CN103886495A - Monitoring method and system based on network transaction - Google Patents
Monitoring method and system based on network transaction Download PDFInfo
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- CN103886495A CN103886495A CN201410142633.6A CN201410142633A CN103886495A CN 103886495 A CN103886495 A CN 103886495A CN 201410142633 A CN201410142633 A CN 201410142633A CN 103886495 A CN103886495 A CN 103886495A
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Abstract
The invention provides a monitoring method and system based on a network transaction. The monitoring method comprises the steps that network behavior data and attribute data of a goods provider are obtained in real time; a corresponding risk model is built based on the network behavior data and attribute data; historical network behavior data and attribute data and the current network behavior data and attribute data of the current goods provider are taken, risk identification is conducted on the historical data and the current data according to the risk model, and an identification result is output; according to the identification result, a corresponding risk countermeasure is adopted for the current goods provider according to the identification result. According to the monitoring method and system based on the network transaction, automatic real-time monitoring of the goods provider during the network transaction is achieved by monitoring the network behavior data and attribute data of the goods provider; compared with static monitoring in the prior art, monitoring is more timely and accurate, and human intervention is reduced as much as possible.
Description
Technical field
The present invention relates to e-commerce field, particularly relate to a kind of method for supervising and system of transaction Network Based.
Background technology
Due in recent years, ecommerce becomes the main trend of internet economy development gradually, relies on the E-business applications of the infotecies such as internet, universal and development with surprising rapidity in worldwide at present.In fact, ecommerce becomes a more and more important ingredient in entire society's economic activity just gradually.Along with the universal and development of ecommerce, whether people can reappear more and more and pay close attention to traditional commercial activity on network.
Network trading platform as ecommerce intermediary need to be by the commodity displaying of goods providers (comprising commodity manufacturer, dealer etc.) to user.Present considerable transaction platform is only placed on focus with it user, as long as transaction platform is paid in payment for goods by user, or first payment for goods is paid to transaction platform or third-party platform, then is given to goods providers by transaction platform or third-party platform.In this process, goods providers does not obtain strong monitoring, and some transaction platform does not even arrange threshold to goods providers, although or have certain requirement, also lack the monitoring to commodity provider.
Particularly, along with the development of ecommerce, a large sum of money commodity on net purchase platform are also more and more, such as heating and ventilating equipment, electromechanical equipment etc. for factory.User is because purchasing power is not enough or only need meet lease demand time, just can only payment in part, and remaining payment for goods is by form payments such as loans.If goods providers is sold user by means such as fraud, packagings by some poor qualities, underproof commodity, cause user's loss, also make the prestige of transaction platform impaired.
Summary of the invention
The shortcoming of prior art in view of the above, the object of the present invention is to provide a kind of method for supervising and system of transaction Network Based, the problem of monitoring participating in the goods providers of online transaction for solving prior art.
For achieving the above object and other relevant objects, the invention provides a kind of method for supervising of transaction Network Based, described method comprises:
Real-time Obtaining article provider's network behavior data and attribute data;
Set up corresponding risk model according to described network behavior data and attribute data;
Transfer current article provider's web-based history behavioral data and attribute data, and current network behavioral data and attribute data, according to described risk model, described history and current data are carried out to risk identification, and export recognition result;
According to described recognition result, described current article provider is taked to corresponding risk countermeasure.
Preferably, described article provider's network behavior data at least comprise described article provider's historical trading data and behavior.
Preferably, described article provider's attribute data at least comprises attribute, credit data, award and punishment data, qualification authentication data and the user evaluating data of described article provider at the hour of log-on of business site, certificate data, log-on message, merchandise provided.
Preferably, after setting up corresponding risk model according to described network behavior data and attribute data, also comprise: according to the definition of described risk model, network behavior data and attribute data to article provider carry out historical risk identification, and corresponding historical risk identification result is preserved as the parameter of described risk model.
Preferably, take corresponding risk countermeasure further to comprise according to described recognition result to described current article provider: to judge whether described recognition result has risk, if, according to preset risk level standard, determine the risk class that described online risk identification result is subordinate to, and described current article provider is taked and the corresponding risk processing of determined risk class.
Correspondingly, the present invention also provides a kind of supervisory system of transaction Network Based, and described system comprises:
Data acquisition module, for Real-time Obtaining article provider's network behavior data and attribute data;
Risk model is set up module, for setting up corresponding risk model according to described network behavior data and attribute data;
Current article provider data are transferred module, for transferring current article provider's web-based history behavioral data and attribute data, and current network behavioral data and attribute data, according to described risk model, described history and current data are carried out to risk identification, and export recognition result;
Risk reply module, for taking corresponding risk countermeasure according to described recognition result to described current article provider.
Preferably, described article provider's network behavior data at least comprise described article provider's historical trading data and behavior.
Preferably, described article provider's attribute data at least comprises attribute, credit data, award and punishment data, qualification authentication data and the user evaluating data of described article provider at the hour of log-on of business site, certificate data, log-on message, merchandise provided.
Preferably, also comprise: risk parameter collection module, for the definition according to described risk model, network behavior data and attribute data to article provider carry out historical risk identification, and corresponding historical risk identification result is preserved as the parameter of described risk model.
Preferably, described risk reply module further comprises: judging unit, be used for judging whether described recognition result has risk, if, according to preset risk level standard, determine the risk class that described online risk identification result is subordinate to, and described current article provider is taked and the corresponding risk processing of determined risk class.
As mentioned above, the method for supervising of transaction Network Based of the present invention and system have following beneficial effect:
The present invention realizes the article provider's of network trading automatic real time monitoring by monitoring article provider's network behavior data and attribute data, it can be applied to pre-sales, mid-sales and the risk monitoring and control in each stage of selling after sale etc., therefore with respect to the static state monitoring of prior art, can be more timely, accurate, and reduced artificial intervention as far as possible.
Brief description of the drawings
Fig. 1 is shown as the schematic flow sheet of the method for supervising of a kind of transaction Network Based of the present invention.
Fig. 2 is shown as the schematic flow sheet of the supervisory system of a kind of transaction Network Based of the present invention.
Embodiment
Below, by specific instantiation explanation embodiments of the present invention, those skilled in the art can understand other advantages of the present invention and effect easily by the disclosed content of this instructions.The present invention can also be implemented or be applied by other different embodiment, and the every details in this instructions also can be based on different viewpoints and application, carries out various modifications or change not deviating under spirit of the present invention.
The present invention can be used in numerous general or special purpose computingasystem environment or configuration.For example: personal computer, server computer, handheld device or portable set, laptop device, multicomputer system, the distributed computing environment that comprises above any system or equipment etc.
The present invention can describe in the general context of computer executable instructions, for example program module.Usually, program module comprises the routine, program, object, assembly, data structure etc. carrying out particular task or realize particular abstract data type.Also can in distributed computing environment, put into practice the present invention.In these distributed computing environment, executed the task by the teleprocessing equipment being connected by communication network.In distributed computing environment, program module can be arranged in the local and remote computer-readable storage medium including memory device.
Refer to Fig. 1, show the schematic flow sheet of the method for supervising of a kind of transaction Network Based of the present invention, described method can comprise the following steps:
Step S1: Real-time Obtaining article provider's network behavior data and attribute data.
It should be noted that, described article provider's network behavior data at least comprise described article provider's historical trading data and behavior.Particularly, historical trading data and behavior comprise: the MAC(Media Access Control of the transaction count of the registered account of article provider, dealing money, number of transaction, accession page, medium access control) address change, whether deliver on time, whether have promise breaking record, have or not the data such as Transaction Disputes occurs.
Described article provider's attribute data at least comprises attribute, credit data, award and punishment data, qualification authentication data and the user evaluating data of described article provider at the hour of log-on of business site, certificate data, log-on message, merchandise provided.Particularly, log-on message comprises that article provider's scale, registered capital, affiliated industry, location, enterprise set up time, financial data etc.The attribute of merchandise provided comprises price, type, performance and the newness degree etc. of commodity.Credit data comprises guarantee data, loan and the refund data etc. on credit rating data, bank's platform of article provider on transaction platform.Qualification authentication data comprise article provider's production and operation licence, operation license and other related credentials.User's evaluating data refers to that user passes through the evaluation situation of transaction platform or the commodity of other approach to article provider, as opinion rating, evaluation score etc.Reward and punish award and the punishment situation that data comprise the departments such as government, industry and commerce, the tax, law court.
Also it should be noted that, can obtain by the mode on line or under line article provider's network behavior data and attribute data.In practice, can set up and being connected of online application program by calling interface, the mode by online application program based on interface interchange, pushes to described calling interface by respective articles provider's network behavior data and attribute data.Here, can be understood as often and obtain at regular intervals in real time, for example, every 1 hour, or 1 day, or 2 days etc.Those skilled in the art can be according to actual needs, and the real-time implication of applying in a flexible way is obtained article provider's network behavior data and attribute data.
Step S2: set up corresponding risk model according to described network behavior data and attribute data.
It should be noted that, described risk model can be the mathematical model of setting up based on machine learning method, wherein, described machine learning method can comprise one or more in following method: relevant (Correlation) learning method, enhancing (Boosting) learning method, Bayes (Bayes) learning method, feature space (Eigen) learning method, proper vector (Vector) learning method and meta-heuristic (Meta-Heuristics) learning method.Those skilled in the art can according to actual needs, adopt other machines learning method, or, can also adopt other Mathematical Modeling Methods, as various linearities or non-linear modeling method etc.In the process of setting up model, can set up as required multiple risk models, for example swindle model, line operation risk model, region business risk model, transaction forecast model etc.
Preferably, after setting up corresponding risk model according to described network behavior data and attribute data, also comprise: according to the definition of described risk model, the data in network behavior data, attribute data and affiliated field to article provider are carried out historical risk identification, and corresponding historical risk identification result is preserved as the parameter of described risk model.
In order to improve objectivity and the accuracy of monitoring, the application carries out quantitative test to network behavior data and attribute data, the result of described quantitative test is reflected in the feature of risk model, for example, the feature of described risk model can comprise article provider's the feature such as decision-making custom, development model.
In specific implementation, can be directly input using article provider's network behavior data and attribute data as risk model, the output of risk model is exactly risk identification result, the form that described risk identification result can risk assessment be divided, for example, the scope that risk assessment divides can be 0～100, wherein, risk assessment divides higher, represents that risk is higher.
Step S3: transfer current article provider's web-based history behavioral data and attribute data, and current network behavioral data and attribute data, according to described risk model, described history and current data are carried out to risk identification, and export recognition result.
After having set up risk model, from transfer respectively article provider's web-based history behavioral data and attribute data from database and online application program, and current network behavioral data and attribute data, these two groups of data are inputted respectively to risk model, output recognition result.
Step S4: described current article provider is taked to corresponding risk countermeasure according to described recognition result.
Preferably, take corresponding risk countermeasure further to comprise according to described recognition result to described current article provider: to judge whether described recognition result has risk, if, according to preset risk level standard, determine the risk class that described online risk identification result is subordinate to, and described current article provider is taked and the corresponding risk processing of determined risk class.
Suppose that risk recognition result divides and represents with risk assessment, and the scope that risk assessment divides is 0～100, wherein, risk assessment divides higher, represents that risk is higher, can think that risk assessment divides the recognition result more than 60 points to have risk.Those skilled in the art's preset described risk class according to actual needs, for example, can be divided into N risk class, wherein, and the risk result that each risk class is corresponding certain.Here N is natural number, for example, can be 3 or 4 etc.Described risk processing mode can adopt freeze network trading account, circulate a notice of, close down, warn, cancel added commodity, notice article provider recalls the forms such as problematic commodity.
Refer to Fig. 2, show the schematic diagram of the supervisory system of a kind of transaction Network Based of the present invention, described system A200 comprises:
Data acquisition module A201, for Real-time Obtaining article provider's network behavior data and attribute data;
Risk model is set up modules A 202, for setting up corresponding risk model according to described network behavior data and attribute data;
Current article provider data are transferred modules A 203, for transferring current article provider's web-based history behavioral data and attribute data, and current network behavioral data and attribute data, according to described risk model, described history and current data are carried out to risk identification, and export recognition result;
Risk reply modules A 204, for taking corresponding risk countermeasure according to described recognition result to described current article provider.
Preferably, described article provider's network behavior data at least comprise described article provider's historical trading data and behavior.
Preferably, described article provider's attribute data at least comprises attribute, credit data, award and punishment data, qualification authentication data and the user evaluating data of described article provider at the hour of log-on of business site, certificate data, log-on message, merchandise provided.
Preferably, also comprise: risk parameter collection module A205, for the definition according to described risk model, network behavior data and attribute data to article provider carry out historical risk identification, and corresponding historical risk identification result is preserved as the parameter of described risk model.
Preferably, described risk reply modules A 205 further comprises: judging unit A2051, be used for judging whether described recognition result has risk, if, according to preset risk level standard, determine the risk class that described online risk identification result is subordinate to, and described current article provider is taked and the corresponding risk processing of determined risk class.
It should be noted that, system embodiment please refer to the explanation of embodiment of the method, does not repeat them here.
In sum, the method for supervising of transaction Network Based of the present invention and system have following beneficial effect:
The present invention realizes the article provider's of network trading automatic real time monitoring by monitoring article provider's network behavior data and attribute data, it can be applied to pre-sales, mid-sales and the risk monitoring and control in each stage of selling after sale etc., therefore with respect to the static state monitoring of prior art, can be more timely, accurate, and reduced artificial intervention as far as possible.
So the present invention has effectively overcome various shortcoming of the prior art and tool high industrial utilization.
Above-described embodiment is illustrative principle of the present invention and effect thereof only, but not for limiting the present invention.Any person skilled in the art scholar all can, under spirit of the present invention and category, modify or change above-described embodiment.Therefore, such as in affiliated technical field, have and conventionally know that the knowledgeable, not departing from all equivalence modifications that complete under disclosed spirit and technological thought or changing, must be contained by claim of the present invention.
Claims (10)
1. a method for supervising for transaction Network Based, is characterized in that, described method comprises:
Real-time Obtaining article provider's network behavior data and attribute data;
Set up corresponding risk model according to described network behavior data and attribute data;
Transfer current article provider's web-based history behavioral data and attribute data, and current network behavioral data and attribute data, according to described risk model, described history and current data are carried out to risk identification, and export recognition result;
According to described recognition result, described current article provider is taked to corresponding risk countermeasure.
2. method according to claim 1, is characterized in that: described article provider's network behavior data at least comprise described article provider's historical trading data and behavior.
3. method according to claim 1, is characterized in that: described article provider's attribute data at least comprises attribute, credit data, award and punishment data, qualification authentication data and the user evaluating data of described article provider at the hour of log-on of business site, certificate data, log-on message, merchandise provided.
4. method according to claim 1, it is characterized in that, after setting up corresponding risk model according to described network behavior data and attribute data, also comprise: according to the definition of described risk model, network behavior data and attribute data to article provider carry out historical risk identification, and corresponding historical risk identification result is preserved as the parameter of described risk model.
5. method according to claim 1, it is characterized in that, take corresponding risk countermeasure further to comprise according to described recognition result to described current article provider: to judge whether described recognition result has risk, if, according to preset risk level standard, determine the risk class that described online risk identification result is subordinate to, and described current article provider is taked and the corresponding risk processing of determined risk class.
6. a supervisory system for transaction Network Based, is characterized in that, described system comprises: data acquisition module, for Real-time Obtaining article provider's network behavior data and attribute data; Risk model is set up module, for setting up corresponding risk model according to described network behavior data and attribute data; Current article provider data are transferred module, for transferring current article provider's web-based history behavioral data and attribute data, and current network behavioral data and attribute data, according to described risk model, described history and current data are carried out to wind
Danger identification, and export recognition result;
Risk reply module, for taking corresponding risk countermeasure according to described recognition result to described current article provider.
7. system according to claim 6, is characterized in that: described article provider's network behavior data at least comprise described article provider's historical trading data and behavior.
8. system according to claim 6, is characterized in that: described article provider's attribute data at least comprises attribute, credit data, award and punishment data, qualification authentication data and the user evaluating data of described article provider at the hour of log-on of business site, certificate data, log-on message, merchandise provided.
9. system according to claim 6, it is characterized in that, also comprise: risk parameter collection module, for the definition according to described risk model, network behavior data and attribute data to article provider carry out historical risk identification, and corresponding historical risk identification result is preserved as the parameter of described risk model.
10. system according to claim 6, it is characterized in that, described risk reply module further comprises: judging unit, be used for judging whether described recognition result has risk, if,, according to preset risk level standard, determine the risk class that described online risk identification result is subordinate to, and described current article provider is taked and the corresponding risk processing of determined risk class.
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| CN106910071A (en) * | 2017-01-11 | 2017-06-30 | 中国建设银行股份有限公司 | The verification method and device of user identity |
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| CN107194767A (en) * | 2017-05-17 | 2017-09-22 | 深圳前海跨海侠跨境电子商务有限公司 | A kind of indicating risk method and system for being used to buy platform on behalf |
| CN107742217A (en) * | 2017-09-07 | 2018-02-27 | 阿里巴巴集团控股有限公司 | Service control method and device based on businessman |
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| CN109064175A (en) * | 2018-06-11 | 2018-12-21 | 阿里巴巴集团控股有限公司 | A kind of account takeover risk prevention system method and device |
| CN109300028A (en) * | 2018-09-11 | 2019-02-01 | 上海天旦网络科技发展有限公司 | Real-time anti-fraud method and system and storage medium based on network data |
| CN109544324B (en) * | 2018-11-27 | 2022-03-22 | 深圳前海微众银行股份有限公司 | Credit anti-fraud method, system, device and computer-readable storage medium |
| CN109544324A (en) * | 2018-11-27 | 2019-03-29 | 深圳前海微众银行股份有限公司 | Credit is counter to cheat method, system, equipment and computer readable storage medium |
| CN111833070A (en) * | 2019-04-10 | 2020-10-27 | 阿里巴巴集团控股有限公司 | After-sale processing method and device and electronic equipment |
| CN116611844A (en) * | 2023-07-21 | 2023-08-18 | 江苏金农股份有限公司 | Local financial consumer equity protection system based on blockchain |
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