TW202009838A - Online application method and system for accurately determining a credit rating result based on which an application for financial commodity is executed - Google Patents

Abstract

An online application system includes a first electronic device, a bank server, and a customer database. When the bank server receives an application request from the first electronic device that includes image data related to a face and identity information and application related to a financial commodity, it determines the target customer data according to one of the facial feature data and the identity identification data extracted from the image data. When the banker server determines that the facial feature data and the identity identification data respectively correspond to the reference identity information and the reference facial feature data of the target customer data, a credit rating model is used to generate a credit rating result based on the face of the image data and, when it is determined that the credit rating result is not less than a threshold level, the application for the financial commodity is executed.

Description

Online solicitation method and system

The present invention relates to a method and system for solicitation and examination, in particular to an online method and system for solicitation.

Existing online banks can be used by their customers to apply for financial products online. However, when the customer's identity is used by other users different from the customer (common methods of counterfeiting include, for example, the use of fake ID cards), if allowed The other user's bid for a financial commodity transaction, such as a loan, may cause losses to the customer and the bank.

In addition, even if the customer's identity is not used fraudulently, when the customer's credit is not good, it may affect the performance of the transaction. Therefore, the bank still needs to conduct a credit evaluation of the customer. Banks usually make assessments based on the records they have stored or provided by the Lianzheng Center corresponding to the customer. However, there is still room for improvement in the credibility of the assessment results based on the records alone.

Therefore, the purpose of the present invention is to provide an online examination method, which can overcome at least one of the disadvantages of the prior art.

Therefore, the online review method of the present invention is suitable to be executed by an electronic system including a first electronic device operated by a user and a first electronic device provided by a bank Communicate and store a bank server with a pre-trained credit rating model and a customer database connected to the bank server, the customer database stores multiple customer data corresponding to multiple customers of the bank, Each customer profile has reference identification data and reference facial feature data. The method includes:

(A) Through the first electronic device, obtain image data related to a face and identity information through the operation of the user, and send a bid request containing the image data and related to a bid for a financial product to the bank server;

(B) Through the bank server, when receiving the bid request from the first electronic device, extract the facial feature data of the face and the identification information of the identification information from the image data, and according to One of the face feature data and the identification data, one of the customer data is used as the target customer data;

(C) through the bank server, determine whether the facial feature data and the identification data are consistent with the reference facial feature data and the reference identification data of the target customer data, respectively;

(D) With the bank server, when it is determined that the facial feature data and the identification data are consistent with the reference identity data and reference facial feature data of the target customer data, respectively, by the credit rating The model, based at least on the face of the image data, produces a credit rating result; and

(E) Through the bank server, when it is determined that the credit rating result is not less than a threshold level, execute the bid for the financial product.

In some implementation aspects, in step (B), the bank server determines the reference facial feature data of one of the facial feature data and the customer data stored in the customer database When the similarity between the two is not less than a first threshold value, the one of the customer data is used as the target customer data.

In some implementations, the bank server also stores a pre-trained face feature comparison model. In step (B), the bank server compares the face feature comparison model In order to obtain the similarity between the facial feature data and the reference facial feature data of the customer data.

In some implementation forms, each customer data stored in the customer database also has application history record data, and the application history record data has at least one financial commodity that the customer corresponding to the customer data has applied for, in In step (C), the bank server not only determines whether the facial feature data and the identification data match the reference identity data and reference facial feature data of the target customer data, but also based on the target customer data The bid history data of the bid determines whether the financial commodity related to the bid request is the same as one of the financial commodities of the bid history data of the target customer data. In step (D), the bank server determines the The facial feature data and the identification data respectively match the reference identification data and the reference facial feature data of the target customer data, and the financial product related to the bid request does not match the bid history of the target customer data When one of the financial products in the data is the same, the credit rating model is used to generate the credit rating result based on at least the face of the image data.

In some implementation forms, the bank server can also communicate with a Lianzheng server belonging to the Lianzheng center. Step (D) further includes:

(d1) Through the bank server, the reference identity data and reference face feature data that determine that the facial feature data and the identification data respectively match the target customer data, and the relevant bid request When the financial product is not the same as one of the financial products in the bid history data of the target customer data, send a data request containing the reference identification data of the target customer data to the Lianzheng server;

(d2) Through the Lianzheng server, upon receiving the data request from the bank server, send the Lianzheng data related to the customer's credit record corresponding to the target customer data to the bank server; and

(d3) Using the bank server and the credit rating model, the credit rating result is generated based at least on the face and the joint data of the image data.

In some implementation aspects, in step (d2), the joint levy data has at least one of the credit card payment record, loan record, education level, job type, and job title of the customer corresponding to the target customer data .

In some implementations, the bank server also stores an external environmental indicator that includes at least one of a current gross domestic product (Gross Domestic Product, GDP) and a prosperity indicator. In the step ( In d3), the bank server uses the credit rating model to generate the credit rating result not only based on the face and the joint data of the image data, but also based on the external environmental indicators.

In some embodiments, the system further includes a second electronic device that can communicate with the bank server. In step (C), when it is determined that the facial feature data and the identification data do not respectively match the reference identity data and reference facial feature data of the target customer data, or the financial related to the bid request When the commodity is the same as one of the financial commodities in the bid history data of the target customer data, a first notification message related to the manual note is sent to the second electronic device for display. In step (E), when determining that the credit rating result is less than the threshold level, the bank server sends a second notification message related to the manual note to the second electronic device for display.

In some implementation aspects, in step (A), the first electronic device obtains the image data by photographing a certificate containing the face and the identity information.

In some embodiments, in step (A), the first electronic device obtains the first image data related to the identity information by shooting a certificate containing the identity information and by shooting the user's The face obtains second image data related to the human face, and the image data includes the first image data and the second image data.

Therefore, the purpose of the present invention is to provide an online examination system that can overcome at least one of the shortcomings of the prior art.

Therefore, the online review system of the present invention includes a first electronic device operated by a user, a bank server and a customer database. The bank server is provided by a bank and can communicate with the first electronic device and stores a pre-trained credit rating model. The customer database is connected to the bank server, and the customer database stores a plurality of customer data corresponding to the customers of the bank, and each customer data has reference identification data and reference facial feature data.

The first electronic device obtains image data related to a face and identity information through the operation of the user, and transmits a bid request containing the image data and related to the bid of a financial commodity to the bank server.

When receiving the bid request from the first electronic device, the bank server extracts the facial feature data of the face and the identification information of the identity information from the image data, and according to the facial feature data and the One of the identification data will use one of these customer data as the target customer data.

The bank server determines whether the facial feature data and the identification data are consistent with the reference facial feature data and the reference identity identification data of the target customer data, respectively.

When the bank server determines that the facial feature data and the identification data are consistent with the reference identification data and the reference facial feature data of the target customer data, using the credit rating model, at least according to the image The face of the data produces a credit rating result.

The bank server executes the bid for the financial product when it determines that the credit rating result is not less than a threshold level.

In some implementation aspects, the bank server determines that the similarity between the facial feature data and the reference facial feature data of one of the customer data stored in the customer database is not less than one At the first threshold, one of these customer profiles is used as the target customer profile.

In some implementations, the bank server also stores a pre-trained face feature comparison model, and the face feature comparison model is used for comparison to obtain the face feature data and the The similarity between the reference facial feature data of equal customer data.

In some implementation forms, each piece of customer data stored in the customer database also has application history record data, and the application history record data has at least one financial commodity that the customer corresponding to the customer data has applied for.

The bank server not only determines whether the facial feature data and the identification data are consistent with the reference identification data and reference facial feature data of the target customer data, but also based on the bid history data of the target customer data Determine whether the financial product related to the bidding request is the same as one of the financial products in the bidding history data of the target customer data.

The bank server determines that the face identification data and the identification data respectively match the reference identification data and reference face characteristic data of the target customer data, and the financial product related to the bid request does not When one of the financial products in the bid history data of the target customer data is the same, the credit rating model is used to generate the credit rating result based at least on the face of the image data.

In some embodiments, the bank server can also communicate with a Lianzheng server belonging to the Lianzheng center. The bank server determines that the face identification data and the identification data respectively match the reference identification data and reference face characteristic data of the target customer data, and the financial product related to the bid request does not When one of the financial products of the bid history data of the target customer data is the same, a data request containing the reference identification data of the target customer data is sent to the Lianzheng server. When receiving the data request from the bank server, the levy server sends the levy data related to the customer's credit record corresponding to the target customer data to the bank server. The bank server uses the credit rating model to generate the credit rating result based on at least the face and the joint data of the image data.

In some implementation forms, the joint levy data has at least one of the customer's credit card payment record, loan record, education level, job type, and job title corresponding to the target customer data.

In some implementations, the bank server also stores an external environmental indicator, which includes at least one of a current gross domestic product (GDP) and a boom indicator. The bank server uses the credit rating model to generate the credit rating result not only based on the face and the joint data of the image data, but also based on the external environment indicators.

In some embodiments, the system further includes a second electronic device that can communicate with the bank server. The bank server determines that the face identification data and the identification data do not respectively match the reference identification data and reference face characteristic data of the target customer data, or the financial product related to the bid request and the financial When one of the financial commodities in the bid history data of the target customer data is the same, a first notification message related to the manual note is sent to the second electronic device for display. When determining that the credit rating result is less than the threshold level, the bank server sends a second notification message related to the manual note to the second electronic device for display.

In some implementations, the first electronic device obtains the image data by photographing a certificate containing the face and the identity information.

In some embodiments, the first electronic device obtains the first image data related to the identity information by photographing a certificate containing the identity information and obtains the related image data by photographing the user's face The second image data of the face, the image data includes the first image data and the second image data.

The effect of the present invention is that the bank server can determine that the facial feature data and the identification data are consistent with the target customer data and the credit rating model based on the facial data of the image data. Only when the result of a more credible credit rating is not less than the threshold level, the bidding of the financial product is allowed, which not only can effectively reduce the possibility of fraudulent use of the customer's identity, but also the external appearance of the face There is a great chance that the characteristics are related to the economic characteristics, so it can effectively reduce the risks of the bank.

Before the present invention is described in detail, it should be noted that in the following description, similar elements are denoted by the same numbers.

1 and 2, the online review system of the present invention includes a bank server 1, a customer database 2, a first electronic device 3, and a second electronic device 4.

The bank server 1 is provided by a bank and can communicate with the first electronic device 3, the second electronic device 4, and a Lianzheng server 6 belonging to the Lianzheng center through a communication network 5. The bank server 1 stores a pre-trained credit rating model 11, a pre-trained face feature comparison model 12, and an external environment indicator 13, which includes, for example, the current gross domestic product ( Gross Domestic Product (GDP) and boom lights.

The customer database 2 is connected to the bank server 1, and stores a plurality of customer data 21, 21' corresponding to a plurality of customers of the bank, each customer data 21 (21') has reference identification data 211, With reference to the face feature data 212 and the bid history data 213, the bid history data 213 has at least one financial product that the client corresponding to the client data 21 (21') has applied for. In this embodiment, the financial product is, for example, credit card, loan, insurance, etc.

The first electronic device 3 is held by a user who is, for example, a customer of the bank. In this embodiment, the first electronic device 3 is, for example, a smart phone, which is not limited to this, and in other embodiments, it may be a tablet computer, a notebook computer, a personal computer, or the like.

In this embodiment, the second electronic device 4 is held by a bank staff, for example. In this embodiment, the first electronic device 3 is, for example, a personal computer, which is not limited thereto, and in other embodiments, it may be a tablet computer, a notebook computer, a smart phone, or the like.

The following describes how the above embodiment cooperates with the joint enlistment server 6 to perform an embodiment of the online enquiry method of the present invention when the user holds the first electronic device 3 and an identity card in order to apply for a credit card online .

First, as described in step S201, the first electronic device 3 obtains image data related to a face and identity information through the user operation. In this embodiment, the identity information is, for example, the ID number, and it is not limited to this.

In this embodiment, the first electronic device 3 obtains the image data by shooting a certificate containing the face and the identity information, but not limited to this. For example, the first electronic device 3 photographs the front of the ID card (including the headshot and the ID number of the ID) held by the user, so as to obtain image data related to the face and ID number of the ID. In other embodiments, the first electronic device 3 obtains the first image data related to the identity information by photographing a certificate containing the identity information and obtains the relevant image data by photographing the user's face The second image data of the face, the image data including the first image data and the second image data, for example, the first electronic device 3 captures the front of the identity card held by the user to obtain Related to the first image data of the ID number of the identity card and obtaining the second image data related to the face by photographing the face of the user, it is worth mentioning that the image data obtained in this way is related The human face is the face appearance of the user before appropriate. Compared with the headshot on the ID card, the results of subsequent steps S205 and S207 of this embodiment have relatively better accuracy.

Next, as described in step S202, the first electronic device 3 transmits a bid request containing the image data and related to a bid for a financial product to the bank server 1. Continuing the previous example, the bid request is related to the bid for the credit card.

When the bank server 1 receives the bid request from the first electronic device 3, as described in step S203, the bank server 1 extracts the facial feature data of the face and the identity information from the image data Identification information.

Next, in step S204, the bank server 1 uses one of the customer data 21, 21' (eg, customer data 21') as the target customer data based on one of the facial feature data and the identification data twenty one'. In this embodiment, the bank server 1 determines between the facial feature data and the reference facial feature data 211 of one of the customer data 21, 21' stored in the customer database 2 When the similarity of is not less than a first threshold, the customer data 21, 21' of which are used as the target customer data (ie, customer data 21') is not limited to this. In other implementations, the bank server 1 can also be designed to refer these customers when it is determined that the identification data is the same as the reference identification information 212 of one of the customer data 21, 21' Data 21, 21', which is the target customer data (ie customer data 21').

It is worth noting that in this embodiment, the bank server 1 compares the facial feature comparison model 12 to obtain the facial feature data and the customer data 21, 21'. Refer to the similarity between the face feature data 212, which can effectively reduce the computing resources of the system, but not limited to this. In other implementations, the face feature comparison model 12 can be used instead of the general face The facial feature comparison software compares the facial feature data with all such reference facial feature data 212. It is worth noting that, when the number of the reference facial feature data 212 is huge, comparing the facial feature data with the reference facial feature data 212 one by one will be very time-consuming and consume computing resources, and In this embodiment, the pre-trained facial feature comparison model 12 is used for comparison, so there is no need to compare one by one, which has the effect of saving time and saving computing resources.

In step S205, the bank server 1 determines whether the facial feature data and the identification data respectively match the reference identification data 211 and the reference facial feature data 212 of the target customer data (ie, customer data 21') . If the bank server 1 determines that the facial feature data and the identification data do not match the reference identity data 211 and the reference facial feature data 212 of the target customer data (ie, customer data 21'), the process Proceed to step S206, otherwise, if the bank server 1 determines that the facial feature data and the identification data respectively match the reference identity data 211 and the reference person of the target customer data (ie, customer data 21') Face feature data 212, the flow proceeds to step S207.

In step S206, a first notification message related to manual notes is sent to the second electronic device 4 for display. In this way, the staff of the bank can be notified immediately that the document held by the user may be forged for subsequent processing, so that the risk of the customer's identity being used can be reduced.

In step S207, the bank server 1 determines whether the financial product related to the bid request is in accordance with the bid history data 213 of the target customer data (ie, customer data 21') and the target customer data (ie, customer data 21 One of the financial commodities in the historical record data 213 of the bid is the same. When the bank server 1 determines that the financial product related to the bid request is the same as one of the financial products in the bid history data 213 of the target customer data (ie, customer data 21'), the flow proceeds to step S206, otherwise , The process goes to step S208, so that the bank staff can be notified immediately that the customer corresponding to the target customer data (ie customer data 21') is about to repeat the bid for the same financial product for subsequent processing, which can reduce The risk of the customer's identity being used. If the previous example shows that when the credit card that the user wants to apply for is the same as the credit card indicated in the application history data, there is a high possibility that the user is using the customer corresponding to the target customer data 21' If you immediately notify the bank’s staff at this time, you can effectively reduce the chance of fraud.

In addition, in other implementations, step S207 may also be omitted, that is, when the determination result of step S205 is yes, the flow directly proceeds to step S208.

In step S208, the bank server 1 transmits a data request of the reference identification data 211 containing the target customer data (i.e., customer data 21') to the Lianzheng server 6.

When the Lianzheng server 6 receives the data request from the bank server 2, as described in step S209, the Lianzheng server 6 transmits the data corresponding to the target customer data (ie, customer data 21') The joint levy information of the customer's credit record is sent to the bank server 1. In this embodiment, the joint levy data has the credit card payment record, loan record, education level, job type and job title of the customer corresponding to the target customer data (i.e. customer data 21').

When the bank server 1 receives the joint levy data from the joint levy server 6, as described in step S210, with the credit rating model 11, based on the face and the joint levy data of the image data And the external environment index 13 produces a credit rating result.

In step S211, the bank server 1 determines whether the credit rating result is not less than a threshold level. If the result is yes, the process proceeds to step S212, otherwise, the process proceeds to step S213.

In step S212, the bank server 1 executes the application for the financial commodity related to the application request. Following the previous example, the bank server 1 executes the application for the credit card.

In step S213, the bank server 1 sends a second notification message related to the manual note to the second electronic device 4 for display. In this way, the bank’s staff can be notified immediately that the user’s credit rating is too low for subsequent processing, which can reduce the bank’s risk.

In summary, the bank server 1 determines that the facial feature data and the identification data respectively match the reference identity data 211 and the reference facial feature data of the target customer data (ie, customer data 21') 212 and only if the credit rating result generated by the credit rating model 11 based on the face of the image data, the joint levy data, and the external environmental indicators 13 is not less than the threshold level, Allowing the bidding of this financial product not only effectively reduces the possibility of being misappropriated by the customer's identity, but also the external characteristics presented by the face have a great chance to be related to economic characteristics, so it can also effectively reduce the risk of the bank .

However, the above are only examples of the present invention, and should not be used to limit the scope of the present invention. Any simple equivalent changes and modifications made according to the scope of the patent application of the present invention and the content of the patent specification are still classified as This invention covers the patent.

100‧‧‧ Online review system 1‧‧‧Bank server 11‧‧‧ Credit rating model 12‧‧‧Face feature comparison model 13‧‧‧External environment indicators 2‧‧‧Customer database 21, 21 '‧‧‧Customer information 211‧‧‧Reference identification data 212‧‧‧Reference facial feature data 213‧‧‧ Bid history 3‧‧‧First electronic device 4‧‧‧Second electronic device 5‧‧‧ Communication network 6‧‧‧Lengzheng server S201 ~ S213‧‧‧

Other features and functions of the present invention will be clearly presented in the embodiment with reference to the drawings, in which: FIG. 1 is a block diagram exemplarily illustrating an embodiment of the online review system of the present invention; and FIG. 2 is A flow chart exemplarily illustrates an embodiment of the online review method of the present invention.

100‧‧‧ Online collection system

1‧‧‧Bank server

11‧‧‧ Credit Rating Model

12‧‧‧ facial feature comparison model

13‧‧‧External environmental indicators

2‧‧‧Customer database

21, 21’‧‧‧ Customer Information

211‧‧‧Reference identification data

212‧‧‧Reference to face feature data

213‧‧‧ Bid history

3‧‧‧ First electronic device

4‧‧‧Second electronic device

5‧‧‧Communication network

6‧‧‧Lianzheng Server

Claims (20)

An online examination method suitable for execution by an electronic system including a first electronic device operated by a user and a bank provided by a bank capable of communicating with and storing the first electronic device There is a bank server with a pre-trained credit rating model and a customer database connected to the bank server. The customer database stores multiple customer data corresponding to multiple customers of the bank, each customer The data has reference identification data and reference face feature data. The method includes: (A) obtaining image data related to a face and identity information through the operation of the user through the first electronic device, and sending a message containing The image data and the application request related to the application for a financial product to the bank server; (B) through the bank server, when receiving the application request from the first electronic device, the image data is extracted Take out the facial feature data of the face and the identification data of the identity information, and according to one of the facial feature data and the identity data, use one of the customer data as the target customer data; (C) Through the bank server, determine whether the facial feature data and the identification data match the reference facial feature data and the reference identity data of the target customer data, respectively; (D) through the bank server, When it is determined that the facial feature data and the identification data are consistent with the reference identification data and the reference facial feature data of the target customer data, respectively, by using the credit rating model, at least the person based on the image data Face, produce a credit rating result; and (E) through the bank server, when it is determined that the credit rating result is not less than a threshold level, execute the bid for the financial product. The online review method as described in claim 1, wherein in step (B), the bank server determines one of the face data and the customer data stored in the customer database When the similarity between the reference facial feature data is not less than a first threshold, the customer data is used as the target customer data. The online review method as described in claim 2, wherein the bank server also stores a pre-trained face feature comparison model. In step (B), the bank server uses the face The feature comparison model performs comparison to obtain the similarity between the facial feature data and the reference facial feature data of the customer data. The online review method as described in claim 1, wherein each customer data stored in the customer database also has application history record data, and the application history record data has the application filed by the customer corresponding to the customer data Of at least one financial product, in step (C), the bank server not only determines whether the facial feature data and the identification data respectively match the reference identity data and reference facial feature data of the target customer data, It is also determined whether the financial product related to the bid request is the same as one of the financial products in the bid history data of the target customer data according to the bid history data of the target customer data. In step (D), the The bank server determines that the face identification data and the identification data respectively match the reference identification data and reference face characteristic data of the target customer data, and the financial product related to the bid request does not match the target When one of the financial products in the bid history data of the customer data is the same, the credit rating model is used to generate the credit rating result based on at least the face of the image data. The online review method as described in claim 4, wherein the bank server can also communicate with a joint signing server belonging to the joint signing center. Step (D) further includes: (d1) through the bank server The device, when it is determined that the facial feature data and the identification data are consistent with the reference identity data and reference facial feature data of the target customer data, respectively, and the financial product related to the bid request is not in contact with the target customer When one of the financial commodities in the bid history data of the data is the same, send a data request containing the reference identification data of the target customer data to the Lianzheng server; (d2) Through the Lianzheng server, at When receiving the data request from the bank server, send the levy data related to the customer's credit record corresponding to the target customer data to the bank server; and (d3) through the bank server, borrow The credit rating model generates the credit rating result based at least on the face and the joint data of the image data. The online solicitation method as described in claim 5, wherein in step (d2), the joint solicitation data has a credit card payment record, loan record, education level, and job of the customer corresponding to the target customer data At least one of category and job title. The online review method as described in claim 6, wherein the bank server also stores an external environmental indicator, which includes a current gross domestic product (Gross Domestic Product, GDP) and a boom signal At least one, in step (d3), the bank server uses the credit rating model to generate the credit rating not only based on the face and the joint data of the image data, but also based on the external environmental indicators Wait for the result. As in the online review method described in claim 7, the system further includes a second electronic device that can communicate with the bank server, wherein: in step (C), the facial feature data and the The identification data does not match the reference identity data and reference facial feature data of the target customer data, or one of the financial commodities related to the bid request and the target customer data of the bid history data At the same time, send a first notification message related to the manual note to the second electronic device for display; and in step (E), the bank server determines that the credit rating result is less than the threshold level , Send a second notification message related to the manual note to the second electronic device for display. The online review method according to claim 1, wherein in step (A), the first electronic device obtains the image data by photographing a certificate containing the face and the identity information. The online review method of claim 1, wherein in step (A), the first electronic device obtains the first image data related to the identity information by shooting a certificate containing the identity information and The second image data related to the human face is obtained by photographing the face of the user, and the image data includes the first image data and the second image data. An online review system includes: a first electronic device operated by a user; a bank server provided by a bank, which can communicate with the first electronic device and store a pre-trained credit rating And other models; and a customer database, connected to the bank server, the customer database stores multiple customer data corresponding to multiple customers of the bank, each customer data has reference identification data and reference facial features Data; wherein, the first electronic device obtains image data related to a face and an identity information through the operation of the user, and transmits a bid request containing the image data and related to a bid for a financial product to the bank server ; Wherein, when receiving the bid request from the first electronic device, the bank server extracts the facial feature data of the face and the identification information of the identity information from the image data, and according to the facial features One of the data and the identification data, one of the customer data is used as the target customer data; wherein, the bank server determines whether the facial feature data and the identification data are consistent with the target customer data. The reference facial feature data and the reference identification data; wherein, the bank server determines that the facial feature data and the identification data respectively match the reference identity data and the reference facial feature of the target customer data When using the credit rating model, at least according to the face of the image data, a credit rating result is generated; and, when the bank server determines that the credit rating result is not less than a threshold level, Implement the bid for the financial product. The online review system as described in claim 11, wherein the bank server determines the reference facial feature data of one of the facial feature data and the customer data stored in the customer database When the similarity between the two is not less than a first threshold value, the one of the customer data is used as the target customer data. The online review system as described in claim 12, wherein the bank server also stores a pre-trained face feature comparison model and compares the face feature comparison model to obtain The similarity between the facial feature data and the reference facial feature data of the customer data. The online solicitation system as described in claim 11, wherein: each customer data stored in the customer database also has application history record data, and the application history record data has the application filed by the customer corresponding to the customer data At least one financial product; the bank server not only determines whether the facial feature data and the identification data match the reference identity data and reference facial feature data of the target customer data, but also based on the target customer data The bid history data of the bid determines whether the financial product related to the bid request is the same as one of the financial products of the bid history data of the target customer data; and the bank server is determining the facial feature data and the The identification data respectively matches the reference identification data and reference facial feature data of the target customer data, and the financial product related to the bid request does not match one of the financial products of the bid history data of the target customer data At the same time, the credit rating model is used to generate the credit rating result based at least on the face of the image data. The online review system as described in claim 14, wherein: the bank server can also communicate with a joint sign server belonging to the joint sign center; the bank server is determining the facial feature data and the identity The identification data respectively matches the reference identification data and reference facial feature data of the target customer data, and the financial product related to the bid request is not the same as one of the financial products of the bid history data of the target customer data When sending a data request containing the reference identification data of the target customer to the Lianzheng server; when the Lianzheng server receives the data request from the bank server, it transmits the data related to the target customer The joint levy data of the customer's credit record corresponding to the data is sent to the bank server; and the bank server uses the credit rating model to generate the credit based on at least the face of the image data and the joint levy data Rating results. The online solicitation system as described in claim 15, wherein the joint solicitation data has at least one of the customer's credit card payment record, loan record, education level, job type and job title corresponding to the target customer data . The online review system as described in claim 16, wherein: The bank server also stores an external environmental indicator, which includes a current gross domestic product (Gross Domestic Product, GDP) and a boom signal At least one; and the bank server uses the credit rating model to generate the credit rating result not only based on the face and the joint data of the image data, but also based on the external environment indicators. The online review system as described in claim 17 further includes a second electronic device that can communicate with the bank server, wherein: the bank server determines that the facial feature data and the identification data are not separate When the reference identification data and reference facial feature data matching the target customer data, or the financial product related to the bid request and the financial data of the target customer data of the bid history are the same, send a The first notification message related to the manual note is sent to the second electronic device for display; and when the bank server determines that the credit rating result is less than the threshold level, it sends a second notification message related to the manual note To the second electronic device for display. The online review system according to claim 11, wherein the first electronic device obtains the image data by photographing a certificate containing the face and the identity information. The online review system of claim 11, wherein the first electronic device obtains the first image data related to the identity information by shooting a certificate containing the identity information and by shooting the user's The face obtains second image data related to the human face, and the image data includes the first image data and the second image data.

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