A big data service system for payment settlement

Abstract

The present invention provides a big data service system for payment and settlement, including a user module, a transaction module, a card management module, an information service module encryption module, a bank module, a risk assessment module, and an information feedback module. The farmer merchant makes a request for payment and settlement, and the third party reviews the payment and settlement request and makes a transaction record. At the same time, a transaction network about the farmer merchant is constructed according to the transaction record; the risk assessment module is used to conduct risk assessment, and after confirming the risk situation, it is sent to the merchant and the farmer, and the merchant and the farmer further confirm the transaction and obtain a transaction voucher with signatures of both parties; the third party institution processes the user's payment and settlement request according to the legality of the transaction voucher, assists in completing the transaction, and after the transaction is completed, the farmer merchant provides information feedback on the transaction situation, and makes a risk assessment record according to the feedback situation. The technical problem that the sole right in the prior art can solve the inconvenience of payment and settlement and the low security is solved.

Description

Technical Field

[0001] The present invention relates to the fields of agricultural product trading and big data technology, and in particular to a big data service system for payment and settlement. Background Art

[0002] Zhu Guangyuan et al. proposed "2017114494937," a "market payment and settlement management system." Through the client's personal center module, sellers can manage their personal information. The transaction inquiry module provides buyers with a portal to query their transactions and easily view their transaction records anytime, anywhere. The membership card management module facilitates card binding and unbinding between buyers and sellers, allowing them to rebind their virtual accounts after changing cards. The points viewing module provides buyers with a convenient way to check their points, and additionally allows them to view their points consumption and historical accumulation. The transfer payment module allows buyers to transfer funds directly to merchants they have previously transacted with, without using a QR code. The message receiving module receives new promotional offers from sellers. The scan code payment module allows transactions to be made by providing a QR code. Buyers use a mobile app to open the QR code payment, generating a payment code. This code is scanned by a handheld device and the buyer enters the transaction password to complete the transaction. This transaction involves transferring money between virtual accounts.

[0003] However, the inventors of this application found that the above technology has at least the following technical problems in the process of implementing the technical solution of the invention in the embodiment of this application: payment settlement is not convenient, security is not high, Summary of the Invention

[0004] The present invention solves the technical problems in the prior art that only the payment settlement is inconvenient and the security is low by providing a big data service method supporting the payment and settlement of agricultural products, and achieves the technical effects of more convenient payment and settlement and safer payment and settlement.

[0005] The present invention provides a big data service system supporting payment and settlement of agricultural products, which specifically includes the following technical solutions:

[0006] A big data service system supporting agricultural product payment and settlement includes the following parts:

[0007] User module, transaction module, card management module, information service module, encryption module, bank module, risk assessment module, information feedback module;

[0008] The transaction module includes a transaction query component, a transaction report component, and a transaction cancellation component. The transaction query component provides merchants and farmers with an entry point for personal transaction inquiry. The transaction cancellation component has a transaction cancellation function, allowing merchants to cancel transactions for the day. The transaction report component is used for merchants and farmers to compile daily transaction data.

[0009] The encryption module uses the elliptic curve encryption algorithm and the DES and RSA hybrid encryption algorithm to encrypt the verification code and QR code that appear in the transaction;

[0010] The bank module is used to build virtual accounts for merchants and farmers, through which transactions between the virtual accounts of merchants and farmers are carried out;

[0011] The risk assessment module uses artificial intelligence to conduct self-learning based on historical data samples, establishes risk assessment thresholds for key indicators, and predicts the risk level and scope of violations of the inspection objects, providing a basis for the selection of inspection objects and the implementation of targeted off-site supervision;

[0012] The information feedback module enables merchants and farmers to evaluate and provide feedback to their counterparties after the transaction is completed, providing a basis for the risk assessment module.

[0013] A big data service method supporting agricultural product payment and settlement includes the following steps:

[0014] S1. The agricultural merchant submits a payment settlement request. The third party reviews the payment settlement request and creates a transaction record based on the relevant information submitted. The third party also builds a transaction network for the agricultural merchant based on the transaction record.

[0015] S2. Once the payment settlement request is approved by a third-party institution, a risk assessment module is used to conduct a risk assessment. After confirming the risk situation, the request is sent to the merchant and farmer. The merchant and farmer then confirm the transaction and obtain a transaction voucher signed by both parties.

[0016] S3. The third-party institution shall process the user's payment settlement request based on the legitimacy of the transaction voucher and assist in completing the transaction. After the transaction is completed, the agricultural merchant shall provide feedback on the transaction status, and risk assessment records shall be made based on the feedback to provide a reference basis for building a transaction network for subsequent transactions.

[0017] Furthermore, the step S1 includes:

[0018] In the payment and settlement service system, all farmers and merchants are numbered and a collection of farmer accounts is obtained.

[0019] ID f ={ID f1 , ID f2 ,..,ID fn}, where ID fi represents the i-th farmer account, n represents the number of farmers; ID b ={lD b1 ID b2 , ...., ID bm} is a merchant account collection, where ID bj represents the jth merchant account, and m represents the number of merchants;

[0020] By using the accounts of each merchant and farmer and the degree of correlation between them, a closeness relationship model is constructed to provide a basis for third parties to distinguish between merchants and farmers;

[0021] The closeness relationship model is constructed as follows:

[0022] Mode c ={ID f , ID b , Con f&b , Net f , Net b}

[0023] Among them, ID f Indicates the farmer account set; ID b Represents a collection of merchant accounts;

[0024] Con f&b Represents the closeness matrix of transactions between farmers and merchants, that is

[0025]

[0026] C ij Indicates the closeness between the ith farmer and the ith merchant; Net f Represents the farmer's network set; Net b Represents the set of merchant relationship networks; overlapping areas between two relationship networks indicate that there is a mutual payment and settlement relationship between the two.

[0027] Furthermore, the step S1 includes:

[0028] When conducting agricultural product transactions, after the merchant submits an application, the security verification code is fed back to further confirm the transaction application, and the security verification code is encrypted using an elliptic curve encryption algorithm; when the farmer makes a payment settlement request, the farmer forwards the transaction payment details QR code and the payment request to a third-party agency for verification and proofreading. When the inspection is correct, the merchant makes the payment; the payment details QR code uses an encryption module to first add a timestamp and the close relationship between the merchant and the farmer as a first encryption, and then uses a DES and RSA hybrid encryption algorithm to double-encrypt the QR code.

[0029] Further, the step S2 includes:

[0030] Based on the personal application information submitted by the agricultural merchants and their historical transaction profiles, a five-dimensional credit assessment model is constructed for the agricultural merchants, as follows:

[0031]

[0032] Among them, ID s Represents the personal information collection of the sth farmer / merchant; BQ s represents the weight set corresponding to the personal information of the sth agricultural merchant; TR s Represents the transaction payment record set of the sth user;

[0033] Represents the relationship network set of the s-th farmer and merchant; Out s Represents the risk profile of the sth agricultural merchant.

[0034] Further, the step S3 includes:

[0035] After the transaction is completed, the third-party institution will record the transaction relationship and feedback information of the farmer-merchant, update the transaction relationship network of the farmer-merchant, and update the credit assessment model of the risk assessment module based on the recorded information, gradually improving the entire big data service system that supports the payment and settlement of agricultural products.

[0036] The present invention has at least the following technical effects or advantages:

[0037] 1. The present invention constructs a close relationship model between farmers and merchants, builds a relationship network based on the closeness between the two, and provides a favorable basis for convenient payment and settlement.

[0038] 2. The present invention encrypts the security verification code using the elliptic curve encryption algorithm to prevent information leakage, thereby ensuring the security of transactions and improving the security of system payment transaction settlement.

[0039] 3. The present invention double-encrypts the payment transaction QR code to form a second layer of protection barrier during the transaction process, thereby increasing the security of the system.

[0040] 4. The present invention conducts risk assessment on farmers / merchants by jointly building a credit assessment model, providing a safe basis for transactions, avoiding unnecessary risks, and making payment settlement more convenient. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a structural block diagram of a big data service system supporting agricultural product payment and settlement according to the present invention;

[0042] Figure 2 This is a flow chart of a big data service method supporting payment and settlement of agricultural products according to the present invention. DETAILED DESCRIPTION

[0043] The technical solution in the embodiments of the present application is to solve the above-mentioned technical problems of inconvenient payment settlement and low security. The overall idea is as follows:

[0044] First, merchants and farmers register accounts in the system through the user module and add the required transaction cards. The farmers and merchants submit payment settlement requests. The bank module (third-party institution) reviews the received payment settlement requests and records the transactions based on the relevant information submitted in the application. At the same time, a transaction network for farmers and merchants is constructed based on the transaction records. At the same time, the encryption module is used to encrypt the verification code and payment QR code that appear during the transaction. Further, when the payment settlement request is reviewed and approved by the third-party institution, the risk assessment module is used to conduct a risk assessment. After confirming the risk situation, it is sent to the merchants and farmers. The merchants and farmers further confirm the transaction and obtain a transaction voucher with signatures of both parties. After obtaining the transaction voucher with signatures of both farmers and merchants, the third-party institution processes the user's payment settlement request based on the legality of the transaction voucher and assists in completing the transaction. After the transaction is completed, the farmers and merchants provide feedback on the transaction situation, and record the risk assessment based on the feedback to provide a reference for building a transaction network for subsequent transactions. The technical solution of the present invention can effectively solve the technical problems of inconvenient payment and settlement and low security. In addition, the above-mentioned system has undergone a series of effect surveys. By constructing a close relationship model between farmers and merchants, a relationship network is constructed according to the closeness between the two, which provides a favorable basis for convenient payment and settlement; by encrypting the security verification code using the elliptic curve encryption algorithm to prevent information leakage, the security of the transaction is guaranteed, and the security of the system payment transaction settlement is improved; by doubly encrypting the payment transaction QR code, a second layer of protection barrier is formed during the transaction process, which increases the security of the system; by jointly building a credit assessment model to conduct risk assessment on farmers / merchants, a security basis is provided for transactions, unnecessary risks are avoided, and payment and settlement are made more convenient.

[0045] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0046] Refer to the attached Figure 1 , a big data service system supporting agricultural product payment and settlement, mainly includes the following parts:

[0047] User module 010, transaction module 020, card management module 030, information service module 040, encryption module 050, bank module 060, risk assessment module 070, information feedback module 080.

[0048] The user module 010 includes a farmer and merchant module, which is used to record personal information and manage personal information accounts. In this module, account details and message notifications can be queried;

[0049] The transaction module 020 includes transaction query, transaction report, and transaction cancellation components. The transaction query component provides merchants and farmers with a portal for personal transaction query, allowing them to conveniently view their transaction records anytime and anywhere. On the other hand, the transaction function allows merchants to directly transfer money to farmers they have previously traded with, or to conduct transactions by providing a QR code. Farmers use a mobile phone app to open the QR code payment and generate a payment code. After scanning the payment code with a handheld device, the merchant enters the transaction password to complete the transaction. This transaction process involves transferring money between virtual accounts. The transaction cancellation component has a transaction cancellation function, allowing merchants to cancel transactions for the day. The transaction report component helps merchants and farmers compile daily transaction data.

[0050] The card management module 030 queries the card binding information and facilitates the binding and unbinding of cards by buyers and sellers, so that they can rebind their virtual accounts after changing cards;

[0051] The message service module includes receiving new messages from buyers and sellers, receiving messages from relevant agricultural product markets and other institutions, and timely understanding of agricultural product market trends and relevant payment information of agricultural product markets; setting module, inter-bank transfer module and one-click help module;

[0052] The encryption module 050 uses the elliptic curve encryption algorithm and the DES and RSA hybrid encryption algorithm to encrypt the verification code and QR code that appear in the transaction;

[0053] The bank module 060, i.e., a third-party institution, is used to build virtual accounts for merchants and farmers, through which transactions between the virtual accounts of merchants and farmers are carried out;

[0054] The risk assessment module 070 uses artificial intelligence to conduct self-learning based on historical data samples, establishes risk warning thresholds for key indicators, and predicts the risk level and scope of violations of the inspection objects, providing a basis for the selection of inspection objects and the implementation of targeted off-site supervision;

[0055] The information feedback module 080 allows merchants and farmers to evaluate and provide feedback to their counterparties after the transaction is completed, providing a basis for the risk assessment module 070.

[0056] As a specific embodiment, a method for executing a big data service supporting payment and settlement of agricultural products includes the following steps:

[0057] S1. The agricultural merchant submits a payment settlement request. The third party reviews the payment settlement request and creates a transaction record based on the relevant information submitted. The third party also builds a transaction network for the agricultural merchant based on the transaction record.

[0058] S11. Both the buyer and seller, i.e., the merchant and the farmer, register their information with a third-party institution (bank). The third-party institution acts as a payment and settlement intermediary between the two parties to ensure transaction security.

[0059] In this system, all farmers and merchants apply for accounts and obtain collective IDs. f and ID b ,in,

[0060] ID f ={ID f1 , ID f2 ,...,ID fn}, where ID fi represents the i-th farmer account, n represents the number of farmers; ID b ={ID b1 , ID b2 ,...,ID bm}, where ID bj represents the j-th merchant account, and m represents the number of merchants.

[0061] Through the accounts of various merchants and farmers and the degree of correlation between them, a closeness relationship model is constructed to provide a basis for third parties to distinguish between merchants and farmers.

[0062] The closeness relationship model is constructed as follows:

[0063] Mode c ={ID f , ID b , Con f&b , Net f , Net b}

[0064] Among them, ID f Indicates the farmer account set; ID b Represents a collection of merchant accounts;

[0065] Con f&b Represents the closeness matrix of transactions between farmers and merchants, that is

[0066]

[0067] C ij Indicates the closeness between the ith farmer and the ith merchant; Net f Represents the farmer's network set; Net b Represents the set of merchant relationship networks; overlapping parts of two relationship networks indicate that there is a mutual payment and settlement relationship between the two, and both merchant and farmer accounts can be one-to-many.

[0068] Furthermore, in the era of big data, the number of merchants and farmers is huge, and it is sufficient to perform addition and deletion management operations on the number sets of merchants and farmers in the input of the closeness relationship model.

[0069] The present invention constructs a close relationship model between farmers and merchants, builds a relationship network according to the closeness between the two, provides a favorable basis for convenient payment and settlement, and provides cheapness in the big data era.

[0070] S12. When submitting a payment settlement application, one must submit one's own account information, transaction details, and partial information about the other party's account. This will allow the payment settlement system to retain transaction records, establish a network between farmers and merchants, and facilitate subsequent transactions and cooperation.

[0071] As a specific embodiment, when conducting agricultural product transactions, when the merchant ID bj When submitting a payment transaction application, the bank payment settlement system obtains the payment settlement application and sends the merchant ID bj The merchant then uses this feedback to further verify the payment transaction application. Once the verification is complete, the third-party institution (i.e., the bank) will provide a security verification code (SMS verification code) based on the merchant's information to further verify the transaction application. The security verification code is the security verification code sent by the third-party institution upon receiving the merchant's payment transaction application to confirm the transaction information.

[0072] Optionally, during a transaction, the merchant can automatically generate a payment QR code and encrypt it using an encryption module to ensure the security of the payment transaction.

[0073] The security verification code is encrypted using an elliptic curve encryption algorithm to prevent information leakage and ensure the security of the transaction.

[0074] The present invention encrypts the security verification code using the elliptic curve encryption algorithm to prevent information leakage, thereby ensuring the security of transactions and improving the security of system payment transaction settlement.

[0075] As a specific embodiment, when conducting agricultural product transactions, the merchant ID bj Make a payment settlement request, which needs to be submitted. The third-party agency will send the request to the farmer ID that needs to conduct the transaction. fi Farmers verify and proofread the payment QR code and payment request of the transaction payment details forwarded by the third-party agency, and make payment when they are correct.

[0076] The payment details QR code is encrypted by an encryption module to ensure the security of the payment transaction.

[0077] Preferably, when encrypting the generated QR code, the encryption module first adds a timestamp and the degree of closeness between merchants and farmers to the QR code as a first encryption, and then uses the DES and RSA hybrid encryption algorithm to perform a second encryption on the QR code. During the implementation of the DES and RSA hybrid encryption algorithm, the DES encryption key K is first generated, and the DES key K is encrypted using the public encryption key of the RSA encryption algorithm to form a DES encryption key Ck, and saved. The generated key Ck is used to perform DES encryption on the plaintext P to generate a ciphertext, and then the encrypted key is further decrypted using the DES algorithm, and the DES key is decrypted using the RSA algorithm to obtain the encryption key Ck, and the DES key Ck is decrypted using the RSA decryption key to form a DES decryption key K, and the ciphertext C is decrypted using the generated key K to generate a plaintext file.

[0078] The present invention double-encrypts the payment transaction QR code to form a second layer of protection barrier during the transaction process, thereby increasing the security of the system.

[0079] S2. Once the payment settlement request is approved by a third-party institution, a risk assessment module is used to conduct a risk assessment. After confirming the risk, the request is sent to the merchant and farmer. The merchant and farmer then confirm the transaction and obtain a transaction voucher signed by both parties.

[0080] S21. After reviewing the settlement application, the risk assessment module is used to assess the transaction risk and the assessment results are sent to the user module via the information feedback module;

[0081] Based on the personal application information submitted by farmers / merchants and their historical transaction profiles, a five-dimensional credit assessment model is constructed for farmers / merchants, as follows:

[0082]

[0083] Among them, ID s Represents the personal information collection of the sth farmer / merchant; BQ s represents the weight set corresponding to the personal information of the sth farmer / merchant; TR s Represents the transaction payment record set of the sth user; Represents the relationship network set of the sth farmer / merchant; Out s Represents the risk profile of the sth farmer / merchant.

[0084]

[0085] It represents a two-dimensional impulse function constructed for the transaction record set and the farmer / merchant transaction network set. After the above formula is applied, the risk profile of the farmer / merchant can be obtained. Setting thresholds τ1 and τ2 will have an impact on the model result Out s The value of Out s >τ2, the farmer / merchant is at high risk; when τ1<Out s <τ2, the farmer / merchant has a moderate risk; when Out s When <τ1, the farmer / merchant has low risk (no risk).

[0086] The present invention conducts risk assessment on farmers / merchants by jointly building a credit assessment model, provides a safe basis for transactions, avoids unnecessary risks, and makes payment settlement more convenient.

[0087] S22. After the risk assessment is completed, the merchant / farmer will store the virtual amount of the payment transaction in a third-party institution, which will then send the transaction application to the other party. After confirming that it is correct, the merchant / farmer will confirm the transaction and obtain a transaction voucher signed by both parties.

[0088] S3. After obtaining the transaction voucher signed by both the farmer and the merchant, the third-party institution verifies the legitimacy of the transaction voucher, processes the user's payment settlement request, and assists in completing the transaction. After the transaction is completed, the farmer and the merchant provide feedback on the transaction status, and risk assessment records are recorded based on the feedback, providing a reference basis for building a transaction network for subsequent transactions.

[0089] After the transaction is completed, the transaction relationship and feedback information of the farmer / merchant will be recorded in a third-party institution, the transaction relationship network of farmers and merchants will be updated, and the credit assessment model of the risk assessment module will be updated based on the recorded information, gradually improving the entire big data system supporting agricultural product payment and settlement.

[0090] Refer to the attached Figure 2 , thus completing a specific implementation method of a big data service system that supports payment and settlement of agricultural products.

[0091] Effect research:

[0092] The technical solution of the present invention can effectively solve the technical problems of inconvenient payment and settlement and low security. In addition, the above-mentioned system has undergone a series of effect surveys. By constructing a close relationship model between farmers and merchants, a relationship network is constructed according to the closeness between the two, which provides a favorable basis for convenient payment and settlement; by encrypting the security verification code using the elliptic curve encryption algorithm to prevent information leakage, the security of the transaction is guaranteed, and the security of the system payment transaction settlement is improved; the present invention forms a second layer of protection barrier during the transaction process by double encrypting the payment transaction QR code, thereby increasing the security of the system; by jointly building a credit assessment model to conduct risk assessment on farmers / merchants, a security basis is provided for transactions, unnecessary risks are avoided, and payment and settlement are made more convenient.

[0093] 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.

[0094] 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 A step that specifies a function in one or more boxes.

[0095] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0096] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A big data service method for supporting payment and settlement of agricultural products, characterized in that: The following steps are involved: S1. When the agricultural merchant makes a payment settlement request, the third party reviews the payment settlement request received, retains the transaction record based on the relevant information of the submitted application, and builds a closeness relationship model based on the transaction record. The construction process of the closeness relationship model is as follows: Mode c ={ID f ,ID b ,Con f&b ,Net f ,Net b } ID f ={ID f1 ,ID f2 ,...,ID fn , ID b ={ID b1 ,ID b2 ,...,ID bm , Among them, ID f Indicates the farmer account set, ID fi represents the i-th farmer account, n represents the number of farmers; ID b Indicates a collection of merchant accounts, ID bj represents the jth merchant account, m represents the number of merchants; Con f&b It represents the closeness matrix of transactions between farmers and merchants. The specific calculation formula is as follows: C ij Indicates the closeness between the ith farmer and the ith merchant; Net f Represents the farmer's network set; Net b Represents the set of merchant relationship networks; the overlap between two relationship networks indicates that there is a mutual payment and settlement relationship between the two. A trading network for farmers and merchants is established based on the closeness between farmers and merchants; when conducting agricultural product transactions, after the merchant submits an application, the transaction application is further confirmed based on the security verification code obtained in the feedback, and the security verification code is encrypted using an elliptic curve encryption algorithm; the transaction payment details QR code and payment request forwarded by the farmer to the third-party institution are verified and proofread, and when the inspection is correct, the merchant makes the payment; the payment details QR code uses an encryption module to first add a timestamp and the closeness between the merchant and the farmer as a first encryption, and then the QR code is double-encrypted using a DES and RSA hybrid encryption algorithm; S2. When the payment settlement request is approved by the third-party institution, a five-dimensional credit assessment model is constructed using the risk assessment module based on the personal application information submitted by the farmer merchant and the historical transaction profile for risk assessment. After confirming the risk situation, it is sent to the merchant and the farmer. The merchant and the farmer further confirm the transaction and obtain a transaction voucher with signatures of both parties. The five-dimensional credit assessment model is constructed as follows: Among them, ID s represents the personal information set of the sth farmer / merchant; BQ s represents the weight set corresponding to the personal information of the sth farmer and merchant; TR s Represents the transaction payment record set of the sth user; Out represents the network set of the sth farmer and merchant; s represents the risk profile of the sth agricultural merchant; S3. The third-party institution processes the user's payment settlement request based on the legitimacy of the transaction voucher and assists in completing the transaction. After the transaction is completed, the farmer merchant will provide feedback on the transaction status and make risk assessment records based on the feedback to provide a reference for building a transaction network for subsequent transactions.

2. A big data service method for supporting payment and settlement of agricultural products as claimed in claim 1, characterized in that: The step S3 comprises: After the transaction is completed, the third-party institution will record the transaction relationship and feedback information of the farmer-merchant, update the transaction relationship network of the farmer-merchant, and update the credit assessment model of the risk assessment module based on the recorded information, gradually improving the entire big data service system supporting the payment and settlement of agricultural products.

3. A big data service system supporting payment and settlement of agricultural products, used to implement the big data service method supporting payment and settlement of agricultural products as claimed in claim 1, characterized in that: Includes the following sections: User module, transaction module, card management module, information service module, encryption module, bank module, risk assessment module, information feedback module; The transaction module includes a transaction query component, a transaction report component and a transaction cancellation component; the transaction query component is an entry for merchants and farmers to query their transactions; the transaction cancellation component has a transaction cancellation function, and merchants can cancel transactions on the same day; the transaction report component is used for merchants and farmers to compile daily transaction data; The encryption module uses an elliptic curve encryption algorithm and a DES and RSA hybrid encryption algorithm to encrypt the verification code and the QR code that appear in the transaction; The bank module is used to build virtual accounts of merchants and farmers, through which transactions between the virtual accounts of merchants and farmers are transferred; The risk assessment module uses artificial intelligence to conduct self-learning based on historical data samples, establishes key indicator risk assessment thresholds, predicts the risk level and violation scope of the inspection object, and provides a basis for the selection of inspection objects and targeted off-site supervision; The information feedback module allows merchants and farmers to evaluate and provide feedback to their counterparties after the transaction is completed, providing a basis for the risk assessment module.

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