CN110443617A - Information processing method, device and computer equipment - Google Patents

Information processing method, device and computer equipment Download PDF

Info

Publication number
CN110443617A
CN110443617A CN201910617897.5A CN201910617897A CN110443617A CN 110443617 A CN110443617 A CN 110443617A CN 201910617897 A CN201910617897 A CN 201910617897A CN 110443617 A CN110443617 A CN 110443617A
Authority
CN
China
Prior art keywords
beneficiary
detected
risk
rate
paying 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.)
Granted
Application number
CN201910617897.5A
Other languages
Chinese (zh)
Other versions
CN110443617B (en
Inventor
付子圣
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Advanced New Technologies Co Ltd
Advantageous New Technologies Co Ltd
Original Assignee
Alibaba Group Holding Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Alibaba Group Holding Ltd filed Critical Alibaba Group Holding Ltd
Priority to CN201910617897.5A priority Critical patent/CN110443617B/en
Publication of CN110443617A publication Critical patent/CN110443617A/en
Application granted granted Critical
Publication of CN110443617B publication Critical patent/CN110443617B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • 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
    • G06Q20/382—Payment protocols; Details thereof insuring higher security of transaction
    • 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

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Accounting & Taxation (AREA)
  • Computer Security & Cryptography (AREA)
  • Finance (AREA)
  • Strategic Management (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

This specification embodiment discloses a kind of information processing method, this method can a plurality of Receiving information determines the direct relative risk of beneficiary to be detected within the set period based on beneficiary to be detected, the indirect relative risk of beneficiary to be detected is determined according to a plurality of payment information of each paying party corresponding with beneficiary to be detected, and the synthetic risk rate of beneficiary to be detected is determined by the direct relative risk of beneficiary to be detected and the indirect relative risk of beneficiary to be detected, and then according to synthetic risk rate, determine that beneficiary to be detected whether there is abnormal payment collection risks.It so, it is possible the gathering position for accurately predicting beneficiary to be detected.

Description

Information processing method, device and computer equipment
Technical field
This application involves field of computer technology more particularly to a kind of information processing methods, device and computer equipment.
Background technique
With the continuous development of science and technology, internet finance has also obtained development at full speed, and people have also enjoyed mutually The various conveniences of development bring for finance of networking.Nowadays, people can carry out receiving on line by various types of electronic equipments Payment transaction.
Embargo area is the region set up for the healthy and stable global economic order of guarantee, and embargo area is prohibited fund or phase It closes article to enter, beneficiary is also forbidden collecting money in embargo area.The prior art is directly handed over by analysis with beneficiary The gathering position of beneficiary is predicted in the geographical location of easy paying party, so that it is determined that beneficiary is with the presence or absence of embargo area gathering row For.
Summary of the invention
This specification embodiment provides a kind of information processing method, device and computer equipment, to solve or part The technical issues of solution is difficult to the gathering position of Accurate Prediction beneficiary.
In order to solve the above technical problems, this specification embodiment first aspect discloses a kind of information processing method, comprising:
Beneficiary to be detected a plurality of Receiving information within the set period is obtained, is paid according to include in every Receiving information The position of money side determines the direct relative risk of the beneficiary to be detected；
Obtain a plurality of payment information of each paying party, wherein the payment information is the paying party default In period with the Transaction Information that is associated with beneficiary；
From each paying party it is corresponding the association gathering that there are abnormal payment collection risks is determined in relevant beneficiary The accounting of side, the co-related risks rate of each paying party is determined according to the accounting；
According to each co-related risks rate, the indirect relative risk of the beneficiary to be detected is obtained；
According to the direct relative risk and the indirect relative risk, the synthetic risk rate of the beneficiary to be detected is obtained；
According to the synthetic risk rate, determine the beneficiary to be detected with the presence or absence of the abnormal payment collection risks.
This specification embodiment second aspect discloses a kind of information processing unit, comprising:
Direct relative risk determining module, for obtaining beneficiary to be detected a plurality of Receiving information within the set period, root According to the position for the paying party for including in every Receiving information, the direct relative risk of the beneficiary to be detected is determined；
Indirect relative risk determining module, for obtaining a plurality of payment information of each paying party, wherein the payment Information be the paying party in preset period of time with the Transaction Information that is associated with beneficiary；It is corresponding all from each paying party It is associated with the accounting for determining the association beneficiary that there are exception payment collection risks in beneficiary, determines each described pair according to the accounting The co-related risks rate of money side；According to each co-related risks rate, the indirect relative risk of the beneficiary to be detected is obtained；
Synthetic risk rate determining module, for according to the direct relative risk and the indirect relative risk, obtain it is described to Detect the synthetic risk rate of beneficiary；
Abnormal gathering judgment module, for determining that the beneficiary to be detected whether there is according to the synthetic risk rate The exception payment collection risks.
This specification embodiment third aspect discloses a kind of computer readable storage medium, is stored thereon with computer journey Sequence, when which is executed by processor the step of the realization above method.
This specification embodiment fourth aspect discloses a kind of computer equipment, including memory, processor and is stored in On memory and the computer program that can run on a processor, the processor realize the above method when executing described program Step.
By one or more technical solution of this specification, this specification has the advantages that or advantage:
Based on the above-mentioned technical proposal, beneficiary to be detected can not only be obtained based on the Receiving information of beneficiary to be detected Direct relative risk, additionally it is possible to which the payment information based on paying party corresponding with beneficiary to be detected obtains between beneficiary to be detected Relative risk is connect, direct relative risk is then based on and indirect relative risk determines synthetic risk rate.By increasing the payment to paying party The investigation of information can effectively increase Transaction Information quantity (sample size) to be investigated, in this way, comprehensive wind can not only be improved The confidence level of dangerous rate, additionally it is possible to improve the anti-interference of synthetic risk rate, this transaction of paying party position confrontation row is distorted in reduction To be influenced on synthetic risk rate bring.Under the premise of guaranteeing the confidence level and anti-interference of synthetic risk rate, enable to It carries out predicting that obtained result is more accurate, reliable based on gathering position of the synthetic risk rate to beneficiary to be detected.
Above description is only the general introduction of this specification technical solution, in order to better understand the technology hand of this specification Section, and can be implemented in accordance with the contents of the specification, and in order to allow above and other objects, features and advantages of this specification It can be more clearly understood, below the special specific embodiment for lifting this specification.
Detailed description of the invention
By reading the following detailed description of the preferred embodiment, various other advantages and benefits are common for this field Technical staff will become clear.The drawings are only for the purpose of illustrating a preferred embodiment, and is not considered as to this explanation The limitation of book.And throughout the drawings, the same reference numbers will be used to refer to the same parts.In the accompanying drawings:
Fig. 1 shows the flow chart according to information processing method in this specification embodiment；
Fig. 2 shows according to the schematic diagram that beneficiary is interacted with paying party in this specification embodiment；
Fig. 3 shows the flow chart for another sub-step that the step S12 according to Fig. 2 in this specification embodiment includes；
Fig. 4 shows the schematic diagram according to area distribution in this specification embodiment；
Fig. 5 shows another schematic diagram interacted according to beneficiary in this specification embodiment with paying party；
Fig. 6 shows the illustrative view of functional configuration according to information processing unit in this specification embodiment；
Fig. 7 shows the schematic diagram according to computer equipment in this specification embodiment.
Specific embodiment
Exemplary embodiments of the present disclosure are described in more detail below with reference to accompanying drawings.Although showing the disclosure in attached drawing Exemplary embodiment, it being understood, however, that may be realized in various forms the disclosure without should be by embodiments set forth here It is limited.On the contrary, these embodiments are provided to facilitate a more thoroughly understanding of the present invention, and can be by the scope of the present disclosure It is fully disclosed to those skilled in the art.
Embargo area is the region set up for the healthy and stable global economic order of guarantee, and beneficiary is forbidden in embargo area It collects money.In order to avoid beneficiary is collected money in embargo area, the gathering position to beneficiary is needed to predict, in turn Judge whether the gathering position of beneficiary is located in embargo area, is supervised to be located at the beneficiary in embargo area to gathering position Pipe and conjunction rule.
Inventor has found that the flexibility for carrying out bank settlement transaction on line by gathering code is larger, and receives through investigation and analysis Money code does not have location information, and beneficiary can enter embargo area by carrying papery gathering code and collect money, therefore, common pair The method that the gathering position of beneficiary is predicted is started with from paying party information corresponding with beneficiary, by paying party information Including location information determine the gathering position position of code (gathering) of beneficiary, thus predict beneficiary gathering position whether In embargo area.
Inventor has found that common gathering position predicting method is difficult to the gathering of Accurate Prediction beneficiary through further analysis Position.On the one hand, common gathering position predicting method only investigates the Transaction Information being directly linked with beneficiary, specifically Ground, common gathering position predicting method only investigate the information for the paying party directly traded with beneficiary, this will lead to sample This quantity (Transaction Information quantity) is on the low side, and then causes the confidence level of prediction result relatively low.On the other hand, nowadays, most of Trading activity has certain antagonism, and more specifically, paying party and beneficiary are before embargo area is traded, paying party The position where itself can be deliberately distorted, the position after distorting is obtained using common gathering position predicting method and is received Money position prediction will increase erroneous judgement and the probability failed to judge.
Defect present in the above scheme in the prior art, is that inventor is obtaining after practicing and carefully studying As a result, therefore, the solution that the discovery procedure of the above problem and the hereinafter embodiment of the present invention are proposed regarding to the issue above Scheme all should be the contribution that inventor makes the present invention in process of the present invention.
In view of this, this specification embodiment provides a kind of information processing method, device and computer equipment, to solve Certainly or part solves the technical issues of being difficult to the gathering position of Accurate Prediction beneficiary.
In the specific implementation process, information processing method provided by this specification embodiment is it can be appreciated to be checked Survey the method that the gathering position of beneficiary is predicted.Further, the gathering position of beneficiary to be detected can be understood as paper Geographical location of the matter gathering code where when trading generation, it is understood that handed over for other objects that can be realized gathering functions Geographical location where when being also easy to produce.
As a kind of optional embodiment, Fig. 1 is please referred to, a kind of information processing provided for this specification embodiment The flow chart of method, the information processing method may comprise steps of:
Step S11, obtains a plurality of Receiving information of beneficiary to be detected, determines gathering to be detected according to a plurality of Receiving information The direct relative risk of side.
In the embodiment of the present application, available beneficiary to be detected a plurality of Receiving information within the set period.Wherein, Set the time frequency that the period can be off-line calculation.For example, can be using some daily period as setting period, and example It such as, can be using this period of daily 8:00am~10:00pm as the setting period.It is appreciated that within the setting period, it can Several Receiving informations for accumulating beneficiary to be detected, specifically, the number of transaction of beneficiary to be detected can be accumulated.
In the embodiment of the present application, the Receiving information of beneficiary to be detected may include: the gathering gold of beneficiary to be detected Volume, account name and position that paying party when trading is generated with beneficiary to be detected etc..Wherein, the gathering letter of beneficiary to be detected Breath can be obtained from Cloud Server, can also be obtained, be not limited thereto by other channels.
It further, in the specific implementation process, can be according to the position for the paying party for including in every Receiving information, really The direct relative risk of fixed beneficiary to be detected specifically determines from all positions that a plurality of Receiving information includes and is located at setting The ratio of position in region, according to the direct relative risk of ratio-dependent beneficiary to be detected.For example, can be according to each payment Side position, determine the quantity that each paying party is located in setting regions, by be located at setting regions in paying party quantity and The total quantity of paying party is compared, using its ratio as the direct relative risk of beneficiary to be detected.
In the embodiment of the present application, beneficiary p to be detectedxDirect relative risk can be S1(px)。
Illustrate that direct relative risk can be S below with a specific example1(px) determination process:
Fig. 2 is please referred to, the schematic diagram that a kind of beneficiary provided for this specification embodiment is interacted with paying party, by Fig. 2 is as it can be seen that beneficiary p to be detectedxThere are n Receiving information, the corresponding paying party difference of n Receiving information within the setting period For u1、u2、...、un。
In the embodiment of the present application, beneficiary p to be detectedxReceiving information is it can be appreciated that be checked within the set period Survey beneficiary pxDirect dealing information within the set period.
Optionally, direct relative risk S1(px) can be determined by following formula:
Wherein,
N be setting the period in beneficiary p to be detectedxGenerate the paying party quantity of transaction, it is understood that when to set Beneficiary p to be detected in sectionxReceiving information (direct dealing information) quantity；
M be setting the period in beneficiary p to be detectedxThe quantity of paying party when generating transaction in setting regions, Due to beneficiary p to be detectedxThe corresponding paying party of every Receiving information, therefore m can also characterize beneficiary p to be detectedxIn It sets in all Receiving informations (direct dealing information) corresponding in the period, the gathering in setting regions occurs for trading activity The quantity of information.
With paying party u1With paying party u2For, if setting the period in beneficiary p to be detectedxIt pays the bill when generating transaction Square u1Position and paying party u2Position be respectively positioned in setting regions, then m=2.
In the embodiment of the present application, the position of paying party can be paying party and beneficiary p to be detectedxIt is paid when generating transaction Geographical location where money side's terminal device, wherein the geographical location can be latitude and longitude information, or geographic area mark Know, is not limited thereto.
In the embodiment of the present application, setting regions can be embargo area, or other specific regions.It should manage Solution, setting regions can be determined according to practical application scene, it is not limited to embargo area disclosed in the present embodiment.
Step S12 obtains a plurality of payment information of each paying party, is determined according to a plurality of payment information of each paying party The co-related risks rate of each paying party obtains the indirect relative risk of beneficiary to be detected according to each co-related risks rate.
In the embodiment of the present application, a plurality of payment information of each paying party can be understood as beneficiary p to be detectedxBetween Connect Transaction Information, every payment information of each paying party is also understood that as the paying party in preset period of time and is associated with gathering The Transaction Information of side, it will be understood that the corresponding association beneficiary of every payment information.
Optionally, preset period of time can be identical as the setting period, can also be not identical as the setting period.Preset period of time with It sets in period identical situation, it is believed that there is no large changes for the position of paying party.In the embodiment of the present application, with The preset period of time situation identical as the setting period is illustrated.
Optionally, the corresponding association beneficiary of each paying party may include beneficiary p to be detectedx, can not also include Beneficiary p to be detectedx, include beneficiary p to be detected to be associated with beneficiary not in the embodiment of the present applicationxThe case where said It is bright.
Further, the co-related risks rate of each paying party can specifically be calculated in the following manner:
From each paying party it is corresponding the association beneficiary that there are abnormal payment collection risks is determined in relevant beneficiary Accounting determines the co-related risks rate of each paying party according to the accounting.
For example, some paying party corresponds to 4 association beneficiaries, wherein there are the association beneficiaries of abnormal payment collection risks Quantity is 2, it will be understood that determines there are the association receipts of abnormal payment collection risks in the relevant beneficiary of the corresponding institute of the paying party The accounting of money side is 0.5, and therefore, the co-related risks rate of the paying party can be 0.5.
In another example if the corresponding association beneficiary negligible amounts of some paying party, the co-related risks rate being calculated are set Reliability may be lower, in this case it is also possible to after the co-related risks rate of the paying party is calculated, to being calculated Co-related risks rate distribute weight coefficient (for example, weight coefficient is less than 1).It is appreciated that being the lower co-related risks of confidence level Rate distributes weight coefficient, can reduce the influence of the co-related risks rate to prediction result.
Further, the indirect relative risk of beneficiary to be detected can specifically obtain in the following manner:
The average value for obtaining the corresponding all co-related risks rates of beneficiary to be detected, obtains gathering to be detected according to average value The indirect relative risk of side.Wherein, the corresponding all co-related risks rates of beneficiary to be detected can be understood as beneficiary pair to be detected The corresponding co-related risks rate of each beneficiary in all beneficiaries answered.In the specific implementation process, each beneficiary is corresponding Co-related risks rate may be assigned with weight coefficient, it is also possible to not distribute weight coefficient, therefore, obtain beneficiary pair to be detected When the average value for all co-related risks rates answered, it can be carried out according to the co-related risks rate after distribution or unallocated weight coefficient Mean value calculation.For example, obtaining the corresponding all co-related risks rates of beneficiary to be detected is 3, the 1st co-related risks rate distribution Weight coefficient, the 2nd co-related risks rate and the 3rd co-related risks rate do not distribute weight coefficient, are calculating 3 co-related risks When the average value of rate, the 2nd co-related risks rate, the 3rd co-related risks rate can be calculated and be assigned with after weight coefficient The average value of 1st co-related risks rate.
Further, each paying party in preset period of time can with multiple association beneficiaries generate trading activity, please after Continue referring to Fig.2, with paying party u1For, paying party u1In preset period of time be associated with beneficiary p1, association beneficiary p2, association Beneficiary p3And association beneficiary p4Trading activity is generated, specifically, paying party u1There are 4 payments in preset period of time Information.
Fig. 3 is please referred to, lists the one of which of step S12 in the present embodiment by step S121 and step S122 Implementation.
Step S121, from each paying party it is corresponding the association that there are abnormal payment collection risks is determined in relevant beneficiary The accounting of beneficiary determines the co-related risks rate of each paying party according to accounting.
In the embodiment of the present application, each paying party it is corresponding there is the passes of abnormal payment collection risks in relevant beneficiary The accounting of connection beneficiary can specifically determine in the following manner:
For each paying party, the indirect synthetic risk rate of each association beneficiary corresponding with the paying party is obtained, In, the indirect synthetic risk rate of each association beneficiary is obtained according to the corresponding a plurality of Receiving information of the association beneficiary.At this Apply being associated with the method for determination class of the indirect synthetic risk rate of beneficiary and the synthetic risk rate of beneficiary to be detected in embodiment Seemingly, it is contemplated that the overall logic of description does not carry out the method for determination of the indirect synthetic risk rate of association beneficiary first herein It is described in detail, after subsequent completion is to the detailed description of the synthetic risk rate of beneficiary to be detected, can think in conjunction with risk conduction Want that the indirect synthetic risk rate to association beneficiary is illustrated.
Further, the indirect synthesis more than preset value is determined from the corresponding all indirect synthetic risk rates of the paying party The ratio of relative risk, using the ratio as the paying party it is corresponding there is the associations of abnormal payment collection risks in relevant beneficiary The accounting of beneficiary.
In the specific implementation process, if some indirect synthetic risk rate of the paying party is more than preset value, it is possible to determine that should There are abnormal payment collection risks in the corresponding association beneficiary of indirect synthetic risk rate, based on this judgment mode, can determine and be more than The quantity of the indirect synthetic risk rate of preset value, will be between the quantity and the paying party of the indirect synthetic risk rate more than preset value The total quantity for connecing synthetic risk rate is compared to obtain determination in the corresponding all indirect synthetic risk rates of the paying party and be more than The ratio of the indirect synthetic risk rate of preset value.
In the embodiment of the present application, preset value is for determining that association beneficiary whether there is one kind of abnormal payment collection risks Criterion, for example, if the indirect synthetic risk rate of some association beneficiary is more than preset value, it is possible to determine that the association beneficiary Gathering position be located in setting regions, so that it is determined that there are abnormal payment collection risks in the association beneficiary.It is appreciated that preset value It can be adjusted according to practical situations, to the adjustment mode class of the adjustment mode and given threshold hereinafter of preset value Seemingly, therefore, it is first not illustrated herein, please refers to the related description hereafter to given threshold.
Illustrate how to determine the co-related risks rate of each paying party with a specific example below:
Please continue to refer to Fig. 2, with paying party u1For, determine association beneficiary p1, association beneficiary p2, association beneficiary p3Be associated with beneficiary p4The accounting of the middle association beneficiary that there are abnormal payment collection risks, determines paying party u according to accounting1Pass Join relative risk.For example, determining association beneficiary p1Be associated with beneficiary p3There are abnormal payment collection risks, then paying party u1Association Relative risk S (u1) it is 0.5.
It similarly, according to the method described above can be in the hope of paying party u1~unCorresponding co-related risks rate S (u1)~S (un)。
Step S122 obtains the indirect relative risk of beneficiary to be detected according to each co-related risks rate.
In the embodiment of the present application, the indirect relative risk of beneficiary to be detected is obtained especially by following manner:
The average value for obtaining the corresponding all co-related risks rates of beneficiary to be detected, obtains gathering to be detected according to average value The indirect relative risk of side.
In the embodiment of the present application, beneficiary p to be detectedxIndirect relative risk can be S2(px)
Optionally, indirect relative risk is S2(px) can be determined by following formula:
Wherein, S (ui) be i-th of beneficiary co-related risks rate.
Specifically, indirect relative risk is S2(px) it can be the average value of n co-related risks rate.
As described above, in the specific implementation process, the corresponding co-related risks rate of each beneficiary may be assigned with weight Coefficient, it is also possible to not distribute weight coefficient, therefore, obtain being averaged for the corresponding all co-related risks rates of beneficiary to be detected When value, mean value calculation can be carried out according to the co-related risks rate after distribution or unallocated weight coefficient.For this purpose, between determination Connecing relative risk is S2(px) when, need to consider whether the co-related risks rate of each beneficiary in n beneficiary is assigned with weight coefficient, It, should be to distribute the co-related risks rate after weight coefficient as S (u if being assigned with weight coefficienti) and bring into above-mentioned formula into In the ranks meet relative risk S2(px) calculating.
Step S13 obtains the synthetic risk rate of beneficiary to be detected according to direct relative risk and indirect relative risk.
In the specific implementation process, the integrated risk of beneficiary to be detected is determined based on direct relative risk and indirect relative risk There are many kinds of the methods of rate, and two of them method is set forth below, certainly, in the specific implementation process, however it is not limited to following two Method:
The first synthetic risk rate determines method, obtains direct relative risk S1(px) and indirect relative risk S2(px) weighting With beneficiary p to be detected is determined according to weighted sumxSynthetic risk rate.
In the embodiment of the present application, beneficiary p to be detectedxSynthetic risk rate be Sp(px)。
Optionally, synthetic risk rate Sp(px) can be determined by following formula:
Sp(px)=w1·S1(px)+w2·S2(px)
Wherein, w1And w2For weighted value, further, weighted value w1With weighted value w2It can be adjusted according to the actual situation It is whole.
In the specific implementation process, weighted value w1And w2It can be adjusted in several ways, be set forth below therein three Kind method of adjustment, certainly, in the specific implementation process, however it is not limited to following three kinds of methods.
The first weight value adjustment method, if beneficiary p to be detectedxWithin the set period the quantity of Receiving information compared with It is few, calculate direct relative risk S1(px) corresponding to sample size it is also corresponding less, can suitably reduce weighted value w at this time1.Example It such as, can be by weighted value w1It will be set as 0.4, by weighted value w2It is set as 0.6, so, it is possible to guarantee synthetic risk rate Sp(px) Confidence level and accuracy will not be affected because sample size is less.
Second of weight value adjustment method, if beneficiary p to be detectedxWithin the set period the quantity of Receiving information compared with It is more, calculate direct relative risk S1(px) corresponding to sample size it is also corresponding more, can suitably increase weighted value w at this time1With true Protect synthetic risk rate Sp(px) confidence level and accuracy.In another example can be by weighted value w1It will be set as 0.7, by weighted value w2 It is set as 0.3.
The third weight value adjustment method, if beneficiary p to be detectedxCorresponding multiple beneficiaries within the setting period In, the beneficiary for being marked as the once geographical location where tampered gathering method, apparatus is on the high side, for example, if beneficiary to be detected pxWithin the setting period in 50 corresponding beneficiaries, it is marked as the geographical location once where tampered gathering method, apparatus Beneficiary quantity be 45, show based on this 50 beneficiaries gathering method, apparatus where geographical location determine it is direct Relative risk S1(px) may be inaccurate, in order to guarantee that synthetic risk rate is Sp(px) confidence level and accuracy, weight can be reduced Value w1.In another example can be by weighted value w1It will be set as 0.2, by weighted value w2It is set as 0.8, so, it is possible effectively to avoid straight Meet relative risk S1(px) to synthetic risk rate Sp(px) influence.
In the above scheme, due to can be according to the actual situation to weighted value w1With weighted value w2It is adjusted, therefore guarantees Synthetic risk rate Sp(px) confidence level and accuracy.
Second of synthetic risk rate determines method, determines synthetic risk rate S by the method for linear, additivep(px)。
Specifically, a relative risk constant can be preset, direct relative risk S is then based on1(px), indirect relative risk S2(px) and the relative risk constant determine synthetic risk rate Sp(px).More specifically, synthetic risk rate Sp(px) can lead to Following formula is crossed to determine:
Sp(px)=h1·S1(px)+h2·S2(px)+h0
Wherein, h0For relative risk constant, h1And h2For linear dimensions.
In the embodiment of the present application, relative risk constant h0It can be used for characterizing synthetic risk rate Sp(px) existing for it is objective can Energy property, specifically, in some special circumstances, passing through the first synthetic risk rate Sp(px) the obtained synthesis wind of the method for determination Dangerous rate Sp(px) may be relatively low, or even level off to 0, but in practical situations, each beneficiary can have gathering position and be located at Objective possibility in setting regions, therefore, second of synthetic risk rate Sp(px) method of determination objective can may examine this Including worry, so that determining obtained synthetic risk rate Sp(px) it is more in line with actual conditions.
Optionally, linear dimensions h1And h2Adjustment mode and weighted value w1And w2Adjustment mode it is similar, therefore herein not Make more explanations.It is appreciated that in view of relative risk constant h0Presence, linear dimensions h1And h2The sum of value compared to weight Value w1And w2The sum of value it is smaller, for example, if weighted value w1And w2The sum of value be 1, then linear dimensions h1And h2Value The sum of can be 0.8.
Optionally, if beneficiary p to be detectedxCarrying out this synthetic risk rate Sp(px) calculating before once existed it is abnormal Payment collection risks (gathering position is located in setting regions), are determining that method determines gathering to be detected using second of synthetic risk rate Just this synthetic risk rate Sp(px) when, it can be by relative risk constant h0It is appropriate to be turned up, it so, it is possible to realize to once existing The beneficiary p to be detected of abnormal payment collection risksxGathering position predicted as strict as possible.
Step S14 determines that beneficiary to be detected whether there is abnormal payment collection risks according to synthetic risk rate.
In the embodiment of the present application, abnormal payment collection risks can be understood as beneficiary p to be detectedxIt is carried out in setting regions The risk of gathering, specifically, abnormal payment collection risks are also understood that as beneficiary p to be detectedxGathering position be located at setting Risk in region.It is possible to further be based on synthetic risk rate Sp(px) prediction beneficiary p to be detectedxGathering position whether In setting regions, so that it is determined that beneficiary p to be detectedxWith the presence or absence of abnormal payment collection risks.
In the specific implementation process, beneficiary p to be detected can be determined by a variety of methodsxWith the presence or absence of abnormal wind of collecting money Danger, three kinds of determinations therein beneficiary to be detected, which is set forth below, whether there is the method for abnormal payment collection risks, certainly, specific real During applying, however it is not limited to following three kinds of methods.
The first determines beneficiary p to be detectedxWith the presence or absence of the method for abnormal payment collection risks, synthetic risk rate S is judgedp (px) it whether is more than given threshold, judging result is obtained, determines that beneficiary to be detected is received with the presence or absence of abnormal according to judging result Money risk.
In the specific implementation process, when judging result characterizes synthetic risk rate Sp(px) be more than given threshold when, determine it is to be checked Survey beneficiary pxGathering position be located in setting regions, further, it is determined that beneficiary p to be detectedxIn the presence of abnormal wind of collecting money Danger.
Optionally, given threshold can be adjusted according to the physical location situation of setting regions.Fig. 4 is please referred to, If setting regions z0Around be non-setting regions z1~z8, then given threshold can suitably be increased, for example, by given threshold It is set as 0.7 or bigger.
In the embodiment of the present application, the reason of given threshold suitably being increased is as follows: due to setting regions z0By multiple non- Setting regions z1~z8It is surrounded, if beneficiary p to be detectedxIt is located in one of in non-setting regions and close to setting regions z0, In this case, paying party is by scanning beneficiary p to be detectedxGathering code when being paid the bill, where method, apparatus of paying the bill Geographical location may occur drift and (such as float to setting regions z0It is interior), it, may be due to payment if not increasing given threshold The drift in the geographical location where method, apparatus is by beneficiary p to be detectedxIt is mistaken for the presence of abnormal payment collection risks, therefore, above-mentioned In the case of, it needs suitably to increase given threshold.
Further, if setting regions z0The non-setting regions z of surrounding1~z8It is interior to exist largely based on gathering code progress Transaction, should also be as suitably increasing given threshold in this case.It so, it is possible to avoid in non-setting regions z1~z8It is interior The geographical location largely paid the bill where method, apparatus when being traded is from non-setting regions z1~z8Drift to setting regions z0It is interior, from And it influences to beneficiary p to be detectedxAbnormal gathering judgement.
In addition, if setting regions z0The non-setting regions z of surrounding1~z8It inside there's almost no the friendship carried out based on gathering code Easily (such as setting regions z0The non-setting regions z of surrounding1~z8Inside almost use cash transaction), it at this time can be by given threshold It is appropriate to reduce.For example, setting 0.6 or smaller for given threshold.It so, it is possible in the geography where less payment method, apparatus Position is located at setting regions z0In the case where interior, remain to be accurately judged to beneficiary p to be detected by lesser given thresholdxIt is It is no to there are abnormal payment collection risks.
It should be appreciated that setting regions z illustrated in fig. 40With non-setting regions z1~z8It is for be checked to the first determination The method that beneficiary is surveyed with the presence or absence of abnormal payment collection risks is illustrated, and is not the restriction to this programme, had been embodied Cheng Zhong, setting regions z0With non-setting regions z1~z8Region shape, area size and the relationship of bordering on can flexibly be adjusted It is whole.
Second of determination beneficiary p to be detectedxWith the presence or absence of the method for abnormal payment collection risks, synthetic risk rate S is judgedp (px) whether be located in set interval, if synthetic risk rate Sp(px) be located in set interval, determine beneficiary p to be detectedxReceipts Money position is located in setting regions, further, it is determined that beneficiary p to be detectedxThere are abnormal payment collection risks.Compared to the first Determine beneficiary p to be detectedxWith the presence or absence of the method for abnormal payment collection risks, second of determination beneficiary p to be detectedxIt whether there is The criterion of the method for abnormal payment collection risks is set interval, specifically, by judging synthetic risk rate Sp(px) whether fall Enter in set interval to predict beneficiary p to be detectedxGathering position whether be located in set interval, so that it is determined that be detected Beneficiary pxWith the presence or absence of abnormal payment collection risks.It should be appreciated that in the specific implementation process, set interval can also be according to reality Situation carries out the adjustment similar with given threshold, does not illustrate more herein.
The third determines beneficiary p to be detectedxWith the presence or absence of the method for abnormal payment collection risks, according to synthetic risk rate Sp (px) determine beneficiary p to be detectedxThere are the probability of abnormal payment collection risks.
It in the specific implementation process, can be by synthetic risk rate Sp(px) directly as beneficiary p to be detectedxGathering position Setting in the probability in setting regions.Such as, however, it is determined that obtained synthetic risk rate Sp(px) it is 0.8, available prediction knot Fruit: beneficiary p to be detectedxGathering position be located at the probability in setting regions be 80%, it is to be detected it is possible to further determination Beneficiary pxIt is 80% in the presence of the probability collected money extremely, on this basis, is different from first two based on classificating thought and determines exception The method of payment collection risks, the third method for determining abnormal payment collection risks can be used for regression test analysis.
Optionally, beneficiary p to be detected is obtained in determinationxSynthetic risk rate Sp(px) after, receipts to be detected can be investigated Money side pxGathering position history predictive result, for example, if in history predictive result determine (prediction) obtain gathering to be detected Square pxGathering position be located at the number in setting regions be greater than setting number, show beneficiary p to be detectedxOnce it was repeatedly setting It collects money in region, in such a case, it is possible in synthetic risk rate Sp(px) on the basis of distribute a risk increment weight Value will complete the synthetic risk rate S of risk increment weighted value distributionp(px) it is used as beneficiary p to be detectedxFinal synthesis wind Dangerous rate.
In the specific implementation process, setting number and risk increment weighted value can be matched according to level, specifically, The node of setting number can be set to 3 and 5.
For example, if determining in history predictive result, (prediction) obtains beneficiary p to be detectedxGathering position be located at setting area Number in domain is less than or equal to 3, and corresponding risk increment weighted value can be 1, and then determines that final synthetic risk rate is Sp (px)。
In another example if determining in history predictive result, (prediction) obtains beneficiary p to be detectedxGathering position be located at setting Number in region is greater than 3 and less than or equal to 5, and corresponding risk increment weighted value can be 1.1, and then determine final synthesis Relative risk is 1.1Sp(px)。
For another example if determining in history predictive result, (prediction) obtains beneficiary p to be detectedxGathering position be located at setting Number in region is greater than 5, and corresponding risk increment weighted value can be 1.3, and then determines that final synthetic risk rate is 1.3·Sp(px)。
It is appreciated that determining that (prediction) obtains beneficiary p to be detected in history predictive resultxGathering position be located at setting Number in region is bigger, and corresponding risk increment weighted value is bigger, in this way, can be to once repeatedly appearing in setting regions The beneficiary p to be detected of gatheringxIt is predicted as strict as possible to improve the accuracy of prediction.
It is appreciated that can be to beneficiary p to be detected by above-mentioned several methodxGathering position predicted, thus Determine detection beneficiary pxWith the presence or absence of abnormal payment collection risks.
It is appreciated that common prediction beneficiary p to be detectedxGathering position whether be located at the method in setting regions only Pass through direct relative risk S1(px) judged, please continue to refer to Fig. 2, for example, n=8 is taken, more specifically, beneficiary to be detected pxThere are 8 paying parties within the setting period.According to common prediction technique to beneficiary p to be detectedxGathering position carry out Judgement, is only determined by the quantity that position in 8 paying parties is located at the paying party in setting regions.In another example if 8 are paid It is 7 that position, which is located at the quantity of the paying party in setting regions, in money side, then beneficiary p to be detectedxDirect relative risk S1(px) It is 0.875, further, if given threshold takes 0.6, determines that result is 0.875 > 0.6, it is possible thereby to determine receipts to be detected Money side pxGathering position be located in setting regions.
However, according to common prediction technique to beneficiary p to be detectedxGathering position judged, can exist such as Lower defect:
On the one hand, involved sample size may less, beneficiary p to be detectedxWhat is accumulated within the setting period pays Money side may only have very few several, in this way, being affected to the confidence level of judgement (prediction) result, may cause judgement (prediction) As a result confidence level is relatively low.
On the other hand, direct relative risk S is determined by the quantity for the paying party being located in setting regions1(px), then only lead to Cross direct relative risk S1(px) prediction beneficiary p to be detectedxGathering position method anti-interference ability it is weaker.In another example if 8 The position of each paying party is respectively positioned in setting regions in a paying party, but wherein 6 paying parties with beneficiary to be detected pxThe geographical location where payment method, apparatus, the then direct relative risk determined by the above method have deliberately been distorted when being traded S1(px) it is 0.25, further, if given threshold takes 0.6, determine that result is 0.25 < 0.6, it is possible thereby to determine to be detected Beneficiary pxGathering position be not in setting regions, in this way, causing beneficiary p to be detectedxGathering position erroneous judgement and It fails to judge.
On the basis of the above, the thought that the present embodiment is conducted based on risk not only considers and beneficiary p to be detectedxDirectly Associated Receiving information (direct dealing information), it is also contemplated that with beneficiary p to be detectedxThe payment information of indirect association (is handed over indirectly Easy information), Transaction Information quantity (sample size) to be investigated is effectively increased, beneficiary p to be detected can be based onxDimension and Paying party dimension is comprehensively considered, so that it is determined that synthetic risk rate, and then guarantee to obtain based on synthetic risk rate to be detected Beneficiary pxJudgement (prediction) result confidence level with higher and accuracy of gathering position, to realize to gathering to be detected Square pxGathering position Accurate Prediction.
Optionally, continue with beneficiary p to be detectedxThere are in case where 8 paying parties within the setting period, using step Rapid S11 determination obtains direct relative risk S1(px) it is 0.25, indirect relative risk S is obtained using step S12 determination2(px) be 0.875, due to paying party negligible amounts (sample size is less), passing through formula Sp(px)=w1·S1(px)+w2·S2(px) really Determine synthetic risk rate Sp(px) when, it can suitably reduce weighted value w1, in another example, take w1=0.2, w2=0.8, it is determined that comprehensive wind Dangerous rate Sp(px) it is 0.75, if given threshold takes 0.6, determine that result is 0.75 > 0.6, it is possible thereby to determine gathering to be detected Square pxGathering position be located in setting regions.It is appreciated that can effectively be kept away using prediction technique provided by the present embodiment Exempt from the less influence to judgement (prediction) result confidence level of sample size, to improve the accuracy of prediction.
Optionally, continue with beneficiary p to be detectedxThere are in case where 8 paying parties within the setting period, if 8 The position of each paying party is respectively positioned in setting regions in paying party, but wherein 7 paying parties with beneficiary p to be detectedx The geographical location where payment method, apparatus is deliberately distorted when being traded, it is determined that obtain direct relative risk S1(px) be 0.125.But prediction technique provided by the present embodiment can also determine the co-related risks rate of each paying party based on step S12, And then detection beneficiary p is determined based on each co-related risks ratexIndirect relative risk S2(px), in another example, it is true based on step S12 Surely the indirect relative risk S obtained2(px) it is 0.9375.Further, w is taken1=0.2, w2=0.8, pass through formula Sp(px)= w1·S1(px)+w2·S2(px) determine synthetic risk rate Sp(px) it is 0.775, if given threshold takes 0.6, determine that result is 0.775 > 0.6, it is possible thereby to determine beneficiary p to be detectedxGathering position be located in setting regions.It can be seen that using this Prediction technique provided by embodiment can effectively increase the anti-interference of judgement (prediction) result, avoid deliberately distorting paying party The position bring of equipment is judged by accident and fails to judge, even if in the presence of the behavior for deliberately distorting the geographical location where paying the bill method, apparatus, Indirect relative risk S can be passed through2(px) and synthetic risk rate Sp(px) accurately judged and predicted.
In the embodiment of the present application, the thought of risk conduction is it is to be understood that by investigating multiple trading activity realization pair Beneficiary p to be detectedxGathering position prediction.Fig. 5 is please referred to, within the setting period, beneficiary p to be detectedxIt is corresponding Paying party is u1、u2And u3, further, u1Corresponding association beneficiary is being set in the period as p1And p2, further, p1 Corresponding association paying party is being set in the period as u4、u5And u6, still further, association paying party u4It is right within the setting period The association beneficiary answered is p20And p21, so, it is possible by with beneficiary p to be detectedxDirect corresponding limited paying party (u1、u2And u3) carry out the layer-by-layer conduction of trading activity, excavate and extend, by deeper trading activity and more Number of transaction predicts beneficiary p to be detectedxGathering position, on the one hand increase effectively sample size, improve prediction knot On the other hand the confidence level of fruit also avoids the position bring erroneous judgement for deliberately distorting payment method, apparatus and fails to judge, improves pre- Survey the accuracy and reliability of result.
It is appreciated that determining that the accounting of association beneficiary is also provided pre- through this embodiment in step S121 What survey method was realized.For example, determining association beneficiary p please continue to refer to Fig. 21, association beneficiary p2, association beneficiary p3The pass and Join beneficiary p4The accounting of the middle association beneficiary that there are abnormal payment collection risks specifically can be based between each association beneficiary Synthetic risk rate is connect to obtain.Wherein, the indirect synthetic risk rate of each association beneficiary passes through the corresponding receipts of association beneficiary Money information obtains.Further, it is each association beneficiary indirect synthetic risk rate by with step S11, step S12 and step S13 similar method determines.Specifically, it can be based on the corresponding Receiving information of each association beneficiary, each association is obtained and receive The direct relative risk (please referring to step S11) and indirect relative risk (please referring to step S12) of money side, then according to every Direct relative risk and the indirect relative risk of a association beneficiary determine it is each be associated with beneficiary indirect synthetic risk rate (incorporated by reference to Refering to step S13).
Please continue to refer to Fig. 2, to be associated with beneficiary p1For, it can be based on association beneficiary p1Direct relative risk S1 (p1) and indirect relative risk S2(p1) determine association beneficiary p1Indirect synthetic risk rate Sp(p1).For example, association beneficiary p1 Corresponding paying party includes u in preset period of time1、un+1And un+2, it is associated with beneficiary p1Direct relative risk S1(p1) can be based on Paying party u1、un+1And un+2In the accounting of paying party that is located in setting regions obtain, paying party u can also be based onn+1And un+2 In the accounting of paying party that is located in setting regions obtain, similarly, be associated with beneficiary p1Indirect relative risk S2(p1) can be based on Paying party u1、un+1And un+2Co-related risks rate obtain.
Further, association beneficiary p is being determined1Indirect synthetic risk rate Sp(p1) after, can by with step S14 similar method determines association beneficiary p1Gathering position whether be located in setting regions, so that it is determined that association beneficiary p1 With the presence or absence of abnormal payment collection risks, and then determine paying party u1Association beneficiary (p1、p2、p3And p4) middle in the presence of abnormal gathering wind The accounting of the association beneficiary of danger.
It specifically, can be from paying party u1Corresponding all indirect synthetic risk rate (Sp(p1)、Sp(p2)、Sp(p3) and Sp (p4)) in determine be more than preset value indirect synthetic risk rate ratio, using the ratio as paying party u1Association beneficiary (p1、p2、p3And p4) in exist abnormal payment collection risks association beneficiary accounting.For example, if Sp(p1) it is more than preset value, Sp (p2)、Sp(p3) and Sp(p4) be not above preset value, then paying party u1It is more than default in corresponding all indirect synthetic risk rates The ratio of the indirect synthetic risk rate of value is 0.25, further, paying party u1There is abnormal receive in corresponding association beneficiary The accounting of the association beneficiary of money risk is 0.25.Wherein, preset value herein is consistent with the preset value in step S121, presets Value can be identical as given threshold, can also be different, is not limited thereto.Further, it is also possible to reference in step S14 to setting threshold The method that value is adjusted carries out similar adjustment to preset value.
It further, can also be from paying party u1Corresponding all indirect synthetic risk rate (Sp(p1)、Sp(p2)、Sp(p3) And Sp(p4)) in determine the ratio for falling into indirect synthetic risk rate in pre-set interval, using the ratio as paying party u1Association Beneficiary (p1、p2、p3And p4) in exist abnormal payment collection risks association beneficiary accounting.For example, if Sp(p1)、Sp(p3) and Sp(p4) fall into pre-set interval, Sp(p2) do not fall in pre-set interval, then paying party u1Corresponding all indirect integrated risks Ratio in rate more than the indirect synthetic risk rate of preset value is 0.75, further, paying party u1Corresponding association beneficiary The accounting of the middle association beneficiary that there are abnormal payment collection risks is 0.75.Wherein, pre-set interval can be with the setting in step S14 Section is identical, can also be not identical as the set interval in step S14.
Optionally, for setting regions, step S11, the setting regions in step S12 and step S13 can be identical Region, or different zones.It in the specific implementation process, can be by a variety of methods to step S11, step S12 and step Setting regions is configured in rapid S13, the method that wherein several pairs of setting regions are configured is set forth below, certainly, specific In implementation process, however it is not limited to following three kinds of methods.
The first setting regions setting method: step S11, the setting regions in step S12 and step S13 is same area Domain.
For example, according to beneficiary p to be detectedxIt is located at setting regions z in all paying parties within the set period0-1Interior The accounting of paying party determines beneficiary p to be detectedxDirect relative risk S1(px)。
It is set in another example position of being collected money in corresponding relevant beneficiary in preset period of time according to each paying party is located at Determine region z0-1The accounting of interior association beneficiary determines the co-related risks rate of each paying party, and then determines beneficiary to be detected pxIndirect relative risk S2(px)。
For another example if according to beneficiary p to be detectedxSynthetic risk rate Sp(px) determine beneficiary p to be detectedxThere are different Normal payment collection risks, then prediction obtains beneficiary p to be detectedxGathering position be located at setting regions z0-1It is interior.
In this case, the setting regions as criterion in step S11, step S12 and step S13 is setting Region z0-1, in this way, can accurately determine (prediction) beneficiary p to be detectedxGathering position whether be located at setting regions z0-1It is interior.
Second of setting regions setting method: step S11, the setting regions in step S12 and step S13 is not same district Domain.
In this case, setting regions can be multiple, such as setting regions z0-1, setting regions z0-2And setting regions z0-3。
Similarly, beneficiary p to be detected is if desired predictedxGathering position whether be located at setting regions z0-1, can pass through Beneficiary p to be detectedxSynthetic risk rate Sp(px) determine.
It is appreciated that by determining beneficiary p to be detected in step S11xDirect relative risk S1(px) when, it needs to obtain Beneficiary p to be detectedxIt is located at the accounting of the paying party in setting regions in all paying parties within the set period, it should obtaining When accounting, if by setting regions z0-1, setting regions z0-2With setting regions z0-3Union as in step S11 for payment The setting regions that the position of side is determined, obtained accounting is bigger than normal, correspondingly, obtained beneficiary p to be detectedxIt is direct Relative risk S1(px) also bigger than normal.Similarly, if by setting regions z0-1, setting regions z0-2With setting regions z0-3Union as step The setting regions determined in S12 for the gathering position to association beneficiary, the receipts to be detected based on determined by step S12 Money side pxIndirect relative risk S2(px) also bigger than normal, the synthetic risk rate S finally obtainedp(px) set compared to the first setting regions The synthetic risk rate S that the method for setting obtainsp(px) also just bigger than normal.Therefore, in other decision conditions (such as given threshold, set interval Deng) in identical situation, based on second of setting regions setting method to beneficiary p to be detectedxGathering position carry out it is pre- When survey, the gathering position predicted is located at setting regions z0-1Interior probability is larger.More specifically, based on second of setting Zone approach is to beneficiary p to be detectedxGathering position when being predicted, it is easier to by beneficiary p to be detectedxGathering Position is determined in setting regions z0-1It is interior, it will be understood that can be to beneficiary to be detected based on second of setting regions setting method pxGathering position predicted as strict as possible.
In the specific implementation process, the setting of setting regions can carry out according to actual needs, for example, if desired rigorous, The gathering position for predicting to maximum magnitude beneficiary to be detected, avoids omitting, and can be based on second of setting regions setting method The gathering position of beneficiary to be detected is predicted, in another example, the receipts of beneficiary to be detected are if desired more accurately predicted Money position is located at the probability in some setting regions, can be based on the first setting regions setting method to beneficiary to be detected It is predicted gathering position.
In the specific implementation process, step S11, step has been performed a plurality of times in gathering position predicting method provided by the present embodiment Rapid S12 and step S13, to realize to from beneficiary p to be detectedxThe obtained direct dealing information of extending and indirect transaction information into Row analysis and processing, thus to beneficiary p to be detectedxGathering position carry out accurate, reliable prediction, and then ensure effectively, Reliable embargo area gathering supervision and conjunction rule.
Based on inventive concept same in previous embodiment, this specification embodiment also provides a kind of information processing unit 100, Fig. 6 is please referred to, which determines mould including direct relative risk determining module 101, indirect relative risk Block 102, synthetic risk rate determining module 103 and abnormal gathering judgment module 104.
Direct relative risk determining module 101, for obtaining beneficiary to be detected a plurality of Receiving information within the set period, According to the position for the paying party for including in every Receiving information, the direct relative risk of the beneficiary to be detected is determined.
Indirect relative risk determining module 102, for obtaining a plurality of payment information of each paying party, wherein described Payment information be the paying party in preset period of time with the Transaction Information that is associated with beneficiary；It is corresponding from each paying party The accounting that there is the association beneficiary of abnormal payment collection risks is determined in relevant beneficiary, each institute is determined according to the accounting State the co-related risks rate of paying party；According to each co-related risks rate, the indirect relative risk of the beneficiary to be detected is obtained.
Synthetic risk rate determining module 103, for according to the direct relative risk and the indirect relative risk, described in acquisition The synthetic risk rate of beneficiary to be detected.
Abnormal gathering judgment module 104, for determining whether the beneficiary to be detected is deposited according to the synthetic risk rate In the abnormal payment collection risks.
In a kind of optional way, direct relative risk determining module 101 is used for the institute for including from a plurality of Receiving information There is the ratio that the position being located in setting regions is determined in position；The beneficiary to be detected according to the ratio-dependent it is direct Relative risk.
In a kind of optional way, indirect relative risk determining module 102 is used to be directed to each paying party, obtains and is somebody's turn to do The indirect synthetic risk rate of the corresponding each association beneficiary of paying party；Wherein, the indirect integrated risk of each association beneficiary Rate is obtained according to the corresponding a plurality of Receiving information of the association beneficiary；From the corresponding all indirect synthetic risk rates of the paying party Determine the ratio of the indirect synthetic risk rate more than preset value；The accounting is determined according to the ratio.
In a kind of optional way, indirect relative risk determining module 102 is used to obtain the average value of all co-related risks rates； The indirect relative risk of the beneficiary to be detected is obtained according to the average value.
In a kind of optional way, synthetic risk rate determining module 103 for obtain the direct relative risk and it is described between Connect the weighted sum of relative risk；According to the weighted sum, the synthetic risk rate is obtained.
In a kind of optional way, abnormal judgment module 104 of collecting money is for judging whether the synthetic risk rate is more than to set Determine threshold value, obtains judging result；Determine the beneficiary to be detected with the presence or absence of the abnormal gathering according to the judging result Risk.
In a kind of optional way, abnormal judgment module 104 of collecting money is used to characterize the comprehensive wind when the judging result When dangerous rate is more than the given threshold, determining the beneficiary to be detected, there are the abnormal payment collection risks；Wherein, the exception Payment collection risks are the risk collected money in setting regions.
In a kind of optional way, abnormal judgment module 104 of collecting money is used for according to the synthetic risk rate, determine it is described to Detecting beneficiary, there are the probability of the abnormal payment collection risks；According to the probability, determine whether the beneficiary to be detected is deposited In the abnormal payment collection risks.
Based on inventive concept same in previous embodiment, this specification embodiment also provides a kind of computer-readable deposit The step of storage media is stored thereon with computer program, and any the method above is realized when which is executed by processor.
Based on inventive concept same in previous embodiment, the embodiment of this specification also provides a kind of computer and sets It is standby, as shown in fig. 7, comprises memory 204, processor 202 and being stored on memory 204 and can run on processor 202 Computer program, the step of processor 202 realizes any the method above when executing described program.
Wherein, in Fig. 7, bus architecture (is represented) with bus 200, and bus 200 may include any number of interconnection Bus and bridge, bus 200 will include the one or more processors represented by processor 202 and what memory 204 represented deposits The various circuits of reservoir link together.Bus 200 can also will peripheral equipment, voltage-stablizer and management circuit etc. it Various other circuits of class link together, and these are all it is known in the art, therefore, no longer carry out further to it herein Description.Bus interface 205 provides interface between bus 200 and receiver 201 and transmitter 203.Receiver 201 and transmitter 203 can be the same element, i.e. transceiver, provide for the list over a transmission medium with various other terminal equipment in communication Member.Processor 202 is responsible for management bus 200 and common processing, and memory 204 can be used for storage processor 202 and exist Execute used data when operation.
By one or more embodiment of this specification, this specification has the advantages that or advantage:
Information processing method disclosed in this specification embodiment, device and computer equipment can not only be based on to be checked The Receiving information for surveying beneficiary obtains the direct relative risk of beneficiary to be detected, additionally it is possible to be based on corresponding with beneficiary to be detected The payment information of paying party obtains the indirect relative risk of beneficiary to be detected, is then based on direct relative risk and indirect relative risk is true Surely synthetic risk rate is obtained.By increasing the investigation to the payment information of paying party, transaction letter to be investigated can be effectively increased It ceases quantity (sample size), the confidence level of synthetic risk rate can not only be improved, additionally it is possible to improve the anti-interference of synthetic risk rate Property, this transaction agonistic behavior of paying party position is distorted in reduction influences the synthetic risk rate bring.Guaranteeing integrated risk Under the premise of the confidence level and anti-interference of rate, synthetic risk rate can be carried out based on the methods of given threshold or set interval Analysis, and then predict whether the gathering position of beneficiary to be detected is located in setting regions according to synthetic risk rate, it can also lead to It crosses synthetic risk rate itself and determines that the gathering position of beneficiary to be detected is located at the probability in setting regions, so, it is possible to be based on Synthetic risk rate carries out accurate, reliable prediction to the gathering position of beneficiary to be detected, so that it is determined that beneficiary to be detected is It is no to there are abnormal payment collection risks.
Algorithm and display are not inherently related to any particular computer, virtual system, or other device provided herein. Various general-purpose systems can also be used together with teachings based herein.As described above, it constructs required by this kind of system Structure be obvious.In addition, this specification is also not for any particular programming language.It should be understood that can use each Kind programming language realizes the content of this specification described herein, and the description done above to language-specific is to disclose The preferred forms of this specification.
In the instructions provided here, numerous specific details are set forth.It is to be appreciated, however, that the reality of this specification Applying example can practice without these specific details.In some instances, well known method, knot is not been shown in detail Structure and technology, so as not to obscure the understanding of this specification.
Similarly, it should be understood that in order to simplify the disclosure and help to understand one or more of the various inventive aspects, In Above in the description of the exemplary embodiment of this specification, each feature of this specification is grouped together into single reality sometimes It applies in example, figure or descriptions thereof.However, the disclosed method should not be interpreted as reflecting the following intention: i.e. required This specification of protection requires features more more than feature expressly recited in each claim.More precisely, such as As following claims reflect, inventive aspect is all features less than single embodiment disclosed above. Therefore, it then follows thus claims of specific embodiment are expressly incorporated in the specific embodiment, wherein each right is wanted It asks in itself all as the separate embodiments of this specification.
Those skilled in the art will understand that can be carried out adaptively to the module in the equipment in embodiment Change and they are arranged in one or more devices different from this embodiment.It can be the module or list in embodiment Member or component are combined into a module or unit or component, and furthermore they can be divided into multiple submodule or subelement or Sub-component.Other than such feature and/or at least some of process or unit exclude each other, it can use any Combination is to all features disclosed in this specification (including adjoint claim, abstract and attached drawing) and so disclosed All process or units of what method or apparatus are combined.Unless expressly stated otherwise, this specification is (including adjoint power Benefit require, abstract and attached drawing) disclosed in each feature can carry out generation with an alternative feature that provides the same, equivalent, or similar purpose It replaces.
In addition, it will be appreciated by those of skill in the art that although some embodiments in this include institute in other embodiments Including certain features rather than other feature, but the combination of the feature of different embodiment means the model for being in this specification Within enclosing and form different embodiments.For example, in the following claims, embodiment claimed it is any One of can in any combination mode come using.
The various component embodiments of this specification can be implemented in hardware, or to transport on one or more processors Capable software module is realized, or is implemented in a combination thereof.It will be understood by those of skill in the art that can make in practice It realized with microprocessor or digital signal processor (DSP) according to the gateway of this specification embodiment, proxy server, be The some or all functions of some or all components in system.This specification is also implemented as being retouched here for executing The some or all device or device programs (for example, computer program and computer program product) for the method stated. Such program for realizing this specification can store on a computer-readable medium, or can have one or more letter Number form.Such signal can be downloaded from an internet website to obtain, and perhaps be provided on the carrier signal or with any Other forms provide.
This specification is limited it should be noted that above-described embodiment illustrates rather than this specification, and Those skilled in the art can be designed alternative embodiment without departing from the scope of the appended claims.In claim In, any reference symbol between parentheses should not be configured to limitations on claims.Word "comprising" is not excluded for depositing In element or step not listed in the claims.Word "a" or "an" located in front of the element do not exclude the presence of it is multiple this The element of sample.This specification can be by means of including the hardware of several different elements and by means of properly programmed computer To realize.In the unit claims listing several devices, several in these devices can be by same hard Part item embodies.The use of word first, second, and third does not indicate any sequence.These words can be explained For title.

Claims (18)

1. a kind of information processing method, which comprises
Beneficiary to be detected a plurality of Receiving information within the set period is obtained, according to the paying party for including in every Receiving information Position, determine the direct relative risk of the beneficiary to be detected；
Obtain a plurality of payment information of each paying party, wherein the payment information is the paying party in preset period of time It is interior with the Transaction Information for being associated with beneficiary；
From each paying party it is corresponding the association beneficiary that there are abnormal payment collection risks is determined in relevant beneficiary Accounting determines the co-related risks rate of each paying party according to the accounting；
According to each co-related risks rate, the indirect relative risk of the beneficiary to be detected is obtained；
According to the direct relative risk and the indirect relative risk, the synthetic risk rate of the beneficiary to be detected is obtained；
According to the synthetic risk rate, determine the beneficiary to be detected with the presence or absence of the abnormal payment collection risks.
2. the method as described in claim 1, described according to the synthetic risk rate, determine whether the beneficiary to be detected is deposited In the abnormal payment collection risks, comprising:
Judge whether the synthetic risk rate is more than given threshold, obtains judging result；According to judging result determination Beneficiary to be detected is with the presence or absence of the abnormal payment collection risks.
3. method according to claim 2, described to determine that the beneficiary to be detected whether there is according to the judging result The exception payment collection risks, comprising:
When the judging result, which characterizes the synthetic risk rate, is more than the given threshold, determine that the beneficiary to be detected is deposited In the abnormal payment collection risks；Wherein, the abnormal payment collection risks are the risk collected money in setting regions.
4. the method as described in claim 1 determines the beneficiary to be detected with the presence or absence of institute according to the synthetic risk rate State abnormal payment collection risks, comprising:
According to the synthetic risk rate, determining the beneficiary to be detected, there are the probability of the abnormal payment collection risks；
According to the probability, determine the beneficiary to be detected with the presence or absence of the abnormal payment collection risks.
5. the method as described in claim 1, the position is that the paying party and the beneficiary to be detected generate when trading Geographical location where the payer terminal equipment, the position according to the paying party for including in every Receiving information, really The direct relative risk of the fixed beneficiary to be detected, comprising:
From the ratio for determining the position being located in setting regions in all positions that a plurality of Receiving information includes；
The direct relative risk of the beneficiary to be detected according to the ratio-dependent.
6. the method as described in claim 1, the determination from each corresponding relevant beneficiary of the paying party is deposited In the accounting of the association beneficiary of abnormal payment collection risks, comprising:
For each paying party, the indirect synthetic risk rate of each association beneficiary corresponding with the paying party is obtained；Its In, the indirect synthetic risk rate of each association beneficiary is obtained according to the corresponding a plurality of Receiving information of the association beneficiary；
The ratio of the indirect synthetic risk rate more than preset value is determined from the corresponding all indirect synthetic risk rates of the paying party；
The accounting is determined according to the ratio.
7. the method as described in claim 1, described according to each co-related risks rate, the beneficiary to be detected is obtained Indirect relative risk, comprising:
Obtain the average value of all co-related risks rates；
The indirect relative risk of the beneficiary to be detected is obtained according to the average value.
It is described according to the direct relative risk and the indirect relative risk 8. the method as described in claim 1, obtain it is described to Detect the synthetic risk rate of beneficiary, comprising:
Obtain the weighted sum of the direct relative risk and the indirect relative risk；
According to the weighted sum, the synthetic risk rate is obtained.
9. a kind of information processing unit, comprising:
Direct relative risk determining module, for obtaining beneficiary to be detected a plurality of Receiving information within the set period, according to every The position for the paying party for including in Receiving information, determines the direct relative risk of the beneficiary to be detected；
Indirect relative risk determining module, for obtaining a plurality of payment information of each paying party, wherein the payment information For the paying party in preset period of time with the Transaction Information that is associated with beneficiary；It is relevant from each corresponding of paying party It determines there is the accounting of the association beneficiary of abnormal payment collection risks in beneficiary, each paying party is determined according to the accounting Co-related risks rate；According to each co-related risks rate, the indirect relative risk of the beneficiary to be detected is obtained；
Synthetic risk rate determining module, for obtaining described to be detected according to the direct relative risk and the indirect relative risk The synthetic risk rate of beneficiary；
Abnormal gathering judgment module, for determining the beneficiary to be detected with the presence or absence of described according to the synthetic risk rate Abnormal payment collection risks.
10. device as claimed in claim 9, the abnormal gathering judgment module, for whether judging the synthetic risk rate More than given threshold, judging result is obtained；Determine the beneficiary to be detected with the presence or absence of described different according to the judging result Normal payment collection risks.
11. device as claimed in claim 10, the abnormal gathering judgment module, described in being characterized when the judging result When synthetic risk rate is more than the given threshold, determining the beneficiary to be detected, there are the abnormal payment collection risks；Wherein, institute Stating abnormal payment collection risks is the risk collected money in setting regions.
12. device as claimed in claim 9, the abnormal gathering judgment module, for determining according to the synthetic risk rate There are the probability of the abnormal payment collection risks for the beneficiary to be detected；According to the probability, the beneficiary to be detected is determined With the presence or absence of the abnormal payment collection risks.
13. device as claimed in claim 9, the position is that the paying party and the beneficiary to be detected generate when trading Geographical location where the payer terminal equipment, the direct relative risk determining module, for believing from a plurality of gathering The ratio for the position being located in setting regions is determined in all positions that breath includes；The receipts to be detected according to the ratio-dependent The direct relative risk of money side.
14. device as claimed in claim 9, the indirect relative risk determining module is obtained for being directed to each paying party Take the indirect synthetic risk rate of each association beneficiary corresponding with the paying party；Wherein, each association beneficiary is indirect comprehensive Relative risk is closed to be obtained according to the corresponding a plurality of Receiving information of the association beneficiary；From the corresponding all indirect comprehensive wind of the paying party The ratio of the indirect synthetic risk rate more than preset value is determined in dangerous rate；The accounting is determined according to the ratio.
15. device as claimed in claim 9, the indirect relative risk determining module, for obtaining all co-related risks rates Average value；The indirect relative risk of the beneficiary to be detected is obtained according to the average value.
16. device as claimed in claim 9, the synthetic risk rate determining module, for obtain the direct relative risk and The weighted sum of the indirect relative risk；According to the weighted sum, the synthetic risk rate is obtained.
17. a kind of computer readable storage medium, is stored thereon with computer program, power is realized when which is executed by processor Benefit requires the step of any one of 1-8 the method.
18. a kind of computer equipment including memory, processor and stores the meter that can be run on a memory and on a processor The step of calculation machine program, the processor realizes any one of claim 1-8 the method when executing described program.
CN201910617897.5A 2019-07-10 2019-07-10 Information processing method and device and computer equipment Active CN110443617B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910617897.5A CN110443617B (en) 2019-07-10 2019-07-10 Information processing method and device and computer equipment

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910617897.5A CN110443617B (en) 2019-07-10 2019-07-10 Information processing method and device and computer equipment

Publications (2)

Publication Number Publication Date
CN110443617A true CN110443617A (en) 2019-11-12
CN110443617B CN110443617B (en) 2023-05-02

Family

ID=68430020

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910617897.5A Active CN110443617B (en) 2019-07-10 2019-07-10 Information processing method and device and computer equipment

Country Status (1)

Country Link
CN (1) CN110443617B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113723759A (en) * 2021-07-30 2021-11-30 北京淇瑀信息科技有限公司 Method and device for providing Internet service for equipment based on equipment intention degree and equipment risk degree

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101286258A (en) * 2007-03-20 2008-10-15 三电有限公司 Electronic money charger
CN104574074A (en) * 2013-10-22 2015-04-29 李宏 Method and system for real-time payment and collection of payer and beneficiary
US20150278809A1 (en) * 2014-03-27 2015-10-01 C1 Bank System and method for distributed real time authorization of payment transactions
CN107578238A (en) * 2017-08-08 2018-01-12 阿里巴巴集团控股有限公司 A kind of risk control method and equipment
CN107844977A (en) * 2017-10-09 2018-03-27 ***股份有限公司 A kind of method of payment and device
CN108280640A (en) * 2018-01-11 2018-07-13 口碑(上海)信息技术有限公司 The payment result page shows method and device
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
CN109063920A (en) * 2018-08-20 2018-12-21 阿里巴巴集团控股有限公司 A kind of transaction risk recognition methods, device and computer equipment
CN109615468A (en) * 2018-12-03 2019-04-12 大汉电子商务有限公司 A kind of receipts payment administrative system and method

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101286258A (en) * 2007-03-20 2008-10-15 三电有限公司 Electronic money charger
CN104574074A (en) * 2013-10-22 2015-04-29 李宏 Method and system for real-time payment and collection of payer and beneficiary
US20150278809A1 (en) * 2014-03-27 2015-10-01 C1 Bank System and method for distributed real time authorization of payment transactions
CN107578238A (en) * 2017-08-08 2018-01-12 阿里巴巴集团控股有限公司 A kind of risk control method and equipment
CN107844977A (en) * 2017-10-09 2018-03-27 ***股份有限公司 A kind of method of payment and device
CN108280640A (en) * 2018-01-11 2018-07-13 口碑(上海)信息技术有限公司 The payment result page shows method and device
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
CN109063920A (en) * 2018-08-20 2018-12-21 阿里巴巴集团控股有限公司 A kind of transaction risk recognition methods, device and computer equipment
CN109615468A (en) * 2018-12-03 2019-04-12 大汉电子商务有限公司 A kind of receipts payment administrative system and method

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
LUCA POLLONINI等: "Self-contained diffuse optical imaging system for real-time detection and localization of vascular occlusions", 《2015 37TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)》 *
冷晓萍等: "以保险业虚列费用为例探讨异常资金流追踪审计", 《审计广角》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113723759A (en) * 2021-07-30 2021-11-30 北京淇瑀信息科技有限公司 Method and device for providing Internet service for equipment based on equipment intention degree and equipment risk degree
CN113723759B (en) * 2021-07-30 2024-06-04 北京淇瑀信息科技有限公司 Method and device for providing Internet service for equipment based on equipment intention degree and equipment risk degree

Also Published As

Publication number Publication date
CN110443617B (en) 2023-05-02

Similar Documents

Publication Publication Date Title
US10102530B2 (en) Card fraud detection utilizing real-time identification of merchant test sites
AU2002244117B2 (en) System and method for depicting on-line transactions
EP3121782A1 (en) Systems and methods for identifying information related to payment card breaches
CN106506454A (en) Fraud business recognition method and device
CN106415576A (en) System for the measurement and automated accumulation of diverging cyber risks, and corresponding method thereof
TWI706356B (en) Method and device for business drainage
CN110599670B (en) Abnormal detection method and system for number of paper money in money box, server and financial equipment
CN109102301A (en) A kind of payment air control method and system
CN107026848A (en) Business authorization method and device
US20220188828A1 (en) Transaction generation for analytics evaluation
US8666829B1 (en) Detecting fraudulent event listings
US20230206333A1 (en) Systems and methods for measurement of data to provide decision support
AU2015233168C1 (en) Transport system user inspection
CN106845881A (en) A kind of detection method of stock abnormal data, device and electronic equipment
CN110348851A (en) Pay Proxy Method, system, electronic equipment and storage medium
CN110443617A (en) Information processing method, device and computer equipment
CN109146148A (en) A kind of determination method and device of remaining sum prediction deviation reason
US10430793B2 (en) Fraud management system and method
CN112328901B (en) Service recommendation method based on cloud computing and block chain finance and cloud computing system
AU2014203818A1 (en) Fraud management system and method
CN115689571A (en) Abnormal user behavior monitoring method, device, equipment and medium
CN108205888A (en) A kind of method and device for judging that passenger is out of the station
CN108230672A (en) A kind of station platform information confirmation method and device
CN114358479A (en) E-commerce platform return goods remote verification method and device, electronic equipment and storage medium
CN108074082A (en) A kind of data transfer control method and relevant device, system

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
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: 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.

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.

GR01 Patent grant
GR01 Patent grant