Information verification method and device, equipment, storage medium and program product
Patent Information
- Application Number
- CN202411629447.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-14
- Publication Date
- 2025-03-11
AI Technical Summary
In the prior art, the name consistency verification of the recipient and the issuing party of the payment is manually performed, which is relatively efficient and takes a long time.
By obtaining the identification of the payment issuer and the recipient, the confidence parameters are calculated. If the confidence parameters are greater than the preset threshold, it is determined that the two matches correctly, and the verification is automatically completed, and manual intervention is reduced.
It improves the efficiency of information verification, reduces the verification time, and does not require manual tedious verification, which significantly improves the automation level of the verification process.
Smart Images
Figure CN119599673A_ABST
Abstract
Description
Technical Field
[0001] The present application belongs to the field of data processing technology, and in particular, relates to an information verification method, device, equipment, storage medium and program product. Background Art
[0002] With the increase in communication time and the rapid expansion of revenue scale, the amount involved in transfer business is getting bigger and bigger.
[0003] When transferring money, you need to enter the information of the recipient and check whether there are any errors in the recipient and the sender. This proofreading method is a name consistency check.
[0004] In the exemplary technology, the consistency check between the payment recipient and the payment issuer is performed manually, which takes a long time to perform the manual check, resulting in low efficiency in information verification. Summary of the invention
[0005] Embodiments of the present application provide an information verification method, apparatus, device, storage medium, and program product to solve the problem of low information verification efficiency.
[0006] In a first aspect, an embodiment of the present application provides an information verification method, which is applied to an information verification device. The information verification method includes:
[0007] Acquire target payment information, and acquire a first identifier of a first payment recipient and a second identifier of a first payment issuer from the target payment information;
[0008] Determining a target confidence parameter according to the first identifier and the second identifier, wherein the target confidence parameter is used to indicate a degree of correctness of a match between the first payment recipient and the first payment issuer;
[0009] In response to the target confidence parameter being greater than a preset threshold, it is determined that the first payment recipient and the first payment issuer are correctly matched.
[0010] In one embodiment, the step of determining a target confidence parameter according to the first identifier and the second identifier includes:
[0011] Determine a common character that overlaps the first identifier and the second identifier;
[0012] A target confidence parameter is determined according to the common character, the first identifier, and the second identifier.
[0013] In another embodiment, the step of determining the confidence parameter according to the common character, the first identifier and the second identifier comprises:
[0014] determining a first ratio between the number of common characters and the number of characters of the first identification, and determining a second ratio between the number of common characters and the number of characters of the second identification;
[0015] A target confidence parameter is determined according to a larger value of the first ratio and the second ratio.
[0016] In another embodiment, the step of determining the target confidence parameter according to the larger value of the first ratio and the second ratio comprises:
[0017] In a relational database, a reference factor is obtained, wherein the reference factor includes at least one of a simplified identifier, a first relation parameter, and a target transaction frequency, wherein the simplified identifier is used to indicate a first identifier with set characters deleted and / or a second identifier with set characters deleted, the first relation parameter is used to indicate a transaction relationship between the first payment recipient and the first payment issuer, and the target transaction frequency is used to indicate a transaction frequency between the first payment recipient and the first payment issuer;
[0018] Determining a target value corresponding to the reference factor;
[0019] Performing weighted calculation on the target value corresponding to the reference factor and the weight corresponding to the reference factor to obtain a weighted score;
[0020] The target confidence parameter is determined based on the weighted score and a target ratio, wherein the target ratio is used to indicate a larger value between the first ratio and the second ratio.
[0021] In another embodiment, the reference factor includes a simplified identifier, and the step of determining the target value corresponding to the reference factor includes:
[0022] Comparing a first simplified identifier corresponding to the first identifier and a second simplified identifier corresponding to the second identifier;
[0023] In response to the first simplified identifier being the same as the second simplified identifier, determining a first preset value as a target value;
[0024] In response to the first simplified identifier being different from the second simplified identifier, a second preset value is determined as a target value, and the first preset value is greater than the second preset value.
[0025] In another embodiment, before the step of obtaining the reference factor in the relational database, the step further includes:
[0026] Acquire multiple historical payment information, and acquire a third identifier of a second payment recipient and a fourth identifier of a second payment issuer from the historical payment information;
[0027] In the third identifier and the fourth identifier, the set character is deleted to obtain a third simplified identifier corresponding to the third identifier and a fourth simplified identifier corresponding to the fourth identifier;
[0028] Establishing a second relationship parameter between the second payment recipient and the second payment issuer, and determining a historical transaction frequency between the second payment recipient and the second payment issuer according to the historical payment information;
[0029] The relational database is constructed according to the third brief identifier, the fourth brief identifier, the second relational parameter and the historical transaction frequency corresponding to each of the historical payment information.
[0030] In another embodiment, the step of establishing the second relationship parameter between the second payment recipient and the second payment issuer includes:
[0031] Determine a first character representing the geographic location in the third identifier, and determine a second character representing the geographic location in the fourth identifier;
[0032] In response to the first character matching the second character, an association relationship between the third identifier and the fourth identifier is established based on the first character and the second character to obtain the second relationship parameter.
[0033] In another embodiment, the step of determining a target confidence parameter according to the first identifier and the second identifier includes:
[0034] Determine whether to store the payment combination constructed by the first payment recipient and the first payment issuer in the relational database;
[0035] In response to the fact that the combination of items is not stored in the relational database, a target confidence parameter is determined according to the first identifier and the second identifier.
[0036] In another embodiment, after the step of determining whether the payment combination constructed by the first payment recipient and the first payment issuer is stored in the relational database, the step further includes:
[0037] In response to the relational database storing the payment combination, obtaining a historical transaction frequency between the first payment recipient and the first payment issuer and a historical confidence parameter associated with the payment combination;
[0038] The historical confidence parameter is corrected according to the historical transaction frequency to obtain the target confidence parameter.
[0039] In another embodiment, a recognition model is provided in the information verification device, and the recognition model is used to determine a target confidence parameter according to the first identifier and the second identifier.
[0040] In another embodiment, the specific training process of the recognition model includes:
[0041] Acquire multiple training samples, where the training samples are obtained based on the third identifier of the second payment recipient and the fourth identifier of the second payment issuer in the historical payment information;
[0042] The preset model is trained according to each of the training samples to obtain a recognition model.
[0043] In a second aspect, an embodiment of the present application provides an information verification determination device, including:
[0044] An acquisition module, used to acquire target payment information, and acquire a first identifier of a first payment recipient and a second identifier of a first payment issuer from the target payment information;
[0045] A first determination module, configured to determine a target confidence parameter according to the first identifier and the second identifier, wherein the target confidence parameter is used to indicate a correct degree of matching between the first payment recipient and the first payment issuer;
[0046] The second determination module is configured to determine that the first payment recipient and the first payment issuer are correctly matched in response to the target confidence parameter being greater than a preset threshold.
[0047] In a third aspect, an embodiment of the present application provides an information verification determination device, including: a processor and a memory storing computer program instructions;
[0048] When the processor executes the computer program instructions, the information verification method as described in one aspect is implemented.
[0049] In a fourth aspect, an embodiment of the present application provides a computer storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the information verification method of the first aspect is implemented.
[0050] In a fifth aspect, an embodiment of the present application provides a computer program product. When instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the information verification method of the first aspect.
[0051] The information verification method, apparatus, device, storage medium and program product provided in the embodiments of the present application determine a confidence parameter through the identifier of the payment issuer and the identifier of the payment recipient, and the confidence represents the degree of correct matching between the payment recipient and the payment issuer. If the confidence parameter is greater than a preset threshold, it can be determined that the payment issuer and the payment recipient are correctly matched, without the need for manual information verification, thereby reducing the verification time and improving the efficiency of information verification. BRIEF DESCRIPTION OF THE DRAWINGS
[0052] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.
[0053] Figure 1 It is a schematic diagram of the scenario involved in realizing the information verification method of this application;
[0054] Figure 2 It is a flowchart of the first embodiment of the information verification method of the present application;
[0055] Figure 3 It is a flowchart of the second embodiment of the information verification method of the present application;
[0056] Figure 4 It is a flowchart of the third embodiment of the information verification method of the present application;
[0057] Figure 5 It is a flowchart of the fourth embodiment of the information verification method of the present application;
[0058] Figure 6 It is a schematic diagram of the functional modules of the information verification and determination device provided in an embodiment of the present application;
[0059] Figure 7 It is a structural diagram of the information verification and determination device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0060] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.
[0061] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.
[0062] With the increase in communication time and the rapid expansion of revenue scale, the amount involved in transfer business is getting bigger and bigger.
[0063] When transferring money, you need to enter the information of the recipient and check whether there are any errors in the recipient and the sender. This proofreading method is a name consistency check.
[0064] The inventors of the present application have discovered that in the exemplary technology, the consistency check between the payment recipient and the payment issuer is performed manually, which takes a long time and results in low efficiency in information verification.
[0065] The inventor of the present application therefore came up with the idea that by using the identification of the payment issuer and the payment recipient, it can be automatically determined whether the payment issuer and the payment recipient are correctly matched, without the need for manual information verification, thus reducing the verification time and improving the efficiency of information verification.
[0066] The embodiments of the present application provide an information verification method, apparatus, device, storage medium and program product. The following first illustrates an example framework to which the information verification method provided by the embodiments of the present application can be applied.
[0067] like Figure 1 As shown, the information verification and determination device 100 obtains the target payment information, which can be sent by the user based on the terminal device 200. The information verification and determination device 100 obtains the first identifier of the payment recipient and the second identifier of the payment issuer from the target payment information, and determines the target confidence parameter that the payment recipient and the payment issuer match correctly based on the first identifier and the second identifier. If the target execution parameter is greater than the preset threshold, it can be determined that the payment recipient and the payment issuer match correctly, and the information verification device 100 can transfer the payment in the target payment information from the payment issuer's account to the payment recipient's account.
[0068] The following combination Figure 1 , the information verification method provided in the embodiment of the present application is introduced.
[0069] Figure 2 A flow chart of a first embodiment of the information verification method provided by the present application is shown.
[0070] like Figure 2 As shown, the information verification method includes:
[0071] Step S201, obtaining target payment information, and obtaining a first identifier of a first payment recipient and a second identifier of a first payment issuer from the target payment information.
[0072] In this embodiment, the execution subject is an information verification device. For the convenience of description, the device is used below to refer to the information verification device. The device can be a server, or a physical device or a virtual device with an information verification function. A virtual device is, for example, a cloud server, and a physical device is, for example, a computer, etc.
[0073] When the target user needs to repay the money, he will send payment information to the device through the terminal device. The payment information is defined as the target payment information. The target payment information includes the recipient of the money and the issuer of the money. The recipient of the money is defined as the first recipient of the money, and the issuer of the money is defined as the first issuer of the money. The target user can be an individual user, or a group or group consisting of multiple users. In addition, the target payment information also includes the second identifier of the first issuer of the money and the first identifier of the first recipient of the money. The first identifier can be the name of the recipient of the money, and the second identifier can be the name of the issuer of the money. The device obtains the first identifier and the second identifier from the target payment information.
[0074] Step S202: determining a target confidence parameter according to the first identifier and the second identifier, where the target confidence parameter is used to indicate the degree of correctness of the match between the first payment recipient and the first payment issuer.
[0075] After obtaining the first identifier and the second identifier, the device determines a confidence parameter based on the first identifier and the second identifier, and the confidence parameter is defined as a target confidence parameter. The target confidence parameter is used to indicate the degree of correct matching between the first payment recipient and the first payment issuer, and the larger the target confidence parameter, the higher the degree of correct matching between the first payment recipient and the first payment issuer, which can be a credibility degree, and the larger the target confidence parameter, the greater the credibility degree.
[0076] Exemplarily, the device stores a correspondence of money remittances, for example, a group engaged in type A needs a group of nature B to lend money, so type A and nature B have a correspondence. The device determines the type of business and group attributes (group attributes are properties, such as private, shared, etc.) engaged in by the group of the first payment recipient, and determines the type of business and group attributes engaged in by the group of the first payment issuer, and determines the combination parameters between the first payment recipient and the first payment issuer. For example, the type of the first payment issuer is C and the group attribute is 1, the type of the first payment recipient is D and the group attribute is 2, then the combination parameters include (C, D), (C, 2), (1, D) and (1, 2), and then determines whether the device stores a corresponding relationship matched by any of the four combination parameters. When the device stores a corresponding relationship matched by any combination parameter, the target confidence parameter is set to the first preset value; when the device does not store the corresponding relationship matched by each combination parameter, the target confidence parameter is set to the second preset value, the second preset value is less than the first preset value, and the first preset value is greater than the preset threshold and the second preset value is less than the preset threshold.
[0077] Step S203, in response to the target confidence parameter being greater than a preset threshold, determining that the first payment recipient and the first payment issuer are correctly matched.
[0078] When the target confidence parameter is greater than a preset threshold, it can be determined that the first payment recipient and the first payment issuer are matched correctly. When the first payment recipient and the first payment issuer are matched correctly, the remittance device is notified or the device is used to transfer the funds from the account of the first payment issuer to the account of the first payment recipient, and the funds are the funds required in the target payment information.
[0079] When the target execution parameter is less than or equal to the preset threshold, it is determined that the match between the first payment recipient and the first payment issuer is incorrect, and the target payment information is sent to the target terminal for manual review by the target terminal.
[0080] In this embodiment, the confidence parameter is determined by the identifier of the payment issuer and the identifier of the payment recipient, and the confidence represents the degree of correct matching between the payment recipient and the payment issuer. If the confidence parameter is greater than a preset threshold, it can be determined that the payment issuer and the payment recipient are correctly matched, without the need for manual verification of the information, which reduces the verification time and improves the efficiency of information verification.
[0081] Reference Figure 3 , Figure 3 The flowchart of the second embodiment of the information verification method of the present application is shown. Based on the first embodiment, step S203 includes:
[0082] Step S301, determining the common characters that overlap between the first identifier and the second identifier.
[0083] Step S302: determining a target confidence parameter according to the common character, the first identifier and the second identifier.
[0084] In this embodiment, the first identifier and the second identifier can be regarded as a string, and the string can be regarded as a set, that is, the first identifier and the second identifier can be regarded as two sets. When measuring the similarity of the two sets, the common sequence in the two sets can be used to calculate the similarity, and the common sequence can be the common characters overlapped by the first identifier and the second identifier. For example, the first identifier is abcdefr, and the second identifier is fhjjkjl. Both identifiers have f, and f is the common character of the two.
[0085] After determining the common character, the device can determine the target confidence parameter for matching between the first payment recipient and the payment issuer based on the common character, the first identifier, and the second identifier. Wherein A∩B represents the number of common characters, A represents the first identifier, B represents the second identifier, |A| can be the number of characters in the first identifier, and |B| represents the number of characters in the second identifier.
[0086] In this embodiment, considering the similarity between the identifiers of the parent group and the child group, the common characters between the first identifier and the second identifier are used to determine the target confidence parameters of the first payment recipient and the payment issuer.
[0087] Reference Figure 4 , Figure 4 The schematic diagram of the third embodiment of the information verification method provided by the present application is shown. Figure 3 In the illustrated embodiment, step S302 includes:
[0088] Step S401, determining a first ratio between the number of common characters and the number of characters of a first mark, and determining a second ratio between the number of common characters and the number of characters of a second mark.
[0089] Step S402: determining a target confidence parameter according to the larger value of the first ratio and the second ratio.
[0090] In this embodiment, the first identifier and the second identifier are used as denominators respectively to improve the similarity of qualified combinations, and the maximum similarity is removed for easy distinction. At the same time, an absolute value limit is imposed on the specific length to prevent identifiers with too small lengths from affecting the result value of the similarity.
[0091] To this end, the device first determines a first ratio between the number of common characters and the number of characters of the first mark, then determines a second ratio between the number of common characters and the number of characters of the second mark, and then determines the target confidence parameter based on the larger value of the first ratio and the second ratio.
[0092] For example, the target confidence parameter
[0093] In this embodiment, by using the larger value of the first ratio and the second ratio as the target confidence parameter, it can be found that the target confidence parameter is less affected by the suffixes of the first identifier and the second identifier (the words after the name are suffixes, such as "limited liability"), which can effectively increase the similarity of the related texts in the two identifiers. In actual application scenarios, there are many cases where the group's identifier has a suffix, so this embodiment is suitable for actual business scenarios.
[0094] It should be noted that the preset threshold is obtained through empirical values. Specifically, this embodiment is used to test multiple groups of samples, and the results are sampled and verified. It is found that when the threshold is 55, the harmful error is 1% (harmful error refers to an incorrect judgment that is judged to be correct), the harmless error is 2% (harmless error refers to an incorrect judgment that is judged to be wrong), and the total error is 3%, and the error rate is the smallest, so 55 is set as the preset threshold. It can be understood that based on the calculation of multiple groups of confidence parameters in this embodiment, multiple values are set, and the total error under the set value is calculated based on each confidence parameter and the set value, and the set value corresponding to the minimum total error is saved as the preset threshold.
[0095] Reference Figure 5 , Figure 5 A schematic diagram showing a fourth embodiment of the information verification method provided by the present application is shown. Figure 4 In the illustrated embodiment, step S403 includes:
[0096] Step S501, in a relational database, obtain a reference factor, the reference factor including at least one of a simplified identifier, a first relational parameter, and a target transaction frequency, the simplified identifier being used to indicate a first identifier for deleting set characters and / or a second identifier for deleting set characters, the first relational parameter being used to indicate a transaction relationship between a first payment recipient and a first payment issuer, and the target transaction frequency being used to indicate a transaction frequency between the first payment recipient and the first payment issuer.
[0097] In this embodiment, a variety of parameters are stored in the relational database, and these parameters can assist in calculating the confidence parameter. The device obtains a reference factor in the relational database, and the reference factor includes at least one of a simplified identifier, a first relational parameter, and a target transaction frequency. The simplified identifier is used to indicate the first identifier for deleting the set characters and / or the second identifier for deleting the set characters. The first relational parameter is used to indicate the transaction relationship between the first payment recipient and the first payment issuer, and the target transaction frequency is used to indicate the transaction frequency between the first payment recipient and the first payment issuer.
[0098] For example, the first identifier and the second identifier are company names. The company names are stripped of set words to obtain simplified identifiers. The set words are, for example, "limited liability company", "branch", etc. The first relationship parameter is, for example, the relationship that company A pays money to company B. The target transaction frequency is, for example, that company D and company C have had four transactions.
[0099] The reference factors acquired by the device are all matched by the first identifier or the second identifier. For example, if the relational database includes a brief identifier of the first identifier, the brief identifier of the first identifier is extracted as a reference factor; if the relational database includes a remittance relationship between the first payment recipient and the first payment issuer, data representing the remittance relationship is extracted from the relational database as a reference factor; in addition, the number of historical transactions between the first payment recipient and the first payment issuer can also be extracted from the relational database as the target transaction frequency.
[0100] Step S502, determining the target value corresponding to the reference factor.
[0101] Each reference factor has a corresponding numerical value, and the device determines the numerical value corresponding to each reference factor, which is defined as the target numerical value.
[0102] Exemplarily, when the reference factor includes a simplified identifier, the device compares the first simplified identifier corresponding to the first identifier with the second simplified identifier corresponding to the second identifier. If the first simplified identifier is the same as the second simplified identifier, the first preset value is determined as the target value; if the first simplified identifier is different from the second simplified identifier, the second preset value is determined as the target value, and the first preset value is greater than the second preset value. For example, the first preset value is 1, and the second preset value is 0. In addition, when the first identifier has the first simplified identifier and the second identifier does not have the second simplified identifier, the target value is the second preset value; or when the first identifier does not have the first simplified identifier and the second identifier has the second simplified identifier, the target value is also the second preset value.
[0103] In addition, when there is no relationship parameter between the first identifier and the second identifier in the relationship database, the target value corresponding to the first relationship parameter is the second preset value, if yes, the target value is the first preset value; when there is no transaction record of the first payment recipient and the first payment issuer in the relationship database, the target value corresponding to the target transaction frequency is the second preset value, if yes, the target value is the first preset value.
[0104] Step S503, performing weighted calculation on the target value corresponding to the reference factor and the weight corresponding to the reference factor to obtain a weighted score.
[0105] The device performs weighted calculation on the target values and weights corresponding to each reference factor to obtain a weighted score. For example, the weight of each reference factor is different, for example, the weight of the brief identifier is 0.2, the weight of the relationship parameter is 0.2, and the weight of the target transaction frequency is 0.8.
[0106] Step S504: determining a target confidence parameter according to the weighted score and the target ratio, where the target ratio is used to indicate a larger value between the first ratio and the second ratio.
[0107] After the weighted score is determined, a target confidence parameter is determined based on the weighted score and the target ratio, where the target ratio refers to the larger value of the first ratio and the second ratio. For example, the product of the weighted score and the target ratio can be used as the target confidence parameter.
[0108] In this embodiment, a reference factor is obtained from a relational database, so that the target confidence parameter between the first payment recipient and the first payment issuer is accurately determined based on the reference factor, the first ratio, and the second ratio.
[0109] In one example, before the device obtains reference factors in the concerned database, it needs to construct a relational database.
[0110] Exemplarily, the device obtains multiple historical payment information, and the historical payment information is the payment information of the payment that has been remitted. The device obtains the third identifier of the second payment recipient and the fourth identifier of the second payment issuer from the historical remittance information. The acquisition process of the third identifier and the fourth identifier is the same as the acquisition process of the first identifier and the second identifier, and will not be repeated here.
[0111] The device first deletes set characters from the third identifier and the third identifier. The set characters are, for example, stop words, such as "limited company", "joint-stock limited liability company" or other industry-specific words, such as "chemical industry", "daily necessities", etc. The third identifier can be deleted by deleting the set characters to obtain the third simplified identifier, and the fourth identifier can be deleted by deleting the set characters to obtain the fourth simplified identifier. Furthermore, aliases can be constructed for the third identifier and the fourth identifier, that is, the third identifier is converted into a nickname to obtain the third simplified identifier, and the fourth identifier is converted into a nickname to obtain the fourth simplified identifier. The alias conversion can be determined based on prior knowledge, that is, the alias of a group is extracted from the Internet, and then the identifier of this group is converted into an alias.
[0112] After obtaining the third simplified identifier and the fourth simplified identifier, the device establishes a second relationship parameter between the second payment recipient and the second payment issuer, and determines the historical transaction frequency between the second payment recipient and the second payment issuer based on the historical payment information, thereby building a relationship database based on the third simplified identifier, the fourth simplified identifier, the second relationship parameter and the historical transaction frequency corresponding to each historical payment information. The second relationship parameter can be an association relationship established between the third identifier and the fourth relationship. The second relationship parameter can also be established based on the geographical location. For example, the third identifier and the fourth identifier include characters representing the geographical location, such as "XX City". The device obtains the first character representing the geographical location from the third identifier, and determines the second character representing the geographical location from the fourth identifier; when the first character is the same as the second character, the area represented by the first character is located in the area represented by the second character, or the area represented by the second character is located in the area represented by the first character, it can be determined that the first character matches the second character, and the device establishes an association relationship between the third identifier and the fourth identifier based on the first character and the second character to obtain the second relationship parameter, that is, configures the association relationship between the two geographical locations and the two identifiers.
[0113] In this embodiment, the device can construct a relational database based on historical payment information, so as to accurately determine the consistency check of subsequent payment recipients and payment issuers based on the relational database.
[0114] In one embodiment, each time the device determines that the match between the payment recipient and the payment issuer is correct, the confidence parameters between the payment recipient and the payment issuer are saved in the relational database, and the confidence parameters are associated with the payment combination and stored. The payment combination refers to a set consisting of the identifier of the payment recipient and the identifier of the payment issuer. The confidence parameter associated with the payment combination is the confidence parameter most recently calculated by the device. After obtaining the first identifier and the second identifier, the device first determines whether the payment combination constructed by the first payment recipient and the first payment issuer is stored in the relational database, that is, checks whether there is an identifier combination consisting of the first identifier and the second identifier. If the payment combination is not stored in the relational database, the confidence parameters that correctly match between the first payment recipient and the first payment issuer are determined based on the first identifier and the second identifier, that is, the target confidence parameters are calculated in real time through the above embodiment. If a payment combination is stored in a relational database, the historical confidence parameters associated with the payment combination are obtained, and the historical transaction frequency between the first payment recipient and the first payment issuer is obtained. The historical confidence parameters are corrected based on the historical transaction frequency to obtain the target confidence parameters. The greater the historical transaction frequency, the greater the corrected target confidence parameter, and the target confidence parameter is greater than the historical confidence parameter.
[0115] In this embodiment, the target confidence parameters of the first payment recipient and the first payment issuer are calculated using historical confidence parameters, thereby quickly determining the correct matching confidence parameters between the first payment recipient and the first payment issuer, thereby improving information verification efficiency.
[0116] In one embodiment, a recognition model is provided in the information verification device, and the recognition model is used to determine the target confidence parameter according to the first identifier and the second identifier, that is, the first identifier and the second identifier are input into the recognition model, and the recognition model outputs the target confidence parameter.
[0117] The specific training process of the recognition model includes: obtaining multiple training samples, the training samples are obtained based on the third identifier of the second payment recipient and the fourth identifier of the second payment issuer in the historical payment information; training the preset model according to each training sample to obtain the recognition model. It is understandable that the training samples can be constructed using data in the relational database, so as to obtain the recognition model based on the training sample training. In some samples, the third identifier and the fourth identifier are included; in other samples, the third identifier, the fourth identifier and the second relationship parameter are included; in some other samples, the third identifier, the fourth identifier, the second relationship parameter and the historical transaction frequency are included.
[0118] In this embodiment, the correct matching confidence parameters between the first payment recipient and the first payment issuer can be quickly determined through the recognition model, thereby improving the efficiency of information verification.
[0119] like Figure 6 As shown, the embodiment of the present application further provides an information verification determination device 600, and the information verification determination device 600 includes:
[0120] An acquisition module 610 is used to acquire target payment information, and acquire a first identifier of a first payment recipient and a second identifier of a first payment issuer from the target payment information;
[0121] A first determination module 620, configured to determine a target confidence parameter according to the first identifier and the second identifier, wherein the target confidence parameter is used to indicate a correct degree of matching between the first payment recipient and the first payment issuer;
[0122] The second determination module 630 is used to determine that the match between the first payment recipient and the first payment issuer is correct in response to the target confidence parameter being greater than a preset threshold.
[0123] In one embodiment, the information verification determination device 600 is further used for:
[0124] Determining common characters that overlap between the first identifier and the second identifier;
[0125] A target confidence parameter is determined according to the common character, the first identifier, and the second identifier.
[0126] In one embodiment, the information verification determination device 600 is further used for:
[0127] determining a first ratio between the number of common characters and the number of characters of the first identification, and determining a second ratio between the number of common characters and the number of characters of the second identification;
[0128] A target confidence parameter is determined based on a larger value of the first ratio and the second ratio.
[0129] In one embodiment, the information verification determination device 600 is further used for:
[0130] In a relational database, a reference factor is obtained, where the reference factor includes at least one of a simplified identifier, a first relation parameter, and a target transaction frequency, wherein the simplified identifier is used to indicate a first identifier for deleting set characters and / or a second identifier for deleting set characters, the first relation parameter is used to indicate a transaction relationship between a first payment recipient and a first payment issuer, and the target transaction frequency is used to indicate a transaction frequency between the first payment recipient and the first payment issuer;
[0131] Determine the target value corresponding to the reference factor;
[0132] The target value corresponding to the reference factor and the weight corresponding to the reference factor are weighted to obtain a weighted score;
[0133] A target confidence parameter is determined based on the weighted score and the target ratio, where the target ratio is used to indicate a larger value between the first ratio and the second ratio.
[0134] In one embodiment, the information verification determination device 600 is further used for:
[0135] Comparing a first simplified identifier corresponding to the first identifier and a second simplified identifier corresponding to the second identifier;
[0136] In response to the first simplified identifier being the same as the second simplified identifier, determining the first preset value as the target value;
[0137] In response to the first simplified identifier being different from the second simplified identifier, the second preset value is determined as the target value, and the first preset value is greater than the second preset value.
[0138] In one embodiment, the information verification determination device 600 is further used for:
[0139] Acquire multiple historical payment information, and acquire the third identifier of the second payment recipient and the fourth identifier of the second payment issuer from the historical payment information;
[0140] In the third identifier and the fourth identifier, the setting character is deleted to obtain a third simplified identifier corresponding to the third identifier and a fourth simplified identifier corresponding to the fourth identifier;
[0141] Establishing a second relationship parameter between the second payment recipient and the second payment issuer, and determining a historical transaction frequency between the second payment recipient and the second payment issuer based on historical payment information;
[0142] A relational database is constructed according to the third brief identifier, the fourth brief identifier, the second relational parameter and the historical transaction frequency corresponding to each historical payment information.
[0143] In one embodiment, the information verification determination device 600 is further used for:
[0144] Determining a first character representing the geographic location in the third identifier, and determining a second character representing the geographic location in the fourth identifier;
[0145] In response to the first character matching the second character, an association relationship between the third identifier and the fourth identifier is established based on the first character and the second character to obtain a second relationship parameter.
[0146] In one embodiment, the information verification determination device 600 is further used for:
[0147] Determine whether to store the payment combination constructed by the first payment recipient and the first payment issuer in the relational database;
[0148] In response to the fact that the combination of items is not stored in the relational database, a target confidence parameter is determined according to the first identifier and the second identifier.
[0149] In one embodiment, the information verification determination device 600 is further used for:
[0150] In response to the relational database storing the payment combination, obtaining the historical transaction frequency between the first payment recipient and the first payment issuer and the historical confidence parameter associated with the payment combination;
[0151] The historical confidence parameters are modified according to the historical transaction frequency to obtain the target confidence parameters.
[0152] In one embodiment, a recognition model is provided in the information verification device, and the recognition model is used to determine the target confidence parameter according to the first identifier and the second identifier.
[0153] In one embodiment, the information verification determination device 600 is further used for:
[0154] Acquire multiple training samples, where the training samples are obtained based on the third identifier of the second payment recipient and the fourth identifier of the second payment issuer in the historical payment information;
[0155] The preset model is trained according to each training sample to obtain a recognition model.
[0156] Figure 7 A schematic diagram of the hardware structure of the information verification and determination device provided in an embodiment of the present application is shown.
[0157] The information verification determination device may include a processor 701 and a memory 702 storing computer program instructions.
[0158] Specifically, the processor 701 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.
[0159] The memory 702 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 702 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 702 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 702 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 702 is a non-volatile solid-state memory.
[0160] In certain embodiments, the memory 702 may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage media device, an optical storage media device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.
[0161] The processor 701 implements any one of the information verification methods in the above embodiments by reading and executing computer program instructions stored in the memory 702 .
[0162] In one example, the information verification determination device may further include a communication interface 703 and a bus 710. Figure 7 As shown, the processor 701, the memory 702, and the communication interface 703 are connected via a bus 710 and communicate with each other.
[0163] The communication interface 703 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.
[0164] Bus 710 includes hardware, software or both, and the parts of online data flow billing equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front-end bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 710 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the present application considers any suitable bus or interconnection.
[0165] In addition, in combination with the terminal device movement and information verification method in the above embodiments, the present application embodiment can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by the processor, any one of the information verification methods in the above embodiments is implemented.
[0166] An embodiment of the present application also provides a computer program product, including a computer program, which implements any one of the information verification methods in the above embodiments when the computer program is processed and executed.
[0167] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.
[0168] The functional blocks shown in the above block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.
[0169] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.
[0170] Aspects of the present disclosure are described above with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable terminal equipment motion device to produce a machine so that these instructions executed by the processor of the computer or other programmable terminal equipment motion device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.
[0171] The above are only specific implementation methods of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.
Claims
1. An information verification method, characterized in that: Applied to an information verification device, the information verification method comprises: Acquire target payment information, and acquire a first identifier of a first payment recipient and a second identifier of a first payment issuer from the target payment information; Determining a target confidence parameter according to the first identifier and the second identifier, wherein the target confidence parameter is used to indicate a degree of correctness of a match between the first payment recipient and the first payment issuer; In response to the target confidence parameter being greater than a preset threshold, it is determined that the first payment recipient and the first payment issuer are correctly matched.
2. The information verification method according to claim 1, characterized in that: The step of determining a target confidence parameter according to the first identifier and the second identifier includes: Determine a common character that overlaps the first identifier and the second identifier; A target confidence parameter is determined according to the common character, the first identifier, and the second identifier.
3. The information verification method according to claim 2, characterized in that: The step of determining the confidence parameter according to the common character, the first identifier and the second identifier comprises: determining a first ratio between the number of common characters and the number of characters of the first identification, and determining a second ratio between the number of common characters and the number of characters of the second identification; A target confidence parameter is determined according to a larger value of the first ratio and the second ratio.
4. The information verification method according to claim 3, characterized in that: The step of determining a target confidence parameter according to a larger value of the first ratio and the second ratio comprises: In a relational database, a reference factor is obtained, wherein the reference factor includes at least one of a simplified identifier, a first relation parameter, and a target transaction frequency, wherein the simplified identifier is used to indicate a first identifier with set characters deleted and / or a second identifier with set characters deleted, the first relation parameter is used to indicate a transaction relationship between the first payment recipient and the first payment issuer, and the target transaction frequency is used to indicate a transaction frequency between the first payment recipient and the first payment issuer; Determining a target value corresponding to the reference factor; Performing weighted calculation on the target value corresponding to the reference factor and the weight corresponding to the reference factor to obtain a weighted score; The target confidence parameter is determined based on the weighted score and a target ratio, wherein the target ratio is used to indicate a larger value between the first ratio and the second ratio.
5. The information verification method according to claim 4, characterized in that: The reference factor includes a brief identifier, and the step of determining a target value corresponding to the reference factor includes: Comparing a first simplified identifier corresponding to the first identifier and a second simplified identifier corresponding to the second identifier; In response to the first simplified identifier being the same as the second simplified identifier, determining a first preset value as a target value; In response to the first simplified identifier being different from the second simplified identifier, a second preset value is determined as a target value, and the first preset value is greater than the second preset value.
6. The information verification method according to claim 4, characterized in that: Before the step of obtaining the reference factor in the relational database, the following steps are also included: Acquire multiple historical payment information, and acquire a third identifier of a second payment recipient and a fourth identifier of a second payment issuer from the historical payment information; In the third identifier and the fourth identifier, the set character is deleted to obtain a third simplified identifier corresponding to the third identifier and a fourth simplified identifier corresponding to the fourth identifier; Establishing a second relationship parameter between the second payment recipient and the second payment issuer, and determining a historical transaction frequency between the second payment recipient and the second payment issuer according to the historical payment information; The relational database is constructed according to the third brief identifier, the fourth brief identifier, the second relational parameter and the historical transaction frequency corresponding to each of the historical payment information.
7. The information verification method according to claim 6, characterized in that: The step of establishing the second relationship parameter between the second payment recipient and the second payment issuer comprises: Determine a first character representing the geographic location in the third identifier, and determine a second character representing the geographic location in the fourth identifier; In response to the first character matching the second character, an association relationship between the third identifier and the fourth identifier is established based on the first character and the second character to obtain the second relationship parameter.
8. The information verification method according to claim 1, characterized in that: The step of determining a target confidence parameter according to the first identifier and the second identifier includes: Determine whether to store the payment combination constructed by the first payment recipient and the first payment issuer in the relational database; In response to the fact that the combination of items is not stored in the relational database, a target confidence parameter is determined according to the first identifier and the second identifier.
9. The information verification method according to claim 8, characterized in that: After the step of determining whether the payment combination constructed by the first payment recipient and the first payment issuer is stored in the relational database, the method further includes: In response to the relational database storing the payment combination, obtaining a historical transaction frequency between the first payment recipient and the first payment issuer and a historical confidence parameter associated with the payment combination; The historical confidence parameter is corrected according to the historical transaction frequency to obtain the target confidence parameter.
10. The information verification method according to claim 1, characterized in that: The information verification device is provided with a recognition model, and the recognition model is used to determine a target confidence parameter according to the first identifier and the second identifier.
11. The information verification method according to claim 10, characterized in that: The specific training process of the recognition model includes: Acquire multiple training samples, where the training samples are obtained based on the third identifier of the second payment recipient and the fourth identifier of the second payment issuer in the historical payment information; The preset model is trained according to each of the training samples to obtain a recognition model.
12. An information verification and determination device, characterized in that: include: An acquisition module, used to acquire target payment information, and acquire a first identifier of a first payment recipient and a second identifier of a first payment issuer from the target payment information; A first determination module, configured to determine a target confidence parameter according to the first identifier and the second identifier, wherein the target confidence parameter is used to indicate a correct degree of matching between the first payment recipient and the first payment issuer; The second determination module is configured to determine that the first payment recipient and the first payment issuer are correctly matched in response to the target confidence parameter being greater than a preset threshold.
13. An information verification and determination device, characterized in that: include: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the information verification method as described in any one of claims 1-11 is implemented.
14. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the information verification method according to any one of claims 1 to 11 is implemented.
15. A computer program product, characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device is enabled to execute the information verification method as described in any one of claims 1 to 11.