Transaction data cancel-after-verification method and device, medium and product

Abstract

The invention discloses a transaction data cancel-after-verification method and device, a medium and a product, belongs to the field of artificial intelligence, and can be applied to the field of financial science and technology. The transaction data cancel-after-verification method comprises the following steps: matching each piece of message data to be cancel-after-verification with each piece of receipt and payment flow data to be cancel-after-verification, and correspondingly cancel-after-verification the successfully matched message data to be cancel-after-verification and receipt and payment flow data to be cancel-after-verification; according to preset transaction characteristics, classifying the to-be-cancelled message data which are not cancelled after verification and the to-be-cancelled receipt and payment flow data which are not cancelled after verification; combining each type of message data to be cancelled after verification, calculating the sum of money of each combination, combining each type of receipt and payment stream data to be cancelled after verification, and calculating the sum of money of each combination; and based on the sum of the amounts associated with the message data to be canceled after verification and the receipt and payment flow data to be canceled after verification in the corresponding type, transaction data canceling after verification is carried out. According to the technical scheme of the embodiment of the invention, the transaction data cancel-after-verification efficiency can be improved.

Description

A method, apparatus, medium, and product for transaction data verification. Technical Field

[0001] This invention relates to the field of artificial intelligence and can be used in the field of financial technology, particularly to a method, apparatus, medium, and product for transaction data verification. Background Technology

[0002] With societal development, business transactions between financial institutions or between financial institutions and enterprises require transaction fund clearing. Transaction data verification is an important task in financial management.

[0003] Transaction data reconciliation refers to the process of matching and verifying payments already made or received with initial payment messages sent by counterparties. After reconciliation is completed, the reconciliation status is updated to facilitate the management of accounts receivable and payable. Its purpose is to ensure the accuracy and authenticity of financial statements of financial institutions or enterprises.

[0004] In actual business operations, a large amount of transaction data needs to be manually reconciled every day. These are mostly many-to-many reconciliation scenarios, requiring business personnel to manually calculate and reconcile data, which is time-consuming and inefficient. Therefore, achieving efficient transaction data reconciliation is crucial. Summary of the Invention

[0005] This invention provides a method, apparatus, medium, and product for transaction data verification to solve the problem of low efficiency in manual verification processing.

[0006] According to one aspect of the present invention, a method for transaction data reconciliation is provided, comprising:

[0007] Match each pending reconciliation message data with each pending reconciliation payment flow data, and then reconcile the successfully matched pending reconciliation message data and pending reconciliation payment flow data accordingly;

[0008] Based on preset transaction characteristics, the unreconciled pending reconciliation message data and the unreconciled pending payment and receipt flow data are classified separately; the transaction characteristics include settlement date, currency, transaction account, and account name;

[0009] Combine each type of pending reconciliation message data and calculate the total amount of each combination; combine each type of pending reconciliation payment and receipt flow data and calculate the total amount of each combination.

[0010] Transaction data is reconciled based on the sum of the amounts associated with the corresponding categories of pending reconciliation message data and pending reconciliation payment and receipt flow data.

[0011] According to another aspect of the present invention, a transaction data verification device is provided, comprising:

[0012] The first data verification module is used to match each message data to be verified with each payment and receipt flow data to be verified, and to verify the successfully matched message data and payment and receipt flow data accordingly.

[0013] The data classification module is used to classify unreconciled pending verification message data and unreconciled pending payment and receipt flow data according to preset transaction characteristics; the transaction characteristics include settlement date, currency, transaction account, and account name;

[0014] The data combination module is used to combine each type of pending reconciliation message data and calculate the total amount of each combination.

[0015] The second data verification module is used to verify transaction data based on the sum of the amounts associated with the corresponding categories of message data to be verified and payment / receipt flow data to be verified.

[0016] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0017] At least one processor; and

[0018] A memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the transaction data reconciliation method according to any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the transaction data reconciliation method according to any embodiment of the present invention.

[0021] According to another aspect of the present invention, a computer program product is provided, including a computer program that, when executed by a processor, implements the transaction data reconciliation method of any embodiment of the present disclosure.

[0022] The technical solution of this invention matches each pending verification message data and each pending verification payment / receipt flow data. The successfully matched pending verification message data and pending verification payment / receipt flow data are then reconciled accordingly. Based on preset transaction characteristics, the unreconciled pending verification message data and unreconciled pending verification payment / receipt flow data are classified. Each category of pending verification message data is combined, and the total amount of each combination is calculated. Similarly, each category of pending verification payment / receipt flow data is combined, and the total amount of each combination is calculated. Based on the total amount associated with the corresponding categories of pending verification message data and pending verification payment / receipt flow data, transaction data reconciliation is performed. By first performing one-to-one reconciliation and then performing many-to-many reconciliation for the unreconciled data, the reconciliation efficiency is improved while controlling the computational load.

[0023] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 is a flowchart of a transaction data verification method according to Embodiment 1 of the present invention;

[0026] Figure 2 is a flowchart of a transaction data verification method according to Embodiment 2 of the present invention;

[0027] Figure 3 is a schematic diagram of a transaction data verification device according to Embodiment 3 of the present invention;

[0028] Figure 4 is a schematic diagram of the structure of an electronic device that implements the transaction data verification method of this invention. Detailed Implementation

[0029] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0031] Example 1

[0032] Figure 1 is a flowchart of a transaction data reconciliation method provided in Embodiment 1 of the present invention. This embodiment is applicable to situations requiring the reconciliation of multiple pending reconciliation message data and multiple pending reconciliation payment / receipt flow data. This method can be executed by a transaction data reconciliation device, which can be implemented in hardware and / or software and can be configured in various general-purpose computing devices. As shown in Figure 1, the method includes:

[0033] S110. Match each pending verification message data with each pending verification payment flow data, and perform corresponding verification on the successfully matched pending verification message data and pending verification payment flow data.

[0034] The pending verification message data describes the transaction information in the payment and receipt messages. It is obtained by extracting transaction elements from the payment and receipt messages, including the settlement date, amount, currency, transaction account, and account name. The pending verification payment and receipt flow data describes the transaction information associated with the payment and receipt flow. It is obtained by extracting transaction elements from the payment and receipt flow, including the settlement date, amount, currency, transaction account, and account name.

[0035] In this embodiment of the invention, the extracted message data to be reconciled can be stored in a message data table (Table A), and the extracted payment and receipt flow data to be reconciled can be stored in a payment and receipt flow data table (Table B). Then, each message data to be reconciled in Table A and each payment and receipt flow data to be reconciled in Table B are matched. The successfully matched message data and payment and receipt flow data are then reconciled accordingly; that is, the successfully matched message data to be reconciled is deleted from Table A, and correspondingly, the successfully matched payment and receipt flow data to be reconciled is deleted from Table B.

[0036] Specifically, each pending verification message is extracted from Table A as the current pending verification message. This current pending verification message is then compared with each pending down payment transaction in Table B. If the transaction elements (including settlement date, amount, currency, transaction account, and account name) are completely identical, the match is considered successful, and verification is performed. This process is repeated until all pending verification messages in Table A have been traversed.

[0037] S120. Based on the preset transaction characteristics, classify the unreconciled pending message data and the unreconciled pending payment and receipt flow data respectively; the transaction characteristics include settlement date, currency, transaction account and account name.

[0038] Transaction characteristics are data used to describe the features of each transaction. Transaction characteristics include settlement date, currency, transaction account, and account name.

[0039] After completing the one-to-one matching between the pending reconciliation message data and the pending reconciliation payment and receipt flow data, there may still be a large number of unreconciled pending reconciliation message data and pending reconciliation payment and receipt flow data. At this time, it is necessary to perform many-to-many matching and reconciliation of the unreconciled pending reconciliation message data and unreconciled pending reconciliation payment and receipt flow data.

[0040] The technical solution of this invention, after one-to-one verification, classifies the unverified pending verification message data and the unverified pending payment / receipt flow data according to preset transaction characteristics. Specifically, for pending verification message data, data with the same settlement date, currency, transaction account, and account name are grouped into one category; similarly, for pending payment / receipt flow data, data with the same settlement date, currency, transaction account, and account name are grouped into another category. Furthermore, it is necessary to establish a correspondence between the categories of pending verification message data and pending payment / receipt flow data.

[0041] In a specific example, for the message data to be reconciled, data with the same settlement date, currency, transaction account, and account name are grouped into one category. Each category of data is stored in a sub-table of the message data table (Table A). For example, the first category is stored in sub-table A1 of Table A, and the second category is stored in sub-table A2 of Table A.

[0042] Similarly, for the pending payment and receipt flow data, data with the same settlement date, currency, transaction account, and account name are grouped into one category. Each category of data is stored in a sub-table of the payment and receipt flow data table (Table B). For example, the first category is stored in sub-table B1 of Table B, and the second category is stored in sub-table B2 of Table B. Simultaneously, it is necessary to establish a correspondence between the categories of pending payment and receipt flow data and the categories of pending payment and receipt flow data to facilitate subsequent many-to-many matching. For example, sub-tables A1 and B1 store pending payment and receipt flow data with the same settlement date, currency, transaction account, and account name, respectively. That is, sub-tables A1 and B1 are associated. During subsequent many-to-many matching, only the data in sub-tables A1 and B1 needs to be matched.

[0043] S130. Combine each type of pending verification message data and calculate the total amount of each combination. Combine each type of pending verification payment and receipt data and calculate the total amount of each combination.

[0044] In this embodiment of the invention, for each type of data to be reconciled, a combination operation is performed to obtain all possible combinations, and the total amount of each combination is calculated. For example, if a type of data to be reconciled includes n data items, then... A number of possible combinations.

[0045] Similarly, for each type of pending reconciliation receipts and payments data, a combination operation is performed to obtain all possible combinations, and the total amount of each combination is calculated.

[0046] S140. Based on the sum of the amounts associated with the corresponding categories of pending verification message data and pending verification payment and receipt flow data, perform transaction data verification.

[0047] In this embodiment of the invention, transaction data reconciliation is performed based on the total amount associated with corresponding categories of pending reconciliation message data and pending reconciliation payment / receipt flow data. Specifically, for a category of pending reconciliation message data and a category of pending reconciliation payment / receipt flow data with corresponding relationships, the total amount of each group of pending reconciliation message data is compared with the total amount of each group of pending reconciliation payment / receipt flow data. If they match, it is determined that the combination of pending reconciliation message data and the combination of pending reconciliation payment / receipt flow data being compared can be reconciled. Based on the completion of one-to-one reconciliation, grouping the unreconciled data can narrow the matching range, reduce computational load, and improve the efficiency of many-to-many reconciliation.

[0048] In addition, a category of pending reconciliation message data can be extracted sequentially as the current category of pending reconciliation message data, and the total amount of each combination associated with the current category of pending reconciliation message data can be stored in a hash table. Then, from the total amount of each combination associated with the target category of pending reconciliation payment and receipt flow data corresponding to the current category of pending reconciliation message data, one amount is extracted sequentially as the current total amount, and the target total amount corresponding to the current total amount is searched in the hash table. Finally, the combination of pending reconciliation message data corresponding to the target total amount is taken as the target combination, and the combination of pending reconciliation payment and receipt flow data corresponding to the current total amount, as well as the target combination, are reconciled.

[0049] Optional, also includes:

[0050] In response to the acquisition of new pending verification message data, the new pending verification message data is matched with each pending verification payment and receipt flow data;

[0051] If no match is found, the newly added pending verification message data is classified into the target category according to the preset transaction characteristics, the combination of pending verification message data in the target category is updated, and the total amount of each combination is calculated.

[0052] The transaction data is reconciled based on the sum of the amounts associated with the pending reconciliation message data of the target category and the pending reconciliation payment and receipt flow data of the corresponding target category.

[0053] In this optional embodiment, a rolling reconciliation mechanism can be used. When new reconciliation message data is obtained, the new reconciliation message data can be stored in the message data table (Table A), and the new reconciliation message data can be matched one-to-one with each reconciliation payment / receipt flow data. If the match is successful, the new reconciliation message data and the successfully matched reconciliation payment / receipt flow data are deleted accordingly.

[0054] If no match is found, the newly added pending verification message data is categorized into the target category based on preset transaction characteristics. Then, the combinations of pending verification message data in the target category are updated, and the total amount of each combination is calculated. Finally, transaction data verification is performed based on the total amount associated with the pending verification message data in the target category and the corresponding pending verification payment / receipt flow data for that category. Specifically, the total amount of each group of pending verification message data associated with the target category is compared with the total amount of each group of pending verification payment / receipt flow data in the corresponding category. If they match, it is determined that the currently compared combination of pending verification message data and pending verification payment / receipt flow data can be verified. Through a rolling update mechanism, only the newly added data needs to be compared with the unverified data, without calculating the full amount of data, thus ensuring efficient verification processing.

[0055] Optionally, embodiments of the present invention further include:

[0056] In response to the acquisition of newly added payment and receipt flow data to be reconciled, the newly added payment and receipt flow data to be reconciled is matched with each message data to be reconciled;

[0057] If no match is found, the newly added payment and receipt flow data to be reconciled is classified into the target category according to the preset transaction characteristics. Then, the combination of payment and receipt flow data to be reconciled in the target category is updated, and the total amount of each combination is calculated.

[0058] The transaction data is reconciled based on the sum of the amounts associated with the pending reconciliation message data of the target category and the pending reconciliation payment and receipt flow data of the corresponding target category.

[0059] In this optional embodiment, if new pending payment / receipt flow data is obtained, it can be stored in the payment / receipt flow data table (Table B), and the new pending payment / receipt flow data can be matched one-to-one with each pending payment / receipt message data. If the match is successful, the new pending payment / receipt flow data and the successfully matched pending payment / receipt message data can be deleted accordingly.

[0060] If no match is found, the newly added pending payment and receipt flow data is categorized into the target category based on preset transaction characteristics. Then, the combinations of pending payment and receipt flow data in the target category are updated, and the total amount of each combination is calculated. Finally, transaction data reconciliation is performed based on the total amount associated with the pending payment and receipt flow data in the target category and the corresponding pending payment and receipt message data. Specifically, the total amount of each group of pending payment and receipt flow data associated with the target category is compared with the total amount of each group of pending payment and receipt message data in the corresponding category. If they match, it is determined that the currently compared combination of pending payment and receipt message data and the combination of pending payment and receipt flow data can be reconciled, achieving rolling data reconciliation and improving reconciliation efficiency.

[0061] The technical solution of this invention matches each pending verification message data and each pending verification payment / receipt flow data. The successfully matched pending verification message data and pending verification payment / receipt flow data are then reconciled accordingly. Based on preset transaction characteristics, the unreconciled pending verification message data and unreconciled pending verification payment / receipt flow data are classified. Each category of pending verification message data is combined, and the total amount of each combination is calculated. Similarly, each category of pending verification payment / receipt flow data is combined, and the total amount of each combination is calculated. Based on the total amount associated with the corresponding categories of pending verification message data and pending verification payment / receipt flow data, transaction data reconciliation is performed. By first performing one-to-one reconciliation and then performing many-to-many reconciliation for the unreconciled data, the reconciliation efficiency is improved while controlling the computational load.

[0062] Example 2

[0063] Figure 2 is a flowchart of a transaction data reconciliation method provided in Embodiment 2 of the present invention. This embodiment further refines the above embodiment, providing specific steps for reconciling transaction data based on the sum of amounts associated with corresponding categories of reconciled message data and reconciled payment / receipt flow data, as well as specific steps for matching each reconciled message data and each reconciled payment / receipt flow data, and performing corresponding reconciliation on the successfully matched reconciled message data and payment / receipt flow data. As shown in Figure 2, the method includes:

[0064] S210. Extract the transaction elements of the payment and receipt messages and payment and receipt flows to obtain the data of the message to be reconciled and the data of the payment and receipt flows to be reconciled; the transaction elements include the settlement date, amount, currency, transaction account and account name.

[0065] Payment and receipt messages are messages sent by counterparties to describe the elements of a transaction, including the settlement date, amount, currency, transaction account, and account name.

[0066] In this embodiment of the invention, transaction elements are extracted from payment and receipt messages to obtain message data to be reconciled, and transaction elements are extracted from payment and receipt flows to obtain payment and receipt flow data to be reconciled. Transaction elements specifically include settlement date, amount, currency, transaction account, and account name.

[0067] S220. For each pending verification message, compare the transaction elements with each pending verification payment / receipt data in turn.

[0068] In this embodiment of the invention, for each message data to be reconciled, transaction elements are compared sequentially with each payment / receipt data to be reconciled. Specifically, one message data to be reconciled is extracted sequentially as the current message data to be reconciled, and the transaction elements of the current message data to be reconciled are compared one by one with each payment / receipt data to be reconciled.

[0069] S230. If the transaction elements of the pending verification message data and the pending verification payment flow data are consistent, it is determined that the two are successfully matched, and the successfully matched pending verification message data and pending verification payment flow data are verified accordingly.

[0070] In this embodiment of the invention, if the transaction elements of the pending reconciliation message data and the pending reconciliation payment flow data are consistent, it is determined that the two are successfully matched. At this time, the successfully matched pending reconciliation message data and pending reconciliation payment flow data can be reconciled accordingly. Performing one-to-one reconciliation of the pending reconciliation message data first can reduce the matching calculation workload of the subsequent many-to-many reconciliation process and improve reconciliation efficiency.

[0071] S240. Based on the preset transaction characteristics, classify the unreconciled pending message data and the unreconciled pending payment and receipt data respectively; the transaction characteristics include settlement date, currency, transaction account and account name.

[0072] S250. Combine each type of pending reconciliation message data and calculate the total amount of each combination.

[0073] S260. Extract one type of message data to be verified as the current type of message data to be verified, and store the total amount of each combination associated with the current type of message data to be verified into a hash table.

[0074] In this embodiment of the invention, in order to further improve the reconciliation efficiency, a type of message data to be reconciled is extracted sequentially as the current type of message data to be reconciled, and the sum of the amount of each combination associated with the current type of message data to be reconciled is stored in a hash table, and many-to-many matching is performed by searching through the hash table.

[0075] S270. From the sum of the amounts of each combination associated with the target class payment and receipt flow data corresponding to the current class payment and receipt message data, extract one as the current sum of amounts, and look up the target sum of amounts corresponding to the current sum of amounts in the hash table.

[0076] In this embodiment of the invention, from the total amount of each combination associated with the target class of payment and receipt flow data corresponding to the current class of payment and receipt data to be reconciled, one is extracted sequentially as the current total amount, and the target total amount corresponding to the current total amount is searched in the hash table. Specifically, the total amount equal to the current total amount in the hash table can be used as the target total amount. If there is no total amount equal to the current total amount in the hash table, the total amount of the candidate seat amounts in the hash table whose difference from the current total amount is within a set range is transferred to a temporary account using the difference-based accounting method, triggering the manual reconciliation process. Alternatively, the target total amount of the seat amounts in the hash table whose difference from the current total amount is less than a set difference threshold can be used.

[0077] Optionally, look up the target sum of amounts corresponding to the current sum of amounts in the hash table, including:

[0078] Extract a sum of amounts from the hash table one by one, and calculate the difference between the sum of amounts and the current sum of amounts.

[0079] If the difference is less than a set difference threshold, the extracted total amount is determined to be the target total amount corresponding to the current total amount.

[0080] Optionally, the target sum of amounts corresponding to the current sum of amounts can be found in the hash table. This includes: sequentially extracting a sum of amounts from the hash table and calculating the difference between that sum and the current sum of amounts. If the difference is less than a set difference threshold, the extracted sum of amounts is determined to be the target sum of amounts corresponding to the current sum of amounts. By setting a threshold tolerance mechanism, the amount tolerance range can be flexibly set, improving the reimbursement success rate.

[0081] Optionally, embodiments of the present invention further include:

[0082] If the target total amount corresponding to the current total amount is not unique when the hash table is searched, obtain the payment and receipt flow version of the payment and receipt flow data to be reconciled associated with the current total amount, and the message version of the message data to be reconciled associated with the target total amount.

[0083] A data version error warning will be issued if the message version and the payment / receiver version are inconsistent.

[0084] In this optional embodiment, if the target total amount corresponding to the current total amount is not unique when searching the hash table, a data error may exist. To verify the data, the payment / receipt flow version associated with the current total amount and the message version corresponding to the message data associated with the target total amount can be obtained, and the message version and payment / receipt flow version can be compared. If the message version and payment / receipt flow version are inconsistent, a data version error warning is issued. By comparing versions, the problem can be located, erroneous reconciliation can be avoided, and the accuracy of reconciliation can be guaranteed.

[0085] In addition, if the target total amount corresponding to the current total amount is not unique when found in the hash table, a uniqueness check can be performed, and the already written-off data can be marked as "locked" to avoid duplicate configuration. Strong consistency checks can also be performed on key fields such as settlement date and account name, triggering alerts when conflicts occur.

[0086] S280. Take the combination of pending reconciliation message data corresponding to the total target amount as the target combination, and reconcile the combination of pending reconciliation receipt and payment flow data corresponding to the total current amount, as well as the target combination.

[0087] In this embodiment of the invention, the combination of pending reconciliation message data corresponding to the total target amount is taken as the target combination. Then, reconciliation can be performed on the combination of pending reconciliation payment and receipt flow data corresponding to the current total amount, as well as the target combination. By reasonably designing the hash function and storage structure, the efficiency of many-to-many reconciliation can be significantly improved, meeting the requirements of high concurrency and low latency.

[0088] The technical solution of this invention stores the sum of the amount of each combination associated with the data to be reconciled in a hash table. Subsequently, the sum of the amount of each combination associated with the corresponding category of payment and receipt data to be reconciled is compared with the sum of the amount in the hash table, thereby improving the efficiency of many-to-many matching, reducing manual operation steps, and improving business processing efficiency.

[0089] Example 3

[0090] Figure 3 is a schematic diagram of a transaction data verification device provided in Embodiment 3 of the present invention.

[0091] As shown in Figure 3, the device includes:

[0092] The first data verification module 310 is used to match each message data to be verified and each payment and receipt flow data to be verified, and to verify the successfully matched message data and payment and receipt flow data accordingly.

[0093] The data classification module 320 is used to classify unreconciled pending verification message data and unreconciled pending verification payment and receipt flow data according to preset transaction characteristics; the transaction characteristics include settlement date, currency, transaction account and account name;

[0094] The data combination module 330 is used to combine each type of pending reconciliation message data and calculate the total amount of each combination.

[0095] The second data verification module 340 is used to perform transaction data verification based on the sum of the amounts associated with the corresponding categories of message data to be verified and payment / receipt flow data to be verified.

[0096] The technical solution of this invention matches each pending verification message data and each pending verification payment / receipt flow data. The successfully matched pending verification message data and pending verification payment / receipt flow data are then reconciled accordingly. Based on preset transaction characteristics, the unreconciled pending verification message data and unreconciled pending verification payment / receipt flow data are classified. Each category of pending verification message data is combined, and the total amount of each combination is calculated. Similarly, each category of pending verification payment / receipt flow data is combined, and the total amount of each combination is calculated. Based on the total amount associated with the corresponding categories of pending verification message data and pending verification payment / receipt flow data, transaction data reconciliation is performed. By first performing one-to-one reconciliation and then performing many-to-many reconciliation for the unreconciled data, the reconciliation efficiency is improved while controlling the computational load.

[0097] Optionally, the second data verification module 340 includes:

[0098] The hash table storage unit is used to sequentially extract a type of message data to be reconciled as the current type of message data to be reconciled, and store the total amount of each combination associated with the current type of message data to be reconciled into the hash table;

[0099] The total amount comparison unit is used to extract one amount from the total amount of each combination associated with the target class payment and receipt flow data corresponding to the current class of payment and receipt message data, and search for the target total amount corresponding to the current total amount in the hash table;

[0100] The data reconciliation unit is used to take the combination of the message data to be reconciled corresponding to the target total amount as the target combination, and to reconcile the combination of the payment and receipt flow data to be reconciled corresponding to the current total amount, as well as the target combination.

[0101] Optionally, the transaction data verification device also includes:

[0102] The transaction element extraction module is used to extract the transaction elements of each pending verification message and each pending verification payment and receipt flow before matching them, thus obtaining the pending verification message data and pending verification payment and receipt flow data; the transaction elements include settlement date, amount, currency, transaction account, and account name;

[0103] The first data verification module 310 is specifically used for:

[0104] For each pending verification message, the transaction elements are compared sequentially with each pending verification payment and receipt flow data.

[0105] If the transaction elements of the pending verification message data and the pending verification payment flow data are consistent, it is determined that the two are successfully matched, and the matched pending verification message data and pending verification payment flow data are verified accordingly.

[0106] Optionally, the transaction data verification device also includes:

[0107] The newly added message data acquisition module is used to match the newly added message data to be reconciled with each payment and receipt flow data to be reconciled in response to the acquisition of newly added message data to be reconciled.

[0108] The message amount total update module is used to, in the case of unsuccessful matching, classify the newly added message data to be reconciled into a target category according to preset transaction characteristics, update the combination of message data to be reconciled in the target category, and calculate the total amount of each combination;

[0109] The first newly added data reconciliation module is used to reconcile transaction data based on the sum of the amounts associated with the reconciliation message data of the target category and the reconciliation payment and receipt flow data of the corresponding target category.

[0110] Optionally, the second data verification module 340 also includes:

[0111] The version determination unit is used to obtain the payment and receipt flow version of the payment and receipt flow data to be reconciled associated with the current total amount and the message version of the message data to be reconciled associated with the target total amount when the target total amount is not unique in the hash table.

[0112] The version error warning unit is used to issue a data version error warning when the message version and the payment / receiver flow version are inconsistent.

[0113] Optionally, the total amount comparison unit is also used for:

[0114] Extract a sum of amounts sequentially from the hash table, and calculate the difference between the sum of amounts and the current sum of amounts;

[0115] If the difference is less than a set difference threshold, the extracted total amount is determined to be the target total amount corresponding to the current total amount.

[0116] The transaction data verification device provided in this embodiment of the invention can execute the transaction data verification method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0117] Optionally, the transaction data verification device also includes:

[0118] A new payment and receipt flow data acquisition module is added, which is used to match the newly acquired payment and receipt flow data to be reconciled with each message data to be reconciled in response to the acquisition of new payment and receipt flow data to be reconciled.

[0119] The total amount update module for receipts and payments is used to, in the case of unsuccessful matching, classify the newly added receipts and payments data to be reconciled into a target category according to preset transaction characteristics, update the combination of receipts and payments data to be reconciled in the target category, and calculate the total amount of each combination;

[0120] The second newly added data reconciliation module is used to reconcile transaction data based on the sum of the amounts associated with the reconciliation message data of the target category and the reconciliation payment and receipt flow data of the corresponding target category.

[0121] In the technical solution of this invention, the information collected is information and data authorized by the user or fully authorized by all parties. The collection, storage, use, processing, transmission, provision, disclosure and application of related data all comply with the relevant laws, regulations and standards of relevant countries and regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entry points for users to choose to authorize or refuse.

[0122] Example 4

[0123] According to embodiments of the present invention, the present invention also provides an electronic device, a readable storage medium, and a computer program product.

[0124] Figure 4 illustrates a schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, application processors, blade application processors, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0125] As shown in Figure 4, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer programs stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0126] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0127] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as transaction data reconciliation methods.

[0128] In some embodiments, the transaction data reconciliation method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the transaction data reconciliation method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the transaction data reconciliation method by any other suitable means (e.g., by means of firmware).

[0129] Various embodiments 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-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0130] Computer programs used to implement the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs can be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or application.

[0131] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0132] To provide interaction with a user, the systems and techniques described herein can 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 provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0133] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data application processors), or computing systems that include middleware components (e.g., application application processors), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0134] A computing system can include clients and applications. Clients and applications are generally geographically separated and typically interact via a communication network. The client-application relationship is established by computer programs running on the respective computers and having a client-application relationship with each other. An application can be a cloud application, also known as a cloud computing application or cloud server, which is a hosting product within the cloud computing application ecosystem. It addresses the shortcomings of traditional physical servers and VPS applications, such as high management difficulty and weak business scalability.

[0135] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0136] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for verifying transaction data, characterized in that, include: Match each pending reconciliation message data with each pending reconciliation payment flow data, and then reconcile the successfully matched pending reconciliation message data and pending reconciliation payment flow data accordingly; Based on preset transaction characteristics, the unreconciled pending reconciliation message data and the unreconciled pending payment and receipt flow data are classified separately; the transaction characteristics include settlement date, currency, transaction account, and account name; Combine each type of pending verification message data and calculate the total amount of each combination. Combine each type of pending verification payment and receipt flow data and calculate the total amount of each combination. Based on the total amount associated with the pending verification message data and pending verification payment and receipt flow data of the corresponding categories, perform transaction data verification.

2. The method according to claim 1, characterized in that, Based on the sum of amounts associated with the corresponding categories of pending verification message data and pending verification payment flow data, transaction data verification is performed, including: sequentially extracting a category of pending verification message data as the current category of pending verification message data, and storing the sum of amounts for each combination associated with the current category of pending verification message data into a hash table; sequentially extracting one of the sums of amounts for each combination associated with the target category of pending verification payment flow data corresponding to the current category of pending verification message data as the current sum of amounts, and searching for the target sum of amounts corresponding to the current sum of amounts in the hash table; taking the combination of pending verification message data corresponding to the target sum of amounts as the target combination, and verifying the combination of pending verification payment flow data corresponding to the current sum of amounts, as well as the target combination.

3. The method according to claim 1, characterized in that, Before matching each pending verification message and each pending verification payment / receipt flow data, the process includes: extracting transaction elements from the payment / receipt messages and payment / receipt flows to obtain the pending verification message data and pending verification payment / receipt flow data; the transaction elements include settlement date, amount, currency, transaction account, and account name; matching each pending verification message and each pending verification payment / receipt flow data, and performing corresponding verification on the successfully matched pending verification message data and pending verification payment / receipt flow data, including: for each pending verification message data, comparing the transaction elements with each pending verification payment / receipt flow data in sequence; if the transaction elements of the pending verification message data and the pending verification payment / receipt flow data are consistent, it is determined that the two are successfully matched, and the successfully matched pending verification message data and pending verification payment / receipt flow data are performed accordingly for verification.

4. The method according to claim 1, characterized in that, Also includes: In response to the acquisition of newly added pending verification message data, the newly added pending verification message data is matched with each pending verification payment and receipt flow data; If no match is found, the newly added message data to be reconciled is classified into the target category according to the preset transaction characteristics, the combination of message data to be reconciled in the target category is updated, and the total amount of each combination is calculated. The transaction data is reconciled based on the sum of the amounts associated with the pending reconciliation message data of the target category and the pending reconciliation payment and receipt flow data of the corresponding target category.

5. The method according to claim 2, characterized in that, Also includes: If the target total amount corresponding to the current total amount is not unique when the hash table is searched, the payment and receipt flow version of the payment and receipt flow data to be reconciled associated with the current total amount and the message version corresponding to the message data to be reconciled associated with the target total amount are obtained. If the message version and the payment / receiver version are inconsistent, a data version error warning will be issued.

6. The method according to claim 2, characterized in that, The process of finding the target sum of amount corresponding to the current sum of amount in the hash table includes: sequentially extracting a sum of amount from the hash table and calculating the difference between the sum of amount and the current sum of amount; if the difference is less than a set difference threshold, determining that the extracted sum of amount is the target sum of amount corresponding to the current sum of amount.

7. The method according to claim 1, characterized in that, Also includes: In response to the acquisition of newly added pending payment and receipt flow data, the newly added pending payment and receipt flow data is matched with each pending payment and receipt message data; if no match is found, the newly added pending payment and receipt flow data is classified into a target category according to preset transaction characteristics, the combination of pending payment and receipt flow data in the target category is updated, and the total amount of each combination is calculated. The transaction data is reconciled based on the sum of the amounts associated with the pending reconciliation message data of the target category and the pending reconciliation payment and receipt flow data of the corresponding target category.

8. A transaction data verification device, characterized in that, include: The first data verification module is used to match each message data to be verified with each payment and receipt flow data to be verified, and to verify the successfully matched message data and payment and receipt flow data accordingly. The data classification module is used to classify unreconciled pending verification message data and unreconciled pending payment and receipt flow data according to preset transaction characteristics; the transaction characteristics include settlement date, currency, transaction account, and account name; The data combination module is used to combine each type of pending reconciliation message data and calculate the total amount of each combination. The second data verification module is used to verify transaction data based on the sum of the amounts associated with the corresponding categories of message data to be verified and payment / receipt flow data to be verified.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the transaction data verification method according to any one of claims 1-7.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the transaction data verification method according to any one of claims 1-7.

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