CN117035794A - Analysis method and system for illegal funds transfer risk transaction - Google Patents
Analysis method and system for illegal funds transfer risk transaction Download PDFInfo
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Abstract
The application discloses a method and a system for analyzing illegal funds transfer risk transaction, which relate to the technical field of big data, wherein the system comprises the following steps: the data calling module is used for calling the client background information and the historical risk transaction data of the client corresponding to the client identifier according to the client identifier in the risk transaction data to be analyzed; the risk transaction data to be analyzed is monitored by an illegal funds transfer transaction monitoring model; the data analysis module is used for analyzing the risk transaction data to be analyzed, the client background information and the historical risk transaction data and determining illegal funds transfer risk information of the risk transaction data to be analyzed; and the report generation module is used for generating an illegal funds transfer risk report of the risk transaction data to be analyzed according to the illegal funds transfer risk information of the risk transaction data to be analyzed. The application can solve the problems of complex data acquisition process, low analysis efficiency, low analysis result accuracy and the like in the existing analysis method of illegal funds transfer risk transaction.
Description
Technical Field
The application relates to the technical field of big data, in particular to an analysis method and an analysis system for illegal funds transfer risk transaction.
Background
This section is intended to provide a background or context to the embodiments of the application that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.
During risk transaction monitoring of illegal funds transfer, an early warning case (transaction with illegal funds transfer risk) generated by an illegal funds transfer transaction monitoring model needs to be manually analyzed. Based on current regulatory requirements, detailed analysis information is required to support conclusions, whether or not the transaction is ultimately considered a risk transaction; meanwhile, as the requirements and standards of the risk transaction report are continuously improved by the supervision department, a great amount of analysis activities need to be carried out by the analyst every day to verify the risk degree of cases, etc., therefore, the analysis of the existing illegal funds transfer risk transaction relies on manually calling the relevant data of the clients for analysis, and the method mainly has the following problems:
1. because risk transaction analysis needs to be combined with various data for analysis, but client data is not centralized enough, multi-party acquisition is needed, the data integration degree is low, and the acquisition process is complex;
2. the analyst needs to collect, calculate and compare a large amount of data, judge the data by combining with a service scene, and write a suspicious analysis report with great effort, so that the analysis efficiency is low;
3. the analysis personnel are affected by subjective ideas during analysis, and the accuracy of analysis results is low.
In summary, the existing analysis method for illegal funds transfer risk transaction has the problems of complex data acquisition process, low analysis efficiency, low analysis result accuracy and the like.
Disclosure of Invention
The embodiment of the application provides an analysis method for illegal funds transfer risk transaction, which is used for solving the problems of complex data acquisition process, low analysis efficiency, low analysis result accuracy and the like in the existing analysis method for illegal funds transfer risk transaction, and comprises the following steps:
according to the client identification in the risk transaction data to be analyzed, client background information and historical risk transaction data of a client corresponding to the client identification are called; the risk transaction data to be analyzed is monitored by an illegal funds transfer transaction monitoring model;
analyzing risk transaction data to be analyzed, customer background information and historical risk transaction data, and determining illegal funds transfer risk information of the risk transaction data to be analyzed;
and generating an illegal funds transfer risk report of the risk transaction data to be analyzed according to the illegal funds transfer risk information of the risk transaction data to be analyzed.
The embodiment of the application also provides an analysis system for illegal funds transfer risk transaction, which is used for solving the problems of complex data acquisition process, low analysis efficiency, low analysis result accuracy and the like in the existing analysis method for illegal funds transfer risk transaction, and comprises the following steps:
the data calling module is used for calling the client background information and the historical risk transaction data of the client corresponding to the client identifier according to the client identifier in the risk transaction data to be analyzed; the risk transaction data to be analyzed is monitored by an illegal funds transfer transaction monitoring model;
the data analysis module is used for analyzing the risk transaction data to be analyzed, the client background information and the historical risk transaction data and determining illegal funds transfer risk information of the risk transaction data to be analyzed;
and the report generation module is used for generating an illegal funds transfer risk report of the risk transaction data to be analyzed according to the illegal funds transfer risk information of the risk transaction data to be analyzed.
The embodiment of the application also provides computer equipment, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the analysis method of illegal funds transfer risk transaction when executing the computer program.
The embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program realizes the analysis method of illegal funds transfer risk transaction when being executed by a processor.
The embodiment of the application also provides a computer program product, which comprises a computer program, wherein the computer program is executed by a processor to realize the analysis method of illegal funds transfer risk transaction.
According to the embodiment of the application, according to the client identification in the risk transaction data to be analyzed, client background information and historical risk transaction data of a client corresponding to the client identification are called; the risk transaction data to be analyzed is monitored by an illegal funds transfer transaction monitoring model; analyzing risk transaction data to be analyzed, customer background information and historical risk transaction data, and determining illegal funds transfer risk information of the risk transaction data to be analyzed; and generating an illegal funds transfer risk report of the risk transaction data to be analyzed according to the illegal funds transfer risk information of the risk transaction data to be analyzed. Compared with the existing analysis method of illegal funds transfer risk transaction, the method has the advantages that customer background information and historical risk transaction data of customers corresponding to the customer identification can be directly called through the customer identification in the risk transaction data to be analyzed, then analysis is carried out on the risk transaction data to be analyzed, the customer background information and the historical risk transaction data to be analyzed, illegal funds transfer risk information of the risk transaction data to be analyzed is determined, an illegal funds transfer risk report of the risk transaction data to be analyzed is generated according to the illegal funds transfer risk information, time cost of data acquisition, data processing and report generation in the analysis process of the illegal funds transfer risk transaction can be saved on a large scale, and analysis efficiency and accuracy of the illegal funds transfer risk transaction are improved.
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In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. In the drawings:
FIG. 1 is a schematic diagram of an analysis system for illegal funds-transfer risk transaction according to an embodiment of the application;
FIG. 2 is a schematic diagram of a data analysis module according to an embodiment of the present application;
FIG. 3 is a flow chart of a method of analyzing an illegal funds-transfer risk transaction according to an embodiment of the present application;
FIG. 4 is a flow chart of a method for analyzing risk transaction data to be analyzed, customer background information and historical risk transaction data to determine illegal funds transfer risk information of the risk transaction data to be analyzed according to an embodiment of the application;
fig. 5 is a schematic diagram of a computer device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the embodiments of the present application will be described in further detail with reference to the accompanying drawings. The exemplary embodiments of the present application and their descriptions herein are for the purpose of explaining the present application, but are not to be construed as limiting the application.
In the description of the present specification, the terms "comprising," "including," "having," "containing," and the like are open-ended terms, meaning including, but not limited to. The description of the reference terms "one embodiment," "a particular embodiment," "some embodiments," "for example," etc., means that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. The order of steps involved in the embodiments is illustrative of the practice of the application, and is not limited and may be suitably modified as desired.
In order to solve the problems of complex data acquisition process, low analysis efficiency, low analysis result accuracy and the like in the existing analysis scheme of illegal funds transfer risk transaction, the embodiment of the application provides an analysis system of illegal funds transfer risk transaction, and the whole analysis flow of illegal funds transfer risk transaction can be put into the analysis system of illegal funds transfer risk transaction to be circulated in a closed manner, so that the time cost of each link of data acquisition, data analysis, report generation and the like in the analysis process is saved on a large scale, and the analysis efficiency and accuracy of illegal funds transfer risk transaction are obviously improved.
The technical scheme of the application obtains, stores, uses, processes and the like the data, which all meet the relevant regulations of national laws and regulations.
FIG. 1 is a schematic diagram of an analysis system for illegal funds-transfer risk transaction according to an embodiment of the application, as shown in FIG. 1, the analysis system may include:
the data calling module 01 is used for calling the client background information and the historical risk transaction data of the client corresponding to the client identifier according to the client identifier in the risk transaction data to be analyzed; the risk transaction data to be analyzed is monitored by an illegal funds transfer transaction monitoring model;
the data analysis module 02 is used for analyzing the risk transaction data to be analyzed, the client background information and the historical risk transaction data and determining illegal funds transfer risk information of the risk transaction data to be analyzed;
the report generating module 03 is configured to generate an illegal funds transfer risk report of the risk transaction data to be analyzed according to the illegal funds transfer risk information of the risk transaction data to be analyzed.
According to the embodiment of the application, through the analysis system of illegal funds transfer risk transaction, all data analyzed by the illegal funds transfer risk transaction can be circulated in the analysis system, so that the data leakage risk in the whole data transmission process is effectively reduced, and the complexity of data acquisition is reduced; meanwhile, various auxiliary data analysis methods are used for giving analysis personnel risk transaction data identification basis, so that the analysis efficiency and the accuracy of analysis results are improved.
In specific implementation, when receiving risk transaction data to be analyzed issued by the illegal funds transfer transaction monitoring model, the data calling module 01 can directly call client background information and historical risk transaction data of a client corresponding to the client identifier according to the client identifier in the risk transaction data to be analyzed.
In one embodiment, the customer context information may include customer identity information, customer occupation information, customer family information, and account information.
The historical risk transaction data may refer to historical risk transaction data issued by an illegal funds transfer transaction monitoring model.
For example, the customer identity information may be a customer name, identity document type, document number, customer number, etc.; the customer occupation information may be a type of occupation, a name of a unit, an address of a unit, etc.; customer home information may be a home address, etc.; the account information may be a customer's bank card number or the like.
Therefore, the data calling module can directly call the client background information and the historical risk transaction data of the client corresponding to the client identifier, so that the work of inquiring the mechanical filling of workers item by item is avoided, the analysis time of illegal funds transfer risk transaction is saved, and the analysis efficiency is improved.
In specific implementation, the data analysis module 02 may be configured to analyze the customer background information and the historical risk transaction data acquired by the data retrieval module, and the risk transaction data to be analyzed, so as to determine illegal funds transfer risk information of the risk transaction data to be analyzed.
In one embodiment, as shown in fig. 2, the data analysis module 02 may include:
the transaction detail analysis unit 021 is used for analyzing historical risk transaction data and determining risk transaction characteristic data of a client;
a customer representation analysis unit 022 for analyzing the customer background information and the risk transaction characteristic data to determine customer representation information;
the relationship link analysis unit 023 is used for analyzing the relationship link of the client according to the historical risk transaction data and determining the association relationship risk data of the client; the association risk data comprises at least one of funds link risk data, trade opponent risk data, benefit owner risk data, associated natural person risk data and associated non-natural person risk data;
the risk probability analysis unit 024 is used for inputting the risk transaction data to be analyzed into a pre-trained risk probability analysis model to determine risk probability information of the risk transaction data to be analyzed; the risk probability analysis is obtained by training a logistic regression model by utilizing historical transaction data of a plurality of clients;
and the information synthesis unit 025 is used for combining the customer portrait information, the customer transaction characteristic data, the association relation risk data of the customers and the risk probability information of the risk transaction data to be analyzed as illegal funds transfer risk information of the risk transaction data to be analyzed.
In particular, the transaction detail analysis unit 021 is used for analyzing the historical transaction detail of the customer, so as to identify the risk transaction characteristic data of the customer. For example, the risk transaction characteristic data may include characteristic data of a customer's transaction frequency, transaction amount, transaction counter-party, transaction IP address, transaction channel, and the like.
In particular, the customer representation analysis unit 022 is configured to analyze customer background information and risk transaction characteristic data to determine customer representation information. For example, the customer portrait information may include customer identity information, account information, primary transaction information, and the like.
In specific implementation, the relationship link analysis unit 023 may analyze the relationship link of the client according to the historical risk transaction data to obtain the association relationship risk data of the client. The associative relationship risk data may include at least one of funds link risk data, trade opponent risk data, benefit owner risk data, associated natural person risk data, and associated non-natural person risk data.
In specific implementation, the risk probability analysis unit 024 utilizes a logistic regression model to quantitatively analyze the risk transaction data. Specifically, historical transaction risk data of a plurality of clients within a preset time period (such as the last three years) and corresponding risk analysis results (with risk or without risk) can be obtained from an illegal funds transfer transaction monitoring model, a logistic regression model is trained, and the correlation coefficient of the logistic regression model is determined to obtain a risk probability analysis model. Then, the risk transaction data to be analyzed can be input into a risk probability analysis model, and the model outputs risk probability information of the risk transaction data to be analyzed.
In one embodiment, the data analysis module 02 may further include:
the risk probability analysis unit is used for inputting the risk transaction data to be analyzed into a pre-trained risk probability analysis model, and extracting risk index data of the risk transaction data to be analyzed according to a preset risk monitoring index before determining risk probability information of the risk transaction data to be analyzed;
the risk probability analysis unit may specifically be configured to:
and inputting the risk index data of the risk transaction data to be analyzed into a pre-trained risk probability analysis model, and determining risk probability information of the risk transaction data to be analyzed.
In the specific implementation, a plurality of risk monitoring indexes can be constructed to describe the risk degree of the client transaction according to the aspects of transaction amount, transaction times, transaction time, IP addresses, transaction channels and the like according to related research and industry experience, then risk index data of risk transaction data to be analyzed are extracted, a risk probability analysis model is input, and risk probability information of the risk transaction data to be analyzed is determined.
Specifically, the logistic regression model may be expressed by the following formula:
wherein p=0 means "is a risk transaction"; 0 means "not a risk transaction"; x is X i Is an independent variable, represents the ith risk index data,as a dependent variable ++>Is'And determining the probability ratio of risk ' to ' excluding risk ', wherein alpha and beta are coefficients of a risk probability analysis model obtained by fitting historical risk transaction data of a plurality of clients.
In this way, the risk transaction data to be analyzed is analyzed through the logistic regression model, so that the risk probability that the risk transaction data to be analyzed is illegal funds transfer is obtained, the judgment of the risk degree of illegal funds transfer risk transaction is facilitated, the influence of subjective ideas is avoided, and the accuracy of risk analysis is improved.
In a specific implementation, the information integration unit 025 is configured to combine the customer portrait information, the customer transaction feature data, the association relationship risk data of the customer, and the risk probability information of the risk transaction data to be analyzed, which are obtained by the analysis units, as illegal funds transfer risk information of the risk transaction data to be analyzed.
It should be noted that, the data analysis module may also develop a visual information analysis unit according to the requirement of risk analysis, such as time sequence analysis, activity track analysis, and the like.
In implementation, the report generating module 03 may generate an illegal funds transfer risk report of the risk transaction data to be analyzed according to the illegal funds transfer risk information of the risk transaction data to be analyzed. The illegal funds-transfer risk report may include: customer portraits, customer associations, risk probabilities, and the like.
In one embodiment, the report generating module 03 may be specifically configured to:
and formatting illegal funds transfer risk information of the risk transaction data to be analyzed according to a preset report template to generate an illegal funds transfer transaction risk report of the client.
In the implementation, a report template can be set according to the requirement of a supervision organization, a data format and a typesetting style are specified in the report template, the format of illegal funds transfer risk information of risk transaction data to be analyzed can be converted into the data format specified by the report template, and an illegal funds transfer risk report is generated according to the typesetting style specified by the report template.
Therefore, the demands of different users on illegal funds transfer risk report texts can be met, and the quality and efficiency of illegal funds transfer risk report generation are improved.
The embodiment of the application also provides an analysis method of illegal funds transfer risk transaction, as described in the following embodiment. Because the principle of the method for solving the problem is similar to that of the analysis system of the illegal funds transfer risk transaction, the implementation of the method can refer to the implementation of the analysis system of the illegal funds transfer risk transaction, and the repetition is omitted.
Fig. 3 is a flow chart of an analysis method of illegal funds transfer risk transaction according to an embodiment of the present application, the method is applied to the analysis system of illegal funds transfer risk transaction, as shown in fig. 3, and the method includes the following steps:
step 301, according to a client identifier in risk transaction data to be analyzed, client background information and historical risk transaction data of a client corresponding to the client identifier are called; the risk transaction data to be analyzed is monitored by an illegal funds transfer transaction monitoring model;
step 302, analyzing risk transaction data to be analyzed, customer background information and historical risk transaction data, and determining illegal funds transfer risk information of the risk transaction data to be analyzed;
step 303, generating an illegal funds transfer risk report of the risk transaction data to be analyzed according to the illegal funds transfer risk information of the risk transaction data to be analyzed.
According to the embodiment of the application, according to the client identification in the risk transaction data to be analyzed, client background information and historical risk transaction data of a client corresponding to the client identification are called; the risk transaction data to be analyzed is monitored by an illegal funds transfer transaction monitoring model; analyzing risk transaction data to be analyzed, customer background information and historical risk transaction data, and determining illegal funds transfer risk information of the risk transaction data to be analyzed; and generating an illegal funds transfer risk report of the risk transaction data to be analyzed according to the illegal funds transfer risk information of the risk transaction data to be analyzed. Compared with the existing analysis method of illegal funds transfer risk transaction, the method has the advantages that customer background information and historical risk transaction data of customers corresponding to the customer identification can be directly called through the customer identification in the risk transaction data to be analyzed, then analysis is carried out on the risk transaction data to be analyzed, the customer background information and the historical risk transaction data to be analyzed, illegal funds transfer risk information of the risk transaction data to be analyzed is determined, an illegal funds transfer risk report of the risk transaction data to be analyzed is generated according to the illegal funds transfer risk information, time cost of data acquisition, data processing and report generation in the analysis process of the illegal funds transfer risk transaction can be saved on a large scale, and analysis efficiency and accuracy of the illegal funds transfer risk transaction are improved.
In one embodiment, the customer context information may include customer identity information, customer occupation information, customer family information, and account information.
In one embodiment, as shown in fig. 4, the step 302 may specifically include:
step 401, analyzing historical risk transaction data to determine risk transaction characteristic data of clients;
step 402, analyzing the customer background information and the risk transaction characteristic data to determine customer portrait information;
step 403, analyzing the relationship link of the client according to the historical risk transaction data to determine the association relationship risk data of the client; the association risk data comprises at least one of funds link risk data, trade opponent risk data, benefit owner risk data, associated natural person risk data and associated non-natural person risk data;
step 404, inputting risk transaction data to be analyzed into a pre-trained risk probability analysis model, and determining risk probability information of the risk transaction data to be analyzed; the risk probability analysis is obtained by training a logistic regression model by utilizing historical transaction data of a plurality of clients;
and step 405, combining the customer portrait information, the customer transaction characteristic data, the association relationship risk data of the customers and the risk probability information of the risk transaction data to be analyzed as illegal funds transfer risk information of the risk transaction data to be analyzed.
In one embodiment, before the step 404, the method may further include:
extracting risk index data of risk transaction data to be analyzed according to preset risk monitoring indexes;
the step 404 may specifically include:
and inputting the risk index data of the risk transaction data to be analyzed into a pre-trained risk probability analysis model, and determining risk probability information of the risk transaction data to be analyzed.
In one embodiment, the step 303 may specifically include:
and formatting illegal funds transfer risk information of the risk transaction data to be analyzed according to a preset report template to generate an illegal funds transfer transaction risk report of the client.
An embodiment of the present application further provides a computer device, and fig. 5 is a schematic diagram of the computer device in the embodiment of the present application, where the computer device 500 includes a memory 510, a processor 520, and a computer program 530 stored in the memory 510 and capable of running on the processor 520, and the processor 520 implements the method for analyzing illegal funds transfer risk transaction when executing the computer program 530.
The embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program realizes the analysis method of illegal funds transfer risk transaction when being executed by a processor.
The embodiment of the application also provides a computer program product, which comprises a computer program, wherein the computer program is executed by a processor to realize the analysis method of illegal funds transfer risk transaction.
According to the embodiment of the application, according to the client identification in the risk transaction data to be analyzed, client background information and historical risk transaction data of a client corresponding to the client identification are called; the risk transaction data to be analyzed is monitored by an illegal funds transfer transaction monitoring model; analyzing risk transaction data to be analyzed, customer background information and historical risk transaction data, and determining illegal funds transfer risk information of the risk transaction data to be analyzed; and generating an illegal funds transfer risk report of the risk transaction data to be analyzed according to the illegal funds transfer risk information of the risk transaction data to be analyzed. Compared with the existing analysis method of illegal funds transfer risk transaction, the method has the advantages that customer background information and historical risk transaction data of customers corresponding to the customer identification can be directly called through the customer identification in the risk transaction data to be analyzed, then analysis is carried out on the risk transaction data to be analyzed, the customer background information and the historical risk transaction data to be analyzed, illegal funds transfer risk information of the risk transaction data to be analyzed is determined, an illegal funds transfer risk report of the risk transaction data to be analyzed is generated according to the illegal funds transfer risk information, time cost of data acquisition, data processing and report generation in the analysis process of the illegal funds transfer risk transaction can be saved on a large scale, and analysis efficiency and accuracy of the illegal funds transfer risk transaction are improved.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the application, and is not meant to limit the scope of the application, but to limit the application to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the application are intended to be included within the scope of the application.
Claims (13)
1. A method of analyzing an illegal funds-transfer risk transaction, comprising:
according to the client identification in the risk transaction data to be analyzed, client background information and historical risk transaction data of a client corresponding to the client identification are called; the risk transaction data to be analyzed is monitored by an illegal funds transfer transaction monitoring model;
analyzing risk transaction data to be analyzed, customer background information and historical risk transaction data, and determining illegal funds transfer risk information of the risk transaction data to be analyzed;
and generating an illegal funds transfer risk report of the risk transaction data to be analyzed according to the illegal funds transfer risk information of the risk transaction data to be analyzed.
2. The method of claim 1, wherein the customer context information includes customer identity information, customer occupation information, customer family information, and account information.
3. The method of claim 1, wherein analyzing risk transaction data to be analyzed, customer background information, and historical risk transaction data to determine illegal funds transfer risk information for the risk transaction data to be analyzed comprises:
analyzing the historical risk transaction data to determine risk transaction characteristic data of the clients;
analyzing the customer background information and the risk transaction characteristic data to determine customer portrait information;
analyzing a relation link of the client according to the historical risk transaction data to determine association relation risk data of the client; the association risk data comprises at least one of funds link risk data, trade opponent risk data, benefit owner risk data, associated natural person risk data and associated non-natural person risk data;
inputting risk transaction data to be analyzed into a pre-trained risk probability analysis model, and determining risk probability information of the risk transaction data to be analyzed; the risk probability analysis is obtained by training a logistic regression model by utilizing historical transaction data of a plurality of clients;
and combining the customer portrait information, the customer transaction characteristic data, the association relationship risk data of the customers and the risk probability information of the risk transaction data to be analyzed to serve as illegal funds transfer risk information of the risk transaction data to be analyzed.
4. The method of claim 3, wherein inputting the risk transaction data to be analyzed into a pre-trained risk probability analysis model, prior to determining risk probability information for the risk transaction data to be analyzed, further comprises:
extracting risk index data of risk transaction data to be analyzed according to preset risk monitoring indexes;
inputting risk transaction data to be analyzed into a pre-trained risk probability analysis model, and determining risk probability information of the risk transaction data to be analyzed, wherein the risk probability information comprises:
and inputting the risk index data of the risk transaction data to be analyzed into a pre-trained risk probability analysis model, and determining risk probability information of the risk transaction data to be analyzed.
5. The method of claim 1, wherein generating an illegal funds transfer risk report of the risk transaction data to be analyzed based on the illegal funds transfer risk information of the risk transaction data to be analyzed comprises:
and formatting illegal funds transfer risk information of the risk transaction data to be analyzed according to a preset report template to generate an illegal funds transfer transaction risk report of the client.
6. An analysis system for illegal funds-transfer risk transactions, comprising:
the data calling module is used for calling the client background information and the historical risk transaction data of the client corresponding to the client identifier according to the client identifier in the risk transaction data to be analyzed; the risk transaction data to be analyzed is monitored by an illegal funds transfer transaction monitoring model;
the data analysis module is used for analyzing the risk transaction data to be analyzed, the client background information and the historical risk transaction data and determining illegal funds transfer risk information of the risk transaction data to be analyzed;
and the report generation module is used for generating an illegal funds transfer risk report of the risk transaction data to be analyzed according to the illegal funds transfer risk information of the risk transaction data to be analyzed.
7. The system of claim 6, wherein the customer context information includes customer identity information, customer occupation information, customer family information, and account information.
8. The system of claim 6, wherein the data analysis module comprises:
the transaction detail analysis unit is used for analyzing the historical risk transaction data and determining risk transaction characteristic data of the clients;
the customer portrait analysis unit is used for analyzing the customer background information and the risk transaction characteristic data and determining customer portrait information;
the relationship link analysis unit is used for analyzing the relationship link of the client according to the historical risk transaction data and determining the association relationship risk data of the client; the association risk data comprises at least one of funds link risk data, trade opponent risk data, benefit owner risk data, associated natural person risk data and associated non-natural person risk data;
the risk probability analysis unit is used for inputting the risk transaction data to be analyzed into a pre-trained risk probability analysis model and determining risk probability information of the risk transaction data to be analyzed; the risk probability analysis is obtained by training a logistic regression model by utilizing historical risk transaction data of a plurality of clients;
and the information synthesis unit is used for combining the customer portrait information, the customer transaction characteristic data, the association relation risk data of the customers and the risk probability information of the risk transaction data to be analyzed to serve as illegal funds transfer risk information of the risk transaction data to be analyzed.
9. The system of claim 8, wherein the data analysis module further comprises:
the risk probability analysis unit is used for inputting the risk transaction data to be analyzed into a pre-trained risk probability analysis model, and extracting risk index data of the risk transaction data to be analyzed according to a preset risk monitoring index before determining risk probability information of the risk transaction data to be analyzed;
the risk probability analysis unit is specifically configured to:
and inputting the risk index data of the risk transaction data to be analyzed into a pre-trained risk probability analysis model, and determining risk probability information of the risk transaction data to be analyzed.
10. The system of claim 6, wherein the report generation module is specifically configured to:
and formatting illegal funds transfer risk information of the risk transaction data to be analyzed according to a preset report template to generate an illegal funds transfer transaction risk report of the client.
11. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of any of claims 1 to 5 when executing the computer program.
12. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, implements the method of any of claims 1 to 5.
13. A computer program product, characterized in that the computer program product comprises a computer program which, when executed by a processor, implements the method of any of claims 1 to 5.
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| CN202311184686.XA CN117035794A (en) | 2023-09-14 | 2023-09-14 | Analysis method and system for illegal funds transfer risk transaction |
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| CN202311184686.XA CN117035794A (en) | 2023-09-14 | 2023-09-14 | Analysis method and system for illegal funds transfer risk transaction |
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