Risk assessment method based on information of mobile phone card of newly opened bank card

Abstract

The invention discloses a risk assessment method based on mobile phone card information of a newly opened bank card. An information exchange technical specification channel is built; the public safety industry carries out risk resource construction by gathering, integrating and managing basic fraud-related source information; risk feature model construction is carried out by integrating financial and communication new card activating resources, and model monitoring is carried out on new card activating personnel; risk measurement construction is carried out according to the monitoring model information, and financial and communication risk assessment results are pushed; through integration of financial and communication new card resources, risk control construction is carried out, and a risk assessment model is corrected. Based on new technologies such as cloud computing and big data, an existing big data resource system is fully utilized, criminal activities are effectively prevented and fished, legitimate rights and interests of banks, operators and individuals are protected, property loss of the masses is reduced, and a safe and ordered social environment is created.

Description

Technical Field

[0001] The present invention relates to the field of public safety prevention technology, and more specifically to a risk assessment method based on newly opened bank card and mobile phone card information. Background Art

[0002] At present, although some banks or operators have adopted biometric recognition technologies such as face recognition and fingerprint recognition, as well as intelligent management technologies such as data analysis and risk assessment to authenticate and monitor the risks of card issuers, these technologies still have many problems and limitations, such as privacy leakage, incomplete data, unstable algorithms, etc. In order to conduct more comprehensive and accurate risk assessment and early warning for card issuers, and establish a risk assessment system for management and control, on the one hand, intelligent and automated risk assessment and management tools are introduced to greatly improve the efficiency and sensitivity of risk prevention and control, and reduce interference and errors caused by human factors; on the other hand, the card opening process is standardized to ensure the compliance and security of card opening operations and reduce risks caused by improper operations. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a risk assessment method based on the information of newly opened bank cards and mobile phone cards, so as to solve the two major problems of identity verification and risk perception of new cardholders in the financial and communication industries.

[0004] In order to solve the above technical problems, the technical solutions adopted by the present invention are as follows.

[0005] A risk assessment method based on newly opened bank card and mobile phone card information includes the following steps:

[0006] S1. Build a technical specification channel for information exchange, open up information exchange channels for the public security industry, the financial industry, and the communications industry, and realize the flow of new card opening information from the financial and communications industries to the public security industry. The public security industry will feed back the resolved risk level information to the financial and communications industries;

[0007] S2. The public security industry builds risk resources by aggregating and integrating basic fraud-related source information;

[0008] S3. Build a risk feature model by integrating new card opening resources from finance and communications, and implement model monitoring of new card opening personnel;

[0009] S4. Construct risk metrics based on monitoring model information and push financial and communication risk assessment results;

[0010] S5. Integrate new financial and communication card resources to build risk control systems and revise risk assessment models.

[0011] To further optimize the technical solution, in step S3, a risk feature module is constructed including a resource comparison model and a behavior feature model.

[0012] To further optimize the technical solution, the resource matching model includes a matching model for persons involved in fraud, a matching model for young / old persons, and a matching model for persons who are easily deceived.

[0013] To further optimize the technical solution, the behavioral feature models include a person-card separation model, a person-number abnormality model, a frequent card activation model, a simultaneous card activation model in two locations, and a group card activation model.

[0014] To further optimize the technical solution, in step S4, the risk metrics include Class A risk, Class B risk, Class C risk and Class D risk.

[0015] To further optimize the technical solution, in step S5, the risk control construction includes risk avoidance for new cardholders, loss control for new cardholders, and risk error correction for new cardholders.

[0016] Due to the adoption of the above technical scheme, the technical progress achieved by the present invention is as follows.

[0017] The present invention provides a risk assessment method based on the information of newly opened bank cards and mobile phone cards. The method is based on new technologies such as cloud computing and big data, makes full use of the existing big data resource system, and constructs an intelligent analysis model based on the comparison of newly opened card resources and risk characteristic behaviors through algorithms and means such as machine learning. The risk control model is constructed through feedback of historical result information from the financial and communication industries, and the intelligent analysis and inference are carried out. The system continuously and accurately adjusts and corrects the risk characteristic model, thereby effectively preventing and combating criminal activities, protecting the legitimate rights and interests of banks, operators and individuals, reducing the property losses of the people, creating a safe and orderly social environment, and meeting the public security industry's requirements for source governance and comprehensive governance, insisting on joint management and group prevention and control, and comprehensively implementing various measures for combating, preventing, controlling and managing and the main responsibility requirements of regulatory bodies in the financial, communication and other industries. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0019] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0020] A risk assessment method based on newly opened bank card and mobile phone card information, combined with Figure 1 As shown, it includes the following steps:

[0021] S1. Build a technical specification channel for information exchange, open up the information exchange channel among the public security industry, the financial industry, and the communications industry, and realize the flow of new card opening information from the financial and communications industries to the public security industry. The public security industry will feed back the smoothed risk level information to the financial and communications industries.

[0022] S2. The public security industry builds risk resources by aggregating and integrating basic fraud-related source information.

[0023] S3. Build risk feature models by integrating new financial and communication card opening resources, and implement model monitoring of new card opening personnel.

[0024] The financial and communications industries push the information of new cardholders to the public security industry network in real time. The system automatically parses the information of new cardholders from the corresponding source. Based on the unique code of the new cardholder, the system automatically monitors the new bank card and mobile phone card information of the person during a specified period of time.

[0025] The construction risk characteristic module includes resource comparison model and behavior characteristic model.

[0026] The resource matching model includes the matching model for persons involved in fraud, the matching model for young / old persons, and the matching model for persons who are easily deceived.

[0027] Fraud-related personnel comparison model: For the same new cardholder, the fraud-related personnel risk resources are compared and risk warnings are issued to the compared personnel.

[0028] Young / older person comparison model: Identify and judge the age of the same new cardholder, and issue risk warnings for abnormal behaviors such as minors and the elderly opening cards more than three times within 30 days.

[0029] Model for comparing vulnerable persons: The model compares the vulnerable persons in the same new cardholder resource and issues risk warnings to the compared persons.

[0030] The behavioral characteristic models include the person-card separation model, the person-number abnormal model, the frequent card opening model, the simultaneous card opening model in two locations and the gang card opening model.

[0031] Person-card separation model: Utilizes the capabilities of the public security network to issue risk warnings for abnormal behaviors at different locations based on the card opening location of the new card holder and whether the card opening person is at the same location.

[0032] Person number anomaly model: Utilizes the capabilities of the public security network to determine whether the new cardholder information and the registered mobile phone number are the same person based on the mobile phone number information provided by the new cardholder, and issues risk warnings for abnormal behaviors that are not from the same person.

[0033] Frequent card opening model: Provide risk warning for the same new cardholder who opens a new mobile phone card or bank card multiple times within a certain period of time.

[0034] Simultaneous card opening model in two locations: risk warning is issued for the same new cardholder who opens a card at two arbitrary outlets at the same time within a certain period of time, and for those who open a card across two districts at the same time.

[0035] Group card opening model: Risk warning is issued for the same card opening person who appears at more than two random outlets to open cards within a certain period of time.

[0036] S4. Construct risk metrics based on monitoring model information and push financial and communication risk assessment results.

[0037] The risk of new cardholders is set as Class A risk according to the risk resource comparison model, which includes (A1 risk, A2 risk, A3 risk); the risk of new cardholders is set as Class B risk according to the behavioral characteristic model, which includes (B1 risk, B2 risk, C risk); the risk of new cardholders is set as Class D risk according to the analysis resource comparison model for susceptible personnel.

[0038] The specific personnel corresponding to different levels are as follows:

[0039] A1 risk personnel: for example, those who have been involved in fraud.

[0040] A2 risk personnel: The person and the card are separated, and the public security industry capabilities are used to determine whether the person is in the same location based on the card opening location.

[0041] A3 risk personnel: The person’s phone number is abnormal. Using the public security industry’s capabilities, based on the mobile phone number information provided by the developer, determine whether the person’s information and mobile phone number are consistent.

[0042] B1 risk personnel: for example, those with a criminal history.

[0043] B2 risk personnel: those who frequently open cards within 1-3 days, open cards at the same time, or are suspected of opening cards in a gang.

[0044] Level C risk personnel: those who frequently open cards for more than 30 days, open cards at the same time, or are suspected of opening cards in a gang.

[0045] Level D risk personnel: those who are within 15 days of the central capital warning and local capital warning.

[0046] S5.Integrate new financial and communication card resources to build risk control systems and revise risk assessment models.

[0047] Risk control construction includes risk avoidance for new cardholders, loss control for new cardholders, and risk error correction for new cardholders.

[0048] Risk avoidance is carried out for new cardholders. After risk level identification is carried out based on risk characteristic models and risk metrics, the corresponding risk level is fed back to the financial and communication industries for measures such as refusing to open cards or reducing the opening limit. The specific measures of the financial and communication industries are fed back to the public security industry network. The system automatically and intelligently adjusts the risk assessment model and updates risk resources based on the results of the measures.

[0049] Carry out loss control for new cardholders. According to the risk level of risk assessment, if the financial industry finds abnormal deposit, withdrawal and transfer behavior of personnel, emergency stop payment and other measures will be taken for the transfer that has already occurred. And the specific results of the financial industry's measures are fed back to the public security industry network. The system automatically adjusts the risk assessment model and updates the risk resources based on the results of the measures.

[0050] Risk correction is carried out for new cardholders. Because of the risk level of risk assessment, in case of misjudgment that causes business failure and leads to complaints, appeal channels are opened for the financial and communications industries. After verification by the public security industry, the number of people on the list is reduced in a timely manner, and the risk assessment model is revised.

Claims

1. A method for risk assessment based on newly opened bank card and mobile phone card information, characterized in that: It includes the following steps: S1. Build a technical specification channel for information exchange, open up information exchange channels for the public security industry, the financial industry, and the communications industry, and realize the flow of new card opening information from the financial and communications industries to the public security industry. The public security industry will feed back the resolved risk level information to the financial and communications industries; S2. The public security industry builds risk resources by aggregating and integrating basic fraud-related source information; S3. Build a risk feature model by integrating new card opening resources from finance and communications, and implement model monitoring of new card opening personnel; S4. Construct risk metrics based on monitoring model information and push financial and communication risk assessment results; S5.Integrate new financial and communication card resources to build risk control systems and revise risk assessment models.

2. A method for risk assessment based on newly opened bank card and mobile phone card information according to claim 1, characterized in that: In step S3, the risk feature module is constructed including a resource comparison model and a behavior feature model.

3. A method for risk assessment based on newly opened bank card and mobile phone card information according to claim 2, characterized in that: The resource comparison model includes a comparison model for persons involved in fraud, a comparison model for young / old persons, and a comparison model for persons who are easily deceived.

4. A method for risk assessment based on newly opened bank card and mobile phone card information according to claim 2, characterized in that: The behavior feature models include a person-card separation model, a person-number abnormality model, a frequent card activation model, a simultaneous card activation model in two locations, and a group card activation model.

5. The method for risk assessment based on newly opened bank card and mobile phone card information according to claim 1, characterized in that: In step S4, the risk metrics include Class A risk, Class B risk, Class C risk and Class D risk.

6. A method for risk assessment based on newly opened bank card and mobile phone card information according to claim 1, characterized in that: In step S5, risk control construction includes risk avoidance for new cardholders, loss control for new cardholders, and risk error correction for new cardholders.

Images