and performing data verification according to the target image recognition result to obtain a data verification result of the current payment record to be recognized. According to the technical scheme of the embodiment of the invention, the payment data auditing efficiency and the data verification precision can be improved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of data processing and image processing, and in particular to a data verification method, device, electronic device, storage medium and program product. Background Art

[0002] In modern enterprises, false reimbursements can cause great cost waste and regulatory risks. When business personnel make expense reimbursements, payment records may be falsified. Therefore, it is often necessary to review the expense reimbursement materials submitted by business personnel.

[0003] The traditional method of reviewing expense reimbursement materials requires financial auditors to manually determine the authenticity of payment records, which is inefficient and prone to errors. Summary of the invention

[0004] The embodiments of the present invention provide a data verification method, device, electronic device, storage medium and program product, which can improve the review efficiency and data verification accuracy of payment data.

[0005] According to one aspect of the present invention, there is provided a data verification method, comprising:

[0006] Get the image data associated with the current payment record to be identified;

[0007] Performing image recognition on the target reference image element in the image data associated with the current payment record to be recognized to obtain a target image recognition result; wherein the target reference image element includes image text, payment amount data, payment date, order number and barcode data;

[0008] Data verification is performed according to the target image recognition result to obtain a data verification result of the current payment record to be recognized.

[0009] According to another aspect of the present invention, there is provided a data verification device, comprising:

[0010] The associated image data acquisition module is used to acquire the associated image data of the current payment record to be identified;

[0011] A target image recognition result acquisition module is used to perform image recognition on the target reference image element in the image data associated with the current payment record to be recognized, and obtain a target image recognition result; wherein the target reference image element includes image text, payment amount data, payment date, order number and barcode data;

[0012] The data verification result acquisition module is used to perform data verification according to the target image recognition result to obtain the data verification result of the current payment record to be recognized.

[0013] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0014] at least one processor; and

[0015] a memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the data verification method described in any embodiment of the present invention.

[0017] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the data verification method described in any embodiment of the present invention when executed.

[0018] According to another aspect of the present invention, a computer program product is provided, including a computer program, wherein when the computer program is executed by a processor, the data verification method according to any embodiment of the present invention is implemented.

[0019] The embodiment of the present invention obtains image data associated with the current payment record to be identified, and further performs image recognition on target reference image elements such as image text, payment amount data, payment date, order number and barcode data included in the image data associated with the current payment record to be identified, to obtain a target image recognition result, so that data verification can be performed based on the target image recognition result to obtain a data verification result of the current payment record to be identified, thereby solving the problems of low efficiency and proneness to errors in the existing manual review of payment data, and being able to improve the review efficiency and data verification accuracy of payment data.

[0020] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 is a flow chart of a data verification method provided by Embodiment 1 of the present invention;

[0023] Figure 2 is a schematic diagram of a data verification device provided by Embodiment 2 of the present invention;

[0024] Figure 3 A schematic diagram of the structure of an electronic device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0026] It should be noted that the term "target" and the like in the specification and claims of the present invention 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 invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] Embodiment 1

[0028] Figure 1 This is a flow chart of a data verification method provided by the first embodiment of the present invention. This embodiment is applicable to the case where the image text, payment amount data, payment date, order number and barcode data included in the payment record image are verified. The method can be executed by a data verification device, which can be implemented by software and / or hardware, and can generally be integrated in an electronic device. The electronic device can be a terminal device or a server device. As long as it can execute the data verification method, the embodiment of the present invention does not limit the specific device type of the electronic device. Accordingly, if Figure 1 As shown, the method includes the following operations:

[0029] S110, obtaining image data associated with the current payment record to be identified.

[0030] The image data associated with the current payment record to be identified may be image data generated during the payment process and not identified and processed by the reimbursement system. Exemplarily, the image data associated with the current payment record to be identified may include but is not limited to application payment screenshots and / or transfer record screenshots. Application payment screenshots may include but are not limited to payment screenshots of various application programs, etc., as long as they have electronic payment functions. The embodiment of the present invention does not limit the type of application that provides application payment screenshots.

[0031] In the embodiment of the present invention, the reimbursement system can automatically review the submitted payment records. Optionally, when reviewing the payment records, it is first necessary to obtain the image data associated with the current payment record to be identified, so that the image data associated with the current payment record to be identified can be identified.

[0032] In a specific example, payment records can be uploaded through the smart fee control system, whether it is a screenshot of a payment from various applications or a screenshot of a bank transfer record.

[0033] S120. Perform image recognition on the target reference image elements in the image data associated with the current payment record to be identified to obtain a target image recognition result, wherein the target reference image elements include image text, payment amount data, payment date, order number and barcode data.

[0034] The target reference image element may be an image element associated with the authenticity of the image data associated with the current payment record to be identified, and needs to be identified to verify the authenticity of the payment. Exemplarily, the target reference image element may include, but is not limited to, image text, payment amount data, payment date, order number, and barcode data, etc. The embodiment of the present invention does not limit the specific type of the target reference image element. The target image recognition result may be the result obtained by identifying the target reference image element in the image data associated with the current payment record to be identified.

[0035] In an embodiment of the present invention, after obtaining the image data associated with the current payment record to be identified, image recognition can be performed on target reference image elements such as image text, payment amount data, payment date, order number and barcode data in the image data associated with the current payment record to be identified, thereby obtaining a target image recognition result.

[0036] In an optional embodiment of the present invention, performing image recognition on the target reference image element in the current image data associated with the payment record to be identified to obtain the target image recognition result may include: identifying the text data in the area near the barcode in the current image data associated with the payment record to be identified to obtain the text data recognition result; identifying the amount value, amount position and amount image area height of the payment amount data in the current image data associated with the payment record to be identified to obtain the payment amount data recognition result; matching the date format in the current image data associated with the payment record to be identified by using a date regular expression, and performing date recognition based on the date format matching result to obtain the date recognition result; extracting keywords from the order-related data in the current image data associated with the payment record to be identified, and performing order number recognition on the extracted keywords by using an order number regular expression to obtain the order number recognition result; identifying and parsing the barcode in the current image data associated with the payment record to be identified to obtain the barcode recognition result.

[0037] Among them, the text data recognition result may be the recognition result of the text data in the area near the barcode in the current image data associated with the payment record to be recognized. Exemplarily, the text data recognition result in the area near the barcode may include but is not limited to the barcode digital code, payment amount, payment method and transaction number, etc., and the embodiment of the present invention does not limit the specific type of the text data recognition result in the area near the barcode. The payment amount data may be the data associated with the current image data associated with the payment record to be recognized and the payment amount. Exemplarily, the payment amount data may include but is not limited to the amount value, the amount position and the amount image area height, etc., and the embodiment of the present invention does not limit the specific type of the payment amount data. The payment amount data recognition result may be the recognition result of the payment amount data in the image data associated with the current payment record to be recognized. The date recognition result may be the recognition result of extracting date information from the image data associated with the current payment record to be recognized and converting it into a readable and understandable format. The order-related data may be the relevant data in the image data associated with the current payment record to be recognized that can reflect the order information. Exemplarily, the order-related data may include but is not limited to the order date, order status and product information, etc., and the embodiment of the present invention does not limit the specific data content of the order-related data. The order number regular expression may be a regular expression for order number recognition, as long as it can be used to recognize the order number. The embodiment of the present invention does not limit the specific expression content of the order number regular expression. The order number recognition result may be the result of recognizing the keywords in the order-related data in the current payment record-related image data to be recognized. The barcode recognition result may be the result of recognizing and parsing the barcode in the current payment record-related image data to be recognized.

[0038] It should be noted that before performing image recognition on the target reference image element in the image data associated with the current payment record to be recognized, the reimbursement system may first classify the image data associated with the current payment record to be recognized, thereby improving the processing efficiency and accuracy of target image recognition. Exemplarily, the reimbursement system may classify the image data associated with the current payment record to be recognized using optical character recognition (OCR) technology, and after determining the category of the image data associated with the current payment record to be recognized, further recognize the image data associated with the current payment record to be recognized, thereby improving the recognition accuracy of the image data associated with the current payment record to be recognized.

[0039] In an embodiment of the present invention, when performing image recognition on the target reference image element in the image data associated with the current payment record to be recognized, the text data in the area near the barcode in the image data associated with the current payment record to be recognized can be recognized, thereby obtaining a text data recognition result. The amount value, amount position and amount image area height of the payment amount data in the image data associated with the current payment record to be recognized can also be recognized, thereby obtaining a payment amount data recognition result. The date format in the image data associated with the current payment record to be recognized can also be matched by a date regular expression, and date recognition can be performed according to the date format matching result, thereby obtaining a date recognition result. Keywords can also be extracted from the order-related data in the image data associated with the current payment record to be recognized, and order number recognition can be performed on the extracted keywords by using an order number regular expression, thereby obtaining an order number recognition result. The barcode in the image data associated with the current payment record to be recognized can also be recognized and parsed, thereby obtaining a barcode recognition result. Further, the data of the current payment record to be recognized can be verified according to the text data recognition result, the payment amount data recognition result, the date recognition result, the order number recognition result and the barcode recognition result.

[0040] It should be noted that there is no order restriction for the above-mentioned process of performing image recognition on different target reference image elements. That is, image recognition can be performed on different target reference image elements in sequence, or image recognition can also be performed on different target reference image elements at the same time, and the embodiment of the present invention does not limit this.

[0041] In a specific example, a payment screenshot is uploaded to the reimbursement system through the smart fee control system. If the reimbursement system uses OCR technology to identify that the screenshot belongs to the payment screenshot of application A, the payment screenshot of application A can be identified according to the preset recognition rules of the payment screenshot of application A. For the recognition of the payment amount, in addition to identifying the amount value, the OCR technology can also identify the position of the amount in the image and the height of the amount image area, which can improve the accuracy and robustness of the recognition. For the recognition of the payment date, the OCR technology can flexibly match a variety of date formats through regular expressions, such as 2024-08-09, August 9, 2024, and 24-08-09, etc., to ensure that no matter what the date format in the payment screenshot is, it can be accurately extracted. For the recognition of the order number, the OCR technology can extract the coordinates of keywords, such as "order number" and "transaction number", and then combine regular expressions to extract 8-22 digits as the order number to ensure the accuracy and uniqueness of the order number. For barcode recognition, the use of OCR technology can improve the barcode recognition ability, ensure the accurate decoding of barcode data, and provide a basis for subsequent comparison and verification.

[0042] S130: Perform data verification according to the target image recognition result to obtain a data verification result of the current payment record to be recognized.

[0043] The data verification result of the current payment record to be identified may be a result obtained by performing data verification according to the target image recognition result. Exemplarily, the data verification result of the current payment record to be identified may include but is not limited to normal and abnormal.

[0044] In an embodiment of the present invention, after performing image recognition on the target reference image element in the image data associated with the current payment record to be identified to obtain the target image recognition result, data verification can be performed based on the target image recognition result to obtain the data verification result of the current payment record to be identified.

[0045] In an optional embodiment of the present invention, data verification is performed based on the target image recognition result to obtain a data verification result of the current payment record to be identified, which may include: comparing the date recognition result with the order date information included in the order number recognition result to obtain a payment date verification result; comparing the barcode recognition result with the text data recognition result to obtain a barcode data verification result; comparing the date recognition result with the system record date included in the barcode recognition result to obtain a barcode decoding date verification result.

[0046] Among them, the order date information can be the date information obtained by extracting the order date keywords from the order-related data in the image data associated with the current payment record to be identified, and identifying the extracted order date keywords through the order number regular expression. The payment date verification result can be the result obtained by comparing the date recognition result with the order date information included in the order number recognition result, which can reflect the accuracy of the date information. Exemplarily, the payment date verification result can include but is not limited to normal and abnormal. The barcode data verification result can be the result obtained by comparing the barcode recognition result with the text data recognition result. Exemplarily, the barcode data verification result can include but is not limited to normal and abnormal. The barcode decoding date verification result can be the result obtained by comparing the date recognition result with the system record date included in the barcode recognition result. Exemplarily, the barcode decoding date verification result can include but is not limited to normal and abnormal.

[0047] Specifically, after performing image recognition on the target reference image element in the image data associated with the current payment record to be recognized to obtain the target image recognition result, the date recognition result can be compared with the order date information included in the order number recognition result to obtain the payment date verification result. Among them, the normal result of the payment date verification result indicates that the date recognition result and the order date information included in the order number recognition result are consistent within the allowable error range, and the abnormal result of the payment date verification result indicates that the difference between the date recognition result and the order date information included in the order number recognition result exceeds the allowable error range. Exemplarily, the error range can be 10 hours, the date recognition result is 18:00 on February 12, 2024, and the order date information included in the order number recognition result is 8:00 on February 12, 2024. Within the allowable error range, it can be considered that the date recognition result is consistent with the order date information included in the order number recognition result. The barcode recognition result can also be compared with the text data recognition result to obtain the barcode data verification result. Among them, the normal result of the barcode data verification result shows that the barcode recognition result is consistent with the text data recognition result, and the abnormal result of the barcode data verification result shows that there is a difference between the barcode recognition result and the text data recognition result. The date recognition result can also be compared with the system record date included in the barcode recognition result to obtain the barcode decoding date verification result. Among them, the normal result of the barcode decoding date verification result shows that the date recognition result and the system record date included in the barcode recognition result are consistent within the allowable error range, and the abnormal result of the barcode decoding date verification result shows that the difference between the date recognition result and the system record date included in the barcode recognition result exceeds the allowable error range. Further, the data verification result of the current payment record to be identified can be obtained based on the payment date verification result, the barcode data verification result and the barcode decoding date verification result.

[0048] It should be noted that if at least one of the payment date verification result, the barcode data verification result and the barcode decoding date verification result is abnormal, the data verification result of the current payment record to be identified is abnormal.

[0049] In a specific example, OCR technology can be used to detect anomalies in the cross-reference relationship in the data of the current payment record to be identified.

[0050] (1) Compare the payment date with the date in the order number.

[0051] The reimbursement system can use OCR technology to extract the payment date and order number from the scanned documents or images. For the order number, if it contains date information (such as a string in a specific format), you need to write parsing logic to convert it into a date format. The parsed order date is further compared with the payment date to check whether they are the same or within a reasonable time difference range. For example, the order date should be equal to the payment date. If the dates are inconsistent and the time difference is beyond a reasonable range, it is marked as an exception.

[0052] (2) Compare the barcode data with the data below.

[0053] The reimbursement system can use OCR technology to read and decode the barcode, obtain the information stored in it, and extract the corresponding data from the text area below the barcode, such as product name, quantity, and price. Further, the decoded barcode data can be compared with the data below, especially those key fields that should be consistent with the barcode information. If the comparison results are inconsistent, it is marked as an exception.

[0054] (3) Compare the payment date and barcode decoding date.

[0055] The payment date usually refers to the date marked on the relevant records or vouchers (such as payment receipts) after the bank or payment institution completes the payment transaction. This date reflects the time when the payment transaction is confirmed and recorded, and is of great significance for verifying the authenticity and timeliness of the transaction.

[0056] The barcode decoding date may be the date information contained in the barcode itself, including but not limited to the production date, expiration date and other date information related to production or sales, or the date when the system decodes and records the barcode when processing documents containing barcodes, such as product packaging, logistics documents, etc. For example, in a specific application scenario, such as a logistics tracking system, the date when the barcode is scanned and decoded may be regarded as an important timestamp.

[0057] During the matching process, the reimbursement system can first convert the text in the image into an editable and searchable format, and then use OCR technology to extract the payment date and barcode information from the payment voucher and the document containing the barcode. The recognition process of barcode information utilizes the information represented by the black and white stripes of different widths and spacing in the barcode. Furthermore, the decoded data can be compared with pre-stored or reference data to verify the accuracy of the barcode or find relevant information. The matching process may involve simple string matching or may require more complex database queries and logical judgments.

[0058] In an optional embodiment of the present invention, before comparing the date recognition result with the order date information included in the order number recognition result to obtain the payment date verification result, it may also include: obtaining the target format date information included in the order number recognition result; parsing and converting the target format date information through date parsing logic to obtain the order date information.

[0059] The target format date information may be date-related information contained in the order number recognition result, which may have a special encoding format.

[0060] It is understandable that the order number usually includes date information in a special encoding format, which is difficult to be directly recognized by OCR technology. Therefore, before comparing the date recognition result with the order date information included in the order number recognition result, the target format date information included in the order number recognition result can be first obtained, and the target format date information can be parsed and converted by the date parsing logic to obtain the order date information that can be directly recognized by OCR technology.

[0061] In a specific example, if the order number recognition result is "XSD202402201234", where "20240220" is the target date format information, the target format date information is parsed through the date parsing logic to obtain the order date information as "February 20, 2024".

[0062] In an optional embodiment of the present invention, after performing data verification according to the target image recognition result to obtain the data verification result of the current payment record to be identified, it may also include: when it is determined that the data verification result of the current payment record to be identified is normal, verifying the compliance of the payment record data to be identified; when it is determined that the data verification result of the current payment record to be identified is abnormal, obtaining the authenticity verification result of the image data associated with the current payment record to be identified, and when it is determined that the authenticity verification result of the image data associated with the current payment record to be identified is passed, verifying the compliance of the payment record data to be identified.

[0063] The authenticity verification result may be a verification result obtained by the financial approval node in the reimbursement system for reviewing the abnormal image data associated with the current payment record to be identified, which can prove the authenticity of the image data associated with the current payment record to be identified. It is understandable that the data verification result of the current payment record to be identified may be wrong. When it is determined that the data verification result of the current payment record to be identified is abnormal, the financial approval node in the reimbursement system can verify the authenticity of the image data associated with the current payment record to be identified, and obtain the authenticity verification result of the image data associated with the current payment record to be identified.

[0064] Specifically, the data verification result of the current payment record to be identified obtained by performing data verification based on the target image recognition result may include normal and abnormal results. If the data verification result of the current payment record to be identified is normal, the compliance of the data of the payment record to be identified can be verified. If the data verification result of the current payment record to be identified is abnormal, the authenticity verification result of the image data associated with the current payment record to be identified can be obtained. For example, the financial approval node in the reimbursement system will review the payment record, such as sending the payment record to the user end that submitted the payment record for manual review, and receiving the review result of the payment record to confirm the authenticity of the payment record. Furthermore, when it is determined that the authenticity verification result of the image data associated with the current payment record to be identified is passed, the compliance of the data of the payment record to be identified is verified.

[0065] Exemplarily, the compliance verification of the payment record data to be identified may include but is not limited to whether the amount value of the payment amount data is reasonable and whether the payment record data to be identified should be reimbursed, etc. The embodiment of the present invention does not limit the specific content of the compliance verification of the payment record data to be identified.

[0066] In an optional embodiment of the present invention, after verifying the compliance of the payment record data to be identified, it may also include: if it is determined that the payment record data to be identified passes the compliance verification, pushing the payment record data to be identified to a subsequent data processing node; if it is determined that the payment record data to be identified does not pass the compliance verification, storing the verification process data of the payment record data to be identified.

[0067] In an embodiment of the present invention, after verifying the compliance of the payment record data to be identified, if it is determined that the payment record data to be identified passes the compliance verification, the payment record data to be identified can be pushed to a subsequent data processing node. If it is determined that the payment record data to be identified does not pass the compliance verification, the verification process data of the payment record data to be identified can be stored to record the data verification process. It is understandable that if the payment record data to be identified does not pass the compliance verification, the current image data associated with the payment record to be identified can be returned.

[0068] In a specific example, when submitting reimbursement information to the reimbursement system, the reimbursement system will automatically execute a series of verification rules, including but not limited to the reasonableness of the amount, the validity of the date, and the compliance of the payment channel. If the reimbursement system verifies that the situation does not meet the preset rules, the reimbursement form status should be marked as "abnormal" and the specific items of the problem should be specially marked, such as "the payment screenshot failed the verification."

[0069] When the status of the reimbursement form is "abnormal" and the problem item involves the payment screenshot, the financial approval node in the reimbursement system will review the reimbursement form again. If the reimbursement form is determined to be authentic, a process is automatically triggered to send a notification to the biller. A dialog box pops up directly on the reimbursement system interface, displaying "Please confirm the authenticity of the uploaded payment screenshot" to obtain the authenticity verification result of the image data associated with the current payment record to be identified. The biller needs to respond by clicking the "Confirm" or "Reject" button. If the reimbursement form is determined to be false, the financial approval node can store the reimbursement form verification process data and return the reimbursement form.

[0070] Once the biller confirms the authenticity of the payment screenshot, the reimbursement system will automatically update the status of the reimbursement form (such as from "abnormal" to "pending approval"), and record the time of this confirmation action, the biller information, etc. The reimbursement form will be pushed to the next approval node (such as the leader node), and a prompt will also pop up on the approval interface of the leader node, stating "The authenticity of the payment screenshot has been confirmed, please approve it." The reviewer of the leader node will approve it based on the reimbursement form information and the authenticity of the confirmed payment screenshot, and can choose "approval" or "reject." Regardless of the approval result, the approver's operation, time, and approval opinion will be recorded in detail.

[0071] The embodiment of the present invention obtains image data associated with the current payment record to be identified, and further performs image recognition on target reference image elements such as image text, payment amount data, payment date, order number and barcode data included in the image data associated with the current payment record to be identified, to obtain a target image recognition result, so that data verification can be performed based on the target image recognition result to obtain a data verification result of the current payment record to be identified, thereby solving the problems of low efficiency and proneness to errors in the existing manual review of payment data, and being able to improve the review efficiency and data verification accuracy of payment data.

[0072] In the technical solution of the present disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information are in compliance with the relevant laws and regulations and do not violate public order and good morals.

[0073] It should be noted that any arrangement and combination of the technical features in the above embodiments also falls within the protection scope of the present invention.

[0074] Embodiment 2

[0075] Figure 2 is a schematic diagram of a data verification device provided by Embodiment 2 of the present invention, such as Figure 2 As shown, the device includes: an associated image data acquisition module 210, a target image recognition result acquisition module 220 and a data verification result acquisition module 230, wherein:

[0076] The associated image data acquisition module 210 is used to acquire the associated image data of the current payment record to be identified;

[0077] The target image recognition result acquisition module 220 is used to perform image recognition on the target reference image element in the image data associated with the current payment record to be recognized, and obtain the target image recognition result; wherein the target reference image element includes image text, payment amount data, payment date, order number and barcode data;

[0078] The data verification result acquisition module 230 is used to perform data verification according to the target image recognition result to obtain the data verification result of the current payment record to be recognized.

[0079] The embodiment of the present invention obtains image data associated with the current payment record to be identified, and further performs image recognition on target reference image elements such as image text, payment amount data, payment date, order number and barcode data included in the image data associated with the current payment record to be identified, to obtain a target image recognition result, so that data verification can be performed based on the target image recognition result to obtain a data verification result of the current payment record to be identified, thereby solving the problems of low efficiency and proneness to errors in the existing manual review of payment data, and being able to improve the review efficiency and data verification accuracy of payment data.

[0080] Optionally, the image data associated with the current payment record to be identified includes an application payment screenshot and / or a transfer record screenshot, and the target image recognition result acquisition module 220 is also used to: identify the text data in the area near the barcode in the image data associated with the current payment record to be identified to obtain a text data recognition result; identify the amount value, amount position and amount image area height of the payment amount data in the image data associated with the current payment record to be identified to obtain a payment amount data recognition result; match the date format in the image data associated with the current payment record to be identified through a date regular expression, and perform date recognition based on the date format matching result to obtain a date recognition result; extract keywords from the order-related data in the image data associated with the current payment record to be identified, and perform order number recognition on the extracted keywords through an order number regular expression to obtain an order number recognition result; identify and parse the barcode in the image data associated with the current payment record to be identified to obtain a barcode recognition result.

[0081] Optionally, the data verification result acquisition module 230 is also used to: compare the date recognition result with the order date information included in the order number recognition result to obtain a payment date verification result; compare the barcode recognition result with the text data recognition result to obtain a barcode data verification result; compare the date recognition result with the system record date included in the barcode recognition result to obtain a barcode decoding date verification result.

[0082] Optionally, the above-mentioned device may also include a date conversion module, which is used to: obtain the target format date information included in the order number recognition result; parse and convert the target format date information through date parsing logic to obtain the order date information.

[0083] Optionally, the above-mentioned device may also include a compliance verification module, which is used to: when it is determined that the data verification result of the current payment record to be identified is normal, verify the compliance of the payment record data to be identified; when it is determined that the data verification result of the current payment record to be identified is abnormal, obtain the authenticity verification result of the image data associated with the current payment record to be identified; and when it is determined that the authenticity verification result of the image data associated with the current payment record to be identified is passed, verify the compliance of the payment record data to be identified.

[0084] Optionally, the above-mentioned device may also include a data management module, which is used to: when it is determined that the payment record data to be identified has passed the compliance check, push the payment record data to be identified to a subsequent data processing node; when it is determined that the payment record data to be identified has not passed the compliance check, store the verification process data of the payment record data to be identified.

[0085] The above data verification device can execute the data verification method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method. For technical details not described in detail in this embodiment, please refer to the data verification method provided by any embodiment of the present invention.

[0086] Since the data verification device introduced above is a device that can execute the data verification method in the embodiment of the present invention, based on the data verification method introduced in the embodiment of the present invention, the technical personnel in this field can understand the specific implementation of the data verification device of this embodiment and its various variations, so how the data verification device implements the data verification method in the embodiment of the present invention is not described in detail here. As long as the technical personnel in this field implement the device used by the data verification method in the embodiment of the present invention, it belongs to the scope of protection of this application.

[0087] Embodiment 3

[0088] Figure 3 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0089] like Figure 3As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0090] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0091] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 11 performs the various methods and processes described above, such as a data verification method. In some embodiments, the data verification method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the data verification method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the data verification method in any other appropriate manner (e.g., by means of firmware).

[0092] Optionally, the data verification method may include: obtaining image data associated with the current payment record to be identified; performing image recognition on target reference image elements in the image data associated with the current payment record to be identified to obtain a target image recognition result; wherein the target reference image elements include image text, payment amount data, payment date, order number and barcode data; performing data verification based on the target image recognition result to obtain a data verification result of the current payment record to be identified.

[0093] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0094] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0095] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0096] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0097] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0098] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0099] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0100] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A data verification method, characterized in that: include: Get the image data associated with the current payment record to be identified; Performing image recognition on the target reference image element in the image data associated with the current payment record to be recognized to obtain a target image recognition result; wherein the target reference image element includes image text, payment amount data, payment date, order number and barcode data; Perform data verification according to the target image recognition result to obtain the data verification result of the current payment record to be recognized; When it is determined that the data verification result of the current payment record to be identified is normal, verifying the compliance of the data of the payment record to be identified; When it is determined that the data verification result of the current payment record to be identified is abnormal, obtaining the authenticity verification result of the image data associated with the current payment record to be identified, and when it is determined that the authenticity verification result of the image data associated with the current payment record to be identified is verified to be passed, verifying the compliance of the data of the payment record to be identified; If it is determined that the payment record data to be identified passes the compliance check, pushing the payment record data to be identified to a subsequent data processing node; In the case where it is determined that the payment record data to be identified does not pass the compliance check, the verification process data of the payment record data to be identified is stored.

2. The method according to claim 1, characterized in that The current image data associated with the payment record to be identified includes a screenshot of the payment application and / or a screenshot of the transfer record; the image recognition of the target reference image element in the current image data associated with the payment record to be identified to obtain the target image recognition result includes: Recognize the text data in the area near the barcode in the image data associated with the current payment record to be recognized, and obtain a text data recognition result; Identify the amount value, amount position and amount image area height of the payment amount data in the image data associated with the current payment record to be identified, and obtain a payment amount data identification result; Matching the date format in the image data associated with the current payment record to be identified by using a date regular expression, and performing date identification according to the date format matching result to obtain a date identification result; Extracting keywords from the order-related data in the current payment record-related image data to be identified, and performing order number identification on the extracted keywords using an order number regular expression to obtain an order number identification result; The barcode in the image data associated with the current payment record to be identified is identified and analyzed to obtain a barcode identification result.

3. The method according to claim 2, characterized in that The data verification is performed according to the target image recognition result to obtain the data verification result of the current payment record to be recognized, including: Comparing the date recognition result with the order date information included in the order number recognition result to obtain a payment date verification result; Comparing the barcode recognition result with the text data recognition result to obtain a barcode data verification result; The date recognition result is compared with the system record date included in the barcode recognition result to obtain a barcode decoding date verification result.

4. The method according to claim 3, characterized in that Before comparing the date recognition result with the order date information included in the order number recognition result to obtain the payment date verification result, the method further includes: Obtaining target format date information included in the order number recognition result; The target format date information is parsed and converted through date parsing logic to obtain the order date information.

5. A data verification device, characterized in that: include: The associated image data acquisition module is used to acquire the associated image data of the current payment record to be identified; A target image recognition result acquisition module is used to perform image recognition on the target reference image element in the image data associated with the current payment record to be recognized, and obtain a target image recognition result; wherein the target reference image element includes image text, payment amount data, payment date, order number and barcode data; A data verification result acquisition module is used to perform data verification according to the target image recognition result to obtain the data verification result of the current payment record to be recognized; A compliance verification module, for verifying the compliance of the data of the payment record to be identified when it is determined that the data verification result of the current payment record to be identified is normal; for obtaining the authenticity verification result of the image data associated with the current payment record to be identified when it is determined that the data verification result of the current payment record to be identified is abnormal, and for verifying the compliance of the data of the payment record to be identified when it is determined that the authenticity verification result of the image data associated with the current payment record to be identified is passed; The data management module is used to push the payment record data to be identified to a subsequent data processing node when it is determined that the payment record data to be identified has passed the compliance check; and to store the verification process data of the payment record data to be identified when it is determined that the payment record data to be identified has not passed the compliance check.

6. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the data verification method described in any one of claims 1-4.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the data verification method described in any one of claims 1-4 when executed.

8. A computer program product comprising a computer program / instructions, wherein: When the computer program / instructions are executed by a processor, the data verification method described in any one of claims 1 to 4 is implemented.

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