KR101909706B1 - Robo advisor system based on investor and financial product and method for providing portfolio using the same - Google Patents

Abstract

The present invention relates to a robo advisor system. To this end, a robo advisor system based on analytical data on financial products and investors is provided comprising: an investment propensity analysis server providing, to a client terminal, analysis questionnaire data having a plurality of group forms including a plurality of related query information, receiving response data for each query information corresponding thereto, and analyzing at least two of a customer′s risk management tendency, investment period, income status, income stability, health, consumption propensity, asset level, asset type, and debt type based on the received response data to generate the customer′s investment propensity analysis data; a financial product analysis server receiving information on a plurality of financial products provided by a securities company, a bank, and an insurance company through a financial company interworking platform, analyzing at least two of financial manager reputation information, market maturity information, and investment scale information based on the received information, generating trend information for each of the plurality of financial products based on the analyzed at least two information, and storing the trend information in a financial product database; and a recommended goods matching server searching the financial product database for a financial product having propensity information similar to that of the investment propensity analysis data within a predetermined range, generating a recommended portfolio by using the financial product, and providing the generated recommended portfolio to the client terminal. The present invention is able to accurately analyze investment propensities of a client, thereby increasing an investment success rate.

Description

TECHNICAL FIELD [0001] The present invention relates to a system and method for providing an investment portfolio based on analysis data of financial products and investors, and a method of providing an investment portfolio using the system.

The present invention relates to a financial adviser system based on analytical data of financial products and investors, and a method of providing an investment portfolio using the same.

In general, portfolio selection theory is widely used as a method for investing and allocating assets most advantageously.

According to the portfolio selection theory, which is one of the strategies for effective asset investment, if the expected return is the same for the asset investment, the combination of the asset type group with low risk is selected and if the risk burden is the same, It is possible to combine the products of the asset type group. While investors may manage their own assets by creating portfolios to manage their own assets, securities firms also provide services for investors visiting their branches to create a portfolio based on current investment products.

Since the composition of this portfolio is varied according to the investment propensity of each individual user, it has been difficult to construct a portfolio that matches his or her propensity. In order to conduct professional consultation, visit the branch office of the relevant securities company and wait for a long time , And it is difficult to receive various information in real time due to limited consulting time.

In addition, since the financial service branch office recommends the products directly to the customers and creates the portfolio, the quality of the portfolio may be different depending on the competence of the staff. Also, the inconsistent investment direction A portfolio can be constructed according to the reliability of the portfolio.

Even if a contract is made based on the creation of a primary portfolio, if it is maintained for a long time, the market will not be able to respond quickly to changing market conditions, and the likelihood of a decline in profitability will increase. To this end, it is extremely difficult for an investor to change a portfolio composed of various assets (adjustment of asset group allocation) in consideration of all market conditions.

Korean Patent Publication No. 10-2017-0034647 (published on Mar. 29, 2017)

The present invention relates to a financial advisory system based on analytical data of financial products and investors that can provide a portfolio composed of financial products that meet customer's investment propensity based on customer's investment propensity information and financial propensity information, Provide a method of providing.

The present invention also relates to a financial advisory system based on analytical data of financial products and investors, which can analyze future propensity of customers and their investment propensity by analyzing customer propensity by including information related to customer's health and investment Provide a portfolio offering method.

In addition, the present invention collects environmental factor information related to investment, changes the tendency information of the financial product based on collected environmental factor information, and changes the financial product constructed in the portfolio, And provides a method of providing an investment portfolio using the analytical data base of the financial products and investors that can be minimized.

In order to solve the problems to be solved, the robot adviser system based on the analytical data of the financial products and the investors according to the embodiment of the present invention is provided with a function of the customer's risk management tendency, investment period, income status, At least one analysis query information which is connected to one of main areas of an asset level, an asset type and a debt type, and connected to a plurality of evaluation areas corresponding to each of the main areas, A score for a plurality of evaluation regions connected to the provided analysis query information is calculated on the basis of the answer information, and the evaluation score for each evaluation region is calculated using the scores for the calculated evaluation regions, An investment propensity analysis server for generating investment propensity information of a customer based on the calculated evaluation score, The information processing apparatus according to any one of claims 1 to 3, further comprising: information receiving means for receiving information on a plurality of financial products provided by a securities company, a bank, and an insurance company through a financial transaction platform and managing at least two of manager's reputation information, market maturity information, A financial product analysis server for generating trend information for each of a plurality of financial products based on the analyzed financial information and storing the information in a financial product database, and a financial product analyzing server for analyzing the financial propensity information and the financial product having similar tendency information within a predetermined range And a recommended goods matching server for searching the financial product database, creating a recommended portfolio using the retrieved recommended portfolio, and providing the generated recommended recommended portfolio to the client side terminal.

According to an embodiment of the present invention, the robot advisor system interlocks with at least one information providing server to provide at least two environmental factor information among search keyword related big data analysis information, interest rate fluctuation and prediction information, news information, Wherein the financial product analysis server checks the reactivity of each of the plurality of financial products with respect to the collected environmental factor information to determine whether or not each of the plurality of financial products Can be changed.

According to the embodiment of the present invention, the robo advisor system calculates a return rate for each financial product in the recommended portfolio after a predetermined time elapses after providing the recommended portfolio, and compares the calculated return rate with the standard rate of return And the degree of mismatch between the investment propensity analysis data of the customer and the propensity information of the financial product is determined by using the checked reactivity, And an investment logic verification server for detecting an error portion with respect to the logic and selecting a financial instrument capable of supplementing the detected error portion from the financial instrument database and using the same to change a financial instrument in the recommended portfolio .

According to an embodiment of the present invention, the investment propensity analysis server collects at least one of health information and asset change information of a customer received from the external server through interworking with an external server, The investment propensity information can be changed based on the investment propensity information.

According to an embodiment of the present invention, the robot advisor system receives evaluation information about each financial product in the recommended portfolio from the customer side terminal after a predetermined time elapses after providing the recommended portfolio, And an investment logic verification server for calculating an error rate between the propensity information for each of the financial products and the investment propensity information for the customer on the basis of the evaluation information and then changing the financial product in the recommended portfolio based on the calculated error rate.

In order to solve the problems to be solved, an investment portfolio providing method using a financial advisory system based on analytical data of a financial product and an investor according to an embodiment of the present invention is implemented in a broker advisor system, Analyzing at least two of manager reputation information, market maturity information, and investment scale information for managing a financial product based on the received information, and analyzing at least two of the plurality of financial instruments based on the analyzed information. The method comprising the steps of: generating trend information for each of the financial products and storing the trend information in the financial product database; and analyzing the main region of the customer's risk management tendency, investment period, income status, income stability, health, consumption propensity, The main area is connected to one of the main areas, Receiving at least one analytical query information connected to a plurality of evaluation regions corresponding to each of the plurality of evaluation regions in response to a request of the client terminal and receiving answer information therefrom; Calculating an evaluation score for each evaluation area using the score for each of the evaluation areas calculated and then generating investment propensity information of the customer based on the calculated evaluation score; Searching for a financial product having investment propensity information and similar propensity information within a predetermined range in the financial product database and using the same to generate a recommended portfolio, and providing the generated recommended portfolio to the customer terminal . ≪ / RTI >

According to an embodiment of the present invention, the investment portfolio providing method may include at least one of providing at least one information providing server in the robo advisor system with at least one of search keyword related big data analysis information, interest rate fluctuation and forecast information, news information, The method comprising the steps of: collecting at least two environmental factor information; checking the responsiveness of each of the plurality of financial products to the collected environmental factor information; and changing the propensity information for each of the plurality of financial products according to the checked reactivity .

According to an embodiment of the present invention, the method of providing an investment portfolio may further include: calculating a rate of return for each financial product in the recommended portfolio when a predetermined time elapses after providing the recommended portfolio; Checking the responsiveness to the environmental factor information of a financial instrument that has recorded a return rate lower than a standard rate of return through a comparison between the return rates of the financial products and a response mismatch between the investment tendency analysis data of the customer and the propensity information of the financial product The method comprising the steps of: detecting an error part of an investment logic by judging a degree of an error in a financial product; searching for a financial product that can complement the detected error part in the financial product database, As shown in FIG.

According to an embodiment of the present invention, the step of generating the investment propensity information includes receiving at least one of the health information and the asset change information of the customer from the external server in cooperation with an external server, And changing the investment propensity information based on one information.

According to an embodiment of the present invention, the method of providing an investment portfolio includes receiving evaluation information on each financial instrument in the recommended portfolio from the customer terminal when a predetermined time elapses after providing the recommended portfolio, Calculating an error rate between the propensity information for each of the financial products and the investment propensity information for the customer on the basis of the received evaluation information and changing the financial product in the recommended portfolio based on the error rate can do.

According to the present invention, it is possible to provide a portfolio composed of financial products that match the customer's investment propensity based on the analysis of the customer's investment propensity and the propensity of the financial product.

In addition, according to the above-mentioned object of the present invention, it is possible to improve the investment success rate by analyzing the tendency of the customer including the information related to the health of the customer, .

According to an aspect of the present invention, there is provided an information processing method for collecting environment factor information related to an investment, changing a tendency of a financial product based on collected environmental factor information, and changing a financial product constructed in the portfolio, It is possible to minimize the investment loss due to external environmental factors.

1 is a network configuration diagram showing an overall connection relationship of a robo advisor system according to an embodiment of the present invention.
2 is a block diagram showing a detailed configuration of a robot advisor system according to an embodiment of the present invention.
3 is a block diagram illustrating a detailed configuration of an investment propensity analysis server according to an embodiment of the present invention.
4 is a diagram for explaining the structure of query information for analysis according to an embodiment of the present invention.
5 is an exemplary diagram illustrating investment propensity information generated by an investment propensity analysis server of a robo advisor system according to an embodiment of the present invention.
FIG. 6 is a flowchart illustrating a process of providing analysis query information to a client terminal in an investment propensity analysis server according to an embodiment of the present invention.
FIG. 7 is a flowchart illustrating a process in which an investment propensity analysis server according to an embodiment of the present invention generates investment propensity information of a customer.
FIG. 8 is a flowchart illustrating a process of creating a recommended portfolio using the robo advisor system according to an embodiment of the present invention.

Hereinafter, specific embodiments of the present invention will be described with reference to the drawings. The following detailed description is provided to provide a comprehensive understanding of the methods, apparatus, and / or systems described herein. However, this is merely an example and the present invention is not limited thereto.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the following description, well-known functions or constructions are not described in detail since they would obscure the invention in unnecessary detail. The following terms are defined in consideration of the functions of the present invention, and may be changed according to the intention or custom of the user, the operator, and the like. Therefore, the definition should be based on the contents throughout this specification. The terms used in the detailed description are intended only to describe embodiments of the invention and should in no way be limiting.

1 is a network configuration diagram showing an overall connection relationship of a robo advisor system according to an embodiment of the present invention and includes a customer terminal 100, a financial company interworking platform 200, a robot advisor system 300, and the like have. At this time, the robot advisor system 300 and the customer-side terminal 100 may be connected through a wired or wireless communication network (not shown).

As shown in FIG. 1, the financial institution interworking platform 200, which is interlocked with the robot advisor system 300 and provides data on financial products, may include a securities company API, a bank API, an insurance API, , A securities company, a bank, an insurance company, and other financial institutions, and then provide the corresponding data to the robot adviser system 300. [

The customer-side terminal 100 can access the robot advisor system 300 and display and receive data corresponding to the investment propensity analysis and the financial product recommendation service.

Such a client-side terminal 100 is a computing device that can be connected to a network and can execute various types of applications. Examples of the computing device include a notebook computer, a personal computer, a smart phone, and the like. Specifically, the computing device corresponding to the customer-side terminal 100 is provided with a communication circuit 102 capable of supporting connection to the robo advisor system 300, and various services through interlocking with the robo advisor system 300 At least one processor 106 for executing applications, a display unit 108 for displaying various services in an identifiable form by the user, various inputs and outputs And an input / output circuit 110 for processing the input / output signals.

The RoboAdvisor system 300 is a system for providing a customer with a portfolio for investment based on the information obtained through quantitative and qualitative analysis of financial products and customers. It analyzes the investment propensity of the customer, The recommended portfolio can be generated by matching at least one financial product matching the investment propensity of the customer through the matching of the analyzed information and providing the generated recommended recommended portfolio to the client side terminal 100. [

Also, the robo advisor system 300 checks the responsiveness of the financial product based on the investment-related information collected by the external information collection server 308, and updates the tendency analysis information of the financial product according to the responsiveness It is possible to change the financial products in the recommended portfolio through the re-matching process between the tendency analysis information of the financial product and the investment propensity of the customer.

On the other hand, the robo advisor system 300 can update the investment analysis standard for determining the investment propensity of the customer and the tendency of the financial product based on the information collected by the external information collection server 308 have.

The robot adviser system 300 is based on a process of deriving a customer investment propensity, that is, a process of analyzing query information and response information provided to a customer, a process of selecting a financial product according to a customer's investment propensity, Investment logic can be created.

In addition, the robot advisor system 300 verifies the investment logic through the analysis of the yield of the financial products in the recommended portfolio as a predetermined period, for example, 3, 6, 9 and 12 months, and then, based on the result of the verification, Financial products can be changed. Specifically, the robo advisor system 300 not only checks the responsiveness of the external information to the financial products having low returns, but also reflects the opinions of the experts, It is possible to detect an error part of the investment logic by judging the degree of mismatch between information and to select a financial product that can complement the detected error part and use it to change the financial product in the recommended portfolio.

Hereinafter, the detailed configuration and operation of the robot advisor system 300 will be described with reference to FIG.

2 is a block diagram showing the detailed configuration of the robot advisor system 300 according to the embodiment of the present invention.

2, the robot advisor system 300 includes an investment propensity analysis server 302, a financial product analysis server 304, a recommended goods matching server 306, an external information collection server 308, Server 310 and automated teller machine support server 312 and may additionally include a membership information database 314, a financial product database 316 and an investment logic database 318.

First, the investment propensity analysis server 302 provides analytic query information in a plurality of query / response formats to the client side terminal 100, receives answer information therefrom, and based on the received response data, The investment propensity information of the customer can be generated by analyzing the investment propensity. 3, the investment propensity analysis server 302 includes a query information database 322, a query information provider 324, a score calculation unit 326, and an investment propensity information generation unit 328, , ≪ / RTI >

As shown in FIG. 4, the query information database 322 stores a plurality of query information for analysis connected to one main area 320a and to which a plurality of evaluation areas 320b are connected. Here, the main area 320a connected to the analysis query information is any one of a risk management tendency, an investment period, health, income stability, consumption status, asset level, asset type, The evaluation area 320b may include all of the data corresponding to the main area 320a. At this time, the evaluation area 320b corresponding to the main area 320a connected to the analysis query information among the plurality of evaluation areas 320b may be the main evaluation area 320b. In other words, any one of the plurality of evaluation areas 320b may be the same data as the main area 320a. For example, the analysis query information linked to the main area 320a of the risk management tendency may be connected to a plurality of evaluation areas 320b including the evaluation area 320b corresponding to the risk management tendency.

On the other hand, the analytical query information is divided into a customer's personal information group, an import / expense group, and an asset management group, and each group can include a plurality of query information for analysis.

The query information providing unit 324 selects at least one or more of the plurality of query information for analysis stored in the query information database 322 according to the investment molding analysis request of the client terminal 100 and transmits the selected query information to the customer terminal 100 .

The query information providing unit 324 searches the query information database 322 for one query information for analysis and provides the query information to the client terminal 100. After the response information is received from the client terminal 100, And the analysis-use query information is retrieved from the query information database 322 and provided to the client-side terminal 100 by providing the query information in association with the answer information. Specifically, the query information providing unit 324 receives a score for a plurality of evaluation regions connected to the query information for analysis calculated by the score calculating unit 326 from the score calculating unit 326, The user can search the query information database 322 for analysis query information linked to the selected main area and select the main area based on the score for the area, and provide the search query information to the client side terminal 100. [ For example, if the score of the evaluation area related to the investment period is high among the scores of the plurality of evaluation areas calculated based on the answer information after providing the query information for analysis related to the risk management tendency, Can search the query information database 322 for analysis query information having the investment period as the main domain and provide the query information to the client terminal 100. [

On the other hand, the query information providing unit 324 counts the number of query information for analysis provided for each main area whenever the query information for analysis is provided to the client terminal 100, and provides the information to the investment propensity information generating unit 328 .

The score calculation unit 326 provides analysis query information to the client side terminal 100 by the query information provision unit 324 and then transmits the analysis query information to the client side terminal 100 using the response information received from the client side terminal 100 And may provide the calculated score to the query information providing unit 324 or the investment propensity information generating unit 328. [

The investment incentive information generating unit 328 evaluates the investment incentive information based on the scores of the plurality of evaluation areas for analysis use query information provided from the score calculating unit 326 after the predetermined analytical query information is provided to the client terminal 100 It is possible to calculate the score for each area.

The investment propensity information generating unit 328 may calculate the evaluation score by reflecting the number of analytical query information for each main area provided from the query information providing unit 324 when calculating the evaluation score for each evaluation area. Specifically, the investment propensity information generation unit 328 calculates the investment propensity information based on the answer information for the analysis query information when the number of analysis query information for a specific main area exceeds a predetermined number (exceeds a predetermined threshold value) It is possible to calculate an evaluation score for an evaluation area corresponding to a specific main area by calculating a predetermined weight to a score associated with the evaluation area corresponding to the specific main area among the scores of the plurality of evaluation areas. For example, when the evaluation score for the evaluation area of the risk management tendency is calculated while the analytic query information linked to the risk management tendency is provided to the customer side terminal 100 exceeding the predetermined number, (For example, a weight below the reference value) to the score for the evaluation area of the risk management tendency calculated from the analysis query information connected to the main area other than the risk management tendency, The score for the risk management tendency can be calculated by calculating the score for the evaluation area of the risk management tendency calculated from the calculated scores and the quality information for analyzing the risk management tendency.

When calculating the evaluation score for each evaluation area using the answer information for the analysis query information, if the evaluation area is the same as the main area of the analysis query information, the investment tendency information generation unit 328 If the evaluation area is different from the main area of the analytical query information, the weight is given to the evaluation score and a score below the reference value is calculated, and the score is calculated to calculate the evaluation score of the evaluation area Can be calculated. For example, when calculating the evaluation score for the evaluation area of the asset type, the score of the evaluation area of the asset type obtained from the answer information of the analysis query information connected to the main area of the asset type is given a weight that is larger than the reference value, And calculating a score by assigning a weight below the reference value to the score of the evaluation area of the asset form acquired from the answer information of the analysis query information connected to the main area other than the main area of the asset form The evaluation score for the evaluation area of the asset type can be calculated.

On the other hand, the investment propensity information generating unit 328 can calculate the evaluation score based on the number of pieces of analysis query information for each main region provided to the customer-side terminal 100 in calculating the evaluation score for each evaluation region. Specifically, when the number of analytical query information from which a specific evaluation region for which an evaluation score is to be calculated is greater than or equal to a predetermined number, the investment tendency information generation section 328 calculates the investment tendency information of analytical query information The score of the specific evaluation area derived from the answer information, and the score of the specific evaluation area derived from the answer information of the analytical query information of the specific evaluation area and the main area are assigned different weights, Can be calculated.

On the other hand, the investment propensity information generation unit 328 calculates the evaluation score for each evaluation area by the above-described method, and generates the investment propensity information of the customer through analysis of the calculated evaluation score for each evaluation area.

For example, as shown in FIG. 5, the investment propensity information generating unit 328 calculates the score calculated based on the answer information on the query information for analysis related to health to calculate the evaluation score, It is possible to generate analysis summary information such as customer's psychology, income stability and consumption propensity through analyzing the score. Also, if analysis query information related to family history is further included in the quality query information related to health, Psychology, income stability, and consumption propensity. Then, based on this information, customers' investment propensity information can be generated.

In the embodiment of the present invention, the investment propensity information may be information in the form of a combination of short-term, medium-term, long-term, offensive (dangerous), stable, For example, information on investment propensity can be information such as investment access needs such as medium-term attack, medium-term stabilization, short-term attack, and short-term stabilization.

Meanwhile, the investment incentive analysis server 302 according to an embodiment of the present invention may interwork with an external information providing server, for example, a hospital server (not shown), a bank server (not shown) Asset status, expenditure status, etc., and can be used to generate investment propensity analysis information. Specifically, the investment propensity analysis server 302 can receive hospital history information, asset status, expenditure status, and the like of a customer and its family by being connected to a hospital server, a bank server, and the like based on the agreement of the customer.

The answer information and the investment propensity information analyzed by the investment propensity analysis server 302 as described above can be stored in the member information database 314.

On the other hand, the investment propensity analysis server 302 provides an interface for receiving customer search information to the customer-side terminal 100, collects site information, query word information, etc., used by the customer through the interface, Can be changed. Specifically, the investment propensity analysis server 302 monitors the behavior of the customer on the customer side terminal 100, that is, on the customer side terminal 100 registered at the time of membership registration, when the customer who is a member of the robot advisor system 300 For example, a web beacon to the customer-side terminal 100, collects site information, search word information, and the like used by the customer through the provided web beacon, derives a customer interest field based on the collected site information, The investment propensity information can be updated based on the field.

A process of analyzing a customer's investment propensity by the investment propensity analysis server 302 having the above-described configuration will be described with reference to FIGS. 6 and 7. FIG.

6 is a flowchart illustrating a process of providing analytic query information to the client side terminal 100 in the investment propensity analysis server 302 according to an embodiment of the present invention.

6, when a service subscription or investment propensity analysis request is first received from the customer terminal 100, the investment propensity analysis server 302 analyzes an analysis (analysis) connected to one of the main areas in the query information database 322, In operation S600, the number of times of providing the query information for analysis is counted in operation S602.

Then, when answer information for a plurality of analytical query information is received from the client side terminal 100 (S604), the investment tendency analysis server 302 calculates a plurality of evaluation regions (S606).

Thereafter, the investment propensity analysis server 302 determines whether the number of times of provision has reached a predetermined number (S608).

If it is determined in step S608 that the provided number of times has not reached the preset number of times, the investment propensity analysis server 302 selects the main area based on the score for the plurality of evaluation areas (S610), and then proceeds to step S600 . That is, the investment propensity analysis server 302 searches the query information database 322 for analysis query information linked to the selected main area, and provides the query information to the customer terminal 100.

On the other hand, if it is determined in step S608 that the number of times of provision has reached the preset number of times, the investment propensity analyzing server 302 may calculate the number of times of providing the evaluation domain by using the scores of the plurality of evaluation areas, (S612), and then generates the investment propensity information of the customer based on the score. This will be described with reference to FIG.

7 is a flowchart illustrating a process of generating investment propensity information of a customer by the investment propensity analysis server 302 according to an embodiment of the present invention.

7, first, the investment propensity analysis server 302 calculates a score of a plurality of evaluation regions calculated on the basis of the answer information for analytical query information connected to the first main region provided to the customer-side terminal 100 (Hereinafter referred to as " same area score ") of the evaluation area corresponding to the first main area among the plurality of evaluation areas (S700).

Then, the investment propensity analysis server 302 calculates an evaluation domain corresponding to the first main area among the scores of the plurality of evaluation domains calculated on the basis of the answer information on the analysis query information linked to the main domain other than the first main domain, (Hereinafter referred to as " another area score ") (S702).

Thereafter, the investment propensity analysis server 302 calculates a first evaluation value by assigning a first weight value (e.g., a value larger than a reference value) to the same area score (S704), and assigns a second weight value (Step S706), the first and second evaluation values are calculated to calculate the evaluation score for the first main area (i.e., the first evaluation area) (S708) .

The above steps are repeatedly performed to calculate the evaluation score for the evaluation area corresponding to each main area.

Thereafter, the investment propensity analysis server 302 generates the investment propensity information of the customer based on the evaluation score of each evaluation area (S710).

Before performing the step of weighting, the investment propensity analysis server 302 determines that only the main region whose number of analysis query information provided to the client side terminal 100 is greater than or equal to a predetermined number is provided to the client side terminal 100 for each main region, The evaluation score can be calculated using the grant method. In this case, the investment propensity analysis server 302 can calculate the score of the evaluation area by calculating a score for the evaluation area when the counted number is less than a predetermined number.

According to the embodiment of the present invention described above, the evaluation score for each evaluation area is calculated by the weighting method, but it is also possible to calculate the evaluation score for each evaluation area through correlation analysis. In this case, when a correlation between the average value of the scores of the evaluation region and the score of the evaluation region, for example, a correlation function is applied and the resultant value exceeds a predetermined value, for example, 0.5 to 0.7 (a high correlation value) -0.7, and an evaluation score for the evaluation area can be calculated using scores other than the excluded scores.

The financial product analysis server 304 receives financial data, such as financial product data, in cooperation with a securities company server, a bank server, and an insurance company server through a financial company interworking platform 200 and analyzes the received financial product data, And store it in the financial product database 316. [0040] FIG. Specifically, the financial product analysis server 304 collects reputation information of a manager using manager information for managing financial products using financial data, determines the maturity level of the financial product investment, Etc., and generate tendency information on the financial product based on the analysis.

The tendency information of the financial product generated by the financial product analysis server 304 according to the embodiment of the present invention has a form of combination of the medium term, short term, long term, attack type (risk type), insurance type, And may be stored in the financial product database 316.

On the other hand, the propensity information of the financial product analyzed by the financial product analysis server 304 may be changed according to external environmental factors. Specifically, the financial product analysis server 304 checks the responsiveness of each financial product based on the environmental factor information, and may change the tendency information of the financial product if the responsiveness is equal to or greater than a predetermined threshold value.

To this end, the robo advisor system 300 according to the embodiment of the present invention may further include an external information collection server 308. [

The external information collection server 308 can collect environmental factor information related to the investment in cooperation with various external servers such as a search server, a rate providing server, a price management server, a media information providing server, and the like. Herein, the environmental factor information includes big data analysis information on the search keyword, price data, news information recently issued, interest rate information, and the like. Big data analysis information includes a search keyword by age group, a search keyword distribution status Information.

The recommended goods matching server 306 searches at least one financial product in the financial product database 316 based on the investment propensity information of the customer and can generate an investment portfolio composed of the retrieved financial products. Specifically, the recommended goods matching server 306 searches the financial product database 316 for a financial product matching the investment propensity information, for example, a financial product related to the insurance property, a safe asset type financial product, a high risk asset type financial product, A recommended asset portfolio type recommended portfolio and a high risk asset type recommended portfolio according to the investment propensity of the customer, and generates a comprehensive recommendation portfolio based on the created portfolio. The generated portfolio is transmitted to the client side terminal 100, Lt; / RTI >

Also, the recommended product matching server 306 generates investment logic based on information on the matching process, for example, a process of calculating investment propensity information and a financial product matching process, and transmits the generated investment logic to the investment logic database 318. [ Lt; / RTI >

The investment logic verification server 310 is a device that operates after a predetermined time elapses after providing a comprehensive recommendation portfolio to a customer. The investment logic verification server 310 calculates a return on a financial product in a comprehensive recommendation portfolio, The return rate set by the adviser system or the return rate set for the financial product) is compared with the standard rate of return, it is possible to check the investment logic through the verification process of the information of the customer's investment propensity and the tendency of the financial product. Specifically, the investment logic verification server 310 not only checks the responsiveness of external information to the financial products whose yields are lower than the standard rate of return among the financial products in the recommendation portfolio, but also reflects the opinions of the experts, The degree of mismatch between the tendency analysis information of the financial product is determined to detect an error portion of the investment logic, and the investment logic stored in the investment logic database 318 is updated based on the detected error portion. In addition, After selecting a financial product, it can be used to change the financial product in the comprehensive recommendation portfolio.

In addition, the investment logic verification server 310 receives the evaluation information for each of the financial products in the comprehensive recommendation portfolio from the client side terminal 100 after a predetermined time has elapsed after providing the comprehensive recommendation portfolio, , The error rate between the propensity information for each of the financial products in the comprehensive recommendation portfolio and the investment propensity information for the customer can be calculated and the financial product in the comprehensive recommendation portfolio can be changed based on the error rate.

The automated teller machine support server 312 provides the customer's terminal 100 with a comprehensive recommendation portfolio, and then provides customer information to a service server (not shown) that sells the financial instrument selected by the customer, And so on.

A process of generating a recommendation photopolis using the robot advisor system 300 having the above-described configuration will be described with reference to FIG.

FIG. 8 is a flowchart illustrating a process of generating a recommended portfolio using the robo advisor system 300 according to an embodiment of the present invention.

8, the robot advisor system 300 is connected to a securities company, a bank, an insurance company, and other financial companies through a financial company interworking platform 200, receives data on a plurality of financial products, The manager's reputation information, the market maturity invested by the financial product, the investment scale of the financial product, and the like, and generates trend information for a plurality of financial products based on the analyzed information (S800).

Thereafter, the robot advisor system 300 matches trend information to a plurality of financial product names and stores them in the financial product database 316 (S802).

Next, the robot advisor system 300 collects environmental factor information that influences the investment (S804), and checks the degree of reactivity to each of the financial products according to the collected environmental factor information, that is, the degree of influence on the financial product (S806). If the checked reactivity exceeds the predetermined threshold, the tendency information on the financial product exceeding the threshold is re-analyzed to update the tendency information of the financial product (S808). Specifically, the robot advisor system 300 can change the trend information of the financial product using the checked reactivity.

Then, the robot advisor system 300 provides a plurality of query information for analysis to the client terminal 100 in response to a request of a customer, that is, a request for membership of a customer, (S810).

The robot advisor system 300 then determines the risk management tendency, the investment period, the income status, the income stability, the health, the consumption propensity, the asset level, the asset type and the like of the customer based on the answer information received from the customer- At least two of the types of the debt are analyzed to generate the investment propensity information of the customer (S812).

Then, the robo advisor system 300 searches the financial product database 316 for a financial product having propensity information matching the investment molding information, generates a recommended portfolio composed of the retrieved financial products, To the customer-side terminal 100 (S814). As a result, customers can invest in financial products based on a recommended portfolio.

When a predetermined period of time has elapsed since the investment in the financial product, the robo advisor system 300 calculates a return rate for each of the financial products in the recommended portfolio (S816), and calculates the return rate and the standard rate of return Or a financial product having a return rate lower than the standard rate (step S818).

As a result of the determination in S818, if there is a financial product, the robo advisor system 300 checks the investment logic through the verification process for the propensity information on the financial product having the return rate lower than the standard return rate and the information about the customer's investment propensity (S820 ). Specifically, the investment logic verification server 310 not only checks the reactivity of the financial products in the recommended portfolio with respect to the external information for the financial products whose yield is lower than the standard rate of return, but also reflects the opinions of the experts, (Step S822). In step S822, the financial product in the recommended portfolio is changed using the selected financial product to detect the error part of the investment logic by determining the degree of mismatch between the tendency analysis information of the product, .

It will be understood by those of ordinary skill in the art that the foregoing description of the embodiments is for illustrative purposes and that those skilled in the art can easily modify the invention without departing from the spirit or essential characteristics thereof. It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive. For example, each component described as a single entity may be distributed and implemented, and components described as being distributed may also be implemented in a combined form.

It is intended that the present invention covers the modifications and variations of this invention provided they come within the scope of the appended claims and their equivalents. .

100: Customer side terminal
200: Interlocking platform of financial companies
300: RoboAdvisor System
302: Investment propensity analysis server
304: financial instrument analysis server
306: Recommended product matching server
308: External information collection server
310: Investment logic validation server
312: Automated marketing support server
314: Member information database
316: financial product database
322: Query information database
324: Query information provisioning
326: score calculation unit
328: Investment propensity information generating unit

Claims (10)

Wherein the main region is connected to one of main regions of a customer's risk management tendency, investment period, income status, income stability, health, consumption propensity, asset level, asset type and debt type, Providing at least one analytical query information connected to the evaluation region according to a request of the client terminal and calculating a score for a plurality of evaluation regions connected to the provided analytical query information based on the answer information, An investment propensity analyzing server for calculating an evaluation score for each evaluation area by using a score for each evaluation area and generating investment propensity information of the customer based on the calculated evaluation score,
A financial institution interworking platform for receiving information on a plurality of financial products provided by a securities company, a bank, and an insurance company, and managing at least two of manager reputation information, market maturity information, and investment scale information for managing financial products based on the received information A financial instrument analysis server for analyzing and analyzing the financial information and generating tendency information for each of the plurality of financial instruments based on the calculated tendency information,
A recommendation portfolio searching unit for generating a recommendation portfolio by searching the financial instrument database for financial instruments having similar tendency information within a predetermined range with the investment propensity information and providing the recommendation portfolio to the customer terminal A matching server,
An external information collection server collecting big data analysis information related to a search keyword through interworking with at least one information providing server, and collecting at least two environmental factor information among interest rate fluctuation, forecast information, news information and price information, ,
The financial instrument analysis server comprises:
Checking the reactivity of each of the plurality of financial products with respect to the collected environmental factor information and the big data analysis information related to the search keyword and changing the tendency information for each of the plurality of financial products according to the checked reactivity, An investor's analytical data-based RoboAdvisor system.
delete The method according to claim 1,
Wherein the robot advisor system comprises:
And calculating a return on each of the financial instruments in the recommended portfolio when a predetermined time elapses after providing the recommended portfolio, and comparing the calculated return rate with the standard rate of return, Environmental factor information, and search keyword related big data analysis information, and determines the degree of mismatch between the investment propensity analysis data of the customer and the propensity information of the financial product using the checked reactivity, And an investment logic verification server for selecting a financial instrument from the financial instrument database that can complement the detected error portion and using the same to change a financial instrument in a recommended portfolio, Of the RoboAdvisor system.
The method according to claim 1,
Wherein the investment propensity analysis server comprises:
The method comprising the steps of: collecting at least one of health information and asset change information of a customer received from the external server through interworking with an external server, Robo advisor system based on analysis data.
The method according to claim 1,
Wherein the robot advisor system comprises:
The method comprising: receiving evaluation information on each financial instrument in the recommended portfolio from the customer terminal when a predetermined time elapses after providing the recommended portfolio, wherein, based on the received evaluation information, And an investment logic verification server for calculating an error rate between the investment propensity information of the customer and the investment propensity information for the customer and then changing the financial product in the recommended portfolio based on the error rate.
The financial product analysis server of the RoboAdvisor system receives information on a plurality of financial products provided by a securities company, a bank, and an insurance company through a financial company interworking platform, and receives manager reputation information for managing financial products based on the received information, Analyzing at least two of the maturity information and the investment scale information, generating tendency information for each of a plurality of financial instruments based on the analysis, and storing the tendency information in a financial product database,
The external information collection server of the robot advisor system collects big data analysis information related to the search keyword through interworking with at least one information providing server and stores at least two environmental factor information among the interest rate fluctuation and forecast information, Collecting,
Checking the reactivity of each of a plurality of financial products stored in the financial product database with respect to the collected search keyword related big data analysis information and environmental factor information in the financial product analysis server of the robot advisor system, Changing propensity information for each of a plurality of financial products stored in a financial product database;
The investment propensity analysis server of the robot advisor system is connected to the main domain of any one of the customer's risk management tendency, investment period, income status, income stability, health, consumption propensity, asset level, asset type and debt type Providing at least one analysis query information connected to a plurality of evaluation areas corresponding to each of the main areas according to a request of the client terminal and receiving answer information therefrom;
Wherein the investment tendency analysis server calculates a score for a plurality of evaluation regions connected to the provided analysis query information, calculates an evaluation score for each evaluation region using the score for each calculated evaluation region, Generating investment propensity information of a customer based on the score;
Searching the financial product database for a financial product having a similar tendency information within a predetermined range and the investment propensity information generated by the recommended goods matching server of the robot adviser system to generate a recommended portfolio using the retrieved financial proprietary information,
And providing the generated recommendation portfolio to the customer terminal in the recommendation product matching server. The method of claim 1,
delete The method according to claim 6,
The method of providing an investment portfolio includes:
Calculating a return on each of the financial products in the recommended portfolio when a predetermined time elapses after providing the recommended portfolio in the investment logic verification server of the robo advisor system;
Checking the responsiveness to the environmental factor information of the financial product and the big data analysis information related to the search keyword, which has recorded a return rate lower than the standard rate of return through comparison between the calculated return rate and the standard rate of return;
Determining an error portion of the investment logic by determining a degree of mismatch between the investment propensity analysis data of the customer and the propensity information of the financial product using the checked reactivity,
Further comprising the step of searching for a financial product that can complement the detected error portion in the financial product database and using the same to change the financial product in the recommended portfolio, How to provide investment portfolio using.
The method according to claim 6,
Wherein the step of generating the investment propensity information comprises:
Receiving at least one of health information and asset change information of a customer from an external server through interworking with an external server;
And changing the investment propensity information based on the received information. The method of claim 1, further comprising:
The method according to claim 6,
The method of providing an investment portfolio includes:
Receiving evaluation information on each financial instrument in the recommended portfolio from the customer terminal when a predetermined time elapses after providing the recommended portfolio in the investment logic verification server of the robo advisor system;
Calculating an error rate between the propensity information for each financial product and the propensity to invest for the customer based on the received evaluation information,
And changing the financial product in the recommended portfolio based on the error rate. The method of claim 1, further comprising:

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