WO2018014811A1 - 风险识别方法、客户端设备及风险识别*** - Google Patents
风险识别方法、客户端设备及风险识别*** Download PDFInfo
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- WO2018014811A1 WO2018014811A1 PCT/CN2017/093179 CN2017093179W WO2018014811A1 WO 2018014811 A1 WO2018014811 A1 WO 2018014811A1 CN 2017093179 W CN2017093179 W CN 2017093179W WO 2018014811 A1 WO2018014811 A1 WO 2018014811A1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR 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
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
- G06Q20/401—Transaction verification
- G06Q20/4016—Transaction verification involving fraud or risk level assessment in transaction processing
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1433—Vulnerability analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR 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
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR 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
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/30—Payment architectures, schemes or protocols characterised by the use of specific devices or networks
- G06Q20/32—Payment architectures, schemes or protocols characterised by the use of specific devices or networks using wireless devices
- G06Q20/322—Aspects of commerce using mobile devices [M-devices]
- G06Q20/3223—Realising banking transactions through M-devices
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR 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
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR 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
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
- G06Q20/405—Establishing or using transaction specific rules
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR 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
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
- G06Q20/409—Device specific authentication in transaction processing
- G06Q20/4093—Monitoring of device authentication
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- G—PHYSICS
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- 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
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0609—Buyer or seller confidence or verification
Definitions
- the present application relates to the field of computer technologies, and in particular, to a risk identification method, a client device, and a risk identification system.
- the centralized processing of the server cluster is usually adopted, and the identification and control of the risk is initiated after the server receives the data.
- This approach requires a large amount of server resources to store, calculate, and analyze data, and the computational cost and hardware cost of the server cluster are very expensive.
- the embodiment of the present invention provides a risk identification method, which aims to solve the problem that the cost of the server is too high in the prior art, reduces the cost of the server, and reduces the storage cost of the risk identification and control.
- the embodiment of the present application further provides a client device, which solves the problem that the cost of the server is too high in the prior art, reduces the cost to the server, and reduces the storage cost of the risk identification and control.
- the embodiment of the present application further provides a risk identification system, which solves the problem that the cost of the server is too high in the prior art, reduces the cost to the server, and reduces the storage cost and calculation and analysis cost of the risk identification and control.
- the embodiment of the present application further provides a second risk identification system, which is to solve the prior art service.
- the problem of excessive cost of the transaction reduces the cost of the server and reduces the storage cost of risk identification and control.
- the embodiment of the present application further provides a third type of risk identification system, which solves the problem that the cost of the server is too high in the prior art, reduces the cost to the server, and reduces the storage cost of the risk identification and control.
- the embodiment of the present application provides a risk identification method, including:
- the client receives a risk identification request initiated according to the service operation request, where the service operation request includes service data;
- the client acquires service data corresponding to the risk identification request
- the embodiment of the present application further provides a client device, including:
- the request receiving module receives a risk identification request initiated according to the service operation request, where the service operation request includes service data;
- a data acquisition module which acquires service data corresponding to the risk identification request
- An indicator storage module configured to store service indicator data determined according to the service data
- the risk identification module determines whether the service operation request has a risk according to the service data and/or the service indicator data based on the risk identification rule or the risk identification model.
- the embodiment of the present application further provides a risk identification system, including
- the service indicator data stored in the client device is received through the data channel.
- the embodiment of the present application further provides a second risk identification system, including
- the third embodiment of the present application further provides a third risk identification system, including
- the embodiment of the present application determines the service indicator data according to the original service data, and stores the service indicator data in the client.
- the advantage is that: on the one hand, the service for risk identification is used.
- the indicator data is stored on the client, which can reduce the storage cost of the server; on the other hand, the original data of the huge amount of data is converted into the business indicator data for storage, which also reduces the overall storage cost, even if the business indicator data is synchronized to The server performs storage, and the storage cost to the server is also lower than the prior art.
- 1 is a typical system to which the risk identification method of the present application is applied;
- FIG. 2 is a schematic flowchart of a risk identification method according to an embodiment of the present application.
- FIG. 3 is a schematic structural diagram of a risk identification device according to an embodiment of the present application.
- FIG. 4 is a schematic structural diagram of a second risk identification device according to an embodiment of the present application.
- FIG. 5 is a schematic structural diagram of a risk identification system according to an embodiment of the present application.
- FIG. 6 is a schematic structural diagram of a second risk identification system in an embodiment of the present application.
- FIG. 7 is a schematic structural diagram of a third risk identification system in an embodiment of the present application.
- FIG. 8 is a schematic structural diagram of a fourth risk identification system in the embodiment of the present application.
- the system is constructed as shown in FIG. 1.
- the system includes a client and a server, and the client and the server synchronize data through a data channel.
- a risk identification method provided by the present application includes the following steps, as shown in FIG. 2:
- S101 The client receives a risk identification request initiated according to the service operation request, where the service operation request includes service data.
- S102 The client obtains service data corresponding to the risk identification request.
- the service operation request is usually initiated by the user.
- the client After the client receives the service operation request, if the service operation request belongs to a more risky operation type, the client starts the risk identification program and initiates the risk identification request.
- the client can identify the request according to the risk, and can The business data corresponding to the risk identification request is obtained, specifically, the business data is extracted from the business operation request associated with the risk identification request.
- the payment request belongs to a highly risky operation type. Therefore, the client starts the risk identification program, and extracts service data related to the payment service from the payment request, such as the login information of the user and the user's use.
- this part of the original business data often needs to be sent to the server, and stored in the server for risk identification and control.
- the identification of the risk can be realized without storing the part of the original business data to the server.
- the original service data may also be sent to the server for storage or retained on the client for storage when the service operation request is completed, the network is idle, or the server storage space is sufficient. Does not affect the implementation of the technical effects of the present application.
- S103 Determine, according to the service identification data or the service indicator data stored in the client, whether the risk exists in the business operation request based on the risk identification rule or the risk identification model; wherein the service indicator data is determined according to the service data.
- the calculation step of calculating the service indicator data according to the service data, and the step of analyzing and judging according to the service data and/or the service indicator data are involved.
- the above calculation steps may be performed on the client side or on the server side; the steps of the above analysis and judgment may be performed on the client side or on the server side.
- Different calculation methods and contents in the calculation step can be calculated simultaneously on the client or the server, or part of the calculation on the client side, and part of the calculation on the server side; the different analysis contents and the judgment process in the analysis and judgment step can be simultaneously
- the client or the server performs the part, and the part is performed on the client side, and the part is performed on the server side, which is not limited herein. Taking the embodiment shown in FIG. 8 as an example, data storage and calculation can be performed in the client device, and analysis and processing are performed in the server device.
- a series of statistical calculations can be performed.
- the result of these calculations is the business indicator data
- the business indicator data can represent the historical situation of the business operation request corresponding to the business data within a certain period of time.
- a series of statistical values of the data generated by the business operation request in a predetermined time window may be calculated, for example, may be a count value (COUNT) of an amount, time, etc., a sum value (SUM), a start value (FIRST), End value (LAST), difference value (DISTINCT), average value (AVG), standard deviation (STDEV), variance (VAR), maximum value (MAX) and / or minimum value (MIN), etc.
- the time window can be 1 hour , 12 hours, 7 days, etc.
- calculating "COUNT, 1 hour payment success” means counting the number of successful payment of the client device and the account in the last hour, wherein the information of the client device and the information of the account may be from the business data extracted from the business operation request.
- calculating "SUM, 24 hour payment amount” means counting the total amount of client device and account payment success amount in the last 24 hours, wherein the client device information, the payment account information, and each time within 24 hours. Information such as the amount of successful payment (related to the business operation request within 24 hours) may be derived from the business data extracted from the business operation request.
- the first manner is that the original service data of the preset time window can be stored, and the corresponding original service data is invoked when the service indicator data is calculated;
- the original business data of the historical history is stored.
- the original business indicator data is recalculated according to the new business data, and the business indicator data is updated, for example, the "COUNT, 1 hour payment success" item is calculated.
- the indicator is used, the data of the indicator can be updated over time and every successful payment.
- the second method is better from the perspective of reducing storage costs.
- the frequency characteristic of the service operation request and/or the running environment characteristic of the client may be calculated, and the running environment characteristic of the client may be embodied as a software environment and a hardware environment run by the client.
- the frequency at which the client device performs the payment operation can be calculated (which can also be converted to the number of times the computing client device performs the payment operation in the preset time window). Calculate the frequency of the payment operation of an account in the client device, and calculate the attenuation level of the battery of the client device.
- the foregoing service indicator data is calculated according to the service data.
- the calculation process may be performed on the client side or on the server side. If the client performs the calculation of the service indicator data, the client calculates the service indicator data according to the service data, and further, the client reports the calculated service indicator data to the server through the data channel; and the server correspondingly The service indicator data calculated by the client according to the service data is received through the data channel. The calculation of the client can reduce the computational cost of the server. After the calculation is completed in the client, the service indicator data is stored in the client, and can also be reported to the server through the data channel to implement the server. Synchronize with the data of the client on the business indicator data.
- the client first reports the service data to the server through the data channel, and then the client receives the service indicator data calculated by the server according to the service data through the data channel; correspondingly, the service The service end receives the service data reported by the client through the data channel, and the server calculates the service indicator data according to the service data, and then the server sends the service indicator data to the client through the data channel.
- the client does not need to calculate the business indicator data, which is beneficial to simplify the design of the client, and the client can receive the service indicator data calculated by the server through the data channel, and also implement the service indicator data of the client and the server.
- the data is synchronized.
- step S103 based on the risk identification rule or the risk identification model, based on the service data and/or the service indicator data stored in the client, determining whether the service operation request has a risk, the client may directly directly access the service data and/or the service indicator data. Perform a logic analysis and/or a probability analysis to determine whether the business operation request is at risk based on the results of the logic analysis and/or the probability analysis.
- the use of such a client for analysis can timely discover abnormal business operation requests, and better achieve the purpose of identifying risks and preventing risks. details as follows:
- the client logically divides the business data and/or business indicator data. Analysis, based on the results of the logical analysis to determine whether the business operation request is at risk; or
- the client Based on the risk identification model, the client performs logical analysis and/or probability analysis on the business data and/or the business indicator data, and determines whether the business operation request is at risk according to the result of the logic analysis and/or the probability analysis.
- the client can also receive the result of logical analysis and/or probability analysis of the service data and/or service indicator data by the server through the data channel, and then determine the service operation request according to the result of the logic analysis and/or the probability analysis. Is there a risk? If there is no information about the service data or the service indicator data in the server, the client needs to send the service data and/or the service indicator data to the server through the data channel before receiving the analysis result of the server.
- the method of sending data to the server for analysis is beneficial to simplify the design of the client, and the client can identify the risk according to the conclusion drawn by the server. details as follows:
- the client receives the result of logical analysis of the service data and/or the service indicator data by the server through the data channel, or determines whether the service operation request has a risk result according to the result of the logic analysis; or
- the client receives the result of logical analysis and/or probability analysis of the service data and/or the service indicator data by the server through the data channel, or determines whether the service operation request exists according to the result of the logic analysis and/or the probability analysis.
- the result of risk is the result of risk.
- the risk identification model When performing probability analysis on business data and/or business indicator data, it can be realized by calling the risk identification model, and the output is a risk probability and a risk-free probability, and the risk can be determined according to the probability.
- Logical analysis of business data and/or business metrics data can be accomplished by invoking business data and/or business metrics data, as well as pre-defined risk identification rules or risk identification models.
- a risk identification rule can be understood as a logical expression, and a preset correspondence between a state value (true or false) of the logical expression and a conclusion of whether or not there is a risk.
- the business data and/or the business indicator data can be understood as a band. Enter the specific value of the above logical expression.
- Example 1 A preset one
- the risk identification rules are:
- the value of “current amount” comes from the current business operation request to be judged whether there is risk, that is, the current business data; the values of “accumulated amount of the day” and “accumulated payment amount of 7 days” are derived from the business indicators. Data, this rule uses both business data and business metrics data for analysis.
- the logical state (current amount + accumulated amount of the day ⁇ 200) AND (7-day cumulative payment amount > 1w) is the determined status value of true or false.
- Example 2 The default risk identification rule is:
- Example 3 The default risk identification rule is:
- the values of “accumulated amount of the day”, “number of payments within one hour”, and “variance of payment amount within one hour” are derived from the business indicator data, and this rule only performs logical analysis based on the business indicator data.
- the output of the logical expression is preset to "true” in the above rule, it indicates that the business operation request is risky.
- the logic analysis or probability analysis is used for whether or not there is risk.
- Risk identification rules, risk-free lists, and/or risk identification models can all belong to configuration data, and business indicator update data can also belong to one type of configuration data.
- the configuration data can be delivered by the server through the data channel, and the client receives and stores the configuration data, which is used to combine with the service data and/or the service indicator data to determine whether the service operation request is at risk. These configuration data can also be obtained by the client itself.
- the preferred embodiment is that the client and the server synchronize data synchronously or irregularly, and store data including service indicator data, service indicator update data, risk identification rules, risk-free list, and risk identification model on the server and the client at the same time. end.
- the network communication PUSH mode may be adopted, that is, the server notifies the client of the communication mode; at this time, when the server finds that the data stored by the client needs to be updated, the server actively informs the client to update the data, where the data includes Synchronized various types of data.
- the network communication PULL mode can also be adopted, that is, the client pulls the communication mode of the server data; at this time, when the client receives the notification of the server or the local storage of the client needs to be updated, the client will actively go to the server to obtain the updated data.
- the method of the present application further includes: determining a processing manner of the service operation request according to whether the risk operation result of the risk exists according to the service operation request.
- the client directly performs the operation of the business operation request. If the business operation request is at risk, the operation authority of the business operation request needs to be restricted. Specifically, if the business operation request is at risk, the client directly limits the operation authority of the business operation request.
- the client receives a request from the server to restrict the operation authority of the business operation request through the data channel, and further restricts the operation authority of the business operation request.
- the limitation of the operation authority of the service operation request may be released after the risk is excluded, which includes: if the release risk check for the release risk check request feedback is received Information, the restriction on the operation authority of the business operation request is released; wherein the release of the risk verification request can be performed by the client Or the server sends out.
- the application also provides a client device, as shown in FIG. 3, including:
- the request receiving module 101 receives a risk identification request initiated according to a service operation request, where the service operation request includes service data;
- the data obtaining module 102 acquires service data corresponding to the risk identification request
- the indicator storage module 103 stores service indicator data determined according to the service data
- the risk identification module 105 determines whether the business operation request has a risk based on the service data and/or the service indicator data based on the risk identification rule or the risk identification model.
- the client device may further include:
- the configuration data storage module 104 receives and stores configuration data synchronized through the data channel; the configuration data is used in combination with the service data and/or the service indicator data to determine whether the service operation request is at risk.
- configuration data storage module 104 includes:
- the rule storage unit 1041 stores a risk identification rule for determining whether the business operation request has a risk
- the list storage unit 1042 stores information related to hardware environment information of the client device, software environment information, and/or account information in the client device;
- the model storage unit 1043 stores a risk identification model for analyzing whether a business operation request is at risk.
- the risk identification module 105 may specifically include:
- the calculating unit 1051 calculates the service indicator data according to the service data.
- the risk identification module 105 may specifically include:
- the analyzing unit 1052 performs logical analysis and/or probability analysis on the service data and/or the service indicator data based on the risk identification rule or the risk identification model, and determines whether the business operation request has a risk according to the result of the logic analysis and/or the probability analysis.
- the client device may further include:
- the processing module 107 determines the processing manner of the service operation request according to whether the risk operation result of the risk exists according to the service operation request.
- FIG. 4 is a schematic structural diagram of a preferred embodiment of a client device, where the device includes a request receiving module 101, a data obtaining module 102, an indicator storage module 103, a configuration data storage module 104, a risk identification module 105, and a processing module. 107.
- the processing module 107 relies on the risk identification module 105.
- the risk identification module 105 relies on the indicator storage module 102 and the configuration data storage module 104.
- the indicator storage module 102 relies on the data acquisition module 101, and the configuration data storage module 104 relies on the data channel.
- the risk identification module 105 specifically, the calculating unit 1051 and the analyzing unit 1052 are included.
- the calculating unit 1051 may specifically include a statistical calculation subunit and a feature calculation subunit for performing statistical calculation and feature calculation, respectively.
- the analyzing unit 1052 may specifically include a probability analysis subunit and a logic analysis subunit for performing probability analysis and logic analysis, respectively.
- the principles and implementations of statistical calculations, feature calculations, probabilistic analysis, and logic analysis have been described in detail in the foregoing description of the embodiments of the risk identification method, and are not described herein.
- the client device constructed in this way will be executed by the client based on the acquisition, storage, calculation and analysis of the original business data, realizing the data-based risk prevention and control, reducing the number of interactions with the server and the data size. , thereby reducing the cost of server-side risk identification and processing.
- the user can sense and process it in time when the business operation is abnormal, achieving the purpose of risk prevention and control.
- the data analysis on the client side concludes that there is a risk, and it also solves the problem of flexible calculation of complex data.
- Obtaining configuration data including service indicator update data, risk identification rules, risk-free list, and risk identification model from the server through the data channel can better ensure the recognition ability of the client itself for calculation and analysis.
- FIG. 5 shows a risk identification system, including a client device and a service, according to an embodiment of the present application.
- Terminal equipment wherein
- Client devices include:
- the request receiving module receives the risk identification request initiated according to the service operation request, and the service operation request includes the service data;
- a data acquisition module which acquires service data corresponding to the risk identification request
- the indicator storage module stores the service indicator data determined according to the service data
- the risk identification module determines whether the business operation request is at risk according to the service data and/or the service indicator data stored in the client device;
- the server device includes:
- the issuing module sends a risk identification rule or a risk identification model for determining whether the business operation request is risky to the client device through the data channel;
- the receiving module receives the service indicator data stored in the client device through the data channel.
- the client completes a series of operations from the acquisition, calculation, storage, analysis, and processing of business data.
- the storage engine is configured to store data, including service indicator data obtained by the client for calculating the service data (stored in the indicator storage module), and the client obtains the data from the management background (corresponding to the server) through the data channel.
- the rules corresponding to the aforementioned risk identification rules, stored in the rule storage module
- the list corresponding to the aforementioned risk-free list, stored in the list storage module
- the model corresponding to the aforementioned risk identification model, Into the model storage module).
- the client starts the calculation engine to perform statistical calculation and feature calculation, and stores the calculation result, that is, the service indicator data, into the indicator storage module, and synchronizes the service indicator data to the management background through the data channel.
- the analysis engine performs probability analysis and/or logic analysis on the business data and/or the business indicator data based on the risk identification rule or the risk identification model, and determines whether the business operation request exists in the wind according to the analysis result. risk.
- the processing engine may be processed by the processing engine according to the result of the risk identification, including a freeze processing (corresponding to the operation authority for restricting the business operation request) and a solution processing (and releasing the operation authority for the business operation request) The corresponding restrictions).
- FIG. 6 shows a second risk identification system according to an embodiment of the present application, including a client device and a server device, where
- Client devices include:
- the request receiving module receives the risk identification request initiated according to the service operation request, and the service operation request includes the service data;
- a data acquisition module which acquires service data corresponding to the risk identification request
- the indicator storage module stores the service indicator data determined according to the service data
- a result receiving module receiving, by the data channel, a result of whether the service operation request determined by the server device has a risk
- the server device includes:
- the receiving module receives the service indicator data stored in the client device through the data channel;
- the risk identification module determines whether the business operation request has a risk according to the service data and/or the service indicator data stored in the client device; wherein the service indicator data is determined according to the service data;
- the sending module sends a result of the risk of the service operation request determined by the server device to the client device through the data channel.
- the client device only includes the storage engine, and the computing engine, the analysis engine, and the processing engine are all implemented by the server device, which is beneficial to simplifying the client and reducing the client SDK (software development tool).
- the size of the package reduces integration costs and avoids problems such as excessive installation packages.
- FIG. 7 shows a third risk identification system, including a client device, in an embodiment of the present application, Cloud risk identification device and server device, wherein
- Client devices include:
- the request receiving module receives the risk identification request initiated according to the service operation request, and the service operation request includes the service data;
- a data acquisition module which acquires service data corresponding to the risk identification request
- the indicator storage module stores the service indicator data determined according to the service data
- a result receiving module receiving, by the data channel, a result of whether the service operation request determined by the cloud risk identification device is at risk
- Cloud risk identification devices include:
- the risk identification module determines whether the business operation request has a risk according to the service data and/or the service indicator data stored in the client device; wherein the service indicator data is determined according to the service data;
- the server device includes:
- the receiving module receives the service indicator data stored in the client device through the data channel;
- the sending module sends the service indicator data to the cloud risk identification device, and sends the risk identification rule or the risk identification model to the cloud risk identification device.
- the server is divided into a cloud risk identification device and a server device, which further reduces the calculation and analysis pressure of the server device and reduces the cost of the server.
- embodiments of the present invention can be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or a combination of software and hardware. Moreover, the present invention can employ a computer program product embodied on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer usable program code embodied therein. form.
- computer usable storage media including but not limited to disk storage, CD-ROM, optical storage, etc.
- the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
- the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
- These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device.
- the instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.
- a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
- processors CPUs
- input/output interfaces network interfaces
- memory volatile and non-volatile memory
- the memory may include non-persistent memory, random access memory (RAM), and/or non-volatile memory in a computer readable medium, such as read only memory (ROM) or flash memory.
- RAM random access memory
- ROM read only memory
- Memory is an example of a computer readable medium.
- Computer readable media includes both permanent and non-persistent, removable and non-removable media.
- Information storage can be implemented by any method or technology.
- Information can be computer readable instructions, data knots Structure, program module or other data.
- Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory. (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disk read only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, Magnetic tape cartridges, magnetic tape storage or other magnetic storage devices or any other non-transportable media can be used to store information that can be accessed by a computing device.
- computer readable media does not include temporary storage of computer readable media, such as modulated data signals and carrier waves.
- embodiments of the present application can be provided as a method, system, or computer program product.
- the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment in combination of software and hardware.
- the application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.
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Abstract
Description
Claims (25)
- 一种风险识别方法,其特征在于,包括:客户端接收依据业务操作请求发起的风险识别请求,所述业务操作请求中包含有业务数据;所述客户端获取与所述风险识别请求相对应的业务数据;基于风险识别规则或风险识别模型,依据所述业务数据和/或存储在所述客户端的业务指标数据,确定所述业务操作请求是否存在风险;其中,所述业务指标数据依据所述业务数据确定。
- 按照权利要求1所述方法,其特征在于,所述业务指标数据依据所述业务数据确定,具体为:所述客户端依据所述业务数据,计算得到所述业务指标数据。
- 按照权利要求2所述方法,其特征在于,在所述客户端依据所述业务数据,计算得到所述业务指标数据之后,还包括:所述客户端将计算得到的所述业务指标数据通过数据通道上报至服务端。
- 按照权利要求1所述方法,其特征在于,所述业务指标数据依据所述业务数据确定,具体为:服务端通过数据通道接收所述客户端依据所述业务数据计算得到的所述业务指标数据。
- 按照权利要求1所述方法,其特征在于,所述业务指标数据依据所述业务数据确定,具体为:所述客户端将所述业务数据通过数据通道上报至服务端;所述客户端通过所述数据通道接收所述服务端依据所述业务数据计算得到的所述业务指标数据。
- 按照权利要求1所述方法,其特征在于,所述业务指标数据依据所述业务数据确定,具体为:服务端通过数据通道接收所述客户端上报的所述业务数据;所述服务端依据所述业务数据,计算得到所述业务指标数据;所述服务端通过所述数据通道将所述业务指标数据发送到所述客户端。
- 按照权利要求1~6之任一所述方法,其特征在于,所述业务指标数据包括所述业务操作请求产生的数据在预定时间窗口的计数值、加和值、起始值、终止值、区别值、平均值、标准差、方差、最大值和/或最小值。
- 按照权利要求1~6之任一所述方法,其特征在于,所述业务指标数据包括所述业务操作请求出现的频率特性和/或客户端的运行环境特性。
- 按照权利要求1所述方法,其特征在于,基于风险识别规则或风险识别模型,依据所述业务数据和/或存储在所述客户端的业务指标数据,确定所述业务操作请求是否存在风险,包括:基于风险识别规则,所述客户端对所述业务数据和/或所述业务指标数据进行逻辑分析,依据逻辑分析的结果确定所述业务操作请求是否存在风险;或者基于风险识别模型,所述客户端对所述业务数据和/或所述业务指标数 据进行逻辑分析和/或概率分析,依据逻辑分析和/或概率分析的结果确定所述业务操作请求是否存在风险。
- 按照权利要求1所述方法,其特征在于,基于风险识别规则或风险识别模型,依据所述业务数据和/或存储在所述客户端的业务指标数据,确定所述业务操作请求是否存在风险,包括:基于风险识别规则,所述客户端通过数据通道接收服务端对所述业务数据和/或所述业务指标数据进行逻辑分析的结果,或依据所述逻辑分析的结果确定所述业务操作请求是否存在风险的结果;或者基于风险识别模型,所述客户端通过数据通道接收服务端对所述业务数据和/或所述业务指标数据进行逻辑分析和/或概率分析的结果,或依据逻辑分析和/或概率分析的结果确定所述业务操作请求是否存在风险的结果。
- 按照权利要求1所述方法,其特征在于,所述方法还包括:所述客户端接收并存储服务端通过数据通道下发的配置数据;所述配置数据用来与所述业务数据和/或所述业务指标数据结合,确定所述业务操作请求是否存在风险。
- 按照权利要求11所述方法,其特征在于,所述配置数据包括业务指标更新数据、所述风险识别规则、无风险名单和/或所述风险识别模型。
- 按照权利要求1所述方法,其特征在于,在确定所述业务操作请求是否存在风险之后,还包括:依据所述业务操作请求是否存在风险的风险识别结果,确定对所述业务操作请求的处理方式。
- 按照权利要求13所述方法,其特征在于,依据所述业务操作请求是否存在风险的风险识别结果,确定对所述业务操作请求的处理方式,包括:若所述业务操作请求存在风险,则所述客户端限制所述业务操作请求的操作权限。
- 按照权利要求13所述方法,其特征在于,依据所述业务操作请求是否存在风险的风险识别结果,确定对所述业务操作请求的处理方式,包括:若所述业务操作请求存在风险,则所述客户端通过数据通道接收服务端发出的限制所述业务操作请求的操作权限的请求,并限制所述业务操作请求的操作权限。
- 按照权利要求14或15所述方法,其特征在于,在限制所述业务操作请求的操作权限之后,还包括:若接收到针对解除风险校验请求反馈的解除风险校验信息,则解除对所述业务操作请求的操作权限的限制;其中,所述解除风险校验请求由所述客户端或服务端发出。
- 一种客户端设备,其特征在于,包括:请求接收模块,接收依据业务操作请求发起的风险识别请求,所述业务操作请求中包含有业务数据;数据获取模块,获取与所述风险识别请求相对应的业务数据;指标存储模块,存储依据所述业务数据确定的业务指标数据;风险识别模块,基于风险识别规则或风险识别模型,依据所述业务数 据和/或所述业务指标数据,确定所述业务操作请求是否存在风险。
- 按照权利要求17所述设备,其特征在于,所述设备还包括:配置数据存储模块,接收并存储通过数据通道同步的配置数据;所述配置数据用来与所述业务数据和/或所述业务指标数据结合,确定所述业务操作请求是否存在风险。
- 按照权利要求18所述设备,其特征在于,所述配置数据存储模块包括:规则存储单元,存储用于判断业务操作请求是否存在风险的风险识别规则;名单存储单元,存储与所述客户端设备的硬件环境信息、软件环境信息和/或所述客户端设备中的账户信息相关联的信息;模型存储单元,存储用于分析业务操作请求是否存在风险的风险识别模型。
- 按照权利要求17所述设备,其特征在于,所述风险识别模块包括:计算单元,依据所述业务数据,计算得到所述业务指标数据。
- 按照权利要求17所述设备,其特征在于,所述风险识别模块包括:分析单元,基于风险识别规则或风险识别模型,对所述业务数据和/或所述业务指标数据进行逻辑分析和/或概率分析,依据逻辑分析和/或概率分析的结果确定所述业务操作请求是否存在风险。
- 按照权利要求17所述设备,其特征在于,所述设备还包括:处理模块,依据所述业务操作请求是否存在风险的风险识别结果,确定对所述业务操作请求的处理方式。
- 一种风险识别***,其特征在于,包括客户端设备和服务端设备,其中,所述客户端设备包括:请求接收模块,接收依据业务操作请求发起的风险识别请求,所述业务操作请求中包含有业务数据;数据获取模块,获取与所述风险识别请求相对应的业务数据;指标存储模块,存储依据所述业务数据确定的业务指标数据;风险识别模块,基于风险识别规则或风险识别模型,依据所述业务数据和/或存储在所述客户端设备的业务指标数据,确定所述业务操作请求是否存在风险;所述服务端设备包括:下发模块,通过数据通道向所述客户端设备下发用于确定所述业务操作请求是否存在风险的所述风险识别规则或所述风险识别模型;接收模块,通过所述数据通道接收存储在所述客户端设备的业务指标数据。
- 一种风险识别***,其特征在于,包括客户端设备和服务端设备,其中,所述客户端设备包括:请求接收模块,接收依据业务操作请求发起的风险识别请求,所述业务操作请求中包含有业务数据;数据获取模块,获取与所述风险识别请求相对应的业务数据;指标存储模块,存储依据所述业务数据确定的业务指标数据;结果接收模块,通过数据通道接收服务端设备确定的所述业务操作请求是否存在风险的结果;所述服务端设备包括:接收模块,通过所述数据通道接收存储在所述客户端设备的业务指标数据;风险识别模块,基于风险识别规则或风险识别模型,依据所述业务数据和/或存储在所述客户端设备的业务指标数据,确定所述业务操作请求是否存在风险;其中,所述业务指标数据依据所述业务数据确定;下发模块,通过数据通道向所述客户端设备发送由所述服务端设备确定的所述业务操作请求是否存在风险的结果。
- 一种风险识别***,其特征在于,包括客户端设备、云端风险识别设备和服务端设备,其中,所述客户端设备包括:请求接收模块,接收依据业务操作请求发起的风险识别请求,所述业务操作请求中包含有业务数据;数据获取模块,获取与所述风险识别请求相对应的业务数据;指标存储模块,存储依据所述业务数据确定的业务指标数据;结果接收模块,通过数据通道接收由云端风险识别设备确定的所述业务操作请求是否存在风险的结果;所述云端风险识别设备包括:风险识别模块,基于风险识别规则或风险识别模型,依据所述业务数据和/或存储在所述客户端设备的业务指标数据,确定所述业 务操作请求是否存在风险;其中,所述业务指标数据依据所述业务数据确定;所述服务端设备包括:接收模块,通过所述数据通道接收存储在所述客户端设备的业务指标数据;发送模块,向所述云端风险识别设备发送所述业务指标数据;向所述云端风险识别设备发送所述风险识别规则或所述风险识别模型。
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CN107644340A (zh) | 2018-01-30 |
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US11075938B2 (en) | 2021-07-27 |
KR20190032517A (ko) | 2019-03-27 |
TW201816692A (zh) | 2018-05-01 |
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