CN113159788A - Transaction data processing method and device, storage medium and electronic equipment - Google Patents
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Abstract
The invention provides a transaction data processing method and device, a storage medium and electronic equipment, wherein the method comprises the following steps: when a transaction request sent by a user to be verified is received, a client behavior track and a user identifier contained in the transaction request are obtained; the client behavior track comprises an operation path adopted by the user to be verified to send the transaction request and operation information generated by the user to be verified in the operation path; the operation path comprises page information of each page visited by the user to be verified; risk recognition is carried out on the client behavior track by applying a pre-constructed risk recognition model corresponding to the user identification, and a risk recognition result of the client behavior track is obtained; and executing the transaction operation corresponding to the transaction request under the condition that the risk identification result represents that the client behavior track has no risk. By applying the transaction data processing method provided by the invention, the transaction risk caused by the leakage of the user name and the password of the user can be avoided, and the property safety of the user can be effectively guaranteed.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a transaction data processing method and apparatus, a storage medium, and an electronic device.
Background
With the rapid development of internet technology, transaction services based on the internet are more and more, and in order to ensure the security of internet service processing, when the service processing is performed, the identity of a user handling the service needs to be verified, and when the identity is verified, corresponding transaction services can be provided for the user.
At present, when transaction business processing is carried out, identity verification is carried out on a user by checking information such as a user name, a password and the like of the user handling the business, however, the user name and the password information of the user are easy to leak, and under the condition that the user name and the password of the user leak, the asset safety of the user cannot be guaranteed.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a transaction data processing method, which can avoid transaction risks caused by leakage of user names and passwords of users and can effectively guarantee asset safety of the users.
The invention also provides a transaction data processing device which is used for ensuring the realization and the application of the method in practice.
A transaction data processing method, comprising:
when a transaction request sent by a user to be verified is received, a customer behavior track and a user identifier contained in the transaction request are obtained; the customer behavior track comprises an operation path adopted by the user to be verified to send the transaction request and operation information generated by the user to be verified in the operation path; the operation path comprises page information of each page visited by the user to be verified;
performing risk recognition on the customer behavior track by applying a pre-constructed risk recognition model corresponding to the user identification to obtain a risk recognition result of the customer behavior track;
and executing the transaction operation corresponding to the transaction request under the condition that the risk identification result represents that the customer behavior trace has no risk.
Optionally, in the method, the applying a pre-constructed risk identification model corresponding to the user identifier to perform risk identification on the customer behavior trajectory to obtain a risk identification result of the customer behavior trajectory includes:
acquiring a pre-constructed risk identification model corresponding to the user identification;
preprocessing the client behavior track to obtain input parameters matched with the input format of the risk identification model;
and inputting the input parameters into the risk identification model to obtain a risk identification result of the customer behavior track output by the risk identification model.
The above method, optionally, the constructing process of the risk identification model includes:
obtaining a training sample set, wherein the training sample set comprises a plurality of historical customer behavior tracks of a user corresponding to the user identification; each historical customer behavior track comprises an operation path adopted by the user to send each historical transaction request and operation information generated by the user in the operation path; the operation path comprises each page visited by the user;
and training the risk recognition model by applying the training sample set.
Optionally, in the foregoing method, the operation information includes page operation information of the user to be verified on each page, and each page operation information includes at least one of: page dwell time, element input order, element input time.
The above method, optionally, further includes:
under the condition that the risk identification result represents that the client behavior track has risks, acquiring a face image of the user to be verified;
the face image is identified by applying a preset face identification model, and the identification result of the face image is obtained;
if the identification result represents that the user to be verified is the user corresponding to the user identification, executing the transaction operation corresponding to the transaction request;
and if the identification result represents that the user to be verified is not the user corresponding to the user identification, rejecting the transaction request.
A transaction data processing apparatus comprising:
the system comprises a receiving unit, a verification unit and a verification unit, wherein the receiving unit is used for acquiring a client behavior track and a user identifier contained in a transaction request when the transaction request sent by a user to be verified is received; the customer behavior track comprises an operation path adopted by the user to be verified to send the transaction request and operation information generated by the user to be verified in the operation path; the operation path comprises page information of each page visited by the user to be verified;
the identification unit is used for carrying out risk identification on the customer behavior track by applying a pre-constructed risk identification model corresponding to the user identification to obtain a risk identification result of the customer behavior track;
and the execution unit is used for executing the transaction operation corresponding to the transaction request under the condition that the risk identification result represents that the customer behavior track has no risk.
The above method, optionally, the identification unit includes:
the obtaining subunit is configured to obtain a training sample set, where the training sample set includes a plurality of historical customer behavior tracks of a user corresponding to the user identifier; each historical customer behavior track comprises an operation path adopted by the user to send each historical transaction request and operation information generated by the user in the operation path; the operation path comprises page information of each page visited by the user;
and the training subunit is used for applying the training sample set to train the risk identification model.
The above method, optionally, further includes a face recognition unit, where the face recognition unit is configured to:
under the condition that the risk identification result represents that the client behavior track has risks, acquiring a face image of the user to be verified;
the face image is identified by applying a preset face identification model, and the identification result of the face image is obtained;
if the identification result represents that the user to be verified is the user corresponding to the user identification, executing the transaction operation corresponding to the transaction request;
and if the identification result represents that the user to be verified is not the user corresponding to the user identification, rejecting the transaction request.
A storage medium comprising stored instructions, wherein the instructions, when executed, control a device on which the storage medium is located to perform a transaction data processing method as described above.
An electronic device comprising a memory, and one or more instructions, wherein the one or more instructions are stored in the memory and configured to be executed by one or more processors to perform a transaction data processing method as described above.
Compared with the prior art, the invention has the following advantages:
the invention provides a transaction data processing method and device, a storage medium and electronic equipment, wherein the method comprises the following steps: when a transaction request sent by a user to be verified is received, a customer behavior track and a user identifier contained in the transaction request are obtained; the customer behavior track comprises an operation path adopted by the user to be verified to send the transaction request and operation information generated by the user to be verified in the operation path; the operation path comprises page information of each page visited by the user to be verified; performing risk recognition on the customer behavior track by applying a pre-constructed risk recognition model corresponding to the user identification to obtain a risk recognition result of the customer behavior track; and executing the transaction operation corresponding to the transaction request under the condition that the risk identification result represents that the customer behavior trace has no risk. By applying the transaction data processing method provided by the invention, the risk identification is carried out on the client behavior track of the user to be verified through the risk identification model corresponding to the user identification, and the transaction request operation is executed under the condition that the risk identification result represents that the client behavior has no risk, so that the transaction risk caused by the leakage of the user name and the password of the user can be avoided, and the property safety of the user can be effectively guaranteed.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a flow chart of a method of transaction data processing according to the present invention;
FIG. 2 is a flow chart of a process for obtaining risk identification results of customer behavior traces according to the present invention;
FIG. 3 is a flow chart of a risk identification model building process provided by the present invention;
FIG. 4 is a flow chart of another method of a transaction data processing method according to the present invention;
FIG. 5 is a schematic diagram of a transaction data processing apparatus according to the present invention;
fig. 6 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In this application, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
An embodiment of the present invention provides a transaction data processing method, which may be applied to an electronic device, where a method flowchart of the method is shown in fig. 1, and specifically includes:
s101: when a transaction request sent by a user to be verified is received, a customer behavior track and a user identifier contained in the transaction request are obtained; the customer behavior track comprises an operation path adopted by the user to be verified to send the transaction request and operation information generated by the user to be verified in the operation path; the operation path comprises page information of each page visited by the user to be verified.
The operation information comprises page operation information of the user to be verified on each page, and each page operation information comprises at least one of the following: page dwell time, element input order, element input time.
Specifically, the page information may include information such as an application to which the page belongs and a page identifier.
Optionally, the element input sequence may be the sequence of each character input by the user on the page, or the sequence of information required for each item of the transaction request sent by the user on the page, that is, the element may be the character input by the user on the page, or may be the information required for sending the transaction request input by the user on the page.
Optionally, the operation path includes page information of each page that is accessed by the user to be verified according to a time sequence, the page is a visual page of the application program, the application programs of each page may be the same or different, and the user to be verified may access at least one page of at least one application program to send the transaction request.
Specifically, the last page of the operation path may be a transaction request sending page, and the user may finally enter the transaction request sending page through a jump between different pages.
S102: performing risk recognition on the customer behavior track by applying a pre-constructed risk recognition model corresponding to the user identification to obtain a risk recognition result of the customer behavior track;
according to the method provided by the embodiment of the invention, the user identification can be a user name or an account number and the like.
Optionally, after obtaining the risk identification result of the customer behavior trajectory, it may be determined whether the risk identification result of the customer behavior characterizes whether a risk exists in the customer behavior trajectory.
In a feasible manner, the risk identification result may be a risk probability value, and in a case that the risk probability value of the risk identification result is greater than a set risk threshold, it is determined that the risk identification result represents that a risk exists in the client behavior track, otherwise, no risk exists.
The risk recognition model is obtained by training according to the historical customer behavior track of the user corresponding to the user identifier, and if the customer behavior track has risks, the characteristics of the customer behavior track and the characteristics of the historical behavior track of the user have larger deviation, that is, the user to be verified has larger possibility that the user is not the user corresponding to the user identifier.
S103: and executing the transaction operation corresponding to the transaction request under the condition that the risk identification result represents that the customer behavior trace has no risk.
In the method provided by the embodiment of the present invention, the transaction request includes a transaction operation type and transaction information, the transaction operation corresponding to the transaction operation type may be executed based on the transaction information, the transaction information may include a target execution object and a resource quantity, the target execution object may be a resource sending object or a resource receiving object, and the resource quantity may be a cash amount, a financial product quantity, and the like.
Wherein the transaction operation type may be a resource transfer type, such as a cash transfer, a redemption of a financial product, etc.
By applying the method provided by the embodiment of the invention, the risk identification is carried out on the client behavior track of the user to be verified through the risk identification model corresponding to the user identification, and the transaction request operation is executed under the condition that the risk identification result represents that the client behavior has no risk, so that the transaction risk caused by the leakage of the user name and the password of the user can be avoided, and the property safety of the user can be effectively guaranteed.
In the method provided in the embodiment of the present invention, based on the above-mentioned scheme, specifically, the process of performing risk recognition on the customer behavior trajectory by using a risk recognition model which is pre-constructed and corresponds to the user identifier to obtain a risk recognition result of the customer behavior trajectory specifically includes, as shown in fig. 2:
s201: and acquiring a pre-constructed risk identification model corresponding to the user identification.
The user identifier may be matched with the risk identification model set, and the candidate risk identification model successfully matched with the user identifier in the risk identification model set is used as the risk identification model corresponding to the user identifier.
S202: and preprocessing the client behavior track to obtain input parameters matched with the input format of the risk identification model.
In the embodiment of the invention, missing value processing can be carried out on the client track behavior track, and the client track subjected to the missing value processing is vectorized to obtain the input parameters matched with the input format of the risk identification model.
S203: and inputting the input parameters into the risk identification model to obtain a risk identification result of the customer behavior track output by the risk identification model.
Wherein the risk identification model may be a multi-layered deep neural network.
In the method provided in the embodiment of the present invention, based on the above scheme, specifically, the construction process of the risk identification model, as shown in fig. 3, specifically includes:
s301: obtaining a training sample set, wherein the training sample set comprises a plurality of historical customer behavior tracks of a user corresponding to the user identification; each historical customer behavior track comprises an operation path adopted by the user to send each historical transaction request and operation information generated by the user in the operation path; the operation path comprises page information of each page visited by the user;
according to the method provided by the embodiment of the invention, the historical customer behavior track can be obtained by the user in the process of sending the transaction request.
Wherein the training sample set further comprises historical customer behavior traces of other users.
S302: and training the risk recognition model by applying the training sample set.
In the embodiment of the invention, the risk identification model can be trained through each historical behavior track in the training sample set, so that the risk identification model with the capability of identifying whether the behavior track of the user is the behavior track of the user corresponding to the user identifier is obtained.
Referring to fig. 4, a flowchart of another method of a transaction data processing method according to an embodiment of the present invention includes the following steps:
s401: when a transaction request sent by a user to be verified is received, a customer behavior track and a user identifier contained in the transaction request are obtained; the customer behavior track comprises an operation path adopted by the user to be verified to send the transaction request and operation information generated by the user to be verified in the operation path; the operation path comprises page information of each page visited by the user to be verified.
The execution process and the execution principle of S401 and S101 are the same, and are not described herein again.
S402: and performing risk identification on the client behavior track by applying a pre-constructed risk identification model corresponding to the user identification to obtain a risk identification result of the client behavior track.
The execution process and the execution principle of S402 and S102 are the same, and are not described herein again.
S403: and executing the transaction operation corresponding to the transaction request under the condition that the risk identification result represents that the customer behavior trace has no risk.
The execution process and the execution principle of S403 and S103 are the same, and are not described herein again.
S404: and under the condition that the risk identification result represents that the client behavior track has risks, acquiring the face image of the user to be verified.
In the embodiment of the invention, the face image of the user to be verified can be acquired through the set camera equipment.
S405: and identifying the face image by using a preset face identification model to obtain an identification result of the face image.
Under the condition that the client behavior track has risks, the face recognition is carried out on the user to be verified, and the asset safety of the user can be further guaranteed.
S406: and if the identification result represents that the user to be verified is the user corresponding to the user identification, executing the transaction operation corresponding to the transaction request.
S407: and if the identification result represents that the user to be verified is not the user corresponding to the user identification, rejecting the transaction request.
The embodiment of the invention can be applied to various fields, for example, transaction data processing of bank users can be applied, specifically, when the bank users have transfer demands, the bank users can send transaction requests through mobile banking application programs, the users usually have own behavior habits during transfer, for example, the users firstly confirm information through chat apps or telephones, open mobile banking and inquire balance and then transfer accounts, and have certain rules on element entry, so the identity of the users can be verified according to the behavior habits of the users, which is specifically as follows:
collecting the customer behavior track of the transfer operation of the user to be checked, namely collecting the application name of the user before opening the mobile phone bank, the login time consumed by entering the mobile phone bank, the menu list selected before opening the transfer interface, the input sequence during transfer, the input time consumed by each element and the like; and performing feature processing on the collected features, constructing a multilayer deep neural network, and performing continuous iterative optimization by using a back propagation algorithm to obtain a risk identification model.
When a mobile phone bank checks that a customer transfers money, whether the money transfer is operated by the customer is judged through a risk identification model, if the money transfer is possibly embezzled, a collection camera is used for collecting images of the customer, face identification is carried out, whether the person is the customer is judged, intelligent identity authentication is carried out through the non-inductive mode, and the transaction is refused after the non-person is confirmed.
Through a click path for a customer to enter a mobile phone bank for transferring money, behavior information such as dwell time, element input sequence and time of each page is collected, intelligent authentication is carried out after danger is identified, and the safety of the customer funds is guaranteed.
Corresponding to the method illustrated in fig. 1, an embodiment of the present invention further provides a transaction data processing apparatus, which is used for implementing the method illustrated in fig. 1 specifically, the transaction data processing apparatus provided in the embodiment of the present invention may be applied to an electronic device, and a schematic structural diagram of the transaction data processing apparatus is illustrated in fig. 5, and specifically includes:
the system comprises a receiving unit 501, a verification unit and a verification unit, wherein the receiving unit 501 is used for acquiring a customer behavior track and a user identifier contained in a transaction request when the transaction request sent by a user to be verified is received; the customer behavior track comprises an operation path adopted by the user to be verified to send the transaction request and operation information generated by the user to be verified in the operation path; the operation path comprises page information of each page visited by the user to be verified;
the identification unit 502 is configured to perform risk identification on the customer behavior trajectory by applying a risk identification model corresponding to the user identifier, which is constructed in advance, to obtain a risk identification result of the customer behavior trajectory;
the execution unit 503 is configured to execute the transaction operation corresponding to the transaction request when the risk identification result indicates that the customer behavior trace has no risk.
In an embodiment provided by the present invention, based on the above scheme, optionally, the transaction data processing apparatus further includes a face recognition unit, where the face recognition unit is configured to:
under the condition that the risk identification result represents that the client behavior track has risks, acquiring a face image of the user to be verified;
the face image is identified by applying a preset face identification model, and the identification result of the face image is obtained;
if the identification result represents that the user to be verified is the user corresponding to the user identification, executing the transaction operation corresponding to the transaction request;
and if the identification result represents that the user to be verified is not the user corresponding to the user identification, rejecting the transaction request.
In an embodiment provided by the present invention, based on the above scheme, optionally, the identification unit includes:
the obtaining subunit is configured to obtain a training sample set, where the training sample set includes a plurality of historical customer behavior tracks of a user corresponding to the user identifier; each historical customer behavior track comprises an operation path adopted by the user to send each historical transaction request and operation information generated by the user in the operation path; the operation path comprises page information of each page visited by the user;
and the training subunit is used for applying the training sample set to train the risk identification model.
In an embodiment provided by the present invention, based on the above scheme, optionally, the identification unit includes:
the first acquisition subunit is used for acquiring a pre-constructed risk identification model corresponding to the user identifier;
the preprocessing subunit is used for preprocessing the client behavior track to obtain an input parameter matched with the input format of the risk identification model;
and the identification subunit is used for inputting the input parameters into the risk identification model so as to obtain a risk identification result of the customer behavior track output by the risk identification model.
The specific principle and the implementation process of each unit and each module in the transaction data processing device disclosed in the embodiment of the present invention are the same as those of the transaction data processing method disclosed in the embodiment of the present invention, and reference may be made to corresponding parts in the transaction data processing method provided in the embodiment of the present invention, which are not described herein again.
The embodiment of the invention also provides a storage medium, which comprises a stored instruction, wherein when the instruction runs, the equipment where the storage medium is located is controlled to execute the transaction data processing method.
An electronic device is provided in an embodiment of the present invention, and the structural diagram of the electronic device is shown in fig. 6, which specifically includes a memory 601 and one or more instructions 602, where the one or more instructions 602 are stored in the memory 601 and configured to be executed by one or more processors 603 to perform the following operations on the one or more instructions 602:
when a transaction request sent by a user to be verified is received, a customer behavior track and a user identifier contained in the transaction request are obtained; the customer behavior track comprises an operation path adopted by the user to be verified to send the transaction request and operation information generated by the user to be verified in the operation path; the operation path comprises page information of each page visited by the user to be verified;
performing risk recognition on the customer behavior track by applying a pre-constructed risk recognition model corresponding to the user identification to obtain a risk recognition result of the customer behavior track;
and executing the transaction operation corresponding to the transaction request under the condition that the risk identification result represents that the customer behavior trace has no risk.
It should be noted that, in the present specification, the embodiments are all described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments may be referred to each other. For the device-like embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functions of the units may be implemented in the same software and/or hardware or in a plurality of software and/or hardware when implementing the invention.
From the above description of the embodiments, it is clear to those skilled in the art that the present invention can be implemented by software plus necessary general hardware platform. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which may be stored in a storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments or some parts of the embodiments.
The transaction data processing method provided by the invention is described in detail above, and the principle and the implementation mode of the invention are explained by applying specific examples, and the description of the above examples is only used for helping understanding the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A transaction data processing method, comprising:
when a transaction request sent by a user to be verified is received, a customer behavior track and a user identifier contained in the transaction request are obtained; the customer behavior track comprises an operation path adopted by the user to be verified to send the transaction request and operation information generated by the user to be verified in the operation path; the operation path comprises page information of each page visited by the user to be verified;
performing risk recognition on the customer behavior track by applying a pre-constructed risk recognition model corresponding to the user identification to obtain a risk recognition result of the customer behavior track;
and executing the transaction operation corresponding to the transaction request under the condition that the risk identification result represents that the customer behavior trace has no risk.
2. The method of claim 1, wherein the applying a pre-constructed risk recognition model corresponding to the user identifier to perform risk recognition on the customer behavior track to obtain a risk recognition result of the customer behavior track comprises:
acquiring a pre-constructed risk identification model corresponding to the user identification;
preprocessing the client behavior track to obtain input parameters matched with the input format of the risk identification model;
and inputting the input parameters into the risk identification model to obtain a risk identification result of the customer behavior track output by the risk identification model.
3. The method of claim 1, wherein the risk identification model building process comprises:
obtaining a training sample set, wherein the training sample set comprises a plurality of historical customer behavior tracks of a user corresponding to the user identification; each historical customer behavior track comprises an operation path adopted by the user to send each historical transaction request and operation information generated by the user in the operation path; the operation path comprises each page visited by the user;
and training the risk recognition model by applying the training sample set.
4. The method according to claim 1, wherein the operation information includes page operation information of the user to be verified on each page, and each page operation information includes at least one of: page dwell time, element input order, element input time.
5. The method of claim 1, further comprising:
under the condition that the risk identification result represents that the client behavior track has risks, acquiring a face image of the user to be verified;
the face image is identified by applying a preset face identification model, and the identification result of the face image is obtained;
if the identification result represents that the user to be verified is the user corresponding to the user identification, executing the transaction operation corresponding to the transaction request;
and if the identification result represents that the user to be verified is not the user corresponding to the user identification, rejecting the transaction request.
6. A transaction data processing apparatus, comprising:
the system comprises a receiving unit, a verification unit and a verification unit, wherein the receiving unit is used for acquiring a client behavior track and a user identifier contained in a transaction request when the transaction request sent by a user to be verified is received; the customer behavior track comprises an operation path adopted by the user to be verified to send the transaction request and operation information generated by the user to be verified in the operation path; the operation path comprises page information of each page visited by the user to be verified;
the identification unit is used for carrying out risk identification on the customer behavior track by applying a pre-constructed risk identification model corresponding to the user identification to obtain a risk identification result of the customer behavior track;
and the execution unit is used for executing the transaction operation corresponding to the transaction request under the condition that the risk identification result represents that the customer behavior track has no risk.
7. The apparatus of claim 6, wherein the identification unit comprises:
the obtaining subunit is configured to obtain a training sample set, where the training sample set includes a plurality of historical customer behavior tracks of a user corresponding to the user identifier; each historical customer behavior track comprises an operation path adopted by the user to send each historical transaction request and operation information generated by the user in the operation path; the operation path comprises page information of each page visited by the user;
and the training subunit is used for applying the training sample set to train the risk identification model.
8. The apparatus of claim 6, further comprising a face recognition unit configured to:
under the condition that the risk identification result represents that the client behavior track has risks, acquiring a face image of the user to be verified;
the face image is identified by applying a preset face identification model, and the identification result of the face image is obtained;
if the identification result represents that the user to be verified is the user corresponding to the user identification, executing the transaction operation corresponding to the transaction request;
and if the identification result represents that the user to be verified is not the user corresponding to the user identification, rejecting the transaction request.
9. A storage medium, comprising stored instructions, wherein the instructions, when executed, control a device on which the storage medium is located to perform the transaction data processing method according to any one of claims 1 to 5.
10. An electronic device comprising a memory, and one or more instructions, wherein the one or more instructions are stored in the memory and configured to be executed by the one or more processors to perform the method of processing transaction data according to any one of claims 1-5.
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| CN202110486435.1A CN113159788A (en) | 2021-04-30 | 2021-04-30 | Transaction data processing method and device, storage medium and electronic equipment |
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