Payment method and system

Abstract

The present invention discloses a payment method and system, relating to the financial field. The method includes: when a transaction is carried out on the client side, if the signal is poor, establishing a wireless communication connection with the device of the counterparty; collecting the biometric data of the customer, encrypting the feature data with the public key pre-distributed by the bank server to the client side, and sending it to the bank server through the device of the counterparty; the server determines the biometric authentication threshold of the customer based on the counterparty and decrypts the encrypted feature data with the corresponding private key to obtain the corresponding biometric data; performing feature recognition on the obtained feature data with the biometric authentication threshold, and encrypting the recognition result with the corresponding private key and sending it to the client side through the device of the counterparty; the client side decrypts the recognition result with the stored public key and determines whether to support the transaction between the customer and the counterparty according to the recognition result. The present invention can make payments safely and conveniently when the signal of the client side is poor or there is no signal.

Description

Technical Field

[0001] The present invention relates to the field of financial technology, and particularly to a payment method and system. Background Art

[0002] This section aims to provide background or context for the embodiments of the present invention described in the claims. The description herein is not admitted to be prior art merely because it is included in this section.

[0003] Currently, when a customer makes a payment, the bank's back-end server must verify the customer's identity information, such as face or password input. When the signal of the customer's terminal is poor or there is no signal, the customer cannot make a payment. Summary of the Invention

[0004] Embodiments of the present invention provide a payment method for securely and conveniently making a payment when the signal of the client is poor or there is no signal. The method includes:

[0005] When a transaction is performed on the client, if the signal of the client is poor, the client establishes a wireless communication connection with the device of the counterparty; collects the biometric data of the customer, encrypts the biometric data with the public key pre-distributed by the bank server to the client, and sends the encrypted biometric data to the device of the counterparty;

[0006] The device of the counterparty sends the encrypted biometric data to the bank server;

[0007] The bank server determines the biometric authentication threshold of the customer based on the counterparty, decrypts the encrypted biometric data with the corresponding private key to obtain the corresponding biometric data; performs biometric recognition on the obtained biometric data with the biometric authentication threshold, and encrypts the recognition result with the corresponding private key to obtain the encrypted recognition result; sends the encrypted recognition result to the device of the counterparty;

[0008] The device of the counterparty sends the encrypted recognition result to the client;

[0009] The client decrypts the encrypted recognition result with the stored public key to obtain the decrypted recognition result, and determines whether to support the transaction between the customer and the counterparty based on the decrypted recognition result.

[0010] Embodiments of the present invention further provide a payment system for securely and conveniently making a payment when the signal of the client is poor or there is no signal. The system includes:

[0011] A client, which is used to establish a wireless communication connection with the device of the counterparty if the signal is poor during a transaction; collect the biometric data of the customer, encrypt the biometric data with the public key pre-distributed by the bank server to the client, and send the encrypted biometric data to the device of the counterparty; decrypt the encrypted recognition result with the stored public key to obtain the decrypted recognition result, and determine whether to support the transaction between the customer and the counterparty based on the decrypted recognition result.

[0012] The device of the counterparty is used to send the encrypted biometric data to the bank server; the device of the counterparty sends the encrypted recognition result to the client.

[0013] The bank server is used to determine the biometric authentication threshold of the customer based on the counterparty, and decrypt the encrypted biometric data with the corresponding private key to obtain the corresponding biometric data; perform biometric recognition on the obtained biometric data with the biometric authentication threshold, and encrypt the recognition result with the corresponding private key to obtain the encrypted recognition result; send the encrypted recognition result to the device of the counterparty.

[0014] An embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the above payment method is implemented.

[0015] An embodiment of the present invention further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above payment method is implemented.

[0016] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the above payment method is implemented.

[0017] In an embodiment of the present invention, a payment solution is provided. When a transaction is carried out on a client, if the signal of the client is poor, a wireless communication connection is established between the client and the device of the counterparty. The biometric data of the customer is collected, and the biometric data is encrypted using the public key pre-distributed by the bank server to the client, and the encrypted biometric data is sent to the device of the counterparty. The device of the counterparty sends the encrypted biometric data to the bank server. The bank server determines the biometric authentication threshold of the customer based on the counterparty, and decrypts the encrypted biometric data using the corresponding private key to obtain the corresponding biometric data. The obtained biometric data is subjected to biometric recognition using the biometric authentication threshold, and the recognition result is encrypted using the corresponding private key to obtain the encrypted recognition result. The encrypted recognition result is sent to the device of the counterparty. The device of the counterparty sends the encrypted recognition result to the client. The client decrypts the encrypted recognition result using the stored public key to obtain the decrypted recognition result, and determines whether to support the transaction between the customer and the counterparty based on the decrypted recognition result, so as to achieve safe and convenient payment when the signal of the client is poor or there is no signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings. In the drawings:

[0019] Figure 1 It is a schematic flowchart of the payment method in the embodiment of the present invention;

[0020] Figure 2 It is a schematic flowchart of the bank server in the embodiment of the present invention determining the biometric authentication threshold of the customer based on the counterparty;

[0021] Figure 3 It is a schematic flowchart of storing the corresponding relationship between the biometric authentication threshold and the risk index of each reference merchant on the bank server in the embodiment of the present invention;

[0022] Figure 4 It is a schematic flowchart of determining the similar reference merchant of the counterparty according to the customer category vector in the embodiment of the present invention;

[0023] Figure 5 It is that the bank server in the embodiment of the present invention obtains the historical transaction data of the counterparty to determine the customer category vector corresponding to the counterparty;

[0024] Figure 6It is a schematic structural diagram of the payment system in the embodiments of the present invention. Detailed implementation manners

[0025] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer and more understandable, the following further describes the embodiments of the present invention in detail with reference to the accompanying drawings. Herein, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but not to limit the present invention.

[0026] Figure 1 It is a schematic flowchart of the payment method in the embodiments of the present invention. As Figure 1 shown, the method includes the following steps:

[0027] Step 101: When a transaction is performed on the client, if the client signal is poor, the client establishes a wireless communication connection with the device of the counterparty; collects the biometric data of the customer, and encrypts the biometric data with the public key pre-distributed by the bank server to the client, and sends the encrypted biometric data to the device of the counterparty;

[0028] Step 102: The device of the counterparty sends the encrypted biometric data to the bank server;

[0029] Step 103: The bank server determines the biometric authentication threshold of the customer based on the counterparty, and decrypts the encrypted biometric data with the corresponding private key to obtain the corresponding biometric data; performs biometric recognition on the obtained biometric data with the biometric authentication threshold, and encrypts the recognition result with the corresponding private key to obtain the encrypted recognition result; sends the encrypted recognition result to the device of the counterparty;

[0030] Step 104: The device of the counterparty sends the encrypted recognition result to the client;

[0031] Step 105: The client decrypts the encrypted recognition result with the stored public key to obtain the decrypted recognition result, and determines whether to support the transaction between the customer and the counterparty based on the decrypted recognition result.

[0032] The payment method provided by the embodiments of the present invention, when working: when a transaction is carried out on the client side, if the signal of the client side is poor, a wireless communication connection is established between the client side and the device of the counterparty of the transaction; the biometric data of the customer is collected, and the biometric data is encrypted with the public key pre-distributed by the bank server to the client side, and the encrypted biometric data is sent to the device of the counterparty of the transaction; the device of the counterparty of the transaction sends the encrypted biometric data to the bank server; the bank server determines the biometric authentication threshold of the customer based on the counterparty of the transaction, and decrypts the encrypted biometric data with the corresponding private key to obtain the corresponding biometric data; the obtained biometric data is subjected to biometric recognition with the biometric authentication threshold, and the recognition result is encrypted with the corresponding private key to obtain the encrypted recognition result; the encrypted recognition result is sent to the device of the counterparty of the transaction; the device of the counterparty of the transaction sends the encrypted recognition result to the client side; the client side decrypts the encrypted recognition result with the stored public key to obtain the decrypted recognition result, and determines whether to support the transaction between the customer and the counterparty of the transaction according to the decrypted recognition result, which can realize safe and convenient payment when the signal of the client side is poor or there is no signal. The following is a detailed introduction.

[0033] Specifically, the client mentioned in the embodiments of the present invention may be the customer's mobile phone, PAD, bracelet, etc.

[0034] In one embodiment, as Figure 2 shown, the bank server determining the biometric authentication threshold of the customer based on the counterparty of the transaction may include:

[0035] Step 201: The bank server obtains the historical transaction data of the counterparty of the transaction and determines the customer category vector corresponding to the counterparty of the transaction;

[0036] Step 202: According to the customer category vector, determine the similar reference merchants of the counterparty of the transaction;

[0037] Step 203: Determine the customer category to which the customer belongs, and based on the transaction data of the customer category, determine the risk index corresponding to the customer;

[0038] Step 204: According to the corresponding relationship between the biometric authentication threshold and the risk index of the similar reference merchant pre-stored in the bank database, and the risk index corresponding to the customer, determine the biometric authentication threshold of the customer.

[0039] In one embodiment, based on the transaction data of the customer category, determining the risk index corresponding to the customer may include:

[0040] Screen out the transaction data within the time period range A from the transaction data of the customer category;

[0041] For each day within the time period range A, determine the proportion of risky transaction data in the transaction data corresponding to that day as the risk indicator sample corresponding to the customer;

[0042] Based on the risk indicator sample corresponding to the customer, determine the number and variance σ of the risk indicator sample;

[0043] Determine whether the number n is greater than or equal to the first threshold;

[0044] If the number n is greater than or equal to the first threshold, then determine the risk indicator corresponding to the customer as the mean value of the risk indicator sample corresponding to the customer;

[0045] If the number n is less than the first threshold, then select a time period range B with the number of days included greater than the first threshold, and filter out the transaction data within the time period range B from the transaction data of the customer category; for each day within the time period range B, determine the proportion of risky transaction data in the transaction data corresponding to that day as the risk indicator sample corresponding to the customer; determine the risk indicator corresponding to the customer as the mean value of the risk indicator sample corresponding to the customer.

[0046] Among them, the first threshold can be determined as: ξ is the set index error threshold, and P is the upper bound of the probability that the index error is greater than ξ.

[0047] In specific implementation, the above implementation manner of determining the biometric authentication threshold of the customer can ensure the security of the customer's payment using the merchant device in the absence of a network.

[0048] In one embodiment, as Figure 3 shown, the above payment method may further include storing the correspondence between the biometric authentication threshold and the risk indicator of each reference merchant on the bank server according to the following method:

[0049] Step 301: Obtain the transaction data of the merchants within the predetermined area, and select multiple reference merchants;

[0050] Step 302: Cluster the reference merchants within the predetermined area based on the transaction data of the reference merchants within the predetermined area to obtain multiple merchant subsets;

[0051] Step 303: For each merchant subset, based on the biometric data of the merchant subset, determine the correspondence between the biometric authentication threshold and the risk indicator corresponding to the merchant subset;

[0052] Step 304: For each reference merchant, determine the corresponding relationship between the biometric authentication threshold and the risk indicator of the merchant subset to which the reference merchant belongs as the corresponding relationship between the biometric authentication threshold and the risk indicator of the reference merchant; that is, for each biometric authentication threshold, when assuming that the biometric recognition threshold is this biometric authentication threshold, it is the proportion of risk biometric data in the biometric data of the merchant subset.

[0053] Step 305: Store the corresponding relationship between the biometric authentication threshold and the risk indicator of each reference merchant on the bank server.

[0054] In specific implementation, the above implementation manner of storing the corresponding relationship between the biometric authentication threshold and the risk indicator of each reference merchant on the bank server further improves the security of payment.

[0055] In one embodiment, clustering the reference merchants in a predetermined area based on the transaction data of the reference merchants in the predetermined area to obtain multiple merchant subsets may include:

[0056] Determine the number of customers belonging to each customer category in the customer set corresponding to the transaction data of each merchant according to the transaction data of each merchant;

[0057] Determine the customer category vector corresponding to the merchant, where each component corresponds to each customer category one by one, and the value of each component is equal to the number of customers belonging to the customer category corresponding to this component in the customer set corresponding to the transaction data of the merchant;

[0058] Determine the distance function of the merchant, where the independent variable of the distance function is any two merchants in the predetermined area, and the corresponding function value is: where and are respectively the values of the i-th component of the customer category vectors of the two merchants, and l is the number of customer categories;

[0059] Cluster the merchants in the predetermined area according to the distance function of the merchant to obtain multiple merchant subsets.

[0060] In one embodiment, select K-means to cluster the merchants in the predetermined area according to the distance function of the merchant to obtain multiple merchant subsets. It is also possible to select the learning vector quantization algorithm to cluster the merchants in the predetermined area with the risk level as the category identifier to obtain multiple merchant subsets.

[0061] In one embodiment, clustering the merchants in the predetermined area according to the distance function of the merchant to obtain multiple merchant subsets may include:

[0062] Select multiple merchants within a predetermined area as merchant subset centers, where each merchant subset center corresponds to a merchant subset. Initially, each merchant subset only contains the corresponding merchant subset center;

[0063] Repeat the following steps for each merchant and each merchant subset until the change value of the customer category vector of all merchant subset centers is less than the change threshold, thereby obtaining multiple merchant subsets:

[0064] For each merchant, perform the following three steps:

[0065] For each merchant subset center, calculate the distance between the merchant subset center and the merchant according to the distance function of the merchant, and determine this distance as the distance corresponding to the merchant subset center;

[0066] Select multiple merchant subset centers with the same risk level as the merchant from all merchant subset centers. Determine the minimum value among the multiple distances corresponding to the selected merchant subset centers as the first distance of the merchant, and determine the merchant subset corresponding to the merchant subset center corresponding to this minimum value as the merchant subset corresponding to the merchant; determine the minimum value among the multiple distances corresponding to the unselected merchant subset centers as the second distance of the merchant;

[0067] If the first distance corresponding to the merchant is less than or equal to the second distance corresponding to the merchant, or the absolute value of the difference between the first distance corresponding to the merchant and the second distance corresponding to the merchant is less than the specified threshold, then classify the merchant into the merchant subset corresponding to the merchant; otherwise, create a new merchant subset center based on the merchant. The newly created merchant subset center corresponds to a new merchant subset, and the initial element of the new merchant subset only contains the merchant subset center;

[0068] For each merchant subset, perform the following steps:

[0069] Update the customer category vector and risk level of the merchant subset center corresponding to the merchant subset according to the customer category vectors and risk levels of all merchants included in the merchant subset. Specifically, update the customer category vector of the merchant subset center corresponding to the merchant subset to the mean value of the customer category vectors of all merchants included in the merchant subset; update the risk level of the merchant subset center corresponding to the merchant subset to the value with the largest quantity among all values of the risk levels of all merchants included in the merchant subset.

[0070] In specific implementation, risk information is an important factor for a customer (or merchant) to conduct transactions. That is to say, the transaction characteristics of different types of merchants are definitely different. The above implementation method for obtaining multiple merchant subsets can ensure that the transaction characteristics of the transactions assigned to the same merchant subset are similar, so as to ensure the accuracy of the corresponding relationship between the biometric authentication threshold and the risk indicator corresponding to the obtained merchant subset.

[0071] In one embodiment, as Figure 4 shown, determining a similar reference merchant for the counterparty according to the customer category vector may include:

[0072] Step 401: Determine the partial order of the reference merchants according to the customer category vector. Among them, for any two reference merchants, this partial order can be used to determine whether the first reference merchant among the two reference merchants is better than the second reference merchant;

[0073] Step 402: Determine the maximum reference merchants of all reference merchants according to the partial order of the reference merchants. Among them, the maximum reference merchant is the maximum element of this partial order;

[0074] Step 403: Determine the similar reference merchant for the counterparty according to the maximum reference merchant.

[0075] In specific implementation, the above implementation method for determining the similar reference merchant for the counterparty can find a reference merchant that has great similarity with the counterparty in some aspects by using the partial order. Compared with the extreme value method (minimum value or maximum value), the information of the similar reference merchant obtained by the partial order method is more comprehensive, while the extreme value method will lose some information.

[0076] In one embodiment, determining the partial order of the reference merchants according to the customer category vector may include:

[0077] For any reference merchant, determine the vector difference between the customer category vector of the counterparty and the customer category vector of this reference merchant, and determine the absolute value of this vector difference as the gap vector corresponding to this reference merchant;

[0078] For any two reference merchants, calculate the difference between the gap vector corresponding to the first reference merchant among the two reference merchants and the gap vector corresponding to the second reference merchant among the two reference merchants. If each component of this difference is less than or equal to 0, then determine that the first reference merchant is better than the second reference merchant.

[0079] The maximum element of the partial order is an element in the set corresponding to the partial order, and there is no other element better than this maximum element.

[0080] When the number of reference merchants is small, the maximum reference merchants can be directly determined according to the definition of the maximum element. When the number of parameter merchants is relatively large, there will be problems of complex and redundant calculations in directly determining the maximum reference merchants according to the definition.

[0081] In one embodiment, determining the maximum reference merchants of all reference merchants according to the partial order of the reference merchants may include:

[0082] 1. Initialize the partial order maximum value corresponding to each reference merchant as undetermined, and initialize the partial order comparison value corresponding to each reference merchant as yes;

[0083] 2. For each reference merchant of all the reference merchants in turn, if the partial order maximum value corresponding to the reference merchant is undetermined, select multiple other reference merchants whose corresponding partial order comparison values are yes from all the other reference merchants except the reference merchant among all the reference merchants, then set the reference merchants to be compared corresponding to the reference merchant as the selected multiple other reference merchants, and then perform the following step 3; if the partial order maximum value corresponding to the reference merchant is not undetermined, continue to perform step 2 on the next reference merchant;

[0084] 3. Select each reference merchant to be compared corresponding to the reference merchant in turn, and confirm whether the reference merchant to be compared is superior to the reference merchant; if the reference merchant to be compared is superior to the reference merchant, set the partial order maximum value corresponding to the reference merchant as no, and then continue to perform the above step 2 on the next reference merchant; if the reference merchant is superior to the reference merchant to be compared, set the partial order maximum value corresponding to the reference merchant to be compared as no, and determine the reference merchant to be compared as the secondary reference merchant of the reference merchant; otherwise, the partial order maximum value corresponding to the reference merchant and the partial order maximum value corresponding to the reference merchant to be compared remain unchanged;

[0085] 4. If it is confirmed that all the reference merchants to be compared of the reference merchant are not superior to the reference merchant (that is, after sequentially comparing the reference merchant and each corresponding reference merchant to be compared, the partial order maximum value corresponding to the reference merchant is still undetermined), then determine the reference merchant as the maximum reference merchant among all the reference merchants, and update the partial order comparison value of each secondary reference merchant of the maximum reference merchant to no;

[0086] 5. Then continue to perform step 2 on the next reference merchant until the above steps are completed for all reference merchants.

[0087] In one embodiment, as Figure 5 shown, the bank server obtains the historical transaction data of the counterparty and determines the customer category vector corresponding to the counterparty, which may include:

[0088] Step 501: Determine the quantities belonging to each customer category in the customer set corresponding to the historical transaction data of the counterparty based on the historical transaction data of the counterparty.

[0089] Step 502: Determine the customer category vector corresponding to the merchant, where each component corresponds to each customer category one by one, and the value of each component is equal to the quantity belonging to the customer category corresponding to the component in the customer set corresponding to the historical transaction data of the counterparty.

[0090] To facilitate understanding of how the present invention is implemented, an example is given below for illustration.

[0091] The application scenario of the embodiment of the present invention can be: The customer's mobile phone network is poor or there is no network, and then the customer's bracelet and mobile phone connect to the bank's back-end server through the merchant's terminal (such as a mobile terminal, a pos machine) to complete a transaction, where the bracelet is used to collect the customer's vein information, and the mobile phone is used to calculate the hash value of the vein information.

[0092] The specific data routing can be: The customer bracelet connects to the customer's mobile phone and connects to the bank back-end server through the customer's mobile phone (when the signal is good). When the signal is bad, the customer bracelet sends the transaction data to the bank server through the merchant node. For example, the customer buys clothes from the merchant and then completes the payment transaction with the help of the merchant's terminal. It can also be to connect to the merchant's terminal to buy financial products.

[0093] At this time, the merchant's terminal is an insecure factor and various risks may exist, such as the merchant intercepting the customer's account password information, etc. At this time, the method of using a hash function + asymmetric secret key + vein information can be used to ensure the security of the customer's transaction information. To ensure the security of the vein information, the vein is converted into a hash value, which can ensure that the customer's vein information will not be leaked, and at the same time, the transaction can be completed. The asymmetric secret key of each customer includes a public key and a private key. The public key is publicly available throughout the network, and the private key is saved by the customer himself.

[0094] In the technical solution of the present application, the acquisition, storage, use, processing, etc. of data all comply with the relevant regulations of national laws and regulations.

[0095] An embodiment of the present invention also provides a payment system as described in the following embodiments. Since the principle of the system to solve problems is similar to that of the payment method, the implementation of the system can refer to the implementation of the payment method, and the repeated parts will not be described again.

[0096] Figure 6 For the structural schematic diagram of the payment system in the embodiment of the present invention, as Figure 6 shown, the system includes:

[0097] The client 01 is used to establish a wireless communication connection with the device of the counterparty when the signal is poor during a transaction; collect the biometric data of the customer, encrypt the biometric data with the public key pre-distributed by the bank server to the client, and send the encrypted biometric data to the device of the counterparty; decrypt the encrypted recognition result with the stored public key to obtain the decrypted recognition result, and determine whether to support the transaction between the customer and the counterparty based on the decrypted recognition result.

[0098] The device 02 of the counterparty is used to send the encrypted biometric data to the bank server; the device of the counterparty sends the encrypted recognition result to the client.

[0099] The bank server 03 is used to determine the biometric authentication threshold of the customer based on the counterparty, and decrypt the encrypted biometric data with the corresponding private key to obtain the corresponding biometric data; perform biometric recognition on the obtained biometric data with the biometric authentication threshold, and encrypt the recognition result with the corresponding private key to obtain the encrypted recognition result; send the encrypted recognition result to the device of the counterparty.

[0100] In one embodiment, the bank server is specifically used for:

[0101] Obtain the historical transaction data of the counterparty, and determine the customer category vector corresponding to the counterparty;

[0102] Based on the customer category vector, determine the similar reference merchants of the counterparty;

[0103] Determine the customer category to which the customer belongs, and based on the transaction data of the customer category, determine the risk indicator corresponding to the customer;

[0104] Based on the corresponding relationship between the biometric authentication threshold and the risk indicator of the similar reference merchant pre-stored in the bank database, and the risk indicator corresponding to the customer, determine the biometric authentication threshold of the customer.

[0105] In one embodiment, the above payment system may further include: a pre-storage unit, which is used to store the corresponding relationship between the biometric authentication threshold and the risk indicator of each reference merchant on the bank server according to the following method:

[0106] Obtain the transaction data of the merchants in the predetermined area, and select multiple reference merchants;

[0107] Based on the transaction data of the reference merchants in the predetermined area, cluster the reference merchants in the predetermined area to obtain multiple merchant subsets;

[0108] For each merchant subset, based on the biometric data of the merchant subset, determine the corresponding relationship between the biometric authentication threshold and the risk indicator of the merchant subset;

[0109] For each reference merchant, determine the corresponding relationship between the biometric authentication threshold and the risk indicator of the merchant subset to which the reference merchant belongs as the corresponding relationship between the biometric authentication threshold and the risk indicator of the reference merchant;

[0110] Store the corresponding relationship between the biometric authentication threshold and the risk indicator of each reference merchant on the bank server.

[0111] In one embodiment, clustering the reference merchants within a predetermined area based on the transaction data of the reference merchants within the predetermined area to obtain multiple merchant subsets may include:

[0112] Based on the transaction data of each merchant, determine the number of customers belonging to each customer category in the customer set corresponding to the transaction data of the merchant;

[0113] Determine the customer category vector corresponding to the merchant, where each component corresponds to each customer category one by one, and the value of each component is equal to the number of customers belonging to the customer category corresponding to the component in the customer set corresponding to the transaction data of the merchant;

[0114] Determine the distance function of the merchants, where the independent variable of the distance function is any two merchants within the predetermined area, and the corresponding function value is: where and are the values of the i-th component of the customer category vectors of the two merchants respectively, and l is the number of customer categories;

[0115] Cluster the merchants within the predetermined area according to the distance function of the merchants to obtain multiple merchant subsets.

[0116] In one embodiment, determining the similar reference merchant of the counterparty according to the customer category vector may include:

[0117] Determine the partial order of the reference merchants according to the customer category vector, where for any two reference merchants, the partial order can be used to determine whether the first reference merchant among the two reference merchants is superior to the second reference merchant;

[0118] Determine the maximal reference merchants of all reference merchants according to the partial order of the reference merchants, where the maximal reference merchant is the maximal element of the partial order;

[0119] Determine the similar reference merchant of the counterparty according to the maximal reference merchant.

[0120] In one embodiment, determining a partial order of reference merchants based on the customer category vectors may include:

[0121] For any reference merchant, determine the vector difference between the customer category vector of the counterparty and the customer category vector of the reference merchant, and determine the absolute value of the vector difference as the gap vector corresponding to the reference merchant;

[0122] For any two reference merchants, calculate the difference between the gap vector corresponding to the first reference merchant of the two reference merchants and the gap vector corresponding to the second reference merchant of the two reference merchants. If each component of the difference is less than or equal to 0, determine that the first reference merchant is superior to the second reference merchant.

[0123] In one embodiment, obtaining the historical transaction data of the counterparty and determining the customer category vector corresponding to the counterparty may include:

[0124] Based on the historical transaction data of the counterparty, determine the quantity belonging to each customer category in the customer set corresponding to the historical transaction data of the counterparty;

[0125] Determine the customer category vector corresponding to the merchant, where each component corresponds to each customer category one by one, and the value of each component is equal to the quantity belonging to the customer category corresponding to the component in the customer set corresponding to the historical transaction data of the counterparty.

[0126] An embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the above payment method is implemented.

[0127] An embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above payment method is implemented.

[0128] An embodiment of the present invention further provides a computer program product, where the computer program product includes a computer program, and when the computer program is executed by a processor, the above payment method is implemented.

[0129] In an embodiment of the present invention, a payment solution includes: when a transaction is performed on a client, if the signal of the client is poor, establishing a wireless communication connection between the client and the device of the counterparty; collecting biometric data of the customer, encrypting the biometric data with a public key pre-distributed by a bank server to the client, and sending the encrypted biometric data to the device of the counterparty; the device of the counterparty sending the encrypted biometric data to the bank server; the bank server determining a biometric authentication threshold of the customer based on the counterparty, and decrypting the encrypted biometric data with a corresponding private key to obtain the corresponding biometric data; performing biometric identification on the obtained biometric data with the biometric authentication threshold, and encrypting the identification result with the corresponding private key to obtain an encrypted identification result; sending the encrypted identification result to the device of the counterparty; the device of the counterparty sending the encrypted identification result to the client; the client decrypting the encrypted identification result with a stored public key to obtain a decrypted identification result, and determining whether to support the transaction between the customer and the counterparty based on the decrypted identification result, so as to achieve safe and convenient payment when the signal of the client is poor or there is no signal.

[0130] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0131] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or multiple flows and / or blocks

[0132] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in the flow Figure 1One or more processes and / or blocks Figure 1 The functions specified in one or more blocks.

[0133] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one Figure 1 One or more processes and / or blocks Figure 1 The steps of the functions specified in one or more blocks.

[0134] The specific embodiments described above further elaborate on the purpose, technical solutions, and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection scope of the present invention.

Claims

1. A payment method, characterized in that, Including: When a transaction is carried out on the client side, if the signal of the client side is poor, the client side establishes a wireless communication connection with the POS machine of the counterparty; collects the biometric data of the customer, encrypts the biometric data with the public key pre-distributed by the bank server to the client side, and sends the encrypted biometric data to the POS machine of the counterparty; The POS machine of the counterparty sends the encrypted biometric data to the bank server; The bank server determines the biometric authentication threshold of the customer based on the counterparty, and decrypts the encrypted biometric data with the corresponding private key to obtain the corresponding biometric data; performs biometric recognition on the obtained biometric data with the biometric authentication threshold, and encrypts the recognition result with the corresponding private key to obtain the encrypted recognition result; sends the encrypted recognition result to the POS machine of the counterparty; The POS machine of the counterparty sends the encrypted recognition result to the client side; The client side decrypts the encrypted recognition result with the stored public key to obtain the decrypted recognition result, and determines whether to support the transaction between the customer and the counterparty based on the decrypted recognition result; The bank server determines the biometric authentication threshold of the customer based on the counterparty, including: the bank server obtains the historical transaction data of the counterparty and determines the customer category vector corresponding to the counterparty; determines the similar reference merchant of the counterparty according to the customer category vector; determines the customer category to which the customer belongs, and determines the risk index corresponding to the customer based on the transaction data of the customer category; determines the biometric authentication threshold of the customer according to the corresponding relationship between the biometric authentication threshold and the risk index of the similar reference merchant pre-stored in the bank database and the risk index corresponding to the customer.

2. The payment method according to claim 1, characterized in that, It also includes storing the corresponding relationship between the biometric authentication threshold and the risk index of each reference merchant on the bank server according to the following method: Obtain the transaction data of the merchants in the predetermined area and select multiple reference merchants; Cluster the reference merchants in the predetermined area according to the transaction data of the reference merchants in the predetermined area to obtain multiple merchant subsets; For each merchant subset, determine the corresponding relationship between the biometric authentication threshold and the risk index corresponding to the merchant subset based on the biometric data of the merchant subset; For each reference merchant, determine the corresponding relationship between the biometric authentication threshold and the risk index corresponding to the merchant subset to which the reference merchant belongs as the corresponding relationship between the biometric authentication threshold and the risk index corresponding to the reference merchant; Store the corresponding relationship between the biometric authentication threshold and the risk index of each reference merchant on the bank server.

3. The payment method according to claim 2, characterized in that, Clustering the reference merchants in the predetermined area according to the transaction data of the reference merchants in the predetermined area to obtain multiple merchant subsets, including: Determine the number of customers belonging to each customer category in the customer set corresponding to the transaction data of each merchant according to the transaction data of each merchant; Determine the customer category vector corresponding to the merchant, where each component corresponds to each customer category one by one, and the value of each component is equal to the number of customers belonging to the customer category corresponding to the component in the customer set corresponding to the transaction data of the merchant; Determine the distance function for merchants, where the independent variable of this distance function is any two merchants within the predetermined area, and the corresponding function value is: where and are respectively the values of the i-th component of the customer category vectors of the two merchants, and l is the number of customer categories; Cluster the merchants within a predetermined area according to the distance function of the merchants to obtain multiple subsets of merchants.

4. The payment method according to claim 1, characterized in that, Determine the similar reference merchants of the counterparty according to the customer category vector, including: Determine the partial order of the reference merchants according to the customer category vector, where, for any two reference merchants, this partial order can be used to determine whether the first reference merchant among the two reference merchants is superior to the second reference merchant; Determine the maximal reference merchants of all reference merchants according to the partial order of the reference merchants, where the maximal reference merchant is the maximal element of this partial order; Determine the similar reference merchants of the counterparty according to the maximal reference merchants.

5. The payment method according to claim 4, characterized in that, Determine the partial order of the reference merchants according to the customer category vector, including: For any reference merchant, determine the vector difference between the customer category vector of the counterparty and the customer category vector of this reference merchant, and determine the absolute value of this vector difference as the gap vector corresponding to this reference merchant; For any two reference merchants, calculate the difference between the gap vector corresponding to the first reference merchant of the two reference merchants and the gap vector corresponding to the second reference merchant of the two reference merchants. If each component of this difference is less than or equal to 0, determine that the first reference merchant is superior to the second reference merchant.

6. The payment method according to claim 1, characterized in that, The bank server obtains the historical transaction data of the counterparty and determines the customer category vector corresponding to the counterparty, including: According to the historical transaction data of the counterparty, determine the quantity belonging to each customer category in the customer set corresponding to the historical transaction data of the counterparty; Determine the customer category vector corresponding to this merchant, where each component corresponds one by one to each customer category, and the value of each component is equal to the quantity belonging to the customer category corresponding to this component in the customer set corresponding to the historical transaction data of the counterparty.

7. A payment system, characterized in that, Including: The client is used to, when conducting a transaction, if the signal is poor, establish a wireless communication connection with the POS machine of the counterparty; collect the biometric data of the customer, encrypt the biometric data with the public key pre-distributed by the bank server to this client, and send the encrypted biometric data to the POS machine of the counterparty; decrypt the encrypted recognition result with the stored public key to obtain the decrypted recognition result, and determine whether to support the transaction between this customer and this counterparty according to the decrypted recognition result; The POS machine of the counterparty is used to send the encrypted biometric data to the bank server; the POS machine of the counterparty sends the encrypted recognition result to the client; The bank server is used to determine the biometric authentication threshold of this customer based on this counterparty, and decrypt the encrypted biometric data with the corresponding private key to obtain the corresponding biometric data; perform biometric recognition on the obtained biometric data with this biometric authentication threshold, and encrypt the recognition result with the corresponding private key to obtain the encrypted recognition result; send the encrypted recognition result to the POS machine of the counterparty; Specifically, the bank server is used to: obtain the historical transaction data of the counterparty and determine the customer category vector corresponding to the counterparty; determine the similar reference merchants of the counterparty according to the customer category vector; Determine the customer category to which the customer belongs, and based on the transaction data of the customer category, determine the risk indicator corresponding to the customer; According to the corresponding relationship between the biometric authentication threshold and the risk indicator of the similar reference merchant pre-stored in the bank database, and the risk indicator corresponding to the customer, determine the biometric authentication threshold of the customer.

8. The payment system according to claim 7, wherein It further includes: A pre-storage unit for storing the corresponding relationship between the biometric authentication threshold and the risk indicator of each reference merchant on the bank server according to the following method: Obtain the transaction data of the merchants in the predetermined area, and select multiple reference merchants; Cluster the reference merchants in the predetermined area according to the transaction data of the reference merchants in the predetermined area to obtain multiple merchant subsets; For each merchant subset, based on the biometric data of the merchant subset, determine the corresponding relationship between the biometric authentication threshold and the risk indicator of the merchant subset; For each reference merchant, determine the corresponding relationship between the biometric authentication threshold and the risk indicator of the merchant subset to which the reference merchant belongs as the corresponding relationship between the biometric authentication threshold and the risk indicator of the reference merchant; Store the corresponding relationship between the biometric authentication threshold and the risk indicator of each reference merchant on the bank server.

9. The payment system according to claim 8, wherein Cluster the reference merchants in the predetermined area according to the transaction data of the reference merchants in the predetermined area to obtain multiple merchant subsets, including: According to the transaction data of each merchant, determine the number of customers belonging to each customer category in the customer set corresponding to the transaction data of the merchant; Determine the customer category vector corresponding to the merchant, where each component corresponds to each customer category one by one, and the value of each component is equal to the number of customers belonging to the customer category corresponding to the component in the customer set corresponding to the transaction data of the merchant; Determine the distance function for merchants, where the independent variable of this distance function is any two merchants within the predetermined area, and the corresponding function value is as follows: where and are respectively the values of the i-th component of the customer category vectors of the two merchants, and l is the number of customer categories; Cluster the merchants in the predetermined area according to the distance function of the merchants to obtain multiple merchant subsets.

10. The payment system according to claim 7, wherein Determine the similar reference merchant of the counterparty according to the customer category vector, including: Determine the partial order of the reference merchants according to the customer category vector, where for any two reference merchants, the partial order can be used to determine whether the first reference merchant among the two reference merchants is superior to the second reference merchant; Determine the maximum reference merchants of all reference merchants according to the partial order of the reference merchants, where the maximum reference merchant is the maximum element of the partial order; Determine the similar reference merchant of the counterparty according to the maximum reference merchant.

11. The payment system according to claim 10, wherein Determine the partial order of the reference merchants according to the customer category vector, including: For any reference merchant, determine the vector difference between the customer category vector of the counterparty and the customer category vector of the reference merchant, and determine the absolute value of the vector difference as the gap vector corresponding to the reference merchant; For any two reference merchants, calculate the difference between the gap vector corresponding to the first reference merchant of the two reference merchants and the gap vector corresponding to the second reference merchant of the two reference merchants. If each component of the difference is less than or equal to 0, determine that the first reference merchant is superior to the second reference merchant.

12. The payment system according to claim 7, wherein Obtain the historical transaction data of the counterparty and determine the customer category vector corresponding to the counterparty, including: Based on the historical transaction data of the counterparty, determine the quantity belonging to each customer category in the customer set corresponding to the historical transaction data of the counterparty; Determine the customer category vector corresponding to the merchant, wherein each component corresponds one-to-one to each customer category, and the value of each component is equal to the quantity belonging to the customer category corresponding to the component in the customer set corresponding to the historical transaction data of the counterparty.

13. A computer device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein When the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

14. A computer-readable storage medium, wherein The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

15. A computer program product, wherein The computer program product includes a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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