Banking business architecture system and analysis method

Abstract

The invention provides a banking business architecture system and an analysis method, and the system is provided with a self-adaptive distributed micro-service module, a data fusion processing module, a risk perception center module and a safety protection module, the self-adaptive distributed micro-service module comprises a plurality of micro-service units, and the micro-service units are in communication connection through quantum entanglement. The data fusion processing module automatically identifies first business data features through cloud computing and processes the first business data to generate second business data, and the risk perception center module constructs a multi-modal risk assessment model through an integrated quantum machine learning algorithm according to the received second business data. According to the invention, high-speed connection between micro-service units is realized through quantum entanglement communication, so that data transmission is rapid, business changes and risk conditions are rapidly responded, and the accuracy, the security and the flexible adaptability of the data are also improved.

Description

Technical Field

[0001] The present invention relates to the technical field of banking services, and particularly to a banking service architecture system and an analysis method. Background Art

[0002] In the wave of the digital transformation of the global financial industry, with the rapid expansion of the scale of banking services, the number of customers, the number of transactions, and the types of services have increased significantly. The traditional monolithic architecture or simple distributed architecture of banking services is difficult to meet the high-concurrency transaction processing requirements, and the service response speed is slow. For example, during peak transaction periods such as e-commerce shopping festivals, the banking systems with traditional architectures often experience lags or even paralysis, seriously affecting the customer experience. Moreover, it is difficult to flexibly adapt to the dynamic changes in the business volume. When new service modules need to be added or computing resources need to be expanded, the cost is high and it is time-consuming and laborious.

[0003] In addition, with the exponential growth of the data volume generated by banking services and the increasing complexity of data types, traditional data processing engines can only process simple structured data and are helpless with complex unstructured data. Moreover, due to the increasing diversification and complexity of network attack means, security incidents such as data leakage, malware intrusion, and online fraud occur frequently. Traditional security protection technologies are difficult to resist new types of network attacks and cannot guarantee the life-cycle security of the core data of banks. Summary of the Invention

[0004] The present invention provides a banking service architecture system and an analysis method to solve the problems in the prior art that it is impossible to flexibly adapt to the dynamic changes in the business volume, is helpless with complex unstructured data, and is difficult to resist new types of network attacks.

[0005] The present invention provides a banking service architecture system, including:

[0006] An adaptive distributed microservice module, which is used to generate first service data. The adaptive distributed microservice module includes several microservice units, and at least two of the microservice units are communicatively connected through quantum entanglement, and the microservice units will automatically adjust resource allocation according to the real-time business volume;

[0007] A data fusion processing module, which is communicatively connected to the adaptive distributed microservice module. The data fusion processing module automatically identifies the characteristics of the first service data through cloud computing and processes the first service data to generate second service data;

[0008] A risk perception central module, the adaptive distributed microservice module and the data fusion processing module are respectively communicatively connected to the risk perception central module. The risk perception central module constructs a multimodal risk assessment model by integrating a quantum machine learning algorithm based on the received second service data. The risk perception central module selects a corresponding decision through the multimodal risk assessment model and feeds back the decision to the adaptive distributed microservice module;

[0009] A security protection module, the adaptive distributed microservice module, the data fusion processing module and the risk perception central module are respectively communicatively connected to the security protection module. The security protection module performs full-life cycle encryption protection on the first service data and the second service data through quantum encryption and constructs an identity authentication mechanism based on biometric recognition and blockchain identity authentication.

[0010] According to the banking business architecture system provided by the present invention, the adaptive distributed microservice module includes a quantum communication unit, the quantum communication unit is connected to the microservice unit, the quantum communication unit includes a quantum entanglement source and a quantum channel, the quantum channel is connected to the quantum entanglement source, and the quantum entanglement source is used to provide entangled quantum bits, and quantum entanglement communication is realized through the entangled quantum bits.

[0011] According to the banking business architecture system provided by the present invention, the quantum entanglement source is a photon entanglement source, the quantum channel is an optical link, and the quantum channel is used to transmit the entangled quantum bits from one microservice unit to another microservice unit.

[0012] According to the banking business architecture system provided by the present invention, the quantum communication unit further includes a quantum measurement component, the quantum measurement component is connected to the quantum entanglement source, the quantum measurement component is used to load the information to be transmitted onto the state of the quantum bit to be transmitted, the quantum measurement component is also used to measure and decode the received quantum bit to obtain the transmitted information, the quantum measurement component includes a single-photon detector, a wave plate and a polarization beam splitter, the single-photon detector is used to detect the state of the entangled quantum bit, and the wave plate and the polarization beam splitter are used to operate and control the polarization state of the entangled quantum bit.

[0013] According to the banking business architecture system provided by the present invention, the banking business architecture system further includes a quantum communication degradation monitoring module, which is connected to the adaptive distributed microservice module. The quantum communication degradation monitoring module includes a quantum communication monitoring unit, a classical encryption communication unit, and a resource recombination unit. When the quantum communication monitoring unit detects an abnormality in quantum entanglement, the quantum entanglement communication switches to the classical encryption communication unit and triggers the resource recombination unit.

[0014] According to the banking business architecture system provided by the present invention, the data fusion processing module includes a data life cycle management unit, and the data life cycle management unit automatically adjusts the storage method of the second business data according to the value density and usage frequency of the second business data.

[0015] According to the banking business architecture system provided by the present invention, the security protection module is further used to monitor network traffic in real time and automatically identify and block network attacks through artificial intelligence algorithms.

[0016] According to the banking business architecture system provided by the present invention, the quantum encryption realizes encrypted communication through post-quantum cryptography algorithms.

[0017] According to the banking business architecture system provided by the present invention, the integrated quantum machine learning algorithm includes a quantum support vector machine, a quantum neural network, and a random forest. The integrated quantum machine learning algorithm constructs the multi-modal risk assessment model by integrating the output results of the quantum support vector machine, the output results of the quantum neural network, and the output results of the random forest. The specific construction formula is:

[0018] F = w 1 f QSVM + w 2 f QNN + w 3 f RF , where F is the fusion result of the multi-modal risk assessment model, f QSVM is the output result of the quantum support vector machine, f QNN is the output result of the quantum neural network, f RF is the output result of the random forest, w 1 、w 2 and w 3 are the weight coefficients of the quantum support vector machine, the quantum neural network, and the random forest respectively. Among them, w 1 + w 2 + w 3 = 1.

[0019] The present invention also provides a banking business analysis method, including:

[0020] Generate the first business data through an adaptive distributed microservice module, where the adaptive distributed microservice module includes several microservice units, at least two of the microservice units are communicatively connected through quantum entanglement, and the microservice units will automatically adjust resource allocation according to the real-time traffic volume;

[0021] The data fusion processing module automatically identifies the characteristics of the first business data through cloud computing and processes the first business data to generate the second business data. Among them, the data fusion processing module is communicatively connected to the adaptive distributed microservice module;

[0022] The risk perception central module constructs a multimodal risk assessment model according to the received second business data through an integrated quantum machine learning algorithm. The risk perception central module selects corresponding decisions through the multimodal risk assessment model and feeds the decisions back to the adaptive distributed microservice module. Among them, the adaptive distributed microservice module and the data fusion processing module are respectively communicatively connected to the risk perception central module;

[0023] The security protection module performs full-life-cycle encryption protection on the first business data and the second business data through quantum encryption and constructs an identity authentication mechanism based on biometric recognition and blockchain identity authentication. Among them, the adaptive distributed microservice module, the data fusion processing module, and the risk perception central module are respectively communicatively connected to the security protection module.

[0024] The present invention provides a banking business architecture system and an analysis method. By setting an adaptive distributed microservice module, a data fusion processing module, a risk perception central module, and a security protection module. Among them, the adaptive distributed microservice module generates first business data. The adaptive distributed microservice module includes several microservice units. At least two of the microservice units are connected by quantum entanglement communication. And the microservice units will automatically adjust resource allocation according to the real-time business volume. The data fusion processing module automatically identifies the characteristics of the first business data through cloud computing and processes the first business data to generate second business data. The risk perception central module constructs a multimodal risk assessment model according to the received second business data through an integrated quantum machine learning algorithm. The risk perception central module selects corresponding decisions through the multimodal risk assessment model and feeds the decisions back to the adaptive distributed microservice module. The security protection module performs full-life cycle encryption protection on the first business data and the second business data through quantum encryption and constructs an identity authentication mechanism based on biometric recognition and blockchain identity authentication. The present invention realizes high-speed connection between microservice units through quantum entanglement communication, enables rapid and low-latency data transmission. In addition, the risk perception central module can quickly complete risk assessment and make decisions and feed them back to the adaptive distributed microservice module, quickly responding to business changes and risk situations. The present invention not only improves the data transmission rate, but also improves the accuracy, security, and flexible adaptability of the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to these drawings.

[0026] Figure 1 It is a schematic structural diagram of the banking business architecture system provided by the embodiment of the present invention;

[0027] Figure 2 It is a schematic structural diagram of the adaptive distributed microservice module in the banking business architecture system provided by the embodiment of the present invention;

[0028] Figure 3 It is a flowchart of the banking business analysis method provided by the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0029] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0030] The present invention provides a banking business architecture system, including:

[0031] An adaptive distributed microservice module, which is used to generate first service data. The adaptive distributed microservice module includes several microservice units. At least two of the microservice units are communicatively connected through quantum entanglement, and the microservice units will automatically adjust resource allocation according to the real-time service volume;

[0032] A data fusion processing module, which is communicatively connected to the adaptive distributed microservice module. The data fusion processing module automatically identifies the characteristics of the first service data through cloud computing and processes the first service data to generate second service data;

[0033] A risk perception central module, the adaptive distributed microservice module and the data fusion processing module are respectively communicatively connected to the risk perception central module. The risk perception central module constructs a multimodal risk assessment model according to the received second service data through an integrated quantum machine learning algorithm. The risk perception central module selects corresponding decisions through the multimodal risk assessment model and feeds the decisions back to the adaptive distributed microservice module;

[0034] A security protection module, the adaptive distributed microservice module, the data fusion processing module, and the risk perception central module are respectively communicatively connected to the security protection module. The security protection module performs full-life cycle encryption protection on the first service data and the second service data through quantum encryption and constructs an identity authentication mechanism based on biometric recognition and blockchain identity authentication.

[0035] Among them, the adaptive distributed microservice module includes a quantum communication unit, the quantum communication unit is connected to the microservice unit, the quantum communication unit includes a quantum entanglement source and a quantum channel, the quantum channel is connected to the quantum entanglement source, and the quantum entanglement source is used to provide entangled quantum bits to achieve quantum entanglement communication through the entangled quantum bits.

[0036] Among them, the quantum entanglement source is a photon entanglement source, and the quantum channel is an optical link, which is used to transmit the entangled qubits from one microservice unit to another microservice unit.

[0037] Among them, the quantum communication unit further includes a quantum measurement component, which is connected to the quantum entanglement source. The quantum measurement component is used to load the information to be transmitted onto the state of the qubit to be transmitted, and is also used to measure and decode the received qubit to obtain the transmitted information. The quantum measurement component includes a single-photon detector, a wave plate, and a polarization beam splitter. The single-photon detector is used to detect the state of the entangled qubit, and the wave plate and the polarization beam splitter are used to operate and control the polarization state of the entangled qubit.

[0038] Among them, the banking business architecture system further includes a quantum communication degradation monitoring module, which is connected to the adaptive distributed microservice module. The quantum communication degradation monitoring module includes a quantum communication monitoring unit, a classical encryption communication unit, and a resource recombination unit. When the quantum communication monitoring unit detects an abnormal quantum entanglement, the quantum entanglement communication is switched to the classical encryption communication unit and the resource recombination unit is triggered.

[0039] Among them, the data fusion processing module includes a data life cycle management unit, which automatically adjusts the storage method of the second business data according to the value density and usage frequency of the second business data.

[0040] Among them, the security protection module is also used to monitor network traffic in real time and automatically identify and block network attacks through artificial intelligence algorithms.

[0041] Among them, the quantum encryption realizes encrypted communication through a post-quantum cryptography algorithm.

[0042] Among them, the integrated quantum machine learning algorithm includes a quantum support vector machine, a quantum neural network, and a random forest. The integrated quantum machine learning algorithm constructs the multimodal risk assessment model by integrating the output results of the quantum support vector machine, the output results of the quantum neural network, and the output results of the random forest. The specific construction formula is:

[0043] F = w 1 f QSVM + w 2 f QNN + w 3 f RF , where F is the fusion result of the multimodal risk assessment model, and f QSVMis the output result of the quantum support vector machine, f QNN is the output result of the quantum neural network, f RF is the output result of the random forest, w 1 、w 2 and w 3 are the weight coefficients of the quantum support vector machine, the quantum neural network, and the random forest respectively. Among them, w 1 +w 2 +w 3 = 1.

[0044] The present invention also provides a banking business analysis method, including:

[0045] Generating first service data through an adaptive distributed microservice module, the adaptive distributed microservice module includes several microservice units, at least two of the microservice units are connected by quantum entanglement communication, and the microservice units will automatically adjust resource allocation according to the real-time service volume;

[0046] The data fusion processing module generates second service data by automatically identifying the characteristics of the first service data and processing the first service data. Among them, the data fusion processing module is communicatively connected to the adaptive distributed microservice module;

[0047] The risk perception central module constructs a multimodal risk assessment model through an integrated quantum machine learning algorithm according to the received second service data. The risk perception central module selects corresponding decisions through the multimodal risk assessment model and feeds the decisions back to the adaptive distributed microservice module. Among them, the adaptive distributed microservice module and the data fusion processing module are respectively communicatively connected to the risk perception central module;

[0048] The security protection module performs full-life cycle encryption protection on the first service data and the second service data through quantum encryption and constructs an identity authentication mechanism based on biometric recognition and blockchain identity authentication. Among them, the adaptive distributed microservice module, the data fusion processing module, and the risk perception central module are respectively communicatively connected to the security protection module.

[0049] The present invention provides a banking business architecture system and an analysis method. By setting an adaptive distributed microservice module, a data fusion processing module, a risk perception central module, and a security protection module. Among them, the adaptive distributed microservice module generates first business data. The adaptive distributed microservice module includes several microservice units. At least two of the microservice units are connected by quantum entanglement communication. And the microservice units will automatically adjust resource allocation according to the real-time business volume. The data fusion processing module automatically identifies the characteristics of the first business data through cloud computing and processes the first business data to generate second business data. The risk perception central module constructs a multimodal risk assessment model according to the received second business data through an integrated quantum machine learning algorithm. The risk perception central module selects corresponding decisions through the multimodal risk assessment model and feeds the decisions back to the adaptive distributed microservice module. The security protection module performs full-life-cycle encryption protection on the first business data and the second business data through quantum encryption and constructs an identity authentication mechanism based on biometric recognition and blockchain identity authentication. The present invention realizes high-speed connection between microservice units through quantum entanglement communication, enabling rapid and low-latency data transmission. In addition, the risk perception central module can quickly complete risk assessment and make decisions and feed them back to the adaptive distributed microservice module, quickly responding to business changes and risk situations. The present invention not only improves the data transmission rate, but also improves the accuracy, security, and flexible adaptability of the data.

[0050] In this embodiment, please refer to Figure 1 , Figure 2 and Figure 3 , which are respectively the schematic structural diagram of the banking business architecture system 1 provided by the embodiment of the present invention, the schematic structural diagram of the adaptive distributed microservice module 10 in the banking business architecture system 1 provided by the embodiment of the present invention, and the flowchart of the banking business analysis method provided by the embodiment of the present invention.

[0051] Specifically, in this embodiment, as Figure 1 and Figure 2As shown in the figure, an embodiment of the present invention provides a banking business architecture system 1, which includes an adaptive distributed microservice module 10. The adaptive distributed microservice module 10 is used to generate first service data. The adaptive distributed microservice module 10 includes a number of microservice units 100. At least two of the microservice units 100 are connected through quantum entanglement communication, and the microservice unit 100 will automatically adjust resource allocation according to the real-time business volume. In this embodiment, the adaptive distributed microservice module 10 uses quantum entanglement communication to achieve high-speed connection between a number of microservice units 100, so as to achieve rapid and low-latency data transmission. At the same time, the microservice unit 100 can automatically adjust resource allocation according to the real-time business volume, avoiding resource waste or shortage, and efficiently generating first service data.

[0052] In this embodiment, the microservice unit automatically adjusts resource allocation according to the real-time business volume. The specific implementation method is as follows:

[0053] Use an index collection tool to collect data on CPU usage rate, memory occupancy, network traffic, request response time, and the number of request processes, and combine logs to analyze user behavior and business operation records to provide a basis for resource adjustment;

[0054] According to business requirements, historical data, and performance goals, set resource allocation rules and thresholds. For example: increase resources when the number of requests exceeds the threshold, and reduce resources when it is lower than another threshold;

[0055] With the help of container orchestration tools (such as Kubernetes) and the API of cloud services, automatically create, delete, or adjust the number of microservice instances and resource configurations according to the rules;

[0056] Establish a feedback mechanism, continuously evaluate the effect of resource adjustment, and dynamically optimize the rules according to business changes and system responses to ensure accurate and efficient resource allocation.

[0057] In this embodiment, such as Figure 1As shown, the banking business architecture system 1 further includes a data fusion processing module 11. The data fusion processing module 11 is communicatively connected to the adaptive distributed microservice module 10. The data fusion processing module 11 automatically identifies the first business data characteristics through cloud computing and processes the first business data to generate second business data. The data fusion processing module 11 includes a data life cycle management unit, and the data life cycle management unit automatically adjusts the storage method of the second business data according to the value density and usage frequency of the second business data. In this embodiment, since the data fusion processing module 11 can automatically identify and process the first business data and generate the second business data, it reduces manual intervention, optimizes data quality, and accelerates the business process. In addition, the data fusion processing module 11 can dynamically adjust the storage according to the value density and usage frequency of the second business data, avoiding resource waste and reducing costs. Hierarchical management of data is more convenient for targeted analysis, supporting long-term data utilization and strategic decision-making.

[0058] In this embodiment, as Figure 1 shown, the banking business architecture system 1 further includes a risk perception central module 12. The adaptive distributed microservice module 10 and the data fusion processing module 11 are respectively communicatively connected to the risk perception central module 12. The risk perception central module 12 constructs a multimodal risk assessment model through an integrated quantum machine learning algorithm based on the received second business data. The risk perception central module 12 selects corresponding decisions through the multimodal risk assessment model and feeds back the decisions to the adaptive distributed microservice module 10. In this embodiment, the risk perception central module 12 constructs a multimodal risk assessment model through an integrated quantum machine learning algorithm, conducts accurate risk assessment based on the second business data, and quickly selects corresponding decisions and feeds them back to the adaptive distributed microservice module 10, overall enhancing the business risk response ability.

[0059] In this embodiment, as Figure 1As shown, the banking business architecture system 1 further includes a security protection module 13. The adaptive distributed microservices module 10, the data fusion processing module 11, and the risk perception central module 12 are respectively communicatively connected to the security protection module 13. The security protection module 13 performs full-life cycle encryption protection on the first service data and the second service data through quantum encryption and constructs an identity authentication mechanism based on biometric recognition and blockchain authentication. The security protection module 13 is also used to monitor network traffic in real time and automatically identify and block network attacks through artificial intelligence algorithms. In this embodiment, the security protection module 13 uses quantum encryption technology to provide full-life cycle encryption protection for the first service data and the second service data, and at the same time constructs an identity authentication mechanism based on biometric recognition and blockchain authentication, which can comprehensively ensure the security of service data and the system.

[0060] In this embodiment, preferably, as Figure 2 shown, the adaptive distributed microservices module 10 includes a quantum communication unit 101. The quantum communication unit 101 is connected to the microservices unit 100. The quantum communication unit 101 includes a quantum entanglement source 1010 and a quantum channel 1011. The quantum channel 1011 is connected to the quantum entanglement source 1010. The quantum entanglement source 1010 is used to provide entangled quantum bits, and quantum entanglement communication is realized through the entangled quantum bits. Among them, the quantum entanglement source 1010 is a photon entanglement source, and the quantum channel 1011 is an optical link. The quantum channel 1011 is used to transmit the entangled quantum bits from one microservices unit 100 to another microservices unit 100. Specifically, the photon entanglement source generates entangled photon pairs through a nonlinear optical crystal (such as: barium borate crystal) using the spontaneous parametric down-conversion process. A high-energy photon will be converted into two low-energy photons in the nonlinear crystal, and these two photons will be in an entangled state. In addition, the optical link is a single-mode optical fiber, which can maintain the quantum state of photons to a certain extent, so as to transmit the entangled quantum bits from one microservices unit 100 to another microservices unit 100. Because the single-mode optical fiber has the characteristics of low loss and low interference, the stability of the quantum is guaranteed.

[0061] In this embodiment, as Figure 2As shown, the quantum communication unit 101 further includes a quantum measurement component 1012. The quantum measurement component 1012 is connected to the quantum entanglement source 1010. The quantum measurement component 1012 is used to load the information to be transmitted onto the state of the quantum bit to be transmitted. The quantum measurement component 1012 is also used to measure and decode the received quantum bit to obtain the transmitted information. The quantum measurement component 1012 includes a single-photon detector, a wave plate, and a polarization beam splitter. The single-photon detector is used to detect the state of the entangled quantum bit. The wave plate and the polarization beam splitter are used to operate and control the polarization state of the entangled quantum bit. Specifically, for example: at the sending end, when encoding the transmitted information, the quantum measurement component 1012 loads the information onto the state of the quantum bit for transmission. At the receiving end, when measuring and decoding the quantum bit, the information transmitted by the sender can be obtained.

[0062] In this embodiment, preferably, as Figure 1 shown, the banking business architecture system 1 further includes a quantum communication degradation monitoring module 14. The quantum communication degradation monitoring module 14 is connected to the adaptive distributed microservice module 10. The quantum communication degradation monitoring module 14 includes a quantum communication monitoring unit, a classical encryption communication unit, and a resource reorganization unit. When the quantum communication monitoring unit monitors an abnormal quantum entanglement, the quantum entanglement communication switches to the classical encryption communication unit and triggers the resource reorganization unit. Specifically, the quantum communication monitoring unit includes sensors and detectors for monitoring the state of the quantum channel. Preferably, the sensor is a single-photon detector and the detector is a phase detector. By real-time monitoring of the transmission characteristics of the quantum bit (polarization state, phase, and intensity of the photon), index data related to the quality of quantum communication is collected. The state of the quantum channel is evaluated through a preset evaluation algorithm. When it is found that the channel state deteriorates to a set threshold, an abnormal signal is sent in a timely manner.

[0063] In this embodiment, the quantum communication degradation monitoring module 14 includes a communication switching decision unit. When receiving the abnormal signal sent by the quantum communication monitoring unit, the communication switching decision unit will make a judgment according to a preset decision rule. Specifically, the communication switching decision unit makes a decision on whether to switch to the classical encryption channel based on the state of the quantum channel and the service requirements. When switching to the classical encryption communication unit, the classical encryption communication unit will select a suitable encryption algorithm from a pre-configured classical encryption algorithm library according to the security requirements of the service and the communication environment, so as to ensure the security of communication data. In addition, based on the traditional communication network, the first service data and the second service data are encrypted through an encryption algorithm and a key, and the encrypted data is transmitted through the classical communication channel, thereby realizing the secure transmission of the first service data and the second service data on the classical encryption channel. In this embodiment, the resource reorganization unit conducts a real-time evaluation of the entire banking business architecture system 1, and formulates corresponding resource reorganization strategies according to the evaluation results and service requirements. The specific strategies include the reallocation, scheduling, and optimization of resources, so as to ensure efficient operation in the classical encryption communication mode. By formulating a reasonable resource reorganization plan, the overall performance and stability are improved.

[0064] In this embodiment, the quantum encryption realizes encrypted communication through a post-quantum cryptography algorithm. Preferably, the post-quantum cryptography algorithm uses the HFE (Hidden Field Equation) algorithm to realize encryption.

[0065] In this embodiment, preferably, the integrated quantum machine learning algorithm includes a quantum support vector machine, a quantum neural network, and a random forest. The integrated quantum machine learning algorithm constructs the multimodal risk assessment model by integrating the output results of the quantum support vector machine, the output results of the quantum neural network, and the output results of the random forest. The specific construction formula is: F = w 1 f QSVM + w 2 f QNN + w 3 f RF , where F is the fusion result of the multimodal risk assessment model, and the fusion result will be used for risk assessment decision-making. For example: judging the default risk size of a loan business or evaluating the risk level of an investment project, f QSVM is the output result of the quantum support vector machine, f QNN is the output result of the quantum neural network, f RF is the output result of the random forest, w 1 、w 2 and w 3They are the weight coefficients of the quantum support vector machine, the quantum neural network, and the random forest respectively, where w 1 + w 2 + w 3 = 1, where the weight coefficients of w 1 , w 2 and w 3 are determined by the adaptive method. During the operation of the multimodal risk assessment model, according to the performance of the quantum support vector machine, the quantum neural network, and the random forest at different time periods, the weight coefficients of the three are dynamically adjusted. For example, if the quantum support vector machine performs poorly in recent predictions, then the weight coefficient w 1 of the quantum support vector machine is reduced.

[0066] In this embodiment, specifically, the quantum support vector machine can process large-scale data and complex classification problems more efficiently. The output result f QSVM of the quantum support vector machine is the predicted probability value that the input data belongs to the corresponding risk category. The quantum neural network simulates the information transmission and processing process of neurons through qubit and quantum gate operations, and has better performance in processing high-dimensional data and complex pattern recognition. The output result f QNN of the quantum neural network is also the predicted probability value that the input data belongs to the corresponding risk category. The random forest improves the accuracy and stability of the multimodal risk assessment model by constructing multiple decision trees and integrating the results of the decision trees.

[0067] In this embodiment, taking the credit business as a specific example, in the credit business, the adaptive distributed microservice module 10 plays a basic role in data generation and processing. For example, it is responsible for collecting basic information submitted by customers, such as name, age, ID number, contact information, etc., as well as financial information, such as income certificate, bank statement, etc. During the peak period of credit applications, such as a large number of customers applying for loans during promotional activities, the adaptive distributed microservice module 10 will automatically increase server resources according to the business volume to ensure that customer information can be collected quickly and stably. In addition, it is connected to external credit investigation agencies through quantum entanglement communication to obtain credit data such as customer credit reports and overdue records. The high speed and security of quantum entanglement communication ensure that the credit data can be transmitted to this microservice unit in a timely and accurate manner. At the same time, the adaptive distributed microservice module 10 will also dynamically adjust resources according to the real-time business volume. For example, during the peak period of credit investigation queries at the end of the month, computing resources are increased to speed up the data integration speed.

[0068] The data fusion processing module 11 receives the first business data from the adaptive distributed microservice module 10, processes it through cloud computing, and utilizes the powerful computing power of cloud computing to automatically identify the key features in customer information and credit data. For example, it analyzes features such as the customer's income stability, credit history length, and number of overdue times. In addition, it cleans, transforms, and integrates the first business data to generate more valuable second business data. For example, it calculates the debt-to-income ratio based on the customer's income and liabilities, and combines it with the credit scoring model to obtain the customer's comprehensive credit score. The data fusion processing module 11 will automatically adjust the storage method according to the value density and usage frequency of these second business data. For frequently used customer credit score data, it uses high-speed solid-state drives for storage; for data with lower usage frequency but long-term preservation requirements such as historical credit records, it uses tape libraries for storage.

[0069] Based on the received second business data, the risk perception central module 12 constructs a multi-modal risk assessment model by integrating quantum machine learning algorithms. Among them, it constructs a multi-modal risk assessment model by integrating the output results of quantum support vector machines, quantum neural networks, and random forests. For example, the quantum support vector machine preliminarily classifies the customer's default risk based on features such as the customer's credit score and debt-to-income ratio; the quantum neural network mines the complex non-linear relationships in the data to further refine the risk assessment; the random forest improves the accuracy of the risk assessment through the comprehensive judgment of multiple decision trees. Finally, according to the fusion result of the multi-modal risk assessment model, the risk perception central module 12 selects the corresponding decision. If the assessment result shows that the customer's default risk is low, it approves the loan application and feeds back this decision to the adaptive distributed microservice module 10. If the risk is high, it may require the customer to increase collateral or reject the loan application.

[0070] The security protection module 13 provides comprehensive security guarantees throughout the credit business process. Through the quantum encryption technology implemented by post-quantum cryptography algorithms, it performs full-life-cycle encryption protection on the first business data (such as the customer's personal sensitive information) and the second business data (such as credit scores and risk assessment results). Whether the data is transmitted between microservice units or stored in the database, it can ensure the confidentiality and integrity of the data. Among them, it constructs an identity authentication mechanism based on biometric recognition and blockchain identity verification. When the customer applies for a loan, it verifies the customer's identity through biometric recognition technologies such as fingerprint recognition and face recognition; at the same time, it uses the immutable feature of the blockchain to store and verify the customer's identity information to prevent identity theft and fraud. In addition, it monitors network traffic in real time and automatically identifies and blocks network attacks through artificial intelligence algorithms. For example, when detecting abnormal network access requests or data transmission behaviors, it takes timely measures to block the attacks to ensure the stable operation of the credit business system.

[0071] In this embodiment, in the adaptive distributed microservice module 10, the photon entanglement source of the quantum communication unit 101 generates entangled qubits, and these qubits are transmitted from one microservice unit to another through an optical link. For example, the encrypted information of the customer is transmitted through quantum entanglement communication to ensure the high speed and security of information transmission. The quantum measurement component 1012 loads the information to be transmitted onto the state of the qubits, and measures and decodes the qubits at the receiving end to achieve accurate information transmission. In addition, the quantum communication monitoring unit monitors the quantum entanglement state in real time. If quantum entanglement anomalies are detected during the credit data transmission process, the system will immediately switch the quantum entanglement communication to the classical encryption communication unit and trigger the resource reorganization unit. The resource reorganization unit will reallocate computing resources and communication resources to ensure the normal operation of the credit business, and at the same time troubleshoot and repair quantum communication failures.

[0072] In this embodiment, the banking business architecture system can efficiently and securely process personal consumer credit applications, achieve accurate risk assessment and decision-making, provide strong support for the bank's credit business, and at the same time ensure the security and privacy of customer data.

[0073] The present invention also provides a banking business analysis method, as Figure 3 shown, the banking business analysis method includes:

[0074] S1: Generate first service data through the adaptive distributed microservice module 10. Specifically, the adaptive distributed microservice module 10 includes several microservice units 100, at least two of the microservice units 100 are connected by quantum entanglement communication, and the microservice units 100 will automatically adjust resource allocation according to the real-time service volume;

[0075] S2: Automatically identify the first service data features through the data fusion processing module 11 and process the first service data to generate second service data, wherein the data fusion processing module 11 is communicatively connected to the adaptive distributed microservice module 10;

[0076] S3: The risk perception central module 12 constructs a multimodal risk assessment model according to the received second service data through an integrated quantum machine learning algorithm. The risk perception central module 12 selects corresponding decisions through the multimodal risk assessment model and feeds the decisions back to the adaptive distributed microservice module 10, wherein the adaptive distributed microservice module 10 and the data fusion processing module 11 are respectively communicatively connected to the risk perception central module 12;

[0077] S4: The security protection module 13 performs full - life - cycle encryption protection on the first service data and the second service data through quantum encryption and constructs an identity authentication mechanism based on biometric recognition and blockchain authentication. Among them, the adaptive distributed microservice module 10, the data fusion processing module 11, and the risk perception central module 12 are respectively communicatively connected to the security protection module 13.

[0078] The present invention provides a banking business architecture system 1 and an analysis method. By setting an adaptive distributed microservice module 10, a data fusion processing module 11, a risk perception central module 12, and a security protection module 13. Among them, the adaptive distributed microservice module 10 generates first service data. The adaptive distributed microservice module 10 includes several microservice units 100. At least two of the microservice units 100 are communicatively connected through quantum entanglement. And the microservice unit 100 automatically adjusts resource allocation according to the real - time traffic volume. The data fusion processing module 11 automatically identifies the characteristics of the first service data through cloud computing and processes the first service data to generate second service data. The risk perception central module 12 constructs a multimodal risk assessment model according to the received second service data through an integrated quantum machine learning algorithm. The risk perception central module 12 selects corresponding decisions through the multimodal risk assessment model and feeds the decisions back to the adaptive distributed microservice module 10. The security protection module 13 performs full - life - cycle encryption protection on the first service data and the second service data through quantum encryption and constructs an identity authentication mechanism based on biometric recognition and blockchain authentication. The present invention realizes high - speed connection between microservice units 100 through quantum entanglement communication, enabling rapid and low - latency data transmission. In addition, the risk perception central module 12 can quickly complete risk assessment and make decisions and feed them back to the adaptive distributed microservice module 10, quickly responding to business changes and risk situations. The present invention not only improves the data transmission rate but also improves the accuracy, security, and flexible adaptability of data.

[0079] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative work.

[0080] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0081] 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 them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A banking business architecture system, characterized in that: include: An adaptive distributed microservice module, wherein the adaptive distributed microservice module is used to generate first business data, and the adaptive distributed microservice module includes a plurality of microservice units, at least two of the microservice units are connected via quantum entanglement communication, and the microservice units automatically adjust resource allocation according to real-time business volume; A data fusion processing module, wherein the data fusion processing module is in communication connection with the adaptive distributed microservice module, and the data fusion processing module automatically identifies the features of the first business data through cloud computing and processes the first business data to generate second business data; A risk perception central module, the adaptive distributed microservice module and the data fusion processing module are respectively connected to the risk perception central module in communication, the risk perception central module builds a multimodal risk assessment model by integrating a quantum machine learning algorithm according to the received second business data, the risk perception central module selects a corresponding decision through the multimodal risk assessment model and feeds the decision back to the adaptive distributed microservice module; The security protection module, the adaptive distributed microservice module, the data fusion processing module and the risk perception central module are respectively communicated with the security protection module, and the security protection module encrypts and protects the first business data and the second business data throughout their life cycle through quantum encryption and builds an identity authentication mechanism based on biometric recognition and blockchain identity authentication.

2. The banking business architecture system according to claim 1, characterized in that: The adaptive distributed microservice module includes a quantum communication unit, which is connected to the microservice unit. The quantum communication unit includes a quantum entanglement source and a quantum channel, which is connected to the quantum entanglement source. The quantum entanglement source is used to provide entangled quantum bits, and quantum entanglement communication is achieved through the entangled quantum bits.

3. The banking business architecture system according to claim 2, characterized in that: The quantum entanglement source is a photon entanglement source, the quantum channel is an optical link, and the quantum channel is used to transmit the entangled quantum bits from one microservice unit to another microservice unit.

4. The banking business architecture system according to claim 3, characterized in that: The quantum communication unit also includes a quantum measurement component, which is connected to the quantum entanglement source. The quantum measurement component is used to load the information to be transmitted onto the state of the quantum bit to be transmitted. The quantum measurement component is also used to measure and decode the received quantum bit to obtain the transmitted information. The quantum measurement component includes a single-photon detector, a wave plate and a polarization beam splitter. The single-photon detector is used to detect the state of the entangled quantum bit, and the wave plate and the polarization beam splitter are used to operate and control the polarization state of the entangled quantum bit.

5. The banking business architecture system according to claim 1, characterized in that: The banking business architecture system also includes a quantum communication degradation monitoring module, which is connected to the adaptive distributed microservice module. The quantum communication degradation monitoring module includes a quantum communication monitoring unit, a classical encryption communication unit and a resource reorganization unit. When the quantum communication monitoring unit detects that the quantum entanglement is abnormal, the quantum entanglement communication switches to the classical encryption communication unit and triggers the resource reorganization unit.

6. The banking business architecture system according to claim 1, characterized in that: The data fusion processing module includes a data lifecycle management unit, and the data lifecycle management unit automatically adjusts the storage method of the second business data according to the value density and usage frequency of the second business data.

7. The banking business architecture system according to claim 1, characterized in that: The security protection module is also used to monitor network traffic in real time and automatically identify and block network attacks through artificial intelligence algorithms.

8. The banking business architecture system according to claim 7, characterized in that: The quantum encryption achieves encrypted communication through a post-quantum cryptography algorithm.

9. The banking business architecture system according to claim 1, characterized in that: The integrated quantum machine learning algorithm includes a quantum support vector machine, a quantum neural network and a random forest. The integrated quantum machine learning algorithm constructs the multimodal risk assessment model by integrating the output results of the quantum support vector machine, the output results of the quantum neural network and the output results of the random forest. The specific construction formula is: F=w1f QSVM +w2f QNN +w3f RF , where F is the fusion result of the multimodal risk assessment model, f QSVM is the output result of the quantum support vector machine, f QNN is the output result of the quantum neural network, f RF is the output result of the random forest, w1, w2 and w3 are the weight coefficients of the quantum support vector machine, the quantum neural network and the random forest respectively, wherein w1+w2+w3=1.

10. A banking business analysis method, characterized in that: include: Generate first business data through an adaptive distributed microservice module, wherein the adaptive distributed microservice module includes a plurality of microservice units, at least two of the microservice units are connected through quantum entanglement communication, and the microservice units automatically adjust resource allocation according to real-time business volume; The data fusion processing module automatically identifies the first business data characteristics through cloud computing and processes the first business data to generate second business data, wherein the data fusion processing module is communicatively connected with the adaptive distributed microservice module; The risk perception center module constructs a multimodal risk assessment model by integrating a quantum machine learning algorithm according to the received second business data, and the risk perception center module selects a corresponding decision through the multimodal risk assessment model and feeds back the decision to the adaptive distributed microservice module, wherein the adaptive distributed microservice module and the data fusion processing module are respectively connected to the risk perception center module in communication; The security protection module encrypts and protects the first business data and the second business data throughout their life cycle through quantum encryption and builds an identity authentication mechanism based on biometric recognition and blockchain identity authentication, wherein the adaptive distributed microservice module, the data fusion processing module and the risk perception center module are respectively communicated with the security protection module.

Images