TW201837824A - Conversational financial management robot system and method including a communication module and a portfolio investment artificial intelligence server - Google Patents

Abstract

Disclosed are a conversational financial management robot system and method. The conversational wealth management robot system includes a communication module and a securities investment artificial intelligence server, wherein the securities investment artificial intelligence server includes an investor behavior analysis module, a financial information analysis module and a database module; the communication module obtains the user's dialogue message and transmits the investment analysis message; the securities investment artificial intelligence server generates the investment analysis message based on the personalized response message and the financial investment information; the investor behavior analysis module generates the personalized response message; the financial information analysis module generates the financial investment information; the database module stores investor attribute data, investor dialogue records, financial investment words and expressions, real-time market data, historical market data, financial rules and trading strategystatistics.

Description

 Conversational wealth management robot system and method  

The present invention relates to a conversational financial robot system and method, and more particularly to a financial investment indicator that can provide a user through a conversational financial robot.

With the rapid advancement of information technology, people's immediate and convenient information acquisition and communication needs are exploding, and there is a great demand for financial investment information. If you can use computers to quickly analyze and predict various financial indicators in real time. Is the problem that most investors want to solve.

In recent years, with the advancement of machine learning technology, task-oriented conversational robots have gradually received attention, and existing conversational robots can only analyze the semantics of users and cannot provide instant personal advice, so conversational Robots are often limited to emotional or customer-oriented systems, and their applications are therefore limited.

The invention provides a system and a method for a conversational wealth management robot, which aims to utilize the financial and economic related open materials opened by domestic and foreign governments to collect, store and analyze various financial indicators through big data, so that the machine can learn by itself. Analyze investor preferences and market information. In addition to proactively reminding investors of risks and suggested actions, this innovative financial management service will not only provide investors with intuitive use experience, but also promote investors to invest in rational investment methods.

The conversational financial robot system of the present invention comprises a communication module and a securities investment artificial intelligence server. The securities investment artificial intelligence server includes an investor behavior analysis module, a financial information analysis module and a database module; the communication module obtains a user dialogue message and transmits an investment analysis message; The securities investment artificial intelligence server generates the investment analysis message according to a personalized response message and a financial investment information; the investor behavior analysis module generates the personalized response message through content analysis according to the user dialogue message; The financial information analysis module generates an instant market data and a historical market data through an internet connection according to the user dialogue message to generate the financial investment information; the database module is configured to store an investor attribute Information, an investor dialogue record, a financial investment statement, the real-time market data, the historical market data, and a financial rule and trading strategy statistics.

In an embodiment of the present invention, the communication module further includes transmitting the user conversation message by using an instant messaging software or a mobile phone short message function.

In an embodiment of the present invention, the above-mentioned securities investment artificial intelligence server further includes analyzing the investment strategy through the financial information analysis module according to the investment target of the user, and providing the user with the user preference and the analysis result. An investment proposal, calculating the trading point of the investment target according to the investment target of the user, giving the user an operation interval suggestion, and the securities investment artificial intelligence server automatically obtaining a market information and analyzing the financial information through the financial information The module generates a push notification.

In an embodiment of the present invention, the investor behavior analysis module further includes using a semantic analysis technique to extract the semantic meaning and investment preference of the user, and generating an investor attribute data, such as investment attributes, risk acceptance, and The investment research method, as well as an investor dialogue record, is generated through a dialogue analysis and a dynamic conversation logic that collects a large number of response trainings to generate the personalized response message.

In an embodiment of the present invention, the financial information analysis module further includes obtaining the static historical market data and the dynamic real-time market data, and performing big data analysis according to the financial rule and the transaction strategy statistics. The market data is in compliance with the conditions that have been trained and can give investors warning or operational advice.

The present invention also provides a method for a conversational wealth management robot, the method comprising: obtaining a user conversation message through a communication module, and then using an investor behavior analysis module of a securities investment artificial intelligence server, according to the user The dialogue message, through content analysis, generates a personalized response message, and through the securities investment AI server, a financial information analysis module, according to the user dialogue message, obtains an instant market data and a history through the Internet connection. Market information, generating a financial investment information, and investing in a database module of the artificial intelligence server for storing an investor attribute data, an investor dialogue record, a financial investment word, the real-time market data The historical market information and a financial rule and trading strategy statistics, through the securities investment artificial intelligence server, generate an investment analysis message according to the personalized response message and the financial investment information, and transmit the information through the communication module The investment analysis message.

In this embodiment, the method further includes: transmitting the user conversation message by using an instant messaging software or a mobile phone short message function.

In this embodiment, the method further includes: using a semantic analysis technique to extract the semantic meaning and investment preference of the user, and generating an investor attribute data, such as investment attributes, risk acceptance and investment research methods, and an investor dialogue record. The personalized response message is generated through conversational content analysis and a dynamic conversation logic that combines a large collection of response training.

In this embodiment, the method further includes: obtaining the static historical market data and the dynamic real-time market data, and performing big data analysis according to the financial rule and the transaction strategy statistics, when the real-time market data meets the trained conditions. , you can give investors advice on warning or operation.

In this embodiment, the method further comprises: analyzing the investment strategy through the financial information analysis module according to the investment target of the user, and providing the user with an investment suggestion based on the user preference and the analysis result, and the investment according to the user's concern. The target is calculated for the trading point of the investment target, the user is given an operation interval suggestion, and the securities investment artificial intelligence server automatically obtains a market information and generates a push notification through the financial information analysis module.

The effect of the present invention is that the conversational financial robot system, combined with the investor behavior analysis and financial information analysis technology, can automatically recognize the investment according to the user's investment preference, in addition to the dynamic training and collecting the investor's preferences. Trading signals on the market, so different investors can be given different investment responses or suggestions, allowing investors to obtain real-time market warnings and investment event analysis in a short period of time, allowing investors to recognize risks in a scientific and digital way. Remuneration can effectively reduce risks and grasp trends when implementing investment strategies, and avoid mistakes caused by irrational influences such as human nature.

110‧‧‧Communication module

120‧‧‧Securities Investment Artificial Intelligence Server

121‧‧‧Investor Behavior Analysis Module

122‧‧‧Financial Information Analysis Module

123‧‧‧Database Module

301‧‧‧ Stocks operation recommendations

302‧‧‧ stock trading information

303‧‧‧ system active warning

S210~S260‧‧‧Step procedure

1 is a block diagram of a conversational financial robot system in accordance with the present invention.

2 is a flow chart showing the steps of a conversational wealth management robot method in accordance with the present invention.

3A to 3C are schematic views showing the operation of the conversational financial robot system according to the present invention.

The above described features and advantages of the present invention will be more apparent from the following description.

1 is a block diagram of a conversational financial robot system of the present invention. In FIG. 1, the conversational financial robot system includes a communication module 110 and a securities investment artificial intelligence server 120. The securities investment artificial intelligence server 120 includes an investor behavior analysis module 121, a financial information analysis module 122, and a database module 123. The communication module 110 obtains a user dialogue message and transmits a message. Investing in the analysis information; the securities investment artificial intelligence server 120 generates the investment analysis message according to a personalized response message and a financial investment information; the investor behavior analysis module 121, according to the user dialogue message, through content analysis, Generating the personalized response message; the financial information analysis module 122 generates an instant market information and a historical market data through the internet connection according to the user dialogue message to generate the financial investment information; the database module 123 For storing an investor attribute data, an investor dialogue record, a financial investment statement, the real-time market data, the historical market data, and a financial rule and trading strategy statistics.

2 is a flow chart showing the steps of the conversational wealth management robot method according to the present invention. The flow of the steps is as follows:

Step S210: Acquire a user conversation message through the communication module.

Step S220: The investor behavior analysis module of the securities investment artificial intelligence server generates a personalized response message through the content analysis according to the user dialogue message.

Step S230: The financial information analysis module of the securities investment artificial intelligence server is used to obtain real-time market data and historical market data through the internet connection according to the user dialogue message, and generate financial investment information.

Step S240: The database module of the AI artificial intelligence server is used to store the investor attribute data, the investor dialogue record, the financial investment word, the real market data, the historical market data, and the financial rule and transaction strategy statistics. .

Step S250: Generate an investment analysis message according to the personalized response message and the financial investment information through the securities investment artificial intelligence server.

Step S260: transmitting the investment analysis message through the communication module.

In this embodiment, the method further includes: transmitting the user conversation message by using an instant messaging software or a mobile phone short message function.

In this embodiment, the method further includes: using a semantic analysis technique to extract the semantic meaning and investment preference of the user, and generating an investor attribute data, such as investment attributes, risk acceptance and investment research methods, and an investor dialogue record. The personalized response message is generated through conversational content analysis and a dynamic conversation logic that combines a large collection of response training.

In this embodiment, the method further includes: generating an immediate response to an individual user through the investor behavior analysis module, and focusing on capturing the user's semantics and investment preferences, and responding promptly to the short-term information, depending on the individual. The user's preferences are designed for service, and a large amount of historical data is used to train the best personalized response mode.

In this embodiment, the method further includes: obtaining the static historical market data and the dynamic real-time market data, and performing big data analysis according to the financial rule and the transaction strategy statistics, when the real-time market data meets the trained conditions. , you can give investors advice on warning or operation.

In this embodiment, the method further comprises: analyzing the investment strategy through the financial information analysis module according to the investment target of the user, and providing the user with an investment suggestion based on the user preference and the analysis result, and the investment according to the user's concern. The target is calculated for the trading point of the investment target, the user is given an operation interval suggestion, and the securities investment artificial intelligence server automatically obtains a market information and generates a push notification through the financial information analysis module.

3A to 3C are schematic diagrams showing the operation of the conversational financial robot system according to the present invention, taking the Facebook Messenger instant messaging software as an example, as follows:

3A: The conversational financial robot system of the present invention includes a user inquiring about a stock operation suggestion, and analyzing the investment strategy according to the target of the user's attention through the communication module 110, and knowing and quantifying the analysis with the user preference and the backtesting. After the result, a stock operation suggestion 301 is generated to give the user an operational suggestion.

FIG. 3B: The conversational financial robot system of the present invention includes a user inquiring about stock transaction information, and through the communication module 110, calculating a trading point for sale and purchase according to the target of the user's attention, generating a stock transaction information 302, and suggesting The operation interval creates a new trading mode for the user and increases the user's willingness to place an order.

Figure 3C: The conversational financial robot system of the present invention includes a system active warning, the system simultaneously collects market information, filters the data, and returns the filtered information for testing, for the valuable information that is highly correlated with the stock price, through the communication The module 110 generates a system active warning 303, and gives a push notification, including a reminder purchase point, a stop loss or a major event date. For example, when the company's revenue announcement is made, the impact of the revenue on the stock price performance can be analyzed immediately, and the financial information data is strengthened. Discriminant and validity.

In this embodiment, the method further includes: transmitting the user conversation message by using an instant messaging software or a mobile phone short message function.

In this embodiment, the method further includes: using a semantic analysis technique to extract the semantic meaning and investment preference of the user, and generating an investor attribute data, such as investment attributes, risk acceptance and investment research methods, and an investor dialogue record. The personalized response message is generated through conversational content analysis and a dynamic conversation logic that combines a large collection of response training.

In this embodiment, the method further includes: obtaining the static historical market data and the dynamic real-time market data, and performing big data analysis according to the financial rule and the transaction strategy statistics, when the real-time market data meets the trained conditions. , you can give investors advice on warning or operation.

In this embodiment, the method further comprises: analyzing the investment strategy through the financial information analysis module according to the investment target of the user, and providing the user with an investment suggestion based on the user preference and the analysis result, and the investment according to the user's concern. The target is calculated for the trading point of the investment target, the user is given an operation interval suggestion, and the securities investment artificial intelligence server automatically obtains a market information and generates a push notification through the financial information analysis module.

In summary, the present invention can provide a better conversational financial robot system and method, combined with investor behavior analysis and financial information analysis technology, in addition to dynamic training and collecting user preferences, the robot can be used The investment preference automatically identifies the trading signals on the investment market, so different investment responses or suggestions can be given to different users.

While the present invention has been described above in the foregoing embodiments, it is not intended to limit the invention, and the equivalents of the modifications and retouchings are still in the present invention without departing from the spirit and scope of the invention. Within the scope of patent protection.

Claims (10)

 A conversational financial management robot system, comprising: a communication module, obtaining a user dialogue message, and transmitting an investment analysis message; a securities investment artificial intelligence server, generating the information according to a personalized response message and a financial investment information The investment analysis message includes: an investor behavior analysis module, based on the user dialogue message, generating the personalized response message through content analysis; a financial information analysis module, based on the user dialogue message, through the Internet The link obtains an instant market data and a historical market data to generate the financial investment information; and a database module for storing an investor attribute data, an investor dialogue record, a financial investment term, and the real-time market data. , historical market data and a financial rule and trading strategy statistics.    The conversational financial robot system of claim 1, wherein the communication module further comprises transmitting the user conversation message through an instant messaging software or a mobile phone short message function.    The conversational wealth management robot system of claim 1, wherein the securities investment artificial intelligence server further comprises: analyzing the investment strategy through the financial information analysis module according to the investment target of the user, and matching the user with the user The preference and analysis result gives the user an investment suggestion, calculates the trading point of the investment target according to the investment target of the user, gives the user an operation interval suggestion, and the securities investment artificial intelligence server automatically obtains a market. Information and a push notification is generated through the financial information analysis module.    For example, in the conversational financial robot system described in claim 1, wherein the investor behavior analysis module further comprises using a semantic analysis technique to extract the semantic meaning and investment preference of the user, and generate an investor attribute data, such as an investment. Attributes, risk acceptance and investment research methods, as well as an investor dialogue record, generate this personalized response message through a dialogue analysis and a dynamic conversation logic that collects a large number of response trainings.    The conversational wealth management robot system of claim 1, wherein the financial information analysis module further comprises obtaining the static historical market data and the dynamic real-time market data, and according to the financial rules and transaction strategy statistics. Perform big data analysis, and when the immediate market data meets the conditions of training, investors can be advised to warn or operate.    A conversational wealth management robot method, comprising: obtaining a user dialogue message through a communication module; and using an investor behavior analysis module of a securities investment artificial intelligence server, according to the user dialogue message, through content analysis, Generate a personalized response message; use a financial information analysis module of the securities investment AI server to generate a real-time market information and a historical market data through the Internet connection based on the user dialogue message, and generate a financial investment information Translating, by the securities, a database module of the artificial intelligence server for storing an investor attribute data, an investor dialogue record, a financial investment sentence, the real-time market data, the historical market data, and a financial rule And trading strategy statistics; through the securities investment artificial intelligence server, generating an investment analysis message based on the personalized response message and the financial investment information; and transmitting the investment analysis message through the communication module.    The method of the conversational financial robot of claim 6, wherein the step of obtaining a user conversation message through a communication module further comprises: transmitting the user conversation message through an instant messaging software or a mobile phone short message function.    The method of conversational financial management robot according to claim 6, wherein an investor behavior analysis module of a securities investment artificial intelligence server generates a personalized response message through content analysis according to the user dialogue message. The steps include: using a semantic analysis technique to capture the user's semantics and investment preferences, and generating an investor attribute data, such as investment attributes, risk acceptance and investment research methods, and an investor dialogue record through dialogue. The content analysis, combined with a large number of dynamic conversation logic for collecting response training, generates the personalized response message.    The method of conversational wealth management robot according to claim 6, wherein a financial information analysis module of the securities investment artificial intelligence server obtains an instant market data through an internet connection according to the user dialogue message. And a historical market data, the step of generating a financial investment information, further comprising: obtaining the static historical market data and the dynamic real-time market data, and performing big data analysis according to the financial rules and transaction strategy statistics, The market data is in compliance with the conditions that have been trained and can give investors warning or operational advice.    The method for processing a conversational financial robot according to claim 6, wherein the step of generating an investment analysis message according to the personalized response message and the financial investment information through the securities investment artificial intelligence server further comprises: According to the investment target that the user pays attention to, through the financial information analysis module, analyze the investment strategy, and give the user an investment suggestion based on the user preference and analysis result, and calculate the investment target for sale and purchase according to the investment target of the user's attention. The trading point gives the user an operation interval suggestion, and the securities investment artificial intelligence server automatically obtains a market information and generates a push notification through the financial information analysis module.