Construction and operation method of smart wealth management system based on dynamic balance

Abstract

The invention discloses a construction and operation method of a smart wealth management system based on dynamic balance, and belongs to the technical field of asset management. Five core function modules including a general financial module, a risk operation control module, a wealth target module, an asset configuration module and an investment portfolio module are constructed, and a module interaction strategy is input; a forward circulation and reverse constraint combined closed-loop system is formed, driving and calculation of the system are realized, and the integrated design of the system is completed, so that the wealth management system forms a whole with relevant driving and mutual constraint; and accurately classified user data is input into the system so as to carry out real-time calculation and visual display on the output state vector of each module and the wealth management health degree score of the system, carry out early warning prompt on a user, and generate a corresponding module updating instruction by utilizing a wealth consultant end so as to finish quick response and updating of the system. And dynamic balance and autonomous adjustment of the system are realized.

Description

Technical Field

[0001] This invention belongs to the field of asset management technology, specifically relating to a method for building and operating a smart wealth management system based on dynamic equilibrium. Background Technology

[0002] Existing automated wealth management platforms, typically based on modern portfolio theory, provide static or semi-static asset allocation plans after initial risk preference assessments through user questionnaires. However, in practice, the static nature of these asset allocation plans makes it difficult for them to adapt and adjust dynamically to changes in the user's financial situation. This results in an assessed initial asset allocation plan failing to evolve adaptively within its applicable timeframe, and failing to make timely and intelligent adjustments when external market conditions fluctuate, leading to a rapid disconnect between the allocation plan and reality. Furthermore, existing intelligent wealth management systems often have relatively isolated processing units within their architecture. Core functions such as risk control, target management, asset allocation, and investment execution are often fragmented, with data not shared. The lack of a unified technical framework to describe and coordinate the complex interdependencies and feedback mechanisms between these functions makes it difficult for the system to make globally optimal decisions.

[0003] Furthermore, existing intelligent wealth management systems exhibit significant lag in risk control and investment execution: most measures are stop-loss solutions or simple risk rate monitoring after asset losses and investment failures occur, lacking pre-emptive warnings and in-process adjustments, and unable to provide proactive intervention based on the system. This results in existing intelligent wealth management systems being unable to effectively respond to extreme market fluctuations in the short term, nor guarantee long-term returns at the investment execution level.

[0004] As mentioned above, how to provide a method for building and operating a smart wealth management system based on dynamic equilibrium that can form an integrated system and achieve dynamic equilibrium and autonomous adjustment has become an urgent research topic in this field. Summary of the Invention

[0005] The purpose of this invention is to provide a method for building and operating a smart wealth management system based on dynamic equilibrium, so as to solve the above-mentioned problems existing in the prior art.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for building and operating a smart wealth management system based on dynamic equilibrium, comprising: The user data is acquired and categorized into financial data, behavioral data, wealth goal data, and market data according to data type. The financial data includes user asset information, user liability information, user income information, and user expenditure information. The behavioral data includes user login information, user historical consultation information, and user feedback information. The wealth goal data includes user goal information, user goal priority information, and user goal time frame information. The market data includes real-time market economic indicators, real-time market return rate information, and market volatility index information. Five core functional modules are constructed: a financial general ledger module, a risk control module, a wealth goal module, an asset allocation module, and a portfolio module. The financial data is input into the financial general ledger module, the behavioral data is input into the risk control module, the wealth goal data is input into the wealth goal module, and the market data is input into the asset allocation module and the portfolio module. Obtain a preset module interaction strategy and input the module interaction strategy into each of the core functional modules to form a first data interaction relationship and a second data interaction relationship between the core functional modules. Use the first data interaction relationship to drive a positive loop between the core functional modules and use the second data interaction relationship to form a reverse constraint between the core functional modules to complete the system construction. Obtain the output state vector of each of the core functional modules, calculate the wealth management health score using the output state vector of each of the core functional modules, and visualize the output state vector of each of the core functional modules and the wealth management health score. Based on the output state vectors of each core functional module and the wealth management health score, a corresponding wealth management status indication signal is generated and output to the wealth advisor terminal. The wealth advisor terminal then generates a corresponding module update instruction based on the wealth management status indication signal, and updates each core functional module according to the module update instruction, thereby forming a dynamic balance adjustment and operation of wealth management.

[0007] In one possible design, user data is acquired and categorized according to data type into financial data, behavioral data, wealth goal data, and market data, including: Using the first data crawling interface and web crawling technology, user asset information, user expenditure information, user income information and user debt information are crawled from user-authorized payment platforms and financial management institutions, and all the information crawled through the first data crawling interface is integrated into one type of user data. Through the second data capture interface, user login information, user historical consultation information and user feedback information are captured from the user's historical access records and user operation logs, and all the information captured through the second data capture interface is integrated into two types of user data; Through the third data capture interface, user target information, user target priority information, and user target time limit information are collected from user input, and all information captured through the third data capture interface is integrated into three types of user data; The fourth data capture interface is used to capture real-time market economic indicators, real-time market return rates, and market volatility index information from the user's bound financial data service platform. All information captured through the fourth data capture interface is integrated into four types of user data. The fourth data capture interface adopts a message queue interface. Using asynchronous acquisition technology, different types of user data are captured in real time from multiple data sources. The first type of user data is used as financial data, the second type of user data is used as behavioral data, the third type of user data is used as wealth goal data, and the fourth type of user data is used as market data. The financial data, behavioral data, wealth goal data, and market data are subjected to data deduplication, missing value imputation, and outlier removal processes, respectively. The processed financial data, behavioral data, wealth goal data, and market data are then standardized.

[0008] In one possible design, five core functional modules are constructed: a financial general ledger module, a risk control module, a wealth goal module, an asset allocation module, and a portfolio module. The financial data is input into the financial general ledger module, the behavioral data into the risk control module, the wealth goal data into the wealth goal module, and the market data into the asset allocation module and the portfolio module, including: Five software objects are created respectively, and historical user data is loaded and initial parameters are configured for each software object through the API call interface of each software object, resulting in five initial core functional modules. Obtain the preset module state vector function, and each initial core function module uses the loaded historical user data to calculate the initial module output state vector corresponding to each initial core function module based on the module state vector function. For each of the initial core functional modules, the module state is initialized using the output state vector of the initial module corresponding to each initial core functional module, resulting in five core functional modules: financial general ledger module, risk operation and control module, wealth goal module, asset allocation module, and investment portfolio module. A preset topology diagram is obtained, and communication connections are made between each core functional module according to the topology diagram, wherein each core functional module forms a communication connection with each of the other core functional modules. The corresponding types of user data are obtained by utilizing the data input interfaces of each core functional module.

[0009] In one possible design, a preset module interaction strategy is obtained and input into each of the core functional modules to form a first data interaction relationship and a second data interaction relationship among the core functional modules. The first data interaction relationship is used to drive a positive loop among the core functional modules, and the second data interaction relationship is used to form a negative constraint among the core functional modules, thus completing the system construction, including: Obtain a preset module interaction strategy, wherein the module interaction strategy is used to define the data flow relationship between each of the core functional modules; The module interaction strategy is used to form a first data interaction relationship and a second data interaction relationship between the core functional modules. The first data interaction relationship and the second data interaction relationship are both used to represent closed-loop data paths formed by connecting the core functional modules one by one, and the data flow directions of the first data interaction relationship and the second data interaction relationship are different. In the closed-loop data path corresponding to the first data interaction relationship, the positive output of each core functional module is obtained sequentially to drive the positive loop between the core functional modules. In the closed-loop data path corresponding to the second data interaction relationship, the reverse constraint of each core functional module is obtained sequentially to form the reverse constraint between the core functional modules, thus completing the system construction.

[0010] In one possible design, the closed-loop data path corresponding to the first data interaction relationship is as follows: the positive interaction output of the financial general ledger module is communicatively connected to the positive interaction input of the risk operation and control module; the positive interaction output of the risk operation and control module is communicatively connected to the positive interaction input of the wealth target module; the positive interaction output of the wealth target module is communicatively connected to the positive interaction input of the asset allocation module; the positive interaction output of the asset allocation module is communicatively connected to the positive interaction input of the investment portfolio module; and the positive interaction output of the investment portfolio module is communicatively connected to the positive interaction input of the financial general ledger module. Correspondingly, the closed-loop data path corresponding to the second data interaction relationship is as follows: the reverse interaction output terminal of the financial general ledger module is connected to the reverse interaction input terminal of the wealth target module; the reverse interaction output terminal of the wealth target module is connected to the reverse interaction input terminal of the investment portfolio module; the reverse interaction output terminal of the investment portfolio module is connected to the reverse interaction input terminal of the risk operation and control module; the reverse interaction output terminal of the risk operation and control module is connected to the reverse interaction input terminal of the asset allocation module; and the reverse interaction output terminal of the asset allocation module is connected to the reverse interaction input terminal of the financial general ledger module.

[0011] In one possible design, the output state vectors of each of the core functional modules are obtained, a wealth management health score is calculated using the output state vectors of each of the core functional modules, and the output state vectors of each of the core functional modules and the wealth management health score are visualized, including: Obtain a preset module state vector function, and calculate the real-time output state vector for each of the core functional modules based on the module state vector function; Obtain real-time weights, and use these real-time weights to perform a weighted summation of the output state vectors of each of the core functional modules to calculate the wealth management health score. The output state vectors of each core functional module and the wealth management health score are integrated into wealth management data, which is then stored and visualized.

[0012] In one possible design, the output state vector of the financial general ledger module is used to characterize the user's wealth benchmark level, the output state vector of the risk operation and control module is used to characterize the remaining value of the risk buffer pool, the output state vector of the wealth goal module is used to characterize the probability of achieving the wealth goal, the output state vector of the asset allocation module is used to characterize the rationality of asset allocation, and the output state vector of the portfolio module is used to characterize the rate of return of the portfolio.

[0013] In one possible design, the wealth management status indication signal includes a module status indication signal and a system status indication signal; Accordingly, based on the output state vectors of each core functional module and the wealth management health score, a corresponding wealth management status indication signal is generated, including: Obtain a preset system warning threshold and determine the relationship between the wealth management health score and the system warning threshold, wherein the system warning threshold includes a first threshold and a second threshold, and the first threshold is higher than the second threshold; If the wealth management health score is lower than the first threshold but higher than the second threshold, a level one warning signal is generated; If the wealth management health score is lower than the second threshold, a level two warning signal is generated; If the wealth management health score is higher than the first threshold, a normal operation signal is generated; The generated first-level warning signal, the second-level warning signal, or the normal operation signal shall be used as system status indication signals; Each preset module warning threshold of each core functional module is obtained, and it is determined whether the output state vector of each core functional module is higher than the corresponding module warning threshold. Based on the determination result, a corresponding module state indication signal is generated for each core functional module. The system status indication signal and the module status indication signals corresponding to each of the core functional modules are integrated to form a wealth management status indication signal, which is then sent to the client and the wealth advisor.

[0014] In one possible design, the wealth management status indication signal is output to the wealth advisor's terminal, and the wealth advisor's terminal generates a corresponding module update instruction based on the wealth management status indication signal, including: The wealth management status indication signal is output to the wealth advisor terminal, and the wealth advisor terminal extracts the module status indication signal and system status indication signal corresponding to each of the core functional modules from the wealth management status indication signal; The wealth advisor terminal generates a data adjustment strategy for the wealth target data based on the module status indication signals corresponding to each of the core functional modules, and generates a parameter optimization strategy for the parameters of each of the core functional modules. Based on the data adjustment strategy and the parameter optimization strategy, module update instructions are generated for each of the core functional modules.

[0015] In one possible design, the core functional modules are updated according to the module update instructions to achieve dynamic balance adjustment and operation of wealth management, including: Send the module update instructions corresponding to each of the core functional modules to each core functional module; The received module update instructions are used to update each of the core functional modules to obtain the updated core functional modules; The updated output state vectors of each core functional module are obtained again, and the updated wealth management health score is calculated. The updated output state vectors of each core functional module and the updated wealth management health score are sent to the wealth advisor for health assessment to obtain the assessment result. If the assessment result is that the health level is unqualified, then the module update instruction is regenerated to update each core functional module until the assessment result is that the health level is qualified. If the assessment result indicates that the health level is satisfactory, then the updated core functional modules will be used for wealth management to achieve dynamic balance adjustment and operation of wealth management.

[0016] Secondly, the present invention provides a smart wealth management system based on dynamic equilibrium, applicable to the construction and operation method of a smart wealth management system based on dynamic equilibrium as described in the first aspect or any possible design of the first aspect, comprising: The data crawling layer is used to acquire user data and classify the user data according to data type into financial data, behavioral data, wealth goal data, and market data. The financial data includes user asset information, user liability information, user income information, and user expenditure information. The behavioral data includes user login information, user historical consultation information, and user feedback information. The wealth goal data includes user goal information, user goal priority information, and user goal time frame information. The market data includes real-time market economic indicators, real-time market return rate information, and market volatility index information. The core engine building layer is used to construct five core functional modules: financial general ledger module, risk operation and control module, wealth goal module, asset allocation module, and investment portfolio module. The financial data is input into the financial general ledger module, the behavioral data is input into the risk operation and control module, the wealth goal data is input into the wealth goal module, and the market data is input into the asset allocation module and the investment portfolio module. The execution logic forming layer is used to obtain the preset module interaction strategy and input the module interaction strategy into each of the core functional modules to form a first data interaction relationship and a second data interaction relationship between the core functional modules. The first data interaction relationship is used to drive the positive loop between the core functional modules, and the second data interaction relationship is used to form the reverse constraint between the core functional modules to complete the system construction. The execution and presentation layer is used to obtain the output state vectors of each of the core functional modules, calculate the wealth management health score using the output state vectors of each of the core functional modules, and visualize the output state vectors of each of the core functional modules and the wealth management health score. The dynamic balance adjustment layer is used to generate corresponding wealth management status indication signals based on the output status vectors of each core functional module and the wealth management health score, and output the wealth management status indication signals to the wealth advisor terminal. The wealth advisor terminal then generates corresponding module update instructions based on the wealth management status indication signals, and updates each core functional module according to the module update instructions, thereby forming a dynamic balance adjustment and operation of wealth management.

[0017] Thirdly, the present invention provides an electronic device comprising a memory, a processor, and a transceiver connected in sequence and in communication, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the method for building and operating a smart wealth management system based on dynamic equilibrium as described in the first aspect or any possible design of the first aspect.

[0018] Fourthly, the present invention provides a computer-readable storage medium storing instructions that, when executed on a computer, perform the method for building and operating the intelligent wealth management system based on dynamic equilibrium as described in the first aspect or any possible design of the first aspect.

[0019] Fifthly, the present invention provides a computer program product containing instructions that, when the instructions are executed on a computer, cause the computer to perform the method for building and operating a smart wealth management system based on dynamic equilibrium as described in the first aspect or any possible design of the first aspect.

[0020] Beneficial Effects: This invention provides a method for building and operating a smart wealth management system based on dynamic equilibrium, including: firstly, acquiring user data and classifying the user data according to data type into financial data, behavioral data, wealth goal data, and market data. The financial data includes user asset information, user liability information, user income information, and user expenditure information; the behavioral data includes user login information, user historical consultation information, and user feedback information; the wealth goal data includes user goal information, user goal priority information, and user goal timeframe information; and the market data includes real-time market economic indicators, real-time market return rate information, and market volatility index information. Secondly, constructing a general ledger module and a risk control module. The system comprises five core functional modules: a wealth goal module, an asset allocation module, and a portfolio module. Financial data is input into the general ledger module, behavioral data into the risk control module, wealth goal data into the wealth goal module, and market data into the asset allocation and portfolio modules. Then, a preset module interaction strategy is obtained and input into each of the core functional modules to establish a first data interaction relationship and a second data interaction relationship among them. The first data interaction relationship drives a positive cycle among the core functional modules, while the second data interaction relationship forms a negative constraint among them, thus completing the system construction. The system acquires the output state vectors of each core functional module, calculates a wealth management health score using these vectors, and visualizes the output state vectors and health scores. It then generates corresponding wealth management status indication signals based on these signals and outputs them to the wealth advisor. The wealth advisor then generates corresponding module update instructions based on these instructions to update each core functional module, thus achieving dynamic balance adjustment and operation in wealth management. By constructing five core functional modules—financial general ledger, risk control, wealth goals, asset allocation, and investment portfolio—and inputting module interaction strategies, a closed-loop system combining positive feedback loops and negative constraints is formed. This achieves system drive and calculation, completing the overall system design and making the wealth management system a cohesive whole with interconnected drives and mutual constraints. Furthermore, by inputting precisely categorized user data into this system, the output state vectors of each module and the system's wealth management health score are calculated and visualized in real time, providing users with early warnings. The wealth advisor terminal generates corresponding module update commands, enabling rapid system response and updates, and achieving dynamic balance and self-regulation of the system. Attached Figure Description

[0021] Figure 1 A flowchart illustrating the construction and operation method of a dynamic equilibrium-based intelligent wealth management system provided in an embodiment of the present invention; Figure 2 A functional structure diagram of a smart wealth management system based on dynamic equilibrium provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the connection relationship of the first data interaction relationship provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the connection relationship of the second data interaction relationship provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be briefly introduced below in conjunction with the accompanying drawings and descriptions of the embodiments or the prior art. Obviously, the following description of the structure of the accompanying drawings is only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. It should be noted that the description of these embodiments is for the purpose of helping to understand the present invention, but does not constitute a limitation of the present invention.

[0023] It should be understood that although the terms first, second, etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit, without departing from the scope of the exemplary embodiments of the invention.

[0024] It should be understood that the term "and / or" that may appear in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, B exists alone, and A and B exist simultaneously. The term " / and" that may appear in this document describes another relationship between related objects, indicating that two relationships can exist. For example, A / and B can mean: A exists alone, and A and B exist alone. In addition, the character " / " that may appear in this document generally indicates that the related objects before and after it are in an "or" relationship.

[0025] Example: like Figure 1As shown, the first aspect of this embodiment provides a method for building and operating a smart wealth management system based on dynamic equilibrium, which may include, but is not limited to, the following steps: S1. Acquire user data and classify the user data according to data type into financial data, behavioral data, wealth goal data, and market data. The financial data includes user asset information, user liability information, user income information, and user expenditure information. The behavioral data includes user login information, user historical consultation information, and user feedback information. The wealth goal data includes user goal information, user goal priority information, and user goal time frame information. The market data includes real-time market economic indicator information, real-time market return rate information, and market volatility index information. In one possible design, step S1, acquiring user data and classifying it according to data type into financial data, behavioral data, wealth goal data, and market data, can be broken down into steps S11-S16, specifically including: S11. Using the first data crawling interface and web crawling technology, extract user asset information, user expenditure information, user income information and user debt information from the user-authorized payment platform and financial management institution, and integrate all the information extracted through the first data crawling interface into one type of user data; S12. Through the second data capture interface, extract user login information, user historical consultation information and user feedback information from the user's historical access records and user operation logs, and integrate all the information captured through the second data capture interface into two types of user data; S13. Collect user target information, user target priority information, and user target time limit information input by the user through the third data capture interface, and integrate all the information captured through the third data capture interface into three types of user data; S14. Through the fourth data capture interface, extract real-time market economic indicator information, real-time market return rate information, and market volatility index information from the financial data service platform bound to the user, and integrate all the information captured through the fourth data capture interface into four types of user data. The fourth data capture interface adopts a message queue interface. S15. Using asynchronous acquisition technology, different types of user data are extracted from multiple data sources in real time, and the first type of user data is used as financial data, the second type of user data is used as behavioral data, the third type of user data is used as wealth goal data, and the fourth type of user data is used as market data. S16. Perform data deduplication, missing value filling, and outlier removal on the financial data, behavioral data, wealth target data, and market data respectively, and then standardize the processed financial data, behavioral data, wealth target data, and market data respectively.

[0026] It should be noted that the user data obtained in this embodiment includes not only data extracted from the platform and various institutions, but also data actively entered by the user in actual applications.

[0027] In addition, the second data capture interface can also capture investment risk tolerance assessment data (obtained by users filling out a preset risk questionnaire) and form a preliminary risk profile. This preliminary risk profile is then added to the second type of data to make the subsequent initialization of the risk control module more accurate. The fourth data capture interface can also capture asset allocation data (which includes the types of assets invested by the user, the proportion of each type of asset, the overall volatility, and the rate of return) and add it to the fourth type of data to improve the accuracy of the subsequent initialization of the asset allocation module, facilitating the formation of constraints and early warning judgments during subsequent operation.

[0028] S2. Construct five core functional modules: financial general ledger module, risk operation and control module, wealth goal module, asset allocation module, and investment portfolio module. Input the financial data into the financial general ledger module, the behavioral data into the risk operation and control module, the wealth goal data into the wealth goal module, and the market data into the asset allocation module and the investment portfolio module. In one possible design, step S2 involves constructing five core functional modules: a financial general ledger module, a risk control module, a wealth goal module, an asset allocation module, and a portfolio module. The financial data is input into the financial general ledger module, the behavioral data into the risk control module, the wealth goal data into the wealth goal module, and the market data into the asset allocation module and the portfolio module. This can be broken down into, but is not limited to, the following steps S21-S25, specifically including: S21. Five software objects are created respectively, and historical user data is loaded and initial parameters are configured for each software object through the API call interface of each software object, so as to obtain five initial core functional modules; S22. Obtain the preset module state vector function. Each initial core function module uses the loaded historical user data to calculate the initial module output state vector corresponding to each initial core function module based on the module state vector function. S23. For each of the initial core functional modules, the module state is initialized by using the initial module output state vector corresponding to each initial core functional module, resulting in five core functional modules: financial general ledger module, risk operation and control module, wealth goal module, asset allocation module and investment portfolio module. S24. Obtain a preset topology diagram to establish communication connections between each core functional module according to the topology diagram, wherein each core functional module establishes a communication connection with each of the other core functional modules. S25. Obtain the corresponding type of user data using the data input interfaces of each core functional module.

[0029] S3. Obtain a preset module interaction strategy and input the module interaction strategy into each of the core functional modules to form a first data interaction relationship and a second data interaction relationship between the core functional modules. Use the first data interaction relationship to drive a positive loop between the core functional modules and use the second data interaction relationship to form a reverse constraint between the core functional modules to complete the system construction. In one possible design, step S3 involves obtaining a preset module interaction strategy and inputting the module interaction strategy into each of the core functional modules to form a first data interaction relationship and a second data interaction relationship among the core functional modules. The first data interaction relationship is used to drive a positive loop among the core functional modules, and the second data interaction relationship is used to form a negative constraint among the core functional modules, thus completing the system construction. This can be decomposed into, but is not limited to, the following steps S31-S33, specifically including: S31. Obtain a preset module interaction strategy, wherein the module interaction strategy is used to define the data flow relationship between each of the core functional modules; S32. Using the module interaction strategy, a first data interaction relationship and a second data interaction relationship are formed between each of the core functional modules, wherein the first data interaction relationship and the second data interaction relationship are both used to represent closed-loop data paths formed by connecting each of the core functional modules one by one, and the data flow directions of the first data interaction relationship and the second data interaction relationship are different. S33. In the closed-loop data path corresponding to the first data interaction relationship, the positive output of each core functional module is obtained sequentially to drive the positive loop between the core functional modules. In the closed-loop data path corresponding to the second data interaction relationship, the reverse constraint of each core functional module is obtained sequentially to form the reverse constraint between the core functional modules, thus completing the system construction.

[0030] like Figure 2As shown, in one possible design, the closed-loop data path corresponding to the first data interaction relationship mentioned in step S3 is as follows: the positive interaction output terminal of the financial general ledger module is communicatively connected to the positive interaction input terminal of the risk operation and control module; the positive interaction output terminal of the risk operation and control module is communicatively connected to the positive interaction input terminal of the wealth target module; the positive interaction output terminal of the wealth target module is communicatively connected to the positive interaction input terminal of the asset allocation module; the positive interaction output terminal of the asset allocation module is communicatively connected to the positive interaction input terminal of the investment portfolio module; and the positive interaction output terminal of the investment portfolio module is communicatively connected to the positive interaction input terminal of the financial general ledger module. like Figure 3 As shown, correspondingly, the closed-loop data path corresponding to the second data interaction relationship mentioned in step S3 is as follows: the reverse interaction output terminal of the financial general ledger module is connected to the reverse interaction input terminal of the wealth target module; the reverse interaction output terminal of the wealth target module is connected to the reverse interaction input terminal of the investment portfolio module; the reverse interaction output terminal of the investment portfolio module is connected to the reverse interaction input terminal of the risk operation and control module; the reverse interaction output terminal of the risk operation and control module is connected to the reverse interaction input terminal of the asset allocation module; and the reverse interaction output terminal of the asset allocation module is connected to the reverse interaction input terminal of the financial general ledger module.

[0031] It should be noted that this embodiment realizes the construction of a smart wealth management system based on dynamic balance through steps S1-S3. The positive loop drive and reverse constraint architecture between the core functional modules makes the core functional modules directly form a whole. When the system is running normally, it breaks the status quo of data silos between functional units in traditional asset allocation. It enables any change in the state of any core functional module to be positively associated with the next core functional module in a timely manner through the first data interaction relationship, and is intelligently and quickly transmitted to the entire system, triggering the system's chain response and real-time calculation, thereby realizing cross-module collaborative calculation and optimal allocation of global resources.

[0032] Furthermore, the intelligent wealth management system in this embodiment constructs the wealth management system as a tightly interconnected organic whole. Through the second data interaction relationship, the various core functional modules in the system can form a constraint chain. With continuous real-time monitoring of users' financial status, market conditions, and wealth goals, dynamic real-time constraints are formed on the system, avoiding the problems of system staticity and rigid constraints. This enables the autonomous adjustment of constraints for each core functional module, and when external input data fluctuates, the constraints of each core functional module also change accordingly, forming continuous constraint fine-tuning, maintaining the optimal system operating state, and overcoming the rigidity defects of traditional static configuration models.

[0033] S4. Obtain the output state vector of each of the core functional modules, calculate the wealth management health score using the output state vector of each of the core functional modules, and visualize the output state vector of each of the core functional modules and the wealth management health score. In one possible design, step S4 involves obtaining the output state vectors of each core functional module, calculating the wealth management health score using the output state vectors of each core functional module, and visually displaying the output state vectors of each core functional module and the wealth management health score. This step can be broken down into, but is not limited to, the following steps S41-S43, specifically including: S41. Obtain a preset module state vector function, and calculate the real-time output state vector for each of the core functional modules according to the module state vector function; S42. Obtain real-time weights, and use the real-time weights to perform a weighted summation of the output state vectors of each of the core functional modules to calculate the wealth management health score; S43. Integrate the output state vectors of each of the core functional modules and the wealth management health score into wealth management data, and store and visualize the wealth management data.

[0034] In one possible design, the output state vector of the financial general ledger module is used to characterize the user's wealth benchmark level, the output state vector of the risk operation and control module is used to characterize the remaining value of the risk buffer pool, the output state vector of the wealth goal module is used to characterize the probability of achieving the wealth goal, the output state vector of the asset allocation module is used to characterize the rationality of asset allocation, and the output state vector of the portfolio module is used to characterize the rate of return of the portfolio.

[0035] S5. Generate corresponding wealth management status indication signals based on the output status vectors of each core functional module and the wealth management health score, and output the wealth management status indication signals to the wealth advisor terminal. The wealth advisor terminal then generates corresponding module update instructions based on the wealth management status indication signals to update each core functional module according to the module update instructions, thereby forming a dynamic balance adjustment and operation of wealth management.

[0036] In one possible design, the wealth management status indication signal includes a module status indication signal and a system status indication signal; Accordingly, in step S5, generating a corresponding wealth management status indication signal based on the output state vectors of each core functional module and the wealth management health score can be, but is not limited to, decomposed into the following steps S51-S57, specifically including: S51. Obtain a preset system warning threshold and determine the relationship between the wealth management health score and the system warning threshold, wherein the system warning threshold includes a first threshold and a second threshold, and the first threshold is higher than the second threshold; S52. If the wealth management health score is lower than the first threshold but higher than the second threshold, a first-level warning signal is generated; S53. If the wealth management health score is lower than the second threshold, a secondary warning signal is generated; S54. If the wealth management health score is higher than the first threshold, a normal operation signal is generated; S55. The generated first-level warning signal, the second-level warning signal, or the normal operation signal shall be used as a system status indication signal; S56. Obtain the preset module warning thresholds for each of the core functional modules respectively, and determine whether the output state vector of each core functional module is higher than the corresponding module warning threshold, so as to generate a corresponding module state indication signal for each core functional module according to the judgment result. S57. Integrate the system status indication signal and the module status indication signals corresponding to each of the core functional modules to form a wealth management status indication signal, and send the wealth management status indication signal to the client and the wealth advisor.

[0037] In one possible design, step S5, where the wealth management status indication signal is output to the wealth advisor terminal, and the wealth advisor terminal generates a corresponding module update instruction based on the wealth management status indication signal, can be broken down into steps S58-S510, specifically including: S58. Output the wealth management status indication signal to the wealth advisor terminal, and the wealth advisor terminal extracts the module status indication signal and system status indication signal corresponding to each of the core functional modules from the wealth management status indication signal; S59. The wealth advisor terminal generates a data adjustment strategy for the wealth target data based on the module status indication signals corresponding to each of the core functional modules, and generates a parameter optimization strategy for the parameters of each of the core functional modules. S510. Based on the data adjustment strategy and the parameter optimization strategy, generate module update instructions corresponding to each of the core functional modules.

[0038] In one possible design, step S5, updating each of the core functional modules according to the module update instruction to achieve dynamic balance adjustment and operation of wealth management, can be, but is not limited to, decomposed into the following steps S511-S5, specifically including: S511. Send the module update instructions corresponding to each of the core functional modules to each core functional module; S512. Update each of the core functional modules using the received module update instruction to obtain the updated core functional modules; S513. Obtain the updated output state vectors of each of the core functional modules again, calculate the updated wealth management health score, and send the updated output state vectors of each of the core functional modules and the updated wealth management health score to the wealth advisor for health assessment to obtain the assessment result. S514. If the evaluation result is that the health level is unqualified, then the module update instruction is regenerated to update each core functional module until the evaluation result is that the health level is qualified. S515. If the assessment result is that the health level is qualified, then the updated core functional modules are used for wealth management to complete the dynamic balance adjustment and operation of wealth management.

[0039] It should be noted that this embodiment realizes the operation of the intelligent wealth management system through steps S4-S5. In actual operation, due to the constraint cycle mechanism between modules (i.e., the second data interaction relationship), the system can assess the health of modules and the system before risk accumulation and investment trend deterioration, so as to issue forward warnings when the health is poor. Through the adjustment and optimization strategies of the wealth advisor, the system automatically performs data updates and parameter optimization for each core functional module to achieve dynamic balance adjustment of the system, which greatly reduces the actual investment risk.

[0040] Furthermore, the intelligent wealth management system built in this embodiment can understand user needs, predict investment risks, and provide users with real-time, visualized wealth management health scores during operation, so that users can grasp the overall situation of wealth management in real time, bringing a fundamental improvement to the user experience and greatly enhancing users' trust, dependence, and stickiness to the system.

[0041] In practical applications, when the intelligent wealth management system in this embodiment is running, each core functional module performs output state vector calculation and completes the overall dynamic adjustment of the system. Specifically, taking the reverse constraint relationship between the portfolio module and the risk operation and control module as an example: the risk operation and control module uses the remaining value H of the risk buffer pool as the output state vector. When calculating it, it needs to be reverse-constrained according to the reverse output amount of the portfolio module (the portfolio consumption value C, which is a market fluctuation and risk quantification value generated by the actual operation of the portfolio module). Specifically, it is calculated using the following formula (1): (1); in, This represents the remaining value of the risk buffer pool at the current moment. This represents the remaining value of the risk buffer pool from the previous moment. After the risk control module calculates the remaining value of the risk buffer pool at the current moment as the output state vector, it obtains the preset module warning threshold of the risk control module (which can be set to 50% of the initial module output state vector of the risk control module). When the risk level falls below the warning threshold of the risk control module, the system sends a warning to the user indicating that the risk control module is not in good condition, and then forwards the warning to the wealth advisor.

[0042] Based on the warning status, the wealth advisor immediately generates a parameter optimization strategy to reduce investment and lower the risk to a safe range, so as to protect the portfolio's consumption value C from excessively consuming the remaining value H of the risk buffer pool, and simultaneously optimizes and adjusts the parameters of the other modules.

[0043] like Figure 4 As shown, the second aspect of this embodiment provides a hardware system for implementing the method for building and operating a smart wealth management system based on dynamic equilibrium as described in the first aspect of the embodiment, including: The data crawling layer is used to acquire user data and classify the user data according to data type into financial data, behavioral data, wealth goal data, and market data. The financial data includes user asset information, user liability information, user income information, and user expenditure information. The behavioral data includes user login information, user historical consultation information, and user feedback information. The wealth goal data includes user goal information, user goal priority information, and user goal time frame information. The market data includes real-time market economic indicators, real-time market return rate information, and market volatility index information. The core engine building layer is used to construct five core functional modules: financial general ledger module, risk operation and control module, wealth goal module, asset allocation module, and investment portfolio module. The financial data is input into the financial general ledger module, the behavioral data is input into the risk operation and control module, the wealth goal data is input into the wealth goal module, and the market data is input into the asset allocation module and the investment portfolio module. The execution logic forming layer is used to obtain the preset module interaction strategy and input the module interaction strategy into each of the core functional modules to form a first data interaction relationship and a second data interaction relationship between the core functional modules. The first data interaction relationship is used to drive the positive loop between the core functional modules, and the second data interaction relationship is used to form the reverse constraint between the core functional modules to complete the system construction. The execution and presentation layer is used to obtain the output state vectors of each of the core functional modules, calculate the wealth management health score using the output state vectors of each of the core functional modules, and visualize the output state vectors of each of the core functional modules and the wealth management health score. The dynamic balance adjustment layer is used to generate corresponding wealth management status indication signals based on the output status vectors of each core functional module and the wealth management health score, and output the wealth management status indication signals to the wealth advisor terminal. The wealth advisor terminal then generates corresponding module update instructions based on the wealth management status indication signals, and updates each core functional module according to the module update instructions, thereby forming a dynamic balance adjustment and operation of wealth management.

[0044] The working process, working details and technical effects of the system provided in this embodiment can be found in the first aspect of the embodiment, and will not be repeated here.

[0045] like Figure 5 As shown, the third aspect of this embodiment provides an electronic device, including: a memory, a processor, and a transceiver that are sequentially and communicatively connected, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the method for building and operating a smart wealth management system based on dynamic balance as described in the first aspect of the embodiment.

[0046] For specific examples, the memory may include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, first-in-first-out (FIFO) memory, and / or first-in-last-out (FILO) memory, etc.; specifically, the processor may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor may be implemented using at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), PLA (Programmable Logic Array). The processor may also include a main processor and a coprocessor. The main processor, also known as the CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state.

[0047] In some embodiments, the processor may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. For example, the processor may not be limited to microprocessors of the STM32F105 series, reduced instruction set computer (RISC) microprocessors, x86 architecture processors, or processors with integrated neural network processing units (NPUs). The transceiver may be, but is not limited to, a Wi-Fi transceiver, a Bluetooth transceiver, a General Packet Radio Service (GPRS) transceiver, a ZigBee (a low-power LAN protocol based on the IEEE 802.15.4 standard) transceiver, a 3G transceiver, a 4G transceiver, and / or a 5G transceiver. Furthermore, the device may also include, but is not limited to, a power module, a display screen, and other necessary components.

[0048] The working process, working details and technical effects of the electronic device provided in this embodiment can be found in the first aspect of the embodiment, and will not be repeated here.

[0049] The fourth aspect of this embodiment provides a storage medium that stores instructions containing the method for building and operating a dynamically balanced intelligent wealth management system as described in the first aspect of the embodiment. That is, the storage medium stores instructions, and when the instructions are run on a computer, the method for building and operating a dynamically balanced intelligent wealth management system as described in the first aspect of the embodiment is executed.

[0050] The storage medium refers to a carrier for storing data, which may include, but is not limited to, floppy disks, optical disks, hard disks, flash memory, USB flash drives, and / or memory sticks. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.

[0051] The working process, working details and technical effects of the storage medium provided in this embodiment can be found in the first aspect of the embodiment, and will not be repeated here.

[0052] The fifth aspect of this embodiment provides a computer program product containing instructions that, when executed on a computer, cause the computer to perform the method for building and operating a smart wealth management system based on dynamic balance as described in the first aspect of the embodiment. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.

[0053] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for building and running a dynamic balance-based intelligent wealth management system, characterized in that, The method comprises the following steps: acquiring user data, and classifying the user data into financial data, behavior data, wealth target data, and market data according to data types, wherein the financial data comprises user asset information, user liability information, user income information, and user expenditure information, the behavior data comprises user login information, user historical consultation information, and user feedback information, the wealth target data comprises user target information, user target priority information, and user target time limit information, and the market data comprises market real-time economic indicator information, market real-time yield information, and market volatility index information; constructing five core function modules, namely, a financial general ledger module, a risk operation and control module, a wealth target module, an asset allocation module, and an investment portfolio module, and inputting the financial data into the financial general ledger module, inputting the behavior data into the risk operation and control module, inputting the wealth target data into the wealth target module, and inputting the market data into the asset allocation module and the investment portfolio module; acquiring a preset module interaction strategy, and inputting the module interaction strategy into each of the core function modules to form a first data interaction relationship and a second data interaction relationship between the core function modules, driving a forward circulation between the core function modules by using the first data interaction relationship, forming a reverse constraint between the core function modules by using the second data interaction relationship, and completing system construction; acquiring an output state vector of each of the core function modules, calculating a wealth management health degree score by using the output state vector of each of the core function modules, and visually displaying the output state vector of each of the core function modules and the wealth management health degree score; generating a corresponding wealth management state indication signal according to the output state vector of each of the core function modules and the wealth management health degree score, outputting the wealth management state indication signal to a wealth consultant end, and generating a corresponding module update instruction according to the wealth management state indication signal by using the wealth consultant end, so as to update each of the core function modules according to the module update instruction, form a dynamic balance adjustment and operation of wealth management.

2. The method of claim 1, wherein the dynamic balance-based intelligent wealth management system is built and operated. The method comprises the following steps: acquiring user data, and classifying the user data into financial data, behavior data, wealth target data, and market data according to data types, wherein the financial data comprises user asset information, user liability information, user income information, and user expenditure information, the behavior data comprises user login information, user historical consultation information, and user feedback information, the wealth target data comprises user target information, user target priority information, and user target time limit information, and the market data comprises market real-time economic indicator information, market real-time yield information, and market volatility index information; acquiring user data, and classifying the user data into financial data, behavior data, wealth target data, and market data according to data types, wherein the financial data comprises user asset information, user liability information, user income information, and user expenditure information, the behavior data comprises user login information, user historical consultation information, and user feedback information, the wealth target data comprises user target information, user target priority information, and user target time limit information, and the market data comprises market real-time economic indicator information, market real-time yield information, and market volatility index information; constructing five core function modules, namely, a financial general ledger module, a risk operation and control module, a wealth target module, an asset allocation module, and an investment portfolio module, and inputting the financial data into the financial general ledger module, inputting the behavior data into the risk operation and control module, inputting the wealth target data into the wealth target module, and inputting the market data into the asset allocation module and the investment portfolio module; acquiring a preset module interaction strategy, and inputting the module interaction strategy into each of the core function modules to form a first data interaction relationship and a second data interaction relationship between the core function modules, driving a forward circulation between the core function modules by using the first data interaction relationship, forming a reverse constraint between the core function modules by using the second data interaction relationship, and completing system construction; acquiring an output state vector of each of the core function modules, calculating a wealth management health degree score by using the output state vector of each of the core function modules, and visually displaying the output state vector of each of the core function modules and the wealth management health degree score; generating a corresponding wealth management state indication signal according to the output state vector of each of the core function modules and the wealth management health degree score, outputting the wealth management state indication signal to a wealth consultant end, and generating a corresponding module update instruction according to the wealth management state indication signal by using the wealth consultant end, so as to update each of the core function modules according to the module update instruction, form a dynamic balance adjustment and operation of wealth management. The user target information, user target priority information and user target time limit information input by the user are collected through a third data grabbing interface, and all the information collected through the third data grabbing interface is integrated into three types of user data; Real-time market economic indicator information, real-time market yield information and market volatility index information are grabbed from the financial data service platform bound by the user through a fourth data grabbing interface, and all the information collected through the fourth data grabbing interface is integrated into four types of user data, wherein the fourth data grabbing interface adopts a message queue interface; Different types of user data are grabbed from multiple data sources in real time by using an asynchronous collection technology, and the one type of user data is used as financial data, the two types of user data are used as behavior data, the three types of user data are used as wealth target data, and the four types of user data are used as market data; The financial data, the behavior data, the wealth target data and the market data are respectively subjected to data deduplication, missing value filling and outlier removal processing, and the processed financial data, behavior data, wealth target data and market data are respectively subjected to standardization processing.

3. The method of claim 1, wherein the dynamic balance-based intelligent wealth management system is constructed and operated. Five core function modules, namely, a financial general ledger module, a risk operation and control module, a wealth target module, an asset allocation module and an investment portfolio module, are constructed, and the financial data is input into the financial general ledger module, the behavior data is input into the risk operation and control module, the wealth target data is input into the wealth target module, and the market data is input into the asset allocation module and the investment portfolio module, including: Five software objects are respectively established, and historical user data loading and initial parameter configuration are respectively performed on each software object through an API calling interface of each software object to obtain five initial core function modules; A preset module state vector function is obtained, and each initial core function module calculates an initial module output state vector corresponding to each initial core function module based on the module state vector function using loaded historical user data; Each initial core function module is subjected to module state initialization using the initial module output state vector corresponding to each initial core function module to obtain the five core function modules, namely, the financial general ledger module, the risk operation and control module, the wealth target module, the asset allocation module and the investment portfolio module; A preset topological relationship diagram is obtained to communicate and connect each core function module according to the topological relationship diagram, wherein any core function module is in communication connection with each of the other core function modules; Each core function module is used to obtain user data of a corresponding type through a data input interface of each core function module.

4. The method of claim 1, wherein the dynamic balance-based intelligent wealth management system is constructed and operated. acquire a preset module interaction strategy, and input the module interaction strategy into each core function module to form a first data interaction relationship and a second data interaction relationship between the core function modules, drive a forward cycle between the core function modules by using the first data interaction relationship, form a reverse constraint between the core function modules by using the second data interaction relationship, and complete system building, comprising: acquiring a preset module interaction strategy, wherein the module interaction strategy is used to define a data flow relationship between each core function module; form a first data interaction relationship and a second data interaction relationship between each core function module by using the module interaction strategy, wherein the first data interaction relationship and the second data interaction relationship are both used to represent a closed loop data path formed by connecting each core function module one by one, and the data flow directions of the first data interaction relationship and the second data interaction relationship are different; in the closed loop data path corresponding to the first data interaction relationship, the forward output of each core function module is acquired in turn to drive the forward cycle between the core function modules, and in the closed loop data path corresponding to the second data interaction relationship, the reverse constraint of each core function module is acquired in turn to constitute the reverse constraint between the core function modules, and the system building is completed.

5. The method of building and running a dynamic balance based smart wealth management system according to claim 1, wherein, The closed loop data path corresponding to the first data interaction relationship is that the forward interaction output end of the financial general ledger module is in communication connection with the forward interaction input end of the risk control module, the forward interaction output end of the risk control module is in communication connection with the forward interaction input end of the wealth target module, the forward interaction output end of the wealth target module is in communication connection with the forward interaction input end of the asset allocation module, the forward interaction output end of the asset allocation module is in communication connection with the forward interaction input end of the investment portfolio module, and the forward interaction output end of the investment portfolio module is in communication connection with the forward interaction input end of the financial general ledger module. Correspondingly, the closed loop data path corresponding to the second data interaction relationship is that the reverse interaction output end of the financial general ledger module is in communication connection with the reverse interaction input end of the wealth target module, the reverse interaction output end of the wealth target module is in communication connection with the reverse interaction input end of the investment portfolio module, the reverse interaction output end of the investment portfolio module is in communication connection with the reverse interaction input end of the risk control module, the reverse interaction output end of the risk control module is in communication connection with the reverse interaction input end of the asset allocation module, and the reverse interaction output end of the asset allocation module is in communication connection with the reverse interaction input end of the financial general ledger module.

6. The method of building and running a dynamic balance based smart wealth management system according to claim 1, wherein, acquire the output state vector of each core function module, calculate the wealth management health score by using the output state vector of each core function module, and visually display the output state vector of each core function module and the wealth management health score, comprising: Obtaining a preset module state vector function, and calculating real-time output state vectors of each core function module according to the module state vector function; Obtaining real-time weights, and performing weighted summation on the output state vectors of each core function module by using the real-time weights to calculate a wealth management health degree score; Integrating the output state vectors of each core function module and the wealth management health degree score into wealth management data, and storing and visualizing the wealth management data.

7. The method of building and running a dynamic balance based smart wealth management system according to claim 1, wherein, The output state vector of the financial general ledger module is used to represent the user's wealth benchmark level, the output state vector of the risk operation and control module is used to represent the remaining value of the risk buffer pool, the output state vector of the wealth target module is used to represent the probability of achieving the wealth target, the output state vector of the asset allocation module is used to represent the rationality of asset allocation, and the output state vector of the portfolio module is used to represent the yield of the investment portfolio.

8. The method of building and running a dynamic balance based smart wealth management system according to claim 1, wherein, The wealth management state indication signal includes a module state indication signal and a system state indication signal; Correspondingly, generating a corresponding wealth management state indication signal according to the output state vectors of each core function module and the wealth management health degree score includes: Obtaining a preset system warning threshold, and determining the size relationship between the wealth management health degree score and the system warning threshold, wherein the system warning threshold includes a first threshold and a second threshold, and the first threshold is higher than the second threshold; If the wealth management health degree score is lower than the first threshold but higher than the second threshold, a first-level warning signal is generated; If the wealth management health degree score is lower than the second threshold, a second-level warning signal is generated; If the wealth management health degree score is higher than the first threshold, a normal operation signal is generated; The generated first-level warning signal, second-level warning signal or normal operation signal is used as a system state indication signal; Respectively obtaining preset module warning thresholds of each core function module, and respectively determining whether the output state vectors of each core function module are higher than the corresponding module warning thresholds to generate corresponding module state indication signals for each core function module according to the determination results; Integrating the system state indication signal and the corresponding module state indication signals of each core function module to form a wealth management state indication signal, and sending the wealth management state indication signal to a client and a wealth advisor terminal.

9. The method of claim 8, wherein the dynamic balance-based intelligent wealth management system is built and operated. Outputting the wealth management state indication signal to the wealth advisor terminal, and generating corresponding module update instructions by the wealth advisor terminal according to the wealth management state indication signal, including: Outputting the wealth management state indication signal to the wealth advisor terminal, and extracting the corresponding module state indication signals of each core function module and the system state indication signal from the wealth management state indication signal by the wealth advisor terminal; The wealth advisor terminal generates data adjustment strategies for the wealth target data according to the corresponding module state indication signals of each core function module, and generates parameter optimization strategies for the parameters of each core function module; According to the data adjustment strategy and the parameter optimization strategy, a module update instruction corresponding to each core function module is generated.

10. The method of claim 9, wherein the dynamic balance-based intelligent wealth management system is constructed and operated. According to the module update instruction, each core function module is updated to form a dynamic balance adjustment and operation of wealth management, including: sending the module update instruction corresponding to each core function module to each core function module; updating each core function module using the received module update instruction to obtain an updated core function module; obtaining the output state vector of each updated core function module again, calculating the updated wealth management health score, and sending the output state vector of each updated core function module and the updated wealth management health score to the wealth consultant end for health assessment to obtain an assessment result; if the assessment result is unqualified health, the module update instruction is regenerated to update each core function module until the assessment result is qualified health; if the assessment result is qualified health, the updated core function module is used for wealth management, and the dynamic balance adjustment and operation of wealth management are completed.

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