Method and apparatus for configuring financial device, electronic device, and storage medium

Abstract

The disclosure provides a configuration method and device of a financial device, electronic equipment, a storage medium and a program product, which can be applied to the technical field of data processing. The configuration method comprises: determining initial configuration parameters of the financial device according to the type of the financial device, the financial device being configured in a target institution and being used for processing assets stored in the target institution; obtaining K detection indexes used for detecting the operating condition of the financial device, the detection indexes being obtained within a first preset time period, and K being greater than or equal to 2; calculating the business saturation of the financial device according to the K detection indexes, the business saturation being used for representing the configuration condition of the financial device within the first preset time period; and determining updated configuration parameters of the financial device according to the business saturation and the initial configuration parameters.

Description

Technical Field

[0001] This disclosure relates to the field of data processing technology, specifically to a configuration method, apparatus, electronic device, and storage medium for financial equipment. Background Technology

[0002] In the daily operations of banks and other institutions, the configuration of financial equipment affects their operational efficiency and costs. For example, too much financial equipment leads to wasted resources and increased operating costs; too little financial equipment affects operational efficiency and user experience.

[0003] In related technologies, the configuration of financial equipment relies on the subjective operational experience of operations and management personnel, which leads to technical problems such as uneven distribution of financial equipment, affecting operating costs and operational efficiency.

[0004] Furthermore, in the event of a shortage of financial equipment, operational staff at banks and other institutions typically increase the quantity of equipment by initiating procurement or allocation requests. However, the lengthy procurement or allocation processes often result in prolonged periods of equipment shortages for these institutions, thereby impacting operational efficiency. Summary of the Invention

[0005] In view of the above problems, this disclosure provides a method, apparatus, device, medium and program product for configuring financial equipment.

[0006] According to a first aspect of this disclosure, a method for configuring a financial device is provided, comprising: determining initial configuration parameters of the financial device according to the type of the financial device, wherein the financial device is configured in a target institution for processing assets stored in the target institution;

[0007] K detection indicators are obtained to detect the operating status of financial equipment. The detection indicators are obtained within a first preset time period, and K is greater than or equal to 2.

[0008] Based on K detection indicators, the business saturation of financial equipment is calculated. Business saturation characterizes the configuration status of financial equipment within a first preset time period; and

[0009] Determine the updated configuration parameters for financial equipment based on business saturation and initial configuration parameters.

[0010] According to embodiments of this disclosure, calculating the business saturation of financial equipment based on K detection indicators includes:

[0011] Obtain the first threshold and the second threshold corresponding to the K detection indicators. The first threshold represents the expected threshold of the detection indicator, and the second threshold represents the lower limit threshold of the detection indicator.

[0012] Based on the first threshold, the second threshold, and the K detection indicators, calculate the K calculated values ​​corresponding to the K detection indicators;

[0013] Based on the importance of the K detection indicators, a comparison matrix including the K detection indicators is obtained. The comparison matrix is ​​used to determine the differences in importance among the K detection indicators.

[0014] Based on the comparison matrix, calculate the K weights corresponding to the K detection indicators; and

[0015] The business saturation of financial equipment is calculated based on K calculated values ​​and K weights.

[0016] According to embodiments of this disclosure, the method further includes:

[0017] Obtain K sets of historical data corresponding to K detection indicators. The historical data includes historical indicator information of the detection indicators within a second preset time period, which is before the first preset time period.

[0018] Using the quartile data of K sets of historical data, outlier data in the K sets of historical data are removed to obtain K sets of standard data;

[0019] Calculate the mean of each of the K sets of standard data to obtain K means; and

[0020] Based on K average values ​​and preset floating data, a first threshold and a second threshold corresponding to K detection indicators are calculated. The preset floating data is used to characterize the degree of elastic fluctuation between the first threshold and the second threshold.

[0021] According to an embodiment of this disclosure, the comparison matrix is ​​a K×K dimension matrix, with K detection indicators in both rows and columns. The comparison matrix includes multiple elements used to describe the difference in importance between the detection indicators in the row and column of the element.

[0022] Based on the comparison matrix, calculate the K weights corresponding to the K detection indicators, including:

[0023] Based on the rows of the comparison matrix, calculate K temporary weights corresponding to the K detection metrics; and

[0024] If the comparison matrix passes the consistency test, the K temporary weights are used as the K weights corresponding to the K detection indicators.

[0025] According to embodiments of this disclosure, the K detection indicators include M positive indicators and N negative indicators, wherein M is greater than or equal to 1 and less than or equal to K, and N is greater than or equal to 1 and less than or equal to K. Positive indicators represent a positive impact on the operation of financial equipment, and negative indicators represent a negative impact on the operation of most financial equipment.

[0026] According to embodiments of this disclosure, determining the updated configuration parameters of the financial equipment based on business saturation and initial configuration parameters includes:

[0027] Subtracting the business saturation level from the initial configuration parameters yields the current configuration number of the financial equipment, which is then used as the updated configuration parameter. A negative business saturation level indicates that the financial equipment is under-configured, while a positive business saturation level indicates that the financial equipment is over-configured.

[0028] According to embodiments of this disclosure, determining the initial configuration parameters of the financial device based on its type includes:

[0029] Based on the type of financial equipment, determine the corresponding basic parameters, including asset parameters and / or equipment parameters; and

[0030] Calculate asset parameters and / or equipment parameters to obtain the initial configuration parameters of the financial equipment.

[0031] According to embodiments of this disclosure, the types of financial devices include a first financial device, a second financial device, a third financial device, and a fourth financial device. The first financial device is used to count assets of a first type, the second financial device is used to count or identify assets of a second type, the third financial device is used to count assets of a first type and identify multiple versions of assets of a first type, and the fourth financial device is used to process assets of a first type in a preset area.

[0032] Based on the type of financial equipment, determine the corresponding basic parameters, including:

[0033] If the financial device is identified as the first financial device, the first device parameters corresponding to the financial device are determined. The first device parameters include the target institution's service type, service delay data, and counter configuration data.

[0034] When a financial device is identified as a second financial device, the parameters of the second device corresponding to the financial device are determined, including the configuration mode of the financial device.

[0035] If the financial equipment is identified as a third financial equipment, the third equipment parameters and the first asset parameters corresponding to the financial equipment are determined. The third equipment parameters include the target institution's equipment maintenance data, self-service equipment configuration data, and counter configuration data. The first asset parameters include the target institution's average daily asset processing data.

[0036] If the financial device is identified as the fourth type of financial device, the parameters of the fourth device corresponding to the financial device are determined. The parameters of the fourth device include the number of asset processing areas of the target institution.

[0037] According to embodiments of this disclosure, determining the basic parameters corresponding to the financial device based on the type of financial device further includes:

[0038] Determine the second asset parameters corresponding to the target institution. The second asset parameters include the asset processing data of the target institution within a preset historical period.

[0039] According to embodiments of this disclosure, calculating asset parameters and / or equipment parameters to obtain initial configuration parameters for the financial equipment includes:

[0040] Based on the type identifier of the financial device, call the preset function corresponding to the financial device from the model library; and

[0041] Call the preset function to calculate asset parameters and / or equipment parameters to obtain the initial configuration parameters for the financial equipment.

[0042] A second aspect of this disclosure provides a configuration device for a financial device, comprising:

[0043] The first determining module is used to determine the initial configuration parameters of the financial equipment based on the type of financial equipment. The financial equipment is configured in the target institution to process the assets stored in the target institution.

[0044] The acquisition module is used to acquire K detection indicators for monitoring the operational status of financial equipment. These indicators are acquired within a first preset time period, and K is greater than or equal to 2.

[0045] The calculation module is used to calculate the business saturation of financial equipment based on K detection indicators. The business saturation is used to characterize the configuration status of financial equipment in the first preset time period.

[0046] The second determining module is used to determine the updated configuration parameters of the financial equipment based on the business saturation and the initial configuration parameters.

[0047] A third aspect of this disclosure provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to perform the configuration method of the aforementioned financial device.

[0048] A fourth aspect of this disclosure also provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the configuration method of the aforementioned financial device.

[0049] The fifth aspect of this disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the configuration method of the aforementioned financial device.

[0050] According to embodiments of this disclosure, by determining the initial configuration parameters of financial equipment based on its type, acquiring K detection indicators for monitoring the operational status of the financial equipment, calculating the business saturation of the financial equipment based on the K detection indicators, and determining the updated configuration parameters of the financial equipment based on the business saturation and the initial configuration parameters, an automated update process from initial parameter configuration to updated parameter configuration is achieved for various financial equipment. Since this disclosure determines the initial configuration parameters corresponding to the financial equipment based on its type and determines the updated configuration parameters based on the business saturation and the initial configuration parameters, there is no need for operation and management personnel to determine the initial and updated configuration parameters, thus achieving the initialization and updating of configuration parameters and improving the accuracy of determining configuration parameters. Attached Figure Description

[0051] The foregoing contents, as well as other objects, features, and advantages of this disclosure, will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0052] Figure 1 This illustration schematically depicts an application scenario of a configuration method for a financial device according to an embodiment of the present disclosure;

[0053] Figure 2 A flowchart illustrating a configuration method for a financial device according to an embodiment of the present disclosure is shown schematically.

[0054] Figure 3 A flowchart illustrating a service saturation calculation method according to an embodiment of the present disclosure is shown schematically.

[0055] Figure 4 A flowchart illustrating a method for determining a first threshold and a second threshold according to an embodiment of the present disclosure is shown schematically.

[0056] Figure 5 A flowchart illustrating an initial configuration parameter determination method according to an embodiment of the present disclosure is shown schematically.

[0057] Figure 6 A schematic diagram illustrating a structural block diagram of a configuration apparatus for a financial device according to an embodiment of the present disclosure; and

[0058] Figure 7 A block diagram of an electronic device suitable for a configuration method for financial devices according to an embodiment of the present disclosure is illustrated schematically. Detailed Implementation

[0059] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0060] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0061] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0062] When using expressions such as "at least one of A, B, and C", they should generally be interpreted in accordance with the meaning that is commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B, and C, etc.).

[0063] In the technical solutions disclosed herein, the collection, storage, use, processing, transmission, provision, disclosure, and application of data (including but not limited to user personal information) comply with the provisions of relevant laws and regulations, necessary confidentiality measures have been taken, and they do not violate public order and good morals.

[0064] In the daily operations of banks and other institutions, the configuration of financial equipment affects their operational efficiency and costs. In some technologies, the configuration of financial equipment relies on the subjective operational experience of management personnel. For example, management personnel estimate the required number of financial equipment based on factors such as branch area and traffic flow, and then apply to the head office or other equipment-related departments to obtain the corresponding number. However, this can lead to uneven distribution of financial equipment, thus impacting operating costs and efficiency.

[0065] After the configuration of financial equipment is completed, the evaluation of the configuration also relies on the subjective experience of the operations and management personnel. This leads to the subsequent adjustment of the number of financial equipment to be configured still relying on the subjective experience of the operations and management personnel, making it impossible to objectively evaluate the current configuration, thereby affecting the subsequent configuration of financial equipment and the operational status of bank branches.

[0066] Furthermore, in related technologies, the application and allocation of financial equipment require banks or branches to initiate applications. In cases of insufficient or excessive financial equipment, applications must be submitted to update the equipment. This can lead to prolonged shortages or idleness of equipment, impacting the institution's operational efficiency. Changes in the number of devices allocated during the application process necessitate re-application or modification of configuration data, further lengthening the allocation process, increasing operating costs, and reducing efficiency. During this period, excess financial equipment cannot be allocated to banks or branches experiencing shortages, resulting in uneven resource distribution.

[0067] Embodiments of this disclosure provide a method for configuring a financial device, comprising: determining initial configuration parameters of the financial device according to the type of the financial device, wherein the financial device is configured in a target institution for processing assets stored in the target institution; acquiring K detection indicators for detecting the operating status of the financial device, wherein the detection indicators are acquired within a first preset time period, and K is greater than or equal to 2; calculating the business saturation of the financial device based on the K detection indicators, wherein the business saturation is used to characterize the configuration status of the financial device within the first preset time period; and determining updated configuration parameters of the financial device based on the business saturation and the initial configuration parameters.

[0068] Figure 1 The illustration depicts an application scenario of a configuration method for a financial device according to an embodiment of the present disclosure.

[0069] like Figure 1 As shown, application scenario 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 serves as a medium for providing a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0070] Users can use at least one of the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 via the network 104 to receive or send messages, etc. The first terminal device 101, the second terminal device 102, and the third terminal device 103 may have application software installed to obtain initial configuration parameters or detection indicators, or various communication client applications installed to receive updated configuration parameters from the server 104 (for example only).

[0071] The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0072] Server 105 can be a server that provides various services, such as a backend management server that supports websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103 (this is just an example). The backend management server can analyze and process data such as received user requests, and feed back the processing results (such as initial configuration parameters obtained or generated based on user requests, detection indicators, etc.) to the terminal devices.

[0073] It should be noted that the configuration method for financial devices provided in this disclosure embodiment can generally be executed by server 105. Correspondingly, the configuration device for financial devices provided in this disclosure embodiment can generally be located in server 105. The configuration method for financial devices provided in this disclosure embodiment can also be executed by a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105. Correspondingly, the configuration device for financial devices provided in this disclosure embodiment can also be located in a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105.

[0074] The configuration method for financial devices provided in this embodiment can also be executed by the first terminal device 101, the second terminal device 102, and the third terminal device 103. Accordingly, the configuration device for financial devices provided in this embodiment can also be disposed in the first terminal device 101, the second terminal device 102, and the third terminal device 103.

[0075] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0076] The following will be based on Figure 1 The described scene, through Figures 2-5 The configuration method of the financial device according to the disclosed embodiments is described in detail.

[0077] Figure 2 A flowchart illustrating a configuration method for a financial device according to an embodiment of the present disclosure is shown schematically.

[0078] like Figure 2 As shown, the method includes operations S210 to S250.

[0079] In operation S210, the initial configuration parameters of the financial equipment are determined according to the type of financial equipment. The financial equipment is configured in the target institution to process the assets stored in the target institution.

[0080] According to embodiments of this disclosure, the target institution includes a savings institution such as a bank that processes multiple assets. The target institution can be configured with various types of financial equipment to process multiple types of assets. For example, the financial equipment can be used to process a general first type of asset, and also to process a second type of asset, wherein the second type of asset includes assets traded between multiple regions.

[0081] According to embodiments of this disclosure, multiple financial devices can process multiple assets or multiple versions of the same asset, therefore, multiple financial devices include multiple configuration parameters. Before determining the configuration parameters of a financial device, initial configuration parameters to be configured for the financial device are determined based on the type of financial device.

[0082] According to embodiments of this disclosure, initial configuration parameters can be determined based on the target institution's basic settings before the target institution begins using the financial device. Alternatively, the initial configuration parameters can be reconfigured based on the basic settings after the target institution has used the financial device for a period of time. Specifically, the basic settings include the number of counters configured by the target institution, the number of asset service areas of the device, and the amount of assets processed.

[0083] For example, financial device A and financial device B are used to process different assets. Financial device A and financial device B include the same amount of assets but different processing methods.

[0084] In operation S220, K detection indicators for detecting the operating status of financial equipment are acquired. These detection indicators are acquired within a first preset time period.

[0085] According to embodiments of this disclosure, after determining the type of financial device and its initial configuration parameters, the initial configuration parameters are updated based on the operational status of the financial device in the target institution. Specifically, the operational status of the financial device in the target institution can be determined based on its detection indicators.

[0086] According to embodiments of this disclosure, the detection indicators include business data from various types of financial devices, the service status of the target institution after using the financial devices, and other detection indicators related to the financial devices. For example, business data includes the number of transactions and transaction amounts processed through the financial devices. Service status includes the target institution's service timeout rate. Other detection indicators include the number and usage rate of self-service devices related to the financial devices.

[0087] According to embodiments of this disclosure, the detection indicators can be obtained within a first preset time period after using the financial device, for example, one week. After the first preset time period has elapsed, the detection indicators obtained within the first preset time period are updated using detection indicators obtained within a time period of the same duration as the first preset time period.

[0088] In operation S230, the business saturation of the financial equipment is calculated based on K detection indicators. The business saturation is used to characterize the configuration status of the financial equipment in the first preset time period.

[0089] According to embodiments of this disclosure, after obtaining the detection indicators, the number of financial devices can be increased or decreased based on the operational status of the financial devices reflected by the detection indicators. Specifically, the business saturation of the financial devices within a first preset time period is calculated using K detection indicators.

[0090] According to embodiments of this disclosure, the business saturation is obtained by weighted summation of calculated values ​​from K detection indicators. The calculated value of each detection indicator is determined based on its expected threshold and lower limit threshold, so as to accurately determine the operating status of the financial equipment based on changes in the detection indicators.

[0091] According to embodiments of this disclosure, the weight of each detection indicator in business saturation is determined by comparing the importance of multiple detection indicators.

[0092] According to embodiments of this disclosure, since the detection indicators for multiple types of financial devices are different, the weight of the same detection indicator can change during the calculation of the business saturation of multiple types of financial devices.

[0093] When operating S240, the updated configuration parameters of the financial equipment are determined based on the business saturation and initial configuration parameters.

[0094] According to embodiments of this disclosure, after calculating the business saturation of the financial device, updated configuration parameters of the financial device are jointly determined based on the business saturation and the initial configuration parameters. Specifically, the number of configurations to be adjusted can be determined based on the product of the initial configuration parameters and the business saturation. Alternatively, the number of configurations to be adjusted can be determined based on the sum and difference between the initial configuration parameters and the business saturation.

[0095] This disclosure automates the process of updating various financial devices from initial parameter configuration to updated parameter configuration by determining the initial configuration parameters based on the type of financial device; acquiring K detection indicators to monitor the operational status of the financial device; calculating the business saturation of the financial device based on the K detection indicators; and finally determining the updated configuration parameters of the financial device based on the business saturation and the initial configuration parameters. Because this disclosure determines the initial configuration parameters corresponding to the type of financial device and the updated configuration parameters based on the business saturation and the initial configuration parameters, it eliminates the need for operation and management personnel to determine the initial and updated configuration parameters, thus achieving both initialization and updating of configuration parameters and improving the accuracy of parameter determination.

[0096] Furthermore, since the updated configuration parameters are determined based on business saturation, which in turn is determined based on the monitoring indicators of financial equipment, the updated configuration parameters rely only on objective monitoring indicators and do not include subjective ones, which helps improve the accuracy of configuring financial equipment. In addition, this disclosure can detect the operational status of financial equipment in a short time based on business saturation, and promptly allocate the number of financial equipment configured in the target institution or multiple institutions, thus advancing the resource allocation process; it eliminates the need to apply for resource allocation after the institution's operational efficiency and operating costs have been affected. Therefore, this disclosure also improves the mobility of financial equipment among multiple institutions and the operational efficiency of the target institution, while reducing the target institution's operating costs.

[0097] Figure 3 A flowchart illustrating a service saturation calculation method according to an embodiment of the present disclosure is shown schematically.

[0098] like Figure 3 As shown, the service saturation calculation method of this embodiment includes operations S331 to S335, which can be used as a specific embodiment of operation S230.

[0099] In operation S331, the first threshold and the second threshold corresponding to the K detection indicators are obtained. The first threshold represents the expected threshold of the detection indicator, and the second threshold represents the lower limit threshold of the detection indicator.

[0100] According to an embodiment of this disclosure, after determining the type of financial device and obtaining K detection indicators corresponding to the type of financial device, a first threshold and a second threshold for each of the K detection indicators are obtained, so as to calculate the calculated value of the detection indicator based on the first threshold and the second threshold.

[0101] In operation S332, based on the first threshold, the second threshold, and the K detection indicators, calculate the K calculated values ​​corresponding to the K detection indicators.

[0102] According to embodiments of this disclosure, after determining the first threshold and the second threshold for each of the K detection indicators, the difference between the detection indicator and the second threshold, and the difference between the first threshold and the second threshold are calculated. Then, the calculated value of the detection indicator is determined based on the ratio of the difference between the detection indicator and the second threshold and the difference between the first threshold and the second threshold.

[0103] Specifically, the process of calculating the numerical values ​​corresponding to the detection indicators satisfies:

[0104]

[0105] Where S represents the calculated value of the detection index, A represents the first threshold, and B represents the lower threshold.

[0106] In operation S333, a comparison matrix is ​​obtained based on the importance of the K detection indicators. The comparison matrix is ​​used to determine the difference in importance among the K detection indicators.

[0107] According to embodiments of this disclosure, the importance of multiple detection indicators may differ during the process of determining business saturation. The weights of each detection indicator are determined based on its importance. Before determining the weights of the K detection indicators, a comparison matrix comprising the K detection indicators is determined based on their respective importance.

[0108] According to embodiments of this disclosure, the comparison matrix is ​​a K×K dimension matrix, with K detection indicators in both rows and columns. The comparison matrix includes multiple elements, each element representing the difference in importance between the detection indicators in its row and the detection indicators in its column.

[0109] According to embodiments of this disclosure, the comparison matrix is ​​determined based on a scale of K detection indicators. The scale represents the degree of difference between two detection indicators among the K detection indicators. Specifically, the scale can be determined according to Table 1.

[0110] Table 1

[0111]

[0112] Here, factor A and factor B represent any two different detection indicators from the K detection indicators.

[0113] In operation S334, based on the comparison matrix, calculate the K weights corresponding to the K detection indicators.

[0114] According to embodiments of this disclosure, K temporary weights corresponding to K detection indicators can be calculated based on the rows of the comparison matrix; and if it is determined that the comparison matrix passes the consistency test, the K temporary weights are used as the K weights corresponding to the K detection indicators.

[0115] According to embodiments of this disclosure, calculating the K temporary weights corresponding to the K detection indicators includes: multiplying the elements of each row of the comparison matrix to obtain the product of the elements in each row of the comparison matrix; taking the nth root of the product to obtain the monitoring indicator weights, where n is the number of columns in the comparison matrix; and then normalizing the monitoring indicator weights to obtain the temporary weights.

[0116] After obtaining K temporary weights based on the comparison matrix of K detection indicators, a consistency check is performed on the relative importance of the K detection indicators. Specifically, the consistency check process satisfies:

[0117]

[0118] Where CR represents the consistency ratio, CI represents the consistency parameter, RI represents the random consistency index, and λ max Let represent the largest eigenvalue of the comparison matrix, and K represent the order of the comparison matrix. The largest eigenvalue λ of the comparison matrix is ​​obtained from this. max The process satisfies:

[0119]

[0120] Among them, AW i Let A represent the product of the comparison matrix and the temporary weights, and W represent the comparison matrix. i Let represent the temporary weight of the i-th row, and K represent the number of rows in the comparison matrix.

[0121] The random consistency index RI can be determined by looking up a table. The standard values ​​of the random consistency index satisfy Table 2.

[0122] Table 2

[0123] Matrix order 1 2 3 4 5 6 7 8 9 10 RI 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49

[0124] According to embodiments of this disclosure, after calculating the consistency ratio, it is determined whether the consistency test has passed based on the consistency ratio. Specifically, a consistency ratio CR < 0.1 indicates that the consistency test has passed. If the comparison matrix is ​​determined to have passed the consistency test, K temporary weights are used as K weights corresponding to the K detection indicators.

[0125] In operation S335, the business saturation of financial equipment is calculated based on K calculated values ​​and K weights.

[0126] According to embodiments of this disclosure, after determining the calculated values ​​and weights of K detection indicators, the business saturation of the financial equipment is calculated by weighted summation.

[0127] According to embodiments of this disclosure, the K detection indicators include M positive indicators and N negative indicators, wherein M is greater than or equal to 1 and less than or equal to K, and N is greater than or equal to 1 and less than or equal to K. Positive indicators represent a positive impact on the operation of financial equipment, and negative indicators represent a negative impact on the operation of most financial equipment.

[0128] According to embodiments of this disclosure, the higher the calculated value of a positive indicator, the higher the operational efficiency of the financial equipment; conversely, the higher the calculated value of a negative indicator, the lower the operational efficiency of the financial equipment. Therefore, when determining the calculated value of the detection indicator based on a first threshold and a second threshold, the first threshold for a positive indicator is greater than the second threshold, and the efficiency of the first threshold for a negative indicator is less than the second threshold.

[0129] According to embodiments of this disclosure, negative indicators include asset business service timeout rate, and positive indicators include the amount of assets processed by various types of financial devices.

[0130] This disclosure improves the accuracy and comprehensiveness of calculating business saturation by utilizing threshold data and importance of detection indicators, thereby further enhancing the accuracy of updated configuration data.

[0131] Furthermore, this disclosure also considers the positive and negative impacts of the detection indicators on the operational status of the financial equipment, which can further improve the accuracy of calculating business saturation and improve the configuration accuracy of the financial equipment.

[0132] Figure 4 A flowchart illustrating a method for determining a first threshold and a second threshold according to an embodiment of the present disclosure is shown schematically.

[0133] like Figure 4 As shown, the method for determining the first threshold and the second threshold in this embodiment includes operations S410 to S440.

[0134] According to an embodiment of this disclosure, operations S410 to S440 are set before operation S331 and are used to determine the first threshold and the second threshold of each of the K detection indicators.

[0135] In operation S410, K sets of historical data corresponding to K detection indicators are obtained.

[0136] According to embodiments of this disclosure, historical data includes historical indicator information of detection indicators within a second preset time period. The second preset time period precedes the first preset time period, and its duration is longer than that of the first preset time period. The historical indicator information of the second preset time period is used to reflect the operational status of the target mechanism within that historical second preset time period.

[0137] According to embodiments of this disclosure, each detection indicator corresponds to a set of historical data, and each set of historical data includes multiple detection values ​​for that detection indicator. The multiple detection values ​​in the historical data are arranged in ascending order.

[0138] For example, taking the asset business service timeout rate as a detection indicator, the historical data includes [1, 1, 2, 4, 5, 6, 10, 12, 13].

[0139] In operation S420, using the quartile data of K sets of historical data, abnormal data in K sets of historical data is deleted to obtain K sets of standard data.

[0140] According to embodiments of this disclosure, after acquiring K sets of historical data corresponding to K detection indicators, the quartile data of the K sets of historical data are determined. Specifically, the quartile data includes the quartile value Q1, the 3rd quartile value Q3, and the interquartile range IQR within the set of historical data.

[0141] According to embodiments of this disclosure, the position of the quarter quantile satisfies (n+1) / 4, and the position of the third quarter quantile satisfies 3(n+1) / 4, where n represents the number of data points in the historical data set.

[0142] After determining the positions of the quartile and the third quartile, the values ​​located at the quartile and the third quartile, respectively, are designated as quartile data Q1 and third quartile data Q3. Then, based on the difference between quartile data Q1 and third quartile data Q3, the interquartile range IQR is determined, where IQR = Q3 - Q1.

[0143] According to embodiments of this disclosure, when there is no value at the quarter-th quartile or third-quarter quartile, the quarter-th quartile data Q1 or the third-quarter quartile data Q3 is calculated based on the two values ​​located before and after the quarter-th quartile position.

[0144] For example, when n is 10 and (n+1) / 4 = 2.75, the quartile data is calculated based on the 2nd and 3rd detection values ​​"3" and "5". The quartile data is: 3*0.25 + 5*0.75 = 4.5.

[0145] According to embodiments of this disclosure, after determining the interquartile range (IQR), the value range of the historical data set is determined based on the IQR, the quartile data, and the tertiary data. Detection values ​​outside this range are identified as abnormal data, and these abnormal data are deleted from the K sets of historical data to obtain K sets of standard data.

[0146] According to embodiments of this disclosure, the upper limit of the value range satisfies min{(Q3+1.5IQR), maximum value)}, and the lower limit of the value range satisfies max{(Q1-1.5IQR), minimum value)}.

[0147] For example, taking the asset service timeout rate as an example, historical data includes [1, 1, 2, 4, 5, 6, 10, 12, 13]. The quartile and tertiary quartile positions are 2.5 and 7.5 respectively, the quartile data Q1 and tertiary quartile data Q3 are 1.5 and 11 respectively, and the IQR is 9.5. Therefore, the range of the asset service timeout rate is [1, 13], and the standard data after deleting abnormal data is still [1, 1, 2, 4, 5, 6, 10, 12, 13].

[0148] In operation S430, the average value of each set of standard data in K sets of standard data is calculated to obtain K average values.

[0149] According to embodiments of this disclosure, after deleting abnormal data from K sets of historical data to obtain K sets of standard data, the average value of each set of standard data in the K sets of standard data is calculated.

[0150] According to embodiments of this disclosure, after deleting abnormal data from K sets of historical data to obtain K sets of standard data, a weighted average of multiple detection values ​​within each set of standard data can be calculated. The weight of each detection value can be determined based on the proximity of the detection time to the current time. For example, the more recent the detection time, the higher the weight; the more distant the detection time, the lower the weight. It can also be determined based on the detection date; for example, a detection date on a weekday has a high weight, while a detection date on a holiday has a low weight.

[0151] According to embodiments of this disclosure, the weight range can be determined based on actual needs.

[0152] In operation S440, based on K average values ​​combined with preset floating data, the first threshold and the second threshold corresponding to the K detection indicators are calculated.

[0153] According to embodiments of this disclosure, after determining the average value of K sets of standard data, the expected threshold and lower limit threshold of K detection indicators can be determined based on preset floating data. The preset floating data is used to characterize the degree of elastic fluctuation between the first threshold and the second threshold.

[0154] Specifically, the preset floating data can be specific measured values ​​or the ratio of the average of K sets of standard data.

[0155] For example, the first threshold for a positive indicator is A = (1 + 20%)μ, and the second threshold is B = (1 - 20%)μ; the first threshold for a negative indicator is A = (1 - 20%)μ, and the second threshold is B = (1 + 20%)μ. Here, μ represents K weighted values ​​determined based on K sets of historical data within the second preset time period.

[0156] This disclosure improves the accuracy of the expected threshold and the lower limit threshold by using quartile data to remove abnormal data, thereby improving the accuracy of calculating business saturation.

[0157] According to embodiments of this disclosure, determining updated configuration parameters for a financial device based on business saturation and initial configuration parameters includes: subtracting the business saturation from the initial configuration parameters to obtain the current configuration count of the financial device, and using the current configuration count as the updated configuration parameter. A negative business saturation indicates that the financial device is under-configured, while a positive business saturation indicates that the financial device is over-configured.

[0158] According to embodiments of this disclosure, after calculating the business saturation of a financial device, updated configuration parameters of the financial device can be determined based on the degree of deviation between the business saturation and the initial configuration parameters.

[0159] Specifically, a negative business saturation indicates that the financial equipment is under-configured; subtracting the business saturation from the initial configuration parameters results in a configuration number greater than the initial parameters. Conversely, a positive business saturation indicates that the financial equipment is over-configured; subtracting the business saturation from the initial configuration parameters results in a configuration number less than the initial parameters.

[0160] After determining the current configuration number based on service saturation and initial configuration parameters, the obtained configuration number can be used as the updated configuration parameter. If the service saturation is not an integer, the integer part of the initial configuration parameter minus the service saturation is used as the current configuration number.

[0161] According to embodiments of this disclosure, different levels can be determined based on business saturation, and then the number of configurations to be added or reduced can be determined based on a preset configuration table; then, the updated configuration parameters can be determined together with the initial configuration parameters.

[0162] Figure 5 A flowchart illustrating an initial configuration parameter determination method according to an embodiment of the present disclosure is shown schematically.

[0163] like Figure 5 As shown, the initial configuration parameter determination method of this embodiment includes operations S511 to S512, which can be used as a specific embodiment of operation S210. Operations S511 to S512 can also be located before operation S210, after the initial configuration parameters are determined, and the initial configuration parameters are directly obtained in S210 according to the type of financial device.

[0164] In operating S511, the basic parameters corresponding to the financial equipment are determined based on the type of financial equipment. The basic parameters include asset parameters and / or equipment parameters.

[0165] According to embodiments of this disclosure, the initial configuration parameters of the financial device are related to the equipment and infrastructure configured by the target institution, as well as the amount of assets processed by the target institution. Based on the type of financial device, basic parameters corresponding to that financial device are determined so that the initial configuration parameters can be calculated based on the determined basic parameters.

[0166] According to embodiments of this disclosure, determining the basic parameters corresponding to a financial device based on its type includes: retrieving basic parameter configuration information corresponding to the type identifier from a database based on the financial device's type identifier, and then determining the corresponding basic parameters based on the basic parameter configuration information. The basic parameter configuration information can be determined based on information data tables provided by multiple target institutions.

[0167] According to embodiments of this disclosure, multiple types of financial devices correspond to multiple types of basic parameters. Specifically, the basic parameters of a financial device may include only asset parameters or equipment parameters, or they may include both asset parameters and equipment parameters simultaneously.

[0168] According to embodiments of this disclosure, the types of financial devices include a first financial device, a second financial device, a third financial device, and a fourth financial device. The first financial device is used to count assets of a first type, the second financial device is used to count or identify assets of a second type, the third financial device is used to count assets of a first type and identify multiple versions of assets of a first type, and the fourth financial device is used to process assets of a first type in a preset area.

[0169] Based on the type of financial equipment, determine the corresponding basic parameters, including:

[0170] When a financial device is identified as the first financial device, first device parameters corresponding to the financial device are determined. These first device parameters include the target institution's service type, service delay data, and counter configuration data. According to embodiments of this disclosure, the target institution's service type includes branch type and whether on-site service is available. Branch type includes light branches, first-type asset branches, and second-type asset branches. Service delay data includes whether a service response delay branch is available and the asset service delay rate. Counter configuration data includes the number of high-counter counters.

[0171] According to embodiments of this disclosure, determining basic parameter configuration information based on an information data table includes: invoking preset rules, matching the information in the information data table with the preset rules, and obtaining digitized basic parameter configuration information. For example, the digitized branch types include: 1, 2, and 3, where 1 represents a light branch, 2 represents a first-type asset branch, and 3 represents a second-type asset branch.

[0172] If the financial equipment is identified as a secondary financial equipment, the parameters corresponding to that secondary equipment are determined. These parameters include the configuration mode of the financial equipment. Configuration modes include configuration by branch and configuration by teller counter.

[0173] Assuming the financial equipment is classified as a third type of financial equipment, the corresponding third equipment parameters and first asset parameters are determined. The third equipment parameters include the target institution's equipment maintenance data, self-service equipment configuration data, and counter configuration data. The first asset parameters include the target institution's average daily asset processing data. The target institution's equipment maintenance data includes the number of devices maintained; the self-service equipment configuration data includes whether there are self-service equipment outlets, the number of self-service equipment installed, and the number of devices maintained; and the counter configuration data includes the number of high-counter counters. The average daily asset processing data includes the average daily asset volume processed by outlets and the average daily asset volume processed through on-site services.

[0174] If the financial device is identified as the fourth type of financial device, the parameters corresponding to the fourth device are determined. These parameters include the number of asset processing areas of the target institution. The number of asset processing areas includes the number of first asset processing areas.

[0175] According to embodiments of this disclosure, the basic parameters also include personnel configuration information and standby mode, wherein the standby mode includes whether to set up a standby machine and the number of standby machines.

[0176] According to embodiments of this disclosure, for various types of financial devices, initial configuration parameters can be determined based on second asset parameters corresponding to the target institution. These second asset parameters include asset processing data of the target institution within a preset historical period.

[0177] In operation S512, asset parameters and / or equipment parameters are calculated to obtain the initial configuration parameters of the financial equipment.

[0178] According to embodiments of this disclosure, after determining the corresponding asset parameters and / or equipment parameters based on the type of financial device, a preset function corresponding to the financial device can be called to calculate the asset parameters and / or equipment parameters to obtain the initial configuration parameters.

[0179] According to embodiments of this disclosure, initial configuration parameters for the financial equipment are obtained by calculating asset parameters and / or equipment parameters, including:

[0180] Based on the type identifier of the financial device, the system calls the preset function corresponding to the financial device from the model library; the preset function is then used to calculate the asset parameters and / or device parameters to obtain the initial configuration parameters for the financial device.

[0181] According to embodiments of this disclosure, for the first type of financial equipment, a preset function first determines the branch type. If the branch type is determined to be a light branch, the initial configuration parameter of the first type of financial equipment is set to 1. If the branch type is determined to be a first type asset branch or a second type asset branch, and it is not a branch with delayed service response, the initial configuration parameter of the first type of financial equipment is set to the number of teller counters plus 4. If the branch type is determined to be a first type asset branch or a second type asset branch, and it is a branch with delayed service response, the initial configuration parameter of the first type of financial equipment is set to twice the number of teller counters plus 3.

[0182] For the second type of financial equipment, the preset function first determines the configuration mode. If the configuration mode is determined to be per branch, the initial configuration parameter for the second type of financial equipment is set to 2; if the configuration mode is determined to be per teller, the initial configuration parameter for the second type of financial equipment is set to the number of teller counters.

[0183] For the third type of financial equipment, a preset function calculates the average daily asset volume processed by branches, the average daily asset volume processed by on-site services, and the number of self-service devices maintained, and determines the first configuration parameter according to preset rules. Specifically, after the average daily asset volume processed by branches meets a first preset threshold, the first configuration parameter for the average daily asset volume processed by branches is determined based on the multiple relationship between the asset volume and the first preset threshold. After the average daily asset volume processed by on-site services meets a second preset threshold, the first configuration parameter for the average daily asset volume processed by on-site services is determined based on the multiple relationship between the asset volume and the second preset threshold. After the number of self-service devices maintained meets a third preset threshold, the first configuration parameter for the number of self-service devices maintained is determined based on the multiple relationship between the maintenance quantity and the third preset threshold. Then, the initial configuration parameters are jointly determined based on the multiple first configuration parameters obtained from the above three factors and the number of queuing machines.

[0184] For the third type of financial equipment, the preset function determines the initial configuration parameters based on the number of first asset processing areas, for example, the initial configuration parameters are equal to the number of first asset processing areas.

[0185] This disclosure improves the accuracy and comprehensiveness of the configuration by considering both equipment and asset factors in completing the initial configuration of financial equipment.

[0186] Figure 6A schematic block diagram of a configuration apparatus for a financial device according to an embodiment of the present disclosure is shown.

[0187] like Figure 6 As shown, the configuration device 600 of the financial equipment in this embodiment includes a first determining module 610, an acquiring module 620, a calculating module 630, and a second determining module 640.

[0188] The first determining module 610 is used to determine the initial configuration parameters of the financial device based on the type of financial device. The financial device is configured in the target institution to process assets stored in the target institution. In one embodiment, the first determining module 610 can be used to execute the operation S210 described above, which will not be repeated here.

[0189] The acquisition module 620 is used to acquire K detection indicators for detecting the operating status of financial equipment. The detection indicators are acquired within a first preset time period, and K is greater than or equal to 2. In one embodiment, the acquisition module 620 can be used to perform the operation S220 described above, which will not be repeated here.

[0190] The calculation module 630 is used to calculate the business saturation of the financial equipment based on K detection indicators. The business saturation is used to characterize the configuration status of the financial equipment within a first preset time period. In one embodiment, the calculation module 630 can be used to perform the operation S230 described above, which will not be repeated here.

[0191] The second determining module 640 is used to determine the updated configuration parameters of the financial equipment based on the business saturation and the initial configuration parameters. In one embodiment, the second determining module 640 can be used to perform the operation S240 described above, which will not be repeated here.

[0192] According to embodiments of this disclosure, the calculation module 630 includes a first calculation submodule, a second calculation submodule, a third calculation submodule, a fourth calculation submodule, and a fifth calculation submodule.

[0193] The first calculation submodule is used to obtain a first threshold and a second threshold corresponding to K detection indicators. The first threshold represents the expected threshold of the detection indicator, and the second threshold represents the lower limit threshold of the detection indicator. In one embodiment, the first calculation submodule can be used to perform the operation S331 described above, which will not be repeated here.

[0194] The second calculation submodule is used to calculate K calculated values ​​corresponding to the K detection indicators based on the first threshold, the second threshold, and the K detection indicators. In one embodiment, the second calculation submodule can be used to perform the operation S332 described above, which will not be repeated here.

[0195] The third calculation submodule is used to obtain a comparison matrix including the K detection indicators based on their importance. The comparison matrix is ​​used to determine the difference in importance among the K detection indicators. In one embodiment, the third calculation submodule can be used to perform the operation S333 described above, which will not be repeated here.

[0196] The fourth calculation submodule is used to calculate the K weights corresponding to the K detection indicators based on the comparison matrix. In one embodiment, the fourth calculation submodule can be used to perform the operation S334 described above, which will not be repeated here.

[0197] The fifth calculation submodule is used to calculate the business saturation of the financial equipment based on K calculated values ​​and K weights. In one embodiment, the fifth calculation submodule can be used to perform the operation S335 described above, which will not be repeated here.

[0198] According to embodiments of this disclosure, the computing module 630 further includes a first computing unit, a second computing unit, a third computing unit, and a fourth computing unit.

[0199] The first calculation unit is used to acquire K sets of historical data corresponding to K detection indicators. The historical data includes historical indicator information of the detection indicators within a second preset time period, which is prior to the first preset time period. In one embodiment, the first calculation unit can be used to perform the operation S410 described above, which will not be repeated here.

[0200] The second calculation unit is used to utilize the quartile data of K sets of historical data to delete outlier data within the K sets of historical data, thereby obtaining K sets of standard data. In one embodiment, the second calculation unit can be used to perform the operation S420 described above, which will not be repeated here.

[0201] The third calculation unit is used to calculate the weighted average of each of the K sets of standard data, resulting in K weighted averages. In one embodiment, the third calculation unit can be used to perform the operation S430 described above, which will not be repeated here.

[0202] The fourth calculation unit is used to calculate a first threshold and a second threshold corresponding to the K detection indicators based on the K weighted average values ​​combined with preset floating data. The preset floating data is used to characterize the degree of elastic fluctuation between the first threshold and the second threshold. In one embodiment, the fourth calculation unit can be used to perform the operation S440 described above, which will not be repeated here.

[0203] According to embodiments of this disclosure, the fourth computing submodule includes a fifth computing unit and a sixth computing unit.

[0204] The fifth calculation unit is used to calculate the K temporary weights corresponding to the K detection indicators based on the rows of the comparison matrix.

[0205] The sixth calculation unit is used to take K temporary weights as K weights corresponding to K detection indicators, provided that the comparison matrix has passed the consistency test.

[0206] According to an embodiment of this disclosure, the second determining module 640 includes a determining submodule, which is used to add the business saturation and the initial configuration parameters to obtain the current configuration number of the financial device, and use the current configuration number as the updated configuration parameter; wherein, a negative business saturation indicates that the financial device is in an under-configured state, and a positive business saturation indicates that the financial device is in an over-configured state.

[0207] According to an embodiment of this disclosure, the first determining module 610 includes: a first determining unit and a second determining unit.

[0208] The first determining unit is used to determine the basic parameters corresponding to the financial equipment based on the type of financial equipment. The basic parameters include asset parameters and / or equipment parameters. In one embodiment, the first determining unit can be used to perform the operation S511 described above, which will not be repeated here.

[0209] The second determining unit is used to calculate asset parameters and / or equipment parameters to obtain the initial configuration parameters of the financial equipment. In one embodiment, the second determining unit can be used to perform the operation S512 described above, which will not be repeated here.

[0210] According to embodiments of this disclosure, the first determining unit includes a first determining subunit, a second determining subunit, a third determining subunit, a fourth determining subunit, and a fifth determining subunit.

[0211] The first determining subunit is used to determine the first equipment parameters corresponding to the financial equipment when the financial equipment is determined to be the first financial equipment. The first equipment parameters include the service type of the target institution, service delay data, and counter configuration data.

[0212] The second determining subunit is used to determine the second equipment parameters corresponding to the financial equipment when the financial equipment is determined to be a second financial equipment. The second parameters include the configuration mode of the financial equipment.

[0213] The third determining subunit is used to determine the third equipment parameters and the first asset parameters corresponding to the financial equipment when the financial equipment is determined to be a third financial equipment. The third equipment parameters include the target institution's equipment maintenance data, self-service equipment configuration data, and counter configuration data. The first asset parameters include the target institution's average daily asset processing data.

[0214] The fourth determining subunit is used to determine the fourth equipment parameters corresponding to the financial equipment when the financial equipment is determined to be a fourth financial equipment. The fourth equipment parameters include the number of asset processing areas of the target institution.

[0215] According to embodiments of this disclosure, the first determining unit further includes a fifth determining subunit.

[0216] The fifth determining subunit is used to determine the second asset parameters corresponding to the target institution. The second asset parameters include the asset processing data of the target institution within a preset historical period.

[0217] According to embodiments of this disclosure, the second determining unit further includes a sixth determining subunit and a seventh determining subunit.

[0218] The sixth determination sub-unit is used to call the preset function corresponding to the financial device from the model library based on the type identifier of the financial device.

[0219] The seventh determination subunit is used to call preset functions to calculate asset parameters and / or equipment parameters to obtain the initial configuration parameters of the financial equipment.

[0220] According to embodiments of this disclosure, any plurality of modules among the first determining module 610, the acquiring module 620, the calculating module 630, and the second determining module 640 may be combined into one module, or any one of these modules may be split into multiple modules. Alternatively, at least a portion of the functionality of one or more of these modules may be combined with at least a portion of the functionality of other modules and implemented in one module. According to embodiments of this disclosure, at least one of the first determining module 610, the acquiring module 620, the calculating module 630, and the second determining module 640 may be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging the circuitry, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in a suitable combination of any of these. Alternatively, at least one of the first determining module 610, the obtaining module 620, the calculating module 630, and the second determining module 640 may be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0221] Figure 7 A block diagram of an electronic device suitable for a configuration method for financial devices according to an embodiment of the present disclosure is illustrated schematically.

[0222] like Figure 7As shown, an electronic device 700 according to an embodiment of the present disclosure includes a processor 701, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage portion 708 into a random access memory (RAM) 703. The processor 701 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 701 may also include onboard memory for caching purposes. The processor 701 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0223] RAM 703 stores various programs and data required for the operation of electronic device 700. Processor 701, ROM 702, and RAM 703 are interconnected via bus 704. Processor 701 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 702 and / or RAM 703. It should be noted that the programs may also be stored in one or more memories other than ROM 702 and RAM 703. Processor 701 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in said one or more memories.

[0224] According to embodiments of this disclosure, the electronic device 700 may further include an input / output (I / O) interface 705, which is also connected to a bus 704. The electronic device 700 may also include one or more of the following components connected to the I / O interface 705: an input section 706 including a keyboard, mouse, etc.; an output section 707 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 710 as needed so that computer programs read from it can be installed into the storage section 708 as needed.

[0225] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0226] According to embodiments of this disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this disclosure, the computer-readable storage medium may include ROM 702 and / or RAM 703 and / or one or more memories other than ROM 702 and RAM 703 described above.

[0227] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code is used to enable the computer system to implement the configuration method for financial devices provided in embodiments of this disclosure.

[0228] When the computer program is executed by the processor 701, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0229] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 709, and / or installed from a removable medium 711. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0230] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 709, and / or installed from the removable medium 711. When the computer program is executed by the processor 701, it performs the functions defined in the system of this disclosure embodiment. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0231] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0232] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0233] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0234] The specific embodiments described above further illustrate the purpose, technical solutions, and beneficial effects of this disclosure. It should be understood that the above descriptions are merely specific embodiments of this disclosure and are not intended to limit this disclosure. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this disclosure should be included within the protection scope of this disclosure.

Claims

1. A method for configuring a financial device, comprising: Based on the type of financial equipment, the initial configuration parameters of the financial equipment are determined. The financial equipment is configured in the target institution to process the assets stored in the target institution. K detection indicators are obtained for detecting the operating status of the financial equipment. The detection indicators are obtained within a first preset time period, and K is greater than or equal to 2. Based on the K detection indicators, the business saturation of the financial equipment is calculated, and the business saturation is used to characterize the configuration status of the financial equipment during the first preset time period; as well as The updated configuration parameters of the financial equipment are determined based on the business saturation and the initial configuration parameters. The step of calculating the business saturation of the financial equipment based on the K detection indicators includes: Obtain a first threshold and a second threshold corresponding to the K detection indicators, wherein the first threshold represents the expected threshold of the detection indicator and the second threshold represents the lower limit threshold of the detection indicator; Based on the first threshold, the second threshold, and the K detection indicators, calculate K calculated values ​​corresponding to the K detection indicators; Based on the importance of the K detection indicators, a comparison matrix including the K detection indicators is obtained, and the comparison matrix is ​​used to determine the difference in importance among the K detection indicators; Based on the comparison matrix, calculate the K weights corresponding to the K detection indicators; and The business saturation of the financial equipment is calculated based on the K calculated values ​​and the K weights. Based on the business saturation and the initial configuration parameters, the updated configuration parameters of the financial equipment are determined, including: Subtracting the business saturation from the initial configuration parameter yields the current configuration number of the financial device, which is then used as the updated configuration parameter. A negative business saturation indicates that the financial device is under-configured, while a positive business saturation indicates that the financial device is over-configured.

2. The method according to claim 1, wherein, The method further includes: Obtain K sets of historical data corresponding to the K detection indicators, wherein the historical data includes historical indicator information of the detection indicators within a second preset time period, and the second preset time period is prior to the first preset time period; Using the quartile data of the K sets of historical data, abnormal data is deleted from the K sets of historical data to obtain K sets of standard data; Calculate the average value of each of the K sets of standard data to obtain K average values; and Based on the K average values ​​combined with preset floating data, the first threshold and the second threshold corresponding to the K detection indicators are calculated. The preset floating data is used to characterize the degree of elastic fluctuation between the first threshold and the second threshold.

3. The method according to claim 1, wherein, The comparison matrix is ​​a K×K dimension matrix, with K rows and K columns of the comparison matrix. The comparison matrix includes multiple elements to describe the difference in importance between the detection indicators in the row and the column of the element. The step of calculating the K weights corresponding to the K detection indicators based on the comparison matrix includes: Based on the rows of the comparison matrix, calculate K temporary weights corresponding to the K detection indicators; as well as If the comparison matrix passes the consistency test, the K temporary weights are used as the K weights corresponding to the K detection indicators.

4. The method according to claim 1, wherein, The K detection indicators include M positive indicators and N negative indicators, where M is greater than or equal to 1 and less than or equal to K, and N is greater than or equal to 1 and less than or equal to K. The positive indicators represent a positive impact on the operation of the financial equipment, and the negative indicators represent a negative impact on the operation of most financial equipment.

5. The method according to claim 1, wherein, The step of determining the initial configuration parameters of the financial equipment according to its type includes: Based on the type of financial device, determine the basic parameters corresponding to the financial device, including asset parameters and / or equipment parameters; and Calculate the asset parameters and / or the equipment parameters to obtain the initial configuration parameters of the financial equipment.

6. The method according to claim 5, wherein, The types of financial equipment include a first financial equipment, a second financial equipment, a third financial equipment, and a fourth financial equipment. The first financial equipment is used to count assets of a first type, the second financial equipment is used to count or identify assets of a second type, the third financial equipment is used to count assets of the first type and identify multiple versions of assets of the first type, and the fourth financial equipment is used to process assets of the first type in a preset area. The step of determining the basic parameters corresponding to the financial device based on the type of financial device includes: If the financial device is determined to be a first financial device, a first device parameter corresponding to the financial device is determined. The first device parameter includes the service type, service delay data and counter configuration data of the target institution. If the financial device is determined to be a second financial device, second device parameters corresponding to the financial device are determined, and the second device parameters include the configuration mode of the financial device. If the financial device is determined to be a third financial device, the third device parameters and the first asset parameters corresponding to the financial device are determined. The third device parameters include the target institution's equipment maintenance data, self-service equipment configuration data, and counter configuration data. The first asset parameters include the target institution's average daily asset processing data. If the financial device is determined to be a fourth financial device, the fourth device parameters corresponding to the financial device are determined, and the fourth device parameters include the number of asset processing areas of the target institution.

7. The method according to claim 5, wherein, The step of determining the basic parameters corresponding to the financial device based on the type of financial device also includes: A second asset parameter corresponding to the target institution is determined, the second asset parameter including the asset processing data of the target institution within a preset historical period.

8. The method according to claim 5, wherein, The calculation of the asset parameters and / or the equipment parameters to obtain the initial configuration parameters of the financial equipment includes: Based on the type identifier of the financial device, a preset function corresponding to the financial device is called from the model library; and The preset function is called to calculate the asset parameters and / or equipment parameters to obtain the initial configuration parameters of the financial equipment.

9. A device for configuring financial equipment, comprising: The first determining module is used to determine the initial configuration parameters of the financial device according to the type of the financial device, wherein the financial device is configured in the target institution and is used to process the assets stored in the target institution; The acquisition module is used to acquire K detection indicators for detecting the operating status of the financial equipment. The detection indicators are acquired within a first preset time period, and K is greater than or equal to 2. as well as The calculation module is used to calculate the business saturation of the financial device based on the K detection indicators, wherein the business saturation is used to characterize the configuration status of the financial device during the first preset time period; The second determining module is used to determine the updated configuration parameters of the financial equipment based on the business saturation and the initial configuration parameters; The calculation module is further configured to: obtain a first threshold and a second threshold corresponding to the K detection indicators, wherein the first threshold represents the expected threshold of the detection indicator and the second threshold represents the lower limit threshold of the detection indicator; calculate K calculated values ​​corresponding to the K detection indicators based on the first threshold, the second threshold, and the K detection indicators; obtain a comparison matrix including the K detection indicators based on the importance of the K detection indicators, wherein the comparison matrix is ​​used to determine the difference in importance among the K detection indicators; calculate K weights corresponding to the K detection indicators based on the comparison matrix; and calculate the business saturation of the financial equipment based on the K calculated values ​​and the K weights. The second determining module is further configured to: subtract the business saturation from the initial configuration parameter to obtain the current configuration number of the financial device, and use the current configuration number as the updated configuration parameter; wherein, a negative business saturation indicates that the financial device is under-configured, and a positive business saturation indicates that the financial device is over-configured.

10. An electronic device, comprising: One or more processors; Storage device for storing one or more programs. Wherein, when the one or more programs are executed by the one or more processors, the one or more processors perform the method according to any one of claims 1 to 8.

11. A computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the method according to any one of claims 1 to 8.

12. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 8.

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