WO2022041834A1 - 一种交易数据处理方法与装置 - Google Patents

一种交易数据处理方法与装置 Download PDF

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Publication number
WO2022041834A1
WO2022041834A1 PCT/CN2021/092711 CN2021092711W WO2022041834A1 WO 2022041834 A1 WO2022041834 A1 WO 2022041834A1 CN 2021092711 W CN2021092711 W CN 2021092711W WO 2022041834 A1 WO2022041834 A1 WO 2022041834A1
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Prior art keywords
rule
transaction
executor
rules
expression
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PCT/CN2021/092711
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English (en)
French (fr)
Inventor
沈志嵘
杨燕明
高建斌
李�瑞
王述振
闻福阳
姜金凤
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China Unionpay Co Ltd
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China Unionpay Co Ltd
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Priority to US17/919,506 priority Critical patent/US20230153781A1/en
Publication of WO2022041834A1 publication Critical patent/WO2022041834A1/zh
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0283—Price estimation or determination
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/08—Payment architectures
    • G06Q20/20—Point-of-sale [POS] network systems
    • G06Q20/201—Price look-up processing, e.g. updating
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/08—Payment architectures
    • G06Q20/10—Payment architectures specially adapted for electronic funds transfer [EFT] systems; specially adapted for home banking systems
    • G06Q20/102—Bill distribution or payments
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/38—Payment protocols; Details thereof
    • G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
    • G06Q20/405—Establishing or using transaction specific rules
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Definitions

  • the embodiments of the present application relate to the technical field of data processing, and in particular, to a transaction data processing method and device.
  • the pricing elements used in transaction pricing come from the transaction message and its associated information.
  • configuring pricing parameters take each pricing element as a column of the parameter table, combine different values of these elements according to the pricing rules, and use each combination as a row of the table to form several pricing parameters and assign each parameter to corresponding pricing.
  • the pricing elements are directly derived from transaction messages, there are many parameters, the maintenance cost is large, the parameter configuration workload is large, and the calculation time is long.
  • Embodiments of the present application provide a transaction data processing method and device, so as to reduce the amount of parameters and improve transaction billing efficiency.
  • the embodiment of the present application provides a transaction data processing method, the method includes:
  • the transaction information of the transaction to be processed determine the transaction key value and transaction characteristic value of the transaction to be processed
  • the transaction key value determine a rule set corresponding to the transaction to be processed, and the rule set includes a plurality of rules to be matched;
  • determining the rule set corresponding to the transaction to be processed according to the transaction key value includes:
  • Matching the transaction feature values of the to-be-processed transaction sequentially with multiple to-be-matched rules in the rule set to obtain the rule-matching result of the to-be-processed transaction including:
  • the transaction characteristic value is sequentially input into the multiple rule executors for matching
  • the processing standard corresponding to the rule executor matching the transaction characteristic value is used as the rule matching result.
  • rule executor includes a rule trigger and at least one expression executor
  • the rule executor inputs the transaction characteristic value into the expression executor according to a preset logical relationship; wherein one expression executor corresponds to one characteristic expression;
  • the expression executor compares the transaction characteristic value with the target value corresponding to the expression executor to obtain a comparison result of the expression executor;
  • the rule trigger determines the matching result of the rule executor according to the comparison results of all expression executors.
  • the method further includes:
  • a rule executor pool corresponding to the set of rules to be parsed is generated.
  • the to-be-analyzed rules of the same business type are formed into a to-be-analyzed rule set.
  • an embodiment of the present application provides a transaction data processing device, the device comprising:
  • an acquisition unit configured to determine the transaction key value and transaction characteristic value of the transaction to be processed according to the transaction information of the transaction to be processed;
  • a determining unit configured to determine a rule set corresponding to the transaction to be processed according to the transaction key value, and the rule set includes a plurality of rules to be matched;
  • a matching unit configured to sequentially match the transaction feature values of the to-be-processed transaction with a plurality of to-be-matched rules in the rule set to obtain a rule matching result of the to-be-processed transaction
  • a charging unit configured to perform charging processing on the transaction to be processed according to the rule matching result.
  • the determining unit is specifically used for:
  • the matching unit is specifically used for:
  • the transaction characteristic value is sequentially input into the multiple rule executors for matching
  • the processing standard corresponding to the rule executor matching the transaction characteristic value is used as the rule matching result.
  • rule executor includes a rule trigger and at least one expression executor
  • the matching unit is specifically used for:
  • the rule executor inputs the transaction characteristic value into the expression executor according to a preset logical relationship; wherein one expression executor corresponds to one characteristic expression;
  • the expression executor compares the transaction characteristic value with the target value corresponding to the expression executor to obtain a comparison result of the expression executor;
  • the rule trigger determines the matching result of the rule executor according to the comparison results of all expression executors.
  • a configuration unit is also included for:
  • a rule executor pool corresponding to the set of rules to be parsed is generated.
  • configuration unit is also used for:
  • the to-be-analyzed rules of the same business type are formed into a to-be-analyzed rule set.
  • an embodiment of the present application provides a computing device, including at least one processor and at least one memory, wherein the memory stores a computer program, and when the program is executed by the processor, all The processor executes the steps of the transaction data processing method provided by the embodiment of the present application.
  • the embodiments of the present application provide a storage medium, where the storage medium stores computer instructions, and when the computer instructions are executed on the computer, the computer executes the steps of the transaction data processing method provided by the embodiments of the present application .
  • the key value of the transaction and the characteristic value of the transaction are determined according to the transaction information of the transaction to be processed.
  • a rule set corresponding to the transaction to be processed is determined, and the rule set includes a plurality of rules to be matched.
  • the transaction feature values of the transaction to be processed are sequentially matched with multiple to-be-matched rules in the rule set to obtain a rule matching result of the to-be-processed transaction.
  • the to-be-processed transaction is billed according to the rule matching result.
  • the pricing parameters adopt easy-to-understand characteristic rules, the parameter readability is high, and the parameter quantity is greatly reduced, which can effectively reduce the probability of parameter mismatch and mismatch, thereby reducing the parameter quantity and improving the transaction billing efficiency.
  • FIG. 1 shows a system architecture diagram of a transaction data processing system provided by an embodiment of the present application
  • FIG. 2 shows a flowchart of a transaction data processing method provided by an embodiment of the present application
  • FIG. 3 shows a schematic structural diagram of a transaction feature pricing model in an embodiment of the present application
  • FIG. 4 shows a schematic structural diagram of a rule parsing module in an embodiment of the present application
  • FIG. 5 shows a flowchart of a rule parsing process provided by an embodiment of the present application
  • FIG. 6 shows a schematic structural diagram of a rule executor provided by an embodiment of the present application
  • FIG. 7 shows a schematic structural diagram of a rule matching module provided by an embodiment of the present application.
  • FIG. 8 shows a block diagram of the structure of a transaction data processing apparatus provided by an embodiment of the present application.
  • FIG. 9 shows a structural block diagram of a server provided by an embodiment of the present application.
  • FIG. 1 is a system architecture diagram of a transaction data processing method provided by an embodiment of the present application.
  • the application scenario includes a terminal device 101 , a server 102 and a database 103 .
  • a client is installed in the terminal device 101, and the server 102 is a server corresponding to the client.
  • the terminal device 101 may be a terminal such as a mobile phone, a personal computer (PC), a tablet computer (PAD), a PDA (Personal Digital Assistant, PDA), a notebook computer, or a smart wearable device (such as a smart watch and a smart bracelet). equipment.
  • Each terminal device 101 is connected to the server 102 through a communication network, and the communication network may be a wired network or a wireless network.
  • the server 102 may be a server corresponding to a client, a server or a server cluster or a cloud computing center composed of several servers, or a virtualization platform.
  • the database 103 exists independently of the server 102 .
  • the database 103 may also be located in the server 102 .
  • the server 102 is connected to the database 103 . After the server 102 generates a set of rules to be parsed according to the transaction message, the set of rules to be parsed can be stored in the database 103 . The server 102 obtains the set of rules to be parsed from the database 103, parses the set of rules to be parsed to generate a rule executor, and further generates a pool of rulers. In this way, when performing charging processing on a transaction, the server 102 can input the transaction characteristic value into the rule executor to perform rule matching, and further perform charging processing according to the rule matching result.
  • the architecture provided by the embodiment of the present application is not limited to the structure shown in FIG. 1 , and the embodiment of the present application does not limit it.
  • the following detailed descriptions are given in conjunction with the accompanying drawings and specific embodiments.
  • the embodiments of the present application provide method operation steps as shown in the following embodiments or the accompanying drawings, more or less operation steps may be included in the method based on routine or without creative work. In steps that logically do not have a necessary causal relationship, the execution order of these steps is not limited to the execution order provided by the embodiments of the present application.
  • the pricing elements (pricing dimensions) of transaction classification include: business type, pricing alliance, transaction mode, product type, transaction type, transaction channel, transaction medium, transaction amount (with currency), institution role, acceptance area, acceptance institution, Sending institution, card issuing area, receiving institution, card issuing institution, merchant code, merchant type, merchant type classification, service point input method, code scanning method, card BIN, card nature, card level, card product, installment payment period, authentication information Wait.
  • Transaction pricing generally selects several pricing elements, and assigns different fee prices according to different value combinations of the pricing elements. Different fees for different transactions, the pricing elements used for pricing will be different.
  • the value of all pricing elements of the transaction is obtained based on the transaction information processing, and then compared with the value combinations of the charging elements set in the fee pricing setting one by one, until a complete match is found. A set of to get the corresponding cost price.
  • FIG. 2 is a schematic flowchart of a transaction data processing method provided by an embodiment of the present invention.
  • the method can be applied to the scenario shown in FIG. 1, and the process of the method is described as follows.
  • Step 201 Determine a transaction key value and a transaction characteristic value of the to-be-processed transaction according to the transaction information of the to-be-processed transaction.
  • Step 202 Determine a rule set corresponding to the transaction to be processed according to the transaction key value, where the rule set includes a plurality of rules to be matched.
  • Step 203 Match the transaction feature values of the to-be-processed transaction to multiple to-be-matched rules in the rule set in sequence to obtain a rule matching result of the to-be-processed transaction.
  • Step 204 Perform charging processing on the transaction to be processed according to the rule matching result.
  • the key value of the transaction and the characteristic value of the transaction are determined according to the transaction information of the transaction to be processed.
  • a rule set corresponding to the transaction to be processed is determined, and the rule set includes a plurality of rules to be matched.
  • the transaction feature values of the transaction to be processed are sequentially matched with multiple to-be-matched rules in the rule set to obtain a rule matching result of the to-be-processed transaction.
  • the to-be-processed transaction is billed according to the rule matching result.
  • the pricing parameters adopt easy-to-understand characteristic rules, the parameter readability is high, and the parameter quantity is greatly reduced, which can effectively reduce the probability of parameter mismatch and mismatch, thereby reducing the parameter quantity and improving the transaction billing efficiency.
  • the transaction characteristic value is matched by the to-be-matched rule stored in the rule executor. The following first describes the configuration process of the rule executor.
  • One rule executor corresponds to one feature rule, so before configuring the rule executor, you need to determine the feature rule. Then, before obtaining the set of rules to be parsed, the method further includes:
  • the to-be-analyzed rules of the same business type are formed into a to-be-analyzed rule set.
  • a transaction feature pricing model is defined, which consists of five parts: message information, feature variables, feature expressions, feature rules, and rule sets.
  • the model structure is shown in Figure 3.
  • the elements of each layer can be freely expanded, the element mapping relationship is configured between two adjacent layers, and the elements can be reused in multiple mapping relationships.
  • the message information comes from the transaction message.
  • the transaction message is in ISO8583 format, and the message consists of several message fields. There are 128 message fields. Common message fields include F2 master account number, F3 transaction processing code, and F4 transaction amount. , F18 merchant type, F22 service point input method code, F49 transaction currency code, etc.
  • Feature variables refer to the pricing elements used in business pricing.
  • the mapping relationship between feature variables and message information is configured.
  • the content of the mapping relationship includes: feature variable name, transaction information field name, mapping type, mapping script, etc.
  • the program is based on transaction information,
  • the mapping relationship can calculate the value of the characteristic variable.
  • Mapping types include but are not limited to:
  • Field splicing such as "transaction amount (with currency)" is composed of F49 transaction currency code splicing F4 transaction amount.
  • Customized which can be processed according to certain program logic according to transaction information and other characteristic variables.
  • the value of "Pricing Alliance” is based on F33 sending institution, F100 receiving institution, "card BIN”, “accepting country and region”, “Card-issuing countries and regions” are calculated through the mapping script.
  • Characteristic expression defined as a triple ⁇ characteristic variable, operator, operand>.
  • the operand can be integer, floating point number, string, amount type with currency, etc.
  • the result of the expression Is a boolean True (yes) or False (no).
  • C1 transaction channel C2 business type
  • the characteristic expression example is as follows:
  • a feature variable can define multiple feature expressions.
  • Feature rules are composed of multiple feature expressions connected by logical relationships.
  • Logical relationship symbols include “&” and, "
  • the result of feature rules is also Boolean.
  • Feature rule R002 ((E002
  • a feature expression can be reused by multiple feature rules.
  • a set of rules A set of rules. Several feature rules form a set of rules according to a certain priority or order. A feature rule can be referenced by multiple rule sets, and the same feature rule can have different priorities in different rule sets.
  • Rule package P001 ⁇ 1R001 ⁇ , ⁇ 2R003 ⁇ , ⁇ 3R002 ⁇ , meaning: There are three rules in the rule package, corresponding to priority 1, 2, and 3 respectively.
  • Rule package P002 ⁇ 1R003 ⁇ , ⁇ 2R001 ⁇ , meaning: There are two rules in the rule package.
  • the final result of the above transaction feature pricing model is several rule sets, one of which corresponds to a business type.
  • the number of characteristic variables that is, pricing elements
  • the value of characteristic variables can be expanded by increasing the types of operators and operands.
  • a feature rule can contain any number of feature expressions, and a rule set can refer to any number of feature rules. Therefore, the transaction feature pricing model in the embodiment of the present invention has good scalability, and elements and mapping relationships therein can be freely changed.
  • the configuration process of the above rule set is described below with a consumption transaction.
  • the pricing rules in the transaction message are as follows: the exchange fee for diamond card consumption is 1.2%, the exchange fee for platinum card consumption is 1.1%, and the exchange fee for other consumption transactions is 1.0%.
  • the steps to configure the rule set are as follows:
  • Feature variables are extracted from the pricing rules of transaction messages: card level (C1), transaction type (C2).
  • R001 (E001&E003), diamond card consumption
  • R002 (E002&E003), platinum card consumption
  • R003 ((!E001&!E002)&E003), other card consumption.
  • a rule set P001: ⁇ 1R001 ⁇ , ⁇ 2R002 ⁇ , ⁇ 3R003 ⁇ .
  • three feature rules R001, R002, and R003 are assigned priorities, and the feature rules and pricing standards are associated in the rule set.
  • R001 corresponds to the exchange fee standard of 1.2%
  • R003 corresponds to the exchange fee standard of 1.0%.
  • a rule set can correspond to the cost pricing of the same type of business.
  • set the business primary key ⁇ business type, expense type> for the rule set that is, the corresponding rule set can be found according to the business primary key.
  • multiple pricing rules and corresponding fees can be defined by scenario. Further, the rule set is saved in the database in Json format.
  • the server aggregates and obtains the set of rules to be parsed from the database, and generates a corresponding ruler pool. Specifically, before determining the transaction key value and transaction characteristic value of the to-be-processed transaction according to the transaction information of the to-be-processed transaction, the method further includes:
  • a rule executor pool corresponding to the set of rules to be parsed is generated.
  • the server obtains the set of rules to be parsed from the database, installs the configured set of rules to be parsed into the application program for rule parsing, and assembles a callable rule executor according to the rules to be parsed in the set of rules to be parsed .
  • one rule executor corresponds to each rule to be parsed.
  • multiple rules to be parsed contained in the set correspond to multiple rule executors, respectively, and multiple rule executors corresponding to the same set of rules to be parsed are combined into a rule executor pool, the rule executor pool Corresponds to a business primary key. Therefore, the business primary key can be determined according to the transaction information, and then the matching ruler pool can be determined according to the corresponding relationship between the ruler pool and the business primary key.
  • the rule set includes N characteristic rules, which are rule 1, rule 2, ... rule N, respectively.
  • Input N feature rules into the rule parsing module.
  • the structure of the rule parsing module is shown in Figure 4. It mainly includes two components. One is the rule assembly module, which is used to logically operate several feature expressions in the feature rules.
  • the assembly template of the logical operator is connected with the assembly template of the logical operator, such as the "and" template, the "or” template, the "not” template, etc.; the other is the expression assembly module, which uses the assembly template of the calculation operator for the feature expression. Assembly, the assembly templates of calculation operators such as “equal to" template, "not equal to” template, "belongs to” template, etc.
  • the rule parsing module parses and assembles each feature rule to obtain a rule executor. Specifically, the process of obtaining a rule executor by parsing the feature rules, and then forming a rule set is shown in FIG. 5 . Enter a rule set that includes multiple feature rules into the rule assembly module. Then read each feature rule cyclically, and assemble the rule executor according to the feature rule, including reading the logical symbols connecting the feature expressions in the feature rules, reading the feature expressions contained in the feature rules, and assembling the expressions according to the feature expressions. , and instantiate the logic symbol to generate a rule executor. Finally, N rule executors are generated according to the N feature rules. For example, parse and assemble rule 1 to obtain rule executor 1, parse and assemble rule 2 to obtain rule executor 2... and parse and assemble rule N to obtain rule executor N.
  • the rule parsing module outputs rule executor 1 , rule executor 2 . . . rule executor N.
  • the above N rule executors form an executor pool, and one rule set corresponds to one executor pool.
  • a rule executor is formed according to the rules to be parsed, and the structure of the obtained rule executor is shown in FIG. 6 .
  • the rule executor is composed of a logic processing module, an expression executor, a rule trigger, and the like.
  • a rule executor contains at least one expression executor and one rule trigger, and the expression executor corresponds to the rule trigger. Further, the rule executor may also include multiple expression executors and corresponding pairs of rule triggers, wherein any expression executor corresponds to one rule trigger. For example, in Figure 6, expression executor 1 corresponds to rule trigger 1, and expression executor 2 corresponds to rule trigger 2.
  • Rule executors can also recursively nest other rule executors.
  • An expression executor consists of two parts: data and methods.
  • inputting the transaction characteristic values into the plurality of rule executors for matching in sequence includes:
  • the rule executor inputs the transaction characteristic value into the expression executor according to a preset logical relationship; wherein one expression executor corresponds to one characteristic expression;
  • the expression executor compares the transaction characteristic value with the target value corresponding to the expression executor to obtain a comparison result of the expression executor;
  • the rule trigger determines the matching result of the rule executor according to the comparison results of all expression executors.
  • the logic processing module in the rule executor is used to perform logical operation processing on the results of several expression executors, and return True (yes) or False (no), and the result returned by the outermost logic processing module Used to determine whether the rule matches.
  • the rule trigger is used to execute the action after the rule is matched, and the action content can be customized according to the application.
  • a corresponding executor pool is generated, which contains three rule executors corresponding to R001, R002, and R003.
  • the logical processing method of the outermost rule executor is the "AND” operation, which contains an expression executor "E003” and a nested rule executor "!E001 & !E002".
  • the data input value of the expression executor "E003” is the characteristic variable C2, the target value is "consumption", and the calculation method is "equal to”. If the executor corresponding to rule R003 gets a matching result of True, then the corresponding rule trigger will be triggered.
  • each ruler pool corresponds to a business primary key. Therefore, when the transaction data of a business type needs to be cleared, the key value of the transaction, that is, the business primary key, can be determined according to the transaction data, and then the corresponding ruler pool can be found. Then, the rule pool is used to match the transaction eigenvalues.
  • the determining the rule set corresponding to the transaction to be processed according to the transaction key value includes:
  • Matching the transaction feature values of the to-be-processed transaction sequentially with multiple to-be-matched rules in the rule set to obtain the rule-matching result of the to-be-processed transaction including:
  • the transaction characteristic value is sequentially input into the multiple rule executors for matching
  • the processing standard corresponding to the rule executor matching the transaction characteristic value is used as the rule matching result.
  • FIG. 7 shows a schematic structural diagram of a rule matching module.
  • the transaction feature extraction module extracts and calculates the feature variable value used in the pricing rule from the transaction information, and then adapts the rule executor and starts the rule executor.
  • the rule executors are shared, but each thread processing the transaction has an independent rule execution cache, and the calculation results of the feature expressions are cached in the rule context information. The same feature expression does not need to be recalculated.
  • the rule executor After the rule executor is executed, it returns the result through the rule trigger and executes other set actions.
  • the rule optimizer collects the matching information of each feature expression during the rule execution process (the number of times the rule is cited, executed, and the number of mismatches). , which is used to optimize the feature rule parameters, which can improve the matching efficiency of the rule executor.
  • the ruler pool P001 is obtained, and the ruler pool includes rule executors (R001, R002, R003).
  • the rule executors are started in sequence according to the priority recorded therein, and the result of rule matching is obtained.
  • the transaction is then billed according to the rule matching result.
  • FIG. 8 shows a structural block diagram of a transaction data processing apparatus provided by an embodiment of the present application.
  • the transaction data processing apparatus becomes all or a part of the server 102 in FIG. 1 through hardware or a combination of software and hardware.
  • the device includes:
  • an obtaining unit 801 configured to determine the transaction key value and transaction characteristic value of the transaction to be processed according to the transaction information of the transaction to be processed;
  • a determination unit 802 configured to determine a rule set corresponding to the transaction to be processed according to the transaction key value, where the rule set includes a plurality of rules to be matched;
  • a matching unit 803 configured to sequentially match the transaction feature values of the to-be-processed transaction with a plurality of to-be-matched rules in the rule set to obtain a rule matching result of the to-be-processed transaction;
  • a charging unit 804 configured to perform charging processing on the transaction to be processed according to the rule matching result.
  • determining unit 802 is specifically used for:
  • the matching unit is specifically used for:
  • the transaction characteristic value is sequentially input into the multiple rule executors for matching
  • the processing standard corresponding to the rule executor matching the transaction characteristic value is used as the rule matching result.
  • rule executor includes a rule trigger and at least one expression executor
  • the matching unit 803 is specifically used for:
  • the rule executor inputs the transaction characteristic value into the expression executor according to the preset logical relationship; wherein, one expression executor corresponds to one characteristic expression;
  • the expression executor compares the transaction characteristic value with the target value corresponding to the expression executor to obtain a comparison result of the expression executor;
  • the rule trigger determines the matching result of the rule executor according to the comparison results of all expression executors.
  • a configuration unit 805 for:
  • a rule executor pool corresponding to the set of rules to be parsed is generated.
  • configuration unit 805 is also used for:
  • the to-be-analyzed rules of the same business type are formed into a to-be-analyzed rule set.
  • FIG. 9 shows a structural block diagram of a server provided by an embodiment of the present application.
  • the server 1000 is implemented as the server 102 in FIG. 1 . Specifically:
  • Server 1000 includes central processing unit (CPU) 1001 , system memory 1004 including random access memory (RAM) 1002 and read only memory (ROM) 1003 , and system bus 1005 connecting system memory 1004 and central processing unit 1001 .
  • the server 1000 also includes a basic input/output system (I/O system) 1006 that facilitates the transfer of information between various devices within the computer, and mass storage for storing the operating system 1013, application programs 1014, and other program modules 1015 Device 1007.
  • I/O system basic input/output system
  • the basic input/output system 1006 includes a display 1008 for displaying information and an input device 1009, such as a mouse, keyboard, etc., for user input of information.
  • the display 1008 and the input device 1009 are both connected to the central processing unit 1001 through the input and output controller 1010 connected to the system bus 1005 .
  • the basic input/output system 1006 may also include an input output controller 1010 for receiving and processing input from a number of other devices such as a keyboard, mouse, or electronic stylus.
  • input output controller 1010 also provides output to a display screen, printer, or other type of output device.
  • the mass storage device 1007 is connected to the central processing unit 1001 through a mass storage controller (not shown) connected to the system bus 1005 .
  • the mass storage device 1007 and its associated computer-readable media provide non-volatile storage for the server 1000 . That is, the mass storage device 1007 may include a computer-readable medium (not shown) such as a hard disk or a CD-ROM drive.
  • the computer-readable media may include computer storage media and communication media.
  • Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data.
  • Computer storage media include RAM, ROM, EPROM, EEPROM, flash memory or other solid state storage technology, CD-ROM, DVD or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices.
  • RAM random access memory
  • ROM read only memory
  • EPROM Erasable programmable read-only memory
  • EEPROM electrically erasable programmable read-only memory
  • the server 1000 may also be operated by connecting to a remote computer on the network through a network such as the Internet. That is, the server 1000 can be connected to the network 1012 through the network interface unit 1011 connected to the system bus 1005, or, in other words, the network interface unit 1011 can also be used to connect to other types of networks or remote computer systems (not shown) .
  • the memory further includes one or more programs, the one or more programs are stored in the memory, and the one or more programs include instructions for performing the transaction data processing method provided by the embodiment of the present invention.
  • ROM Read Only Memory
  • RAM Random Access Memory
  • magnetic disk or optical disk etc.

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Abstract

一种交易数据处理方法与装置，属于数据处理技术领域。该方法包括：根据待处理交易的交易信息，确定所述待处理交易的交易关键值以及交易特征值（201）；根据所述交易关键值，确定所述待处理交易对应的规则集合，所述规则集合中包括多个待匹配规则（202）；将所述待处理交易的交易特征值依次匹配所述规则集合中的多个待匹配规则，得到所述待处理交易的规则匹配结果（203）；根据所述规则匹配结果对所述待处理交易进行计费处理（204）。减少了参数量，提升交易计费效率。

Description

一种交易数据处理方法与装置
相关申请的交叉引用
本申请要求在2020年08月28日提交中国专利局、申请号为202010884882.8、申请名称为“一种交易数据处理方法与装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请实施例涉及数据处理技术领域，特别涉及一种交易数据处理方法与装置。
背景技术
交易定价时用到的定价要素来自于交易报文及其附属信息。在配置定价参数时，将每个定价要素作为参数表的一列，根据定价规则将这些要素的不同取值进行组合，每种组合作为表格的一行，这样形成若干条定价参数并对每条参数赋予相应的定价。在计算一笔交易的某项费用时，需要将交易信息与排序后的定价参数进行逐条比较，如果定价要素的取值完全匹配，则可确定该笔交易的费用定价。
现有技术中，定价要素直接来源于交易报文，参数较多，维护开销大，参数配置工作量大，计算耗时较长。
发明内容
本申请实施例提供了一种交易数据处理方法与装置，以减少参数量，提升交易计费效率。
一方面，本申请实施例提供了一种交易数据处理方法，该方法包括：
根据待处理交易的交易信息，确定所述待处理交易的交易关键值以及交易特征值；
根据所述交易关键值，确定所述待处理交易对应的规则集合，所述规则集合中包括多个待匹配规则；
将所述待处理交易的交易特征值依次匹配所述规则集合中的多个待匹配规则，得到所述待处理交易的规则匹配结果；
根据所述规则匹配结果对所述待处理交易进行计费处理。
进一步地，所述根据所述交易关键值，确定所述待处理交易对应的规则集合，包括：
根据所述交易关键值，确定所述待处理交易对应的规则执行器，其中，一个规则执行器对应于一个待匹配规则，所述规则执行器用于执行所述待匹配规则；
所述将所述待处理交易的交易特征值依次匹配所述规则集合中的多个待匹配规则，得到所述待处理交易的规则匹配结果，包括：
根据规则执行器的优先级，将所述交易特征值依次输入所述多个规则执行器中进行匹配；
确定与所述交易特征值相匹配的规则执行器；
将所述与所述交易特征值相匹配的规则执行器对应的处理标准作为所述规则匹配结果。
进一步地，所述规则执行器中包括规则触发器以及至少一个表达式执行器；
所述将所述交易特征值依次输入所述多个规则执行器中进行匹配，包括：
针对任一规则执行器，所述规则执行器按照预先设置的逻辑关系，将所述交易特征值输入表达式执行器中；其中，一个表达式执行器对应一个特征表达式；
针对任一表达式执行器，所述表达式执行器将所述交易特征值与所述表达式执行器对应的目标值进行对比，得到所述表达式执行器的对比结果；
所述规则触发器根据所有表达式执行器的对比结果，确定所述规则执行器的匹配结果。
进一步地，所述根据待处理交易的交易信息，确定所述待处理交易的交易关键值以及交易特征值之前，还包括：
获取待解析规则集合，所述待解析规则集合中包括多个待解析规则；
针对任一待解析规则，根据所述待解析规则中的逻辑关系以及特征表达式，确定所述待解析规则对应的规则执行器；
根据所述多个待解析规则对应的规则执行器，生成所述待解析规则集合对应的规则器池。
进一步地，所述获取待解析规则集合之前，还包括：
根据报文信息，确定特征变量；
利用所述特征变量，生成特征表达式；
将所述特征表达式通过逻辑符号进行连接，生成待解析规则；
将同一业务类型的待解析规则组成待解析规则集合。
另一方面，本申请实施例提供了一种交易数据处理装置，该装置包括：
获取单元，用于根据待处理交易的交易信息，确定所述待处理交易的交易关键值以及交易特征值；
确定单元，用于根据所述交易关键值，确定所述待处理交易对应的规则集合，所述规则集合中包括多个待匹配规则；
匹配单元，用于将所述待处理交易的交易特征值依次匹配所述规则集合中的多个待匹配规则，得到所述待处理交易的规则匹配结果；
计费单元，用于根据所述规则匹配结果对所述待处理交易进行计费处理。
进一步地，所述确定单元，具体用于：
根据所述交易关键值，确定所述待处理交易对应的规则执行器，其中，一个规则执行器对应于一个待匹配规则，所述规则执行器用于执行所述待匹配规则；
所述匹配单元，具体用于：
根据规则执行器的优先级，将所述交易特征值依次输入所述多个规则执行器中进行匹配；
确定与所述交易特征值相匹配的规则执行器；
将所述与所述交易特征值相匹配的规则执行器对应的处理标准作为所述规则匹配结果。
进一步地，所述规则执行器中包括规则触发器以及至少一个表达式执行器；
所述匹配单元，具体用于：
针对任一规则执行器，所述规则执行器按照预先设置的逻辑关系，将所述交易特征值输入表达式执行器中；其中，一个表达式执行器对应一个特征表达式；
针对任一表达式执行器，所述表达式执行器将所述交易特征值与所述表达式执行器对应的目标值进行对比，得到所述表达式执行器的对比结果；
所述规则触发器根据所有表达式执行器的对比结果，确定所述规则执行器的匹配结果。
进一步地，还包括配置单元，用于：
获取待解析规则集合，所述待解析规则集合中包括多个待解析规则；
针对任一待解析规则，根据所述待解析规则中的逻辑符号以及特征表达式，确定所述待解析规则对应的规则执行器；
根据所述多个待解析规则对应的规则执行器，生成所述待解析规则集合对应的规则器池。
进一步地，所述配置单元，还用于：
根据报文信息，确定特征变量；
利用所述特征变量，生成特征表达式；
将所述特征表达式通过逻辑符号进行连接，生成待解析规则；
将同一业务类型的待解析规则组成待解析规则集合。
另一方面，本申请实施例提供了一种计算设备，包括至少一个处理器、以及至少一个存储器，其中，所述存储器存储有计算机程序，当所述程序被所述处理器执行时，使得所述处理器执行本申请实施例提供的交易数据处理 方法的步骤。
另一方面，本申请实施例提供了一种存储介质，所述存储介质存储有计算机指令，当所述计算机指令在计算机上运行时，使得计算机执行本申请实施例提供的交易数据处理方法的步骤。
本申请实施例对待处理交易进行计费处理时，根据待处理交易的交易信息，确定交易关键值以及交易特征值。根据交易关键值，确定待处理交易对应的规则集合，规则集合中包括多个待匹配规则。将待处理交易的交易特征值依次匹配规则集合中的多个待匹配规则，得到待处理交易的规则匹配结果。最后根据规则匹配结果对待处理交易进行计费处理。本发明实施例中，定价参数采用易于理解的特征规则，参数可读性高，参数量大大减少，可有效降低参数误配、错配的概率，从而减少了参数量，提升了交易计费效率。
附图说明
为了更清楚地说明本申请实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1示出了本申请实施例提供的一种交易数据处理系统的系统架构图；
图2示出了本申请实施例提供的一种交易数据处理方法的流程图；
图3示出了本申请实施例中一种交易特征定价模型的结构示意图；
图4示出了本申请实施例中一种规则解析模块的结构示意图；
图5示出了本申请实施例提供的一种规则解析处理的流程图；
图6示出了本申请实施例提供的一种规则执行器的结构示意图；
图7示出了本申请实施例提供的一种规则匹配模块的结构示意图；
图8示出了本申请一个实施例提供的交易数据处理装置的结构方框图；
图9示出了本申请一个实施例提供的服务器的结构方框图。
具体实施方式
为使本申请实施例的目的、技术方案和优点更加清楚，下面将结合本申请实施例中的附图，对本申请的技术方案进行清楚、完整地描述，显然，所描述的实施例是本申请技术方案的一部分实施例，而不是全部的实施例。基于本申请文件中记载的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请技术方案保护的范围。
本发明的说明书和权利要求书及上述附图中的术语“第一”和“第二”是用于区别不同对象，而非用于描述特定顺序。此外，术语“包括”以及它们任何变形，意图在于覆盖不排他的保护。例如包含了一系列步骤或单元的过程、方法、系统、产品或设备没有限定于已列出的步骤或单元，而是可选地还包括没有列出的步骤或单元，或可选地还包括对于这些过程、方法、产品或设备固有的其它步骤或单元。
下面对本申请实施例的技术方案的架构做一些简单介绍，需要说明的是，以下介绍的架构仅用于说明本申请实施例而非限定。在具体实施时，可以根据实际需要灵活地应用本申请实施例提供的技术方案。
为进一步说明本申请实施例提供的技术方案，下面结合附图以及具体实施方式对此进行详细的说明。虽然本申请实施例提供了如下述实施例或附图所示的方法操作步骤，但基于常规或者无需创造性的劳动在所述方法中可以包括更多或者更少的操作步骤。在逻辑上不存在必要因果关系的步骤中，这些步骤的执行顺序不限于本申请实施例提供的执行顺序。
参考图1，其为本申请实施例提供的交易数据处理方法的系统架构图。图1所示，该应用场景中包括终端设备101、服务器102和数据库103。
终端设备101中安装有客户端，服务器102为客户端对应的服务器。终端设备101可以是手机、个人电脑(personal computer，PC)、平板电脑(PAD)、掌上电脑(Personal Digital Assistant，PDA)、笔记本电脑或者智能穿戴式设备(例如智能手表和智能手环)等终端设备。各终端设备101通过通信网络与服务器102连接，该通信网络可以是有线网络或无线网络。服务器102可以 是客户端对应的服务器，可以是一台服务器或由若干台服务器组成的服务器集群或云计算中心，或者是一个虚拟化平台。
其中，图1是以数据库103独立于所述服务器102存在进行说明的，在其他可能的实现方式中，数据库103也可以位于服务器102中。
服务器102与数据库103连接，服务器102根据交易报文生成待解析规则集合后，可以将待解析规则集合存储于数据库103中。服务器102从数据库103中获取待解析规则集合，并对待解析规则集合进行解析生成规则执行器，进一步生成规则器池。这样，在对交易进行计费处理时，服务器102可以将交易特征值输入规则执行器中进行规则匹配，并进一步根据规则匹配结果进行计费处理。
当然，本申请实施例提供的架构并不限用于图1所示的结构，本申请实施例并不进行限制。为进一步说明本申请实施例提供的技术方案，下面结合附图以及具体实施方式对此进行详细的说明。虽然本申请实施例提供了如下述实施例或附图所示的方法操作步骤，但基于常规或者无需创造性的劳动在所述方法中可以包括更多或者更少的操作步骤。在逻辑上不存在必要因果关系的步骤中，这些步骤的执行顺序不限于本申请实施例提供的执行顺序。
交易清分的定价要素(定价维度)包括：业务类型、定价联盟、交易模式、产品类型、交易类型、交易渠道、交易介质、交易金额(带币种)、机构角色、受理地区、受理机构、发送机构、发卡地区、接收机构、发卡机构、商户代码、商户类型、商户类型分类、服务点输入方式、扫码方式、卡BIN、卡性质、卡等级、卡产品、分期付款期数、认证信息等。
交易定价一般会选取若干定价要素，根据定价要素的不同取值组合赋予不同的费用价格。不同交易的不同费用，定价用到的定价要素会有所区别。本发明实施例中，交易在清分处理时，先基于交易信息处理得到这笔交易所有定价要素的值，然后与费用定价设置的计费要素取值组合进行逐个比较，直至找出完全匹配的一组获取对应的费用价格。
请参见图2，为本发明实施例提供的交易数据处理方法的流程示意图，该 方法例如可以应用于如图1所示的场景中，该方法的流程描述如下。
步骤201、根据待处理交易的交易信息，确定所述待处理交易的交易关键值以及交易特征值。
步骤202、根据所述交易关键值，确定所述待处理交易对应的规则集合，所述规则集合中包括多个待匹配规则。
步骤203、将所述待处理交易的交易特征值依次匹配所述规则集合中的多个待匹配规则，得到所述待处理交易的规则匹配结果。
步骤204、根据所述规则匹配结果对所述待处理交易进行计费处理。
本申请实施例对待处理交易进行计费处理时，根据待处理交易的交易信息，确定交易关键值以及交易特征值。根据交易关键值，确定待处理交易对应的规则集合，规则集合中包括多个待匹配规则。将待处理交易的交易特征值依次匹配规则集合中的多个待匹配规则，得到待处理交易的规则匹配结果。最后根据规则匹配结果对待处理交易进行计费处理。本发明实施例中，定价参数采用易于理解的特征规则，参数可读性高，参数量大大减少，可有效降低参数误配、错配的概率，从而减少了参数量，提升了交易计费效率。
由于规则执行器具有良好的扩展性，为了便于规则的扩展和执行，本发明实施例中通过规则执行器内部存储的待匹配规则，对交易特征值进行匹配。下面首先介绍规则执行器的配置过程。
一个规则执行器对应一个特征规则，因此配置规则执行器之前，需要先确定特征规则。则，所述获取待解析规则集合之前，还包括：
根据报文信息，确定特征变量；
利用所述特征变量，生成特征表达式；
将所述特征表达式通过逻辑符号进行连接，生成待解析规则；
将同一业务类型的待解析规则组成待解析规则集合。
具体实施过程中，定义一个交易特征定价模型，由报文信息、特征变量、特征表达式、特征规则、规则集合五个部分组成，模型结构如图3所示。其中每一层的元素都可自由扩展，相邻两层之间配置元素映射关系，元素可在 多个映射关系中复用。
其中，报文信息来自交易报文。以银行卡转接交易为例，交易报文为ISO8583格式，报文由若干报文域组成，报文域有128个，常见的报文域有F2主账号、F3交易处理码、F4交易金额、F18商户类型、F22服务点输入方式码、F49交易货币代码等。
特征变量指业务定价用到的定价要素，特征变量和报文信息之间配置映射关系，映射关系的内容包含：特征变量名、交易信息字段名、映射类型、映射脚本等，程序依据交易信息、映射关系可计算得到特征变量的值。映射类型包括但不限于：
(1)完全相同，如：“商户类型”直接从交易信息的F18商户类型赋值得到。
(2)字段截取，如“受理国家地区”截取交易信息F32受理机构代码(8位字符串)的后四位。
(3)字段拼接，如“交易金额(带币种)”通过F49交易货币代码拼接F4交易金额组成。
(4)查参补充，如“卡BIN”、“卡性质”、“卡品牌”、“卡等级”等是根据报文F2主账号根据查找参数获得。
(5)自定义，可根据交易信息、其他特征变量按照一定的程序逻辑处理得到，如“定价联盟”的取值根据F33发送机构、F100接收机构、“卡BIN”、“受理国家地区”、“发卡国家地区”等通过映射脚本计算得到。
特征表达式，定义为一个三元组<特征变量，操作符，操作数>。操作符可以是“＝”，“<>”，“>”，“<”，“IN”等，操作数可以是整数、浮点数、字符串、带币种的金额类型等，表达式的结果是布尔型的True(是)或False(否)。假设存在特征变量：C1交易渠道，C2业务类型，则特征表达式举例如下：
表达式E001：C1＝‘03’，含义：交易渠道等于03；
表达式E002：C1<>‘01’，含义：交易渠道不等于01；
表达式E003：C2IN(‘B01’,‘B02’)，含义：业务类型为B01或B02。
一个特征变量可以定义多个特征表达式。
特征规则，由多个特征表达式通过逻辑关系连接组成，逻辑关系符包括“&”与，“|”或，“！”非，“()”括号等，特征规则的结果也是布尔型。
特征规则举例如下：
特征规则R001：(E001&E003)，即E001和E003是“与”的关系，两个表达式都为True，则规则结果为True。
特征规则R002：((E002|E003)&E004)，即E001和E003是“或”的关系，其结果和E004再进行“与”操作。
需要说明的是，一个特征表达式可以被多个特征规则复用。
规则集合，若干特征规则按一定优先级或顺序组成规则集合。一条特征规则可以被多个规则集合引用，同一个特征规则在不同规则集合中的优先级也可以不同。
规则包举例如下：
规则包P001:{{1R001},{2R003},{3R002}}，含义：规则包里有三条规则，分别对应优先级1、2、3。
规则包P002:{{1R003},{2R001}}，含义：规则包里有两条规则。
上述交易特征定价模型最终产生的结果是若干个规则集合，其中一个规则集合对应一个业务类型。其中，特征变量即定价要素的个数可任意扩展，特征变量的取值可以通过增加操作符和操作数的类型进行功能扩展。一个特征规则可以包含任意数量的特征表达式，一个规则集合可以引用任意数量的特征规则。因此，本发明实施例中的交易特征定价模型具有较好的可扩展性，可以自由改变其中的元素和映射关系。
下面以消费交易来说明上述规则集合的配置过程。交易报文中的定价规则如下：钻石卡消费的交换费为1.2％，白金卡消费的交换费为1.1％，其他消费交易交换费1.0％。规则集合配置步骤如下：
(1)从交易报文的定价规则中抽取得到特征变量：卡等级(C1)、交易类型(C2)。
(2)在特征变量和交易信息映射表中配置C1和C2与报文域的映射关系。
(3)根据上述特征变量构建特征表达式，其中，卡等级的表达式包括：E001:C1＝‘钻石’，E002：C1＝‘白金’；交易类型的表达式为：E003：C2＝‘消费’。
(4)构建特征规则，分别是规则R001、R002、R003：
R001:(E001&E003)，钻石卡消费；
R002:(E002&E003)，白金卡消费；
R003:((！E001&！E002)&E003)，其他卡消费。
(5)构建规则集合：P001:{{1R001},{2R002},{3R003}}。具体为三个特征规则R001、R002、R003分配优先级，并在规则集合中将特征规则与定价标准进行关联，如R001对应交换费标准为1.2％，R003对应交换费标准为1.0％。
在业务上，一个规则集合可以对应同一类型的业务的费用定价。为了便于分辨，为规则集合设置业务主键<业务种类、费用类型>，即可以根据业务主键查找到对应的规则集合。在规则集合里可以按场景定义多条定价规则及相应的费用。进一步地，规则集合以Json格式保存在数据库中。
进一步地，服务器从数据库汇总获取待解析规则集合，生成对应的规则器池。具体地，所述根据待处理交易的交易信息，确定所述待处理交易的交易关键值以及交易特征值之前，还包括：
获取待解析规则集合，所述待解析规则集合中包括多个待解析规则；
针对任一待解析规则，根据所述待解析规则中的逻辑关系以及特征表达式，确定所述待解析规则对应的规则执行器；
根据所述多个待解析规则对应的规则执行器，生成所述待解析规则集合对应的规则器池。
具体实施过程中，服务器从数据库中获取待解析规则集合，将配置好的待解析规则集合装置至规则解析的应用程序中，根据待解析规则集合中的待解析规则装配可被调用的规则执行器。其中，一个规则执行器对应个待解析规则。对于一个待解析规则集合，集合中包含的多个待解析规则分别对应多 个规则执行器，则将同一个待解析规则集合对应的多个规则执行器组合成一个规则器池，该规则器池对应一个业务主键。从而可以根据交易信息确定业务主键，再根据规则器池与业务主键的对应关系，确定匹配的规则器池。
具体的，规则集合中包含N个特征规则，分别为规则1、规则2……规则N。将N个特征规则输入规则解析模块中，该规则解析模块的结构如图4所示，主要包含两个组成部分，一个是规则装配模块，用于将特征规则中的若干特征表达式用逻辑操作符的装配模板进行连接，逻辑操作符的装配模板如“与”模板、“或”模板、“非”模板等；另一个是表达式装配模块，将特征表达式用计算操作符的装配模板进行组装，计算操作符的装配模板如“等于”模板、“不等于”模板、“属于”模板等。
规则解析模块对每一个特征规则进行解析装配，得到一个规则执行器。具体的，根据特征规则解析得到规则执行器，进而形成规则集合的处理过程如图5所示。向规则装配模块中输入一个规则集合，该规则集合中包括多个特征规则。然后循环读取每一个特征规则，根据特征规则装配规则执行器，包括读取特征规则中连接特征表达式的逻辑符号，读取特征规则中包含的特征表达式，根据特征表达式装配表达式执行器，并将逻辑符号实例化，生成一个规则执行器。最后根据N个特征规则生成N个规则执行器。例如，对规则1进行解析装配得到规则执行器1，对规则2进行解析装配得到规则执行器2……对规则N进行解析装配得到规则执行器N。
从而，规则解析模块输出规则执行器1、规则执行器2……规则执行器N。上述N个规则执行器形成一个执行器池，一个规则集合对应一个执行器池。
根据待解析规则形成规则执行器，得到的规则执行器的结构如图6所示。其中，规则执行器由逻辑处理模块、表达式执行器、规则触发器等组成。一个规则执行器至少包含一个表达式执行器和一个规则触发器，该表达式执行器与规则触发器相对应。进一步地，规则执行器也可以包括多个表达式执行器和对应的对个规则触发器，其中，任一表达式执行器对应一个规则触发器。例如，图6中表达式执行器1对应规则触发器1，表达式执行器2对应规则触 发器2。
规则执行器还可以递归嵌套其他规则执行器。表达式执行器由数据和方法两部分组成。
进一步地，所述将所述交易特征值依次输入所述多个规则执行器中进行匹配，包括：
针对任一规则执行器，所述规则执行器按照预先设置的逻辑关系，将所述交易特征值输入表达式执行器中；其中，一个表达式执行器对应一个特征表达式；
针对任一表达式执行器，所述表达式执行器将所述交易特征值与所述表达式执行器对应的目标值进行对比，得到所述表达式执行器的对比结果；
所述规则触发器根据所有表达式执行器的对比结果，确定所述规则执行器的匹配结果。
具体实施过程中，规则执行器中的逻辑处理模块用于对若干个表达式执行器的结果进行逻辑运算处理，返回True(是)或者False(否)，最外层的逻辑处理模块返回的结果用于判断规则是否匹配。规则触发器用于执行规则匹配后的动作，可根据应用自定义动作内容。
以上文的消费交易为例，对规则集合P001解析后，生成一个对应的执行器池，里面包含R001、R002、R003对应的三个规则执行器。以R003:((！E001&！E002)&E003)为例，最外层规则执行器的逻辑处理方法是“与”操作，它包含了一个表达式执行器“E003”，嵌套了一个规则执行器“！E001&！E002”。表达式执行器“E003”的数据输入值是特征变量C2，目标值是“消费”，计算方法是“等于”。如果规则R003对应的执行器得到匹配结果是True，那么就会触发对应的规则触发器。
上述过程形成多个规则器池，每个规则器池对应一个业务主键。从而，需要对一个业务类型的交易数据进行清算处理时，可以根据交易数据确定交易关键值，即业务主键，进而找到对应的规则器池。进而利用规则器池对交易特征值进行匹配。
所述根据所述交易关键值，确定所述待处理交易对应的规则集合，包括：
根据所述交易关键值，确定所述待处理交易对应的规则执行器，其中，一个规则执行器对应于一个待匹配规则，所述规则执行器用于执行所述待匹配规则；
所述将所述待处理交易的交易特征值依次匹配所述规则集合中的多个待匹配规则，得到所述待处理交易的规则匹配结果，包括：
根据规则执行器的优先级，将所述交易特征值依次输入所述多个规则执行器中进行匹配；
确定与所述交易特征值相匹配的规则执行器；
将所述与所述交易特征值相匹配的规则执行器对应的处理标准作为所述规则匹配结果。
图7示出了规则匹配模块的结构示意图。具体实施过程中，交易特征抽取模块从交易信息中抽取并计算定价规则用到的特征变量值，然后适配规则执行器并启动规则执行器。在对交易进行批量清分时，规则执行器是共享的，但处理交易的每个线程都拥有独立的规则执行缓存，特征表达式的计算结果缓存在规则上下文信息里，多个规则用到的相同特征表达式无需重复计算。规则执行器执行完毕后通过规则触发器返回结果并执行其他设定的动作。
规则优化器采集规则执行过程中各特征表达式的匹配信息(规则引用次数、被执行次数、不匹配次数)，每天清算批量处理后将这些信息进行汇总统计分析，计算特征表达式的区分度值，用于优化特征规则参数，可提升规则执行器的匹配效率。
下面以具体实施例对上述流程进行详细介绍。
以上文提到的消费交易为例，先根据交易信息确定交易关键值和交易特征值，具体按业务逻辑得到业务主键值<消费、交换费>。
依据业务主键值查找得到规则器池P001，规则器池中包括规则执行器(R001、R002、R003)。按照其中记录的优先级依次启动规则执行器，得到规则匹配的结果。再根据规则匹配结果对交易进行计费处理。
下述为本申请装置实施例，对于装置实施例中未详尽描述的细节，可以参考上述一一对应的方法实施例。
请参考图8，其示出了本申请一个实施例提供的交易数据处理装置的结构方框图。该交易数据处理装置通过硬件或者软硬件的结合实现成为图1中服务器102的全部或者一部分。该装置包括：
获取单元801，用于根据待处理交易的交易信息，确定所述待处理交易的交易关键值以及交易特征值；
确定单元802，用于根据所述交易关键值，确定所述待处理交易对应的规则集合，所述规则集合中包括多个待匹配规则；
匹配单元803，用于将所述待处理交易的交易特征值依次匹配所述规则集合中的多个待匹配规则，得到所述待处理交易的规则匹配结果；
计费单元804，用于根据所述规则匹配结果对所述待处理交易进行计费处理。
进一步地，所述确定单元802，具体用于：
根据所述交易关键值，确定所述待处理交易对应的规则执行器，其中，一个规则执行器对应于一个待匹配规则，所述规则执行器用于执行所述待匹配规则；
所述匹配单元，具体用于：
根据规则执行器的优先级，将所述交易特征值依次输入所述多个规则执行器中进行匹配；
确定与所述交易特征值相匹配的规则执行器；
将所述与所述交易特征值相匹配的规则执行器对应的处理标准作为所述规则匹配结果。
进一步地，所述规则执行器中包括规则触发器以及至少一个表达式执行器；
所述匹配单元803，具体用于：
针对任一规则执行器，所述规则执行器按照预先设置的逻辑关系，将所 述交易特征值输入表达式执行器中；其中，一个表达式执行器对应一个特征表达式；
针对任一表达式执行器，所述表达式执行器将所述交易特征值与所述表达式执行器对应的目标值进行对比，得到所述表达式执行器的对比结果；
所述规则触发器根据所有表达式执行器的对比结果，确定所述规则执行器的匹配结果。
进一步地，还包括配置单元805，用于：
获取待解析规则集合，所述待解析规则集合中包括多个待解析规则；
针对任一待解析规则，根据所述待解析规则中的逻辑符号以及特征表达式，确定所述待解析规则对应的规则执行器；
根据所述多个待解析规则对应的规则执行器，生成所述待解析规则集合对应的规则器池。
进一步地，所述配置单元805，还用于：
根据报文信息，确定特征变量；
利用所述特征变量，生成特征表达式；
将所述特征表达式通过逻辑符号进行连接，生成待解析规则；
将同一业务类型的待解析规则组成待解析规则集合。
请参考图9，其示出了本申请一个实施例提供的服务器的结构方框图。该服务器1000实现为图1中的服务器102。具体来讲：
服务器1000包括中央处理单元(CPU)1001、包括随机存取存储器(RAM)1002和只读存储器(ROM)1003的系统存储器1004，以及连接系统存储器1004和中央处理单元1001的系统总线1005。所述服务器1000还包括帮助计算机内的各个器件之间传输信息的基本输入/输出系统(I/O系统)1006，和用于存储操作系统1013、应用程序1014和其他程序模块1015的大容量存储设备1007。
所述基本输入/输出系统1006包括有用于显示信息的显示器1008和用于 用户输入信息的诸如鼠标、键盘之类的输入设备1009。其中所述显示器1008和输入设备1009都通过连接到系统总线1005的输入输出控制器1010连接到中央处理单元1001。所述基本输入/输出系统1006还可以包括输入输出控制器1010以用于接收和处理来自键盘、鼠标、或电子触控笔等多个其他设备的输入。类似地，输入输出控制器1010还提供输出到显示屏、打印机或其他类型的输出设备。
所述大容量存储设备1007通过连接到系统总线1005的大容量存储控制器(未示出)连接到中央处理单元1001。所述大容量存储设备1007及其相关联的计算机可读介质为服务器1000提供非易失性存储。也就是说，所述大容量存储设备1007可以包括诸如硬盘或者CD-ROM驱动器之类的计算机可读介质(未示出)。
所述计算机可读介质可以包括计算机存储介质和通信介质。计算机存储介质包括以用于存储诸如计算机可读指令、数据结构、程序模块或其他数据等信息的任何方法或技术实现的易失性和非易失性、可移动和不可移动介质。计算机存储介质包括RAM、ROM、EPROM、EEPROM、闪存或其他固态存储其技术，CD-ROM、DVD或其他光学存储、磁带盒、磁带、磁盘存储或其他磁性存储设备。当然，本领域技术人员可知所述计算机存储介质不局限于上述几种。上述的系统存储器1004和大容量存储设备1007可以统称为存储器。
根据本发明的各种实施例，所述服务器1000还可以通过诸如因特网等网络连接到网络上的远程计算机运行。也即服务器1000可以通过连接在所述系统总线1005上的网络接口单元1011连接到网络1012，或者说，也可以使用网络接口单元1011来连接到其他类型的网络或远程计算机系统(未示出)。
所述存储器还包括一个或者一个以上的程序，所述一个或者一个以上程序存储于存储器中，所述一个或者一个以上程序包含用于进行本发明实施例提供的交易数据处理方法的指令。
本领域普通技术人员可以理解上述实施例的签到方法中的全部或部分步 骤是可以通过程序来指令相关的硬件来完成，该程序可以存储于一计算机可读存储介质中，存储介质可以包括：只读存储器(ROM，Read Only Memory)、随机存取记忆体(RAM，Random Access Memory)、磁盘或光盘等。
本领域普通技术人员可以理解上述实施例的签到方法中的全部或部分步骤是可以通过程序来指令相关的硬件来完成，该程序可以存储于计算机可读存储介质中，存储介质可以包括：只读存储器(ROM，Read Only Memory)、随机存取记忆体(RAM，Random Access Memory)、磁盘或光盘等。
上述本申请实施例序号仅仅为了描述，不代表实施例的优劣。
以上所述仅为本申请的较佳实施例，并不用以限制本申请，凡在本申请的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本申请的保护范围之内。

Claims (12)

  1. 一种交易数据处理方法，其特征在于，所述方法包括：
    根据待处理交易的交易信息，确定所述待处理交易的交易关键值以及交易特征值；
    根据所述交易关键值，确定所述待处理交易对应的规则集合，所述规则集合中包括多个待匹配规则；
    将所述待处理交易的交易特征值依次匹配所述规则集合中的多个待匹配规则，得到所述待处理交易的规则匹配结果；
    根据所述规则匹配结果对所述待处理交易进行计费处理。
  2. 根据权利要求1所述的方法，其特征在于，所述根据所述交易关键值，确定所述待处理交易对应的规则集合，包括：
    根据所述交易关键值，确定所述待处理交易对应的规则执行器，其中，一个规则执行器对应于一个待匹配规则，所述规则执行器用于执行所述待匹配规则；
    所述将所述待处理交易的交易特征值依次匹配所述规则集合中的多个待匹配规则，得到所述待处理交易的规则匹配结果，包括：
    根据规则执行器的优先级，将所述交易特征值依次输入所述多个规则执行器中进行匹配；
    确定与所述交易特征值相匹配的规则执行器；
    将所述与所述交易特征值相匹配的规则执行器对应的处理标准作为所述规则匹配结果。
  3. 根据权利要求2所述的方法，其特征在于，所述规则执行器中包括规则触发器以及至少一个表达式执行器；
    所述将所述交易特征值依次输入所述多个规则执行器中进行匹配，包括：
    针对任一规则执行器，所述规则执行器按照预先设置的逻辑关系，将所述交易特征值输入表达式执行器中；其中，一个表达式执行器对应一个特征 表达式；
    针对任一表达式执行器，所述表达式执行器将所述交易特征值与所述表达式执行器对应的目标值进行对比，得到所述表达式执行器的对比结果；
    所述规则触发器根据所有表达式执行器的对比结果，确定所述规则执行器的匹配结果。
  4. 根据权利要求2所述的方法，其特征在于，所述根据待处理交易的交易信息，确定所述待处理交易的交易关键值以及交易特征值之前，还包括：
    获取待解析规则集合，所述待解析规则集合中包括多个待解析规则；
    针对任一待解析规则，根据所述待解析规则中的逻辑关系以及特征表达式，确定所述待解析规则对应的规则执行器；
    根据所述多个待解析规则对应的规则执行器，生成所述待解析规则集合对应的规则器池。
  5. 根据权利要求4所述的方法，其特征在于，所述获取待解析规则集合之前，还包括：
    根据报文信息，确定特征变量；
    利用所述特征变量，生成特征表达式；
    将所述特征表达式通过逻辑符号进行连接，生成待解析规则；
    将同一业务类型的待解析规则组成待解析规则集合。
  6. 一种交易数据处理装置，其特征在于，所述装置包括：
    获取单元，用于根据待处理交易的交易信息，确定所述待处理交易的交易关键值以及交易特征值；
    确定单元，用于根据所述交易关键值，确定所述待处理交易对应的规则集合，所述规则集合中包括多个待匹配规则；
    匹配单元，用于将所述待处理交易的交易特征值依次匹配所述规则集合中的多个待匹配规则，得到所述待处理交易的规则匹配结果；
    计费单元，用于根据所述规则匹配结果对所述待处理交易进行计费处理。
  7. 根据权利要求6所述的装置，其特征在于，所述确定单元，具体用于：
    根据所述交易关键值，确定所述待处理交易对应的规则执行器，其中，一个规则执行器对应于一个待匹配规则，所述规则执行器用于执行所述待匹配规则；
    所述匹配单元，具体用于：
    根据规则执行器的优先级，将所述交易特征值依次输入所述多个规则执行器中进行匹配；
    确定与所述交易特征值相匹配的规则执行器；
    将所述与所述交易特征值相匹配的规则执行器对应的处理标准作为所述规则匹配结果。
  8. 根据权利要求7所述的装置，其特征在于，所述规则执行器中包括规则触发器以及至少一个表达式执行器；
    所述匹配单元，具体用于：
    针对任一规则执行器，所述规则执行器按照预先设置的逻辑关系，将所述交易特征值输入表达式执行器中；其中，一个表达式执行器对应一个特征表达式；
    针对任一表达式执行器，所述表达式执行器将所述交易特征值与所述表达式执行器对应的目标值进行对比，得到所述表达式执行器的对比结果；
    所述规则触发器根据所有表达式执行器的对比结果，确定所述规则执行器的匹配结果。
  9. 根据权利要求7所述的装置，其特征在于，还包括配置单元，用于：
    获取待解析规则集合，所述待解析规则集合中包括多个待解析规则；
    针对任一待解析规则，根据所述待解析规则中的逻辑符号以及特征表达式，确定所述待解析规则对应的规则执行器；
    根据所述多个待解析规则对应的规则执行器，生成所述待解析规则集合对应的规则器池。
  10. 根据权利要求9所述的装置，其特征在于，所述配置单元，还用于：
    根据报文信息，确定特征变量；
    利用所述特征变量，生成特征表达式；
    将所述特征表达式通过逻辑符号进行连接，生成待解析规则；
    将同一业务类型的待解析规则组成待解析规则集合。
  11. 一种计算设备，其特征在于，包括至少一个处理器、以及至少一个存储器，其中，所述存储器存储有计算机程序，当所述程序被所述处理器执行时，使得所述处理器执行权利要求1至5任一项所述的交易数据处理方法。
  12. 一种存储介质，所述存储介质存储有计算机指令，其特征在于，当所述计算机指令在计算机上运行时，使得计算机执行权利要求1至5任一项所述的交易数据处理方法。
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Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112016967B (zh) * 2020-08-28 2023-09-05 中国银联股份有限公司 一种交易数据处理方法与装置
CN112598498B (zh) * 2020-12-16 2024-08-23 中国建设银行股份有限公司 一种数据处理方法和装置
CN112862608A (zh) * 2021-01-22 2021-05-28 中国建设银行股份有限公司 一种交易数据匹配方法和装置
CN114049169A (zh) * 2021-10-22 2022-02-15 汇通数科智能科技有限公司 基于清分收费模型计算交易费用的方法、装置和计算设备
CN115580571B (zh) * 2022-09-26 2024-02-09 中国建设银行股份有限公司 一种报文发送方法、装置、计算设备及存储介质
CN115796886B (zh) * 2022-11-29 2025-10-31 中国银联股份有限公司 数据处理方法、装置、设备及存储介质

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20170323006A1 (en) * 2015-11-29 2017-11-09 Vatbox, Ltd. System and method for providing analytics in real-time based on unstructured electronic documents
CN108090755A (zh) * 2017-12-18 2018-05-29 深圳市快付通金融网络科技服务有限公司 计费模型定义方法、数据清算系统和计算机可读存储介质
CN109600243A (zh) * 2017-09-30 2019-04-09 华为技术有限公司 数据分析方法和装置
CN110378699A (zh) * 2019-07-25 2019-10-25 中国工商银行股份有限公司 一种交易反欺诈方法、装置及系统
CN110415118A (zh) * 2019-07-29 2019-11-05 中国工商银行股份有限公司 处理方法及其装置、电子设备和介质
CN111402057A (zh) * 2020-03-31 2020-07-10 中国工商银行股份有限公司 交易报文匹配方法、装置、计算设备以及介质
CN112016967A (zh) * 2020-08-28 2020-12-01 中国银联股份有限公司 一种交易数据处理方法与装置

Family Cites Families (36)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080172314A1 (en) * 1996-11-12 2008-07-17 Hahn-Carlson Dean W Financial institution-based transaction processing system and approach
US20040015579A1 (en) * 2001-06-14 2004-01-22 Geoffrey Cooper Method and apparatus for enterprise management
US6801905B2 (en) * 2002-03-06 2004-10-05 Sybase, Inc. Database system providing methodology for property enforcement
US20040167863A1 (en) * 2003-02-21 2004-08-26 Knowles W. Jeffrey System and method of transferring data through transaction process
WO2005022416A1 (en) * 2003-08-21 2005-03-10 The Trustees Of Columbia University In The City Of New York Methods and systems for autonomously managing a network
EP1676189A4 (en) * 2003-08-27 2008-01-02 Equifax Inc APPLICATION PROCESSING AND DECISION-MAKING SYSTEMS AND PROCESSES
US20050060372A1 (en) * 2003-08-27 2005-03-17 Debettencourt Jason Techniques for filtering data from a data stream of a web services application
KR20130082516A (ko) * 2004-12-07 2013-07-19 비코드 피티와이 엘티디. 전자 상거래 시스템, 방법 및 장치
US20060247944A1 (en) * 2005-01-14 2006-11-02 Calusinski Edward P Jr Enabling value enhancement of reference data by employing scalable cleansing and evolutionarily tracked source data tags
US20060235714A1 (en) * 2005-01-14 2006-10-19 Adinolfi Ronald E Enabling flexible scalable delivery of on demand datasets
US8346638B2 (en) * 2005-10-26 2013-01-01 Capital One Financial Corporation Systems and methods for processing transaction data to perform a merchant chargeback
US8412624B2 (en) * 2008-07-17 2013-04-02 Toshiba Global Commerce Solutions Holdings Corporation Multiple financial account transaction processing
US10504126B2 (en) * 2009-01-21 2019-12-10 Truaxis, Llc System and method of obtaining merchant sales information for marketing or sales teams
US20110029367A1 (en) * 2009-07-29 2011-02-03 Visa U.S.A. Inc. Systems and Methods to Generate Transactions According to Account Features
US8738418B2 (en) * 2010-03-19 2014-05-27 Visa U.S.A. Inc. Systems and methods to enhance search data with transaction based data
US8326760B2 (en) * 2010-09-13 2012-12-04 Cybersource Corporation Computer-based collective intelligence recommendations for transaction review
US20130066771A1 (en) * 2011-07-22 2013-03-14 Visa International Service Association Systems and Methods to Configure Data for Diverse Services
US20140222533A1 (en) * 2013-02-07 2014-08-07 Visa International Service Association Systems and methods to use transaction authorization communications to process individualized offers
US11030341B2 (en) * 2013-11-01 2021-06-08 Anonos Inc. Systems and methods for enforcing privacy-respectful, trusted communications
US10922767B2 (en) * 2014-05-11 2021-02-16 Zoccam Technologies, Inc. Systems and methods for database management of transaction information and payment instruction data
US10922766B2 (en) * 2014-05-11 2021-02-16 Zoccam Technologies, Inc. Systems and methods for database management of transaction information and payment data
US11170445B2 (en) * 2015-12-16 2021-11-09 Alegeus Technologies, Llc Systems and methods for allocating resources using information technology infrastructure
US20170178135A1 (en) * 2015-12-16 2017-06-22 Alegeus Technologies, Llc Systems and methods for notifications using a multi-purse card
US10770181B2 (en) * 2015-12-16 2020-09-08 Alegeus Technologies, Llc Systems and methods for reducing resource consumption via information technology infrastructure
US11019101B2 (en) * 2016-03-11 2021-05-25 Netskope, Inc. Middle ware security layer for cloud computing services
US11755997B2 (en) * 2017-02-22 2023-09-12 Anduin Transactions, Inc. Compact presentation of automatically summarized information according to rule-based graphically represented information
CN109146440B (zh) * 2017-06-16 2020-06-05 腾讯科技（深圳）有限公司 交易结算方法、装置、服务器以及存储介质
US20190172027A1 (en) * 2017-12-04 2019-06-06 Mastercard International Incorporated Payment facilitation system for facilitating payment for a transaction
US10949450B2 (en) * 2017-12-04 2021-03-16 Panjiva, Inc. Mtransaction processing improvements
US11023897B1 (en) * 2017-12-05 2021-06-01 Worldpay, Llc Systems and methods for optimizing transaction conversion rate using measured feedback
GB201810707D0 (en) * 2018-06-29 2018-08-15 Bedrock Capital Ltd Gospel L
US10901955B2 (en) * 2018-07-29 2021-01-26 International Business Machines Corporation Smart contract input mapping
US10896149B2 (en) * 2018-07-29 2021-01-19 International Business Machines Corporation Composition operators for smart contract
SG11202110011WA (en) * 2019-03-11 2021-10-28 Baton Systems Inc Analysis systems and methods
US10990879B2 (en) * 2019-09-06 2021-04-27 Digital Asset Capital, Inc. Graph expansion and outcome determination for graph-defined program states
US20210264423A1 (en) * 2020-02-21 2021-08-26 Mastercard International Incorporated Systems and methods for automatically initiating chargeback transactions for dual message transactions

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20170323006A1 (en) * 2015-11-29 2017-11-09 Vatbox, Ltd. System and method for providing analytics in real-time based on unstructured electronic documents
CN109600243A (zh) * 2017-09-30 2019-04-09 华为技术有限公司 数据分析方法和装置
CN108090755A (zh) * 2017-12-18 2018-05-29 深圳市快付通金融网络科技服务有限公司 计费模型定义方法、数据清算系统和计算机可读存储介质
CN110378699A (zh) * 2019-07-25 2019-10-25 中国工商银行股份有限公司 一种交易反欺诈方法、装置及系统
CN110415118A (zh) * 2019-07-29 2019-11-05 中国工商银行股份有限公司 处理方法及其装置、电子设备和介质
CN111402057A (zh) * 2020-03-31 2020-07-10 中国工商银行股份有限公司 交易报文匹配方法、装置、计算设备以及介质
CN112016967A (zh) * 2020-08-28 2020-12-01 中国银联股份有限公司 一种交易数据处理方法与装置

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