KR101802990B1 - Method and apparatus for social funding using analysis of big data - Google Patents
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Abstract
A method and apparatus for social funding using personal credit rating estimates based on Big Data analysis. The social funding method is a social funding method for providing an environment of a mutual assistance society in a social funding device accessible to a social network service (SNS) A step of receiving a credit rating request signal for the membership candidate, a step of evaluating the creditworthiness of the member candidate by analyzing the big data of the member candidates collectable in the SNS according to the credit rating request signal, And providing a result of the credit rating evaluation.
Description
BACKGROUND OF THE
Generally, a "group meeting" is a small-scale social fellowship and financial transaction gathering formed between believers who can trust for the purpose of making a certain amount of money, and various forms are possible depending on the interest or operation method. In addition to the fund, the group is not a financial transaction between the investor and the management company, but rather a mutual support type transaction between the individual and the individual, rather than a financial transaction between the investor and the management company. There is a difference in the point of being.
In other words, the group is a very private gathering, and is used as a means of finance and finance. It is usually composed of one person 's relay and several people' s members. The relay carries out the functions of the manager and the manager. This function is performed to send the collected money to one person every month. If you use this system, you can get your money easily in a short period of time, and those who get a later payment can get the added money. In other words, the person who receives the first payment will pay the added money, and the person with the late number can receive the last money with the interest of the late person as much as the interest of the latter. The reason why people do the above-mentioned meetings is because banks have difficulty in borrowing loans, interest rates are better than banks, and deposits are quicker than savings.
However, the existing system has a relatively high risk of accident due to the reliability problem of the relay, the reliability of the trustee, and the lack of legal management means. The problem of trust in the relay is the risk that the relay that manages the money is useful or embezzled in the other place. If the trustee of the trustee gets the money before the interest payment, And the risk of increasing the burden of relaying money on behalf of the manager. In addition, the lack of legal management means that there is no way to guarantee damages in the institutional rights other than 'believe' because it is based on human friendship.
SUMMARY OF THE INVENTION It is an object of the present invention to provide a system and method for providing personal credit rating based on big data analysis while implementing the conventional system as social funding in a social network service, Method and apparatus.
Another object of the present invention is to provide a method and apparatus for social funding using a big data analysis having high reliability and stability by providing a separate common account or escrow for managing deposit and withdrawal of funds in social funding.
Another object of the present invention is to provide a social funding method and apparatus using big data analysis that can monitor the health of a mutual support group for social funding through big data analysis and detect the risk of the group in advance.
In order to achieve the above object, in one aspect of the present invention, there is provided a social funding device that can access a social network service (SNS), and a social funding device that provides an environment of a mutual assistance society (MAS) Receiving a credit rating request signal for a member candidate of the SNS from a leader terminal or a member terminal of a mutual support group; Evaluating the creditworthiness of the member candidates by analyzing the big data of the member candidates collectable in the SNS according to the credit rating request signal, the big data including unstructured data; And providing a credit rating result of the member candidate to the leader terminal or the member terminal, using the big data analysis.
Here, the above-described social funding method may further include a step of, prior to the step of receiving the credit rating request signal, instructing the reader and the one or more members to make a pre- (money for MAS), and the leader or one or more members who receive the money collected during the above-mentioned period and receive the grant within the set period, And providing the environment of a mutual support group that invests money in addition to the money.
Here, the above-mentioned social funding method may further include a step of establishing a common account for the mutual support meeting at the request of the leader terminal after the step of establishing the mutual support group and before the step of investing the mutual aid money .
Here, the amount of money may further include a reserve amount of a predetermined amount or ratio by the leader or by the leader and the one or more members, and the amount of money may include collecting the amount of money minus the reserve amount.
According to another aspect of the present invention, there is provided a social funding device which is accessible to a social network service (SNS) and provides an environment of a mutual assistance society (MAS) A network interface for receiving a credit rating request signal for a member candidate of the SNS from a leader terminal or a member terminal of a mutual support group; A credit evaluation unit for evaluating the creditworthiness of the member candidates by analyzing the big data of the member candidates collectable from the SNS according to the credit rating request signal; the big data includes unstructured data; And a social funding environment providing unit for providing the leader terminal or the member terminal with a credit rating result on the member candidates.
Here, the social funding environment providing unit may include a generating unit for establishing a mutual support meeting in cooperation with the social network service according to an opening request signal for mutual support meeting from the leader terminal; The leader and one or more members invest money for MAS every predetermined period within a predetermined period of time according to a predetermined rule for a mutual support group, and when a reader or one member or more collects money for each cycle An operating unit that receives a grant and provides an environment for a mutual support group in which the reader or the member who receives the grant within the set period invests the money in addition to the predetermined interest for each remaining period of the set period; A management unit for storing and managing information on leaders, information on members, information on mutual support groups, and information on credit rating results; A message processing unit for transmitting an invitation message to member candidate terminals of one or more member candidates upon receipt of a message transmission request signal for inviting at least one member candidate to a mutual support meeting from a leader terminal or a member terminal; And receives a credit rating request signal from a reader terminal or a member terminal for a member or leader of a mutual support group and analyzes the big data of the member or leader collectable in the SNS according to the credit rating request signal to evaluate the creditworthiness of the member or leader And a monitoring unit for providing the leader terminal or the member terminal with a credit rating result of the member or the leader.
When the social funding method and apparatus using the big data analysis according to the present invention as described above, the conventional system meeting (mutual support meeting) is implemented as social funding in the social network service, and the personal credit rating based on the big data analysis is provided The problems of the conventional system can be effectively solved.
Also, there is an advantage that a social funding method and apparatus using a big data analysis having high reliability and stability can be provided by providing a separate common account or escrow for managing deposit and withdrawal of funds in social funding.
Also, there is an advantage that a social funding method and apparatus using big data analysis can be provided, which can monitor the health of the mutual support group for social funding through big data analysis and detect the risk of the meeting in advance.
FIG. 1 is a general configuration diagram of a social funding system capable of implementing a social funding method including a social funding device using a big data analysis according to an embodiment of the present invention.
2 is a block diagram of an embodiment of a configuration that can be employed in the social funding device of FIG.
3 is a block diagram of one embodiment of a module configuration that can be mounted in the memory system of FIG.
Figure 4 is a detailed block diagram of some module configurations of the memory system of Figure 3;
5 is a flow chart for explaining the operation principle of the generator of FIG.
FIG. 6 is a flowchart for explaining a specific operating principle for the operating unit of FIG. 4; FIG.
FIG. 7 is a flowchart for explaining the main operation principle of the social funding apparatus of FIG. 2;
FIG. 8 is a flowchart of an embodiment of a member (or member) registration process in the social funding device of FIG. 2;
FIG. 9 is a flowchart of an embodiment of a deposit payment process in the social funding apparatus of FIG.
FIG. 10 is a flowchart illustrating an example of a payment process in the social funding apparatus of FIG.
11 is a flowchart of an embodiment of a mutual support group (social system) update process in the social funding device of FIG.
Figure 12 is a detailed block diagram of another module configuration of the memory system of Figure 2;
13 is a flowchart for explaining the operation principle of the collecting unit of FIG.
Fig. 14 is an exemplary diagram of structured data classified by the classification unit of Fig. 12; Fig.
15 is a flowchart for explaining the operation principle of the classification unit of FIG.
While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail. It is to be understood, however, that the invention is not to be limited to the specific embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.
The terms first, second, A, B, etc. may be used to describe various elements, but the elements should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component. And / or < / RTI > includes any combination of a plurality of related listed items or any of a plurality of related listed items.
It is to be understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, . On the other hand, when an element is referred to as being "directly connected" or "directly connected" to another element, it should be understood that there are no other elements in between.
The terminology used in this application is used only to describe a specific embodiment and is not intended to limit the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. In the present application, the terms "comprises" or "having" and the like are used to specify that there is a feature, a number, a step, an operation, an element, a component or a combination thereof described in the specification, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or combinations thereof.
Unless otherwise defined, all terms used herein, including technical or scientific terms, may have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries are to be interpreted as being consistent with the meanings in the context of the relevant art and are not to be construed as ideal or overly formal meanings unless explicitly defined in the present application.
Throughout the specification, the network can be a wireless Internet, such as, for example, wireless fidelity (WiFi), wireless broadband internet (WiBro) or world interoperability for microwave access (WiMax) a 3G mobile communication network such as WCDMA (Wideband Code Division Multiple Access) or CDMA2000, a high speed downlink packet access (HSDPA), or a high speed uplink packet access (HSUPA) , A 4G mobile communication network such as an LTE (Long Term Evolution) network or an LTE-Advanced network, and a 5G mobile communication network.
Also, throughout the specification, a terminal may be referred to as a mobile station, a mobile terminal, a subscriber station, a portable subscriber station, a user equipment, an access terminal a mobile terminal, a mobile terminal, a subscriber station, a mobile subscriber station, a user equipment, an access terminal, a wireless telephone, a wireless telephone, a wireless telephone, a mobile phone, a smart phone, , A mobile phone, a smart phone, and the like. In addition, the terminal may take the form of a desktop computer, a laptop computer, a tablet PC, etc., which can communicate according to an implementation.
Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In order to facilitate the understanding of the present invention, the same reference numerals are used for the same constituent elements in the drawings and redundant explanations for the same constituent elements are omitted. In the following description of the present invention, a detailed description of known functions and configurations incorporated herein will be omitted when it may make the subject matter of the present invention rather unclear.
FIG. 1 is a general configuration diagram of a social funding system capable of implementing a social funding method including a social funding device using a big data analysis according to an embodiment of the present invention.
Referring to FIG. 1, a social funding system according to an embodiment of the present invention includes a plurality of
The
The
The
The
In addition, the
The
Further, the
The above-described
In this embodiment, big data is used to assess the creditworthiness of at least one of the reader, the member and the membership candidate in a social gathering or mutual support meeting for social funding, Data acquired through the SNS account of another user who is connected to the account in a friend relationship, and refers to data including unstructured data. Such big data can not be stored in one server at a scale or capacity beyond a certain size, or it is not structured too much so that it does not fit into a database in a column and a row, or is continuously introduced into a static data warehouse data warehouse, but is not limited to this. Big data can be referred to as massive data, including less structured data.
In other words, Big Data contains unstructured data that has a dataset size that exceeds the data analysis capability (qualitative and / or quantitative capabilities) of existing database management tools and is not stored in a fixed field. Big data can have data sizes ranging from Terabyte to Petabyte and can have a variety of mixed data such as regular, irregular, text, and multimedia data. Further, the big data can be analyzed as streaming data so that it can be decided for a predetermined time (for example, 1 second or less), has an inherently uncertain data type, and is used to obtain high reliability accuracy through management of predictability . In addition to basic information such as images, images and texts collected in SNS, big data is used for trading transactions, log data, events, email, social media, sensors, external data, RFID scan and POS data, free format text, And the like.
In the present embodiment, social funding can be used for social networking such as Facebook (www.facebook.com or https://ko-facebook.com) or bands (www.band.us or http://band.naver.com) It can refer to a platform that creates and manages an on-line network of mutual support groups (mutual support groups) for social network service (SNS) based on acquaintances with common interests. Thus, the term "social funding method and apparatus" herein may be replaced by "cloud funding method and apparatus ".
The relay of the meeting is the leader of the meeting, and through the app, the purpose of the social network, the amount of money, the staff information and the ordering method can be determined, and the staff can be recruited on the social network service, and the social funding can be operated and managed. And they can send or transfer money directly to the common account via the app on a fixed date every month. In addition, the relay can set the reserve amount of the accumulated money collected in the common account to be automatically deposited into the account of the corresponding member when the order of the specific member is approaching.
The common account described above may include an escrow account. In this case, since the deposit and withdrawal is managed through an independent escrow account rather than a specific relay, it is possible to reliably remove the existing relay list.
2 is a block diagram of an embodiment of a configuration that can be employed in the social funding device of FIG.
2, the
The
The
The
The
The
The
The
In addition, the
3 is a block diagram of one embodiment of a module configuration that can be mounted in the memory system of FIG.
Referring to FIG. 3, the
In the present embodiment, the case where the social funding
Figure 4 is a detailed block diagram of some module configurations of the memory system of Figure 3;
4, the social funding
The
The
In addition, when the
In addition, the
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The
In addition, the
The above-mentioned
The
Also, the
5 is a flow chart for explaining the operation principle of the generator of FIG. 6 is a flowchart for explaining the specific operation principle of the operation unit of FIG.
The social funding method according to the present embodiment allows a user of a relay (or reader) connected via a network to generate a social funding in the form of a social network in a social funding device that provides a social funding service in connection with a social network service The process is illustrated.
Referring to FIG. 5, the relay sets a social network name through a user interface on the user terminal provided in the social funding device (S50). The user interface may be a user interface in a screen of a computing device provided by an online social network service or a user interface running in an app of a user terminal in cooperation with a social network service. The computing device is a device connected to a network and capable of displaying a screen of a social network service. The computing device is connected to a network and has a display device. The user inputs the user input, which is set in a user interface displayed on the screen, (Hereinafter, simply referred to as an SNS server), and the like.
Next, the relay sets a social purpose (S51). In this step, the setting information including the social network purpose is transmitted from the computing device or the user terminal to the social funding device or the SNS server. In association with the SNS server, the social funding device transmits the current social You can update the settings for funding (social system). The social system can be subdivided according to the purpose of use such as travel, marriage, concert.
Next, the relay sets the amount of money (S52). In this step, the amount of money may differ depending on the order in which the money is spent. Here, the social funding device or the relay can set the upper limit of the amount of money for social center-based social network activation. For example, a social funding device or a relay can set the maximum amount of monthly money received by an individual to 1 million won. The upper limit can be set based on the principal excluding interest.
Next, the relay sets the number of social network members (S53). The relay can set the number of staff members considering the upper limit of the allowance. This is because, for example, when the relay is set up for 20 members, the monthly deposit limit per member can be limited to 50,000 won.
Next, the relay sets the reserve (S54). The reserve can be collected in such a way as to be included in the interest of the manager who has received the first payment. If the relay sets the reserve to a certain rate, the interest of the manager can be determined accordingly. For example, the social funding device may force, but not limited to, more than 5% of the monthly money to be credited to a separate account of the relay or group. The reserve setting step may be omitted in the social funding method depending on implementation.
Next, the relay sets the monthly deposit date (S55). Then, the relay sets the monthly payment date (S56). The payment date may be set at least 5 days after the deposit date in order to resolve the problem such as the non-payment. On the other hand, the deposit date or the payment date is not limited to a period of a month, and may be set to at least any one period selected from 10 days, 15 days, 45 days, two months, or other periods. In addition, the period can be set to a predetermined number of times, and in this case, a period obtained by multiplying the period by a certain number of times can be set period of the corresponding network system.
Next, the relay sets a method of determining the disbursement order (S57). The order determination method can be one or more of all available sequence determination methods such as self-selection order, lot drawing order, and the like. When the audio system setting is completed (S58), the relay (user) can recruit the clerk.
If one or more members are recruited, the social funding apparatus can issue a family-based common account by a family name in accordance with the request of the relay, the clerk, or the relay and the clerk according to the implementation as shown in FIG. 6 (S59) .
Common accounts can include escrow accounts. In this case, since the deposit and withdrawal is managed through an independent escrow account which is not a specific relay, it is possible to reliably remove the relay list. Escrow accounts can be managed by a social funding device or managed through a specific service of a separate financial institution.
FIG. 7 is a flowchart for explaining the main operation principle of the social funding apparatus of FIG. 2;
The method of social funding according to the present embodiment illustrates an interworking process for joining a member of a staff member in a social funding system between a social funding apparatus and a user terminal of a staff member connected to the social funding apparatus through a network.
Referring to FIG. 7, a reader (relay) is connected to one or more members for social funding (social network, mutual support group, etc.) established through a user interface on the
Next, the
The
Next, the
Next, the
Next, the leader provides the member candidate information for inviting the new user (member 2) to the social funding through the
In the above-described case, the
The
The
Next, the
The
Next, the user of the
In the present embodiment, the member candidate who has been requested to participate in social funding can also perform credit evaluation using real-time inquiry by using big data analysis for members who are already registered in social funding if necessary. This can be used for the purpose of analyzing the intimacy between the person and the existing staff members, thereby enhancing the reliability and stability of the required social funding (group meeting). In addition, if it is mandatory to obtain the consent of all the other registrants for the selected candidate, it is also advantageous to give responsibility to the manager and to prevent future complaints in advance.
When the acceptance message for the social funding invitation is received from the
On the other hand, in the above-described embodiment, the
In addition, a registration officer who has the authority to select a candidate may be set to continue to select a candidate for the position until the recruitment of the member has been completed, unless he or she gives up. The right to select candidates can be transferred in the order of social funding (system or social) registration.
FIG. 8 is a flowchart of an embodiment of a member (or member) registration process in the social funding device of FIG. 2;
Referring to FIG. 8, a device (social funding device) for performing the social funding method according to the present embodiment can transmit and receive signals and data to and from a user terminal of a staff member for registering a staff member. That is, if the information of the social funding (social system etc.) is confirmed in the user terminal of the staff member and the participation request or the social funding invitation is accepted (S81), the social funding apparatus transmits the staff information (S82). The essential items include name, date of birth, and mobile phone number, and at least one member information selected from a resident number (or a personal identifier), an address, a bank account information, and the like can be optionally included in the essentials according to the type of social funding.
Next, the social funding device asks whether the automatic transfer setting is selectively performed (S83). If YES, the automatic fund transfer registration is performed (S84), and then the routine proceeds to a step S85 of selecting the order setting method. (S85) of selecting a method. In the present embodiment, the self selection method and the lot drawing method are exemplified, but the present invention is not limited thereto.
In the step S85 of selecting the order setting method, when the member selects "self selection ", the social funding device provides a user interface for setting the order number to the user terminal of the member, (S86). The order number setting can select one of the order numbers other than the order numbers previously set by the registrants registered in the order of registration, but the present invention is not limited thereto. For example, in another implementation, all members of the team set an arbitrary sequence number out of the total sequence number, and only the members of the duplicated sequence are selected from among the sequence numbers that have not yet been set. If all sequence numbers are not determined despite the predetermined number of iterations, And performing the lot drawing only by the remaining members.
On the other hand, if the staff member selects "lot drawing" in the step S85 of selecting the order number setting method, the social funding apparatus can use a program such as a lot drawing program or a similar ladder riding program or a twisted- So that the sequence numbers can be automatically set. At this time, the social funding device can set the order by performing lot drawing simultaneously while all members of the social funder are in the lot drawing program. However, the present invention is not limited to this, and a predetermined setting such as a registration order, a date of birth order, The sequence number can be set automatically at the same time or sequentially. That is, the order setting process of the reader (relay) can be omitted.
When the sequence number setting is completed through the self selection or the lot drawing, the social funding device completes the staff member registration (S87). The completion of the member registration can correspond to storing the member information required for the social funding in the corresponding field and transmitting the start message of the social funding to both the relay member and the member. The starting message of social funding may include information such as the name of the social fund, the type or purpose of the social fund, the name of the relay and the member, the date of payment, the date of payment, the amount of the monthly deposit, and the monthly interest.
FIG. 9 is a flowchart of an embodiment of a deposit payment process in the social funding apparatus of FIG.
Referring to FIG. 9, in step S91, the social funding method according to the present embodiment can inquire whether or not the automatic transfer is performed to the manager through the user interface on the screen of the user terminal or the social funding device of each staff member. If the inquiry result is YES, the social funding device confirms whether or not the payment is made in a preset account or a common account (S92). In the deposit confirmation step S92, if the social funding device is a small deposit of a predetermined amount or less, it can be implemented to use a simple and simple remittance function such as a cacao pay.
If the result of the inquiry is NO in the step S91, the social funding device can judge whether the money is pre-deposited (S93). As a result of the determination, if the advance payment is made, the social funding device notifies the completion of the payment (S95) and the present process can be terminated. On the other hand, if it is determined in step S93 that the payment has not been made in advance, the payment request message may be transmitted to the user terminal of the corresponding member (S94), and the process may proceed to the deposit confirmation step (S92). When the deposit is confirmed, the social funding device notifies the corresponding member of the completion of the deposit (S95) and ends the process.
If the deposit confirmation is not made in the deposit confirmation step S92, it is determined whether the deposit date has passed or the payment date arrives (S96). If the payment date arrives as a result of the determination, the user terminal of the dispatcher can be notified of the default (S97). On the other hand, if it is determined in step S96 that the payment date does not reach a predetermined date or less, the process returns to step S94 to repeat the subsequent steps.
Then, if there is no pre-set response of the staff member after the notification of default, the social funding device will send the staff member to a social funding meeting (meeting, social or mutual support meeting ) (S98). In this case, the social funding device (or the management section of the apparatus) may perform the obligatory default recording process for the forced withdrawal member (S99) and store the recording process in the memory system or the database.
FIG. 10 is a flowchart illustrating an example of a payment process in the social funding apparatus of FIG.
The social funding apparatus according to the present embodiment uses a combination of a method of determining the order of payment in advance by a self-selection or a lot drawing, and a method of determining a person to be paid in this period through a lot drawing at every cycle Can be implemented.
Referring to FIG. 10, when the payment date arrives, the social funding device determines whether the person to receive the money is determined and decides whether to perform lot drawing or the like (S101). If the person to be paid is determined, the step of selecting the payout target (S102) is omitted, and if the person to receive the payout is not determined, the lottery is performed to select the payout target (S102). The lottery is carried out for the remaining members except for those who have been paid in advance.
Next, the social funding device notifies the fund payment object to the social funding (social networking, group meeting or mutual support group) (S103). The notice can be posted in the bulletin board of the leader account in the SNS or in the chat window or message window of the social funding space in the form of a notice.
Next, at step S104, the social funding device deposits the money in the account of the member who is to be paid in the common account or the predetermined deposit account according to the request of the leader or the special member. Then, the social funding apparatus can notify all the members of the dispatcher of the completion of the payment (S105).
11 is a flowchart of an embodiment of a mutual support group (social system) update process in the social funding device of FIG.
The social funding apparatus according to the present embodiment can perform a process for updating the social funding (e.g., social system) after a predetermined period of time has elapsed. In other words, the novel funding device provides a social-based renewal environment so that the relay can collect the opinion of the staff members and decide whether or not to maintain a social network.
Referring to FIG. 11, first, the social funding device determines whether or not to maintain a social network according to the opinion of the relay or the staff member (S111). If it is determined that the social system is maintained, the social funding device can provide the user with a user interface for resetting the social system for resetting the amount of money, the number of employees, the reserve money, the deposit date, the current job, In addition, the lottery interface can be provided in the social funding space in the SNS in which all the members participate (S113).
If the lot drawing is not carried out in the step S113, the social funding device recognizes the self-selection or the automatic order determination and automatically determines the order of dispensing the money (S114). In the case of self-selection, the order of disbursement may be set to take equity into account by assigning priority rights in the reverse order of the last disbursement order.
If the lot number or the automatic disbursement order is determined, the social funding apparatus can determine whether the dispenser number is satisfied through the order (S115). The social funding device may terminate the process if the number of staff members is satisfied and guide the user to create a new family system after finishing the process after proceeding to the staff member recruitment step S116 if the staff number is not satisfied.
On the other hand, if it is determined in step S111 that the social system is not maintained, the social funding device proceeds to the social network dissolving step S117 and performs the process necessary for the social network dissolution.
Figure 12 is a detailed block diagram of another module configuration of the memory system of Figure 2; 13 is a flowchart for explaining the operation principle of the collecting unit of FIG. 14 is a flowchart for explaining the operation principle of the classification unit of FIG. 15 is an exemplary diagram of structured data classified by the classification unit of FIG. 14. FIG.
12, the
The collecting
The big data collected by the collecting
14 (a), the collecting
The classifying
The classifying
15, the
According to the
The
For example, as shown in FIG. 14 (c), among the information analyzed in the Big Data, the basic information includes fields classified into occupation, salary, marital status, home, automobile, address, age, sex, hobby, , And the issue information may be stored in a table 83b including fields classified into periods, issue-specific trends (fraud, credit card fraud, past records, etc.) And the re-identification information may be stored in a table 83c including fields classified by name, resident registration number, card information, etc., and the financial information includes a field classified by card information, bank account, insurance information, And stored in the table 83d.
Also, the analyzing
In the case of the comment analysis, the
In the case of frequency analysis, the
The above-described comment analysis and frequency analysis can be performed mainly through text analysis by the text analysis unit of the
In addition, in the case of the interest analysis, the
In the case of food analysis, the analyzing
The above-described interest analysis and food analysis can be performed mainly through text analysis by the text analysis unit of the
In addition to the above-described embodiments, the
The
14 (d), the
In the present embodiment, the credit contrast value may be an average of a whole credit period or a predetermined period (for example, three months) or a difference between the immediately preceding credit rating and the corresponding credit value. For example, if the value of the creditworthiness is -10, it indicates that the creditworthiness has decreased by the
Table 1 below is a table showing an example of data definition and arithmetic information of the analysis model for evaluating the creditworthiness of the
Table 2 is an example of the weights of classes in Table 1.
As shown in Tables 1 and 2, in the present embodiment, the evaluating
In the present embodiment, a weight of 30% is set in the structured data of the big data acquired in the SNS account, but the present invention is not limited to this. The weight set in the structured data among the database classes of the analysis model, It may be set to more than 30% and not more than 90% or 100% depending on the accumulation. According to this configuration, the creditworthiness evaluation according to the present embodiment can reliably evaluate the creditworthiness of the leader, the member, or the member candidate using only the big data analysis acquired from the SNS.
In addition, in the present embodiment, the weight does not assign weight to the identification information for personal information protection. However, when the personal information protection is executed, a class for protection of personal information may be added and a predetermined weight may be added to the class .
Table 3 shows an example in which the credit evaluation result of the social funding apparatus according to the present embodiment is converted into a predetermined conversion score.
As shown in Table 3, the credit evaluation result using the Big Data analysis can be expressed as the conversion score of the credit rating grade that can be used in the social funding. At this time, the ratio (%) of the reflected big data can be displayed in the credit rating result. Also, according to the implementation, the social funding device may be configured to preset the ratio of the big data to be reflected in the credit evaluation, to collect big data in the SNS or to request specific data to the user until the set data is filled.
In the present embodiment, the first rank (A) represents a case where 90 points are obtained as a result of analyzing the user-related data including the 90% or more big data and the personal credit rating, and the second rank (B) (C) obtained 70 points of personal credit score by analyzing user-related data including 70% or more of big data. , And grade 4 (D) indicates a case where the personal credit score of less than 70 points is obtained by analyzing the user-related data including the big data of less than 70%.
In addition, depending on the implementation, each grade and the ratio of big data inclusions can be adjusted according to the characteristics of the social funding service. For example, the evaluation data including less than 70% of the big data is analyzed to find that the personal credit score between 70 and 80 points is classified as 3-3 (C-3) and the personal credit score is between 80 and 90 points as 2 (A-3) in the case of the personal credit score of 90 or more, or in the case of including the big data of 70% or more and less than 80% in the similar case (C-2), 2 (C-2), and 2 (C-2) according to the personal credit score of the analysis result, (B-2), 1-2 (A-2), 3-1 (C-1), 2-1 (B-1) Can be used separately.
Also, the social funding apparatus according to the present embodiment can use the credit score obtained by converting the credit score using the big data analysis into a predetermined personal credit score. Table 4 below shows the converted personal credit rating.
According to the embodiment described above, it is possible to open social funding anytime and anywhere by utilizing an application (application, App.) For social network service, and to perform efficient management, operation and deposit / withdrawal management of social funding. Such an app may be provided by, but not limited to, a service provider providing a social network service. Of course, this can be provided by the device providing the social funding service.
According to the social funding apparatus of the above-described embodiment, it is possible to organize social gathering and personal funds conveniently and conveniently on-line, mainly by acquaintances with the same interests in the social network service.
In addition, a new shared economic financial social network can be created. For example, social funding can be established in the form of a microcentre-centered gathering. For example, a banker or a staff member can easily limit the scope of social funding to a level that can be overcome even if the social funding is broken by setting the upper limit of the money. In this case, the relay and staff members can greatly reduce or eliminate the burden of participation in social funding.
In addition, real-time big data analysis enables effective risk management. In other words, it is possible for the relay or staff members to decide whether or not to participate in social funding through the results of big data analysis for each member of the staff. In this case, there is an advantage that social funding can be activated by improving the reliability of the social funding and giving responsibility.
In addition, when a method of earning a portion of the collected money is operated, it is possible to reduce the damage at the time of an accident, and there is an advantage that it can be utilized for social donation at the time of an accident. In this case, it is possible to provide opportunities for the staff members to participate in donation culture society.
In addition, by excluding interest-earning functions in order to comply with lending or similar credit-related laws, it is possible to effectively maintain the characteristics of the committee and to prevent the linkage of lending.
In addition, there is an advantage in activating the social funding group culture that supports mutual funds depending on the difference in the time required for the paying, centering on the 20-30 users including the preparation for the employment such as the depression difficult to prepare. In addition, there is an advantage in that it is possible to easily set up sanctions (limitation of service use, penalty, etc.) through restriction of participation in social funding, permanent withdrawal, and record sharing on social network services to a member providing a cause of breaking social funding.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the present invention as defined by the following claims It can be understood that
1, 2, 3, 4: user terminal
9: Social network service (SNS) provision device
10: Social Funding Devices
11: Processor
12: Memory system
12a: Social Funding Environment Offering
12b: Credit Rating Department
13: Network interface
Claims (20)
Receiving a credit rating request signal for a member candidate of the SNS from a leader terminal or a member terminal of the mutual support group;
Analyzing the big data of the member candidates collectable in the SNS according to the credit rating request signal and evaluating the creditworthiness of the member candidate, the big data including unstructured data; And
And providing the leader terminal or the member terminal with a credit rating result for the member candidate,
Further comprising collecting the big data, classifying the big data, and analyzing the big data,
Wherein the classifying step generates data in the form of a database by storing data corresponding to a predetermined item among the big data collected for the membership candidate in the SNS in a correspondence item of a predetermined class,
The analyzing step may include analyzing the structured data after the categorizing step to generate analyzed information as a table having a predetermined column or field name, wherein the table stores basic information of the member candidate A second table for storing issue information, a third table for storing re-identification information, and a fourth table for storing financial information, wherein the issue information includes at least one of fraud, credit card fraud, Information about any one of them,
Wherein the evaluating step comprises: generating a tree structure of data based on user-related data including an analysis result of the structured data after the analyzing step and before evaluating the creditworthiness of the member candidates, 4 < / RTI > table,
The step of evaluating the creditworthiness includes the steps of: setting a ratio of the big data to be reflected in the credit rating evaluation in advance; requesting specific data from the reader terminal or the member terminal to fill the set ratio; or continuously collecting big data from the SNS Social Funding Method Using Data Analysis.
Receiving an open request signal for the mutual support meeting from the leader terminal and opening the mutual support meeting in connection with the social network service according to the open request signal before receiving the credit rating request; Further comprising the steps of: a.
Receiving a message transmission request signal for inviting at least one member candidate for the mutual support meeting from the reader terminal or the member terminal after the step of providing a credit rating result for the member candidate, And transmitting the invitation message to the candidate candidate terminals of the one or more member candidates according to the method.
Wherein the step of transmitting the invitation message includes performing the message through a messenger or a chat window provided by the SNS.
Wherein the transmitting of the invitation message comprises: when the one or more member candidates are sequentially registered in the mutual support group and the first member registered with the leader of the leader terminal agrees to register the next member candidate, And sending the invitation message to the member candidate terminals sequentially so as to be registered as a member of the mutual support group.
At least one member of the reader terminal of the leader terminal or one or more members of the one or more member terminals receives the invitation message from the member candidate terminal who desires to register as a member in the mutual support group after the invitation message is transmitted And evaluating the reliability of the reader or the member by analyzing the reader or member-related big data collectable in the SNS according to the credit rating request, and evaluating the reliability of the reader or the member And transmitting the membership information to the member candidate terminal.
After the step of establishing the mutual support group, the reader of the leader terminal and the one or more members of the leader terminal make a money for MAS at predetermined intervals within a preset period according to a predetermined rule in the environment of the mutual support group Wherein the leader or one or more members receive the fund collected in each period by the leader or the member who receives the fund within the set period, The method further comprising the step of investing in the fund.
Further comprising the step of establishing a common account for the mutual support meeting at the request of the leader terminal after the step of establishing the mutual support group and before the step of investing the mutual fund,
Wherein the fund further comprises a reserve amount or ratio predetermined by the leader or by the leader and the one or more members, and the grant includes collecting a sum of money minus the reserve, Funding method.
After establishing the mutual support meeting,
Receiving a credit rating request signal from the reader terminal or the member terminal for a member or leader of the mutual support group;
Analyzing the big data of the member or leader collectable in the SNS according to the credit rating request signal to evaluate creditworthiness of the member or reader; And
Further comprising providing the leader terminal or the member terminal with a credit rating result of the member or leader.
Wherein the providing of the credit rating result of the member or leader comprises providing a monitoring message to the member terminal or the leader terminal, the monitoring message including a risk score for the member, the reader or the mutual support group. Social Funding Method Using.
Wherein the step of analyzing the big data comprises:
Analyzing atypical text data, atypical image, and image data of the big data, or counting the frequency of exposure of a user's interest object, and assigning a score to the social funding.
The step of classifying the big data comprises:
The first user-related data including the information about the account of the leader, the member, or the membership candidate, or the first user-related data including the personal information, the housing, the job, Storing second user-related data including at least one item selected from an insurance, an insurance, a social and a vehicle in a corresponding field of a database of a predetermined format to generate the structured data A method of social funding using Big Data analysis.
A network interface for receiving a credit rating request signal for a member candidate of the SNS from a leader terminal or a member terminal of the mutual support group;
A credit evaluation unit for analyzing the big data of the member candidates collectable in the SNS according to the credit rating request signal to evaluate creditworthiness of the member candidates, the big data including atypical data; And
And a social funding environment provision unit for providing the leader terminal or the member terminal with a credit rating result of the member candidate,
A collecting unit for collecting the big data, a classifying unit for classifying the big data, and an analyzing unit for analyzing the big data,
Wherein the classification unit generates structured data in a database form by storing data corresponding to a predetermined item among the big data collected for the member candidates in the SNS in a corresponding item of a predetermined class,
Wherein the analyzing unit analyzes the structured data generated by the classifying unit and generates analyzed information as a table having a predetermined column or field name, wherein the table includes a first table storing basic information of the member candidates , A second table for storing issue information, a third table for storing re-identification information, and a fourth table for storing financial information, wherein the issue information includes at least one of fraud, credit card fraud, Information,
Wherein the evaluation unit generates a tree structure of data based on user-related data including an analysis result of the structured data after analysis by the analysis unit and before evaluating the creditworthiness of the member candidates, The row data is strengthened in the membership data of the membership candidate,
Wherein the collecting unit is configured to set a ratio of the big data to be reflected in the credit evaluation, to request specific data from the reader terminal or the member terminal to fill the set ratio, or to continuously collect the big data from the SNS, Social Funding Devices.
A memory system including a first module corresponding to the credit evaluation unit and a second module corresponding to the social funding environment provisioning; And
A processor coupled to the memory system and the network interface,
Wherein the processor provides an environment of credit rating and social funding by the first module and the second module.
The social funding environment provision unit,
A generating unit for establishing the mutual support meeting through association with the social network service according to an opening request signal for the mutual support meeting from the leader terminal;
Wherein the reader and one or more members invest money for a predetermined period in a preset period in accordance with a predetermined rule for the mutual support meeting, and the reader or one of the one or more members Wherein the leader or the member who received the grant within the set period invests a predetermined amount of money in each of the remaining periods of the set period during the set period, Operating department;
A manager for storing and managing information on the leader, information on the member, information on the mutual support group, and information on the credit rating result;
A message processing unit for transmitting an invitation message to the member candidate terminals of the one or more member candidates upon receipt of a message transmission request signal for inviting one or more member candidates from the leader terminal or the member terminal to the mutual support group; And
Receiving a credit rating request signal for the member or reader of the mutual support group from the reader terminal or the member terminal and analyzing the big data of the member or leader collectable in the SNS according to the credit rating request signal, And a monitoring unit for evaluating the creditworthiness of the reader or for providing a credit rating result of the member or leader to the leader terminal or the member terminal,
Social Funding Apparatus Using Big Data Analysis.
Wherein the message processing unit receives the invitation message and receives a credit rating request for at least one member of the leader terminal of the leader terminal or one or more member terminals from a member candidate terminal desiring to register as a member in the mutual support group Analyzing the leader or member-related big data collectable in the SNS, and transmitting the result of the evaluation of the reliability of the reader or the member in the credit evaluation unit, which evaluated the credit of the reader or the member, to the member candidate terminal A social funding device using big data analysis.
Wherein,
A social funding device using big data analysis that collects big data including unstructured data or unstructured data from a social network service of a member candidate who wants to become the leader, member or member.
Wherein the classifying section generates the structured data includes first user related data including information on a financial transaction of the reader, the member, or the member candidate, or the first user related data in addition to the first user related data, related data including at least one selected from personal, housing, job, insurance, social, and vehicle to a corresponding database of a database of a predetermined format 0.0 > a < / RTI > field.
The social funding device may be a device (SNS provision device) for providing the social network service, or may be a functional part or a configuration part of at least a part of the SNS providing device integrally coupled to the SNS providing device, Device.
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