Method and system for preventing telecommunication fraud

Abstract

The invention discloses a method and a system for preventing telecommunication fraud. The system comprises an anti-fraud control center module, a first cooperation end, a second cooperation end and a third cooperation end, the first cooperation end, the second cooperation end and the third cooperation end are all connected with the anti-fraud control center module through the Internet or a special line, and the anti-fraud control center module is used for receiving and processing information of the first cooperation end, the second cooperation end and the third cooperation end and sending a processing result to the related cooperation ends for processing; through interconnection and information sharing among the first cooperation end, the second cooperation end and the third cooperation end, on the basis of shared information judgment, judgment of transfer risks can be realized, transfer reminding with different measures is carried out on the first cooperation end, the second cooperation end and the third cooperation end, so that the transfer security is improved, and meanwhile, under the state of information sharing, the transfer risk of the first cooperation end, the second cooperation end and the third cooperation end is improved. The method can achieve the judgment of the transfer risk in an extremely short time, can avoid the delay of normal transfer, and guarantees the service effect.

Description

Technical Field

[0001] The present invention relates to the technical field of telecommunication network security, and in particular to a method and system for preventing telecommunication fraud. Background Art

[0002] The country has invested a lot of police and financial resources in anti-telecom fraud, but telecom fraud cases are still rampant. The main reason is that telecom operators, commercial banks, Internet companies, public security departments and other departments have not shared information in real time, which has led to telecom fraud not being stopped in time at the source. At present, telecom operators, banks and Internet companies have implemented a real-name system for users, which provides a good foundation for preventing telecom fraud.

[0003] At present, the electronic transfer function has brought unprecedented convenience and speed to people's lives, but at the same time, it has also derived new criminal activities using related technological means. For example, the common SMS fraud in recent years has caused serious harassment or economic losses to the people, which is disgusting. For the public security department, SMS fraud has the characteristics of a wide range of sites, fast fund transfer, and difficulty in obtaining evidence. The ideal way to stop the crime is to notify the bank that opened the suspected account as soon as the fraud is reported, and the bank will freeze the suspected account as soon as possible. However, for modern commercial banks that attach importance to customer service, account monitoring, freezing, and return are highly sensitive business operations, involving many other aspects of funds and business risks, and must be operated with caution. Therefore, according to bank business regulations, sufficient judgment information and legally effective judicial notices must be provided.

[0004] At present, the main measures to prevent telecommunications fraud are:

[0005] 1) Telecom operators have implemented strict management on voice relay lines and the sending of junk text messages, which has led to a significant decrease in telecom fraud calls and text messages;

[0006] 2) Banks should strengthen friendly reminders when rejecting Taiwan transfers, reminding the transferor of the relationship between the transferee and the transferee and the possible risks of telecommunications fraud;

[0007] 3) Internet companies will provide reminder services during the chat process of instant messaging tools. When bank card information appears in the chat content, they will remind the chatter of possible telecommunications fraud;

[0008] 4) When receiving a report, the public security department will immediately intervene in the investigation and detection of the case.

[0009] The main problems are: all major relevant units (public security, banks, telecommunications) have basically built mature computer national network information systems, and each system is fully capable of rapid and accurate information retrieval, but it is still the result of manual transmission of computer processing. For example, public security or judicial personnel can only go to the bank in person to present relevant judicial documents and communicate case investigation requirements, which has become a serious information bottleneck. Therefore, most cases will be delayed in the processing level, and it is impossible to deal with the electronic economic crimes under the new situation, and even the situation of "watching the money being transferred away" will occur.

[0010] Therefore, a method and system for preventing telecommunication fraud are proposed to solve the current deficiencies. Summary of the invention

[0011] The technical problem to be solved by the present invention is to overcome the defects of the above-mentioned technology and provide a method and system for preventing telecommunication fraud.

[0012] To solve the above technical problems, the technical solution provided by the present invention is a system for preventing telecommunication fraud, comprising an anti-fraud control center module, a first collaboration terminal deployed in a financial institution, a second collaboration terminal deployed in an operator, and a third collaboration terminal deployed in a social platform;

[0013] The first collaboration terminal, the second collaboration terminal and the third collaboration terminal are all connected to the anti-fraud control center module via the Internet or a dedicated line, and the anti-fraud control center module is used to receive information from the first collaboration terminal, the second collaboration terminal and the third collaboration terminal and process it, and send the processing results to the relevant collaboration terminals for processing;

[0014] As an improvement, the anti-fraud control center module includes a central processing module, a data collection module, a big data analysis module, a machine learning module, a shared database, a warning information feedback module, a user feedback module and an interception module;

[0015] The central processing module is used to receive and process the working information of the big data analysis module, the data collection module, the machine learning module, the shared database, the warning information feedback module, the user feedback module and the interception module, and send the processing results to the relevant modules for processing;

[0016] The data collection module is used to collect transaction data between the user and the transfer user at different first collaboration terminals and interaction data at different third collaboration terminals;

[0017] The big data analysis module is used to perform risk assessment and obtain risk levels based on the interaction data collected by the data collection module and the preset risk model, and feed back the risk level results to the central processing module so that the interception module can trigger the early warning information feedback module to perform corresponding processing strategies. At the same time, the interaction data and risk levels are transmitted to the shared database and can be called by the machine learning module;

[0018] The machine learning module is used for deep learning and assisting the big data analysis module to identify the characteristics of telecommunications fraud;

[0019] The shared database is used to store fraud information data transmitted by the big data analysis module, and to establish fraud warning information for bank card accounts and / or telephone numbers whose storage times exceed a certain threshold. At the same time, the data in the shared database can be called by the machine learning module to form a fraud model;

[0020] The interception module is used to trigger the early warning information feedback module to send early warning confirmation information to the transfer user;

[0021] The early warning information feedback module is used to take corresponding treatment measures according to the risk level evaluated by the big data analysis module;

[0022] The user feedback module is used for the transfer user to send warning confirmation information to the warning information feedback module to confirm whether to perform the transfer operation.

[0023] As an improvement, it also includes a multi-platform integration module, which can realize information interaction between the anti-fraud control center module and other platforms.

[0024] As an improvement, the data collection module further includes a feature extraction unit;

[0025] The feature extraction unit is used to extract features of interaction information between users at the first collaboration end and the third collaboration end, and the features include call duration, keywords, and social network behavior patterns.

[0026] As an improvement, the risk level includes a low risk level, a medium risk level and a high risk level;

[0027] The low risk level means that there is a connection between the first cooperation end and the third cooperation end between the transfer users and the characteristic information is safe;

[0028] The medium risk level means that there is a connection between the first cooperation end or the third cooperation end between the transfer users. If there is a connection between the third cooperation ends, its characteristic information is basically safe.

[0029] The high risk level means that there is no connection between the first cooperation end and the third cooperation end between the transfer users.

[0030] As an improvement, the warning information feedback module includes a text message reminder unit, an intelligent outbound call unit and a manual outbound call unit;

[0031] The SMS reminder unit is used to send a transfer warning confirmation SMS to the transfer user with a low risk level through the second cooperation terminal;

[0032] The outbound call-only unit is used to initiate an intelligent voice warning confirmation call to the transfer user with a medium risk level through the second cooperation terminal;

[0033] The manual outbound call unit is used to initiate a manual warning confirmation service call to the transfer user with a high risk level through the second cooperation terminal;

[0034] A method for preventing telecommunication fraud comprises the following steps:

[0035] S1. Deploy a first collaboration terminal at a financial institution, a second collaboration terminal at an operator, and a third collaboration terminal at a social platform, and connect them to the anti-fraud control center module via the Internet or a dedicated line.

[0036] S2: When the transfer user performs a transfer operation, the anti-fraud control center module collects transaction data between the user and the transfer user at different first collaborative terminals and interaction data at different third collaborative terminals, and performs risk level assessment;

[0037] S3: The anti-fraud control center module sends different early warning confirmation information to the transfer user through the second collaboration terminal according to the risk assessment level;

[0038] S4: The transfer user confirms whether to perform the transfer operation based on the warning confirmation information;

[0039] S5: The first collaboration end determines whether to perform the transfer operation according to the feedback information of the transfer user.

[0040] The advantages of the present invention compared with the prior art are:

[0041] 1. With the anti-fraud control center module as the center, the interconnection between the first collaboration end (bank), the second collaboration end (operator) and the third collaboration end (social platform) is realized, and the SMS notification, voice outbound call and other functions of the second collaboration end (operator) are integrated. The anti-fraud control center module is used to realize the sharing of information of each collaboration end, and the anti-fraud control center module determines the risk level of the shared information to determine the transfer process. At the same time, the transfer process is reminded and confirmed by SMS, voice and other means to avoid the occurrence of fraudulent transfers;

[0042] 2. By interconnecting and sharing information between the first collaborative end (bank), the second collaborative end (operator) and the third collaborative end (social platform), it is possible to determine the risk of transfer based on the judgment of their shared information, and to provide transfer reminders with different measures to improve the security of their transfers. At the same time, in the state of information sharing, the transfer risk can be determined in a very short time, which can avoid delays in normal transfers and ensure service effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic diagram of the architecture of a method and system for preventing telecommunication fraud according to the present invention.

[0044] Figure 2 It is a schematic diagram of the architecture of an anti-fraud control center module in a method and system for preventing telecommunication fraud of the present invention.

[0045] Figure 3 It is a schematic diagram of the architecture of a method for preventing telecommunication fraud and a warning information feedback module in the system of the present invention.

[0046] Figure 4 This is the information collection scope of the data collection module in the method for preventing telecommunication fraud and the system of the present invention. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solutions and advantages of the embodiments of the invention clearer, the technical solutions in the embodiments of the invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the invention. Obviously, the described embodiments are part of the embodiments of the invention, but the following embodiments do not limit the scope of protection of the invention.

[0048] Combined with Figure 1-4 As shown, a system for preventing telecommunication fraud includes an anti-fraud control center module, a first collaboration terminal deployed in a financial institution, a second collaboration terminal deployed in an operator, and a third collaboration terminal deployed in a social platform;

[0049] The first collaboration terminal, the second collaboration terminal and the third collaboration terminal are all connected to the anti-fraud control center module via the Internet or a dedicated line, and the anti-fraud control center module is used to receive information from the first collaboration terminal, the second collaboration terminal and the third collaboration terminal and process it, and send the processing results to the relevant collaboration terminals for processing;

[0050] As an improvement, the anti-fraud control center module includes a central processing module, a data collection module, a big data analysis module, a machine learning module, a shared database, a warning information feedback module, a user feedback module and an interception module;

[0051] The central processing module is used to receive and process the working information of the big data analysis module, the data collection module, the machine learning module, the shared database, the warning information feedback module, the user feedback module and the interception module, and send the processing results to the relevant modules for processing;

[0052] The data collection module is used to collect transaction data between the user and the transfer user at different first collaboration terminals and interaction data at different third collaboration terminals;

[0053] Specifically, the data collection module also includes a feature extraction unit; the feature extraction unit is used to extract features of interaction information between users at the first collaborative end and the third collaborative end, and the features include but are not limited to call duration, keywords, and social network behavior patterns.

[0054] The big data analysis module is used to perform risk assessment and obtain risk levels based on the interaction data collected by the data collection module and the preset risk model, and feed back the risk level results to the central processing module so that the interception module can trigger the early warning information feedback module to perform corresponding processing strategies. At the same time, the interaction data and risk levels are transmitted to the shared database and can be called by the machine learning module;

[0055] In implementation, the risk levels include low risk level, medium risk level and high risk level;

[0056] The low risk level means that there is a connection between the first cooperation end and the third cooperation end between the transfer users and the characteristic information is safe;

[0057] The medium risk level means that there is a connection between the first cooperation end or the third cooperation end between the transfer users. If there is a connection between the third cooperation ends, its characteristic information is basically safe.

[0058] The high risk level means that there is no connection between the first cooperation end and the third cooperation end between the transfer users.

[0059] The machine learning module is used for deep learning and assisting the big data analysis module to identify the characteristics of telecommunications fraud;

[0060] The shared database is used to store fraud information data transmitted by the big data analysis module, and to establish fraud warning information for bank card accounts and / or telephone numbers whose storage times exceed a certain threshold. At the same time, the data in the shared database can be called by the machine learning module to form a fraud model;

[0061] The interception module is used to trigger the early warning information feedback module to send early warning confirmation information to the transfer user;

[0062] The early warning information feedback module is used to take corresponding treatment measures according to the risk level evaluated by the big data analysis module;

[0063] Specifically, the warning information feedback module includes a text message reminder unit, an intelligent outbound call unit and a manual outbound call unit;

[0064] The SMS reminder unit is used to send a transfer warning confirmation SMS to the transfer user with a low risk level through the second cooperation terminal;

[0065] The outbound call-only unit is used to initiate an intelligent voice warning confirmation call to the transfer user with a medium risk level through the second cooperation terminal;

[0066] The manual outbound calling unit is used to initiate a manual early warning confirmation service call to the transfer user with a high risk level through the second cooperation terminal.

[0067] The user feedback module is used for the transfer user to send warning confirmation information to the warning information feedback module to confirm whether to perform the transfer operation.

[0068] It also includes a multi-platform integration module, which can realize information interaction between the anti-fraud control center module and other platforms.

[0069] A method for preventing telecommunication fraud comprises the following steps:

[0070] S1. Deploy a first collaboration terminal at a financial institution, a second collaboration terminal at an operator, and a third collaboration terminal at a social platform, and connect them to the anti-fraud control center module via the Internet or a dedicated line.

[0071] S2: When the transfer user performs a transfer operation, the anti-fraud control center module collects transaction data between the user and the transfer user at different first collaborative terminals and interaction data at different third collaborative terminals, and performs risk level assessment;

[0072] S3: The anti-fraud control center module sends different early warning confirmation information to the transfer user through the second collaboration terminal according to the risk assessment level;

[0073] S4: The transfer user confirms whether to perform the transfer operation based on the warning confirmation information;

[0074] S5: The first collaboration end determines whether to perform the transfer operation according to the feedback information of the transfer user.

[0075] The following is an explanation of the anti-telecom fraud process:

[0076] In specific implementation, the first collaboration terminal (bank), the second collaboration terminal (operator), and the third collaboration terminal (social platform) are interconnected with the anti-fraud control center module through the Internet or a dedicated line;

[0077] Before a transfer occurs between users, the specific information is as follows:

[0078] Transfer account information: Account: Bank A: User X: User A’s mobile phone number: T1;

[0079] Information about the account being transferred: Account: B Bank: Y User: User B Mobile phone number: T2;

[0080] When performing a transfer operation, when user A transfers money to user B, the data collection module extracts characteristic interaction information such as call duration, keywords, social network behavior patterns, transaction records, etc. between users A and B at the first collaboration terminal and the third collaboration terminal;

[0081] When account A transfers money to account B, the transfer system of Bank X determines whether there is a historical transaction between A and B. If there is a historical record of transfer from A to B or from B to A, the bank can complete the transaction immediately.

[0082] If there is no historical transaction between A and B, Bank X will temporarily freeze the transfer. Then, Bank X will transmit the user information of A and B to the anti-fraud control center module. The big data analysis module will perform risk assessment based on the interaction data collected by the data collection module and the preset risk model to obtain the risk level, and feed back the risk level result to the central processing module for the interception module to trigger the early warning information feedback module to take corresponding processing measures, including the following methods:

[0083] 1. There is a connection between User A and User B between the first collaboration terminal (bank) and the third collaboration terminal (social platform), and the characteristic information is safe. The anti-fraud control center module sends a transfer warning confirmation SMS through the second collaboration terminal (operator), and then User A replies via SMS whether to continue the transfer;

[0084] 2. There is a first collaboration terminal (bank) or a third collaboration terminal (social platform) between User A and User B. If there is a connection between the third collaboration terminals (social platforms) and the characteristic information is basically safe, the anti-fraud control center module initiates an intelligent voice warning confirmation call through the second collaboration terminal (operator), and then User A responds by voice whether to continue the transfer;

[0085] 3. There is no connection between User A and User B between the first and third collaborative terminals. The anti-fraud control center module initiates an artificial early warning confirmation service call through the second collaborative terminal (operator), and then User A replies by phone whether to continue the transfer.

[0086] The present invention and its embodiments are described above, and such description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. In short, if ordinary technicians in the field are inspired by it, without departing from the purpose of the invention, they can design a structure and embodiment similar to the technical solution without creativity, which should belong to the protection scope of the present invention.

Claims

1. A system for preventing telecommunication fraud, characterized in that: It includes an anti-fraud control center module, a first collaboration terminal deployed in a financial institution, a second collaboration terminal deployed in an operator, and a third collaboration terminal deployed in a social platform; The first collaboration end, the second collaboration end and the third collaboration end are all connected to the anti-fraud control center module via the Internet or a dedicated line. The anti-fraud control center module is used to receive and process information from the first collaboration end, the second collaboration end and the third collaboration end, and send the processing results to the relevant collaboration ends for processing.

2. The system for preventing telecommunication fraud according to claim 1, characterized in that: The anti-fraud control center module includes a central processing module, a data collection module, a big data analysis module, a machine learning module, a shared database, a warning information feedback module, a user feedback module and an interception module; The central processing module is used to receive and process the working information of the big data analysis module, the data collection module, the machine learning module, the shared database, the warning information feedback module, the user feedback module and the interception module, and send the processing results to the relevant modules for processing; The data collection module is used to collect transaction data between the user and the transfer user at different first collaboration terminals and interaction data at different third collaboration terminals; The big data analysis module is used to perform risk assessment and obtain risk levels based on the interaction data collected by the data collection module and the preset risk model, and feed back the risk level results to the central processing module so that the interception module can trigger the early warning information feedback module to perform corresponding processing strategies. At the same time, the interaction data and risk levels are transmitted to the shared database and can be called by the machine learning module; The machine learning module is used for deep learning and assisting the big data analysis module to identify the characteristics of telecommunications fraud; The shared database is used to store fraud information data transmitted by the big data analysis module, and to establish fraud warning information for bank card accounts and / or telephone numbers whose storage times exceed a certain threshold. At the same time, the data in the shared database can be called by the machine learning module to form a fraud model; The interception module is used to trigger the early warning information feedback module to send early warning confirmation information to the transfer user; The early warning information feedback module is used to take corresponding treatment measures according to the risk level evaluated by the big data analysis module; The user feedback module is used for the transfer user to send warning confirmation information to the warning information feedback module to confirm whether to perform the transfer operation.

3. The system for preventing telecommunication fraud according to claim 2, characterized in that: It also includes a multi-platform integration module, which can realize information interaction between the anti-fraud control center module and other platforms.

4. The system for preventing telecommunication fraud according to claim 2, characterized in that: The data collection module also includes a feature extraction unit; The feature extraction unit is used to extract features of interaction information between users at the first collaboration end and the third collaboration end, and the features include call duration, keywords, and social network behavior patterns.

5. The system for preventing telecommunication fraud according to claim 4, characterized in that: The risk levels include low risk level, medium risk level and high risk level; The low risk level means that there is a connection between the first cooperation end and the third cooperation end between the transfer users and the characteristic information is safe; The medium risk level means that there is a connection between the first cooperation end or the third cooperation end between the transfer users. If there is a connection between the third cooperation ends, its characteristic information is basically safe. The high risk level means that there is no connection between the first cooperation end and the third cooperation end between the transfer users.

6. The system for preventing telecommunication fraud according to claim 1, characterized in that: The warning information feedback module includes a text message reminder unit, an intelligent outbound call unit and a manual outbound call unit; The SMS reminder unit is used to send a transfer warning confirmation SMS to the transfer user with a low risk level through the second cooperation terminal; The outbound call-only unit is used to initiate an intelligent voice warning confirmation call to the transfer user with a medium risk level through the second cooperation terminal; The manual outbound calling unit is used to initiate a manual early warning confirmation service call to the transfer user with a high risk level through the second cooperation terminal.

7. A method for preventing telecommunication fraud, characterized in that: The following steps are involved: S1. Deploy a first collaboration terminal at a financial institution, a second collaboration terminal at an operator, and a third collaboration terminal at a social platform, and connect them to the anti-fraud control center module via the Internet or a dedicated line. S2: When the transfer user performs a transfer operation, the anti-fraud control center module collects transaction data between the user and the transfer user at different first collaborative terminals and interaction data at different third collaborative terminals, and performs risk level assessment; S3: The anti-fraud control center module sends different early warning confirmation information to the transfer user through the second collaboration terminal according to the risk assessment level; S4: The transfer user confirms whether to perform the transfer operation based on the warning confirmation information; S5: The first collaboration end determines whether to perform the transfer operation according to the feedback information of the transfer user.

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