JP6962839B2 - Information processing equipment, information processing methods, and programs - Google Patents

Description

The present invention relates to an information processing device, an information processing method, and a program.

Conventionally, a method of providing financial information via a network has been known (see Patent Document 1). This method accepts the access of those who wish to receive financial information, provides financial information to those who have accessed it, introduces financial institution-related information related to financial information at that time, and informs the financial institution. It is characterized by encouraging access by information recipients.

JP-A-2002-99730

Since the conventional method uniformly recommends financial institutions, it may not be possible to recommend financial institutions according to the user's intentions.

The present invention has been made in consideration of such circumstances, and an object of the present invention is to provide an information processing device, an information processing method, and a program capable of recommending a financial institution according to a user's intention. Make one.

One aspect of the present invention is to network a collection unit that collects user information, which is information about a user, and information that recommends one or more financial institutions to the user based on the user information collected by the collection unit. An information processing device including a recommendation unit provided to the user via the user.

According to one aspect of the present invention, a financial institution that meets the user's intention can be recommended.

It is a figure which shows an example of the configuration and use environment of the service server 100 using an information processing apparatus. It is a figure which shows an example of the content of the user information 162. It is a figure which shows an example of the contents of financial institution information 168. It is a figure which shows an example of the screen IM1 generated by the recommendation part 140 and displayed on the terminal apparatus 10. It is a flowchart which shows an example of the flow of processing executed by the recommendation unit 140 centering on a score calculation unit 146.

Hereinafter, the information processing apparatus, the information processing method, and the embodiment of the program of the present invention will be described with reference to the drawings. The information processing device is realized by one or more processors. The information processing device is a device that recommends a financial institution with which a user will make a transaction via a network based on user information collected by various methods. A financial institution is an entity that sells securities or rights of some value (stocks, bonds, investment trusts, FX, virtual currency), and corresponds to, for example, securities companies, banks, FX companies, virtual currency exchange companies, etc. .. As a method of recommending a financial institution via a network, a method of embedding as an image in content such as a web page, a method of embedding an advertisement image with a link to the site of the financial institution in content such as search results, a method of pushing Various methods such as a method of notifying are adopted. The information processing device may be a device that realizes a function by itself, or may be a virtual device included in a server that provides various services. In the following description, the information processing device will be described as being included in the service server that provides economic information.

FIG. 1 is a diagram showing an example of a configuration and a usage environment of a service server 100 using an information processing device. In the environment shown in the figure, one or more terminal devices 10, a financial institution server 20, a household account book service server 30, and a service server 100 can communicate with each other via a network NW. The network NW includes, for example, the Internet, a WAN (Wide Area Network), a LAN (Local Area Network), a cellular network, and the like.

The terminal device 10 is used by the user. The terminal device 10 is, for example, a personal computer, a mobile phone such as a smartphone, a tablet terminal, or the like. In the terminal device 10, a UA (User Agent) such as a browser or an application program is activated, and various contents acquired via the network NW are provided to the user.

The financial institution server 20 is a server device operated by a financial institution. The financial institution server 20 provides the terminal device 10 with contents for buying and selling securities and the like. Further, the financial institution server 20 may provide account information to the service server 100 in cooperation with the service server 100.

The household account book service server 30 provides the household account book service to the user. The household account book service calculates the user's balance based on the information input to the terminal device 10 or in cooperation with the terminal of a financial institution or POS (Point Of Sales system), and displays the visualized image on the terminal device 10. It is a service to be provided. In the household account book service, a bank account may be registered and the actual balance may be included in the visualized image.

The service server 100 provides the terminal device 10 with comprehensive information on economics and finance. The service server 100 is a web server that provides a web page to the terminal device 10 in response to a request from a browser, or an application server that provides content to the terminal device 10 in response to a request from an application program. The service server 100 includes, for example, a user management unit 110, an economic information providing unit 120, a user information collecting unit 130, and a recommendation unit 140. The recommendation unit 140 includes a financial instrument estimation unit 142, an intentionality estimation unit 144, and a score calculation unit 146. Some or all of these components are hardware such as LSI (Large Scale Integration), ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array), GPU (Graphics Processing Unit) It may be realized by (including circuits), or it may be realized by the cooperation of software and hardware. The program may be stored in advance in a storage device such as an HDD (Hard Disk Drive) or a flash memory, or is stored in a removable storage medium such as a DVD or a CD-ROM, and the storage medium is stored in the drive device. It may be installed by being attached. The information processing device includes at least a user information collecting unit 130 and a recommended unit 140.

Further, the service server 100 stores information such as user information 162, user position information 164, estimation result information 166, and financial institution information 168 in the storage unit 160. The storage unit 160 is realized by, for example, an HDD, a flash memory, a RAM (Random Access Memory), or the like. The storage unit 160 may be realized by hardware attached to the service server 100, or may be realized by an external device such as NAS (Network Attached Storage) that the service server 100 can access via the network NW.

The user management unit 110 registers the information of the user who logs in to the service server 100 as a part of the user information 162. FIG. 2 is a diagram showing an example of the contents of the user information 162. The user information 162 is, for example, information in which age, gender, occupation, and other information are associated with a user ID, which is user identification information. Of these, the user management unit 110 acquires, for example, age, gender, and occupation from the terminal device 10 at the time of user registration, and registers them as a part of user information 162.

The economic information providing unit 120 generates the content provided by the service server 100 and transmits it to the terminal device 10.

The user information collecting unit 130 collects information such as an address, a work address, an action history, a service usage status, and a financial institution in the user information 162 by various methods described below.

(1) The user information collecting unit 130 estimates and collects the user's address and work address based on the location information acquired from the terminal device 10. The location information is uploaded to the service server 100 or to another service server linked with the service server 100 by an application program or the like running on the terminal device 10 and accumulated as the user location information 164. Is. For example, the user information collecting unit 130 estimates that the position indicated by the location information that is intensively distributed at night is an address, and the position indicated by the location information that is intensively distributed during the daytime on weekdays is the work address ( (Including seconded address, etc.). The user information collecting unit 130 registers the estimated address and the work address in the user information 181.

(2) The user information collecting unit 130 collects the contents provided by the service server 100 and other browsing histories. In addition, the user information collecting unit 130 collects the purchase history of products and the like by the user from the shopping server and the auction server linked with the service server 100. Further, the user information collecting unit 130 may collect the browsing history of browsing the purchase screen of the product or the like in addition to the purchase history.

(3) The user information collecting unit 130 acquires the service usage status of the user from, for example, the result of a questionnaire conducted to the user, the information input to the terminal device 10 at the time of registration to the service server 100, and the like. The service usage status is, for example, information indicating whether or not points (privileges) that can be commonly used in a plurality of services can be used.

(4) The user information collecting unit 130 acquires the information (account information) of the user's financial institution from the transaction financial institution, for example, from the linked household account book service server 30 or from the website provided by the financial institution server 20.

The financial product estimation unit 142 of the recommendation unit 140 estimates the financial product that the user is likely to be interested in based on the user information 162. For example, the financial product estimation unit 142 estimates a financial product that the user is likely to be interested in based on the browsing history and search history of the content provided by the economic information providing unit 120. The financial instrument estimation unit 142 estimates that, for example, a user who frequently searches for the price of a stock is interested in the stock, and a user who frequently browses the advertisement of the investment trust is interested in the investment trust. presume. The estimation result by the financial instrument estimation unit 142 is registered as the estimation result information 166.

The orientation estimation unit 144 estimates which of the safety-oriented, risk-oriented, long-term-oriented, short-term-oriented, and the like, the user has, based on the user information 162. The intentionality estimation unit 144 uses, for example, the user's intentionality acquired as a questionnaire result in advance as teacher data, and performs machine learning based on the "action history" in the user information 162, and the trained model obtained as a result. Is used to estimate the user's orientation.

The score calculation unit 146 calculates individual scores for each of the above-mentioned multiple factors by comparing with financial institution information 168, and further calculates an integrated score that integrates the individual scores for each financial institution. Determine one or more financial institutions to recommend to users based on their integrated score.

FIG. 3 is a diagram showing an example of the contents of the financial institution information 168. The financial institution information 168 is, for example, information associated with each financial institution, such as a business form, a list of branches, affiliated services, financial institution cooperation, product types handled, and business scale. The "business form" is information indicating whether the user is specialized in the Internet or is engaged in counter business. The "affiliated service" is information indicating a service in which points are accumulated by conducting a transaction. "Financial institution cooperation" is information indicating a financial institution that can obtain benefits such as preferential interest rates by doing business with both parties.

For example, as shown in the equation (1), the score calculation unit 146 sums the values obtained by multiplying the individual score Score (i, k) for each factor by the coefficient αk to obtain the integrated score Score of the financial institution i ( i) Calculate the _TOTAL. k is an argument indicating a factor.
Score (i) _TOTAL = Σ _{k = 1} ⁿ {αk × Score (i, k)}… (1)

Hereinafter, each factor will be illustrated.
(Factor 1)
When the age of the user registered in the item of "age" in the user information 162 is high, the score calculation unit 146 recognizes from the "business form" in the financial institution information 168 of the financial institution i performing the counter business. The individual score Score (i, 1) is calculated high. For example, as shown in the equation (2), the score calculation unit 146 has a constant value (for example, zero) when the user's age is less than the reference age (for example, 50 years), and when the user's age is above the reference age. In the case of a financial institution specializing in the Internet, the individual score Score (i, i, 1) is calculated. The "value that gradually increases with age" is obtained by a calculation such as MAX {(age-reference age) / 50,1}.
Score (i, 1) = 0 (less than the standard age)
0 (Age over standard age, Internet only)
Increases according to age (aged above standard age, with window work)
… (2)

(Factor 2)
The score calculation unit 146 uses the user's address or work address (hereinafter, address) based on the item of "address" or "work address" in the user information 162 and the item of "branch office list" in the financial institution information 168. The individual score Score (i, 2) of the financial institution i having a branch close to (referred to as, etc.) is calculated high. "Near" means that the straight line distance obtained from the coordinates on the map is less than or equal to a predetermined distance, or that the time required for traveling in consideration of transportation is less than or equal to a predetermined time. In the following explanation, the former will be adopted. For example, as shown in the equation (3), the score calculation unit 146 is zero when the straight line distance to the branch closest to the address or the like exceeds a predetermined distance, and the straight line distance to the branch closest to the address or the like is equal to or less than the predetermined distance. If, the value that increases as the straight line distance becomes shorter is calculated as the individual score Score (i, 2). The "value that increases as the linear distance decreases" can be obtained by a calculation such as MAX {reference distance / linear distance, 1}. The reference distance is a distance shorter than a predetermined distance.
Score (i, 2) = 0 (exceeds a predetermined distance)
Increases as the distance decreases (less than the specified distance)
… (3)

(Factor 3)
The score calculation unit 146 compares the item of "service usage status" in the user information 162 with the item of "affiliated service" in the financial institution information 168, and both match (for example, the point used by the user is (It is a mechanism to accumulate), the individual score Score (i, 3) of the financial institution i is calculated high. The score calculation unit 146 calculates, for example, 1 when both match, and zero when they do not match, as an individual score Score (i, 3).

(Factor 4)
The score calculation unit 146 compares the item of "transaction financial institution" in the user information 162 with the item of "financial institution cooperation" in the financial institution information 168, and the financial institution i is the finance in which the user has an account. The individual score Score (i, 4) is calculated high when benefits such as preferential interest rates can be obtained by cooperating with an institution. The score calculation unit 146 calculates, for example, 1 when the above is applicable and zero when the above is not applicable as an individual score Score (i, 4).

(Factor 5)
The score calculation unit 146 compares the estimation result information 166 with the item of "handled products" in the financial institution information 168, and the financial institution i is estimated by the financial product estimation unit 142 and is likely to be of interest to the user. When dealing with financial products, the individual score Score (i, 5) of the financial institution i is calculated high. The score calculation unit 146 calculates, for example, 1 when dealing with a financial product that the user is likely to be interested in, and zero when not dealing with it, as an individual score Score (i, 5).

(Factor 6)
The score calculation unit 146 compares the estimation result information 166 with the items of "business scale" and "handled products" in the financial institution information 168. For example, if the user's orientation is safety-oriented, the financial institution i The larger the business scale, the higher the individual score Score (i, 6) of the financial institution i is calculated. If the user's orientation is risk-oriented, the individual score Score (i, 6) of the financial institution i is calculated higher as the financial institution i handles more financial products with large fluctuations. If the user's orientation is long-term, the higher the financial institution i handles long-term investment products such as government bonds, the higher the individual score Score (i, 6) of the financial institution i is calculated.

The factors illustrated above are merely examples, and some factors may be omitted or other factors may be added.

The score calculation unit 146 substitutes the individual score Score (i, k) calculated as illustrated above into the equation (1) to calculate _{the integrated score Score (i) TOTAL of the financial institution i.} Then, a predetermined number of financial institutions are selected as the recommended financial institutions in descending order of the integrated score Score (i) _TOTAL.

The recommendation unit 140 generates information (for example, a screen) that recommends the financial institution selected by the score calculation unit 146, and transmits the information (for example, a screen) to the terminal device 10 of the user. At this time, the recommendation unit 140 may include a factor having a higher individual score Score (i, k) than the other factors in the recommended information and transmit it to the user's terminal device 10. good. FIG. 4 is a diagram showing an example of the screen IM1 generated by the recommendation unit 140 and displayed on the terminal device 10. In the illustrated example, the user whose user ID is AAA is presumed to be risk-oriented, so that he / she handles stocks and FX, and because he / she uses U points, he / she accumulates U points. , ○ × Securities' integrated score Score (i) _TOTAL was the highest. Therefore, the screen IM1 includes the above points as reasons for recommendation. In addition, the uneven bank has a branch office close to the user's office, which has the effect of having the second highest _{integrated score Score (i) TOTAL.} This point is also included in the screen IM1.

FIG. 5 is a flowchart showing an example of the flow of processing executed by the recommendation unit 140 centering on the score calculation unit 146.

First, the score calculation unit 146 selects a target user (S100) and reads out the information of the target user from the user information 162 (S102).

Next, the score calculation unit 146 processes S104 and S106 for all financial institutions (i = 1, 2, ...), And processes S104 for all factors (k = 1, 2, ...). The score calculation unit 146 calculates the individual score Score (i, k) (S104). In addition, the score calculation unit 146 calculates the integrated Score (i) _TOTAL (S106).

Next, the score calculation unit 146 selects a predetermined number of financial institutions in descending order of _{integrated Score (i) TOTAL (S108).} For each of the selected financial institutions, the factors for which the individual score Score (i, k) was higher than the other factors are picked up (S110). Then, the recommendation unit 140 selects as the target user in S100, generates information recommended to the user, and transmits the information to the terminal device 10 of that user (S112).

According to the information processing apparatus of the embodiment described above, one or more financial institutions are provided to the user based on the user information collecting unit 130 that collects the user information 162 and the user information 162 collected by the user information collecting unit 130. By providing the recommendation unit 140 that provides the recommended information to the user via the network NW, it is possible to recommend the financial institution according to the intention of the user.

Although the embodiments for carrying out the present invention have been described above using the embodiments, the present invention is not limited to these embodiments, and various modifications and substitutions are made without departing from the gist of the present invention. Can be added.

100 Service server 110 User management unit 120 Economic information provision unit 130 User information collection unit 140 Recommendation unit 142 Financial product estimation unit 144 Orientation estimation unit 146 Score calculation unit 160 Storage unit 162 User information 164 User location information 166 Estimated result information 168 Finance Institutional information

Claims (12)

A collection unit that collects user information, which is information about users,
Based on the user information collected by the collection unit, the recommendation unit that provides the user with information recommending one or more financial institutions that mediate the investment made by the user to the user via the network.
With
The recommendation section preferentially recommends a financial institution of a predetermined business format as the age of the user included in the user information increases.
Information processing device. A collection unit that collects user information, which is information about users,
Based on the user information collected by the collection unit, the recommendation unit that provides the user with information recommending one or more financial institutions that mediate the investment made by the user to the user via the network.
With
The recommendation section preferentially recommends a financial institution having a branch office close to the user's address or work address included in the user information.
Information processing device. The recommendation unit estimates the financial product that the user is interested in based on the user information, and recommends the financial institution that handles the estimated financial product to the user.
The information processing device according to claim 1 or 2. The recommendation unit estimates the user's intentionality based on the user information, and recommends a financial institution that matches the estimated intentionality to the user.
The information processing device according to any one of claims 1 to 3. The user information includes information on services that are used by the user and can use points.
The recommendation section recommends the financial institution associated with the point to the user.
The information processing device according to any one of claims 1 to 4. The user information includes information on the financial institution with which the user is dealing.
The recommendation section recommends to the user a financial institution that can receive benefits by trading in parallel with the financial institution included in the user information.
The information processing device according to any one of claims 1 to 5. The recommendation unit calculates individual scores for each of the plurality of factors, and determines one or more financial institutions recommended for the user based on the integrated score that integrates the individual scores.
The information processing device according to any one of claims 1 to 6. The recommendation unit provides the user with information recommending one or more financial institutions to the user, along with a reason for recommending the user, via the network.
The information processing device according to any one of claims 1 to 7. The computer
Collect user information, which is information about the user,
Based on the collected user information, information that recommends one or more financial institutions that mediate the investment made by the user is provided to the user via a network.
When providing the recommended information, the financial institution of a predetermined business format is preferentially recommended according to the age of the user included in the user information.
Information processing method. On the computer
Collect user information, which is information about the user,
Based on the collected user information, the user is made to provide information recommending one or more financial institutions that mediate the investment made by the user via the network.
When providing the recommended information, the financial institution of a predetermined business format is preferentially recommended according to the age of the user included in the user information.
program. The computer
Collect user information, which is information about the user,
Based on the collected user information, information that recommends one or more financial institutions that mediate the investment made by the user is provided to the user via a network.
In providing the recommended information, preferentially recommend a financial institution having a branch office close to the user's address or work address included in the user information.
Information processing method. On the computer
Collect user information, which is information about the user,
Based on the collected user information, the user is made to provide information recommending one or more financial institutions that mediate the investment made by the user via the network.
When providing the recommended information, preferentially recommend a financial institution having a branch office close to the user's address or work address included in the user information.
program.

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