CN110930102A - Payment method, device and system - Google Patents
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Abstract
The invention discloses a payment method, a payment device and a payment system, wherein the method comprises the steps of judging whether transaction information of an article meets payment conditions; when the article transaction information accords with the payment condition, calculating an auditing coefficient of the article; and determining a payment mode to pay based on the auditing coefficient. The payment method is strong in universality, automatic payment of the articles is realized, the auditing workload of a payment auditor is reduced, the working efficiency is improved, and the cost is saved.
Description
Technical Field
The invention belongs to the technical field of computers, and particularly relates to a payment method, device and system.
Background
For the vehicles which are priced and wait for applying for the first payment in the business process, a payment auditor needs to manually audit the vehicles and determines whether to submit the vehicles to a financial specialist for payment, the business mode has the following problems that along with the rapid development of company business, the workload of the payment auditor is large, the existing mass auditing task is difficult to complete, the number of auditors can only be expanded, and the labor cost is too high; and the payment auditor can only determine the vehicle audit condition by self experience, which causes the arbitration or re-transaction of vehicles with problems due to audit, wastes manpower and material resources and causes the loss of company performance.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a payment method, a payment device and a payment system.
In view of this, the present invention aims to provide a payment method, which adopts the following technical scheme:
a method of payment, the method comprising,
judging whether the transaction information of the article meets the payment condition;
when the article transaction information accords with the payment condition, calculating an auditing coefficient of the article;
and determining a payment mode to pay based on the auditing coefficient.
Further, the payment condition includes a legitimacy condition of the article.
Further, the legitimacy condition includes one or more of the following conditions,
whether the item transaction information is complete and whether there are more than a first number of historical items of the same type.
Further, the method also comprises the step of executing manual checking payment when the article transaction information does not accord with the payment condition.
Further, the calculating the audit coefficient of the article further comprises,
and calculating the auditing coefficient based on the comprehensive scoring value and the average scoring value of the article.
Further, determining a composite score value for the item by,
calculating a composite score value for the item based on the score values and weights corresponding to the one or more dimensional conditions for the item.
Further, the calculation formula of the comprehensive score value of the article is as follows,
Score1＝A1+A2+……+An
wherein A is1To AnRespectively, the product of the score value and the weight of one or more dimension conditions of the article, wherein n represents n dimension conditions.
Further, determining an average value of the score for the item,
obtaining one or more historical items of the same type as the item in a historical sample;
determining an average value of credit for the item based on the item and one or more historical items.
Further, determining the average score value for the item further comprises,
recording a sample number of the one or more historical items;
calculating cosine values of the article and each historical article in one or more historical articles respectively;
selecting a second quantity of historical articles in the top ranking from the one or more historical articles based on the cosine value size reduction ranking;
respectively calculating the comprehensive scoring value of each historical item in the second quantity of historical items;
and calculating the average scoring value of the item based on the comprehensive scoring value of each historical item.
Further, the average score value of the item is an average value of the sum of the comprehensive score values of the historical items in the second quantity of historical items.
Further, determining the average score value for the item further comprises,
and when the sample number of the one or more historical articles is less than the second number, selecting a first number of historical articles from the one or more historical articles.
Further, the cosine value is calculated by,
wherein A is1To AnThe product of the value of credit and the weight of one or more dimension conditions of the item respectively; b is1To BnThe product of the scoring value and the weight of one or more dimension conditions of any calendar item respectively; wherein n represents n dimensional conditions, and n is more than or equal to 1.
Further, the determining a payment method to pay based on the audit coefficient includes,
when the auditing coefficient is greater than or equal to a preset coefficient, executing automatic payment; or the like, or, alternatively,
and when the auditing coefficient is less than the preset coefficient, executing manual auditing payment.
Further, one or more dimensional conditions including,
item status rating, item price rating, item cost rating.
It is also an object of the present invention to provide a payment device, said device comprising,
the judging module is used for judging whether the transaction information of the article meets the payment condition;
the calculation module is used for calculating the auditing coefficient of the article when the article transaction information accords with the payment condition;
and the determining module is used for determining a payment mode to pay based on the auditing coefficient.
Further, the calculation module is further configured to calculate a composite score value and an average score value of the item.
It is also an object of the invention to provide a payment system comprising at least one processor and at least one memory;
the memory stores a computer program for executing the method, and the processor calls the computer program in the memory to execute the method.
The payment method of the invention is based on the payment condition and the audit coefficient, realizes the automatic payment of the article through double audits, so that the article audit result has authority, and further, the audit coefficient of the article is calculated through the dimension condition and the corresponding credit value and weight thereof, thereby ensuring the accuracy of the automatic payment audit of the article; therefore, the payment method solves the contradiction that the existing business personnel system cannot bear huge checking business volume, improves the checking response speed and efficiency, and reduces the labor cost.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 shows a schematic flow chart of a payment method according to an embodiment of the invention;
FIG. 2 is a schematic diagram illustrating an audit coefficient calculation flow according to an embodiment of the present invention;
FIG. 3 is a flow chart illustrating calculation of an average score value according to an embodiment of the present invention;
FIG. 4 shows another payment method flow diagram of an embodiment of the invention;
FIG. 5 is a schematic diagram of a payment device according to an embodiment of the present invention;
fig. 6 shows a schematic structural diagram of a payment system according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a payment method is introduced in the embodiment of the present invention, and the method includes, first, determining whether transaction information of an article meets payment conditions; then, when the transaction information of the article accords with the payment condition, calculating an auditing coefficient of the article; and finally, determining a payment mode to pay based on the auditing coefficient. By the payment method, whether the goods have the automatic payment condition is automatically checked, the automatic payment of the goods is realized, the checking workload of a payment checker is reduced, the working efficiency is improved, and the cost is saved.
More specifically, the present invention is exemplified by a used vehicle transaction, but is not limited to a used vehicle transaction, and other transactions for other articles may be applicable to the present invention.
In the second-hand vehicle transaction process, the payment condition of the vehicle comprises one or more of the following conditions, whether the vehicle has unprocessed violation of regulations, whether all kinds of certificates of the vehicle are complete, whether all kinds of certificates of the vehicle owner are complete, whether the payment information of the vehicle owner is complete, whether the historical vehicles which are higher than the first quantity and have the same vehicle type of the vehicle to be paid exist. Preferably, before determining whether the transaction information of the article meets the payment condition, the transaction information of the vehicle to be paid needs to be recorded, wherein the transaction information of the vehicle to be paid includes vehicle conditions, vehicle certificates, vehicle owner payment information, vehicle conditions, vehicle types of the vehicle, and the like. The vehicle certificate includes various certificates such as a vehicle driving certificate, a vehicle registration certificate, a vehicle purchase additional fee certificate, a vehicle purchase invoice and the like, but is not limited to the above certificates, and may also include other necessary certificates, such as an operation certificate and the like. The owner certificate comprises an owner identity card and the like. The payment information of the vehicle owner comprises a bank card number, an identification card number, a name and the like of the vehicle owner. The presence of the historical vehicles of the same vehicle type is higher than a first number, wherein the first number may be configured as appropriate. Preferably, the first number may be configured to be 5, and further preferably, the first number is smaller than or equal to the second number. The payment condition of the article is configured based on the necessary transaction information of the transaction article, or the transaction information of the article is input based on the payment condition of the article, so that the automatic audit of the article to be paid is achieved.
Further, when transaction information of the vehicle to be paid is checked based on the payment condition, when the transaction information of the vehicle to be paid does not accord with the payment condition, the transaction information of the vehicle to be paid is sent to a payment checker, and the payment checker checks and finally executes manual payment; and when the transaction information of the vehicle to be paid meets the payment condition, performing further payment verification on the vehicle to be paid. The integrity of the transaction information of the vehicle to be paid is preliminarily screened by setting the payment condition, when one or more transaction information in the vehicle to be paid does not meet the payment condition, the transaction information is directly sent to a payment auditor and is manually audited by the payment auditor, the payment method ensures that automatic audit payment is more rigorous, and the integrity and the accuracy of the automatic payment information of the article are ensured.
Further, calculating an auditing coefficient of the vehicle to be paid; specifically, as shown in fig. 2, the auditing coefficient is calculated based on the comprehensive Score value and the average Score value of the vehicle to be paid, and first, the comprehensive Score value Score1 of the vehicle to be paid is calculated; then, calculating an average Score value Score2 of the vehicle to be paid; finally, the ratio of the vehicle to be paid integrated Score value Score1 to the average Score value Score2 is calculated. The ratio is an audit coefficient of the vehicle to be paid. More specifically, the comprehensive average value Score1 of the vehicles to be paid is,
Score1＝A1+A2+……+An
wherein A is1To AnAre respectively as followsThe product of the value of credit and the weight of one or more dimensional conditions of the vehicle to be paid, n representing n dimensional conditions.
As shown in fig. 3, the specific steps of calculating the average Score value Score2 of the vehicle to be paid are as follows,
based on big data processing analysis, screening out historical vehicles of the same family as the vehicle to be paid from the historical orders, and forming a result set R1 by using the screened historical vehicles;
calculating cosine values of the respective historical vehicles and the vehicle to be paid based on the result set R1, by,
wherein A is1To AnThe products of the scoring values and the weights of one or more dimension conditions of the vehicle to be paid respectively; b is1To BnThe products of the scores and the weights of the one or more dimension conditions of each historical vehicle are respectively;
cosine values of each historical vehicle and the vehicle to be paid in a result set R1 are obtained through calculation, wherein the cosine values are cos theta 1, cos theta 2, … … and cos theta m, m represents that m historical vehicles are included in the result set R1, and m is larger than or equal to 1;
determining historical vehicles for calculating the average Score value Score2 of the vehicles to be paid; the historical vehicles in the result set R1 are sorted in a descending order based on the sizes of the cosine values of each historical vehicle in the result set R1 and the vehicle to be paid; wherein the size of the cosine value represents the similarity of the vehicle to be paid and each historical vehicle in the result set R1, and the larger the cosine value is, the higher the similarity is;
selecting a second, top-ranked number of historical vehicles from the result set R1;
respectively calculating the comprehensive score value of each historical vehicle in the second quantity of historical vehicles;
calculating the average Score value of the vehicle to be paid based on the integrated Score values of the respective historical items, preferably, the integrated Score values of the respective historical items are Score11, Score12, … … and Score1L, wherein L represents the number of the historical vehicles for which the average Score value of the vehicle to be paid is calculated, and then the average Score value Score2 is:
the audit coefficient k of the vehicle to be paid is satisfied,
the auditing coefficient of the vehicle to be paid is calculated and analyzed based on the big data, so that the auditing coefficient is more authoritative, and the accuracy of vehicle transaction is ensured.
Preferably, before calculating the cosine values of each historical vehicle and the vehicle to be paid, the method further comprises,
calculating a dimension vector of the vehicle to be paid and one or more historical vehicles;
wherein A is1To AnRespectively, the product of the value of credit and the weight of one or more dimensional conditions of the vehicle to be paid, said A therefore1To AnComposing the vehicle vector to be paid as a (A)1,A2...,An)；B1To BnThe product of the score value and the weight of one or more dimension conditions of each historical vehicle, so that B1To BnAny historical vehicle dimension vector in the historical vehicles is B (B)1,B2,...,Bn)；
Therefore, the cosine values of each historical vehicle and the vehicle to be paid are the cosine values of the vehicle vector a to be paid and any historical vehicle vector b,
further preferably, the calculating the average score value of the vehicle to be paid may further include, first, forming a result set R2 by cos θ 1, cos θ 2, … … and cos θ m, and sorting cosine values in the result set R2 according to the size of the cosine values; next, based on the number of cosine values in the result set R2, the number Num of historical vehicles for calculating the Score2 average Score value is determined. If the number of cosine values in the result set R2 is greater than or equal to the second number, Num is equal to the second number; if the number of cosine values in the result set R2 is less than the second number, Num is equal to the first number. Then, calculating comprehensive scoring values of the historical vehicles respectively corresponding to the Num cosine values; and finally, calculating the average value of the sum of the Num historical vehicle comprehensive score values, wherein the average value is the average score value of the vehicle to be paid.
Further preferably, the average score value of the vehicle to be paid is calculated, and a preset number of historical vehicles of the same vehicle type as the vehicle to be paid are screened out from historical orders based on big data processing analysis; and then, calculating the average score value of the vehicle to be paid based on the comprehensive score value of each historical vehicle in the preset number of historical vehicles, wherein the calculation method is the same as the method and is not repeated.
Further, the payment method also comprises the step of configuring a preset coefficient, and when the audit coefficient k is greater than or equal to a preset coefficient, automatic payment is executed; or when the audit coefficient k is smaller than a preset coefficient, executing manual audit payment. Therefore, the payment method solves the contradiction that the existing business personnel system cannot bear huge auditing business volume, and integrally enhances the business capacity of the company.
Further specifically, the payment method further comprises the step of configuring the dimension of the vehicle, wherein the dimension of the vehicle comprises one or more dimension conditions and grading values and weights corresponding to the one or more dimension conditions, and the dimension conditions comprise a vehicle condition grade, a vehicle damage grade, a service cost grade, a vehicle equipment comprehensive grade, an oil inspection abnormal item ratio, an electromechanical inspection abnormal item ratio, paint surface repair, a vehicle money price, a meter display mileage and a vehicle age depreciation rate. Wherein the configuring the dimension of the vehicle further comprises configuring the weight of one or more dimension conditions, and the sum of the weights of the dimension conditions is 100%. Preferably, the vehicle models or vehicle series are different, and the dimension condition and/or the weight configured by the dimension condition are different. The dimension conditions of the trading vehicles are configured and the weights of the dimension conditions are configured based on big data analysis, the proportion of the vehicle receiving weights can be flexibly configured in real time according to the rapidly changing market demands, and the rapid development of the individual vehicle selling business of a company is facilitated.
Further, the list names of one or more of the vehicle dimensions are C1, C2, … …, Cn, respectively; the corresponding score values of the one or more dimension conditions are S1, S2, … … and Sn respectively; the weights corresponding to the one or more dimension conditions are P1, P2, … … and Pn respectively; n represents that the vehicle dimension comprises n dimension conditions and n is larger than or equal to 1. In the embodiment of the present invention, therefore, the condition that n is 9 dimensions is set, the vehicle dimensions are as shown in table 1,
TABLE 1 vehicle dimensions
| Dimension (d) of | Value of credit | Weight of | Rank name |
| Vehicle condition rating score | S1 | P1 | C1 |
| Vehicle damage rating scoring | S2 | P2 | C2 |
| Cost of service rating score | S3 | P3 | C3 |
| Comprehensive grading of vehicle framework, appearance, interior trim, electric appliance and working condition | S4 | P4 | C4 |
| Oil check outlier proportion score | S5 | P5 | C5 |
| Electromechanical inspection outlier proportion scoring | S6 | P6 | C6 |
| Paint repair scoring | S7 | P7 | C7 |
| Vehicle money price scoring | S8 | P8 | C8 |
| Scoring mileage and vehicle age depreciation rate | S9 | P9 | C9 |
In table 1, the P1+ P2+ P3+ P4+ P5+ P6+ P7+ P8+ P9 is 100%, and preferably, the values of P1 to P9 may be configured as (but not limited to) 20%, 10%, 5%, 15%, 5%, 10%, 15%; and the score values of all dimension conditions in the vehicle dimensions are recorded according to the actual vehicle conditions of the vehicles, and the score values of the dimension conditions in the vehicle dimensions corresponding to any vehicle have uniqueness. Preferably, the scoring of any dimension condition is 10 points, but is not limited to 10 points, and can be 100 points, etc. More specifically, A is1、A2、……、AnRespectively satisfy A1＝S1*P1，A2＝S2*P2，……，AnSn × Pn; b is1、B2、……、BnSatisfies B1＝S1*P1，B2＝S2*P2，……，BnSn × Pn. Based on the configured vehicle dimension, the vehicle auditing is more systematized, the auditing purpose in the vehicle transaction process is further enhanced, and the transaction efficiency is improved.
Further, taking the vehicle to be paid as an example, which is popular, as shown in fig. 4, the payment method performed on the vehicle to be paid specifically includes the following steps,
step one, a first filter judges whether a vehicle to be paid meets a payment condition, if so, step two is executed, and if not, manual check payment is executed; wherein the payment condition comprises whether 1 vehicle is a historical vehicle with a vehicle type sharp to the public;
step two, the second filter judges whether the auditing coefficient of the vehicle to be paid is greater than or equal to the preset coefficient, and if the auditing coefficient of the vehicle to be paid is greater than or equal to the preset coefficient, automatic payment is executed; and if the checking coefficient of the vehicle to be paid is smaller than the preset coefficient, executing manual checking and payment.
The second step also comprises a second filter for calculating the auditing coefficient of the vehicle to be paid, and specifically comprises the following steps,
taking the vehicle dimensions of table 2 as an example,
TABLE 2 vehicle dimension
| Dimension (d) of | Value of credit | Weight of | Rank name |
| Vehicle condition rating score | S1 | 80％ | C1 |
| Vehicle money price scoring | S2 | 20％ | C2 |
The second filter calculates a composite score value of the vehicle to be paid,
the vehicle dimensions of the vehicle to be paid are shown in table 3,
TABLE 3 vehicle dimension to be paid
| Dimension (d) of | Value of credit | Weight of | Rank name |
| Vehicle condition rating score | 5 | 80％ | C1 |
| Vehicle money price scoring | 8 | 20％ | C2 |
As can be seen from table 3, the composite score of the vehicle to be paid is,
Score1＝5*80％+8*20％
score1 ═ 5.6 for the vehicle to be paid;
the second filter calculates the average value of credit for the vehicle to be paid,
extracting historical vehicles with vehicle type sharp to the public from massive historical order data based on big data, and taking the example of extracting 2 historical vehicles as an example, wherein the result set R1 is formed by the 2 historical vehicles;
the vehicle dimensions of the 2 historical vehicles are as shown in tables 4 and 5 for example,
TABLE 4 History vehicle 1 dimension
| Dimension (d) of | Value of credit | Weight of | Rank name |
| Vehicle condition rating score | 8 | 80％ | C1 |
| Vehicle money price scoring | 9 | 20％ | C2 |
TABLE 5 History vehicle 2-dimension
| Dimension (d) of | Value of credit | Weight of | Rank name |
| Vehicle condition rating score | 7 | 80％ | C1 |
| Vehicle money price scoring | 9 | 20％ | C2 |
The dimension vector a of the vehicle to be paid is a (4, 1.6), the dimension vector b1 of the historical vehicle 1 is b1(6.4, 1.8), the dimension vector b2 of the historical vehicle 2 is b2(5.6, 1.8),
the cosine values of the dimension vector a of the vehicle to be paid and the dimension vector b1 of the dimension of the historical vehicle 1 are,
the vehicle dimension vector a of the article and the dimension vector b2 cosine of the historical vehicle 2 are,
then cos theta 1 and cos theta 2 form a result set R2, and cosine values in the result set R2 are reduced according to the size of the cosine values and are arranged into cos theta 2 and cos theta 1,
since the number Num of samples in the result set R2 is 2 and less than 10, 1 historical vehicle is selected from the result set R2 as the historical vehicle 2,
the integrated score value of the history vehicle 2 is calculated,
Score1＝7*80％+9*20％
the historic vehicle 2 has a composite score of 7.4,
the average Score value Score2 of the vehicle to be paid is Score2
Score2＝7.4/1＝7.4，
The second filter calculates an audit factor of the item of 5.6/7.4-0.76,
configuring the preset coefficient to be 0.5; and the second filter judges whether the auditing coefficient of the vehicle to be paid is greater than or equal to a preset coefficient, if the auditing coefficient of the vehicle to be paid is greater than 0.76 and greater than 0.5, the vehicle to be paid is automatically paid.
The calculation of the average score value of the vehicle to be paid utilizes a big data analysis processing technology, firstly, the vehicle which best meets the reference standard is screened out from a mass of historical transaction orders according to the vehicle to be checked, and then the average score value of the vehicle to be paid is calculated, so that the calculation method ensures the accuracy of automatically checking whether the vehicle to be paid meets the automatic payment.
As shown in fig. 5, the embodiment of the present invention introduces a payment apparatus, the apparatus includes a determining module, a calculating module, and a determining module connected by data, where the determining module is configured to determine whether transaction information of an article meets payment conditions; the calculation module is used for calculating the auditing coefficient of the article when the article transaction information accords with the payment condition; and the determining module is used for determining a payment mode based on the auditing coefficient. The judgment module is used for determining payment conditions, and the payment conditions comprise one or more of the following conditions: whether the vehicle has unprocessed violation, whether various certificates of the vehicle are complete, whether various certificates of a vehicle owner are complete, whether payment information of the vehicle owner is complete, and whether historical vehicles of the same vehicle type with the number higher than the first number exist. The calculation module is further configured to calculate a composite score value and an average score value for the item.
The method in the embodiment of the invention can be realized by a computer or an embedded program controlled system. Accordingly, in accordance with another embodiment of the present invention, there is provided another payment system, as shown in fig. 6, the testing system includes at least one processor and at least one memory; the memory stores a computer program for performing any of the above methods of embodiments of the invention, and the processor invokes the computer program in the memory to perform any of the methods of embodiments of the invention.
Although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (17)
1. A payment method, characterized in that the method comprises,
judging whether the transaction information of the article meets the payment condition;
when the transaction information of the article accords with the payment condition, calculating an auditing coefficient of the article;
and determining a payment mode to pay based on the auditing coefficient.
2. A payment method as recited in claim 1, wherein the payment condition comprises a legitimacy condition of the item.
3. A payment method as claimed in claim 2, wherein the legitimacy condition comprises one or more of the following conditions,
whether the item transaction information is complete and whether there are more than a first number of historical items of the same type.
4. A payment method as recited in claim 1, further comprising performing a manual audit payment if the item transaction information does not comply with the payment terms.
5. A payment method as recited in claim 1, wherein the calculating an audit coefficient for the item comprises,
and calculating the auditing coefficient based on the comprehensive scoring value and the average scoring value of the article.
6. The payment method of claim 5, wherein the composite value of credit for the item is determined by,
calculating a composite score value for the item based on the score values and weights corresponding to the one or more dimensional conditions for the item.
7. The payment method of claim 6, wherein the item's composite score value is calculated by the formula,
Score1＝A1+A2+……+An
wherein A is1To AnRespectively one of said articles orThe product of the scores of the plurality of dimension conditions and the weight, n representing n dimension conditions.
8. The payment method of claim 5, wherein the average value of credit for the item is determined by,
obtaining one or more historical items of the same type as the item in a historical sample;
determining an average value of credit for the item based on the item and one or more historical items.
9. The payment method of claim 8, wherein determining the average value of credit for the item further comprises,
recording a sample number of the one or more historical items;
calculating cosine values of the article and each historical article in one or more historical articles respectively;
selecting a second quantity of historical articles in the top ranking from the one or more historical articles based on the cosine value size reduction ranking;
respectively calculating the comprehensive scoring value of each historical item in the second quantity of historical items;
and calculating the average scoring value of the item based on the comprehensive scoring value of each historical item.
10. The payment method of claim 9, wherein the item's average score value is an average of the sum of the composite score values of the individual historical items in the second quantity of historical items.
11. The payment method of claim 9, wherein determining the average value of credit for the item further comprises,
and when the sample number of the one or more historical articles is less than the second number, selecting a first number of historical articles from the one or more historical articles.
12. A payment method as claimed in claim 8, wherein the cosine value is calculated by,
wherein A is1To AnThe product of the value of credit and the weight of one or more dimension conditions of the item respectively; b is1To BnThe products of the scoring values and the weights of one or more dimension conditions of any historical item respectively; wherein n represents n dimensional conditions, and n is more than or equal to 1.
13. The payment method of claim 1, wherein determining a payment method to pay based on the audit coefficient comprises:
when the auditing coefficient is greater than or equal to a preset coefficient, executing automatic payment; or the like, or, alternatively,
and when the auditing coefficient is less than the preset coefficient, executing manual auditing payment.
14. A payment process as claimed in any one of claims 6 to 10, comprising one or more dimensional conditions,
item status rating, item price rating, item cost rating.
15. A payment device, characterized in that it comprises,
the judging module is used for judging whether the transaction information of the article meets the payment condition;
the calculation module is used for calculating the auditing coefficient of the article when the transaction information of the article accords with the payment condition;
and the determining module is used for determining a payment mode to pay based on the auditing coefficient.
16. The payment device of claim 15, wherein the calculation module is further configured to calculate a composite score value and an average score value for the item.
17. A payment system, the system comprising at least one processor and at least one memory;
the memory stores a computer program for performing the method of any of claims 1-14, and the processor calls the computer program in the memory to perform the method of any of claims 1-14.
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