A financial data risk control system based on big data

Abstract

The present invention discloses a financial data risk control system based on big data, which relates to the technical field of financial risk control management, and comprises a monitoring center, wherein the monitoring center is communicatively connected with an information base, a data acquisition module, a data processing module, a data analysis module and a risk buffer module; the financial transaction data generated by the financial transactions conducted by individual users are obtained, thereby obtaining the transaction objects of the financial transactions, and the historical long-term historical financial data and recent historical financial data of the transaction objects are monitored, thereby obtaining the financial volatility coefficient of the enterprise, and at the same time, the online financial data of the individual users are analyzed to determine the risk level of the financial transaction process conducted by the individual users, and when the risk level is high, the users are warned; at the same time, a risk buffer period is set, so that there can be a buffer period in the financial transaction process of the individual users, thereby preventing the individual users from blindly conducting financial transactions, and providing a reference for the individual users to avoid risks.

Description

Technical Field

[0001] The present invention relates to the technical field of financial risk control management, and in particular to a financial data risk control system based on big data. Background Art

[0002] Applications in the financial field tend to be data-informed and structured, and the credit assessment of customer credit lines is also based on a large amount of personal information of customers. At present, more and more financial network platforms and terminal financial software have emerged, generating a large amount of data information on the network.

[0003] In the process of financial transactions, individual users are unable to conduct a good risk assessment of the selected transaction targets, which makes individual users not understand the risk level of their financial transactions and causes blind transactions. How to conduct an effective risk assessment of individual users' financial transactions and provide an effective reference for their financial transactions is a problem we need to solve. Now we provide a financial data risk control system based on big data. Summary of the invention

[0004] The purpose of the present invention is to provide a financial data risk control system based on big data.

[0005] The object of the present invention can be achieved by the following technical solutions: A financial data risk control system based on big data, comprising a monitoring center, wherein the monitoring center is communicatively connected to an information base, a data acquisition module, a data processing module, a data analysis module and a risk buffer module;

[0006] The information database stores client information and financial institution information, wherein the client information is specifically generated based on information registered by individual users, and the financial institution information is specifically generated based on information registered by enterprises;

[0007] The data acquisition module is used to obtain financial data of client information and financial institution information, thereby obtaining online financial data of individual users and historical financial data of enterprises;

[0008] The data processing module is used to process the obtained historical financial data of the enterprise to obtain the financial volatility coefficient of the enterprise;

[0009] The data analysis module is used to analyze the online financial data of individual users to obtain the financial transaction risk coefficient of the individual users;

[0010] The risk buffer module is used to buffer the online financial data of the individual user according to the received risk warning information and transaction confirmation information.

[0011] Furthermore, the process of generating the client information includes:

[0012] Set up a user information registration port, through which individual users can verify their basic personal information online;

[0013] Enter basic personal information; the individual user confirms the personal information entered and sends the confirmed personal information to the monitoring center, which will review the personal information. Once the review is passed, a personal financial account will be generated based on the real-name authenticated mobile phone number entered by the individual user.

[0014] Furthermore, the process of generating the financial institution information includes:

[0015] Set up an enterprise registration port. The enterprise conducts enterprise qualification verification through the enterprise registration port and inputs the basic information of the enterprise. The monitoring center verifies the basic information of the enterprise. After the verification, a financial institution account is generated. After the financial institution account is verified, an enterprise business platform is generated, and the enterprise business platform is bound to the financial institution account to obtain the financial institution information.

[0016] Furthermore, the financial data process of the data acquisition module acquiring the client information and the financial institution information includes:

[0017] A unique client information platform is generated based on the client information. When an individual user conducts online financial transactions, the online financial data generated by the online financial transactions conducted by the individual user is uploaded to the client information platform; the online financial data in the client information platform is obtained, and the online financial data includes the transaction target, transaction amount and transaction type, and the transaction time is marked as BT; and the client information and online financial data corresponding to the client information platform are sent to the data processing module; according to the online financial data transaction target of the individual user, the transaction target financial institution information is obtained, and the historical financial data of the financial institution is obtained.

[0018] Furthermore, the data processing module processes the historical financial data of the enterprise including:

[0019] Establishing a two-dimensional coordinate system, and setting a first time period and a second time period;

[0020] Generate a financial data change curve of the financial data in the past first time period according to the acquired historical financial data of the enterprise;

[0021] Obtain the maximum and minimum values ​​in the financial data change curve within the first time period, and simultaneously obtain the time corresponding to the maximum and minimum values;

[0022] Obtain all fluctuation points in the second time period, and obtain the value corresponding to each fluctuation point; at the same time, obtain the duration of each fluctuation point, so as to obtain the financial volatility coefficient of the enterprise.

[0023] Furthermore, the data analysis module analyzes the online financial data of individual users including:

[0024] Obtain the current transaction amount of individual users and the transaction value in online financial data, so as to obtain the financial transaction risk coefficient of individual users;

[0025] A risk factor threshold is set, and the financial transaction risk factor is compared with the risk factor threshold to determine the risk level of the individual user's financial transaction.

[0026] Compared with the prior art, the beneficial effects of the present invention are: the financial transaction data generated by the financial transactions conducted by individual users are used to obtain the transaction objects of the financial transactions, the historical long-term historical financial data and the recent historical financial data of the transaction objects are monitored, so as to obtain the financial volatility coefficient of the enterprise, and at the same time, the online financial data of individual users are analyzed to determine the risk level of the financial transaction process conducted by individual users, and when the risk level is high, the user is warned; at the same time, a risk buffer period is set so that there can be a buffer period in the financial transaction process of individual users, thereby preventing individual users from blindly conducting financial transactions and providing a reference for individual users to avoid risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0028] like Figure 1 As shown, a financial data risk control system based on big data includes a monitoring center, wherein the monitoring center is communicatively connected to an information base, a data acquisition module, a data processing module, a data analysis module, and a risk buffer module;

[0029] The information database stores client information and financial institution information, wherein the client information is specifically generated based on information registered by individual users, and the financial institution information is specifically generated based on information registered by enterprises;

[0030] It should be further explained that, in the specific implementation process, the process of generating the client information includes:

[0031] A user information registration port is set up, and individual users verify their basic personal information online through the user information registration port; it should be further explained that in the specific implementation process, the basic personal information verification process includes:

[0032] Enter basic personal information, including name, gender, age, real-name authenticated mobile phone number, and face photo;

[0033] The individual user confirms the personal information entered and sends the confirmed personal information to the monitoring center, which reviews the personal information. After the review is passed, a personal financial account is generated based on the real-name authenticated mobile phone number entered by the individual user;

[0034] After an individual user enters the system through a personal financial account, the user can select at least one bank card to bind to the personal financial account;

[0035] It needs to be further explained that, during the specific implementation process, after completing the verification of personal basic information, the individual user obtains the individual user's transaction limit, binds the individual user's transaction limit to the individual user's personal financial account, and obtains client information. It needs to be further explained that, during the specific implementation process, the user's transaction limit will increase with the increase in the individual user's usage time and the number of successful transactions.

[0036] It should be further explained that, in the specific implementation process, the process of generating the financial institution information includes:

[0037] Set up an enterprise registration port, and the enterprise will verify its qualifications through the enterprise registration port. It should be further explained that in the specific implementation process, the enterprise qualification verification process includes:

[0038] Enter the basic information of the enterprise, including name, legal person, registered capital, business scope and operating data;

[0039] The monitoring center verifies the basic information of the enterprise and generates a financial institution account after verification;

[0040] It should be further explained that, in the specific implementation process, after the financial institution account is verified, an enterprise business platform is generated, and the enterprise business platform is bound to the financial institution account to obtain the financial institution information.

[0041] The data acquisition module is used to obtain financial data of client information and financial institution information, and the specific process includes:

[0042] Generate a unique client information platform based on the client information, and upload the online financial data generated by the online financial transactions conducted by the individual users to the client information platform; obtain the online financial data in the client information platform, the online financial data includes the transaction target, transaction amount and transaction type, and mark the transaction time, which is recorded as BT; and send the client information and online financial data corresponding to the client information platform to the data processing module;

[0043] It should be further explained that, in the specific implementation process, after an individual user completes a financial online transaction, the financial data generated during the transaction will not take effect immediately, but the financial data will be uploaded to the client information platform;

[0044] According to the online financial data transaction target of the individual user, the transaction target financial institution information is obtained, the historical financial data of the financial institution is obtained, and the historical financial data is sent to the data processing module.

[0045] The data processing module is used to process the obtained historical financial data of the enterprise, and the specific processing process includes:

[0046] Establish a two-dimensional coordinate system, and set a first time period T1 and a second time period T2, wherein T1>T2;

[0047] Generate a financial data change curve of the financial data in the past first time period T1 according to the obtained historical financial data of the enterprise;

[0048] Get the maximum and minimum values ​​in the financial data change curve in the first time period T1, and mark the maximum and minimum values ​​as JZ respectively max and JZ min ;

[0049] At the same time, obtain the time corresponding to the maximum value and the minimum value, and mark the time corresponding to the maximum value and the minimum value as t1 and t2;

[0050] It should be further explained that, in the specific implementation process, the second period T2 is included in the first period T1, and the second period T2 is composed of two time axes, one of which corresponds to the current moment, and the other corresponds to a past moment with a time interval of T2 from the current moment;

[0051] Obtain all fluctuation points in the second time period, and label each fluctuation point as i; wherein i=1, 2, ..., n, and n is an integer; it should be further explained that in the specific implementation process, the financial data will be continuously updated over time, and when the financial data changes, it indicates a corresponding fluctuation point;

[0052] Get the value corresponding to each fluctuation point and mark the value as SZ i ; At the same time, obtain the duration of each fluctuation point and mark the duration of each fluctuation point as BS i ;

[0053] When the maximum or minimum value in the financial data change curve is not within the second time period T2, the financial volatility coefficient of the enterprise is obtained as JB1, where

[0054] When at least one of the maximum value or the minimum value in the financial data change curve is within the second time period T2, the financial volatility coefficient of the enterprise is obtained as JB2, where

[0055] The obtained financial volatility coefficient of the enterprise is sent to the data analysis module.

[0056] The data analysis module is used to analyze the online financial data of individual users. The specific analysis process includes:

[0057] Obtain the current transaction amount of the individual user, and record the current transaction amount of the individual user as JE;

[0058] Obtain transaction values ​​from online financial data of personal user financial transactions and mark the transaction values ​​as JS;

[0059] Then the financial transaction risk coefficient of the individual user is obtained, and the financial transaction risk coefficient of the individual user is marked as JX;

[0060] When the maximum and minimum values ​​of the financial data change curve corresponding to the transaction target are not within the second time period T2, the financial transaction risk coefficient of the individual user JX = (JS / JE)*k1*JB1;

[0061] When at least one of the maximum value and the minimum value of the financial data change curve corresponding to the transaction target is within the second time period T2, the financial transaction risk coefficient of the individual user JX = (JS / JE)*k2*JB2;

[0062] It should be further explained that, in the specific implementation process, k1 and k2 are weight coefficients, and 0<k1<k2;

[0063] A risk coefficient threshold J0 is set. When JX≥J0, it means that the risk level of the financial transaction of the individual user is high, and a risk warning message is generated and sent to the mobile phone terminal of the individual user. When JX<J0, it means that the risk level of the financial transaction of the individual user is low, and a transaction confirmation message is generated and sent to the mobile phone terminal of the individual user.

[0064] The financial transaction data generated by the financial transactions conducted by individual users are used to obtain the transaction objects of the financial transactions. The historical long-term historical financial data and recent historical financial data of the transaction objects are monitored to obtain the financial volatility coefficient of the enterprise. At the same time, the online financial data of individual users are analyzed to determine the risk level of the financial transaction process conducted by individual users, and when the risk level is high, the user is warned.

[0065] The risk buffer module is used to buffer the online financial data of individual users according to the received risk warning information and transaction confirmation information. The specific process includes:

[0066] When an individual user receives risk warning information, a buffer period HT is set, and the individual user confirms the risk warning information. When the individual user confirms the risk warning information, the financial transaction process is completed after the buffer period HT ends; when the user does not confirm the risk warning, the financial transaction process is cancelled;

[0067] When the individual user receives the transaction confirmation information, the individual user confirms the transaction confirmation information. If the individual user confirms the transaction confirmation information, the financial transaction process is completed immediately; when the individual user does not confirm the transaction confirmation information, the financial transaction process is automatically completed after the buffer period HT ends.

[0068] It should be further explained that, in the specific implementation process, when an individual user confirms the risk warning information or transaction confirmation information, the starting time of the financial transaction is the transaction time BT of the individual user;

[0069] By setting a risk buffer period, individual users can have a buffer period during their financial transactions, thus preventing them from blindly conducting financial transactions and providing a reference for them to avoid risks.

[0070] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A financial data risk control system based on big data, including a monitoring center, It is characterized in that The monitoring center is communicatively connected to an information base, a data acquisition module, a data processing module, a data analysis module and a risk buffer module; The information database stores client information and financial institution information, wherein the client information is specifically generated based on information registered by individual users, and the financial institution information is specifically generated based on information registered by enterprises; The data acquisition module is used to obtain financial data of client information and financial institution information, thereby obtaining online financial data of individual users and historical financial data of enterprises; The data processing module is used to process the obtained historical financial data of the enterprise to obtain the financial volatility coefficient of the enterprise. The specific processing process includes: Establish a two-dimensional coordinate system, and set a first time period T1 and a second time period T2, wherein T1>T2; Generate a financial data change curve of the financial data in the past first time period T1 according to the obtained historical financial data of the enterprise; Get the maximum and minimum values ​​in the financial data change curve in the first time period T1, and mark the maximum and minimum values ​​as JZ respectively max and JZ min ; At the same time, obtain the time corresponding to the maximum value and the minimum value, and mark the time corresponding to the maximum value and the minimum value as t1 and t2; Obtain all fluctuation points in the second time period, and label each fluctuation point as i; wherein i=1, 2, ..., n, where n is an integer; Get the value corresponding to each fluctuation point and mark the value as SZ i ; At the same time, obtain the duration of each fluctuation point and mark the duration of each fluctuation point as BS i ; When the maximum or minimum value in the financial data change curve is not within the second time period T2, the financial volatility coefficient of the enterprise is obtained as JB1, where When at least one of the maximum value or the minimum value in the financial data change curve is within the second time period T2, the financial volatility coefficient of the enterprise is obtained as JB2, where Sending the obtained financial volatility coefficient of the enterprise to the data analysis module; The data analysis module is used to analyze the online financial data of individual users to obtain the financial transaction risk coefficient of the individual users. The specific analysis process includes: Obtain the current transaction amount of the individual user, and record the current transaction amount of the individual user as JE; Obtain transaction values ​​from online financial data of personal user financial transactions and mark the transaction values ​​as JS; Then the financial transaction risk coefficient of the individual user is obtained, and the financial transaction risk coefficient of the individual user is marked as JX; When the maximum and minimum values ​​of the financial data change curve corresponding to the transaction target are not within the second time period T2, the financial transaction risk coefficient of the individual user JX = (JS / JE)*k1*JB1; When at least one of the maximum value and the minimum value of the financial data change curve corresponding to the transaction target is within the second time period T2, the financial transaction risk coefficient of the individual user JX = (JS / JE)*k2*JB2; k1 and k2 are both weight coefficients, and 0<k1<k2; A risk coefficient threshold J0 is set. When JX≥J0, it means that the risk level of the financial transaction of the individual user is high, and a risk warning message is generated and sent to the mobile phone terminal of the individual user. When JX<J0, it means that the risk level of the financial transaction of the individual user is low, and a transaction confirmation message is generated and sent to the mobile phone terminal of the individual user. The risk buffer module is used to buffer the online financial data of the individual user according to the received risk warning information and transaction confirmation information.

2. According to the financial data risk control system based on big data as described in claim 1, It is characterized in that The process of generating the client information includes: Set up a user information registration port, through which individual users can verify their basic personal information online; Enter basic personal information; the individual user confirms the personal information entered and sends the confirmed personal information to the monitoring center, which will review the personal information. Once the review is passed, a personal financial account will be generated based on the real-name authenticated mobile phone number entered by the individual user.

3. According to the financial data risk control system based on big data as described in claim 2, It is characterized in that The process of generating the financial institution information includes: Set up an enterprise registration port. The enterprise conducts enterprise qualification verification through the enterprise registration port and inputs the basic information of the enterprise. The monitoring center verifies the basic information of the enterprise. After the verification, a financial institution account is generated. After the financial institution account is verified, an enterprise business platform is generated, and the enterprise business platform is bound to the financial institution account to obtain the financial institution information.

4. According to the financial data risk control system based on big data as described in claim 3, It is characterized in that The process of the data acquisition module acquiring the financial data of the client information and the financial institution information includes: A unique client information platform is generated based on the client information. When an individual user conducts online financial transactions, the online financial data generated by the online financial transactions conducted by the individual user is uploaded to the client information platform; the online financial data in the client information platform is obtained, and the online financial data includes the transaction target, transaction amount and transaction type, and the transaction time is marked as BT; and the client information and online financial data corresponding to the client information platform are sent to the data processing module; according to the online financial data transaction target of the individual user, the transaction target financial institution information is obtained, and the historical financial data of the financial institution is obtained.

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