Financial data integration and analysis system and analysis method

Abstract

The invention provides a financial data integration and analysis system and analysis method, and relates to the technical field of financial data integration and analysis systems.The financial data integration and analysis system comprises a processing platform, a storage platform, a user platform, a mechanism platform and an integration platform, the storage platform comprises a database module, a data generation module and a data analysis module, the user platform comprises an intelligent interaction module, an investment analysis module and a simulation market module, and the institution platform comprises a behavior analysis module, a label updating module and an institution docking module; the method not only supports the analysis of the user to the financial data, but also supports the analysis of the financial institution to the behavior of the user, thereby providing a bidirectional service, facilitating the financial institution to better understand the market dynamics, customer behaviors and risk factors, making a more intelligent decision, and improving the user experience. And the user can better know the market dynamics, the financial products and the corresponding risk factors.

Description

Technical Field

[0001] The present invention relates to the technical field of financial data integration and analysis systems, and in particular to a financial data integration and analysis system and an analysis method. Background Art

[0002] The main purpose of financial data analysis systems is to help financial institutions, investors, and analysts process and analyze large amounts of financial data. As financial markets become more and more complex and the amount of data grows explosively, traditional manual analysis methods can no longer meet the needs. Therefore, financial data analysis systems have emerged, which use advanced computing technology and algorithms to provide in-depth insights and decision support. At present, artificial intelligence technology is developing rapidly, so in the further research of financial data analysis systems, artificial intelligence technology will be combined with financial data analysis systems to bring better experience to users.

[0003] In the prior art, financial data analysis systems are usually established by financial institutions to serve the users of the financial institutions, that is, they are user-oriented, so that users can analyze and predict the situation of the financial market and the future of finance during use, which brings certain help to users. However, they are user-oriented and involve a single aspect. For financial institutions, they also need to understand the current financial market, and at the same time, they also need to understand the user's own behavior, data, etc., in order to provide them with more appropriate services. At the same time, the data source of the financial data analysis system will be single. Therefore, the present invention proposes a financial data integration and analysis system and analysis method to solve the problems existing in the prior art. Summary of the invention

[0004] In view of the above problems, the purpose of the present invention is to propose a financial data integration and analysis system and analysis method, which have services for users and institutions, and by integrating data from different data sources, can provide comprehensive financial data analysis and solve the problems existing in the prior art.

[0005] To achieve the purpose of the present invention, the present invention is implemented through the following technical solutions: a financial data integration and analysis system, including a processing platform, a storage platform, a user platform, an institutional platform and an integration platform, the processing platform includes a data acquisition module for collecting financial-related data and a data integration module for processing financial-related data, the storage platform includes a database module for storing data, a data generation module for generating report data and a data analysis module for data analysis, the user platform includes an intelligent interaction module for interacting with users using an AI large model, an investment analysis module for testing user investment tendencies and a simulated market module for users to simulate and predict market fluctuations, the institutional platform includes a behavior analysis module for analyzing user financial behavior, a label update module for updating user investment tendencies and an institutional docking module for institutional docking, the integration platform includes a login module for user and institutional login, a verification module for verifying login information and a recording module for recording login-related information, and the behavior analysis module is docked with the intelligent interaction module.

[0006] A further improvement is that the database module is provided with a financial data unit for storing financial-related data, a user data unit for storing user information, an institutional data unit for storing institutional information, an intelligent model unit for storing an AI large model database, and a shared data unit for sharing data between institutions.

[0007] A further improvement is that the institutional platform also includes a communication and collaboration module for communication and collaboration among multiple institutions, and the communication and collaboration module is connected to the shared data unit.

[0008] A further improvement is that: the data acquisition module is provided with a data acquisition unit, and the data acquisition unit is provided with several groups, the data sources accessed by the several groups of data acquisition units are inconsistent, and the data acquisition units obtain data from the data sources through crawler technology.

[0009] A further improvement is that the data sources include social media data sources, financial market data sources, exchange data sources, bank data sources and financial institution data sources.

[0010] A further improvement is that the data integration module includes a data pre-processing unit for cleaning incoming data, a data conversion unit for converting the data format and a data integration unit for merging data.

[0011] An analysis of a financial data integration and analysis system includes the following steps: Step 1: The data acquisition module collects data from different data sources, then processes it through the data integration module, and then enters the database module for storage; Step 2: The user or organization logs in to the integration platform and issues analysis requirements; Step 3: The intelligent interaction module analyzes the data stored in the database module according to the received analysis requirements, obtains the target results and provides feedback.

[0012] A further improvement is that in step 2, when a new user logs in, the investment analysis module pushes a questionnaire to the user, and after the user fills in the questionnaire, the user's type is analyzed based on the results of the questionnaire.

[0013] The beneficial effects of the present invention are as follows: the financial data integration and analysis system and analysis method not only support users' analysis of financial data, but also support financial institutions in analyzing users' behavior, thereby providing two-way services to users and financial institutions. Financial institutions can then better understand market dynamics, customer behavior and risk factors, thereby making more informed decisions, while users can better understand market dynamics, financial products and corresponding risk factors. At the same time, the system has automated data collection, preprocessing and integration processes, high data processing efficiency, and by integrating data from different data sources, it can provide comprehensive financial data analysis, avoid the occurrence of data islands, improve the quality and efficiency of decision-making, and also help risk management, business process optimization, customer experience improvement and product innovation. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a schematic diagram of the system structure framework of the present invention. DETAILED DESCRIPTION

[0015] In order to deepen the understanding of the present invention, the present invention will be further described in detail below in conjunction with examples. The examples are only used to explain the present invention and do not constitute a limitation on the protection scope of the present invention.

[0016] according to Figure 1 As shown, this embodiment proposes a financial data integration and analysis system, including a processing platform, a storage platform, a user platform, an institution platform and an integration platform.

[0017] The processing platform includes a data acquisition module for collecting financial-related data and a data integration module for processing financial-related data. The data acquisition module is provided with a data acquisition unit, and the data acquisition unit is provided with several groups. The data sources accessed by the several groups of data acquisition units are inconsistent. The data acquisition units obtain data from the data sources through crawler technology. The data sources include social media data sources, financial market data sources, exchange data sources, bank data sources and financial institution data sources. The data integration module includes a data preprocessing unit for cleaning the incoming data, a data conversion unit for converting the data format and a data integration unit for merging the data.

[0018] Therefore, in this system, the processing platform is mainly used to process data-related content, and the data collection unit obtains relevant financial data from different data sources, among which the social media data source corresponds to the financial data corresponding to social media on the Internet; the financial market data source is the financial data on the financial market, such as the price information of financial assets such as stocks, bonds, commodities, and foreign exchange; the exchange data source is the detailed information of financial products listed on the exchange, including code, name, type, etc.; the bank data source is the deposit interest rate, loan interest rate, etc. provided by the bank; the financial institution data source is the asset scale and investment portfolio composition managed by the financial institution.

[0019] After obtaining these data, they are integrated and processed through the data integration module, and then through the cooperation of the data preprocessing unit, the data conversion unit and the data integration unit, the collected data are first cleaned to remove irrelevant content such as advertisements and spam information, and then converted into a unified data format, and finally merged and stored in the database module.

[0020] The storage platform includes a database module for storing data, a data generation module for generating report data, and a data analysis module for data analysis. The database module is provided with a financial data unit for storing financial-related data, a user data unit for storing user information, an institutional data unit for storing institutional information, an intelligent model unit for storing an AI large model database, and a shared data unit for sharing data between institutions.

[0021] The data processed by the processing platform will be stored through the financial data unit, while the user data unit and the institutional data unit will store the corresponding information. The intelligent model unit stores the trained AI big model, and with the application of this system, each interaction can play a training role, and the intelligent model unit is used alone for the use of AI big models. This system is applied to financial institutions, and financial institutions will also have financial institutions cooperating with them. Therefore, under this condition, it is convenient for financial institutions to share data with each other and facilitate subsequent communication and collaboration.

[0022] The user platform includes an intelligent interaction module that uses an AI big model to interact with users, an investment analysis module for testing users' investment tendencies, and a simulated market module for users to simulate and predict market fluctuations. The intelligent interaction module provides an AI robot for interacting with users, while the investment analysis module is used to test a user's investment tendency. When a user logs in, there is no information about the user in the database module, and it needs to be recreated. Therefore, the user is a new user, so the investment analysis module pushes it to the user in the form of a questionnaire. The specific composition of the questionnaire is set by the financial institution, and the user is marked according to the results of the questionnaire. The type is divided into conservative, aggressive, and Aggressive and semi-aggressive. The types are not limited to these three and can be set by the financial institutions themselves according to the actual situation. Therefore, when the user logs in, the financial institution can obtain the corresponding label of the user, so as to recommend more suitable financial products to the user. At the same time, according to the user's category, when the user puts forward corresponding analysis requirements, the user's type can also be taken into consideration. Correspondingly, the simulation market module provides a simulation prediction function, which builds a market simulator based on the data in the database module. It can generate a simulation path of market fluctuations based on historical data and prediction models, thereby providing different market scenario settings, allowing users to simulate market fluctuations according to hypothetical conditions, which is convenient for users to use.

[0023] The institutional platform includes a behavior analysis module for analyzing user financial behavior, a label update module for updating user investment tendencies, and an institutional docking module for docking between institutions. The institutional platform also includes a communication and collaboration module for multi-institutional communication and collaboration. The communication and collaboration module is docked with the shared data unit, and the behavior analysis module is docked with the intelligent interaction module. The behavior analysis module extracts market sentiment indicators and user data (with user consent) by analyzing text data such as social media and news reports, thereby predicting market fluctuations and user behavior. Correspondingly, its implementation method is: based on the data in the database module, natural language processing (NLP) technology is used, such as sentiment analysis model, to classify text into positive, negative or neutral emotions, and then evaluate the intensity of emotions in the text, and then perform feature extraction to identify keywords and phrases related to market sentiment in the text, use the LDA (Latent Dirichlet Allocation) algorithm to identify the main topics in the text, and then assign an emotion score to each text to reflect its emotional tendency and intensity, and arrange the emotion scores in time series to construct market sentiment indicators, and then combine the intelligent interaction module to predict market fluctuations and investor behavior.

[0024] As users use the product more deeply, financial institutions will also provide users with corresponding services and products, and the overall behavior of users will change. Based on these behavioral changes, the investment analysis module can be used to regularly push questionnaires to users, and the corresponding user labels can be changed through the label update module, making it easier for financial institutions to improve and adapt their services to users.

[0025] The integrated platform includes a login module for users and institutions to log in, a verification module for verifying login information, and a recording module for recording login-related information. The integrated platform provides a login portal. When a user or institution logs in, they enter the corresponding platform. The corresponding recording module is mainly used to record the time, login information, and other data of each user or institution login to ensure that the logged-in user is authentic.

[0026] An analysis of a financial data integration and analysis system includes the following steps: Step 1: The data acquisition module collects data from different data sources, then processes it through the data integration module, and then enters the database module for storage; Step 2: The user or institution logs in to the integrated platform and issues an analysis request. When a new user logs in, the investment analysis module pushes the questionnaire to the user. After the user fills in the questionnaire, the user's type is analyzed based on the results of the questionnaire. Step 3: The intelligent interaction module analyzes the data stored in the database module according to the received analysis requirements, obtains the target results and provides feedback.

[0027] The analysis involves historical data and data stored in the database module. It involves various financial data sources (such as exchanges, financial databases, APIs, etc.) to collect historical prices, trading volumes, financial statements and other data, use machine learning algorithms (neural networks) to train prediction models, and apply time series analysis methods to simulate and predict market fluctuations. This is one way of analysis. There are other ways of analysis, such as analyzing the data of a single financial institution or investment product to understand its operating conditions and risk situation, or analyzing the financial data of an industry to predict market trends.

[0028] Therefore, the present invention not only supports users' analysis of financial data, but also supports financial institutions in analyzing users' behavior, thereby providing two-way services to users and financial institutions. Financial institutions can then better understand market dynamics, customer behavior and risk factors, thereby making more informed decisions, while users can better understand market dynamics, financial products and corresponding risk factors. At the same time, the system has automated data collection, preprocessing and integration processes, high data processing efficiency, and by integrating data from different data sources, it can provide comprehensive financial data analysis, avoid the occurrence of data islands, improve the quality and efficiency of decision-making, and also help risk management, business process optimization, customer experience improvement and product innovation.

[0029] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the framework and scope of application of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A financial data integration and analysis system, characterized by: It includes a processing platform, a storage platform, a user platform, an institutional platform and an integration platform. The processing platform includes a data acquisition module for collecting financial-related data and a data integration module for processing financial-related data. The storage platform includes a database module for storing data, a data generation module for generating report data and a data analysis module for data analysis. The user platform includes an intelligent interaction module for interacting with users using an AI big model, an investment analysis module for testing user investment tendencies and a simulated market module for users to simulate and predict market fluctuations. The institutional platform includes a behavior analysis module for analyzing user financial behavior, a label update module for updating user investment tendencies and an institutional docking module for institutional docking. The integration platform includes a login module for user and institutional login, a verification module for verifying login information and a recording module for recording login-related information. The behavior analysis module is docked with the intelligent interaction module.

2. A financial data integration and analysis system according to claim 1, characterized in that: The database module is provided with a financial data unit for storing financial-related data, a user data unit for storing user information, an institutional data unit for storing institutional information, an intelligent model unit for storing an AI large model database, and a shared data unit for sharing data between institutions.

3. A financial data integration and analysis system according to claim 2, characterized in that: The institutional platform also includes a communication and collaboration module for communication and collaboration among multiple institutions, and the communication and collaboration module is connected to the shared data unit.

4. A financial data integration and analysis system according to claim 1, characterized in that: The data acquisition module is provided with a data acquisition unit, and the data acquisition unit is provided with several groups. The data sources accessed by the several groups of data acquisition units are inconsistent. The data acquisition units obtain data from the data sources through crawler technology.

5. A financial data integration and analysis system according to claim 4, characterized in that: The data sources include social media data sources, financial market data sources, exchange data sources, bank data sources and financial institution data sources.

6. A financial data integration and analysis system according to claim 1, characterized in that: The data integration module includes a data preprocessing unit for cleaning incoming data, a data conversion unit for converting the data format, and a data integration unit for merging data.

7. The analysis applied to the financial data integration and analysis system of claim 1, characterized in that: The following steps are involved: Step 1: The data acquisition module collects data from different data sources, then processes it through the data integration module, and then enters the database module for storage; Step 2: The user or organization logs in to the integration platform and issues analysis requirements; Step 3: The intelligent interaction module analyzes the data stored in the database module according to the received analysis requirements, obtains the target results and provides feedback.

8. The analysis method of a financial data integration and analysis system according to claim 7, characterized in that: In the step 2, when a new user logs in, the investment analysis module pushes a questionnaire to the user, and after the user fills in the questionnaire, the user's type is analyzed based on the results of the questionnaire.

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