CN110033151B - Relation risk evaluation method and device, electronic equipment and computer storage medium - Google Patents
Relation risk evaluation method and device, electronic equipment and computer storage medium Download PDFInfo
- Publication number
- CN110033151B CN110033151B CN201811333172.5A CN201811333172A CN110033151B CN 110033151 B CN110033151 B CN 110033151B CN 201811333172 A CN201811333172 A CN 201811333172A CN 110033151 B CN110033151 B CN 110033151B
- Authority
- CN
- China
- Prior art keywords
- relationship
- risk evaluation
- relation
- data
- party
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Development Economics (AREA)
- Marketing (AREA)
- Educational Administration (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The embodiment of the invention discloses a method, a device, electronic equipment and a computer storage medium for evaluating relationship risks, wherein the method comprises the following steps: responding to the relation behavior of the related party, and acquiring relation risk evaluation data of the related party; carrying out relationship risk evaluation on the related party according to the relationship risk evaluation data to obtain a relationship risk evaluation score of the related party; and determining a relational risk evaluation result of the relevant party according to the relational risk evaluation score of the relevant party. According to the technical scheme, risks can be accurately and timely identified in the process that the user and other people generate relation behaviors, the risk identification capability of the user is improved, funds and privacy of the user are protected from being affected, meanwhile, the disturbance to normal users can be reduced, the use experience of the user is improved, and in addition, the technical scheme has universality for risk identification, so that the risk identification method has the advantages of being high in coverage rate, accuracy and flexibility.
Description
Technical Field
The embodiment of the invention relates to the technical field of data processing, in particular to a method and a device for evaluating relationship risks, electronic equipment and a computer storage medium.
Background
With the development of data and communication technologies, many social applications have been developed, and the social applications can provide various services such as communication, transfer of money, payment, file transmission and information transmission for users, and provide great convenience for the work and life of users, so that the social applications are widely used. At the same time, many lawbreakers also utilize the universality of social application to emit bad contents such as advertisements, pornography, harassment and the like to other people, or impersonate friends, relatives, leadership, colleagues and classmates of the other party to practice fraud, thereby seriously affecting the user experience and causing the user fund loss or privacy disclosure.
The method for processing the social risk of the relationship in the prior art mainly comprises the following steps: the method comprises the following steps of a blacklist rule, weak disturbance of the same-organization users and establishment of a risk service rule, wherein the blacklist rule is used for judging whether a relationship event has risks according to whether complaint records exist in histories of the two users, and intercepting the relationship request if the risks exist; the weak disturbing of the same-organization user refers to that according to whether the two parties of the relation are in the same organization (such as a company, a same department and a same social group), if so, the weak disturbing is executed for the user; the step of formulating the risk business rule refers to setting a threshold value of the number of added friends of the user in a certain period of time (such as 1 day, 7 days and the like), and intercepting the behavior of continuing to add friends of the user if the threshold value is exceeded. Although the above processing method can restrict the relation behavior to a certain extent, it still has the insurmountable drawbacks, such as for the blacklist rule, the blacklist is difficult to identify for the blackusers which are not complained or the newly added blackusers due to the limited magnitude of the blacklist, so the coverage rate is lower, the accuracy of part of the history blacklist is lower, and the situation of false interference exists; for the weak disturbance of the same-organization user, the coverage rate of the normal user is lower because the user outside the organization cannot be effectively identified; for formulating the risk business rule, because the relationship behavior of the users is limited by the dependence of the threshold value, the flexibility is lacking, the black users are not recognized timely, and the good users are disturbed to a certain extent.
Disclosure of Invention
The embodiment of the invention provides a method and a device for evaluating relationship risks, electronic equipment and a computer storage medium.
In a first aspect, an embodiment of the present invention provides a method for evaluating a relationship risk.
Specifically, the relationship risk evaluation method includes:
responding to the relation behavior of the related party, and acquiring relation risk evaluation data of the related party;
carrying out relationship risk evaluation on the related party according to the relationship risk evaluation data to obtain a relationship risk evaluation score of the related party;
and determining a relational risk evaluation result of the relevant party according to the relational risk evaluation score of the relevant party.
With reference to the first aspect, in a first implementation manner of the first aspect, the obtaining, in response to the generating, by the interested party, relationship risk evaluation data of the interested party includes:
determining a relationship risk evaluation element;
and responding to the relation behavior of the correlative party, and acquiring correlative party relation risk evaluation data corresponding to the relation risk evaluation element according to the relation risk evaluation element.
With reference to the first aspect and the first implementation manner of the first aspect, in a second implementation manner of the first aspect, the relationship risk evaluation element includes one or more of the following elements: transfer element, account recharging element, equipment element, location element, and communication element; the relationship risk assessment data includes one or more of the following: transfer data between parties, account recharge data between parties, equipment data of parties, location data of parties, communication data of parties.
With reference to the first aspect, the first implementation manner of the first aspect, and the second implementation manner of the first aspect, in a third implementation manner of the first aspect, the performing, according to the relationship risk evaluation data, relationship risk evaluation on the related party, to obtain a relationship risk evaluation score of the related party includes:
determining a relationship risk evaluation model;
and inputting the relationship risk evaluation data into the relationship risk evaluation model to obtain the relationship risk evaluation score of the related party.
With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, and the third implementation manner of the first aspect, in a fourth implementation manner of the first aspect, the performing, according to the relationship risk evaluation data, relationship risk evaluation on the related party to obtain a relationship risk evaluation score of the related party includes:
calculating a related party relationship risk evaluation sub-score according to the relationship risk evaluation element and the corresponding relationship risk evaluation data;
and carrying out weighted calculation on the related party relationship risk evaluation sub-scores to obtain the related party relationship risk evaluation scores.
With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, the third implementation manner of the first aspect, and the fourth implementation manner of the first aspect, in a fifth implementation manner of the first aspect, the disclosure further includes:
And executing preset operation on the related party relation behaviors according to the related party relation risk evaluation result.
In a second aspect, an embodiment of the present invention provides a relationship risk evaluation apparatus.
Specifically, the relationship risk evaluation device includes:
the acquisition module is configured to respond to the relation behavior generated by the related party and acquire relation risk evaluation data of the related party;
the evaluation module is configured to perform relationship risk evaluation on the related party according to the relationship risk evaluation data to obtain a relationship risk evaluation score of the related party;
and the determining module is configured to determine a relationship risk evaluation result of the related party according to the relationship risk evaluation score of the related party.
With reference to the second aspect, in a first implementation manner of the embodiment of the second aspect, the acquiring module includes:
a first determination submodule configured to determine a relationship risk assessment element;
and the obtaining sub-module is configured to respond to the relation behavior of the correlative party and obtain correlative party relation risk evaluation data corresponding to the relation risk evaluation element according to the relation risk evaluation element.
With reference to the second aspect and the first implementation manner of the second aspect, in a second implementation manner of the second aspect, the relationship risk evaluation element includes one or more of the following elements: transfer element, account recharging element, equipment element, location element, and communication element; the relationship risk assessment data includes one or more of the following: transfer data between parties, account recharge data between parties, equipment data of parties, location data of parties, communication data of parties.
With reference to the second aspect, the first implementation manner of the second aspect, and the second implementation manner of the second aspect, in a third implementation manner of the second aspect, the evaluation module includes:
a second determination submodule configured to determine a relational risk assessment model;
and the first evaluation sub-module is configured to input the relationship risk evaluation data into the relationship risk evaluation model to obtain the relationship risk evaluation score of the related party.
With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, and the third implementation manner of the second aspect, in a fourth implementation manner of the second aspect, the evaluation module includes:
a computing sub-module configured to compute a related-party relationship risk evaluation sub-score from the relationship risk evaluation element and its corresponding relationship risk evaluation data;
and the second evaluation sub-module is configured to perform weighted calculation on the correlation risk evaluation sub-scores to obtain the correlation risk evaluation scores.
With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, the third implementation manner of the second aspect, and the fourth implementation manner of the second aspect, in a fifth implementation manner of the second aspect, the disclosure further includes:
And the execution module is configured to execute preset operation on the related party relation behaviors according to the related party relation risk evaluation result.
In a third aspect, an embodiment of the present invention provides an electronic device, including a memory for storing one or more computer instructions for supporting a relationship risk assessment apparatus to perform the relationship risk assessment method in the first aspect, and a processor configured to execute the computer instructions stored in the memory. The relationship risk assessment means may further comprise a communication interface for the relationship risk assessment means to communicate with other devices or a communication network.
In a fourth aspect, an embodiment of the present invention provides a computer readable storage medium storing computer instructions for use by a relational risk assessment device, where the computer instructions include computer instructions for executing the relational risk assessment method according to the first aspect are related to the relational risk assessment device.
The technical scheme provided by the embodiment of the invention can have the following beneficial effects:
according to the technical scheme, the relation risk existing between the related parties is evaluated by acquiring the relation risk evaluation data of the aspects of the related parties. According to the technical scheme, risks can be accurately and timely identified in the process that the user and other people generate relation behaviors, the risk identification capability of the user is improved, funds and privacy of the user are protected from being affected, meanwhile, the disturbance to normal users can be reduced, the use experience of the user is improved, and in addition, the technical scheme has universality for risk identification, so that the risk identification method has the advantages of being high in coverage rate, accuracy and flexibility.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of embodiments of the invention.
Drawings
Other features, objects and advantages of embodiments of the present invention will become more apparent from the following detailed description of non-limiting embodiments, taken in conjunction with the accompanying drawings. In the drawings:
FIG. 1 shows a flow chart of a method of relational risk assessment in accordance with an embodiment of the present invention;
fig. 2 shows a flowchart of step S101 of the relationship risk assessment method according to the embodiment shown in fig. 1;
FIG. 3 shows a flowchart of step S102 of a method of relational risk assessment, according to one embodiment;
fig. 4 shows a flowchart of step S102 of a relationship risk evaluation method according to another embodiment;
FIG. 5 shows a flow chart of a method of relational risk assessment in accordance with another embodiment of the invention;
FIG. 6 is a block diagram showing the construction of a relationship risk evaluating apparatus according to an embodiment of the present invention;
fig. 7 shows a block diagram of the acquisition module 601 of the relationship risk evaluation apparatus according to the embodiment shown in fig. 6;
FIG. 8 shows a block diagram of the evaluation module 602 of the relationship risk evaluation device according to an embodiment;
Fig. 9 shows a block diagram of the evaluation module 602 of the relationship risk evaluation apparatus according to another embodiment;
fig. 10 is a block diagram showing the construction of a relationship risk evaluating apparatus according to another embodiment of the present invention;
FIG. 11 shows a block diagram of an electronic device according to an embodiment of the invention;
fig. 12 is a schematic diagram of a computer system suitable for use in implementing a method of relational risk assessment in accordance with an embodiment of the present invention.
Detailed Description
Hereinafter, exemplary implementations of embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. In addition, for the sake of clarity, portions irrelevant to description of the exemplary embodiments are omitted in the drawings.
In embodiments of the invention, it should be understood that terms such as "comprises" or "comprising," etc., are intended to indicate the presence of features, numbers, steps, acts, components, portions, or combinations thereof disclosed in the specification, and are not intended to exclude the possibility that one or more other features, numbers, steps, acts, components, portions, or combinations thereof are present or added.
In addition, it should be noted that, without conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other. Embodiments of the present invention will be described in detail below with reference to the accompanying drawings in conjunction with the embodiments.
According to the technical scheme provided by the embodiment of the invention, the relation risk existing between the related parties is evaluated by acquiring the relation risk evaluation data of the aspects of the related parties. According to the technical scheme, risks can be accurately and timely identified in the process that the user and other people generate relation behaviors, the risk identification capability of the user is improved, funds and privacy of the user are protected from being affected, meanwhile, the disturbance to normal users can be reduced, the use experience of the user is improved, and in addition, the technical scheme has universality for risk identification, so that the risk identification method has the advantages of being high in coverage rate, accuracy and flexibility.
Fig. 1 shows a flowchart of a relationship risk evaluation method according to an embodiment of the present invention, which includes the following steps S101 to S103, as shown in fig. 1:
in step S101, in response to the related party generating a relationship action, relationship risk evaluation data of the related party is obtained;
in step S102, performing a relationship risk evaluation on the related party according to the relationship risk evaluation data, to obtain a relationship risk evaluation score of the related party;
in step S103, a relational risk evaluation result of the relevant party is determined according to the relational risk evaluation score of the relevant party.
As mentioned above, with the development of data and communication technologies, many social applications have been developed, which can provide various services such as communication, transfer, payment, file transmission, and information transmission to users, and thus provide great convenience to the work and life of users, and thus are widely used. At the same time, many lawbreakers also utilize the universality of social application to emit bad contents such as advertisements, pornography, harassment and the like to other people, or impersonate friends, relatives, leadership, colleagues and classmates of the other party to practice fraud, thereby seriously affecting the user experience and causing the user fund loss or privacy disclosure. In the prior art, some processing methods for dealing with the social risk of the relationship are proposed, but these methods have defects of different degrees, so that the requirements of practical application cannot be met.
In view of the above, in this embodiment, a relationship risk evaluation method is proposed that evaluates relationship risks existing between related parties by acquiring relationship risk evaluation data of aspects of the related parties. According to the technical scheme, risks can be accurately and timely identified in the process that the user and other people generate relation behaviors, the risk identification capability of the user is improved, funds and privacy of the user are protected from being affected, meanwhile, the disturbance to normal users can be reduced, the use experience of the user is improved, and in addition, the technical scheme has universality for risk identification, so that the risk identification method has the advantages of being high in coverage rate, accuracy and flexibility.
In an alternative implementation of this embodiment, the related parties refer to parties that use social applications to generate relational actions, such as parties to communications, parties to transfers, and so on. The social application can be, for example, weChat, QQ, nail and the like, and the relationship behavior can be, for example, communication, transfer of money, payment, file transmission, information propagation and the like, which are established on the relationship between related parties.
In an alternative implementation manner of this embodiment, the relationship risk refers to a risk that when a relationship action occurs between related parties, the action may bring about for the related parties. The technical scheme of the invention aims to collect the risk evaluation related data, and provide visual and reliable evaluation for risks existing in the relation behaviors among related parties by means of the data so as to help a user identify the risks possibly existing in the relation behaviors, and further make a favorable judgment on whether the relation behaviors should be continuously executed or not, thereby avoiding fund loss or privacy leakage.
In an alternative implementation manner of this embodiment, as shown in fig. 2, the step S101, that is, the step of obtaining the relationship risk assessment data of the interested party in response to the interested party generating the relationship behavior, includes the following steps S201 to S202:
In step S201, a relationship risk evaluation element is determined;
in step S202, in response to the relatives generating the relational behavior, the relatives' relational risk assessment data corresponding to the relational risk assessment elements are obtained according to the relational risk assessment elements.
In this embodiment, in order to accurately identify risks existing in a relationship behavior generated between related parties, a complete relationship risk evaluation element needs to be determined first, and then, when a relationship behavior is generated between related parties, relationship risk evaluation data of related parties corresponding to the relationship risk evaluation element is acquired according to the relationship risk evaluation element.
In an alternative implementation of this embodiment, the relationship risk assessment element may include one or more of the following elements: transfer element, account recharge element, device element, location element, communication element. Accordingly, the relationship risk assessment data may include one or more of the following: transfer data between parties, account recharge data between parties, equipment data of parties, location data of parties, communication data of parties.
In an alternative implementation manner of this embodiment, the transfer element refers to a transfer behavior element existing between related parties, and it is generally considered that if the number of times of transfer generated between related parties is greater, the transfer amount is higher, the first transfer occurrence time is earlier, the first and last transfer time spans are greater, the relationship between related parties is more intimate, and the risk is naturally smaller, so that transfer data between corresponding related parties may include the historical number of times of transfer of related parties, the amount of transfer of each time of related parties, the historical total amount of transfer of related parties, the historical first transfer occurrence time of related parties, the historical last transfer occurrence time of related parties, and so on. The transfer data can be obtained through identification information of related parties such as mobile phone numbers, identification card numbers, bank account numbers, social application accounts and the like.
In an optional implementation manner of this embodiment, the account recharging element refers to a recharging behavior element existing between related parties, where the recharging behavior may be, for example, a recharging behavior of a mobile phone, a recharging behavior of a social application account, or the like. It is generally considered that if the number of times of recharging generated between related parties historically is larger, the higher the recharging amount, the earlier the time of occurrence of the first recharging, the longer the time span of occurrence of the last recharging, the closer the relationship between the related parties, and the smaller the risk naturally, the recharging data between the corresponding related parties may include the historical recharging number of the related parties, the historical recharging amount of each related party, the historical recharging total amount of the related parties, the historical time of occurrence of the first recharging of the related parties, the historical time of occurrence of the last recharging of the related parties, and so on. The recharging data can be obtained through identification information of related parties such as mobile phone numbers, identification card numbers, bank account numbers, social application accounts and the like.
In an alternative implementation manner of this embodiment, the device element is used to characterize the device association relationship existing between the related parties, which is generally considered that if the device association occurs between the related parties historically, and the number of device associations is greater, the relationship between the related parties is tighter, and the risk is naturally smaller, where the device association may be, for example, the device identification number used by the related parties is consistent, the IP address used by the related parties is consistent, and so on. Accordingly, the device data between the respective correlators may include correlators device identification information, correlators IP address information, and the like.
In an alternative implementation manner of this embodiment, the location element is used to characterize a location association relationship existing between related parties, which is generally considered that if there is a location intersection or overlap between related parties in history, or the number of location intersections or overlaps is greater, the more closely the relationship between related parties is, the less risk is natural, where the location intersection or overlap may be, for example, that the related parties are in the same county, the same cell, the same office building, the same office place, or the like. Thus, the location data between the respective interested parties may include location information of the interested party, in particular location information that resulted in a take-away, online purchase, shipment, etc. location-based service.
In an optional implementation manner of this embodiment, the communication element is used to indicate whether there is a communication association relationship between related parties, which is generally considered that if there is a communication association between related parties in history or the number of times of communication association is greater, the relationship between related parties is tighter, and the risk is naturally smaller, where the communication association may be, for example, that related parties exist in a contact list or contact information of each other. Accordingly, the communication data between the corresponding correspondents may include address book information or contact information of the correspondents.
In an optional implementation manner of this embodiment, in order to facilitate data collection and statistics, a limitation of a collection period may be further added when the above-mentioned relationship risk evaluation data is collected, for example, the relationship risk evaluation data generated in a certain historical period is collected, where the length of the historical period may be set according to the needs of practical applications, and the present invention is not limited specifically.
In an optional implementation manner of this embodiment, as shown in fig. 3, step S102, that is, a step of performing a relationship risk evaluation on the related party according to the relationship risk evaluation data to obtain a relationship risk evaluation score of the related party, includes the following steps S301 to S302:
in step S301, a relationship risk evaluation model is determined;
in step S302, the relationship risk evaluation data is input into the relationship risk evaluation model, so as to obtain the relationship risk evaluation score of the relevant party.
In this embodiment, a calculation model is used to calculate the relationship risk evaluation score, where the relationship risk evaluation model may be selected as a calculation model such as a logistic regression model, and a person skilled in the art may select an appropriate calculation model according to the needs of the actual application and the characteristics of the relationship risk evaluation data, which is not specifically limited in the present invention.
In another optional implementation manner of this embodiment, as shown in fig. 4, step S102, that is, a step of performing a relationship risk evaluation on the related party according to the relationship risk evaluation data to obtain a relationship risk evaluation score of the related party, includes the following steps S401 to S402:
in step S401, calculating a relational risk evaluation sub-score of the relevant party according to the relational risk evaluation element and the corresponding relational risk evaluation data thereof;
in step S402, the correlation risk evaluation sub-score is weighted, so as to obtain the correlation risk evaluation score.
In order to fully consider all influence factors on the relationship risk, in this embodiment, all relationship risk evaluation data corresponding to the relationship risk evaluation elements are evaluated respectively, and then the obtained evaluation results are weighted, so that a relatively comprehensive and comprehensive relationship risk evaluation score is obtained.
In another alternative implementation manner of this embodiment, when calculating the related party relationship risk evaluation sub-score according to the relationship risk evaluation element and the corresponding relationship risk evaluation data, the following evaluation principle may be used: the more the transfer times generated between the related parties historically, the higher the transfer amount, the earlier the first transfer occurs, the longer the first and last transfer time spans, the closer the relationship between the related parties is considered, the smaller the risk, and the higher the related party relationship risk evaluation sub-value; similarly, the more the number of times of recharging that occurs between historically relevant parties, the higher the amount of recharging, the earlier the time of occurrence of the first recharging, the greater the time span of the last recharging, the more the number of times of device association and device association occurs between historically relevant parties, the more the number of times of positional intersection or overlap exists between historically relevant parties, the more the number of times of communication association exists between historically relevant parties, the more the relationship between the relevant parties is considered to be intimate, the less the risk, and the higher the relevant party relationship risk evaluation sub-score.
When the related party relationship risk evaluation sub-scores are weighted, corresponding weights may be set for different relationship risk evaluation elements, different relationship risk evaluation data, or different related party relationship risk evaluation sub-scores, and then weighted or weighted average calculation may be performed to obtain the related party relationship risk evaluation scores corresponding to the relationship risk evaluation data. When each weight is set, a principle that the more important the relation risk evaluation data is, the higher the corresponding weight is can be adopted, other assignment principles can be adopted, the specific value of each weight can be set according to the requirement of practical application, and the disclosure is not limited specifically.
In an optional implementation manner of this embodiment, the method further includes a step of performing a preset operation on the related party relationship behavior according to the related party relationship risk evaluation result, that is, as shown in fig. 5, the method includes the following steps S501-S504:
in step S501, in response to the correlation party generating the relationship behavior, relationship risk evaluation data of the correlation party is acquired;
in step S502, performing a relationship risk evaluation on the related party according to the relationship risk evaluation data, to obtain a relationship risk evaluation score of the related party;
In step S503, the risk of the correlation is evaluated according to the risk evaluation score of the correlation;
in step S504, a preset operation is performed on the correlation behavior according to the correlation risk evaluation result.
In this embodiment, after the related party relationship risk evaluation result is obtained, it may be determined whether or not limitation on the relationship behavior between the related parties is required according to the evaluation result. For example, if the related party relationship risk evaluation result shows that the relationship behavior risk is small, the relationship behavior between related parties is not required to be limited, but if the related party relationship risk evaluation result shows that the relationship behavior risk is large, a limitation measure such as reminding, inquiring, confirming, verifying, intercepting or rejecting can be adopted for the relationship behavior between related parties.
The following are examples of the apparatus of the present invention that may be used to perform the method embodiments of the present invention.
Fig. 6 shows a block diagram of a relationship risk evaluation apparatus according to an embodiment of the present invention, which may be implemented as part or all of an electronic device by software, hardware, or a combination of both. As shown in fig. 6, the relationship risk evaluation device includes:
An obtaining module 601 configured to obtain relationship risk evaluation data of a related party in response to a related party generating a relationship behavior;
an evaluation module 602 configured to perform a relationship risk evaluation on the related party according to the relationship risk evaluation data, to obtain a relationship risk evaluation score of the related party;
a determining module 603 is configured to determine a relational risk assessment result of the interested party according to the relational risk assessment score of the interested party.
As mentioned above, with the development of data and communication technologies, many social applications have been developed, which can provide various services such as communication, transfer, payment, file transmission, and information transmission to users, and thus provide great convenience to the work and life of users, and thus are widely used. At the same time, many lawbreakers also utilize the universality of social application to emit bad contents such as advertisements, pornography, harassment and the like to other people, or impersonate friends, relatives, leadership, colleagues and classmates of the other party to practice fraud, thereby seriously affecting the user experience and causing the user fund loss or privacy disclosure. In the prior art, some processing methods for dealing with the social risk of the relationship are proposed, but these methods have defects of different degrees, so that the requirements of practical application cannot be met.
In view of the above, in this embodiment, a relationship risk evaluation apparatus is proposed that evaluates relationship risks existing between related parties by acquiring relationship risk evaluation data of aspects of the related parties. According to the technical scheme, risks can be accurately and timely identified in the process that the user and other people generate relation behaviors, the risk identification capability of the user is improved, funds and privacy of the user are protected from being affected, meanwhile, the disturbance to normal users can be reduced, the use experience of the user is improved, and in addition, the technical scheme has universality for risk identification, so that the risk identification method has the advantages of being high in coverage rate, accuracy and flexibility.
In an alternative implementation of this embodiment, the related parties refer to parties that use social applications to generate relational actions, such as parties to communications, parties to transfers, and so on. The social application can be, for example, weChat, QQ, nail and the like, and the relationship behavior can be, for example, communication, transfer of money, payment, file transmission, information propagation and the like, which are established on the relationship between related parties.
In an alternative implementation manner of this embodiment, the relationship risk refers to a risk that when a relationship action occurs between related parties, the action may bring about for the related parties. The technical scheme of the invention aims to collect the risk evaluation related data, and provide visual and reliable evaluation for risks existing in the relation behaviors among related parties by means of the data so as to help a user identify the risks possibly existing in the relation behaviors, and further make a favorable judgment on whether the relation behaviors should be continuously executed or not, thereby avoiding fund loss or privacy leakage.
In an alternative implementation manner of this embodiment, as shown in fig. 7, the obtaining module 601 includes:
a first determination submodule 701 configured to determine a relationship risk assessment element;
an obtaining sub-module 702 is configured to respond to the relation behavior of the correlative party and obtain correlative party relation risk assessment data corresponding to the relation risk assessment element according to the relation risk assessment element.
In this embodiment, in order to accurately identify the risk of the relational behavior generated between the related parties, first, the first determining submodule 701 is required to determine a complete relational risk evaluation element, and then when the relational behavior is generated between the related parties, the obtaining submodule 702 obtains relational risk evaluation data of the related parties corresponding to the relational risk evaluation element according to the relational risk evaluation element.
In an alternative implementation of this embodiment, the relationship risk assessment element may include one or more of the following elements: transfer element, account recharge element, device element, location element, communication element. Accordingly, the relationship risk assessment data may include one or more of the following: transfer data between parties, account recharge data between parties, equipment data of parties, location data of parties, communication data of parties.
In an alternative implementation manner of this embodiment, the transfer element refers to a transfer behavior element existing between related parties, and it is generally considered that if the number of times of transfer generated between related parties is greater, the transfer amount is higher, the first transfer occurrence time is earlier, the first and last transfer time spans are greater, the relationship between related parties is more intimate, and the risk is naturally smaller, so that transfer data between corresponding related parties may include the historical number of times of transfer of related parties, the amount of transfer of each time of related parties, the historical total amount of transfer of related parties, the historical first transfer occurrence time of related parties, the historical last transfer occurrence time of related parties, and so on. The transfer data can be obtained through identification information of related parties such as mobile phone numbers, identification card numbers, bank account numbers, social application accounts and the like.
In an optional implementation manner of this embodiment, the account recharging element refers to a recharging behavior element existing between related parties, where the recharging behavior may be, for example, a recharging behavior of a mobile phone, a recharging behavior of a social application account, or the like. It is generally considered that if the number of times of recharging generated between related parties historically is larger, the higher the recharging amount, the earlier the time of occurrence of the first recharging, the longer the time span of occurrence of the last recharging, the closer the relationship between the related parties, and the smaller the risk naturally, the recharging data between the corresponding related parties may include the historical recharging number of the related parties, the historical recharging amount of each related party, the historical recharging total amount of the related parties, the historical time of occurrence of the first recharging of the related parties, the historical time of occurrence of the last recharging of the related parties, and so on. The recharging data can be obtained through identification information of related parties such as mobile phone numbers, identification card numbers, bank account numbers, social application accounts and the like.
In an alternative implementation manner of this embodiment, the device element is used to characterize the device association relationship existing between the related parties, which is generally considered that if the device association occurs between the related parties historically, and the number of device associations is greater, the relationship between the related parties is tighter, and the risk is naturally smaller, where the device association may be, for example, the device identification number used by the related parties is consistent, the IP address used by the related parties is consistent, and so on. Accordingly, the device data between the respective correlators may include correlators device identification information, correlators IP address information, and the like.
In an alternative implementation manner of this embodiment, the location element is used to characterize a location association relationship existing between related parties, which is generally considered that if there is a location intersection or overlap between related parties in history, or the number of location intersections or overlaps is greater, the more closely the relationship between related parties is, the less risk is natural, where the location intersection or overlap may be, for example, that the related parties are in the same county, the same cell, the same office building, the same office place, or the like. Thus, the location data between the respective interested parties may include location information of the interested party, in particular location information that resulted in a take-away, online purchase, shipment, etc. location-based service.
In an optional implementation manner of this embodiment, the communication element is used to indicate whether there is a communication association relationship between related parties, which is generally considered that if there is a communication association between related parties in history or the number of times of communication association is greater, the relationship between related parties is tighter, and the risk is naturally smaller, where the communication association may be, for example, that related parties exist in a contact list or contact information of each other. Accordingly, the communication data between the corresponding correspondents may include address book information or contact information of the correspondents.
In an optional implementation manner of this embodiment, in order to facilitate data collection and statistics, a limitation of a collection period may be further added when the above-mentioned relationship risk evaluation data is collected, for example, the relationship risk evaluation data generated in a certain historical period is collected, where the length of the historical period may be set according to the needs of practical applications, and the present invention is not limited specifically.
In an alternative implementation of the present embodiment, as shown in fig. 8, the evaluation module 602 includes:
a second determination sub-module 801 configured to determine a relationship risk assessment model;
A first evaluation sub-module 802, configured to input the relationship risk evaluation data into the relationship risk evaluation model, to obtain the correlation side relationship risk evaluation score.
In this embodiment, a calculation model is used to calculate the relationship risk evaluation score, where the relationship risk evaluation model may be selected as a calculation model such as a logistic regression model, and a person skilled in the art may select an appropriate calculation model according to the needs of the actual application and the characteristics of the relationship risk evaluation data, which is not specifically limited in the present invention.
In another alternative implementation of the present embodiment, as shown in fig. 9, the evaluation module 602 includes:
a calculating sub-module 901 configured to calculate a relational risk evaluation sub-score of the relevant party from the relational risk evaluation elements and their corresponding relational risk evaluation data;
and the second evaluation sub-module 902 is configured to perform weighted calculation on the correlation risk evaluation sub-scores to obtain the correlation risk evaluation scores.
In order to fully consider all influence factors on the relationship risk, in this embodiment, the calculation submodule 901 evaluates all relationship risk evaluation data corresponding to the relationship risk evaluation element respectively, and then the second evaluation submodule 902 performs weighting processing on the obtained evaluation result, so as to obtain a relatively comprehensive and comprehensive relationship risk evaluation score.
In another alternative implementation manner of this embodiment, when calculating the related party relationship risk evaluation sub-score according to the relationship risk evaluation element and the corresponding relationship risk evaluation data, the following evaluation principle may be used: the more the transfer times generated between the related parties historically, the higher the transfer amount, the earlier the first transfer occurs, the longer the first and last transfer time spans, the closer the relationship between the related parties is considered, the smaller the risk, and the higher the related party relationship risk evaluation sub-value; similarly, the more the number of times of recharging that occurs between historically relevant parties, the higher the amount of recharging, the earlier the time of occurrence of the first recharging, the greater the time span of the last recharging, the more the number of times of device association and device association occurs between historically relevant parties, the more the number of times of positional intersection or overlap exists between historically relevant parties, the more the number of times of communication association exists between historically relevant parties, the more the relationship between the relevant parties is considered to be intimate, the less the risk, and the higher the relevant party relationship risk evaluation sub-score.
When the related party relationship risk evaluation sub-scores are weighted, corresponding weights may be set for different relationship risk evaluation elements, different relationship risk evaluation data, or different related party relationship risk evaluation sub-scores, and then weighted or weighted average calculation may be performed to obtain the related party relationship risk evaluation scores corresponding to the relationship risk evaluation data. When each weight is set, a principle that the more important the relation risk evaluation data is, the higher the corresponding weight is can be adopted, other assignment principles can be adopted, the specific value of each weight can be set according to the requirement of practical application, and the disclosure is not limited specifically.
In an optional implementation manner of this embodiment, the apparatus further includes a portion for performing a preset operation on the correlation behavior according to the correlation risk evaluation result, that is, as shown in fig. 10, the apparatus includes:
an obtaining module 1001 configured to obtain relationship risk evaluation data of a relevant party in response to the relevant party generating a relationship behavior;
an evaluation module 1002 configured to perform a relationship risk evaluation on the relevant party according to the relationship risk evaluation data, to obtain a relationship risk evaluation score of the relevant party;
a determining module 1003 configured to determine a relationship risk evaluation result of the related party according to the relationship risk evaluation score of the related party
The execution module 1004 is configured to execute a preset operation on the related party relationship behavior according to the related party relationship risk evaluation result.
In this embodiment, after obtaining the related party relationship risk evaluation result, the execution module 1004 may determine whether limitation on the relationship behavior between the related parties is required according to the evaluation result. For example, if the related party relationship risk evaluation result shows that the relationship behavior risk is small, the relationship behavior between related parties is not required to be limited, but if the related party relationship risk evaluation result shows that the relationship behavior risk is large, a limitation measure such as reminding, inquiring, confirming, verifying, intercepting or rejecting can be adopted for the relationship behavior between related parties.
The embodiment of the invention also discloses an electronic device, fig. 11 shows a block diagram of the electronic device according to an embodiment of the invention, and as shown in fig. 11, the electronic device 1100 includes a memory 1101 and a processor 1102; wherein,
the memory 1101 is configured to store one or more computer instructions that are executed by the processor 1102 to implement any of the method steps described above.
Fig. 12 is a schematic diagram of a computer system suitable for implementing a relationship risk assessment method according to an embodiment of the present invention.
As shown in fig. 12, the computer system 1200 includes a Central Processing Unit (CPU) 1201, which can execute various processes in the above-described embodiments in accordance with a program stored in a Read Only Memory (ROM) 1202 or a program loaded from a storage section 1208 into a Random Access Memory (RAM) 1203. In the RAM1203, various programs and data required for the operation of the system 1200 are also stored. The CPU1201, ROM1202, and RAM1203 are connected to each other through a bus 1204. An input/output (I/O) interface 1205 is also connected to the bus 1204.
The following components are connected to the I/O interface 1205: an input section 1206 including a keyboard, a mouse, and the like; an output portion 1207 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage section 1208 including a hard disk or the like; and a communication section 1209 including a network interface card such as a LAN card, a modem, or the like. The communication section 1209 performs communication processing via a network such as the internet. The drive 1210 is also connected to the I/O interface 1205 as needed. A removable medium 1211 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed as needed on the drive 1210 so that a computer program read out therefrom is installed into the storage section 1208 as needed.
In particular, the method described above may be implemented as a computer software program according to an embodiment of the invention. For example, embodiments of the present invention include a computer program product comprising a computer program tangibly embodied on a medium readable thereby, the computer program comprising program code for performing the relationship risk assessment method. In such an embodiment, the computer program can be downloaded and installed from a network through the communication portion 1209, and/or installed from the removable media 1211.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units or modules described in the embodiments of the present invention may be implemented by software, or may be implemented by hardware. The units or modules described may also be provided in a processor, the names of which in some cases do not constitute a limitation of the unit or module itself.
As another aspect, the embodiment of the present invention further provides a computer-readable storage medium, which may be a computer-readable storage medium included in the apparatus described in the above embodiment; or may be a computer-readable storage medium, alone, that is not assembled into a device. The computer-readable storage medium stores one or more programs for use by one or more processors to perform the methods described in embodiments of the present invention.
The above description is only illustrative of the preferred embodiments of the present invention and of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present invention is not limited to the specific combination of the above technical features, but also encompasses other technical features formed by any combination of the above technical features or their equivalents without departing from the inventive concept. Such as the technical solution formed by mutually replacing the above features and the technical features with similar functions (but not limited to) disclosed in the embodiments of the present invention.
Claims (12)
1. A method for evaluating a relationship risk, comprising:
responding to the relation behavior of the related party, and acquiring relation risk evaluation data of the related party; the interested parties include parties that generate relational behavior based on social applications; the relation behavior comprises at least one of transfer behavior, recharging behavior, equipment association relation, position association relation and communication association relation;
carrying out relationship risk evaluation on the related party according to the relationship risk evaluation data to obtain a relationship risk evaluation score of the related party;
determining a relationship risk evaluation result of the related party according to the relationship risk evaluation score of the related party; the relation risk evaluation result is used for reflecting the risk of the relation behavior;
taking limiting measures for the relation behaviors among the related parties under the condition that the relation risk evaluation result shows that the relation behaviors are quite dangerous; the limiting means includes at least one of alerting, asking, verifying, intercepting, rejecting.
2. The method of claim 1, wherein the obtaining the relational risk assessment data of the interested party in response to the interested party generating the relational behavior comprises:
Determining a relationship risk evaluation element;
and responding to the relation behavior of the correlative party, and acquiring correlative party relation risk evaluation data corresponding to the relation risk evaluation element according to the relation risk evaluation element.
3. The method of claim 2, wherein the relationship risk assessment element comprises one or more of the following elements: transfer element, account recharging element, equipment element, location element, and communication element; the relationship risk assessment data includes one or more of the following: transfer data between parties, account recharge data between parties, equipment data of parties, location data of parties, communication data of parties.
4. A method according to claim 2 or 3, wherein said performing a relationship risk assessment on said interested party based on said relationship risk assessment data to obtain a interested party relationship risk assessment score comprises:
determining a relationship risk evaluation model;
and inputting the relationship risk evaluation data into the relationship risk evaluation model to obtain the relationship risk evaluation score of the related party.
5. A method according to claim 2 or 3, wherein said performing a relationship risk assessment on said interested party based on said relationship risk assessment data to obtain a interested party relationship risk assessment score comprises:
Calculating a related party relationship risk evaluation sub-score according to the relationship risk evaluation element and the corresponding relationship risk evaluation data;
and carrying out weighted calculation on the related party relationship risk evaluation sub-scores to obtain the related party relationship risk evaluation scores.
6. A relational risk assessment device comprising:
the acquisition module is configured to respond to the relation behavior generated by the related party and acquire relation risk evaluation data of the related party; the interested parties include parties that generate relational behavior based on social applications; the relation behavior comprises at least one of transfer behavior, recharging behavior, equipment association relation, position association relation and communication association relation;
the evaluation module is configured to perform relationship risk evaluation on the related party according to the relationship risk evaluation data to obtain a relationship risk evaluation score of the related party;
a determining module configured to determine a relationship risk assessment result of the relevant party according to the relevant party relationship risk assessment score; the relation risk evaluation result is used for reflecting the risk of the relation behavior;
an execution module configured to take a limiting measure for the relationship behavior between the related parties in case the relationship risk evaluation result shows that the relationship behavior is highly risky; the limiting means includes at least one of alerting, asking, verifying, intercepting, rejecting.
7. The apparatus of claim 6, wherein the acquisition module comprises:
a first determination submodule configured to determine a relationship risk assessment element;
and the obtaining sub-module is configured to respond to the relation behavior of the correlative party and obtain correlative party relation risk evaluation data corresponding to the relation risk evaluation element according to the relation risk evaluation element.
8. The apparatus of claim 7, wherein the relationship risk assessment element comprises one or more of the following elements: transfer element, account recharging element, equipment element, location element, and communication element; the relationship risk assessment data includes one or more of the following: transfer data between parties, account recharge data between parties, equipment data of parties, location data of parties, communication data of parties.
9. The apparatus of claim 6 or 7, wherein the evaluation module comprises:
a second determination submodule configured to determine a relational risk assessment model;
and the first evaluation sub-module is configured to input the relationship risk evaluation data into the relationship risk evaluation model to obtain the relationship risk evaluation score of the related party.
10. The apparatus of claim 6 or 7, wherein the evaluation module comprises:
a computing sub-module configured to compute a related-party relationship risk evaluation sub-score from the relationship risk evaluation element and its corresponding relationship risk evaluation data;
and the second evaluation sub-module is configured to perform weighted calculation on the correlation risk evaluation sub-scores to obtain the correlation risk evaluation scores.
11. An electronic device comprising a memory and a processor; wherein,
the memory is for storing one or more computer instructions, wherein the one or more computer instructions are executable by the processor to implement the method steps of any one of claims 1-5.
12. A computer readable storage medium having stored thereon computer instructions, which when executed by a processor, implement the method steps of any of claims 1-5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811333172.5A CN110033151B (en) | 2018-11-09 | 2018-11-09 | Relation risk evaluation method and device, electronic equipment and computer storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811333172.5A CN110033151B (en) | 2018-11-09 | 2018-11-09 | Relation risk evaluation method and device, electronic equipment and computer storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110033151A CN110033151A (en) | 2019-07-19 |
| CN110033151B true CN110033151B (en) | 2024-01-19 |
Family
ID=67235254
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811333172.5A Active CN110033151B (en) | 2018-11-09 | 2018-11-09 | Relation risk evaluation method and device, electronic equipment and computer storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110033151B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112529691B (en) * | 2020-12-16 | 2024-08-06 | 深圳市卡牛科技有限公司 | Behavior risk result display method, device, terminal and storage medium |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105378790A (en) * | 2013-03-15 | 2016-03-02 | 索库里公司 | Risk assessment using social networking data |
| CN106067088A (en) * | 2016-05-30 | 2016-11-02 | 中国邮政储蓄银行股份有限公司 | E-bank accesses detection method and the device of behavior |
| CN106295349A (en) * | 2015-05-29 | 2017-01-04 | 阿里巴巴集团控股有限公司 | Risk Identification Method, identification device and the anti-Ore-controlling Role that account is stolen |
| CN107274042A (en) * | 2016-04-06 | 2017-10-20 | 阿里巴巴集团控股有限公司 | A kind of business participates in the Risk Identification Method and device of object |
| CN107622432A (en) * | 2017-07-28 | 2018-01-23 | 阿里巴巴集团控股有限公司 | Trade company's evaluation method and system |
| CN108122163A (en) * | 2017-11-14 | 2018-06-05 | 阿里巴巴集团控股有限公司 | Risk monitoring and control method, apparatus and equipment based on internet credit |
| CN108399509A (en) * | 2018-04-12 | 2018-08-14 | 阿里巴巴集团控股有限公司 | Determine the method and device of the risk probability of service request event |
| CN108734380A (en) * | 2018-04-08 | 2018-11-02 | 阿里巴巴集团控股有限公司 | Adventure account determination method, device and computing device |
| CN108764667A (en) * | 2018-05-15 | 2018-11-06 | 阿里巴巴集团控股有限公司 | Risk data determines method and device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120330819A1 (en) * | 2011-06-21 | 2012-12-27 | Early Warning Services, Llc | System and method for locating and accessing account data |
-
2018
- 2018-11-09 CN CN201811333172.5A patent/CN110033151B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105378790A (en) * | 2013-03-15 | 2016-03-02 | 索库里公司 | Risk assessment using social networking data |
| CN106295349A (en) * | 2015-05-29 | 2017-01-04 | 阿里巴巴集团控股有限公司 | Risk Identification Method, identification device and the anti-Ore-controlling Role that account is stolen |
| CN107274042A (en) * | 2016-04-06 | 2017-10-20 | 阿里巴巴集团控股有限公司 | A kind of business participates in the Risk Identification Method and device of object |
| CN106067088A (en) * | 2016-05-30 | 2016-11-02 | 中国邮政储蓄银行股份有限公司 | E-bank accesses detection method and the device of behavior |
| CN107622432A (en) * | 2017-07-28 | 2018-01-23 | 阿里巴巴集团控股有限公司 | Trade company's evaluation method and system |
| CN108122163A (en) * | 2017-11-14 | 2018-06-05 | 阿里巴巴集团控股有限公司 | Risk monitoring and control method, apparatus and equipment based on internet credit |
| CN108734380A (en) * | 2018-04-08 | 2018-11-02 | 阿里巴巴集团控股有限公司 | Adventure account determination method, device and computing device |
| CN108399509A (en) * | 2018-04-12 | 2018-08-14 | 阿里巴巴集团控股有限公司 | Determine the method and device of the risk probability of service request event |
| CN108764667A (en) * | 2018-05-15 | 2018-11-06 | 阿里巴巴集团控股有限公司 | Risk data determines method and device |
Non-Patent Citations (2)
| Title |
|---|
| Leveraging Financial Social Media Data for Corporate Fraud Detection;Dong 等;《Journal of Management Information Systems》;第35卷(第2期);461-487 * |
| 微信用户风险感知因素研究;杨瑞仙 等;《现代情报》;第36卷(第05期);94-97+103 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110033151A (en) | 2019-07-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11989789B2 (en) | Systems and methods for locating merchant terminals based on transaction data | |
| CN108133013B (en) | Information processing method, information processing device, computer equipment and storage medium | |
| US20220058672A1 (en) | System and method for facilitating real-time feedback in response to collection of real-world data | |
| US20130096968A1 (en) | Performance data in a worker profile aggregated by a job distribution platform for workers that perform crowd sourced tasks | |
| US20130006717A1 (en) | Evaluating a worker in performing crowd sourced tasks and providing in-task training through programmatically generated test tasks | |
| WO2020103560A1 (en) | Risk control method and apparatus, and server and storage medium | |
| US20180108029A1 (en) | Detecting differing categorical features when comparing segments | |
| KR102042442B1 (en) | Regtech platform apparatus for digital compliance and risk management, method for risk management of financial transactions and computer program for the same | |
| US20210049721A1 (en) | User security awareness detection method and apparatus | |
| WO2022257720A1 (en) | Method, apparatus, and system for multi-party algorithm negotiation for privacy computing | |
| US20210201394A1 (en) | Dynamic financial health predictor | |
| CN107886361A (en) | A kind of method and server for assessing ad conversion rates prediction model | |
| WO2022257731A1 (en) | Method, device and system for performing algorithm negotiation on privacy computation | |
| CN114819436A (en) | A financial risk management method, device and storage medium | |
| US20210279794A1 (en) | Systems and methods for determining a graphical user interface for goal development | |
| CN110033151B (en) | Relation risk evaluation method and device, electronic equipment and computer storage medium | |
| WO2013003861A2 (en) | Evaluating a worker in performing crowd sourced tasks and providing in-task training through programmatically generated test tasks | |
| US20140279378A1 (en) | Model performance simulator | |
| US10885526B2 (en) | Monitoring flows in an evolving transaction network using dynamic rules | |
| CN110428253A (en) | Trading channel control method, device, computer equipment and storage medium | |
| CN116757816A (en) | Information approval method, device, equipment and storage medium | |
| CN112016791B (en) | Resource allocation method and device and electronic equipment | |
| CN113487408A (en) | Information processing method and device | |
| US20210397602A1 (en) | Systems and methods for analyzing electronic data to determine faults in a transit system | |
| Sposit | Adapting to digital marketing regulations: the impact of the General Data Protection Regulation on individualised, behaviour-based marketing techniques |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20200923 Address after: Cayman Enterprise Centre, 27 Hospital Road, George Town, Grand Cayman Islands Applicant after: Innovative advanced technology Co.,Ltd. Address before: Cayman Enterprise Centre, 27 Hospital Road, George Town, Grand Cayman Islands Applicant before: Advanced innovation technology Co.,Ltd. Effective date of registration: 20200923 Address after: Cayman Enterprise Centre, 27 Hospital Road, George Town, Grand Cayman Islands Applicant after: Advanced innovation technology Co.,Ltd. Address before: A four-storey 847 mailbox in Grand Cayman Capital Building, British Cayman Islands Applicant before: Alibaba Group Holding Ltd. |
|
| TA01 | Transfer of patent application right | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |