Payment transaction quality evaluation method, equipment, device and computer program product

Abstract

The present application discloses a payment transaction quality evaluation method, equipment, device and computer program product, which relates to the technical field of data analysis and evaluation. The method includes: establishing a hierarchical model based on pre-collected multi-dimensional measurement indicators that affect the payment transaction quality, the hierarchical model includes a target layer, a criterion layer and a solution layer; constructing a weight comparison matrix based on the criterion layer and calculating the weight comparison matrix according to the square root method formula to obtain a weight vector; using a paired comparison method and a comparison scale to form a score comparison matrix for each solution in the solution layer, and calculating the score comparison matrix according to the square root method formula to obtain a score vector; evaluating the payment transaction quality according to the target layer, the score vector and the weight vector. The purpose of comprehensively evaluating the payment transaction quality in multiple dimensions is achieved, and a more accurate payment transaction quality evaluation result is obtained.

Description

Technical Field

[0001] The present application relates to the technical field of data analysis and evaluation, and in particular to payment transaction quality evaluation methods, equipment, devices and computer program products. Background Art

[0002] During the development process, payment transaction systems often face issues such as decision-making on development implementation solutions and the need to track system operation quality. However, the essence of these issues is to focus on the quality of payment transactions in payment transaction systems. As an important measure of the performance of payment transaction systems, payment transaction quality currently lacks a unified standard for payment transaction quality evaluation, or payment transaction quality is only evaluated from a single dimension, lacking a comprehensive multi-dimensional evaluation, resulting in the neglect of the correlation between payment transaction evaluation metrics. The final payment transaction quality evaluation results are relatively one-sided and not suitable for the evaluation and comparison of implementation solutions for actual business needs.

[0003] Therefore, how to comprehensively evaluate the payment transaction quality from multiple dimensions and obtain more accurate payment transaction quality evaluation results has become an urgent problem to be solved in this application.

[0004] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] The main purpose of this application is to provide a payment transaction quality evaluation method, equipment, device and computer program product, aiming to solve the technical problem of how to comprehensively evaluate the quality of payment transactions in multiple dimensions and obtain more accurate payment transaction quality evaluation results.

[0006] To achieve the above objectives, the present application proposes a payment transaction quality evaluation method, the method comprising:

[0007] Establishing a hierarchical model based on pre-collected multi-dimensional measurement indicators that affect payment transaction quality, wherein the hierarchical model includes a target layer, a criterion layer, and a solution layer;

[0008] Constructing a weight comparison matrix based on the criterion layer and calculating the weight comparison matrix according to the square root method formula to obtain a weight vector;

[0009] Using the paired comparison method and the comparison scale to form a score comparison matrix for each solution in the solution layer, and calculating the score comparison matrix according to the square root method formula to obtain a score vector;

[0010] The payment transaction quality is evaluated according to the target layer, the score vector, and the weight vector.

[0011] In one embodiment, the step of constructing a weight comparison matrix based on the criterion layer and calculating the weight comparison matrix according to the square root method formula to obtain a weight vector includes:

[0012] Comparing all multidimensional metrics in the criterion layer using a pairwise comparison method to construct a weight comparison matrix;

[0013] The weight comparison matrix is ​​calculated according to the square root method formula to obtain a weight vector.

[0014] In one embodiment, after the step of constructing a weight comparison matrix based on the criterion layer and calculating the weight comparison matrix according to the square root method formula to obtain a weight vector, the step further includes:

[0015] A consistency check is performed on the weight comparison matrix according to the weight vector to obtain a consistency ratio of the weight comparison matrix.

[0016] In one embodiment, the step of performing consistency check on the weight comparison matrix according to the weight vector to obtain a consistency ratio of the weight comparison matrix includes:

[0017] Calculate the maximum eigenvalue of the weight comparison matrix according to the weight vector;

[0018] Calculate the consistency index value of the weight comparison matrix according to the maximum characteristic root, and query the random consistency index value corresponding to the order of the weight comparison matrix in a preset random consistency index value table;

[0019] A weight comparison matrix consistency ratio is calculated according to the weight comparison matrix consistency index value and the random consistency index value, and a consistency check is performed on the weight comparison matrix according to the weight comparison matrix consistency ratio.

[0020] In one embodiment, the step of using the paired comparison method and the comparison scale to form a score comparison matrix for each solution at the solution layer, and calculating the score comparison matrix according to the square root method formula to obtain a score vector includes:

[0021] Using a comparative scale to quantify the importance of each solution in the solution layer relative to the multi-dimensional metric;

[0022] Using a pairwise comparison method to compare the importance levels, a score comparison matrix is ​​formed;

[0023] The score comparison matrix is ​​calculated according to the square root method formula to obtain the score weight.

[0024] In one embodiment, the step of using the paired comparison method and the comparison scale to determine the score weights of each solution in the solution layer and forming a score comparison matrix based on the score weights further includes:

[0025] A consistency check is performed on the score comparison matrix to obtain a score comparison matrix consistency ratio.

[0026] In one embodiment, the step of evaluating the payment transaction quality according to the target layer, the score vector, and the weight vector includes:

[0027] When the score comparison matrix consistency ratio and the weight comparison matrix consistency ratio both meet the preset threshold, the score weights are spliced ​​into a payment transaction quality evaluation matrix;

[0028] Using the weight vector as a weighting rule for the multi-dimensional measurement indicator;

[0029] The payment transaction quality evaluation is performed according to the payment transaction quality evaluation matrix, the weighting rule selection and the target layer.

[0030] In addition, to achieve the above-mentioned purpose, the present application also proposes a payment transaction quality evaluation device, which includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the payment transaction quality evaluation method described above.

[0031] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the payment transaction quality evaluation method described above are implemented.

[0032] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the payment transaction quality evaluation method described above are implemented.

[0033] One or more technical solutions proposed in this application have at least the following technical effects:

[0034] Based on the pre-collected multi-dimensional measurement indicators that affect the quality of payment transactions, a hierarchical model including the target layer, the criterion layer, and the solution layer is established. The target layer clarifies the core purpose of the payment transaction quality evaluation, that is, to obtain the best payment transaction quality, and provides a clear guide for the subsequent selection of measurement indicators and weight allocation. Based on the criterion layer, a weight comparison matrix is ​​constructed and the weight comparison matrix is ​​calculated according to the square root method formula to obtain the weight vector. By constructing the weight comparison matrix and calculating the weight vector according to the square root method formula, the importance of each measurement indicator to the payment transaction quality is reflected, thereby ensuring the objectivity and accuracy of the evaluation results. The score comparison matrix of each solution at the solution layer is formed using the paired comparison method and the comparison scale, and the score comparison matrix is ​​calculated according to the square root method formula to obtain the score vector, which quantifies the performance of each solution on different measurement indicators and provides data support for the subsequent comprehensive evaluation. The payment transaction quality is evaluated according to the target layer, the score vector and the weight vector, so as to determine the payment transaction quality solution that meets the target layer, achieve the purpose of multi-dimensional comprehensive evaluation of payment transaction quality, and obtain more accurate payment transaction quality evaluation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0036] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0037] Figure 1 This is a flow chart of the first embodiment of the payment transaction quality evaluation method of the present application;

[0038] Figure 2 A schematic diagram of a hierarchical structure model provided for the payment transaction quality evaluation method of this application;

[0039] Figure 3 A schematic diagram of the comparison scale provided for the payment transaction quality evaluation method of this application;

[0040] Figure 4 A schematic diagram of a weight comparison matrix provided for the payment transaction quality evaluation method of this application;

[0041] Figure 5 A schematic diagram of a second embodiment of the payment transaction quality evaluation method provided in this application;

[0042] Figure 6Schematic diagram of the third embodiment of the payment transaction quality evaluation method provided in this application

[0043] Figure 7 A schematic diagram of the module structure of the payment transaction quality device according to an embodiment of the present application;

[0044] Figure 8 Schematic diagram of the device structure of the hardware operating environment involved in the payment transaction quality method in the embodiment of the present application.

[0045] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0046] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0047] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0048] The main solution of the embodiment of the present application is: based on the pre-collected multi-dimensional measurement indicators that affect the quality of payment transactions, a hierarchical model including a target layer, a criterion layer, and a solution layer is established; based on the multiple multi-dimensional measurement indicators for evaluating the quality of payment transactions contained in the criterion layer, a weight comparison matrix is ​​constructed and the weight comparison matrix is ​​calculated according to the square root method formula to obtain a weight vector; for each measurement indicator of the criterion layer, a score comparison matrix of each solution in the solution layer is formed using a paired comparison method and a comparison scale, and a score vector is calculated; the payment transaction quality is evaluated according to the target layer, the score vector and the weight vector, and the comprehensive score of each solution can be obtained by combining the score of each solution and the weight of the measurement indicator, thereby determining which solution can achieve better payment transaction quality.

[0049] In this embodiment, for ease of description, the following description is made by taking the identification of the payment transaction system as the execution entity.

[0050] The embodiments of the present application take into account that: since the payment transaction system often faces the decision-making of the development implementation plan and the need to track the system operation quality during the development process, the essence of these issues is the payment transaction quality in the payment transaction system. As an important measure of the performance of the payment transaction system, the payment transaction quality currently lacks a unified standard for the evaluation of payment transaction quality, or the payment transaction quality is only evaluated from a single dimension, lacking a comprehensive multi-dimensional evaluation, resulting in ignoring the correlation between the payment transaction evaluation metrics. The final payment transaction quality evaluation result is relatively one-sided and not suitable for the evaluation and comparison of the implementation plan of actual business needs.

[0051] Therefore, the present application provides a solution, which establishes a hierarchical model including a target layer, a criterion layer, and a scheme layer based on the pre-collected multi-dimensional measurement indicators that affect the quality of payment transactions, wherein the target layer clarifies the core purpose of payment transaction quality evaluation, namely, obtaining the best payment transaction quality, and provides a clear guide for the subsequent selection of measurement indicators and weight allocation; a weight comparison matrix is ​​constructed based on the criterion layer, and the weight comparison matrix is ​​calculated according to the square root method formula to obtain a weight vector, the criterion layer includes multiple multi-dimensional measurement indicators for evaluating the quality of payment transactions, and the weight comparison matrix is ​​constructed and the weight vector is calculated according to the square root method formula to reflect the importance of each measurement indicator for the quality of payment transactions. The importance of quantity is evaluated, thereby ensuring the objectivity and accuracy of the evaluation results; the paired comparison method and comparison scale are used to form a score comparison matrix for each scheme at the scheme level, and the score comparison matrix is ​​calculated according to the square root method formula to obtain a score vector, which quantifies the performance of each scheme on different measurement indicators and provides data support for subsequent comprehensive evaluation; the payment transaction quality is evaluated according to the target layer, score vector and weight vector, and the comprehensive score of each scheme is obtained by combining the score of each scheme and the weight of the measurement indicators, so as to determine the payment transaction quality scheme that meets the target layer, achieve the purpose of multi-dimensional comprehensive evaluation of payment transaction quality, and obtain more accurate payment transaction quality evaluation results.

[0052] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a payment transaction system, etc. The following takes the payment transaction system as an example to illustrate this embodiment and the following embodiments.

[0053] Based on this, the present application embodiment provides a payment transaction quality evaluation method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the payment transaction quality evaluation method of the present application.

[0054] In this embodiment, the payment transaction quality evaluation method includes steps S10 to S40:

[0055] Step S10, establishing a hierarchical model based on the pre-collected multi-dimensional measurement indicators that affect the payment transaction quality, wherein the hierarchical model includes a target layer, a criterion layer, and a solution layer;

[0056] To establish a hierarchical model, we must first clarify the evaluation objectives, that is, determine the target layer. Then, based on the characteristics of payment transaction quality and evaluation requirements, extract appropriate metrics from the technical and business levels as the content of the criterion layer. Finally, determine the demand implementation solutions to be evaluated and compared as the content of the solution layer. In addition, during the establishment process, we also need to pay attention to the correlation and weight distribution between the metrics.

[0057] like Figure 2 As shown, Figure 2 A schematic diagram of a hierarchical model provided for the payment transaction quality evaluation method of this application. The target layer is the top layer of the hierarchical model, representing the purpose and core pursuit of establishing the hierarchical model: payment transaction quality evaluation, that is, hoping to comprehensively and accurately evaluate the quality of payment transactions through this hierarchical model.

[0058] The criteria layer is located below the target layer and is the specific dimension and measurement indicator for evaluating the quality of payment transactions. The criteria layer contains multi-dimensional measurement indicators extracted from the technical level and the business level. The technical level mainly considers the efficiency and high availability of transaction processing, such as transaction response time, system success rate, system capacity peak, etc.; the business level mainly considers whether the business can be completed normally and in a standardized manner, such as business acceptance rate, risky transaction (gambling, fraud, loan-related transactions) rate, counterparty and address standardization rate, etc.

[0059] The solution layer is the bottom layer of the hierarchical model, representing the statistical period of the demand realization scheme or payment transaction quality-related indicators to be evaluated and compared. When evaluating the quality of payment transactions, different demand realization schemes or statistical periods can be compared at the solution layer. By comparing the performance of different schemes on various metrics at the criterion layer, it can be determined which scheme is better in terms of payment transaction quality, or the development trend of payment transaction quality can be judged.

[0060] Step S20, constructing a weight comparison matrix based on the criterion layer and calculating the weight comparison matrix according to the square root method formula to obtain a weight vector;

[0061] First, determine the various metrics in the criteria layer, such as transaction response time, system success rate, system capacity peak, business acceptance rate, risky transaction rate, and counterparty and address standardization rate.

[0062] Furthermore, the metrics in the criteria layer are compared in pairs to determine the importance of each metric for the evaluation of payment transaction quality. The comparison results can be expressed using a scale of 1-9, where 1 means that the two metrics are equally important, 9 means that one metric is more important than the other, and the numbers in between indicate different degrees of importance.

[0063] Finally, the results of the pairwise comparisons are organized into a matrix, namely the weight comparison matrix. Each row and column of this matrix represents a metric, and the elements in the matrix represent the importance comparison results between the two metrics. The weight comparison matrix is ​​calculated using the square root formula to obtain the weight vector, which is used for subsequent comprehensive score calculations, thereby achieving a comprehensive evaluation of the payment transaction quality.

[0064] Step S30, using a pairwise comparison method and a comparison scale to form a score comparison matrix for each solution in the solution layer, and calculating the score comparison matrix according to the square root method formula to obtain a score vector;

[0065] First, identify all the solutions included in the solution layer, such as Solution A, Solution B, Solution C, etc., and use the paired comparison method to compare the relative scores of each solution in the solution layer one by one for each metric in the criterion layer (such as transaction response time, system success rate, etc.). When comparing, use a comparison scale of 1-9 to indicate the relative importance or superiority of different solutions under the same metric. For example, if Solution A is significantly better than Solution B in terms of transaction response time, then Solution A will be given a higher score (such as 7 or 8), while Solution B will be given a lower score (such as 1 / 7 or 1 / 8).

[0066] Furthermore, the scheme comparison results under all metrics are summarized to form a score comparison matrix. The rows of the matrix represent different metrics, the columns represent different schemes, and the elements in the matrix represent the relative scores of each scheme under the corresponding metric.

[0067] Finally, similar to the calculation of the weight vector, the square root formula is applied to each row of the score comparison matrix (i.e., the solution score under each metric). Specifically, the nth root of the product of the elements in each row is calculated (n is the number of solutions) to obtain an n-dimensional column vector. Then, the vector is standardized, that is, each element is divided by the sum of all elements of the vector to obtain the score vector.

[0068] Step S40: evaluating the payment transaction quality according to the target layer, the score vector, and the weight vector.

[0069] Since each element in the score vector represents the comprehensive score of the corresponding solution under all metrics, the target layer represents the ultimate goal of payment transaction quality evaluation, that is, to obtain the best payment transaction quality. The weight vector represents the importance of each metric in the payment transaction quality evaluation.

[0070] Perform matrix multiplication on the score vector and the weight vector, i.e. Y×W, where Y is the matrix of score vectors (each column represents the score vector of a solution) and W is the weight vector. The result is a new vector, each element of which represents the comprehensive score of the corresponding solution. The comprehensive score takes into account the comprehensive evaluation results of all metrics and their weights.

[0071] The solutions are ranked according to their comprehensive scores. The solution with the highest comprehensive score is considered to be the one that can achieve better payment transaction quality. Based on this ranking result, the best solution can be selected for implementation, or multiple solutions can be selected for combined optimization according to specific needs.

[0072] This embodiment provides a payment transaction quality evaluation method. A hierarchical model including a target layer, a criterion layer, and a solution layer is established based on pre-collected multi-dimensional measurement indicators that affect the payment transaction quality. The target layer clarifies the core purpose of the payment transaction quality evaluation, that is, obtaining the best payment transaction quality, and provides a clear guide for the subsequent selection of measurement indicators and weight allocation. A weight comparison matrix is ​​constructed based on the criterion layer, and the weight comparison matrix is ​​calculated according to the square root method formula to obtain a weight vector. By constructing the weight comparison matrix and calculating the weight vector according to the square root method formula, the importance of each measurement indicator to the payment transaction quality is reflected, thereby ensuring the objectivity and accuracy of the evaluation result. A score comparison matrix of each solution at the solution layer is formed using a paired comparison method and a comparison scale, and the score comparison matrix is ​​calculated according to the square root method formula to obtain a score vector, quantifying the performance of each solution on different measurement indicators, and providing data support for the subsequent comprehensive evaluation. The payment transaction quality is evaluated according to the target layer, the score vector, and the weight vector, so as to determine the payment transaction quality solution that meets the target layer, achieve the purpose of multi-dimensional comprehensive evaluation of the payment transaction quality, and obtain a more accurate payment transaction quality evaluation result.

[0073] In a feasible implementation, step S20 may include steps S21 to S22:

[0074] Step S21, using a pairwise comparison method to compare all multi-dimensional measurement indicators in the criterion layer to construct a weight comparison matrix;

[0075] The paired comparison method is a method for determining the relative importance of elements by comparing them pairwise. In this application, the paired comparison method is used to compare the importance of each metric in the criterion layer to the quality of the payment transaction.

[0076] like Figure 3 As shown, Figure 3A schematic diagram of a comparison scale provided for the payment transaction quality evaluation method of this application. A comparison scale of 1-9 is used to indicate the relative importance of elements. For example, 1 indicates that the importance of two elements is the same, 3 indicates that one element is slightly more important than the other element, 5 indicates that one element is more important than the other element, 7 indicates that one element is much more important than the other element, and 9 indicates that one element is extremely important than the other element. 2, 4, 6, and 8 represent values ​​between two adjacent importance levels. In addition, if element j is more important than element i, the comparison value of element i with element j is the reciprocal of the comparison value of element j with element i.

[0077] According to the comparison scale and paired comparison method, the metrics in the criterion layer are compared pairwise to form a weight comparison matrix. Figure 4 As shown, Figure 4 A schematic diagram of a weight comparison matrix provided for the payment transaction quality evaluation method of this application, wherein each row and column of the weight comparison matrix represents a measurement indicator, and the elements of the matrix represent the relative importance between two indicators.

[0078] It can be understood that the above example is only to better illustrate the step of using the paired comparison method to compare the various metrics in the criterion layer to form a weight comparison matrix. In actual operation, the metrics and the appropriate comparison scale can be determined according to the specific situation to construct a weight comparison matrix. Figure 4 A weight comparison matrix with different elements.

[0079] Step S22, calculating the weight comparison matrix according to the square root method formula to obtain a weight vector.

[0080] The weight comparison matrix is ​​calculated according to the square root method formula. First, the m-dimensional column vector of the product of each row element is calculated. m represents the number of metrics in the weight comparison matrix, that is, the number of multi-dimensional metrics. Further, the calculated m-dimensional column vector is standardized to obtain the weight vector w. The square root method formula is as follows:

[0081]

[0082] Among them, m represents the number of metrics in the weight comparison matrix, and aij represents the importance scale of the i-th metric relative to the j-th metric in the weight comparison matrix. For example, Figure 4 Middle 12 A value of 3 indicates that the system success rate is important and the transaction response time is slightly important. Represents the product of the elements in the i-th row and column of the comparison matrix, w i express The normalized value, w of each row i The values ​​compose the weight vector w.

[0083] The following references Figure 4 The example in the following explains the process of calculating the weight vector w in detail:

[0084] First calculate the sixth root of the product of each row element to get a 6-dimensional column vector (3.6077, 0.6609, 0.4817, 1.7285, 0.6206, 0.8116) T , such as the first element is the sixth root of 1×3×5×3×7×7, which is 3.6077. After standardizing the vector, the weight vector w is (0.456, 0.0835, 0.0609, 0.2185, 0.0785, 0.1026) T , such as the first element is 3.6077 / (3.6077+0.6609+0.4817×1.7285+0.6206+0.8116)=0.456, so the weight of the system success rate is 0.456, the weight of the transaction response time is 0.0835, the weight of the system capacity peak is 0.0609, the weight of the business acceptance rate is 0.2185, the weight of the risk transaction rate is 0.0785, and the weight of the counterparty and address standardization rate is 0.1026.

[0085] In a feasible implementation, step S30 may include steps S31 to S33:

[0086] Step S31, using a comparison scale to quantify the importance of each solution in the solution layer relative to the multi-dimensional measurement indicator;

[0087] In order to quantify the importance of each solution in the solution layer on each metric, a comparison scale of 1-9 is used to score each solution in the solution layer to quantify their importance on the metric. The importance of each solution in the solution layer relative to the multi-dimensional metric is quantified as a score to form the basis of the score comparison matrix in the subsequent steps.

[0088] Step S32, using a paired comparison method to compare the importance levels to form a score comparison matrix;

[0089] The importance obtained by using the comparison scale is organized into a matrix form. The score comparison matrix is ​​a matrix in which both rows and columns represent the solutions in the solution layer. Each element in the score comparison matrix represents the relative importance of the two solutions in the corresponding row and column on a certain metric. For each metric, a score comparison matrix will be constructed.

[0090] Step S33, calculating the score comparison matrix according to the square root method formula to obtain the score weight.

[0091] Similar to the method of calculating the weight vector w, the square root formula is used to calculate the product of all elements in each row of the score comparison matrix, and the product is taken as the nth root (n is the order of the score comparison matrix, that is, the number of solutions) to obtain an n-dimensional column vector, that is, the score weight.

[0092] Based on the first embodiment of the present application, the second embodiment of the present application is proposed. In the second embodiment of the present application, the same or similar contents as those of the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following.

[0093] On this basis, please refer to Figure 5 , Figure 5 A flowchart of a second embodiment of the payment transaction quality evaluation method provided in this application.

[0094] In this embodiment, after step S20 of constructing a weight comparison matrix based on the criterion layer and calculating the weight comparison matrix according to the square root method formula to obtain a weight vector, step S1 is also included:

[0095] Step S1, performing consistency check on the weight comparison matrix according to the weight vector to obtain a consistency ratio of the weight comparison matrix.

[0096] In the analytic hierarchy process (AHP), consistency checking is used to ensure that the judgments made in the evaluation process remain reasonable and consistent. Specifically, the process of performing consistency checking on the weight comparison matrix according to the weight vector includes calculating the consistency index value CI of the weight comparison matrix, finding the random consistency index value RI, and the consistency ratio CR of the weight comparison matrix.

[0097] Specifically, in a feasible implementation, step S1 may include steps A1 to A3:

[0098] Step A1, calculating the maximum eigenvalue of the weight comparison matrix according to the weight vector;

[0099] The maximum eigenvalue, also known as the spectral radius, is an important attribute of the weight comparison matrix, reflecting some inherent characteristics of the weight comparison matrix. In the calculation process, characteristic polynomials or numerical methods (such as power method, Jacobi method, etc.) can be used to solve the characteristic roots of the matrix.

[0100] Exemplarily, the calculation formula of the maximum characteristic root is as follows:

[0101]

[0102] Among them, λ maxrepresents the maximum eigenvalue of the weight comparison matrix, n is the order of the weight comparison matrix, A represents the comparison matrix, such as the comparison matrix formed by comparing the importance of each metric or the comparison matrix formed by comparing the advantages and disadvantages of each solution, which is mainly used to identify different solutions in the solution layer and distinguish different solutions in the solution layer. (AW) i Represents the weight comparison matrix of scheme A and the corresponding element w in the weight vector w i The product of W i are the elements in the weight vector.

[0103] Step A2, calculating the consistency index value of the weight comparison matrix according to the maximum characteristic root, and searching the random consistency index value corresponding to the order of the weight comparison matrix in a preset random consistency index value table;

[0104] The consistency index (CI) is a measure used to measure the consistency of the judgment matrix. It is usually defined as the difference between the maximum eigenvalue and the matrix order, divided by the matrix order minus one. The consistency index value of the weight comparison matrix reflects the state of the weight comparison matrix deviating from complete consistency. The specific calculation formula is as follows:

[0105]

[0106] Among them, CI represents the consistency index value of the weight comparison matrix, λmax represents the maximum eigenvalue of the weight comparison matrix, and n is the order of the weight comparison matrix.

[0107] The Random Consistency Index (RI) is a measure used to measure the consistency of randomly generated judgment matrices. It is usually obtained through a large number of simulation experiments and stored in a preset random consistency index value table. In practical applications, the corresponding random consistency index value can be found in the preset random consistency index value table according to the matrix order.

[0108] Step A3, calculating a weight comparison matrix consistency ratio according to the weight comparison matrix consistency index value and the random consistency index value, and performing consistency check on the weight comparison matrix according to the weight comparison matrix consistency ratio.

[0109] The Random Consistency Index (RI) is a measure used to measure the consistency of randomly generated judgment matrices. The Consistency Ratio (CR) is another measure used to measure the consistency of weight comparison matrices, usually defined as the ratio of the consistency index to the random consistency index. The specific calculation formula is:

[0110]

[0111] In this embodiment, the consistency ratio of the weight comparison matrix is ​​calculated to further judge the consistency of the weight comparison matrix, thereby ensuring the rationality and accuracy of the weight distribution, thereby providing a reliable weight basis for subsequent evaluation schemes.

[0112] Based on the above-mentioned embodiments of the present application, a third embodiment of the present application is proposed. In the third embodiment of the present application, the same or similar contents as those of the above-mentioned embodiments can be referred to the above introduction and will not be repeated later.

[0113] On this basis, please refer to Figure 6 , please refer to Figure 6 , Figure 6 A flowchart of a third embodiment of the payment transaction quality evaluation method provided in this application.

[0114] In this embodiment, the score weights of each solution in the solution layer are determined using a paired comparison method and a comparison scale, and step S30 of forming a score comparison matrix based on the score weights further includes step S2:

[0115] Step S2: performing a consistency check on the score comparison matrix to obtain a score comparison matrix consistency ratio.

[0116] Analogous to the process of calculating the consistency ratio of the weight comparison matrix, the maximum eigenvalue of the score comparison matrix is ​​first calculated; then the score comparison matrix consistency index value CI is calculated based on the maximum eigenvalue of the score comparison matrix to reflect the consistency of the score comparison matrix. In order to evaluate the rationality of CI, it is necessary to query the random consistency index value RI (Random Consistency Index) corresponding to the order of the score comparison matrix. This value is usually calculated through a large number of randomly generated matrices and stored as a standard value in the preset random consistency index value table. In actual operation, the corresponding RI value is found from the table according to the matrix order. Finally, the consistency ratio CR is calculated to determine whether the consistency of the score comparison matrix A is within the acceptable range.

[0117] In this embodiment, each metric represents an aspect of the payment transaction quality. Whether the weight distribution of the metric is reasonable directly affects the accuracy and comprehensiveness of the comprehensive evaluation results. The consistency check of the score comparison matrix is ​​to ensure the rationality of the weight distribution. By performing a consistency check on the score comparison matrix and calculating the consistency ratio, it is ensured that the weight distribution of the score comparison matrix is ​​stable and reliable. In the subsequent comprehensive evaluation, the advantages and disadvantages of each solution in terms of payment transaction quality can be more accurately reflected.

[0118] Based on the above-mentioned embodiments of the present application, a fourth embodiment of the present application is proposed. In the fourth embodiment of the present application, the same or similar contents as those of the above-mentioned embodiments can be referred to the above introduction and will not be repeated later.

[0119] In this embodiment, the step S40 of evaluating the payment transaction quality according to the target layer, the score vector, and the weight vector may include steps S41 to S43:

[0120] Step S41, when the score comparison matrix consistency ratio and the weight comparison matrix consistency ratio both meet the preset threshold, the score weights are spliced ​​into a payment transaction quality evaluation matrix;

[0121] After completing the consistency check of the solution-level score comparison matrices under each criterion-level metric and confirming that the consistency ratios of these matrices meet the preset threshold (usually this threshold is set to 0.1, indicating that the consistency of the matrix is ​​within an acceptable range), the score weights calculated from each score comparison matrix are concatenated.

[0122] Specifically, for each criterion-level metric (such as transaction response time, system success rate, etc.), a score comparison matrix for the solution level will be obtained, and the score weight vector of the matrix will be calculated. These score weight vectors represent the relative merits of each solution (or statistical period) under different metric indicators. By splicing these score weight vectors in the order of the criterion level, a payment transaction quality evaluation matrix can be obtained. Each row of this matrix represents a solution (or statistical period), and each column represents a score weight under a criterion-level metric.

[0123] Step S42, using the weight vector as a weighting rule for the multi-dimensional measurement index;

[0124] After completing the consistency test of the comparison matrix obtained by pairwise comparison of the importance of the criterion layer metrics and confirming that the consistency ratio of the matrix meets the preset threshold, the calculated weight vector can be used as the weight determination rule for the multi-dimensional metric.

[0125] This weight vector represents the relative importance of each criterion-level metric in the payment transaction quality evaluation. By multiplying this weight vector with the payment transaction quality evaluation matrix, the comprehensive score of each scheme (or statistical period) can be obtained, thereby achieving a quantitative evaluation of the payment transaction quality.

[0126] Step S43, performing payment transaction quality evaluation according to the payment transaction quality evaluation matrix, the weighting rule selection and the target layer.

[0127] After obtaining the payment transaction quality evaluation matrix and the weighting rule, the payment transaction quality evaluation matrix is ​​multiplied by the weighting rule (i.e., the weight vector) to obtain a comprehensive score vector. Each element of this vector represents the comprehensive score of a scheme (or statistical period). According to these comprehensive scores, the various schemes (or statistical periods) are sorted or compared to determine which scheme (or statistical period) has better payment transaction quality. At the same time, a threshold or standard can be set according to the target layer (i.e., the target of payment transaction quality evaluation) to determine which schemes (or statistical periods) have reached the expected payment transaction quality level.

[0128] In summary, by performing consistency checks on the score comparison matrix and obtaining the consistency ratio, we can ensure consistency and accuracy in the evaluation process; and splicing the score weights into a payment transaction quality evaluation matrix, using the weight vector as a weight determination rule, and evaluating the payment transaction quality based on this information are key steps to achieve a multi-dimensional comprehensive evaluation of payment transaction quality and obtain more accurate evaluation results.

[0129] In this embodiment, the consistency check ensures the rationality and reliability of the score comparison matrix and the weight comparison matrix, and avoids unreasonable weight distribution due to subjective bias or errors in the comparison process. The splicing of score weights provides a data basis for multi-dimensional comprehensive evaluation, ensuring the comprehensiveness and accuracy of the evaluation process. The setting of weight vectors makes the contribution of each metric in the comprehensive evaluation reasonably reflected, avoiding the one-sidedness of single-dimensional evaluation. Using the payment transaction quality evaluation matrix and the set weight determination rules, a comprehensive evaluation is conducted in combination with the target layer (i.e., the goal of payment transaction quality evaluation) to obtain the payment transaction quality score of each scheme or statistical period. Through the combination of the evaluation matrix and the weight determination rules, a multi-dimensional comprehensive evaluation of the payment transaction quality is achieved. The comprehensive evaluation process fully considers the importance and relevance of each metric, making the evaluation results more accurate and comprehensive, and providing strong support for the optimization and improvement of the payment system.

[0130] This application also provides a payment transaction quality device, please refer to Figure 7 , the payment transaction quality device comprises:

[0131] A hierarchical structure model building module 10 is used to establish a hierarchical structure model based on pre-collected multi-dimensional measurement indicators that affect the quality of payment transactions, wherein the hierarchical structure model includes a target layer, a criterion layer, and a solution layer;

[0132] A weight vector calculation module 20, configured to construct a weight comparison matrix based on the criterion layer and calculate the weight comparison matrix according to a square root method formula to obtain a weight vector;

[0133] A score vector calculation module 30, used to form a score comparison matrix of each solution in the solution layer using a pairwise comparison method and a comparison scale, and calculate the score comparison matrix according to the square root method formula to obtain a score vector;

[0134] The scheme evaluation module 40 is used to evaluate the payment transaction quality according to the target layer, the score vector and the weight vector.

[0135] The payment transaction quality device provided by the present application adopts the payment transaction quality method in the above embodiment to solve the technical problem of payment transaction quality. Compared with the prior art, the beneficial effects of the payment transaction quality device provided by the present application are the same as the beneficial effects of the payment transaction quality method provided by the above embodiment, and the other technical features in the payment transaction quality device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0136] The present application provides a payment transaction quality device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the payment transaction quality method in the above-mentioned embodiment 1.

[0137] Reference below Figure 8 , which shows a schematic diagram of the structure of a payment transaction quality device suitable for implementing the embodiment of the present application. The payment transaction quality device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 8 The payment transaction quality device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0138] like Figure 8As shown, the payment transaction quality device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the payment transaction quality device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the payment transaction quality device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a payment transaction quality device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0139] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0140] The payment transaction quality device provided by the present application adopts the payment transaction quality method in the above embodiment to solve the technical problem of payment transaction quality. Compared with the prior art, the beneficial effects of the payment transaction quality device provided by the present application are the same as the beneficial effects of the payment transaction quality method provided by the above embodiment, and the other technical features in the payment transaction quality device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0141] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0142] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0143] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the payment transaction quality method in the above-mentioned embodiment.

[0144] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0145] The computer-readable storage medium may be included in the payment transaction quality device; or may exist independently without being assembled into the payment transaction quality device.

[0146] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the payment transaction quality device, the payment transaction quality device: establishes a hierarchical model based on the pre-collected multi-dimensional measurement indicators that affect the payment transaction quality, and the hierarchical model includes a target layer, a criterion layer, and a solution layer; constructs a weight comparison matrix based on the criterion layer and calculates the weight comparison matrix according to the square root method formula to obtain a weight vector; uses a paired comparison method and a comparison scale to form a score comparison matrix for each solution in the solution layer, and calculates the score comparison matrix according to the square root method formula to obtain a score vector; and evaluates the payment transaction quality according to the target layer, the score vector, and the weight vector.

[0147] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0148] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0149] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0150] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned payment transaction quality method, and can solve the technical problems of payment transaction quality. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the payment transaction quality method provided in the above-mentioned embodiment, and will not be repeated here.

[0151] The present application also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the steps of the payment transaction quality method as described above are implemented.

[0152] The computer program product provided by this application can solve the technical problem of payment transaction quality. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the payment transaction quality method provided by the above embodiment, which will not be repeated here.

[0153] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A payment transaction quality evaluation method, characterized in that: The method comprises: Establishing a hierarchical model based on pre-collected multi-dimensional measurement indicators that affect payment transaction quality, wherein the hierarchical model includes a target layer, a criterion layer, and a solution layer; Constructing a weight comparison matrix based on the criterion layer and calculating the weight comparison matrix according to the square root method formula to obtain a weight vector; Using the paired comparison method and the comparison scale to form a score comparison matrix for each scheme in the scheme layer, and calculating the score comparison matrix according to the square root method formula to obtain a score vector; The payment transaction quality is evaluated according to the target layer, the score vector, and the weight vector.

2. The method according to claim 1, characterized in that The step of constructing a weight comparison matrix based on the criterion layer and calculating the weight comparison matrix according to the square root method formula to obtain a weight vector comprises: Comparing all multidimensional metrics in the criterion layer using a pairwise comparison method to construct a weight comparison matrix; The weight comparison matrix is ​​calculated according to the square root method formula to obtain a weight vector.

3. The method according to claim 1, characterized in that After the step of constructing a weight comparison matrix based on the criterion layer and calculating the weight comparison matrix according to the square root method formula to obtain a weight vector, the following step further includes: A consistency check is performed on the weight comparison matrix according to the weight vector to obtain a consistency ratio of the weight comparison matrix.

4. The method according to claim 3, characterized in that The step of performing consistency check on the weight comparison matrix according to the weight vector to obtain a consistency ratio of the weight comparison matrix comprises: Calculate the maximum eigenvalue of the weight comparison matrix according to the weight vector; Calculate the consistency index value of the weight comparison matrix according to the maximum characteristic root, and query the random consistency index value corresponding to the order of the weight comparison matrix in a preset random consistency index value table; A weight comparison matrix consistency ratio is calculated according to the weight comparison matrix consistency index value and the random consistency index value, and a consistency check is performed on the weight comparison matrix according to the weight comparison matrix consistency ratio.

5. The method according to claim 3, characterized in that The step of using the paired comparison method and the comparison scale to form a score comparison matrix for each solution at the solution layer, and calculating the score comparison matrix according to the square root method formula to obtain a score vector includes: Using a comparative scale to quantify the importance of each solution in the solution layer relative to the multi-dimensional metric; Using a pairwise comparison method to compare the importance levels, a score comparison matrix is ​​formed; The score comparison matrix is ​​calculated according to the square root method formula to obtain the score weight.

6. The method according to claim 5, characterized in that The step of using the paired comparison method and the comparison scale to determine the score weights of each solution in the solution layer, and forming a score comparison matrix based on the score weights further includes: A consistency check is performed on the score comparison matrix to obtain a score comparison matrix consistency ratio.

7. The method according to claim 6, characterized in that The step of evaluating the payment transaction quality according to the target layer, the score vector, and the weight vector comprises: When the score comparison matrix consistency ratio and the weight comparison matrix consistency ratio both meet the preset threshold, the score weights are spliced ​​into a payment transaction quality evaluation matrix; Using the weight vector as a weighting rule for the multi-dimensional measurement indicator; The payment transaction quality evaluation is performed according to the payment transaction quality evaluation matrix, the weighting rule selection and the target layer.

8. A payment transaction quality evaluation device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the payment transaction quality evaluation method according to any one of claims 1 to 7.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the payment transaction quality evaluation method according to any one of claims 1 to 7 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the payment transaction quality evaluation method according to any one of claims 1 to 7 are implemented.

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