Method and system for carrying out risk control on aggregate payment transaction

Abstract

The invention relates to the technical field of payment transaction risk control, in particular to a method and system for carrying out risk control on aggregate payment transaction, and provides an autonomous and controllable risk control method meeting supervision requirements aiming at the limitation that existing aggregate payment depends on third-party risk control. And through the merchant rating module, the system can monitor the transaction behavior of the merchant in real time, dynamically adjust the transaction limit, and particularly perform key monitoring on large-amount, overseas and high-risk transactions. The VPN risk control module prevents cross-border fraud, provides a complaint mechanism and improves user experience; the user risk control module dynamically adjusts user transaction frequency and amount limitation through multi-dimensional analysis; the equipment risk control module effectively verifies the legality of the transaction equipment, and prevents the equipment from being used abnormally. The merchant risk control module manages high-risk and low-risk merchants in a classified manner, and improves risk control efficiency in combination with a reward and punishment mechanism. Through cooperative work of the autonomous risk control module, the acquirer does not depend on risk control of a third party any more.

Description

Technical Field

[0001] The present invention relates to the technical field of payment transaction risk control, and in particular to a method and system for performing risk control on aggregate payment transactions. Background Art

[0002] In the era of mobile Internet, aggregate payment fraud transactions occur frequently. Acquiring institutions need to strengthen risk control over aggregate payment transactions and promptly identify and handle suspicious risk transactions, including: monitoring large-value, overseas and high-risk transactions, limiting the transaction frequency and amount of merchants or users within a specific time period, triggering risk control when the limit is reached, and strictly reviewing the qualifications of merchants to ensure that their transaction behaviors are consistent with their business scope.

[0003] At present, for aggregated payment transactions, many acquiring institutions rely on the risk control services of third-party payment institutions such as WeChat Pay and Alipay, using their massive data and algorithms to identify transaction risks. However, if they completely rely on third-party risk control, there will be problems such as insufficient uniformity of risk control rules, failure to identify risks in the first place, and failure to flexibly set risk rules based on their own acquiring situations, thus failing to identify fraudulent transactions more efficiently. Summary of the invention

[0004] The object of the present invention is to provide a method and system for risk control of aggregate payment transactions, so as to more efficiently implement risk control of aggregate payment transactions.

[0005] In order to achieve the above objectives, the present application provides the following technical solutions: On the one hand, an embodiment of the present application provides a method for risk control of aggregate payment transactions, the method comprising: when a merchant submits an application, comprehensively scoring the merchant based on multi-dimensional information, and setting the merchant's single transaction amount limit, daily transaction amount limit, monthly transaction amount limit and transaction frequency limit according to the scoring results, and then regularly re-evaluating the merchant's transaction behavior, credit record and customer complaint data within a first time period to ensure that the rating results always reflect the merchant's latest operating conditions; when a user scans a code to pay, the IP address in the payment request is obtained and compared with the proxy IP database to determine whether the user is using a VPN proxy service. If it is detected that the user is using a VPN, a risk prompt will pop up immediately, and if the user chooses to continue the transaction, the transaction operation will be marked as a risky operation; when the user is trading , based on the user's payment identity, detect whether the user is a blacklist user. If he is a blacklist user, cancel the transaction; if he is not a blacklist user, detect the user's transaction frequency, single merchant transaction frequency and transaction amount in turn, and prompt the user for risky operations when any of the transaction frequency, single merchant transaction frequency and transaction amount is abnormal; when the user is scanned for payment, based on the device information in the payment request, query the database to determine whether the merchant's scanning device has been put into storage. If the scanning device has not been put into storage, prompt the merchant that the device is not under management and cancel the transaction; if the scanning device passes the storage verification, further verify whether the reported IP of the scanning device is consistent with the IP in the payment request. If not, prompt the merchant and cancel the transaction; based on the merchant number, detect in real time whether the merchant is on the blacklist. If not, continuously monitor the merchant's transaction behavior.

[0006] Optionally, the comprehensive scoring of merchants based on multi-dimensional information includes: Obtain the business category, registered capital, operating years, business entity, credit record and complaint status of the merchant, and give the merchant a comprehensive score through a weighted algorithm; Among them, the scoring system is based on the following formula: S = (A × W A )+(B×W B )+(C×W C )+(D×W D )+(E×W E )+(F×W F ); S is the total score, A is the business category score, B is the registered capital score, C is the operating years score, D is the merchant entity score, E is the credit record score, and F is the complaint score. The minimum score is 1 point and the maximum score is 5 points. A is the weight corresponding to the business category, W A is 30%, W Bis the weight corresponding to the registered capital, W B is 20%, W C is the weight corresponding to the operating years, W C is 20%, W D The weight corresponding to the merchant entity, W D is 15%, W E is the weight corresponding to the credit record, W E =10%, W F is the weight corresponding to the complaint situation, W F It is 5%.

[0007] Optionally, the merchant's single transaction amount limit, daily transaction amount limit, monthly transaction amount limit and transaction frequency limit are set according to the scoring results, including: Rating merchants based on the scores, and then obtaining the corresponding score level of the merchants, and setting the merchant's single transaction amount limit, daily transaction amount limit, monthly transaction amount limit and transaction frequency limit based on the score level; The formula for the upper limit of a single transaction amount is: upper limit of a single transaction = 5,000 yuan + (rating level − 1) × 3,750 yuan. The upper limit of a single transaction amount ranges from 5,000 to 20,000 yuan. The formula for the upper limit of daily transaction amount is: upper limit of daily transaction amount = 10,000 yuan + (score level − 1) × 122,500 yuan. The upper limit of daily transaction amount fluctuates between 10,000 yuan and 500,000 yuan. Monthly transaction limit formula: Monthly transaction limit = 200,000 yuan + (score level − 1) × 2.45 million yuan, the floating range of the monthly transaction limit is 200,000 to 10 million yuan; The formula for the upper limit of minute trading frequency is: upper limit of trading frequency = 30 transactions + (score level − 1) × 142.5 transactions. The upper limit of trading frequency ranges from 30 to 600 transactions. Optionally, if it is detected that the user is using a VPN, a risk prompt is immediately popped up, and if the user chooses to continue the transaction, the transaction operation is marked as a risky operation, and further includes: When the number of risky operations of a user reaches the preset threshold, the user will be blacklisted and subsequent transactions will be restricted.

[0008] Optionally, sequentially detecting the transaction frequency of the user, the transaction frequency of a single merchant, and the transaction amount includes: Based on the user payment identity, query the order data for orders related to the user within a preset period, and divide the number of orders by the transaction period to obtain the minute transaction frequency and hour transaction frequency respectively; Based on the minute transaction frequency and hour transaction frequency, determine whether the user's transaction frequency reaches the risk value. If it is > 3 transactions per minute or > 50 transactions per hour, a pop-up window will prompt the user and give the choice: continue the transaction or cancel the transaction. If the user chooses to continue the transaction, the operation will be recorded in the database; if the user chooses to cancel the transaction, the transaction will end; Based on the minute transaction frequency and hourly transaction frequency, determine whether the user's transaction frequency reaches the risk value. If it is ≤ 3 transactions per minute or ≤ 50 transactions per hour, the transaction frequency test passes, and then the single merchant transaction frequency test is performed. The single merchant transaction frequency test includes: Based on the user payment identity and internal merchant identity, query the order data for orders related to the current user and the current merchant within a preset period, divide the order quantity by the transaction period to obtain the transaction frequency, and determine whether the user's single merchant transaction frequency reaches the risk value; If there are more than 5 transactions every 10 minutes, it is determined that the risk value exceeds the set value, and a pop-up box will be displayed to prompt the user, and give the user a choice: continue the transaction or cancel the transaction. If the user chooses to continue the transaction, the current transaction will proceed normally, but the operation will be recorded in the database; if the user chooses to cancel the transaction, the transaction will end; If the transaction frequency is ≤ 5 per 10 minutes, the single merchant transaction frequency test is passed and the transaction amount test is continued, where the transaction amount test includes: Based on the user's payment identity, query the order data for orders related to the user within a preset period, sum up the order transaction amounts to get the total transaction amount, divide the total transaction amount by the number of orders to get the average transaction amount. If the current transaction amount is ≤ 5 times the average historical transaction amount, and the current transaction amount is ≤ 5,000 yuan, the transaction amount detection passes.

[0009] Optionally, after prompting the user for risky operations when any one of the transaction frequency, single merchant transaction frequency and transaction amount is abnormal, the method further includes: If the user chooses to continue the transaction, the operation will be marked as a risky operation, and after reaching the preset number of times, the corresponding user will be added to the blacklist. The implementation method is: User risk value calculation formula: R total =(W1×S VPN )+(W2×S freq )+(W3×S single )+(W4×S amount )+(W5×S time )+(W6×S location ); Among them, R total is the risk value, S VPNis the VPN usage, S freq is the transaction frequency, S single is the single merchant transaction frequency, S amount is the transaction amount, S time is the transaction time, S location It is the place of transaction; W1 is the weight corresponding to VPN usage, W1 is 30%, W2 is the weight corresponding to transaction frequency, W2 is 20%, W3 is the weight corresponding to the frequency of transactions for a single merchant, W3 is 15%, W4 is the weight corresponding to the transaction amount, W4 is 15%, W5 is the weight corresponding to the transaction time, W5 is 10%, W6 is the weight corresponding to the transaction location, W6 is 10%; Secondly, when the user's risk record calculation value is R total <0.3, it means that although there is a record, there is no risk. If 0.3≤R total <0.7, indicating that this is a medium-risk transaction. total ≥0.7, indicating that the transaction triggered multiple high-risk factors and was a high-risk transaction; The conditional formula that triggers blacklisting is as follows: R total_risk =α×(R cumulative / T total )+(1−α)×(N risk / N threshold ); Among them, R total_risk : Final comprehensive risk value; R cumulative_ : Current cumulative risk value; T total : The cumulative risk value threshold set; N risk : Current number of risk operations; N threshold : The set risk operation number threshold; α: Weighting coefficient, used to control the weight distribution of cumulative risk value and operation number. total_risk When ≥1, the user is added to the blacklist.

[0010] Optionally, the continuous monitoring of the merchant's transaction behavior includes: The merchant's single transaction amount limit, daily transaction amount limit, monthly transaction amount limit and transaction frequency are detected in turn, and then the transaction behavior is judged to meet the preset security standards. When the merchant triggers any limit, the transaction is canceled and the corresponding risk operation is recorded. The implementation method is: Merchant risk value calculation formula: R merchant =(W7×S single_amount )+(W8×S daily_amount )+(W9×S monthly_amount )+(W10 ×S freq )+(W 11 ×S time )+(W 12 ×S user_risk ); Among them, R merchant is the merchant risk value; S single_amount is the risk value of a single transaction amount. When the upper limit is triggered, the value is 1, and in other cases it is 0; S daily_amount is the risk value of the transaction amount on that day. When the upper limit is triggered, the value is 1, and in other cases it is 0; S monthly_amount is the risk value of the transaction amount for the month. When the upper limit is triggered, the value is 1, and in other cases it is 0; S freq is the transaction frequency risk value, which is 1 when the upper limit is triggered and 0 in other cases; S time is the transaction time risk value, and its value is divided according to the transaction time in the merchant rating (0 / 0.5 / 1); S user_risk is the user risk value. In the user main scan, this value is calculated based on the actual situation. In the user scan, this value is 0.25. W7 is the weight corresponding to the risk value of the single transaction amount. W7 is 30%. W8 is the weight corresponding to the risk value of the transaction amount on the day. W8 is 20%. W9 is the weight corresponding to the risk value of the transaction amount on the month. W9 is 15%. 10 is the weight corresponding to the transaction frequency risk value, W 10 is 20%, W 11 is the weight corresponding to the transaction time, W 11 =10%, W 12 is the weight corresponding to the user’s risk value, W 12 It is 5%.

[0011] Second, as Figure 1 As shown, this embodiment provides a system for risk control of aggregate payment transactions, the system comprising: The merchant rating module is used to comprehensively rate merchants based on multi-dimensional information when merchants submit applications, and set the merchant's single transaction amount limit, daily transaction amount limit, monthly transaction amount limit and transaction frequency limit according to the rating results; The VPN risk control module is used to obtain the IP address in the payment request when the user scans the code to pay, and compare it with the proxy IP database to determine whether the user is using the VPN proxy service. If it is detected that the user is using VPN, a risk prompt will pop up immediately, and if the user chooses to continue the transaction, the transaction operation will be marked as a risky operation; The user risk control module is used to detect whether the user is a blacklist user based on the user's payment identity when the user is making a transaction. If the user is a blacklist user, the transaction is cancelled; if the user is not a blacklist user, the user's transaction frequency, single merchant transaction frequency and transaction amount are detected in turn, and the user is prompted to perform risky operations if any of the transaction frequency, single merchant transaction frequency and transaction amount is abnormal; The device risk control module is used to determine whether the merchant's code scanning device has been put into storage by querying the database based on the device information in the payment request when the user is scanned for payment. If the code scanning device has not been put into storage, the merchant is prompted that the device is not under management and the transaction is canceled; if the code scanning device passes the storage verification, the reported IP address of the code scanning device is further verified to be consistent with the IP address in the payment request. If they are inconsistent, the merchant is prompted and the transaction is canceled; The merchant risk control module is used to detect in real time whether the merchant is on the blacklist based on the merchant number. If not, the merchant's transaction behavior is continuously monitored.

[0012] The beneficial effects of the present invention are: In view of the limitation of existing aggregate payment relying on third-party risk control, the present invention provides an autonomous and controllable risk control method that meets regulatory requirements. Through the merchant rating module, the system can monitor the merchant's transaction behavior in real time, dynamically adjust the transaction limit, and focus on monitoring large, overseas and high-risk transactions. The VPN risk control module prevents cross-border fraud, provides a complaint mechanism, and improves user experience; the user risk control module dynamically adjusts the user transaction frequency and amount limit through multi-dimensional analysis to ensure compliance; the device risk control module effectively verifies the legitimacy of the transaction equipment and prevents abnormal use of the equipment. The merchant risk control module classifies and manages high- and low-risk merchants, and combines the reward and punishment mechanism to improve the efficiency of risk control.

[0013] Through the collaborative work of independent risk control modules, acquiring institutions do not have to rely heavily on third-party payment risk control, and can enhance risk control flexibility, transparency and response speed, thereby more efficiently identifying fraudulent transactions and ensuring the financial security of users and merchants.

[0014] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or be understood by implementing the embodiments of the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0016] Figure 1 It is a schematic diagram of the system flow structure for risk control of aggregate payment transactions described in an embodiment of the present invention; Figure 2 This is a flowchart corresponding to the user risk control monitoring link in an embodiment of the present invention; Figure 3 It is a flowchart corresponding to the merchant risk control monitoring link in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0018] It should be noted that similar reference numerals or letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance. Example

[0019] This embodiment provides a method for risk control of aggregate payment transactions, the method comprising step S100, step S200, step S300, step S400 and step S500.

[0020] Among them, S100 occurs when the merchant submits the application. S200 and S300 are modules that are triggered only when the user scans the QR code. S400 is a module that is triggered only when the user is scanned (the user presents the payment code). S500 is a module that is triggered after S300 or S400 ends.

[0021] Step S100: When a merchant submits an application, the system will conduct a comprehensive scoring based on the merchant's multi-dimensional information. The multi-dimensional information includes business category, registered capital, years of operation, merchant entity, credit record and complaint status. The merchant entity can be evaluated by comprehensively evaluating the type of enterprise and the number of employees to obtain the corresponding merchant entity score of the enterprise.

[0022] The scoring system is based on the following formula: S = (A × W A )+(B×W B )+(C×W C )+(D×W D )+(E×W E )+(F×W F ); Among them, S is the total score, A is the business category score, B is the registered capital score, C is the operating years score, D is the merchant entity score, E is the credit record score, and F is the complaint score. The minimum score is 1 point and the maximum score is 5 points. The weight ratio of each item is as follows: Business category W A Accounting for 30%, registered capital W B 20% of the total, operating years W C Accounting for 20%, the merchant entity W D 15%, credit record W E 10% of the cases were complaints F Accounting for 5%.

[0023] The following are the business category scoring criteria: Business Category Rating Industry Type Risk Description 1 point The transaction amounts involved are large and the frequency is high, which can be easily exploited by criminals. High risk 2 points Complex fund flows or risk of fraud. Higher risk 3 points The transaction amount is moderate and the industry is stable, but there are certain business risks. Medium risk 4 points The industry is well regulated and supervised, and transaction amounts and frequencies are relatively stable. Lower risk 5 points Daily life services and small transactions, simple capital flow Low risk The following are the registered capital scoring criteria: Register for this score Registered paid-in capital Risk Description 1 point <500,000 RMB Poor risk resistance 2 points 500,000-1 million yuan Limited risk resistance 3 points 1 million-5 million yuan Medium risk resistance 4 points 5 million-10 million yuan High risk resistance 5 points >10 million yuan Strong risk resistance The following are the operating years scoring criteria: Years of operation rating Registered paid-in capital Risk Description 1 point <1 year Poor stability 2 points 1 year - 2 years There are certain risks 3 points 2 years - 3 years Average stability 4 points 3 years - 5 years Relatively stable 5 points >5 years Very low risk The following are the credit history scoring criteria: Credit score Credit history Risk Description 1 point Repeated breach of trust or financial default There is a great financial risk 2 points Occasional default or delay in payment There are some financial risks 3 points A few occasional delayed payments Medium financial risk 4 points No major breach of contract Lower financial risk 5 points No breach of trust or financial default Almost no financial risk The following are the complaint scoring criteria: Complaint Rating Complaints Risk Description 1 point A large number of complaints, the content of the complaints is serious Higher risk 2 points More complaints, more serious complaints There are certain risks 3 points Moderate complaint, general service issue Medium risk 4 points Few complaints, occasional minor issues Lower risk 5 points Almost no complaints, no serious problems Very low risk Through this rating system, the merchant's total score is 5.0. Based on the total score, the system divides merchants into 5 levels: Rating range grade Risk Description Greater than 4.5, less than or equal to 5 Level 5 Very low risk, excellent credit Greater than 3.5, less than or equal to 4.5 Level 4 Low risk, good credit Greater than 2.5, less than or equal to 3.5 Level 3 Medium risk, average credit Greater than 1.5, less than or equal to 2.5 Level 2 High risk, average credit Less than or equal to 1.5 Level 1 High risk, poor credit And according to the merchant's level, the system will automatically set corresponding transaction limits for it, including the upper limit of a single transaction amount, the upper limit of a daily transaction amount, the upper limit of a monthly transaction amount and the upper limit of the transaction frequency per minute.

[0024] The formula for the upper limit of a single transaction amount is: Single transaction limit = 5,000 yuan + (rating level − 1) × 3,750 yuan; From the grading standards and the formula for the upper limit of a single transaction amount, it can be seen that the upper limit of a single transaction amount fluctuates between 5,000 and 20,000 yuan.

[0025] Daily transaction limit formula: Daily transaction limit = 10,000 yuan + (rating level − 1) × 122,500 yuan; From the grading standards and the daily transaction amount upper limit formula, we can see that the daily transaction amount upper limit fluctuates between 10,000 and 500,000 yuan.

[0026] Monthly transaction limit formula: Monthly transaction limit = 200,000 yuan + (rating level − 1) × 2.45 million yuan; From the grading standards and the formula for the upper limit of monthly transaction amount, we can see that the upper limit of monthly transaction amount fluctuates between 200,000 and 10 million yuan.

[0027] Minute trading frequency cap formula: Transaction frequency limit = 30 transactions + (score level − 1) × 142.5 transactions; From the grading standards and the formula for the upper limit of transaction frequency, we can see that the upper limit of transaction frequency fluctuates between 30 and 600 transactions.

[0028] Step S200, when the user scans the code to pay, the VPN risk control module requests the VPN risk control module. The system obtains the IP address of the user's payment request according to the request header information of the http protocol (X-Forwarded-For, Proxy-Client-IP, WL-Proxy-Client-IP), and compares it with the proxy IP database. If the proxy IP is hit, it means that the user has turned on the VPN proxy (VPN proxy refers to a virtual private network proxy, which changes the user's IP address to the IP address of the proxy server through VPN technology, thereby hiding the user's real IP address). If it is turned on, a risk prompt pops up on the interface: It is detected that you are using a network proxy, which may be risky. It is recommended that you switch to a secure network to ensure the safety of funds. And give the choice: continue to use or cancel the transaction. If the user clicks to continue to use, the transaction can proceed normally, but this operation will be recorded and stored. When the risk operation reaches a certain requirement, the user may be blacklisted (the specific conditions for entering the blacklist will be elaborated in detail in S300), and the transaction is restricted. If the network proxy is not turned on and the VPN detection passes, the risk control detection continues.

[0029] Step S300: The user risk control module obtains the user's payment identity (such as WeChat openId, Alipay userId, etc.) and first checks whether the user is on the blacklist. If so, an interface pops up to prompt: Your recent transaction is detected to have a high risk. For the safety of funds, the transaction has been canceled. And give a choice: I know or I want to appeal. If the user clicks I know, the transaction interface is closed and the transaction is canceled. If the user chooses I want to appeal, the platform customer service contact information pops up. Users can get help by phone or email, and specific appeal materials need to be provided according to different situations.

[0030] If it is not in the blacklist, the transaction frequency detection is performed. Based on the user payment identity obtained, the order data is queried for orders related to the user within a certain period (within one minute and one hour). The minute transaction frequency and hour transaction frequency are obtained by dividing the number of orders by the transaction period, respectively, to determine whether the user's transaction frequency reaches the risk value (≤ 3 transactions per minute or ≤ 50 transactions per hour is a safe value, otherwise it is a risk value). If it exceeds the set risk value, a pop-up box will prompt the user: It is detected that your recent transactions are frequent. To ensure the safety of funds, please trade with caution. And give the choice: continue the transaction or cancel the transaction. If the user chooses to continue the transaction, the transaction can proceed normally, but this operation will be recorded in the warehouse. If the user chooses to cancel the transaction, the transaction ends.

[0031] After passing the transaction frequency detection, continue the single merchant transaction frequency detection. According to the obtained user payment identity and internal merchant identity, query the order data for orders related to the user and the merchant within a certain period (within ten minutes), divide the number of orders by the transaction period to get the transaction frequency, and judge whether the user's single merchant transaction frequency reaches the risk value (≤ 5 transactions per 10 minutes is a safe value, otherwise it is a risk value). If it exceeds the set risk value, a pop-up box will prompt the user: It is detected that you have made frequent transactions with this merchant recently. To ensure the safety of funds, please trade with caution. And give the choice: continue the transaction or cancel the transaction. If the user chooses to continue the transaction, the transaction can proceed normally, but this operation will be recorded in the warehouse. If the user chooses to cancel the transaction, the transaction ends.

[0032] After passing the single merchant transaction frequency detection, continue with the transaction amount detection. Based on the obtained user payment identity, query the order data for orders related to the user within a certain period (within one year), sum up the order transaction amounts to get the total transaction amount, divide the total transaction amount by the number of orders to get the average transaction amount, and judge whether the user's transaction amount reaches the risk value (the current transaction amount ≤ 5 times the average historical transaction amount, and ≤ 5,000 yuan is a safe value, otherwise it is a risk value). If it exceeds the set risk value, a pop-up box will prompt the user: Your transaction amount is detected to be large. To ensure the safety of funds, please trade with caution. And give the choice: continue the transaction or cancel the transaction. If the user chooses to continue the transaction, the transaction can proceed normally, but this operation will be recorded in the warehouse. If the user chooses to cancel the transaction, the transaction ends.

[0033] The following are the evaluation criteria for transaction frequency, single merchant transaction frequency, transaction amount, transaction time and transaction location (transaction time and transaction location are included in the blacklist scoring system, but are not included in the user risk control detection method).

[0034] Judging Criteria Low risk (0 points) Medium risk (0.5 points) High risk (1 point) Trading frequency ≤ 3 transactions per minute, or ≤ 50 transactions per hour 3-5 transactions per minute, or 50-70 transactions per hour > 5 transactions per minute, or > 70 transactions per hour Single merchant transaction frequency ≤ 5 transactions per 10 minutes 5-8 transactions per 10 minutes > 8 transactions per 10 minutes Transaction amount Current transaction ≤ 5 times the average historical transaction amount and ≤ 5,000 yuan The current transaction amount is 5-20 times the average historical transaction amount and ≤ 5,000 yuan Current transaction amount > 20 times the average historical transaction amount and > 5,000 yuan Trading Hours 11:00 - 14:0017:00 - 22:00 06:00 - 11:0014:00 - 17:0022:00 - 23:00 23:00 - 06:00 Trading location The transaction location is consistent with the historical transaction records or has little change Cross-city transactions in a short period of time, with large or frequent transactions Cross-border or cross-continental transactions in a short period of time, especially large transactions

[0035] Each risk-triggering operation of the user will be recorded and the risk value will be calculated. When the number of risky operations reaches a certain number, the user will be added to the blacklist.

[0036] The following is the formula for calculating user risk value: R total =(W1×S VPN )+(W2×S freq )+(W3×S single )+(W4×S amount )+(W5×S time )+(W6×S location ); Where R total is the risk value, S VPN is the VPN usage, S freq is the transaction frequency, S single is the single merchant transaction frequency, S amount is the transaction amount, S time is the transaction time, S location is the transaction location. W1 is the weight corresponding to VPN usage, W1 is 30%, W2 is the weight corresponding to transaction frequency, W2 is 20%, W3 is the weight corresponding to the frequency of transactions of a single merchant, W3 is 15%, W4 is the weight corresponding to the transaction amount, W4 is 15%, W5 is the weight corresponding to the transaction time, W5 is 10%, W6 is the weight corresponding to the transaction location, W6 is 10%.

[0037] According to the above formula, when the risk record calculation value of a user is R total <0.3, it means that although there is a record, there is no risk. If 0.3≤R total <0.7, indicating that this is a medium-risk transaction. total ≥0.7, indicating that the transaction triggered multiple high-risk factors and was a high-risk transaction.

[0038] The following is the conditional formula that triggers blacklisting: R total_risk =α×(R cumulative / T total )+(1−α)×(N risk / N threshold ); Among them, R total_risk : Final comprehensive risk value (used to determine whether to add the user to the blacklist). R cumulative_ : The current cumulative risk value (the cumulative risk value of multiple operations by the user). total : The cumulative risk value threshold is set to 2.5 in this system. N risk : The current number of risk operations. N threshold : The threshold of the number of risk operations set, which is set to 3 times in this system. α: Weighting coefficient, which controls the weight distribution of the cumulative risk value and the number of operations, and is set to 0.6 in this system. total_risk When ≥1, the user is added to the blacklist.

[0039] Step S400, the device risk control module, when the user is scanned, obtains the device information (device number, request IP address) in the payment request, queries the database device entry table according to the device number, and determines whether the code scanning device used by the merchant is in the warehouse. If the device is not in the warehouse, a pop-up interface prompts the merchant: It is detected that the device is not in the system management. To ensure the safety of funds, the transaction has been cancelled. If the entry detection passes, continue the device IP detection. Query the database device information table according to the device number, obtain the device registration information, and determine whether the IP address when initiating the payment request is consistent with the registered IP when the device is authenticated. If the device IP address is missing, a pop-up interface prompts the merchant: It is detected that the device is not registered. To ensure the safety of funds, the transaction has been cancelled. Please register before use. If the IP is inconsistent, a pop-up interface prompts the merchant: It is detected that the device IP is inconsistent with the registered IP. To ensure the safety of funds, the transaction has been cancelled. Please re-register.

[0040] After completing the user risk control or device risk control test, enter the merchant risk control test.

[0041] Step S500: In the merchant risk control module, by obtaining the merchant number carried in the payment request, query the merchant blacklist table in the database to determine whether the merchant is in the merchant blacklist. If it is in the blacklist, a prompt box will pop up to remind the user or merchant: the merchant status is detected to be abnormal, and the transaction has been cancelled to ensure the safety of funds. (The specific conditions for merchants to be added to the blacklist will be described in detail later).

[0042] If the merchant is not on the blacklist, the single transaction amount limit detection will continue. The merchant's single transaction limit will be queried according to the merchant number, and it will be determined whether the current transaction amount triggers the single transaction limit. If the single transaction amount exceeds the limit, a prompt box will pop up to remind the user or merchant: the merchant's single transaction limit has been detected, and the transaction has been canceled to ensure the safety of funds. And this operation will be recorded and stored.

[0043] If the single transaction amount limit test passes, the daily transaction limit test will continue. All orders of the merchant on that day will be queried according to the merchant number, and the transaction amount of the order will be summed up to get the transaction amount of the day. If the transaction amount of the day + the current transaction amount > the daily transaction limit, the transaction amount of the day exceeds the limit, and a prompt box will pop up to remind the user or merchant: the merchant's daily fund limit has been detected, and the transaction has been canceled to ensure fund safety. And this operation will be recorded and stored.

[0044] If the upper limit of the amount for the day is passed, the upper limit of the monthly transaction will be tested. All orders of the merchant for the month will be queried according to the merchant number, and the transaction amount of the order will be summed up to get the transaction amount for the month. If the transaction amount for the month + the current transaction amount > the upper limit of the monthly transaction, the transaction amount for the month exceeds the limit, and a prompt box will pop up to remind the user or merchant: the merchant's upper limit of the month has been detected, and the transaction has been canceled to ensure the safety of the funds. And this operation will be recorded and stored.

[0045] If the monthly amount limit test passes, the transaction frequency limit test will continue. All orders of the merchant within one minute will be queried according to the merchant number. If the total number of orders within one minute + 1> the transaction frequency limit, the transaction frequency exceeds the limit, and a prompt box will pop up to remind the user or merchant: the merchant has been detected to have frequent transactions, and the transaction has been canceled to ensure the safety of funds. And this operation will be recorded and stored.

[0046] The following is the merchant risk value calculation formula: R merchant =(W7×S single_amount )+(W8×S daily_amount )+(W9×S monthly_amount )+(W 10 ×S freq )+(W 11 ×S time )+(W 12 ×S user_risk ); Among them, R merchant is the merchant risk value; S single_amount is the risk value of a single transaction amount. When the upper limit is triggered, the value is 1, and in other cases it is 0; S daily_amount is the risk value of the transaction amount on that day. When the upper limit is triggered, the value is 1, and in other cases it is 0; S monthly_amount is the risk value of the transaction amount for the month. When the upper limit is triggered, the value is 1, and in other cases it is 0; S freq is the transaction frequency risk value, which is 1 when the upper limit is triggered and 0 in other cases; S time is the transaction time risk value, and its value is divided according to the transaction time in the merchant rating (0 / 0.5 / 1); S user_risk is the user risk value. In the user main scan, this value is calculated based on the actual situation. In the user scan, this value is 0.25. W7 is the weight corresponding to the risk value of the single transaction amount. W7 is 30%. W8 is the weight corresponding to the risk value of the transaction amount on the same day. W8 is 20%. W9 is the weight corresponding to the risk value of the transaction amount on the same month. W9 is 15%. 10 is the weight corresponding to the transaction frequency risk value, W 10 is 20%, W 11 is the weight corresponding to the transaction time, W 11 =10%, W 12 is the weight corresponding to the user’s risk value, W 12 It is 5%.

[0047] According to the above formula, when the merchant's risk record calculation value is R merchant <0.3, it means that the risk factors triggered by this transaction are few or no key risk factors are triggered, which is a low-risk or risk-free transaction, and the system can pass safely; if 0.3≤R merchant <0.7, indicating that such transactions have triggered more risk factors, but have not yet reached an extremely high risk level. Such transactions often involve some factors that trigger the upper limit, such as a single amount close to the upper limit or a high daily transaction amount, but still not completely beyond the safety range set by the system; if R merchant ≥0.7 indicates that such transactions have triggered multiple high-risk factors and are typical high-risk transactions. They may also exceed multiple limits such as the single transaction amount and daily transaction limit at the same time, and the transaction frequency may be abnormally high or conducted during high-risk time periods.

[0048] The following is the conditional formula that triggers blacklisting: R total_risk =α×(R cumulative / T total )+(1−α)×(N risk / N threshold ); Among them, Rtotal_risk : Final comprehensive risk value (used to determine whether to add the merchant to the blacklist); R cumulative_ : The current merchant’s cumulative risk value (the accumulation of risk values ​​triggered multiple times by the merchant). total : The cumulative risk value threshold is set to 2.5 in this system. N risk : The current number of risk triggers. N threshold : The threshold of the number of risk operations is set to 3 in this system. α: Weighting coefficient, which controls the weight distribution of the cumulative risk value and the number of operations (the value of α can be flexibly adjusted according to actual business needs. If the system pays more attention to the accumulation of a single major risk, α can be set to a larger value, such as 0.7 or 0.8. If the system pays more attention to frequent small-amount risk operations, the value of α can be reduced, such as 0.3 or 0.4). This value is set to 0.6 in this system. When the comprehensive risk value R total_risk When ≥1, the merchant is added to the blacklist.

[0049] At this point, merchant risk control is complete. System risk control checks are complete. Example

[0050] This embodiment provides a system for risk control of aggregate payment transactions, the system comprising: The merchant rating module is used to comprehensively rate merchants based on multi-dimensional information when merchants submit applications, and set the merchant's single transaction amount limit, daily transaction amount limit, monthly transaction amount limit and transaction frequency limit according to the rating results; The VPN risk control module is used to obtain the IP address in the payment request when the user scans the code to pay, and compare it with the proxy IP database to determine whether the user is using the VPN proxy service. If it is detected that the user is using VPN, a risk prompt will pop up immediately, and if the user chooses to continue the transaction, the transaction operation will be marked as a risky operation; User risk control module, such as Figure 2 As shown, when a user makes a transaction, it is used to detect whether the user is a blacklist user based on the user's payment identity identifier. If the user is a blacklist user, the transaction is canceled; if the user is not a blacklist user, the user's transaction frequency, single merchant transaction frequency and transaction amount are detected in sequence, and the user is prompted to perform risky operations if any of the transaction frequency, single merchant transaction frequency and transaction amount is abnormal; The device risk control module is used to determine whether the merchant's code scanning device has been put into storage by querying the database based on the device information in the payment request when the user is scanned for payment. If the code scanning device has not been put into storage, the merchant is prompted that the device is not under management and the transaction is canceled; if the code scanning device passes the storage verification, the reported IP address of the code scanning device is further verified to be consistent with the IP address in the payment request. If they are inconsistent, the merchant is prompted and the transaction is canceled; Merchant risk control module, such as Figure 3 As shown, it is used to detect in real time whether a merchant is in the blacklist based on the merchant ID. If not, the merchant's transaction behavior is continuously monitored.

[0051] It should be noted that, regarding the system in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0052] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for risk control of aggregate payment transactions, characterized in that: The method comprises: When merchants submit applications, we will conduct a comprehensive rating on them based on multi-dimensional information, and set the merchant's single transaction amount limit, daily transaction amount limit, monthly transaction amount limit and transaction frequency limit based on the rating results. Secondly, we will conduct regular re-evaluations based on the merchant's transaction behavior, credit record and customer complaint data in the first time period to ensure that the rating results always reflect the merchant's latest operating conditions; When the user scans the code to pay, the IP address in the payment request is obtained and compared with the proxy IP database to determine whether the user is using a VPN proxy service. If it is detected that the user is using a VPN, a risk warning will pop up immediately, and if the user chooses to continue the transaction, the transaction operation will be marked as a risky operation; When a user is making a transaction, the user is detected as a blacklist user based on the user's payment identity. If the user is a blacklist user, the transaction is canceled; if the user is not a blacklist user, the user's transaction frequency, single merchant transaction frequency and transaction amount are detected in turn, and the user is prompted to perform risky operations if any of the transaction frequency, single merchant transaction frequency and transaction amount is abnormal; When a user is scanned to pay, based on the device information in the payment request, the database is queried to determine whether the merchant's scanning device has been put into storage. If the scanning device has not been put into storage, the merchant is prompted that the device is not under management and the transaction is canceled. If the scanning device passes the storage verification, the reported IP address of the scanning device is further verified to be consistent with the IP address in the payment request. If not, the merchant is prompted and the transaction is canceled. Based on the merchant ID, it is detected in real time whether the merchant is on the blacklist. If not, the merchant's transaction behavior is continuously monitored.

2. The method for risk control of aggregate payment transactions according to claim 1, characterized in that: The comprehensive scoring of merchants based on multi-dimensional information includes: Obtain the business category, registered capital, operating years, business entity, credit record and complaint status of the merchant, and give the merchant a comprehensive score through a weighted algorithm; Among them, the scoring system is based on the following formula: S=(A×W A )+(B×W B )+(C×W C )+(D×W D )+(E×W E )+(F×W F ); S is the total score, A is the business category score, B is the registered capital score, C is the operating years score, D is the merchant entity score, E is the credit record score, and F is the complaint score. The minimum score is 1 point and the maximum score is 5 points. A is the weight corresponding to the business category, W A is 30%, W B is the weight corresponding to the registered capital, W B is 20%, W C is the weight corresponding to the operating years, W C is 20%, W D The weight corresponding to the merchant entity, W D is 15%, W E is the weight corresponding to the credit record, W E =10%, W F is the weight corresponding to the complaint situation, W F It is 5%.

3. The method for risk control of aggregate payment transactions according to claim 2, characterized in that: The merchant's single transaction amount limit, daily transaction amount limit, monthly transaction amount limit and transaction frequency limit are set based on the scoring results, including: Rating merchants based on the scores, and then obtaining the corresponding score level of the merchants, and setting the merchant's single transaction amount limit, daily transaction amount limit, monthly transaction amount limit and transaction frequency limit based on the score level; The formula for the upper limit of a single transaction amount is: upper limit of a single transaction = 5,000 yuan + (rating level − 1) × 3,750 yuan. The upper limit of a single transaction amount ranges from 5,000 to 20,000 yuan. The formula for the upper limit of daily transaction amount is: upper limit of daily transaction amount = 10,000 yuan + (score level − 1) × 122,500 yuan. The upper limit of daily transaction amount fluctuates between 10,000 yuan and 500,000 yuan. Monthly transaction limit formula: Monthly transaction limit = 200,000 yuan + (score level − 1) × 2.45 million yuan, the floating range of the monthly transaction limit is 200,000 to 10 million yuan; The formula for the upper limit of minute transaction frequency is as follows: upper limit of transaction frequency = 30 transactions + (score level − 1) × 142.5 transactions. The upper limit of transaction frequency ranges from 30 to 600 transactions.

4. The method for risk control of aggregate payment transactions according to claim 1, characterized in that: If it is detected that the user is using a VPN, a risk prompt will be popped up immediately, and if the user chooses to continue the transaction, the transaction operation will be marked as a risky operation, and the following also includes: When the number of risky operations of a user reaches the preset threshold, the user will be blacklisted and subsequent transactions will be restricted.

5. The method for risk control of aggregate payment transactions according to claim 1, characterized in that: The sequential detection of the user's transaction frequency, the single merchant's transaction frequency and the transaction amount includes: Based on the user payment identity, query the order data for orders related to the user within a preset period, and divide the number of orders by the transaction period to obtain the minute transaction frequency and hour transaction frequency respectively; Based on the minute transaction frequency and hour transaction frequency, determine whether the user's transaction frequency reaches the risk value. If it is > 3 transactions per minute or > 50 transactions per hour, a pop-up window will prompt the user and give the choice: continue the transaction or cancel the transaction. If the user chooses to continue the transaction, the operation will be recorded in the database; if the user chooses to cancel the transaction, the transaction will end; Based on the minute transaction frequency and hourly transaction frequency, determine whether the user's transaction frequency reaches the risk value. If it is ≤ 3 transactions per minute or ≤ 50 transactions per hour, the transaction frequency test passes, and then the single merchant transaction frequency test is performed. The single merchant transaction frequency test includes: Based on the user payment identity and internal merchant identity, query the order data for orders related to the current user and the current merchant within a preset period, divide the order quantity by the transaction period to obtain the transaction frequency, and determine whether the user's single merchant transaction frequency reaches the risk value; If there are more than 5 transactions every 10 minutes, it is determined that the risk value exceeds the set value, and a pop-up box will be displayed to prompt the user, and give the user a choice: continue the transaction or cancel the transaction. If the user chooses to continue the transaction, the current transaction will proceed normally, but the operation will be recorded in the database; if the user chooses to cancel the transaction, the transaction will end; If the transaction frequency is ≤ 5 per 10 minutes, the single merchant transaction frequency test is passed and the transaction amount test is continued, where the transaction amount test includes: Based on the user's payment identity, query the order data for orders related to the user within a preset period, sum up the order transaction amounts to get the total transaction amount, divide the total transaction amount by the number of orders to get the average transaction amount. If the current transaction amount is ≤ 5 times the average historical transaction amount, and the current transaction amount is ≤ 5,000 yuan, the transaction amount detection passes.

6. The method for risk control of aggregate payment transactions according to claim 1, characterized in that: After prompting the user for risky operations when any of the transaction frequency, single merchant transaction frequency and transaction amount is abnormal, the method further includes: If the user chooses to continue the transaction, the operation will be marked as a risky operation, and after reaching the preset number of times, the corresponding user will be added to the blacklist. The implementation method is: User risk value calculation formula: R total =(W1×S VPN )+(W2×S freq )+(W3×S single )+(W4×S amount )+(W5×S time )+(W6×S location ); Among them, R total is the risk value, S VPN is the VPN usage, S freq is the transaction frequency, S single is the single merchant transaction frequency, S amount is the transaction amount, S time is the transaction time, S location It is the place of transaction; W1 is the weight corresponding to VPN usage, W1 is 30%, W2 is the weight corresponding to transaction frequency, W2 is 20%, W3 is the weight corresponding to the frequency of transactions for a single merchant, W3 is 15%, W4 is the weight corresponding to the transaction amount, W4 is 15%, W5 is the weight corresponding to the transaction time, W5 is 10%, W6 is the weight corresponding to the transaction location, W6 is 10%; Secondly, when the user's risk record calculation value is R total <0.3, it means that although there is a record, there is no risk. If 0.3≤R total <0.7, indicating that this is a medium-risk transaction. total ≥0.7, indicating that the transaction triggered multiple high-risk factors and was a high-risk transaction; The conditional formula for triggering blacklisting: R total_risk =α×(R cumulative / T total )+(1−α)×(N risk / N threshold ); Among them, R total_risk : Final comprehensive risk value; R cumulative_ : Current cumulative risk value; T total : The cumulative risk value threshold set; N risk : Current number of risk operations; N threshold : The set risk operation number threshold; α: Weighting coefficient, used to control the weight distribution of cumulative risk value and operation number. total_risk When ≥1, the user is added to the blacklist.

7. The method for risk control of aggregate payment transactions according to claim 1, characterized in that: The continuous monitoring of merchant transaction behaviors includes: The merchant's single transaction amount limit, daily transaction amount limit, monthly transaction amount limit and transaction frequency are detected in turn, and then the transaction behavior is judged to meet the preset security standards. When the merchant triggers any limit, the transaction is canceled and the corresponding risk operation is recorded. The implementation method is: Merchant risk value calculation formula: R merchant =(W7×S single_amount )+(W8×S daily_amount )+(W9×S monthly_amount )+(W 10 ×S freq )+(W 11 ×S time )+(W 12 ×S user_risk ); Among them, R merchant is the merchant risk value; S single_amount is the risk value of a single transaction amount. When the upper limit is triggered, the value is 1, and in other cases it is 0; S daily_amount is the risk value of the transaction amount on that day. When the upper limit is triggered, the value is 1, and in other cases it is 0; S monthly_amount is the risk value of the transaction amount for the month. When the upper limit is triggered, the value is 1, and in other cases it is 0; S freq is the transaction frequency risk value, which is 1 when the upper limit is triggered and 0 in other cases; S time is the transaction time risk value, and its value is divided according to the transaction time in the merchant rating (0 / 0.5 / 1); S user_risk is the user risk value. In the user main scan, this value is calculated based on the actual situation. In the user scan, this value is 0.

25. W7 is the weight corresponding to the risk value of the single transaction amount. W7 is 30%. W8 is the weight corresponding to the risk value of the transaction amount on the day. W8 is 20%. W9 is the weight corresponding to the risk value of the transaction amount on the month. W9 is 15%. 10 is the weight corresponding to the transaction frequency risk value, W 10 is 20%, W 11 is the weight corresponding to the transaction time, W 11 =10%, W 12 is the weight corresponding to the user’s risk value, W 12 It is 5%.

8. A system for risk control of aggregate payment transactions, characterized in that: The system comprises: The merchant rating module is used to comprehensively rate merchants based on multi-dimensional information when merchants submit applications, and set the merchant's single transaction amount limit, daily transaction amount limit, monthly transaction amount limit and transaction frequency limit according to the rating results; The VPN risk control module is used to obtain the IP address in the payment request when the user scans the code to pay, and compare it with the proxy IP database to determine whether the user is using the VPN proxy service. If it is detected that the user is using VPN, a risk prompt will pop up immediately, and if the user chooses to continue the transaction, the transaction operation will be marked as a risky operation; The user risk control module is used to detect whether the user is a blacklist user based on the user's payment identity when the user is making a transaction. If the user is a blacklist user, the transaction is cancelled; if the user is not a blacklist user, the user's transaction frequency, single merchant transaction frequency and transaction amount are detected in turn, and the user is prompted to perform risky operations if any of the transaction frequency, single merchant transaction frequency and transaction amount is abnormal; The device risk control module is used to determine whether the merchant's code scanning device has been put into storage by querying the database based on the device information in the payment request when the user is scanned for payment. If the code scanning device has not been put into storage, the merchant is prompted that the device is not under management and the transaction is canceled; if the code scanning device passes the storage verification, the reported IP address of the code scanning device is further verified to be consistent with the IP address in the payment request. If they are inconsistent, the merchant is prompted and the transaction is canceled; The merchant risk control module is used to detect in real time whether the merchant is on the blacklist based on the merchant number. If not, the merchant's transaction behavior is continuously monitored.

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