Blockchain-based terminal payment method and system

Abstract

The present invention discloses a terminal payment method and system based on blockchain, which relates to the technical field of blockchain. The method includes: the bank server determines the risk vector and customer vector corresponding to the corresponding transaction scenario according to the customer transaction data of different transaction scenarios and different identity confirmation methods; determines multiple identity confirmation methods corresponding to each transaction scenario based on the risk vector and customer vector; for low-risk customers, determines the main transaction scenario based on their historical transaction data, and sends the main transaction scenario and the corresponding multiple identity confirmation methods of the low-risk customers to the corresponding mobile terminal; when making a transaction with the network signal strength less than the threshold, the mobile terminal determines whether the transaction scenario of the transaction is included in the main transaction scenario according to the transaction data, and if it is included, determines the identity confirmation method; and performs identity verification on the transaction of the customer based on the identity confirmation method. The present invention can improve the transaction experience of customers when the network is poor.

Description

Technical Field

[0001] The present invention relates to the technical field of blockchain, and in particular, to a terminal payment method and system based on blockchain. 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 by including it in this section.

[0003] Currently, the risk control for customers' bank transactions is deployed on the bank server, and risk control needs to be performed online, which requires a good network signal on the customer's mobile terminal. When the network signal of the customer's mobile terminal is poor, transactions may not be possible. This situation often occurs, which limits customers' transactions and results in poor customer experience. Summary of the Invention

[0004] An embodiment of the present invention provides a terminal payment method based on blockchain, the method comprising:

[0005] The bank server determines a risk vector and a customer vector corresponding to a corresponding transaction scenario according to customer transaction data in different transaction scenarios;

[0006] The bank server determines a risk vector and a customer vector corresponding to a corresponding transaction scenario according to customer transaction data in different identity confirmation methods;

[0007] The bank server determines multiple identity confirmation methods corresponding to each transaction scenario based on the risk vector and the customer vector;

[0008] For low-risk customers, the bank server determines the main transaction scenario of the low-risk customer based on the historical transaction data of the low-risk customer, and issues the main transaction scenario of the low-risk customer, the corresponding multiple identity confirmation methods, and the information of the low-risk customer corresponding to the multiple identity confirmation methods to the mobile terminal of the low-risk customer;

[0009] When a low-risk customer conducts a transaction when the network signal strength of the mobile terminal is less than the signal strength threshold, the mobile terminal determines whether the transaction scenario of the transaction is included in the main transaction scenarios stored in the mobile terminal according to the transaction data. If it is included, the identity confirmation method corresponding to the transaction is determined;

[0010] The mobile terminal authenticates the customer's transaction based on the identity confirmation method corresponding to the transaction.

[0011] An embodiment of the present invention further provides a terminal payment system based on blockchain, the system comprising: a bank server and a mobile terminal, for implementing the above-mentioned terminal payment method based on blockchain.

[0012] 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-mentioned blockchain-based terminal payment method is implemented.

[0013] An embodiment of the present invention further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned blockchain-based terminal payment method is implemented.

[0014] An embodiment of the present invention further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the above-mentioned blockchain-based terminal payment method is implemented.

[0015] In an embodiment of the present invention, compared with the prior art in which transactions cannot be made when the mobile terminal network signal is poor, the bank server determines the risk vector and customer vector corresponding to the corresponding transaction scenario according to the customer transaction data in different transaction scenarios; the bank server determines the risk vector and customer vector corresponding to the corresponding transaction scenario according to the customer transaction data in different identity confirmation methods; the bank server determines multiple identity confirmation methods corresponding to each transaction scenario based on the risk vector and customer vector; for low-risk customers, the bank server determines the main transaction scenario of the low-risk customer based on the historical transaction data of the low-risk customer, and sends the main transaction scenario of the low-risk customer, the corresponding multiple identity confirmation methods, and the information of the low-risk customer corresponding to the multiple identity confirmation methods to the mobile terminal of the low-risk customer; when a low-risk customer makes a transaction when the network signal strength of the mobile terminal is less than the signal strength threshold, the mobile terminal determines whether the transaction scenario of the transaction is included in the main transaction scenario stored in the mobile terminal. If it is included, the mobile terminal determines the identity confirmation method corresponding to the transaction, and the mobile terminal authenticates the identity of the customer for the transaction based on the identity confirmation method corresponding to the transaction. Transactions can be made even when the network is poor, the security of transactions can be guaranteed, and the customer experience can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] 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 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 be obtained based on these drawings. In the drawings:

[0017] Figure 1 is the flow of the blockchain-based terminal payment method in the embodiment of the present invention Figure 1 ;

[0018] Figure 2 The process flow of the terminal payment method based on blockchain in the embodiments of the present invention Figure 2 ;

[0019] Figure 3 The process flow of the terminal payment method based on blockchain in the embodiments of the present invention Figure 3 ;

[0020] Figure 4 The process flow of the terminal payment method based on blockchain in the embodiments of the present invention Figure 4 ;

[0021] Figure 5 The process flow of the terminal payment method based on blockchain in the embodiments of the present invention Figure 5 ;

[0022] Figure 6 The process flow of the terminal payment method based on blockchain in the embodiments of the present invention Figure 6 ;

[0023] Figure 7 The process flow of the terminal payment method based on blockchain in the embodiments of the present invention Figure 7 . Specific embodiments

[0024] 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 do not limit the present invention.

[0025] Based on the problems existing in the above prior art, the present invention proposes a terminal payment system based on blockchain. The system includes a bank server and a mobile terminal, and also includes a blockchain node of the mobile terminal. The system can realize transaction payments when the network is poor. The specific method steps are as Figures 1 to 7 shown.

[0026] Figure 1 The process flow of the terminal payment method based on blockchain in the embodiments of the present invention Figure 1 , as Figure 1 shown, the method includes:

[0027] Step 101: The bank server determines the risk vector and customer vector corresponding to the corresponding transaction scenario according to the customer transaction data of different transaction scenarios;

[0028] Step 102: The bank server determines the risk vector and customer vector corresponding to the corresponding transaction scenario according to the customer transaction data of different identity confirmation methods;

[0029] Step 103: The bank server determines multiple identity verification methods corresponding to each transaction scenario based on the risk vector and the customer vector;

[0030] Step 104: For low-risk customers, the bank server determines the main transaction scenarios of the low-risk customers based on the historical transaction data of the low-risk customers, and sends the main transaction scenarios of the low-risk customers, the corresponding multiple identity verification methods, and the information of the low-risk customers corresponding to the multiple identity verification methods (the information required for verifying the customer identity) to the mobile terminals of the low-risk customers;

[0031] Step 105: When a low-risk customer conducts a transaction when the network signal strength of the mobile terminal is less than the signal strength threshold, the mobile terminal determines whether the transaction scenario of the transaction is included in the main transaction scenarios stored in the mobile terminal according to the transaction data. If it is included, the identity verification method corresponding to the transaction is determined;

[0032] Step 106: The mobile terminal verifies the identity of the customer for the transaction based on the identity verification method corresponding to the transaction.

[0033] Specifically, different scenarios may include shopping, payment scenarios, hospitals, ETC transactions, private transfers, and so on. Different identity verification methods may include face recognition, fingerprint recognition, passwords, and face recognition with different implementation methods (or different parameters), and fingerprint recognition with different implementation methods, and so on.

[0034] In the embodiment of the present invention, as Figure 2 shown, the method may further include:

[0035] Step 201: When the network signal strength of the customer's mobile terminal is greater than the signal strength threshold, the mobile terminal uploads the transaction data and the hash value corresponding to the transaction data to the bank server;

[0036] Step 202: The bank server compares whether the hash value corresponding to the uploaded transaction data is consistent with the uploaded hash value, and processes the uploaded transaction data based on the comparison result.

[0037] In the embodiment of the present invention, as Figure 3 shown, in step 101, the bank server determines the risk vector and the customer vector corresponding to the corresponding transaction scenario according to the customer transaction data of different transaction scenarios, including:

[0038] Step 301: According to the customer transaction data of different transaction scenarios, determine the number of customers in each customer category corresponding to the corresponding transaction scenario, and the proportion of risk data in the transaction data corresponding to each customer category;

[0039] Step 302: Determine the risk vector corresponding to the transaction scenario. Each component of the risk vector corresponds one-to-one with a customer category, and the value of each component is equal to the proportion of risk data in the transaction data of the customer category corresponding to this component for the corresponding transaction scenario;

[0040] Step 303: Determine the customer vector corresponding to the transaction scenario. Each component of the customer vector corresponds one-to-one with a customer category, and the value of each component is equal to the number of customers in the customer category corresponding to this component for the corresponding transaction scenario.

[0041] In the embodiment of the present invention, as Figure 4 shown, step 102 the bank server determines the risk vector and the customer vector corresponding to the transaction scenario according to the customer transaction data of different identity confirmation methods, including:

[0042] Step 401: According to the customer transaction data of different identity confirmation methods, determine the number of customers in each customer category corresponding to the corresponding identity confirmation method, and the proportion of risk data in the transaction data of each customer category;

[0043] Step 402: Determine the risk vector corresponding to the identity confirmation method. Each component of the risk vector corresponds one-to-one with a customer category, and the value of each component is equal to the proportion of risk data in the transaction data of the customer category corresponding to this component for the corresponding identity confirmation method;

[0044] Step 403: Determine the customer vector corresponding to the identity confirmation method. Each component of the customer vector corresponds one-to-one with a customer category, and the value of each component is equal to the number of customers in the customer category corresponding to this component for the corresponding identity confirmation method.

[0045] In the embodiment of the present invention, as Figure 5 shown, step 103 the bank server determines multiple identity confirmation methods corresponding to each transaction scenario according to the risk vector and the customer vector, including:

[0046] Step 501: For each identity confirmation method, determine the difference between the customer vector of this identity confirmation method and the customer vector of this transaction scenario, and determine this difference as the customer vector difference corresponding to this identity confirmation method; and determine the difference between the risk vector of this identity confirmation method and the risk vector of this transaction scenario, and determine this difference as the risk vector difference corresponding to this identity confirmation method;

[0047] Step 502: According to the customer vector difference and the risk vector difference, determine the partial order corresponding to this transaction scenario. Among them, for any two identity confirmation methods, this partial order can determine whether the first identity confirmation method among the two identity confirmation methods is superior to the second identity confirmation method among the two identity confirmation methods;

[0048] Step 503: Determine multiple maximum identity confirmation methods for this partial order, where the maximum identity confirmation method is the maximum element of this partial order;

[0049] Step 504: Determine multiple identity confirmation methods corresponding to this transaction scenario based on the multiple maximum identity confirmation methods of this partial order.

[0050] The (definition of the) maximum element of a partial order is that in the set corresponding to the partial order, there is no other element that is superior to this maximum element. In one embodiment, determining multiple maximum identity confirmation methods for this partial order includes:

[0051] For each identity confirmation method, determine the partial order relationship between this identity confirmation method and each other identity confirmation method except this identity confirmation method. If there is no other identity confirmation method that is superior to this identity confirmation method, then determine that this identity confirmation method is the maximum identity confirmation method of this partial order.

[0052] In the embodiments of the present invention, as Figure 6 shown, Step 502 determines the partial order corresponding to this transaction scenario based on the customer vector difference and the risk vector difference, including:

[0053] Step 601: For each identity confirmation method, determine the modulus length of the customer vector difference corresponding to this identity confirmation method as the customer distance corresponding to this identity confirmation method;

[0054] Step 602: For any two identity confirmation methods, determine the difference between the risk vector difference corresponding to the first identity confirmation method and the risk vector difference corresponding to the second identity confirmation method among these two identity confirmation methods. If each component of this difference is less than or equal to 0, and the customer distance corresponding to the first identity confirmation method is less than or equal to the customer distance corresponding to the second identity confirmation method, then determine that the first identity confirmation method is superior to the second identity confirmation method.

[0055] In the embodiments of the present invention, this method further includes: The bank server determines that a customer is a low-risk customer according to the following method:

[0056] Determine the transaction risk indicator of this customer based on the historical transaction data of the customer category to which this customer belongs. If the transaction risk indicator is less than the threshold value, then determine that this customer is a low-risk customer;

[0057] Or,

[0058] Predict the transaction risk indicator of this customer based on the existing risk prediction model and the attributes of this customer. If the transaction risk indicator is less than the threshold value, then determine that this customer is a low-risk customer.

[0059] It should be noted that the transaction data of a single customer is usually relatively small, and it is impossible to accurately judge the risk information of this customer. It is necessary to rely on the transaction data of the customer category of this customer. In this way, the risk information of a single customer can be determined, and a certain degree of accuracy can be ensured.

[0060] In one embodiment, the customer category can be obtained and the customer category to which each customer belongs can be determined according to the following method:

[0061] Determine the values of each customer of the bank in each attribute. For example, the attributes include customer attributes and transaction attributes. Among them, the customer attributes include the customer's funds, income, and risk level, and the transaction attributes include the transaction quantities of the customer in each transaction category.

[0062] Based on the values of each customer of the bank in each attribute, determine the function corresponding to the customer, where this function can determine the distance between any two customers.

[0063] Cluster the customers of the bank based on the function corresponding to the customer to obtain multiple customer categories, where each customer category corresponds to a clustering center;

[0064] For each obtained customer category, continue to perform clustering analysis until the consistency parameter of each newly generated customer category is greater than the set value. Each newly generated customer category corresponds to a clustering center. Among them, the consistency parameter of each customer category is determined as the maximum value of the proportion of the number of customers corresponding to each risk level among all the customers in this customer category;

[0065] For each customer, determine the distance between this customer and each clustering center according to the function corresponding to the customer, and determine the customer category corresponding to the clustering center with the smallest corresponding distance as the customer category to which this customer belongs.

[0066] In one embodiment, determine the transaction risk index of this customer based on the historical transaction data of the customer category to which this customer belongs. If this transaction risk index is less than the threshold value, it is determined that this customer is a low-risk customer, including:

[0067] Divide the time period range corresponding to the historical transaction data into multiple time period intervals, where the difference in the transaction quantities included in any two time intervals is less than the first threshold value, and the transaction quantity included in each time period interval is greater than the second threshold value;

[0068] For each time period interval, screen out the historical transaction data corresponding to this time period interval from the historical transaction data;

[0069] For each time period interval, use the proportion of the number of risk transaction data in the historical transaction data corresponding to this time period interval as the sample of the transaction risk index of this customer;

[0070] (Step s) Determine the transaction risk indicator of this customer as the mean of all transaction risk indicator samples of this customer;

[0071] If the transaction risk indicator of this customer is less than the threshold value, determine that this customer is a low-risk customer.

[0072] In one embodiment, another method for the bank server to determine that a customer is a low-risk customer includes:

[0073] After (step s) determining the transaction risk indicator of this customer as the mean of all transaction risk indicator samples of this customer, based on all transaction risk indicator samples (multiple samples of the same distribution) of this customer, determine the variance corresponding to the transaction risk indicator of this customer, and the number of indicator samples corresponding to the transaction risk indicator of this customer;

[0074] Take the quotient of the square of the variance corresponding to the transaction risk indicator of this customer and the number of indicator samples corresponding to the transaction risk indicator of this customer as the upper bound of error convergence corresponding to the transaction risk indicator of this customer;

[0075] If the transaction risk indicator of this customer is less than the threshold value and the upper bound of error convergence corresponding to the transaction risk indicator of this customer is less than the convergence threshold value, determine that this customer is a low-risk customer.

[0076] Among them, according to the law of large numbers, the convergence threshold value can be determined by the following method:

[0077] Set the maximum acceptable indicator error, and the probability that the acceptable indicator error is greater than this maximum indicator error;

[0078] Determine the convergence threshold value as the product of the square of the maximum indicator error and the probability.

[0079] In step 104, for a low-risk customer, the bank server determines the main transaction scenarios of this low-risk customer based on the historical transaction data of this low-risk customer, and sends the main transaction scenarios of this low-risk customer and the corresponding multiple identity confirmation methods, as well as the information of this low-risk customer corresponding to these multiple identity confirmation methods (the information required when verifying the customer's identity) to the mobile terminal of this low-risk customer, including:

[0080] According to the historical transaction data of this low-risk customer, determine the transaction quantity and average transaction amount corresponding to each transaction scenario;

[0081] Select from the transaction scenarios included in the historical transaction data of this low-risk customer multiple transaction scenarios where the corresponding transaction quantity is greater than the quantity threshold value and the corresponding average transaction amount is less than the amount threshold value, and use the selected multiple transaction scenarios as the main transaction scenarios of this low-risk customer.

[0082] The method of the above embodiments can ensure that when the network signal of the mobile terminal of a low-risk customer is relatively weak, the low-risk customer can continue to conduct transactions, and the risk of the transactions is within a controllable range by selecting low-risk customers and determining the main transaction scenarios of the low-risk customers.

[0083] In one embodiment, in step 105, when a low-risk customer conducts a transaction when the network signal strength of the mobile terminal is less than the signal strength threshold, the mobile terminal determines whether the transaction scenario of the transaction is included in the main transaction scenarios stored in the mobile terminal according to the transaction data. If it is included, the identity confirmation method corresponding to the transaction is determined, including:

[0084] If it is determined that the transaction scenario of the transaction is included in the main transaction scenarios stored in the mobile terminal, multiple identity confirmation methods corresponding to the transaction scenario of the transaction are selected from the identity confirmation methods sent to the mobile terminal of the low-risk customer, and the selected multiple identity confirmation methods are used as the identity confirmation method corresponding to the transaction.

[0085] In the embodiments of the present invention, as Figure 7 shown, in step 106, the mobile terminal authenticates the identity of the customer for the transaction based on the identity confirmation method corresponding to the transaction, including:

[0086] Step 701: Based on a randomization method, only one identity confirmation method is selected from the identity confirmation methods corresponding to the transaction to confirm the identity of the customer (when the network signal is weak this time, only this identity verification method is used, that is, other identity verification methods will not be changed). Until the consecutive number of times (the previous identity verification failed) confirmed by this method reaches the maximum number of times corresponding to the identity confirmation method (if the identity verification of the customer still fails after reaching the maximum number of times), the account of the customer is locked until the network signal of the customer becomes better, and risk control and identity confirmation of the customer are performed based on the bank server.

[0087] Specifically, selecting the identity confirmation method through a randomization method can ensure the security of the transactions of the customer's mobile terminal to a certain extent when the signal is relatively weak.

[0088] In one embodiment, based on a randomization method, only one identity confirmation method is selected from the identity confirmation methods corresponding to the transaction to confirm the identity of the customer, including:

[0089] For each identity confirmation method corresponding to the transaction, according to the proportion of the risk data in the transaction data of each customer category corresponding to the identity confirmation method (step 401), the risk value corresponding to the identity confirmation method is determined; wherein, the risk value corresponding to the i-th identity confirmation method of the transaction is determined as r

[0089] , ,

[0087] , ,

[0088] , , Figure 7 , ,

[0086] , ij ,

[0085] , is the ratio of the risk data in the transaction data corresponding to the j-th customer category for the i-th identity confirmation method corresponding to the transaction;

[0090] For each identity confirmation method corresponding to the transaction, based on the customer vector of the transaction scenario (main transaction scenario) of the transaction and the customer vector of this identity confirmation method, determine the customer value corresponding to this identity confirmation method; (for example, determine this customer value as the distance between the two customer vectors)

[0091] Based on the corresponding risk value and the corresponding customer value, determine the priority probability of each identity confirmation method corresponding to the transaction; among them, determine the priority probability of the i-th identity confirmation method corresponding to the transaction as: c j and r j are respectively the customer value and the corresponding risk value corresponding to the j-th identity confirmation method corresponding to the transaction;

[0092] Select a probability density function f and determine the minimum value m of the independent variable of the function f;

[0093] Sort the identity confirmation methods corresponding to the transaction;

[0094] For each identity confirmation method corresponding to the transaction, determine the sum of the priority probabilities of all the identity determination methods before this identity confirmation method in the sorting as the left endpoint probability corresponding to this identity confirmation method; based on the left endpoint probability corresponding to this identity confirmation method, determine the left endpoint value corresponding to this identity confirmation method, where the integral of f from the minimum value m to the left endpoint value corresponding to this identity confirmation method is equal to the left endpoint probability corresponding to this identity confirmation method;

[0095] Generate a random number according to the function f;

[0096] Select the largest left endpoint value less than this random number from the left endpoint values corresponding to the identity confirmation methods corresponding to the transaction;

[0097] Select the identity confirmation method corresponding to the left endpoint value equal to this largest left endpoint value to confirm the identity of the customer.

[0098] In the embodiment of the present invention, it further includes:

[0099] The mobile terminal stores the transaction data of the customer in the local database and stores the hash value corresponding to the transaction data on the blockchain node of the mobile terminal.

[0100] In one embodiment, a customer can set transaction elements during transactions when the network signal is weak, such as the time when the transaction can be conducted, the limit value, the set of counter-parties for the transaction, etc. The above data is stored in the blockchain. When the customer is in a weak network signal environment and needs to conduct a transaction, the transaction of the customer is audited based on the transaction elements stored in the blockchain. If any one condition is not met, the transaction behavior of the customer is rejected, which can maximize the avoidance of transaction risks.

[0101] In the technical solution of this application, the acquisition, storage, use, processing, etc. of data all comply with the relevant provisions of national laws and regulations.

[0102] 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-mentioned blockchain-based terminal payment method is implemented.

[0103] An embodiment of the present invention further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned blockchain-based terminal payment method is implemented.

[0104] An embodiment of the present invention further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the above-mentioned blockchain-based terminal payment method is implemented.

[0105] In the embodiment of the present invention, compared with the prior art solution where transactions cannot be conducted when the mobile terminal network signal is poor, the bank server determines the risk vector and customer vector corresponding to the corresponding transaction scenario according to the customer transaction data in different transaction scenarios; the bank server determines the risk vector and customer vector corresponding to the corresponding transaction scenario according to the customer transaction data in different identity confirmation methods; the bank server determines multiple identity confirmation methods corresponding to each transaction scenario based on the risk vector and customer vector; for low-risk customers, the bank server determines the main transaction scenario of the low-risk customer based on the historical transaction data of the low-risk customer, and issues the main transaction scenario of the low-risk customer, the corresponding multiple identity confirmation methods, and the information of the low-risk customer corresponding to the multiple identity confirmation methods to the mobile terminal of the low-risk customer; when a low-risk customer conducts a transaction when the network signal strength of the mobile terminal is less than the signal strength threshold, the mobile terminal determines whether the transaction scenario of the transaction is included in the main transaction scenario stored in the mobile terminal. If it is included, the mobile terminal determines the identity confirmation method corresponding to the transaction, and the mobile terminal authenticates the identity of the customer for the transaction based on the identity confirmation method corresponding to the transaction, which can realize transactions even when the network is poor, ensure the security of transactions, and improve the customer experience.

[0106] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0107] The present invention is described with reference to 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 process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes 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 a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0108] These computer program instructions may 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, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0109] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0110] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A terminal payment method based on blockchain, characterized in that, Including: The bank server determines the risk vector and customer vector corresponding to the corresponding transaction scenario according to the customer transaction data of different transaction scenarios; The bank server determines the risk vector and customer vector corresponding to the corresponding identity verification method according to the customer transaction data of different identity verification methods; The bank server determines multiple identity verification methods corresponding to each transaction scenario based on the risk vector and customer vector; For low-risk customers, the bank server determines the main transaction scenario of the low-risk customer based on the historical transaction data of the low-risk customer, and sends the main transaction scenario of the low-risk customer, the corresponding multiple identity verification methods, and the information of the low-risk customer corresponding to the multiple identity verification methods to the mobile terminal of the low-risk customer; When a low-risk customer conducts a transaction when the network signal strength of the mobile terminal is less than the signal strength threshold, the mobile terminal determines whether the transaction scenario of the transaction is included in the main transaction scenario stored in the mobile terminal according to the transaction data. If it is included, the identity verification method corresponding to the transaction is determined; The mobile terminal performs identity verification on the transaction of the customer based on the identity verification method corresponding to the transaction; The bank server determines multiple identity verification methods corresponding to each transaction scenario based on the risk vector and customer vector, including: for each identity verification method, determining the difference between the customer vector of the identity verification method and the customer vector of the transaction scenario, and determining the difference as the customer vector difference corresponding to the identity verification method; and determining the difference between the risk vector of the identity verification method and the risk vector of the transaction scenario, and determining the difference as the risk vector difference corresponding to the identity verification method; determining the partial order corresponding to the transaction scenario based on the customer vector difference and the risk vector difference, where, for any two identity verification methods, the partial order can determine whether the first identity verification method among the two identity verification methods is superior to the second identity verification method among the two identity verification methods; determining multiple maximal identity verification methods of the partial order, where the maximal identity verification method is the maximal element of the partial order; determining multiple identity verification methods corresponding to the transaction scenario based on the multiple maximal identity verification methods of the partial order.

2. The method according to claim 1, characterized in that Also including: When the network signal strength of the customer's mobile terminal is greater than the signal strength threshold, the mobile terminal uploads the transaction data and the hash value corresponding to the transaction data to the bank server; The bank server compares whether the hash value corresponding to the uploaded transaction data is consistent with the uploaded hash value, and processes the uploaded transaction data based on the comparison result.

3. The method according to claim 1, wherein The bank server determines the risk vector and customer vector corresponding to the corresponding transaction scenario according to the customer transaction data of different transaction scenarios, including: According to the customer transaction data of different transaction scenarios, determining the number of customers in each customer category corresponding to the corresponding transaction scenario, and the proportion of risk data in the transaction data corresponding to each customer category; Determining the risk vector corresponding to the corresponding transaction scenario, where each component of the risk vector corresponds one-to-one with the customer category, and the value of each component is equal to the proportion of risk data in the transaction data of the customer category corresponding to the component in the corresponding transaction scenario; Determine the customer vector corresponding to the corresponding transaction scenario. Each component of this customer vector corresponds one-to-one with the customer category, and the value of each component is equal to the number of customers in the customer category corresponding to this component for the corresponding transaction scenario.

4. The method according to claim 1, characterized in that, The bank server determines the risk vector and customer vector corresponding to the corresponding identity verification method based on the customer transaction data of different identity verification methods, including: Based on the customer transaction data of different identity verification methods, determine the number of customers in each customer category corresponding to the corresponding identity verification method, and the proportion of risk data in the transaction data of each customer category; Determine the risk vector corresponding to the corresponding identity verification method. Each component of this risk vector corresponds one-to-one with the customer category, and the value of each component is equal to the proportion of risk data in the transaction data of the customer category corresponding to this component for the corresponding identity verification method; Determine the customer vector corresponding to the corresponding identity verification method. Each component of this customer vector corresponds one-to-one with the customer category, and the value of each component is equal to the number of customers in the customer category corresponding to this component for the corresponding identity verification method.

5. The method according to claim 1, characterized in that, Based on the customer vector difference and risk vector difference, determine the partial order corresponding to this transaction scenario, including: For each identity verification method, determine the norm of the customer vector difference corresponding to this identity verification method as the customer distance corresponding to this identity verification method; For any two identity verification methods, determine the difference between the risk vector difference corresponding to the first identity verification method in these two identity verification methods and the risk vector difference corresponding to the second identity verification method in these two identity verification methods. If each component of this difference is less than or equal to 0, and the customer distance corresponding to the first identity verification method is less than or equal to the customer distance corresponding to the second identity verification method, then determine that the first identity verification method is superior to the second identity verification method.

6. The method according to claim 1, wherein It also includes: The bank server determines that the customer is a low-risk customer according to the following method: Based on the historical transaction data of the customer category to which the customer belongs, determine the transaction risk index of this customer. If this transaction risk index is less than the threshold, then determine that this customer is a low-risk customer; Or, Based on the existing risk prediction model and the attributes of this customer, predict the transaction risk index of this customer. If this transaction risk index is less than the threshold, then determine that this customer is a low-risk customer.

7. The method according to claim 1, wherein The mobile terminal authenticates the identity of the customer for this transaction based on the identity verification method corresponding to this transaction, including: Based on a randomized method, only select one of the identity verification methods corresponding to this transaction to verify the identity of the customer until the consecutive number of times confirmed by this method reaches the maximum number corresponding to this identity verification method, then lock the customer's account until the customer's network signal improves, and perform risk control and identity verification on the customer based on the bank server.

8. The method according to claim 1, wherein It also includes: The mobile terminal stores the customer's transaction data in the local database and stores the hash value corresponding to the transaction data on the blockchain node of the mobile terminal.

9. A blockchain-based terminal payment system, characterized in that, It includes: The bank server and the mobile terminal are used to implement the method described in any one of claims 1 to 8.

10. The system according to claim 9, characterized in that, It also includes: The blockchain node is used to store the hash value corresponding to the transaction data uploaded by the mobile terminal.

11. A computer device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, the method according to any one of claims 1 to 8 is implemented.

12. A computer-readable storage medium, characterized in that, 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 8 is implemented.

13. A computer program product, characterized in that, 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 8 is implemented.

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