Enterprise digital operation application aggregation platform based on software as service (SAAS) software

Abstract

The invention relates to the technical field of intelligent digital operation, and discloses an enterprise digital operation application aggregation platform based on SAAS software, and the platform comprises a registration authentication module which is used for carrying out account registration and operation subject authentication management; the payment acquisition module is used for transaction acquisition, product management, transaction risk assessment, transaction data encryption and fund clearing; the data statistics module is used for collecting, monitoring and counting the operation data in real time; the operation management module is used for managing orders before and after sales of products; and the message reminding module is used for reminding the system message and the transaction message. According to the invention, the transaction data can be encrypted in a targeted manner, the transaction security and the system performance are both considered, the transaction security is improved, the resource utilization rate is improved, and the performance loss is reduced.

Description

Technical Field

[0001] The present invention relates to the field of smart digital business technology, and in particular to an enterprise digital business application aggregation platform based on SAAS software. Background Art

[0002] SAAS is Software as a Service, and its full English name is Software as a Server. The concept of SAAS is that the cloud has already set up the operating system, the operating environment, and the software client. The user does not need to install any environment or software, and can directly use it by accessing the client. Empowering small and medium-sized enterprises to transform their business into digital ones refers to the use of digital technologies (such as the Internet of Things, cloud computing, edge computing, artificial intelligence, etc.) and data-driven strategies to comprehensively reshape and optimize the business models, processes, products and services of small and medium-sized enterprises to promote fundamental changes in their business methods. This process involves not only technical upgrades, but also changes in organizational structure, corporate culture, talent management, and other aspects.

[0003] Existing small and medium-sized enterprises face the problem of data loss of multiple digital products when using products and services provided by different digital transformation service providers, especially the loss of transaction data, which poses a major data security risk. In the prior art, although there are methods for predicting transaction risks by using neural network models, due to the large amount of transaction data and the different risk situations corresponding to different transaction types, using multiple models for separate training not only results in parameter redundancy, but also requires training each model and adjusting parameters separately, increasing model training time, and also causes different tasks to be unable to share learned information with each other, resulting in poor consistency in model result output, thereby reducing the accuracy of the output results. In addition, the prior art usually only considers the characteristics of the transaction data itself. Due to the complexity and variability of transaction information, it is difficult to identify subtle anomalies between different transactions by only considering the characteristics of the transaction data itself, resulting in potential fraud behaviors that are difficult to predict, and thus it is impossible to perform encryption in a targeted manner, resulting in insufficient transaction security. However, if a higher level of encryption is used for all transaction information, it will lead to a waste of system resources, thereby reducing system performance and causing poor user experience.

[0004] Therefore, there is an urgent need for an enterprise digital business application aggregation platform based on SAAS software that can encrypt transaction data in a targeted manner, take into account both transaction security and system performance, improve transaction security, increase resource utilization, and reduce performance loss. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides an enterprise digital business application aggregation platform based on SAAS software, which can encrypt transaction data in a targeted manner, take into account transaction security and system performance, improve transaction security, improve resource utilization, and reduce performance loss.

[0006] The present invention provides an enterprise digital business application aggregation platform based on SAAS software, including:

[0007] Registration and authentication module, used for account registration and business entity authentication management;

[0008] Payment acquiring module, used for transaction acquiring, product management, transaction risk assessment, transaction data encryption and fund clearing;

[0009] The payment acquiring module includes:

[0010] A transaction risk prediction module, wherein the transaction risk prediction module includes a transaction risk prediction model, wherein the transaction risk prediction model includes a transaction type branch and a risk level branch, wherein the transaction type branch and the risk level branch share the same input layer, encoder, and decoder, wherein the transaction type branch also includes a first fully connected layer and a first output layer, and the risk level branch also includes a second fully connected layer and a second output layer, and a correlation calculation module and a fusion layer embedded between the input layer and the encoder;

[0011] The transaction type branch is used to determine the transaction type of the transaction to be tested based on the transaction data to be tested; the risk level branch is used to predict the risk level of the transaction to be tested based on the transaction data to be tested and the correlation matrix;

[0012] Among them, the input layer is used to receive data;

[0013] The encoder is used to encode the received data to obtain a feature vector;

[0014] The decoder is used to decode the acquired feature vector;

[0015] The first fully connected layer is used to output the probability that the transaction to be tested belongs to each transaction type;

[0016] The first output layer is used to output the transaction type to which the transaction to be tested belongs;

[0017] The correlation calculation module is used to construct a test matrix according to the test transaction data, and calculate the correlation matrix between the test matrix and the corresponding security matrix;

[0018] The fusion layer is used to combine the correlation matrix with the transaction data to be tested to obtain comprehensive features;

[0019] The second fully connected layer is used to output the probability that the transaction to be tested belongs to each risk level;

[0020] The second output layer is used to output the risk level of the transaction to be tested;

[0021] Data statistics module, used to collect, monitor and compile statistics of business data in real time;

[0022] The business management module is used to manage pre-sale and after-sale orders of products;

[0023] The message reminder module is used to remind system messages and transaction messages.

[0024] Furthermore, the training method of the transaction risk prediction model includes:

[0025] Get historical transaction data;

[0026] Each historical transaction data is labeled with the transaction type and risk level, as well as whether the historical transaction is a fraudulent transaction; transaction types include offline transactions, online non-directional transactions, online directional transactions, and contractual transactions; risk levels include high risk, medium risk, and low risk;

[0027] Select N historical transaction data that are not marked as fraudulent transactions from the historical transaction data of different transaction types to construct a security matrix; the offline transaction security matrix is ​​denoted as S 线下 , the security matrix of online non-directional transactions is denoted as S 非定向 , the online directional transaction security matrix is ​​denoted as S 定向 , the contract transaction security matrix is ​​denoted as S 合同 ;

[0028] Take historical transaction data as input, take transaction type as output to train the transaction type branch, select the corresponding security matrix according to the output of the transaction type branch, take historical transaction data and the corresponding security matrix as input, take risk level as output, train the risk level branch, and obtain a trained transaction risk prediction model;

[0029] A data set is constructed based on historical transaction data and a security matrix, and a transaction risk prediction model is trained to obtain a trained transaction risk prediction model.

[0030] Furthermore, the risk level is determined based on the transaction amount and information sensitivity;

[0031] When the transaction amount belongs to the first range and the information sensitivity is high or medium, or the transaction amount belongs to the second range and the information sensitivity is high, the risk level is high;

[0032] When the transaction amount belongs to the first interval and the information sensitivity is low sensitivity, or the transaction amount belongs to the second interval and the information sensitivity is medium sensitivity, or the transaction amount belongs to the third interval and the information sensitivity is high sensitivity, the risk level is medium risk;

[0033] When the transaction amount belongs to the second interval and the information sensitivity is low sensitivity, or the transaction amount belongs to the third interval and the information sensitivity is medium sensitivity or low sensitivity, the risk level is low risk;

[0034] The lower limit value of the first interval is greater than or equal to the upper limit value of the second interval, and the lower limit value of the second interval is greater than or equal to the upper limit value of the third interval.

[0035] Furthermore, the registration and authentication module includes:

[0036] Account registration control unit, used to provide platform account registration function;

[0037] The business entity authentication management unit is used to provide business entity authentication functions;

[0038] The payment channel authentication management unit is used to provide the enterprise merchants with authenticated business entities with the ability to access the payment channel for digital payment collection;

[0039] The business entity switching management unit is used to provide multiple account switching functions, supporting merchants to switch multiple business entities under the same mobile phone number;

[0040] Account information management unit, used to provide account management and setting functions, including setting and changing login passwords, after-sales processing passwords, and editing customer service phone numbers;

[0041] Account abnormality appeal unit, used to provide business merchants with an entry point for appealing account abnormalities;

[0042] The account cancellation unit is used to provide the enterprise merchant account cancellation function.

[0043] Furthermore, the payment acquiring module also includes:

[0044] Offline acquiring unit, used to provide offline acquiring QR code, allowing corporate merchants to conduct offline transactions;

[0045] Online acquiring unit, used to provide directional and non-directional acquiring capabilities combined with business carriers or service scenarios, allowing corporate merchants to conduct online directional transactions and online non-directional transactions;

[0046] The acquiring scene management unit is used to provide management functions for business carriers and service scenes, allowing enterprise merchants to edit pictures, titles and prices of acquiring scenes;

[0047] The contract issuing unit is used to provide electronic contract distribution, signing and acquiring capabilities, including selecting preset contract templates, uploading custom contract templates, contract editing, setting order transaction amounts, order sharing and contract acquiring functions, allowing corporate merchants to conduct contract transactions;

[0048] Mini Program Management Unit, which is used to provide the Mini Program performance dashboard function, allowing business merchants to view the day's performance in real time;

[0049] The product management unit is used to provide the mini program product management function, allowing enterprise merchants to implement product listing, inventory change, deletion, and conditional screening management;

[0050] The invoicing unit is used to provide the ability to manually issue digital electronic invoices and automatically issue digital electronic invoices in conjunction with digital acquiring product services;

[0051] The electronic invoice management unit is used to provide detailed information of the electronic invoice, including the status, subject, amount and time of the electronic invoice;

[0052] The fund clearing management unit is used to provide detailed information on the clearing and settlement of flexible employment funds for enterprises;

[0053] The employee management unit is used to provide management functions for clearing personnel and clearing ratios;

[0054] AI digital communication unit, used to provide business merchants with monitoring and analysis capabilities of business data through artificial intelligence and big data models;

[0055] The transaction data encryption module is used to preset encryption strategies and encrypt the transaction data at corresponding levels based on the preset encryption strategies according to the risk levels output by the transaction risk prediction module.

[0056] Furthermore, the data statistics module includes:

[0057] The transaction amount data unit is used to provide real-time transaction amount data generated by business merchants using digital products and services, allowing business merchants to select different dates and view the transaction amount of the day;

[0058] A transaction volume trend monitoring unit is used to provide transaction volume data trend comparisons at different time dimensions;

[0059] The transaction order data unit is used to provide real-time transaction order volume data generated by business enterprises using digital products and services, allowing business enterprises to select different dates and view the transaction order volume of the day;

[0060] The transaction order trend unit is used to provide transaction order volume data trend comparison in different time dimensions;

[0061] The payment channel data unit is used to record the data generated by consumers using different payment channels, allowing business merchants to select different dates and view the payment channel data of that day;

[0062] The payment channel proportion unit is used to provide a comparison of the proportions of data generated by consumers using different payment channels in different time dimensions.

[0063] Furthermore, the business management module includes:

[0064] The transaction distribution control unit is used to retain the editing results of the business carrier by the enterprise merchant and allow the enterprise merchant to distribute the business carrier within a preset time;

[0065] The transaction carrier management unit is used to provide editing and management functions for business carriers, allowing business merchants to add, delete, and modify business carriers;

[0066] The transaction post-sales customer complaint communication management unit is used to provide business merchants with the function of handling post-sales customer complaints initiated by consumers, allowing business merchants to upload vouchers to the platform and view information on post-sales complaints initiated by consumers;

[0067] The transaction post-sales refund management unit is used to provide business merchants with the function of handling post-sales customer complaints and refunds initiated by consumers for orders, allowing business merchants to directly initiate a refund for the order by clicking the refund button;

[0068] A digital product setting management unit is used to provide business merchants with the function of personalizing digital products;

[0069] The digital product ordering unit allows corporate merchants to order or renew a variety of digital products based on their own business stage and development scale.

[0070] Furthermore, the message reminder module includes:

[0071] System message reminder unit, used to provide system notification function;

[0072] Transaction reminder unit, used to provide business merchants with reminders of new transaction orders generated when using digital products and services;

[0073] Online customer service console, used to provide support when business merchants encounter product usage problems;

[0074] The transaction after-sales abnormality reminder unit is used to provide after-sales complaint notification reminder function generated by transaction orders.

[0075] The embodiments of the present invention have the following technical effects:

[0076] 1. The present invention combines the basic features of the transaction data to be tested and the correlation matrix to enable the model to capture more information dimensions. The basic features provide direct transaction attributes, while the correlation matrix reflects the similarities and differences between the transaction to be tested and the historical normal transactions, which can help the model identify abnormal patterns between the transaction to be tested and the historical normal transactions, thereby more effectively detecting potential fraudulent behaviors. As new transaction data continues to accumulate, the correlation matrix can be dynamically updated, allowing the model to adapt to changing transaction patterns; different levels of encryption for transactions with different risk levels can improve the security level of different types of transactions, and can also effectively manage resources and avoid performance loss caused by excessive encryption.

[0077] 2. The present invention integrates products and services into one to form a digital business aggregation application platform, realizing miniaturized products and powerful functional services; the functional modules deployed by the present invention do not require repeated authentication when used individually or in conjunction, and one account can use all the products and services required for the digital transformation of small and medium-sized enterprises, meeting various business scenarios encountered by small and medium-sized enterprises, greatly improving the efficiency of enterprise use; based on cloud computing, big data, blockchain capabilities and technologies, digital products and service functions are integrated to achieve lightweight applications; focusing on user needs, the products and services provided can meet the business scenarios encountered by small and medium-sized enterprises at different development scales; making products small, fast, light and accurate, and increasing the operating efficiency of small and medium-sized enterprises.

[0078] 3. The present invention integrates different application modules. During the business operation process of the enterprise merchants using the present invention, the functions and units deployed by different modules link data and information, and share and transmit information through application integration technology. A unified data management module is provided to enable enterprises to monitor and manage business data more efficiently and conveniently, eliminate the possibility of data information islands caused by single point failures from the system architecture, and can customize the viewing of integrated and distributed data information to achieve business data collaboration. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0080] Figure 1 It is a structural diagram of an enterprise digital business application aggregation platform based on SAAS software provided by an embodiment of the present invention;

[0081] Figure 2It is a business service flow chart of an enterprise digital business application aggregation platform based on SAAS software provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0082] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0083] The present invention proposes an enterprise digital business application aggregation platform based on SAAS software. Figure 1 is a structural diagram of an enterprise digital business application aggregation platform based on SAAS software provided by an embodiment of the present invention. Figure 2 This is a business service flow chart of a SAAS software-based enterprise digital business application aggregation platform provided by an embodiment of the present invention, see Figure 1 and Figure 2 , including:

[0084] Registration and authentication module, used for account registration and business entity authentication management;

[0085] Payment acquiring module, used for transaction acquiring, product management, transaction risk assessment, transaction data encryption and fund clearing;

[0086] Data statistics module, used to collect, monitor and compile statistics of business data in real time;

[0087] The business management module is used to manage pre-sale and after-sale orders of products;

[0088] The message reminder module is used to remind system messages and transaction messages.

[0089] Furthermore, based on the legal and compliant operation of business enterprises, business enterprises are required to pass real-name authentication and have payment and collection capabilities. The registration and authentication module provides functions related to account registration and business entity authentication management to meet the relevant digital payment collection needs faced by enterprises when using digital products and services. After the business enterprise registers an account and completes the settlement, there is no need to submit authentication materials again for other links. One account can be authenticated once to use the services required by the business enterprise in various business scenarios, which increases security while greatly improving the convenience of business enterprises in using digital products and services. The registration and authentication module includes:

[0090] Account registration control unit, used to provide platform account registration function;

[0091] The business entity authentication management unit is used to provide business entity authentication functions;

[0092] The payment channel authentication management unit is used to provide the enterprise merchants with authenticated business entities with the ability to access the payment channel for digital payment collection;

[0093] The business entity switching management unit is used to provide multiple account switching functions, supporting merchants to switch multiple business entities under the same mobile phone number;

[0094] Account information management unit, used to provide account management and setting functions, including login password, after-sales processing password setting and changing, customer service phone number editing, etc.;

[0095] The account abnormality appeal unit is used to provide an entry for enterprises and merchants to appeal for account abnormalities due to violations of business entities or accounts, abnormal payment status, risk control by regulatory authorities, etc. When the platform receives the appeal, it will assist the enterprise and merchant to restore the abnormal account status;

[0096] The account cancellation unit is used to provide the enterprise merchant account cancellation function.

[0097] Furthermore, based on the cloud computing scenario-based digital solution base capabilities, we will create a digital application toolbox for business enterprises and merchants, and provide digital integrated products and services to solve various business scenarios in different business scenarios for business enterprises and merchants at different development stages, including but not limited to low offline transaction security, difficulty in remote collection, inconvenient paper-based contract collection, cumbersome online mini-program mall development and filing processes, high cost and low security of paper invoice issuance, complex scenarios and high tax burdens when funds are split, and low efficiency in discovering business management problems. On the basis of ensuring the speed of funds arrival and transaction security, we will promote transaction efficiency and convenience in business scenarios, simplify the payment collection process for business enterprises and merchants, reduce costs and increase efficiency, and facilitate corporate supervision and compliance management. The payment collection module includes:

[0098] A transaction risk prediction module, wherein the transaction risk prediction module includes a transaction risk prediction model, wherein the transaction risk prediction model includes a transaction type branch and a risk level branch, wherein the transaction type branch and the risk level branch share the same input layer, encoder, and decoder, wherein the transaction type branch also includes a first fully connected layer and a first output layer, and the risk level branch also includes a second fully connected layer and a second output layer, and a correlation calculation module and a fusion layer embedded between the input layer and the encoder;

[0099] The transaction type branch is used to determine the transaction type to which the transaction to be tested belongs based on the transaction data to be tested; the risk level branch is used to predict the risk level of the transaction to be tested based on the transaction data to be tested and the correlation matrix.

[0100] Specifically, the input layer receives the transaction data to be tested;

[0101] The encoder encodes the transaction data to be tested to obtain a feature vector;

[0102] The decoder decodes the acquired feature vector; illustratively, the encoder and the decoder may adopt a T5 model structure;

[0103] The first fully connected layer outputs the probability of the transaction to be tested belonging to each transaction type based on the decoding result;

[0104] The first output layer outputs the transaction type with the highest probability as the transaction type to which the transaction to be tested belongs.

[0105] Input the transaction data to be tested and the security matrix corresponding to the transaction type to which the transaction to be tested belongs into the input layer again;

[0106] The correlation calculation module represents each element in the transaction data to be tested as a vector and constructs the matrix T to be tested;

[0107] The correlation calculation module calculates the correlation between each vector in the matrix to be tested T and all vectors in the corresponding security matrix to obtain the correlation matrix R;

[0108] For example, the cosine similarity method may be used to calculate the correlation between each vector in the matrix to be tested T and all vectors in the corresponding security matrix:

[0109]

[0110] Among them, r j represents the cosine similarity between the matrix to be tested T and the j-th row vector in the security matrix S, ||T|| represents the modulus length of the matrix to be tested T, ||S j || represents the modulus of the j-th row vector in the security matrix S, S j Represents the j-th row vector in the security matrix S.

[0111] Finally, we get the correlation matrix R = [r1, r2, ..., r n ], where n represents the total number of rows in the security matrix S.

[0112] The fusion layer combines the correlation matrix R with the transaction data to be tested to obtain comprehensive features;

[0113] The encoder encodes the comprehensive features to obtain a comprehensive feature vector;

[0114] The decoder decodes the obtained comprehensive feature vector;

[0115] The second fully connected layer outputs the probability of the transaction to be tested belonging to each risk level based on the decoding result;

[0116] The second output layer outputs the risk level with the highest probability as the risk level to which the transaction to be tested belongs.

[0117] Among them, the risk level is determined based on the transaction amount and information sensitivity:

[0118] When the transaction amount belongs to the first range and the information sensitivity is high or medium, or the transaction amount belongs to the second range and the information sensitivity is high, the risk level is high;

[0119] When the transaction amount belongs to the first interval and the information sensitivity is low sensitivity, or the transaction amount belongs to the second interval and the information sensitivity is medium sensitivity, or the transaction amount belongs to the third interval and the information sensitivity is high sensitivity, the risk level is medium risk;

[0120] When the transaction amount belongs to the second interval and the information sensitivity is low sensitivity, or the transaction amount belongs to the third interval and the information sensitivity is medium sensitivity or low sensitivity, the risk level is low risk;

[0121] The lower limit value of the first interval is greater than or equal to the upper limit value of the second interval, and the lower limit value of the second interval is greater than or equal to the upper limit value of the third interval.

[0122] Among them, information sensitivity can be divided according to laws and regulations, business rules or historical data. For example, information that is easy to leak in historical data can be classified as highly sensitive information.

[0123] In some embodiments, the risk level classification may also be adjusted according to actual conditions.

[0124] Furthermore, the training method of the transaction risk prediction model includes:

[0125] Get historical transaction data.

[0126] Exemplarily, it may include transaction amount, payment method, geographic location, timestamp, etc.

[0127] Carefully process historical transaction data, including outlier removal and normalization.

[0128] Label each historical transaction data, mark the transaction type and risk level, and whether the historical transaction is a fraudulent transaction.

[0129] Among them, transaction types include offline transactions, online non-directional transactions, online directional transactions and contractual transactions; risk levels include high risk, medium risk and low risk.

[0130] N historical transaction data that are not marked as fraudulent transactions are selected from the historical transaction data of different transaction types to construct a security matrix.

[0131] Among them, the offline transaction security matrix is ​​recorded as S 线下 , the security matrix of online non-directional transactions is denoted as S 非定向 , the online directional transaction security matrix is ​​denoted as S 定向 , the contract transaction security matrix is ​​denoted as S 合同 .

[0132] Take historical transaction data as input and transaction type as output to train the transaction type branch. Select the corresponding security matrix according to the output of the transaction type branch. Take historical transaction data and the corresponding security matrix as input and risk level as output to train the risk level branch to obtain a trained transaction risk prediction model.

[0133] A data set is constructed based on historical transaction data and a security matrix, and a transaction risk prediction model is trained to obtain a trained transaction risk prediction model.

[0134] Furthermore, the payment acquiring module also includes:

[0135] Offline acquiring unit, used to provide offline acquiring QR code, allowing corporate merchants to conduct offline transactions;

[0136] The online acquiring unit is used to provide targeted and non-targeted acquiring capabilities combined with business carriers or service scenarios, allowing corporate merchants to conduct online targeted transactions and online non-targeted transactions; corporate merchants can select the set business carriers or service scenarios, and at the same time set the acquiring transaction amount to share the transaction amount of the order with consumers to complete targeted acquiring, or set the payee to fill in the transaction amount to share the order with multiple consumers to complete non-targeted acquiring.

[0137] The acquiring scene management unit is used to provide management functions for business carriers and service scenes, allowing enterprise merchants to edit pictures, titles and prices of acquiring scenes;

[0138] The contract issuance unit is used to provide electronic contract distribution, signing and acquiring capabilities, including selecting preset contract templates, uploading custom contract templates, contract editing, setting order transaction amounts, order sharing and contract acquiring functions, allowing corporate merchants to conduct contract transactions; corporate merchants can select contract templates provided by the platform or uploaded by themselves in this unit and edit variable items to improve the contract, and set the transaction amount to share the order with consumers. After the consumer pays and signs the contract, the contract initiator automatically signs to complete the contract acquisition; and the contract template can be added, deleted, modified and checked through the contract template management unit.

[0139] Mini Program Management Unit, which is used to provide the Mini Program performance dashboard function, allowing business merchants to view the day's performance in real time;

[0140] The product management unit is used to provide the mini program product management function, allowing enterprise merchants to implement product listing, inventory change, deletion, and conditional screening management;

[0141] The invoicing unit is used to provide the ability to manually issue digital electronic invoices and automatically issue digital electronic invoices in conjunction with digital acquiring product services;

[0142] The electronic invoice management unit is used to provide detailed information of the electronic invoice, including the status, subject, amount and time of the electronic invoice;

[0143] The fund clearing management unit is used to provide detailed information on the clearing and settlement of flexible employment funds for enterprises;

[0144] The employee management unit is used to provide management functions for clearing personnel and clearing ratios;

[0145] AI digital communication unit, used to provide business merchants with monitoring and analysis capabilities of business data through artificial intelligence and big data models;

[0146] The transaction data encryption module is used to preset encryption strategies and encrypt the transaction data at corresponding levels based on the preset encryption strategies according to the risk levels output by the transaction risk prediction module.

[0147] Furthermore, based on the big data model, it provides enterprises and merchants with the ability to collect, monitor in real time and make statistics on the business data generated by the digital products and services they subscribe to and use in the cloud computing digital solution module, solving the difficulties of enterprises and merchants in aggregating business data across multiple platforms and channels, and being unable to monitor trends and compare to analyze data. It helps enterprises and merchants determine whether their business methods are effective, adjust strategies, optimize resource allocation, and improve business efficiency and market competitiveness. The data statistics module includes:

[0148] The transaction amount data unit is used to provide real-time transaction amount data generated by business merchants using digital products and services, allowing business merchants to select different dates and view the transaction amount of the day;

[0149] A transaction volume trend monitoring unit is used to provide transaction volume data trend comparisons at different time dimensions;

[0150] The transaction order data unit is used to provide real-time transaction order volume data generated by business enterprises using digital products and services, allowing business enterprises to select different dates and view the transaction order volume of the day;

[0151] The transaction order trend unit is used to provide transaction order volume data trend comparison in different time dimensions;

[0152] The payment channel data unit is used to record the data generated by consumers using different payment channels, allowing business merchants to select different dates and view the payment channel data of that day;

[0153] The payment channel proportion unit is used to provide a comparison of the proportions of data generated by consumers using different payment channels in different time dimensions.

[0154] Furthermore, based on the service orders generated by the cloud computing scenario-based digital solution module, it provides the ability to manage pre-sales and after-sales work of orders and the related settings and operation management of digital products. Enterprise merchants can manage different order statuses according to their own business status and data to improve the quality of pre-sales and after-sales services. The business management module includes:

[0155] The transaction distribution control unit is used to retain the editing results of the business carrier by the enterprise merchant and allow the enterprise merchant to distribute the business carrier within a preset time;

[0156] The transaction carrier management unit is used to provide editing and management functions for business carriers, allowing business merchants to add, delete, and modify business carriers;

[0157] The transaction post-sales customer complaint communication management unit is used to provide business merchants with the function of handling post-sales customer complaints initiated by consumers, allowing business merchants to upload vouchers to the platform and view information on post-sales complaints initiated by consumers;

[0158] The transaction post-sales refund management unit is used to provide business merchants with the function of handling post-sales customer complaints and refunds initiated by consumers for orders, allowing business merchants to directly initiate a refund for the order by clicking the refund button;

[0159] A digital product setting management unit is used to provide business merchants with the function of personalizing digital products;

[0160] The digital product ordering unit allows corporate merchants to order or renew a variety of digital products based on their own business stage and development scale.

[0161] Furthermore, based on the platform publishing or capturing the data of the business data statistics and detection module, it provides enterprises and merchants with the function of receiving system notifications and transaction changes, and can view and manage system messages and transaction changes in real time, including viewing new transaction orders generated by digital products and services subscribed and used by enterprises and merchants in the cloud computing digital solution module and details of after-sales customer complaints of transaction orders. At the same time, the online customer service channel is used for enterprise merchant consultation and Q&A. The message reminder module includes:

[0162] System message reminder unit, used to provide system notification function;

[0163] Transaction reminder unit, used to provide business merchants with reminders of new transaction orders generated when using digital products and services;

[0164] Online customer service console, used to provide support when business merchants encounter product usage problems;

[0165] The transaction after-sales abnormality reminder unit is used to provide after-sales complaint notification reminder function generated by transaction orders.

[0166] The present invention enables the model to capture more information dimensions by combining the basic features of the transaction data to be tested and the correlation matrix. The basic features provide direct transaction attributes, while the correlation matrix reflects the similarities and differences between the transaction to be tested and the historical normal transactions, which can help the model identify abnormal patterns between the transaction to be tested and the historical normal transactions, thereby more effectively detecting potential fraudulent behaviors. As new transaction data continues to accumulate, the correlation matrix can be dynamically updated, allowing the model to adapt to changing transaction patterns; different levels of encryption for transactions with different risk levels can improve the security level of different types of transactions, and can also effectively manage resources and avoid performance loss caused by excessive encryption.

[0167] The present invention integrates products and services into one to form a digital business aggregation application platform, realizing miniaturized products and powerful functional services; the functional modules deployed by the present invention do not need repeated authentication when used individually or in conjunction, and one account can use all the products and services required for the digital transformation of small and medium-sized enterprises, meeting various business scenarios encountered by small and medium-sized enterprises, greatly improving the efficiency of enterprise use; based on cloud computing, big data, blockchain capabilities and technologies, digital products and service functions are integrated to achieve lightweight applications; focusing on user needs, the products and services provided can meet the business scenarios encountered by small and medium-sized enterprises at different development scales; the products are small, fast, light and accurate, increasing the operating efficiency of small and medium-sized enterprises.

[0168] The present invention integrates different application modules. During the business operation process of the enterprise merchants using the present invention, the functions deployed by different modules are linked with data and information between units. Information is shared and transmitted through application integration technology, and a unified data management module is provided to enable enterprises to monitor and manage business data more efficiently and conveniently. The possibility of data information islands caused by single point failures is eliminated from the system architecture, and integrated and distributed data information can be customized to be viewed, thereby realizing business data collaboration.

[0169] It should be noted that the terms used in the present invention are only for describing specific embodiments, rather than limiting the scope of the present application. As shown in the present specification, unless the context clearly indicates an exception, the words "one", "a", "a kind of" and / or "the" do not specifically refer to the singular, but may also include the plural. The terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method or device. In the absence of more restrictions, the elements defined by the sentence "include one..." do not exclude the presence of other identical elements in the process, method or device including the elements.

[0170] It should also be noted that the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. Unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", etc. should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be a connection between the two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0171] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. An enterprise digital business application aggregation platform based on SAAS software, characterized by: include: Registration and authentication module, used for account registration and business entity authentication management; Payment acquiring module, used for transaction acquiring, product management, transaction risk assessment, transaction data and fund clearing; The payment acquiring module includes: A transaction risk prediction module, wherein the transaction risk prediction module includes a transaction risk prediction model, wherein the transaction risk prediction model includes a transaction type branch and a risk level branch, wherein the transaction type branch and the risk level branch share the same input layer, encoder, and decoder, wherein the transaction type branch further includes a first fully connected layer and a first output layer, and the risk level branch further includes a second fully connected layer and a second output layer, and a correlation calculation module and a fusion layer embedded between the input layer and the encoder; The transaction type branch is used to determine the transaction type of the transaction to be tested according to the transaction data to be tested; the risk level branch is used to predict the risk level of the transaction to be tested according to the transaction data to be tested and the correlation matrix; Wherein, the input layer is used to receive data; The encoder is used to encode the received data to obtain a feature vector; The decoder is used to decode the acquired feature vector; The first fully connected layer is used to output the probability that the transaction to be tested belongs to each transaction type; The first output layer is used to output the transaction type to which the transaction to be tested belongs; The correlation calculation module is used to construct a test matrix according to the test transaction data, and calculate the correlation matrix between the test matrix and the corresponding security matrix; The fusion layer is used to combine the correlation matrix with the transaction data to be tested to obtain comprehensive features; The second fully connected layer is used to output the probability that the transaction to be tested belongs to each risk level; The second output layer is used to output the risk level of the transaction to be tested; Data statistics module, used to collect, monitor and compile statistics of business data in real time; The business management module is used to manage pre-sale and after-sale orders of products; The message reminder module is used to remind system messages and transaction messages.

2. According to claim 1, a SAAS software-based enterprise digital business application aggregation platform is characterized in that: The training method of the transaction risk prediction model includes: Get historical transaction data; Label each historical transaction data, mark the transaction type and risk level, and whether the historical transaction is a fraudulent transaction; wherein the transaction type includes offline transactions, online non-directional transactions, online directional transactions, and contractual transactions; the risk level includes high risk, medium risk, and low risk; Select N historical transaction data that are not marked as fraudulent transactions from the historical transaction data of different transaction types to construct a security matrix; the offline transaction security matrix is ​​denoted as S 线下 , the security matrix of online non-directional transactions is denoted as S 非定向 , the online directional transaction security matrix is ​​denoted as S 定向 , the contract transaction security matrix is ​​denoted as S 合同 ; Take historical transaction data as input, take transaction type as output to train the transaction type branch, select the corresponding security matrix according to the output of the transaction type branch, take historical transaction data and the corresponding security matrix as input, take risk level as output, train the risk level branch, and obtain a trained transaction risk prediction model; A data set is constructed based on historical transaction data and a security matrix, and a transaction risk prediction model is trained to obtain a trained transaction risk prediction model.

3. According to claim 2, a SAAS software-based enterprise digital business application aggregation platform is characterized in that: Determine the risk level based on the transaction amount and information sensitivity; When the transaction amount belongs to the first range and the information sensitivity is high or medium, or the transaction amount belongs to the second range and the information sensitivity is high, the risk level is high; When the transaction amount belongs to the first interval and the information sensitivity is low sensitivity, or the transaction amount belongs to the second interval and the information sensitivity is medium sensitivity, or the transaction amount belongs to the third interval and the information sensitivity is high sensitivity, the risk level is medium risk; When the transaction amount belongs to the second interval and the information sensitivity is low sensitivity, or the transaction amount belongs to the third interval and the information sensitivity is medium sensitivity or low sensitivity, the risk level is low risk; The lower limit value of the first interval is greater than or equal to the upper limit value of the second interval, and the lower limit value of the second interval is greater than or equal to the upper limit value of the third interval.

4. The enterprise digital business application aggregation platform based on SAAS software according to claim 1, characterized in that: The registration and authentication module includes: Account registration control unit, used to provide platform account registration function; The business entity authentication management unit is used to provide business entity authentication functions; The payment channel authentication management unit is used to provide the enterprise merchants with authenticated business entities with the ability to access the payment channel for digital payment collection; The business entity switching management unit is used to provide multiple account switching functions, supporting merchants to switch multiple business entities under the same mobile phone number; Account information management unit, used to provide account management and setting functions, including setting and changing login passwords, after-sales processing passwords, and editing customer service phone numbers; Account abnormality appeal unit, used to provide business merchants with an entry point for appealing account abnormalities; The account cancellation unit is used to provide the enterprise merchant account cancellation function.

5. The enterprise digital business application aggregation platform based on SAAS software according to claim 3 is characterized in that: The payment acquiring module also includes: Offline acquiring unit, used to provide offline acquiring QR code, allowing corporate merchants to conduct offline transactions; Online acquiring unit, used to provide directional and non-directional acquiring capabilities combined with business carriers or service scenarios, allowing corporate merchants to conduct online directional transactions and online non-directional transactions; The acquiring scene management unit is used to provide management functions for business carriers and service scenes, allowing enterprise merchants to edit pictures, titles and prices of acquiring scenes; The contract issuing unit is used to provide electronic contract distribution, signing and acquiring capabilities, including selecting preset contract templates, uploading custom contract templates, contract editing, setting order transaction amounts, order sharing and contract acquiring functions, allowing corporate merchants to conduct contract transactions; Mini Program Management Unit, which is used to provide the Mini Program performance dashboard function, allowing business merchants to view the day's performance in real time; The product management unit is used to provide the mini program product management function, allowing enterprise merchants to implement product listing, inventory change, deletion, and conditional screening management; The invoicing unit is used to provide the ability to manually issue digital electronic invoices and automatically issue digital electronic invoices in conjunction with digital acquiring product services; The electronic invoice management unit is used to provide detailed information of the electronic invoice, including the status, subject, amount and time of the electronic invoice; The fund clearing management unit is used to provide detailed information on the clearing and settlement of flexible employment funds for enterprises; The employee management unit is used to provide management functions for clearing personnel and clearing ratios; AI digital communication unit, used to provide business merchants with monitoring and analysis capabilities of business data through artificial intelligence and big data models; The transaction data encryption module is used to preset encryption strategies and encrypt the transaction data at corresponding levels based on the preset encryption strategies according to the risk levels output by the transaction risk prediction module.

6. The enterprise digital business application aggregation platform based on SAAS software according to claim 1, characterized in that: The data statistics module includes: The transaction amount data unit is used to provide real-time transaction amount data generated by business merchants using digital products and services, allowing business merchants to select different dates and view the transaction amount of the day; A transaction volume trend monitoring unit is used to provide transaction volume data trend comparisons at different time dimensions; The transaction order data unit is used to provide real-time transaction order volume data generated by business enterprises using digital products and services, allowing business enterprises to select different dates and view the transaction order volume of the day; The transaction order trend unit is used to provide transaction order volume data trend comparison in different time dimensions; The payment channel data unit is used to record the data generated by consumers using different payment channels, allowing business merchants to select different dates and view the payment channel data of that day; The payment channel proportion unit is used to provide a comparison of the proportion of data generated by consumers using different payment channels in different time dimensions.

7. The enterprise digital business application aggregation platform based on SAAS software according to claim 1, characterized in that: The business management module includes: The transaction distribution control unit is used to retain the editing results of the business carrier by the enterprise merchant and allow the enterprise merchant to distribute the business carrier within a preset time; The transaction carrier management unit is used to provide editing and management functions for business carriers, allowing business merchants to add, delete, and modify business carriers; The transaction post-sales customer complaint communication management unit is used to provide business merchants with the function of handling post-sales customer complaints initiated by consumers, allowing business merchants to upload vouchers to the platform and view information on post-sales complaints initiated by consumers; The transaction post-sales refund management unit is used to provide business merchants with the function of handling post-sales customer complaints and refunds initiated by consumers for orders, allowing business merchants to directly initiate a refund for the order by clicking the refund button; A digital product setting management unit is used to provide business merchants with the function of personalizing digital products; The digital product ordering unit allows corporate merchants to order or renew a variety of digital products based on their own business stage and development scale.

8. The enterprise digital business application aggregation platform based on SAAS software according to claim 1, characterized in that: The message reminder module includes: System message reminder unit, used to provide system notification function; Transaction reminder unit, used to provide business merchants with reminders of new transaction orders generated when using digital products and services; Online customer service console, used to provide support when business merchants encounter product usage problems; The transaction after-sales abnormality reminder unit is used to provide after-sales complaint notification reminder function generated by transaction orders.

Images