Credit investigation query method, device and equipment for dynamic routing and storage medium

Abstract

The invention relates to a dynamic routing credit investigation query method and device, equipment and a storage medium, and the method comprises the steps: obtaining a pedestrian credit investigation channel set and an initial routing configuration parameter corresponding to each pedestrian credit investigation channel in the pedestrian credit investigation channel set when it is detected that a credit investigation query request does not have a corresponding credit investigation query cache result; based on a multi-dimensional routing screening rule, screening the pedestrian credit investigation channel set to obtain an available pedestrian credit investigation channel set; if the available pedestrian credit investigation channel set is not empty, respectively calculating a routing probability corresponding to each available pedestrian credit investigation channel based on an initial routing configuration parameter corresponding to each available pedestrian credit investigation channel in the available pedestrian credit investigation channel set; determining a target credit investigation channel from the available pedestrian credit investigation channel set through a random number interval matching mechanism based on the routing probability, and initiating a credit investigation query request based on the target credit investigation channel; compared with the prior art, the technical scheme of the invention can improve the callable performance and the utilization rate of the pedestrian credit investigation channel.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data query, and in particular to a dynamic routing credit inquiry method and device, equipment and a storage medium. BACKGROUND

[0002] In the whole process of credit business, the PBOC credit data is the core basis for risk control decision. The real-time risk control system needs to obtain user credit information by calling the PBOC credit data source to support real-time decision-making in key business links such as credit approval, loan monitoring, and post-loan management. The timeliness and effectiveness of data calling directly affect the risk control effect and user experience of credit business.

[0003] Currently, the real-time risk control system relying on PBOC credit data mostly uses fixed channels or simple polling methods to call PBOC credit channels without dynamic adjustment according to channel state, performance, etc. Moreover, there is no targeted cache reuse mechanism for queried credit data, and each query needs to initiate a channel call.

[0004] However, the existing scheme cannot break through the performance constraints. The fixed or simple polling strategy cannot avoid channel abnormalities and select low-time-consuming channels, resulting in poor system stability and high latency. Moreover, the existing strategy does not establish a dynamic screening mechanism according to channel call volume, failure threshold, and traffic limit. When the channel reaches the call limit or the number of failures exceeds the threshold, it may still initiate invalid requests, resulting in a decrease in the callability of the credit channel. Therefore, how to break through the performance constraints and improve the callability and utilization of the credit channel has become a technical problem to be solved in the field. SUMMARY

[0005] The present application provides a dynamic routing credit inquiry method, device, equipment and storage medium, which can improve the callability and utilization of PBOC credit channels.

[0006] In the first aspect, the present application provides a dynamic routing credit inquiry method, comprising: when it is detected that there is no corresponding credit inquiry cache result for a credit inquiry request, obtaining a preset PBOC credit channel set and initial routing configuration parameters corresponding to each PBOC credit channel in the PBOC credit channel set; based on a preset multi-dimensional routing screening rule, screening the PBOC credit channel set to obtain a set of available PBOC credit channels; if the set of available PBOC credit channels is not empty, calculating a routing probability corresponding to each available PBOC credit channel based on the initial routing configuration parameters corresponding to each available PBOC credit channel in the set of available PBOC credit channels; determining a target credit channel from the set of available PBOC credit channels based on the routing probability through a random number interval matching mechanism, and initiating a credit inquiry request based on the target credit channel.

[0007] The dynamic routing credit inquiry method provided in the application further includes: receiving a credit inquiry request, wherein the credit inquiry request carries a credit inquiry request parameter, and the credit inquiry request parameter at least contains user identification information; determining whether there is a credit inquiry cache result corresponding to the user identification information and within a valid period based on the user identification information, if there is, determining that the credit inquiry request has a corresponding credit inquiry cache result, directly obtaining the credit inquiry cache result and outputting; if there is not, determining that the credit inquiry request does not have a corresponding credit inquiry cache result.

[0008] In a possible implementation, the multi-dimensional routing screening rule at least includes one or more of a time routing rule, a call quantity routing rule, a stage routing rule, an application routing rule, a failure threshold routing rule, an average time consumption routing rule, a traffic routing rule, a queue routing rule, and an authorization check routing rule.

[0009] In a possible implementation, the multi-dimensional routing screening rule at least includes one or more of a time routing rule, a call quantity routing rule, a stage routing rule, an application routing rule, a failure threshold routing rule, an average time consumption routing rule, a traffic routing rule, a queue routing rule, and an authorization check routing rule.

[0010] In a possible implementation, the multi-dimensional routing screening rule at least includes one or more of a time routing rule, a call quantity routing rule, a stage routing rule, an application routing rule, a failure threshold routing rule, an average time consumption routing rule, a traffic routing rule, a queue routing rule, and an authorization check routing rule.

[0011] In a possible implementation, the determining the target credit investigation channel from the set of available pedestrian credit investigation channels based on the routing probability through a random number interval matching mechanism specifically includes: constructing a probability interval, wherein the probability interval takes 0 as the interval starting point and the total routing probability as the interval ending point, wherein the total routing probability is calculated from the routing probability corresponding to each available pedestrian credit investigation channel; performing sorting processing on the routing probability in a preset order based on the routing probability corresponding to each available pedestrian credit investigation channel, to obtain a routing probability sorting result; dividing the probability interval based on the routing probability sorting result, and making each probability sub-interval obtained by the division correspond to a single available pedestrian credit investigation channel; generating a random decimal based on a random function, judging a target probability interval into which the random decimal falls, and taking a target available pedestrian credit investigation channel corresponding to the target probability interval as the target credit investigation channel.

[0012] In a possible implementation, the initiating the credit investigation query request based on the target credit investigation channel specifically includes: calling a contract processing system to sign a credit investigation authorization contract, receiving a contract signing identifier returned by the contract processing system, and obtaining a contract file address from the contract processing system based on the contract signing identifier; calling a user information system to obtain user basic information and authorized image information according to the user identifier information; performing availability verification on the user basic information and the authorized image information, and interrupting the credit investigation query process if the verification fails; if the verification passes, calling an external system to initiate a credit investigation query request based on the target credit investigation channel, inputting the user identifier information, the authorized image information and the contract file address into the external system, receiving a credit report and a query result identifier returned by the external system, and storing the credit report, the query result identifier and the corresponding user identifier information into a data storage medium.

[0013] In a second aspect, the application provides a dynamic routing credit inquiry device, comprising: a human credit channel set acquisition module, a multi-dimensional routing screening module, a routing probability calculation module, and a target credit channel determination module; wherein the human credit channel set acquisition module is configured to acquire a preset human credit channel set and initial routing configuration parameters corresponding to each human credit channel in the human credit channel set when it is detected that there is no corresponding credit inquiry cache result for a credit inquiry request; the multi-dimensional routing screening module is configured to screen the human credit channel set based on a preset multi-dimensional routing screening rule to obtain an available human credit channel set; the routing probability calculation module is configured to calculate routing probabilities corresponding to each available human credit channel based on initial routing configuration parameters corresponding to each available human credit channel in the available human credit channel set if the available human credit channel set is not empty; and the target credit channel determination module is configured to determine a target credit channel from the available human credit channel set based on the routing probabilities through a random number interval matching mechanism and initiate a credit inquiry request based on the target credit channel.

[0014] In a third aspect, the application provides a computer device, which comprises a memory and a processor, the memory stores a computer program, and the processor implements the above method when executing the computer program.

[0015] In a fourth aspect, the application provides a computer readable storage medium, which stores a computer program, and the computer program can implement the above method when executed by a processor.

[0016] The embodiments of the application provide a dynamic routing credit inquiry method, device, equipment, and storage medium, which have the following advantages compared with the prior art.

[0017] The technical solution of the present application detects that there is no corresponding credit inquiry cache result for the credit inquiry request, obtains a preset human credit channel set and initial routing configuration parameters corresponding to each human credit channel in the human credit channel set, filters the human credit channel set based on a preset multi-dimensional routing filtering rule to obtain a set of available human credit channels, calculates the routing probability of each available human credit channel based on the initial routing configuration parameters corresponding to each available human credit channel in the set of available human credit channels, determines a target credit channel from the set of available human credit channels based on the routing probability through a random number interval matching mechanism, and initiates a credit inquiry request based on the target credit channel. Compared with the prior art, the technical solution of the present application takes cache detection as a prerequisite, preferentially reuses credit inquiry cache results within the effective period, reduces unnecessary channel calls, reduces system redundant requests from the source, and relieves real-time link pressure. Secondly, the initial human credit channel set is filtered based on the multi-dimensional routing filtering rule, which can dynamically exclude abnormal, non-compliant or resource-saturated human credit channels, ensuring the stability and low-time characteristics of the set of available human credit channels, and effectively breaking through the system performance constraints. Based on the initial routing configuration parameters, the routing probability of each available channel is calculated, and the target channel is determined through random number interval matching, which can realize differentiated scheduling of key channels with high adaptability and low cost through parameter configuration, avoid excessive dependence on a single channel, significantly improve the callability and utilization of key human credit channels, and finally realize comprehensive optimization of real-time risk control link performance and credit data call efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0018] The accompanying drawings, which are incorporated into and form a part of the specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the application.

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, for those skilled in the art, other drawings can also be obtained based on these drawings without creative labor.

[0020] One or more embodiments are exemplarily illustrated by pictures in the corresponding drawings, which do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, unless otherwise specified. The drawings in the drawings do not constitute a proportional limitation.

[0021] Figure 1 is a flowchart of an embodiment of a dynamic routing credit inquiry method provided by the present application;

[0022] Figure 2 is a structural schematic diagram of one embodiment of a dynamic routing credit inquiry device provided by the present application;

[0023] Figure 3 is a structural schematic diagram of a computer device provided by the present application. DETAILED DESCRIPTION

[0024] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0025] The following disclosure provides many different embodiments, or examples, for implementing different structures of the present application. For the purpose of simplifying the present application, components and settings of specific examples are described below. Of course, they are only examples, and the purpose is not to limit the present application. In addition, reference numerals and / or letters can be repeated in different examples in the present application. Such repetition is for the purpose of simplification and clarity, and does not itself indicate a relationship between the various embodiments and / or settings discussed.

[0026] It should be understood that when used in the specification and the appended claims, the terms "comprise" and "include" indicate the presence of described features, integers, steps, operations, elements, and / or components, but do not exclude one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0027] It should also be understood that the terms used in the present application specification are only for the purpose of describing specific embodiments and do not intend to limit the present application. As used in the present application specification and the appended claims, unless otherwise clearly indicated by the context, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0028] It should be further understood that the term "and / or" used in the present application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0029] As used in the specification and the appended claims, the term “if’ can be interpreted as meaning “when” or “upon” or “in response to determining” or “in response to detecting” depending on the context. Similarly, the phrase “if it is determined” or “if [the described condition or event] is detected” can be interpreted as meaning “upon determining” or “in response to determining” or “upon detecting [the described condition or event]” or “in response to detecting [the described condition or event]” depending on the context.

[0030] Embodiment 1, see Figure 1 , Figure 1 is a flowchart of an embodiment of a dynamic routing credit inquiry method provided by the present application, as shown in Figure 1 , the method comprises steps 101-104, specifically as follows:

[0031] Step 101: When it is detected that there is no corresponding credit inquiry cache result of the credit inquiry request, a preset human credit channel set and initial routing configuration parameters corresponding to each human credit channel in the human credit channel set are obtained.

[0032] In an embodiment, a credit inquiry request is received, wherein the credit inquiry request carries credit inquiry request parameters, and the credit inquiry request parameters at least include user identification information; it is judged whether there is a credit inquiry cache result corresponding to the user identification information and within a valid period based on the user identification information, if there is, it is determined that there is a corresponding credit inquiry cache result of the credit inquiry request, the credit inquiry cache result is directly obtained and output; if there is not, it is determined that there is no corresponding credit inquiry cache result of the credit inquiry request.

[0033] Specifically, the credit inquiry platform receives a credit inquiry request initiated by a user, wherein the credit inquiry request needs to carry standardized credit inquiry request parameters, including user identification information, the user identification information includes a user number and a customer number; the user identification information is used as a key matching field for cache retrieval, ensuring accurate positioning of the user's historical query records and avoiding cache mismatch or missing caused by ambiguous identification.

[0034] Specifically, the credit inquiry request parameters further include a business serial number, a credit inquiry unique serial number and a user login application.

[0035] Specifically, when determining whether a valid credit query cache result corresponding to the user identifier exists based on the user identifier information, the user identifier information is used as the retrieval query to search the credit query log records stored in the MySQL database. These credit query log records contain information such as the user's identifier, application success status, application time, and unique query serial number. It is then determined whether the user identifier information matches the user identifier in the credit query log record. If so, based on the application time in the credit query log record, it is determined whether the credit query log record is within a preset validity period. If so, based on the unique query serial number in the credit query log record, the Mongo database is queried to obtain the credit query cache result corresponding to the unique query serial number. This result is then stored as a credit query request in the corresponding credit query cache result. This reuse of historical valid query results reduces unnecessary channel calls and improves the efficiency of the real-time risk control link. Furthermore, the subsequent steps of obtaining the preset credit channel set and initial parameters are only triggered when it is determined that no corresponding credit query cache result exists, ensuring that new channel calls are initiated only when necessary, avoiding resource redundancy.

[0036] In one embodiment, the preset set of PBOC credit information channels refers to the sum of all agent channels pre-configured by the system that have the ability to query PBOC credit information, and is the initial data source for subsequent multi-dimensional filtering.

[0037] Specifically, the aforementioned set of PBOC credit information channels consists of no less than one PBOC credit information channel. By providing a pool of multiple PBOC credit information channels as alternatives, the interruption of the credit information inquiry process due to the failure of a single channel can be avoided.

[0038] Specifically, each of the People's Bank of China (PBOC) credit information channels in the PBOC credit information channel set is an agent supplier that connects to the PBOC's application pre-processing system and has the basic capability to initiate PBOC credit information inquiries; moreover, the PBOC credit information channel set is not generated temporarily, but is pre-entered and maintained through the system management interface or configuration center to ensure that it can be quickly invoked after cache verification fails, without the need for real-time creation.

[0039] In one embodiment, the initial routing configuration parameters corresponding to each People's Bank of China credit reporting channel include the initial routing probability; this parameter will accompany the entire routing lifecycle of this People's Bank of China credit reporting channel and will not change due to other reasons.

[0040] Specifically, the initial routing probability directly determines the scheduling priority of the People's Bank of China (PBOC) credit reporting channel after final screening. Preferably, the initial routing probability supports setting different routing probabilities according to different conditions. For example, for the same PBOC credit reporting channel, when the user logs in to the app "xyf", the initial routing probability corresponding to the PBOC credit reporting channel is 0.1, and when the user logs in to the app "cxh", the initial routing probability corresponding to the PBOC credit reporting channel is 0.2, thus meeting the differentiated scheduling needs of different business scenarios.

[0041] Step 102: Based on the preset multi-dimensional routing filtering rules, filter the set of PBOC credit reporting channels to obtain a set of available PBOC credit reporting channels.

[0042] In one embodiment, before filtering the set of PBOC credit reporting channels based on preset multi-dimensional routing filtering rules, a routing algorithm interface is called to pass in routing matching parameters, wherein the routing matching parameters include, but are not limited to, stage parameters, application parameters, customer number parameters, and user number parameters.

[0043] In one embodiment, the multi-dimensional routing filtering rules include at least one or more of the following: time routing rules, call count routing rules, stage routing rules, application routing rules, failure threshold routing rules, average time consumption routing rules, traffic routing rules, queue routing rules, and authorization verification routing rules.

[0044] Specifically, the time routing rule is to configure the unavailable time periods for each People's Bank of China credit reporting channel. If the current query time falls within the unavailable time period of a certain People's Bank of China credit reporting channel, that People's Bank of China credit reporting channel will be excluded.

[0045] Specifically, the unavailable time period includes unavailable time points and / or unavailable days and dates; if the current query time falls within an unavailable time point of a certain People's Bank of China credit reporting channel, that People's Bank of China credit reporting channel will be removed; if the current query time falls within an unavailable day and date of a certain People's Bank of China credit reporting channel, that People's Bank of China credit reporting channel will be removed.

[0046] Specifically, the call count routing rule is to configure the maximum number of calls for each People's Bank of China credit reporting channel. If the current number of calls for a certain People's Bank of China credit reporting channel exceeds the maximum number of calls, that People's Bank of China credit reporting channel will be removed.

[0047] Specifically, the stage routing rule is to configure the unavailable business stages of each People's Bank of China credit reporting channel. If the currently queried business stage matches the unavailable business stage of a certain People's Bank of China credit reporting channel, that People's Bank of China credit reporting channel is removed.

[0048] Specifically, the application routing rule is to configure the available application identifiers for each People's Bank of China credit reporting channel. If the currently queried application identifier does not match the available application identifier of a certain People's Bank of China credit reporting channel, that People's Bank of China credit reporting channel will be removed.

[0049] Specifically, the failure threshold routing rule configures the maximum number of failed calls for each People's Bank of China (PBOC) credit reporting channel. If the current number of failed calls for a certain PBOC credit reporting channel exceeds the maximum number of failed calls, that PBOC credit reporting channel is removed from the list.

[0050] Specifically, the average time-consuming routing rule is to configure an average time-consuming threshold for each People's Bank of China (PBOC) credit reporting channel. If the current average query time of a certain PBOC credit reporting channel exceeds the average time-consuming threshold, that PBOC credit reporting channel will be removed.

[0051] Specifically, the traffic routing rule is to configure the maximum number of times each People's Bank of China credit reporting channel can be called per unit time through the token bucket mechanism. If there is no available traffic token for a certain People's Bank of China credit reporting channel, that People's Bank of China credit reporting channel will be removed.

[0052] Specifically, the queue routing rule is to configure the maximum number of parallel queries for each People's Bank of China (PBOC) credit reporting channel, and to count the number of queries in transit for each PBOC credit reporting channel in real time. If the number of queries in transit for a certain PBOC credit reporting channel exceeds the maximum number of parallel queries, that PBOC credit reporting channel will be removed.

[0053] Specifically, the authorization verification routing rule is to configure whether each People's Bank of China credit reporting channel requires authorization verification, query the user's current valid authorization information, and if a certain People's Bank of China credit reporting channel requires authorization verification and the current user does not have valid authorization information, then that People's Bank of China credit reporting channel is removed.

[0054] In one embodiment, the step of filtering the set of People's Bank of China (PBOC) credit reporting channels based on preset multi-dimensional routing filtering rules to obtain a set of available PBOC credit reporting channels specifically includes: the credit inquiry request parameters at least include routing matching parameters; obtaining rule configuration information corresponding to the multi-dimensional routing filtering rules; based on the rule configuration information and the routing matching parameters, determining whether each PBOC credit reporting channel in the set of PBOC credit reporting channels conforms to the multi-dimensional routing filtering rules; eliminating PBOC credit reporting channels that do not conform to the multi-dimensional routing filtering rules; and integrating PBOC credit reporting channels that conform to the multi-dimensional routing filtering rules into a set of available PBOC credit reporting channels.

[0055] Specifically, the time routing rules are implemented as follows: the hour information of the current query time is obtained through the time acquisition module and matched with the unavailable time periods configured for each People's Bank of China credit reporting channel (format: "start hour, end hour; start hour, end hour") to determine whether to exclude the People's Bank of China credit reporting channel; and the week information corresponding to the current query time is obtained through the time acquisition module and matched with the unavailable week information configured for each People's Bank of China credit reporting channel (format: "week value, week value") to determine whether to exclude the People's Bank of China credit reporting channel.

[0056] Example Explanation: Currently, thirteen People's Bank of China (PBOC) credit reporting channels (A, B, C, D, E, F, G, H, I, J, K, L, M) are available for inquiry; the time routing rule is for unavailable time periods: {"A":"","B":"","C":"","D":"","E":"","F":"","G":"0,2;14,15","H":"","I":"","J":"","K":"","L":"","M":""}; representing the PBOC..."}"}; Credit reporting channel G is unavailable from 0:00 to 2:00 and from 14:00 to 15:00. Other People's Bank of China (PBOC) credit reporting channels are available at all times. Commasons indicate the start and end of time periods, and a block symbol indicates multiple unavailable time periods. Implementation: The current hour is obtained using Java's Calendar class. Assuming the current time is 1:00 AM, PBOC credit reporting channel G matches this routing rule and is removed from the available channels. Therefore, the remaining available PBOC credit reporting channels are A, B, C, D, E, F, and H. The 12 rules (I, J, K, L, M) will bring these 12 People's Bank of China (PBOC) credit reporting channels into the next layer of routing rules; and the time-based routing rule is for unavailable days and dates: {"A":"","B":"","C":"","D":"","E":"","F":"","H":"1,7","I":"","J":"","K":"","L":"","M":""}; indicating that PBOC credit reporting channel H is unavailable on Saturdays and Sundays, while other PBOC credit reporting channels are unavailable on other days and dates. The channel can be called at any time, and commas are used to distinguish different dates (the first day of the week is Sunday); Implementation method: Get the day of the current time through Java's Calendar class. Assuming that the date being called is Saturday, then the People's Bank of China credit channel H hits the routing rule and needs to be removed from the funnel of available People's Bank of China credit channels. So now there are 11 available People's Bank of China credit channels left: A, B, C, D, E, F, I, J, K, L, and M. These 11 People's Bank of China credit channels are brought into the next layer of routing rules.

[0057] Specifically, the implementation of the call count routing rule is as follows: the maximum number of calls for each People's Bank of China (PBOC) credit reporting channel is initialized daily through a scheduled task mechanism and stored in a cache storage module, and the number of calls for each PBOC credit reporting channel is updated in real time; during filtering, the number of calls for each PBOC credit reporting channel in the cache storage module is read and compared with its corresponding maximum number of calls, and PBOC credit reporting channels whose number of calls exceeds the maximum number of calls are eliminated; the scheduled task module also supports manual updating of the maximum number of calls for PBOC credit reporting channels through the management interface.

[0058] Example explanation:

[0059] {"A":"","B":"50","C":"","D":"","E":"","F":"","I":"100","J":"","K":"","L":"","M":""}; This indicates that the maximum number of calls allowed by the People's Bank of China (PBOC) credit reporting channel B is 50, the maximum number of calls allowed by PBOC credit reporting channel I is 100, and there is no limit to the number of calls allowed by other PBOC credit reporting channels. The implementation method is as follows: The xxljob scheduled task will scan the quantity routing parameter configuration at 00:00 every day, and set the maximum number of calls allowed per day for each PBOC credit reporting channel based on the number of channels already included. The number of calls is refreshed to the Redis cache. In addition to the daily scheduled task processing, the maximum number of calls to the People's Bank of China (PBOC) credit reporting channels can also be manually entered through the management page. When filtering routing rules, the currently available channels are retrieved from Redis. Since the current number of calls to PBOC credit reporting channel B is 51, it hits the routing rule for this number of calls and needs to be removed from the funnel of available PBOC credit reporting channels. However, PBOC credit reporting channel I has not reached 100 calls and has not hit the rule, so it does not need to be removed. Therefore, the remaining available PBOC credit reporting channels are A, C, D, E, F, I, J, K, L, and M, which are then carried into the next layer of routing rules.

[0060] Specifically, the implementation of the stage routing rule is as follows: Obtain the unavailable business stages of each People's Bank of China (PBOC) credit reporting channel, using the channel identifier of the PBOC credit reporting channel as the key and the unavailable business stage corresponding to the PBOC credit reporting channel as the value, constructing a key-value pair structure. If a personal PBOC credit reporting channel has no stage call restrictions, the corresponding value is empty. When receiving a credit query request, obtain the current stage parameter from the routing matching parameters. Match the current stage parameter with the unavailable business stages corresponding to each PBOC credit reporting channel: if the unavailable business stage of a certain PBOC credit reporting channel matches the current stage parameter, then it is determined that the personal PBOC credit reporting channel hits the stage routing rule and is removed from the set of available personal PBOC credit reporting channels; if the stage routing parameter value of the personal PBOC credit reporting channel is empty or inconsistent with the current business stage parameter, then the personal PBOC credit reporting channel is retained.

[0061] Example explanation:

[0062] The parameter {"A":"","C":"","D":"","E":"","F":"","I":"01","J":"02","K":"","L":"","M":""} means: People's Bank of China (PBOC) credit reporting channel I cannot be called in stage 01, PBOC credit reporting channel J cannot be called in stage 02, and other PBOC credit reporting channels have no stage call restrictions. Implementation: When requesting the routing interface, a stage parameter is passed in. During routing matching, the system judges based on this stage parameter. Since the current stage parameter contains stage=01, PBOC credit reporting channel I matches this rule and needs to be removed. Although PBOC credit reporting channel J is also configured, it matches the parameter stage=02, so it does not need to be removed. Therefore, the remaining available PBOC credit reporting channels are A, C, D, E, F, J, K, L, and M (9 channels). These 9 PBOC credit reporting channels are then passed to the next layer of routing rules.

[0063] Specifically, the application routing rule is implemented as follows: Obtain the available application identifiers for each People's Bank of China (PBOC) credit reporting channel; use the channel identifier of the PBOC credit reporting channel as the key and the available application identifier corresponding to the PBOC credit reporting channel as the value; if the PBOC credit reporting channel has no application restrictions, the corresponding value is empty; use a key-value pair structure, and when receiving a credit query request, obtain the current application identifier parameter carried in the request; match the current application identifier parameter with the available application identifiers corresponding to each PBOC credit reporting channel: if the available application identifier of a certain PBOC credit reporting channel is inconsistent with the current application identifier parameter, then it is determined that the PBOC credit reporting channel hits the application routing restriction rule and is removed from the set of available PBOC credit reporting channels; if the application routing parameter value of the PBOC credit reporting channel is empty or consistent with the current application identifier parameter, then the PBOC credit reporting channel is retained; pass the set of available PBOC credit reporting channels retained after application routing filtering to the next dimension routing filtering step.

[0064] Example explanation:

[0065] The expression {"A":"","C":"","D":"","E":"","F":"","J":"xyf","K":"fyx","L":"","M":""} indicates that the app unavailable for PBOC credit channel J is xyf, the app unavailable for PBOC credit channel K is fyx, and other PBOC credit channels have no app-related restrictions. Specifically, when requesting the routing interface, an available application identifier called "app" is included. During route matching, this parameter is used for judgment. Since the current input parameter contains "app = xyf", PBOC credit channel J is matched, while PBOC credit channel K is not matched. Therefore, PBOC credit channel J is removed, leaving eight available PBOC credit channels: A, C, D, E, F, K, L, and M. These eight PBOC credit channels are then carried over to the next layer of routing rules.

[0066] Specifically, the failure threshold routing rule is implemented as follows: the number of failed calls to each People's Bank of China credit reporting channel is recorded in real time and stored in the cache storage module; the number of failed calls to each People's Bank of China credit reporting channel is reset at a specified time every day through the scheduled task module, and manual reset of the number of failed calls is also supported through the management interface; when querying, the number of failed calls in the cache storage module is read and compared with the maximum number of failed calls, and People's Bank of China credit reporting channels with more than the limit of failed calls are eliminated.

[0067] Example explanation:

[0068] {"A":"","C":"20","D":"","E":"","F":"","K":"20","L":"","M":""} represents the maximum number of failed requests allowed for People's Bank of China (PBOC) credit reporting channels C and K, both at 20. Other PBOC credit reporting channels have no failure threshold. Implementation: Each time an external interface call occurs, if a timeout exception or a downstream interface returns a failed request, the failure count for that PBOC credit reporting channel is recorded and stored in Redis. This count is refreshed and reset by the scheduled task `xxlJob` at 9 AM the following day. Additionally, if the exception is resolved on the same day... Once completed, the failure count can also be manually reset. Each time routing rules are filtered, it is checked whether the failure count of the People's Bank of China credit channel in Redis exceeds the threshold. In this case, due to a sudden network interruption during the query of channel C, the failure threshold immediately accumulated to 30, which exceeded the set failure threshold. When a new request comes in later, the People's Bank of China credit channel will be removed. However, the failure count of People's Bank of China credit channel K is only 1, so it will not be affected by the failure removal. Therefore, People's Bank of China credit channel C is removed, leaving 7 available People's Bank of China credit channels: A, D, E, F, K, L, and M. These 7 People's Bank of China credit channels are then brought into the next layer of routing rules.

[0069] Specifically, the average time-consuming routing rule is implemented as follows: record the start time and result return time of each query, and calculate the time consumed in a single query; calculate the average query time of each People's Bank of China credit reporting channel and store it in the cache storage module; if the time consumed in a single query exceeds the preset time-consuming warning value, record an excessively long time-consuming record for that People's Bank of China credit reporting channel; if the number of excessively long time-consuming records for a certain People's Bank of China credit reporting channel exceeds a preset threshold or the average query time exceeds the average time-consuming threshold, remove that People's Bank of China credit reporting channel.

[0070] Example explanation:

[0071] {"A":"10","C":"","D":"","E":"","F":"","K":"10","L":"","M":""} represents the threshold of 10 seconds for the time consumed by People's Bank of China (PBOC) credit reporting channels A and K. Other PBOC credit reporting channels have no time threshold limit. Implementation: Each time an external interface is called, a start time 'a' is recorded. After the external interface is called and the result is obtained, a result retrieval time 'b' is recorded. The time taken to obtain the query result is calculated by combining 'a' and 'b'. If the time exceeds the limit set in Apollo, a channel call time exceeding the limit is recorded. This data is stored in Redis. This data is used during each routing selection process. When the time is right, it will be determined whether the number of excessive calls to the People's Bank of China (PBOC) credit reporting channel exceeds the configured threshold. If it does, it will be removed. Because PBOC credit reporting channel A experienced a sudden network timeout during the query process, the overall average timeout reached 20 seconds, which exceeded the set timeout threshold. At this time, the number of timeouts for the PBOC credit reporting channel had reached the threshold. When a new request comes in later, the PBOC credit reporting channel will be removed. However, the average timeout for PBOC credit reporting channel K is currently only 5 seconds, and the number of timeouts has not reached the threshold, so there will be no timeout removal. Therefore, PBOC credit reporting channel A is removed, leaving 6 available PBOC credit reporting channels: D, E, F, K, L, and M. These 6 PBOC credit reporting channels will be brought to the next layer of routing rules.

[0072] Specifically, the traffic routing rules are implemented as follows: the scheduled task module delivers traffic tokens to the token bucket of the cache storage module according to the maximum number of times each People's Bank of China credit reporting channel can be called per unit time (in the format of "time unit: number of times", where the time unit includes seconds s and minutes m); during a query, an attempt is made to retrieve a token from the token bucket corresponding to the People's Bank of China credit reporting channel. If the retrieval is successful, the People's Bank of China credit reporting channel is retained; if the retrieval fails, the People's Bank of China credit reporting channel is removed.

[0073] Example explanation:

[0074] {"D":"s:10","E":"","F":"","K":"m:10","L":"","M":""} represents that the People's Bank of China (PBOC) credit reporting channel D can be called 10 times per second, the PBOC credit reporting channel K can be called 10 times per minute, and other PBOC credit reporting channels have no traffic call limit; Implementation: The xxljob scheduled task scans the above routing parameters at regular intervals. If a PBOC credit reporting channel is configured, it will add available traffic according to the specified configuration through the Redis token bucket mechanism, such as s:1, which means once per second, and m:1, which means once per second; When making routing decisions, it will check whether the PBOC credit reporting channel currently has available traffic tokens. If no available tokens are available, it will be removed; PBOC credit reporting channel D has already been called 10 times in 1 second, and PBOC credit reporting channel K has not been called, so PBOC credit reporting channel D is removed, leaving 5 available PBOC credit reporting channels: E, F, K, L, and M. These 5 channels are then carried into the next layer of routing rules.

[0075] Specifically, the queue routing rule is implemented as follows: each time a query is initiated, the user identification information is associated with the in-transit query queue of the corresponding channel and stored in the cache storage module; after the query is completed, the user identification information is removed from the in-transit query queue; during the query, the number of user identification information in the in-transit query queue of each People's Bank of China credit reporting channel is counted, and if it exceeds the maximum number of parallel queries, the People's Bank of China credit reporting channel is removed.

[0076] Example Explanation: {"E":"20","F":"","K":"","L":"","M":""} represents the meaning of this parameter: the maximum number of concurrent queries for the People's Bank of China (PBOC) credit reporting channel E is 20. Other channels have no maximum limit on the number of concurrent queries. Implementation: Each time a query is initiated, the user ID corresponding to that user is recorded in the query channel in Redis. This user ID is only removed after the user completes the query. Therefore, if a PBOC credit reporting channel experiences query backlog exceeding the backlog threshold, it will be automatically removed from the available list. Currently, PBOC credit reporting channel E has 25 queries in the queue, exceeding the 20 available channels, so it needs to be removed. The remaining available PBOC credit reporting channels are F, K, L, and M, which are then carried over to the next layer of routing rules.

[0077] Specifically, the authorization verification routing rule is implemented as follows: during filtering, the user information management system is called to query the current user's valid authorization information; if the People's Bank of China credit reporting channel is configured to require authorization verification and the user has no valid authorization information, the People's Bank of China credit reporting channel is removed; if the People's Bank of China credit reporting channel is configured not to require authorization verification, the People's Bank of China credit reporting channel is retained and enters the next filtering stage.

[0078] For example: {"F":"1","K":"0","L":"0","M":"0"} indicates that the People's Bank of China (PBOC) credit reporting channel F requires authorization verification, while PBOC credit reporting channels K, L, and M do not. Implementation: During each routing decision, the user center is first called to query whether the user has authorization information. Based on the data returned by the user center, if there is no authorization information and the channel configuration is 1, then the PBOC credit reporting channel needs to be removed. For example, if the current user has no authorization information and PBOC credit reporting channel F cannot bypass authorization verification, then PBOC credit reporting channel F needs to be removed, leaving three available PBOC credit reporting channels: K, L, and M.

[0079] In one embodiment, the credit reporting channels retained after being filtered by multi-dimensional routing rules are used as the set of available credit reporting channels. In the example above, since all credit reporting channels have been filtered by all routing rules, the remaining three personal credit reporting channels are K, L, and M3, which are then used as the set of available credit reporting channels.

[0080] Step 103: If the set of available PBOC credit reporting channels is not empty, then calculate the routing probability corresponding to each available PBOC credit reporting channel based on the initial routing configuration parameters corresponding to each available PBOC credit reporting channel in the set of available PBOC credit reporting channels.

[0081] In one embodiment, if the set of available credit reporting channels is not empty, the initial routing configuration parameters corresponding to each available credit reporting channel in the set are obtained, wherein the initial routing configuration parameters include at least the initial routing probability; all initial routing configuration parameters in the set of available credit reporting channels are summed to obtain the total initial routing probability; the ratio of the initial routing configuration parameter corresponding to each available credit reporting channel to the total initial routing probability is calculated, and the ratio is used as the routing probability corresponding to each available credit reporting channel.

[0082] Example Explanation: The set of available People's Bank of China (PBOC) credit reporting channels includes three channels: K, L, and M. The proportions of these three channels are "K":"0.1", "L":"0.2", and "M":"0.2", respectively. Therefore, the routing probability of PBOC credit reporting channel K is 0.1 / (0.1+0.2+0.2) = 0.2, or 20%; the routing probability of PBOC credit reporting channel L is 0.2 / (0.1+0.2+0.2) = 0.4, or 40%; and the routing probability of PBOC credit reporting channel M is 0.2 / (0.1+0.2+0.2) = 0.4, or 40%.

[0083] In one embodiment, if the set of available People's Bank of China credit reporting channels is empty, a preset default credit reporting channel is automatically activated as the target credit reporting channel.

[0084] Step 104: Based on the routing probability, determine the target credit reporting channel from the set of available People's Bank of China credit reporting channels through a random number interval matching mechanism, and initiate a credit reporting query request based on the target credit reporting channel.

[0085] In one embodiment, when determining the target credit reporting channel from the set of available People's Bank of China (PBOC) credit reporting channels based on the routing probability using a random number interval matching mechanism, a probability interval is constructed, wherein the probability interval starts at 0 and ends at the total routing probability, which is calculated from the routing probabilities corresponding to each available PBOC credit reporting channel; based on the routing probabilities corresponding to each available PBOC credit reporting channel, the routing probabilities are sorted in a preset order to obtain a routing probability sorting result; based on the routing probability sorting result, the probability interval is divided, and each sub-interval uniquely corresponds to a single available PBOC credit reporting channel; a random decimal is generated based on a random function, and the target probability interval into which the random decimal falls is determined, and the target available PBOC credit reporting channel corresponding to the target probability interval is taken as the target credit reporting channel.

[0086] Specifically, the routing probabilities corresponding to each available People's Bank of China (PBOC) credit reporting channel are sorted in ascending order. For example, the routing probabilities of PBOC credit reporting channels K, L, and M (0.2, 0.4, 0.4) are sorted in ascending order, resulting in K: 0.2 → L: 0.4 → M: 0.4. If there are PBOC credit reporting channels with the same routing probability, such as L and M (both 0.4), they are sorted according to the channel identifier or preset priority to ensure a unique sorting result.

[0087] Specifically, when dividing the probability interval based on the routing probability ranking result, the cumulative value of the routing probability corresponding to each routing probability in the routing probability ranking result is calculated, and the cumulative value of the routing probability is used as the interval boundary point to divide the probability interval; for example, the sub-interval of the first channel K after ranking is [0, the probability of the first channel), i.e., [0, 0.2); the sub-interval of the second channel L is the cumulative value of the probability of the previous channel, i.e., [0.2, 0.2+0.4=0.6, the cumulative value of the probability of the first two channels); the sub-interval of the third channel M is [the cumulative value of the probability of the first two channels, 1), i.e., [0.6, 1); this division method follows the principle that each sub-interval corresponds to only a single channel, ensuring a unique mapping relationship between channels and intervals.

[0088] Specifically, the Math.random() function is used to generate random numbers. This function generates random decimals that are greater than or equal to 0 and less than 1.

[0089] Specifically, the target channel is determined by the sub-interval into which the random decimal number falls. For example, if the random number is in the range [0, 0.2), it corresponds to the K-level People's Bank of China credit reporting channel; if it is in the range [0.2, 0.6), it corresponds to the L-level channel; and if it is in the range [0.6, 1), it corresponds to the M-level channel. Example: Taking the generated random number 0.314 as an example, this value is greater than 0.2 and less than 0.6, falling into the sub-interval corresponding to the L-level channel. Therefore, the L-level channel is ultimately determined as the target credit reporting channel. This method reflects the channel scheduling priority through probability and avoids uneven channel load caused by fixed allocation through random generation, thus improving channel utilization and ensuring link stability.

[0090] In one embodiment, initiating a credit inquiry request based on a target credit reporting channel specifically includes: calling a contract processing system to sign a credit authorization contract, receiving a contract signing identifier returned by the contract processing system, and obtaining the contract file address from the contract processing system based on the contract signing identifier; calling a user information system to obtain user basic information and authorized image information based on the user identifier information; performing availability verification on the user basic information and the authorized image information, and interrupting the credit inquiry process if the verification fails; if the verification passes, initiating a credit inquiry request based on the target credit reporting channel by calling an external system, passing the user identifier information, the authorized image information, and the contract file address to the external system, receiving the credit report and query result identifier returned by the external system, and storing the credit report, the query result identifier, and the corresponding user identifier information together in a data storage medium.

[0091] Specifically, when the contract processing system is invoked to sign a credit information authorization contract, the credit information platform, after determining the target credit information channel, first invokes the interface of the internally deployed contract processing system, and then further connects to the signing service of the third-party electronic signature supplier based on the contract processing system; the user completes the electronic signature operation of the "Personal Credit Information Inquiry Authorization Letter" through the signing page of the upstream business system.

[0092] Specifically, after the signing is completed, the third-party signing supplier returns a confirmation message of successful signing to the contract processing system. The contract processing system then generates a unique contract signing identifier, such as a contract signing serial number, and returns the contract signing identifier to the credit reporting platform.

[0093] Specifically, after receiving the contract signing identifier, the credit reporting platform stores it in the Redis cache. Subsequently, the credit reporting platform calls the contract file query interface of the contract processing system again, passing in the contract signing identifier. The contract processing system retrieves the signed "Personal Credit Inquiry Authorization Letter" PDF file from the OSS storage service, returns the OSS address corresponding to the file, and uses the OSS address as the contract file address.

[0094] Specifically, the credit reporting platform extracts user identification information from the credit inquiry request and calls the user authorization data query interface of the unified user information system. The request parameters of this interface include user identification information and data type identifier. After receiving the request, the user information system retrieves the user's basic information carried in the credit inquiry request from its MySQL master database. At the same time, it retrieves the authorized image information that the user has uploaded in advance and passed the review from the OSS storage module. The authorized image information includes, but is not limited to, a live face image, a front image of the ID card, and a back image of the ID card. The system returns the three OSS addresses corresponding to the above images and uses them as the authorized image information. After receiving the data returned by the user information system, the credit reporting platform integrates the user's basic information and the authorized image information into a user authorization data package, which, together with the contract document address obtained in the previous steps, constitutes the core data for subsequent verification and query.

[0095] Specifically, the credit reporting platform performs field non-empty checks on the acquired user basic information to determine whether there are empty values ​​or incorrect formats in the user's name, ID number, and mobile phone number. If any field does not meet the requirements, the check fails, the credit reporting query process is immediately interrupted, and an error message indicating that the user information is incomplete is returned to the upstream system, requesting that the information be supplemented and improved.

[0096] Specifically, the credit reporting platform iterates through the three OSS addresses corresponding to the authorized image information and the contract file address, initiating HTTP GET requests to verify address validity, file format conformity, and file integrity. Address validity refers to checking if the returned status code is 200 (indicating the address is accessible); a 404 (file not found) or 403 (insufficient permissions) indicates the address is invalid. File format conformity is verified by reading the header information of the URL to determine if the facial liveness image and the front and back images of the ID card are in JPG format, and if the contract file is in PDF format; mismatches result in invalidity. File integrity refers to performing an MD5 checksum on accessible files; inconsistent checksums indicate file corruption. If all the OSS addresses of the authorized image information pass verification and the user's basic information is normal, the verification is successful, and the query process continues. If any file fails verification, the verification is considered a failure, the process is interrupted, and a failure log is recorded for subsequent troubleshooting.

[0097] Specifically, after the credit reporting platform identifies the target credit reporting channel, it calls the credit query interface of the People's Bank of China's (PBOC) front-end system associated with that channel, according to the corresponding interface protocol. The request parameters are in JSON format and include: user identification information, user basic information, authorized image information, contract document address, and the credit reporting platform's signature information. Upon receiving the request, the PBOC front-end system verifies the signature of the parameters and reviews the authorized image. After the review is passed, it initiates a formal query request to the PBOC credit reporting system. After the PBOC credit reporting system returns the credit report, the PBOC front-end system generates a unique query result identifier and returns the credit report and the query result identifier to the credit reporting platform.

[0098] Specifically, after receiving the returned data, the credit reporting platform stores core fields such as user identification information, query result identifier, query time, and target channel identifier in the credit query log table of the MySQL database. At the same time, it associates the credit report with the user authorization data package and stores it in the MongoDB database, and creates an index of user identification information and query result identifier to improve the efficiency of subsequent cached queries.

[0099] Example 2, see Figure 2 , Figure 2 This is a schematic diagram of an embodiment of a dynamic routing credit inquiry device provided in this application. Corresponding to the above-described dynamic routing credit inquiry method, this application also provides a dynamic routing credit inquiry device. This dynamic routing credit inquiry device includes modules for executing the aforementioned dynamic routing credit inquiry method, and can be configured in a desktop computer, tablet computer, laptop computer, or other terminal. Specifically, the dynamic routing credit inquiry device includes a People's Bank of China credit channel set acquisition module 201, a multi-dimensional route filtering module 202, a route probability calculation module 203, and a target credit channel determination module 204.

[0100] The People's Bank of China (PBOC) credit information channel set acquisition module 201 is used to acquire a preset PBOC credit information channel set and the initial routing configuration parameters corresponding to each PBOC credit information channel in the PBOC credit information channel set when it is detected that there is no corresponding credit information query cache result for the credit information query request.

[0101] The multi-dimensional routing filtering module 202 is used to filter the set of PBOC credit reporting channels based on preset multi-dimensional routing filtering rules to obtain a set of available PBOC credit reporting channels.

[0102] The routing probability calculation module 203 is used to calculate the routing probability of each available credit reporting channel based on the initial routing configuration parameters corresponding to each available credit reporting channel in the available credit reporting channel set if the available credit reporting channel set is not empty.

[0103] The target credit reporting channel determination module 204 is used to determine the target credit reporting channel from the set of available People's Bank of China credit reporting channels based on the routing probability through a random number interval matching mechanism, and to initiate a credit reporting query request based on the target credit reporting channel.

[0104] In one embodiment, the credit inquiry device with dynamic routing provided in this application further includes: a credit inquiry request receiving module; wherein, the credit inquiry request receiving module is used to receive a credit inquiry request, wherein the credit inquiry request carries inquiry request parameters, the inquiry request parameters include at least user identification information, and based on the user identification information, determines whether there is a credit inquiry cache result corresponding to the user identification information and within its validity period; if it exists, it determines that a corresponding credit inquiry cache result has been detected for the credit inquiry request, and directly obtains and outputs the credit inquiry cache result; if it does not exist, it determines that no corresponding credit inquiry cache result has been detected for the credit inquiry request.

[0105] In one embodiment, the multi-dimensional routing filtering rules include at least one or more of the following: time routing rules, call count routing rules, stage routing rules, application routing rules, failure threshold routing rules, average time consumption routing rules, traffic routing rules, queue routing rules, and authorization verification routing rules.

[0106] In one embodiment, the multi-dimensional routing filtering module 202 is used to filter the set of People's Bank of China (PBOC) credit reporting channels based on preset multi-dimensional routing filtering rules to obtain a set of available PBOC credit reporting channels. Specifically, this includes: the credit inquiry request parameters at least include routing matching parameters; obtaining rule configuration information corresponding to the multi-dimensional routing filtering rules; determining, based on the rule configuration information and the routing matching parameters, whether each PBOC credit reporting channel in the set of PBOC credit reporting channels conforms to the multi-dimensional routing filtering rules; eliminating PBOC credit reporting channels that do not conform to the multi-dimensional routing filtering rules; and integrating PBOC credit reporting channels that conform to the multi-dimensional routing filtering rules into a set of available PBOC credit reporting channels.

[0107] In one embodiment, the routing probability calculation module 203 is used to calculate the routing probability corresponding to each available credit reporting channel based on the initial routing configuration parameters corresponding to each available credit reporting channel in the set of available credit reporting channels. Specifically, this includes: obtaining the initial routing configuration parameters corresponding to each available credit reporting channel in the set of available credit reporting channels, wherein the initial routing configuration parameters include at least the initial routing probability; summing all the initial routing configuration parameters in the set of available credit reporting channels to obtain the total initial routing probability; calculating the ratio of the initial routing configuration parameter corresponding to each available credit reporting channel to the total initial routing probability, and using the ratio as the routing probability corresponding to each available credit reporting channel.

[0108] In one embodiment, the target credit reporting channel determination module 204 is used to determine the target credit reporting channel from the set of available People's Bank of China (PBOC) credit reporting channels based on the routing probability using a random number interval matching mechanism. Specifically, this includes: constructing a probability interval, wherein the probability interval starts at 0 and ends at the total routing probability, wherein the total routing probability is calculated from the routing probabilities corresponding to each available PBOC credit reporting channel; sorting the routing probabilities according to a preset order based on the routing probabilities corresponding to each available PBOC credit reporting channel to obtain a routing probability sorting result; dividing the probability interval based on the routing probability sorting result, and ensuring that each sub-interval uniquely corresponds to a single available PBOC credit reporting channel; generating a random decimal based on a random function, determining the target probability interval into which the random decimal falls, and using the target available PBOC credit reporting channel corresponding to the target probability interval as the target credit reporting channel.

[0109] In one embodiment, the target credit reporting channel determination module 204 is used to initiate a credit reporting query request based on the target credit reporting channel. Specifically, it includes: calling a contract processing system to sign a credit reporting authorization contract, receiving a contract signing identifier returned by the contract processing system, and obtaining the contract file address from the contract processing system based on the contract signing identifier; calling a user information system to obtain user basic information and authorized image information based on the user identifier information; performing availability verification on the user basic information and the authorized image information, and interrupting the credit reporting query process if the verification fails; if the verification passes, initiating a credit reporting query request based on the target credit reporting channel by calling an external system, passing the user identifier information, the authorized image information, and the contract file address to the external system, receiving the credit report and query result identifier returned by the external system, and storing the credit report, the query result identifier, and the corresponding user identifier information in a data storage medium.

[0110] The aforementioned dynamic routing credit inquiry device can implement the dynamic routing credit inquiry method of the above method embodiments. The options in the above method embodiments are also applicable to this embodiment, and will not be detailed here.

[0111] like Figure 3 As shown, Figure 3 This is a schematic diagram of the structure of a computer device provided in this application; it includes a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112 and the memory 113 communicate with each other through the communication bus 114, and the memory 113 is used to store computer programs.

[0112] In one embodiment of this application, the processor 111, when executing the program stored in the memory 113, implements the dynamic routing credit query method provided in any of the foregoing method embodiments.

[0113] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program may be stored in a storage medium, which is a computer-readable storage medium. The computer program is executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0114] Therefore, embodiments of this application also provide a computer-readable storage medium storing a computer program thereon, wherein the computer program, when executed by a processor, implements the steps of the dynamic routing credit query method provided in any of the foregoing method embodiments.

[0115] The storage medium is a physical, non-transient storage medium, such as a USB flash drive, external hard drive, read-only memory (ROM), magnetic disk, or optical disk, or any other physical storage medium capable of storing program code. The computer-readable storage medium can be non-volatile or volatile.

[0116] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0117] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is merely a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0118] The steps in the methods of this application embodiment can be adjusted, merged, or deleted according to actual needs. The units in the apparatus of this application embodiment can be merged, divided, or deleted according to actual needs. Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0119] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0120] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0121] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Since these modifications and variations fall within the scope of the claims and their equivalents, this application also intends to include these modifications and variations.

[0122] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A dynamic routing method for credit inquiry, characterized in that, Comprise: When it is detected that the credit inquiry request does not exist corresponding credit inquiry cache result, a preset human credit channel set and initial routing configuration parameters corresponding to each human credit channel in the human credit channel set are obtained; Based on the preset multi-dimensional routing screening rule, the human credit channel set is screened to obtain a set of available human credit channels; If the set of available human credit channels is not empty, the routing probability corresponding to each available human credit channel is calculated based on the initial routing configuration parameters corresponding to each available human credit channel in the set of available human credit channels; Based on the routing probability, a target credit channel is determined from the set of available human credit channels through a random number interval matching mechanism, and a credit inquiry request is initiated based on the target credit channel.

2. The method of claim 1, wherein, Also include: Receive a credit inquiry request, wherein the credit inquiry request carries a credit request parameter, and the credit request parameter at least contains user identification information; Based on the user identification information, it is judged whether there is a credit inquiry cache result corresponding to the user identification information and within the valid period, if there is, it is determined that the credit inquiry request exists corresponding credit inquiry cache result, the credit inquiry cache result is directly obtained and output; if not, it is determined that the credit inquiry request does not exist corresponding credit inquiry cache result.

3. The method of claim 1, wherein, The multi-dimensional routing screening rule at least includes one or more of time routing rule, call quantity routing rule, stage routing rule, application routing rule, failure threshold routing rule, average time consumption routing rule, traffic routing rule, queue routing rule and authorization check routing rule.

4. The method of claim 3, wherein, Based on the preset multi-dimensional routing screening rule, the human credit channel set is screened to obtain a set of available human credit channels, specifically including: The credit request parameter at least contains a routing matching parameter; Obtain the rule configuration information corresponding to the multi-dimensional routing screening rule, and based on the rule configuration information and the routing matching parameter, judge whether each human credit channel in the human credit channel set meets the multi-dimensional routing screening rule, eliminate human credit channels that do not meet the multi-dimensional routing screening rule, and integrate human credit channels that meet the multi-dimensional routing screening rule into a set of available human credit channels.

5. The method of claim 1, wherein, Based on the initial routing configuration parameters corresponding to each available human credit channel in the set of available human credit channels, the routing probability corresponding to each available human credit channel is calculated, specifically including: Obtain the initial routing configuration parameters corresponding to each available human credit channel in the set of available human credit channels, wherein the initial routing configuration parameters at least include initial routing probability; Sum all initial routing configuration parameters in the set of available human credit channels to obtain total initial routing probability; The ratio of the initial routing configuration parameter corresponding to each available human credit channel to the total initial routing probability is calculated respectively, and the ratio is taken as the routing probability corresponding to each available human credit channel.

6. The method of claim 5, wherein, The target credit investigation channel is determined from the set of available credit investigation channels based on the routing probability through a random number interval matching mechanism, and specifically includes: A probability interval is constructed, wherein the probability interval has 0 as the interval starting point and the total routing probability as the interval ending point, wherein the total routing probability is calculated from the routing probability corresponding to each available credit investigation channel; The routing probability is sorted in a preset order based on the routing probability corresponding to each available credit investigation channel, and a routing probability sorting result is obtained; Based on the routing probability sorting result, the probability interval is divided, and each probability sub-interval obtained by the division is uniquely corresponding to a single available credit investigation channel; A random decimal is generated based on a random function, it is judged that the target probability interval into which the random decimal falls, and the target available credit investigation channel corresponding to the target probability interval is taken as the target credit investigation channel.

7. The method of claim 2, wherein, The credit investigation query request is initiated based on the target credit investigation channel, and specifically includes: A contract processing system is called to sign a credit investigation authorization contract, a contract signing identifier returned by the contract processing system is received, and a contract file address is obtained from the contract processing system based on the contract signing identifier; Based on the user identifier information, a user information system is called to obtain user basic information and authorized image information; The user basic information and the authorized image information are subjected to availability verification, and if the verification fails, the credit investigation query process is interrupted; If the verification passes, an external system is called based on the target credit investigation channel to initiate a credit investigation query request, the user identifier information, the authorized image information, and the contract file address are input into the external system, a credit investigation report and a query result identifier returned by the external system are received, and the credit investigation report, the query result identifier, and the corresponding user identifier information are stored in a data storage medium.

8. A dynamic routing credit inquiry apparatus, comprising: It includes: A set of credit investigation channel collection acquisition modules, multi-dimensional routing screening modules, routing probability calculation modules, and target credit investigation channel determination modules; The set of credit investigation channel collection acquisition modules are used to acquire a preset set of credit investigation channels and initial routing configuration parameters corresponding to each credit investigation channel in the set of credit investigation channels when it is detected that there is no corresponding credit investigation query cache result for a credit investigation query request; The multi-dimensional routing screening modules are used to screen the set of credit investigation channels based on preset multi-dimensional routing screening rules to obtain a set of available credit investigation channels; The routing probability calculation modules are used to calculate the routing probability corresponding to each available credit investigation channel based on the initial routing configuration parameters corresponding to each available credit investigation channel in the set of available credit investigation channels if the set of available credit investigation channels is not empty; The target credit investigation channel determination modules are used to determine a target credit investigation channel from the set of available credit investigation channels based on the routing probability through a random number interval matching mechanism, and initiate a credit investigation query request based on the target credit investigation channel.

9. A computer device, comprising: The computer device comprises a memory and a processor, the memory stores a computer program, and the processor implements the method according to any one of claims 1-7 when executing the computer program.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, and the computer program can implement the method according to any one of claims 1-7 when being executed by a processor.

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