WO2022134424A1 - 业务流处理方法、装置、计算机设备及存储介质 - Google Patents

业务流处理方法、装置、计算机设备及存储介质 Download PDF

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Publication number
WO2022134424A1
WO2022134424A1 PCT/CN2021/091691 CN2021091691W WO2022134424A1 WO 2022134424 A1 WO2022134424 A1 WO 2022134424A1 CN 2021091691 W CN2021091691 W CN 2021091691W WO 2022134424 A1 WO2022134424 A1 WO 2022134424A1
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Prior art keywords
customer group
node
category
target
flow
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PCT/CN2021/091691
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English (en)
French (fr)
Inventor
叶冰清
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平安普惠企业管理有限公司
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Publication of WO2022134424A1 publication Critical patent/WO2022134424A1/zh

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/10—Flow control; Congestion control
    • H04L47/24—Traffic characterised by specific attributes, e.g. priority or QoS
    • H04L47/2441—Traffic characterised by specific attributes, e.g. priority or QoS relying on flow classification, e.g. using integrated services [IntServ]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/25—Integrating or interfacing systems involving database management systems
    • G06F16/254—Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/54—Interprogram communication
    • G06F9/546—Message passing systems or structures, e.g. queues
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2209/00—Indexing scheme relating to G06F9/00
    • G06F2209/54—Indexing scheme relating to G06F9/54
    • G06F2209/547—Messaging middleware
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2209/00—Indexing scheme relating to G06F9/00
    • G06F2209/54—Indexing scheme relating to G06F9/54
    • G06F2209/548—Queue

Definitions

  • the present application relates to the technical field of rack operation and maintenance, and in particular, to a business flow processing method, apparatus, computer equipment and storage medium.
  • the Southeast Asian market as a popular area for Chinese fintech to go overseas in recent years, has a customer base of about 600 million, has a relatively stable network infrastructure construction, and has the basic coverage of mobile Internet and smart phones.
  • Embodiments of the present application provide a service flow processing method, apparatus, computer equipment and storage medium to solve the problem that the existing traditional single service flow processing process cannot be executed normally when there is a gap or blank in user information.
  • a business flow processing method comprising:
  • the workflow engine calling the workflow engine to execute the first business flow corresponding to the customer group category, so as to collect the personal information of the user synchronously; wherein, the first business flow includes a first difference node;
  • a service flow processing device comprising:
  • the initial customer group category acquisition module is used to acquire the customer group category selected by the user according to the preset customer group category classification conditions
  • a personal information collection module configured to invoke a workflow engine to execute the first business flow corresponding to the customer group category, so as to collect the personal information of the user synchronously; wherein, the first business flow includes a first difference node;
  • a customer group category detection module configured to perform category analysis according to the currently collected personal information when the first difference node in the first business flow is executed, and determine whether the customer group category of the user has changed;
  • the second business flow acquisition and execution module is configured to acquire the second business flow corresponding to the changed target customer group category when the customer group category changes, and control the workflow engine to execute the second business flow .
  • a computer device comprising a memory, a processor and a computer program stored in the memory and running on the processor, the processor implements the following steps when executing the computer program:
  • the workflow engine calling the workflow engine to execute the first business flow corresponding to the customer group category, so as to collect the personal information of the user synchronously; wherein, the first business flow includes a first difference node;
  • a computer storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:
  • the workflow engine calling the workflow engine to execute the first business flow corresponding to the customer group category, so as to collect the personal information of the user synchronously; wherein, the first business flow includes a first difference node;
  • the customer group category selected by the user according to the preset customer group category classification condition is obtained in advance, and the process node in the first business flow corresponding to the customer group category is first executed.
  • the category analysis is performed according to the collected personal information to determine whether the user's customer group category changes, and when the customer group category changes, the changed target customer group is obtained.
  • the second service flow corresponding to the group category is controlled, and the workflow engine is controlled to execute the second service flow, so as to realize the dynamic determination of the credit authorization process that conforms to the user, so as to ensure the smooth execution of the service flow in the case of blank or faulty user information.
  • the customer group selected by the user is inaccurate, it can be judged dynamically based on the collected personal information to finally determine the business flow that matches the user.
  • FIG. 1 is a schematic diagram of an application environment of a service flow processing method in an embodiment of the present application
  • FIG. 2 is a flowchart of a service flow processing method in an embodiment of the present application
  • FIG. 3 is a flowchart of a service flow processing method in an embodiment of the present application.
  • FIG. 5 is a flowchart of a service flow processing method in an embodiment of the present application.
  • FIG. 6 is a flowchart of a service flow processing method in an embodiment of the present application.
  • FIG. 7 is a flowchart of a service flow processing method in an embodiment of the present application.
  • FIG. 8 is a flowchart of a service flow processing method in an embodiment of the present application.
  • FIG. 9 is a schematic diagram of a service flow processing apparatus in an embodiment of the present application.
  • FIG. 10 is a schematic diagram of a computer device in an embodiment of the present application.
  • the service flow processing method can be applied in the application environment as shown in FIG. 1 , wherein a computer device communicates with a server through a network.
  • Computer devices can be, but are not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices.
  • the server can be implemented as a standalone server.
  • a service flow processing method is provided, and the method is applied to the server in FIG. 1 as an example for description, including the following steps:
  • S201 Acquire a customer group category selected by a user according to a preset customer group category classification condition.
  • the method can be applied to an intelligent credit granting system, which is used to collect the user's personal information synchronously by executing the process nodes in the business flow when the user information is blank or faulty, and according to the collected personal information, Dynamically determine the credit process that conforms to the user to ensure the smooth execution of the credit process and achieve pricing differentiation.
  • the customer group selected by the user is inaccurate, the user can make a dynamic judgment based on the collected personal information to finally determine the credit granting process that conforms to the user, so as to achieve the purpose of risk control and fraud prevention.
  • users can be divided according to the customer group preset by the system. Conditions (such as whether the user has a credit card), choose the corresponding customer group.
  • multiple categories of the customer group can be set according to actual needs, such as good, general, and poor.
  • the customer score can be obtained by combining the scores of multiple judgment conditions, such as judgment condition A, when it is judged to be yes, its corresponding score is a, and no. is b, the judgment condition B, when the judgment is yes, the corresponding score is c, and no is d; the user accumulates the branches corresponding to each judgment branch according to their own actual conditions to obtain the final score (customer score), so that According to the customer rating, select the customer group category to which it belongs.
  • judgment condition A when it is judged to be yes, its corresponding score is a, and no. is b
  • the judgment condition B when the judgment is yes, the corresponding score is c, and no is d
  • the user accumulates the branches corresponding to each judgment branch according to their own actual conditions to obtain the final score (customer score), so that According to the customer rating, select the customer group category to which it belongs.
  • S202 Invoke the workflow engine to execute the first business flow corresponding to the customer group category, so as to synchronously collect the personal information of the user; wherein the first business flow includes a first difference node.
  • the business flow may refer to a credit granting process or other business processes, which is not limited here.
  • the first business flow refers to the business flow corresponding to the current customer group category.
  • the server will call the workflow engine to execute the first business flow corresponding to the customer group category, and synchronously collect the user's personal information, so that the user can follow the user's personal information.
  • the update of the personal information includes but is not limited to the user's basic information and qualification information, and the basic information may refer to the user's name, age, gender and other basic information.
  • the qualification information may refer to the user's credit information, such as whether the payment is overdue, credit information, loan information, and the like.
  • the personal information of the above-mentioned users can also be stored in a node of a blockchain.
  • the first business flow includes a first difference node
  • the first difference node refers to a personalized flow node between the first business flow and business flows corresponding to other customer groups, such as a credit inquiry node, an internal and external hacker List node.
  • different business flows include a reference flow
  • the reference flow includes a plurality of reference nodes executed in sequence, such as information verification, basic information collection, customer group qualification collection, initial credit granting by customer group, asset classification increase. Letter, contact information input, lending bank card binding, submission for approval (STP/manual approval), return of supplementary documents.
  • the first difference node may be disposed between two adjacent reference nodes.
  • S203 When executing to the first difference node in the first service flow, perform category analysis according to the currently collected personal information to determine whether the category of the user's customer group has changed.
  • the change result of the customer group category includes change or no change, and when the customer group category changes, it may include the increase or decrease of the customer category level, which is not limited here.
  • the workflow engine executes each process node in the first business flow in sequence, and when the first difference node in the first business flow is executed, a customer group analysis program is triggered, that is, according to the currently collected data The personal information is analyzed to determine whether the user's customer group has changed.
  • the second business flow corresponding to the changed target customer group is obtained, and the workflow engine is controlled to execute the second business flow.
  • the current personal information is analyzed by category, and the dynamic determination is made.
  • the target customer group category of the current user so as to determine whether the customer group category of the user has changed, by first collecting the customer group category selected by the customer, and dynamically determining the target customer group category according to the user's personal information, so that the workflow engine can dynamically determine the target customer group category. Execute the second business flow corresponding to the target customer group category.
  • the second business flow refers to a business flow that needs to be executed at the next moment when the customer group category changes. Specifically, when the customer group category changes, the second business flow corresponding to the changed target customer group category is obtained, and the workflow engine is controlled to execute the second business flow, so as to set the corresponding business flow for different customer group categories, In order to execute the corresponding business flow when the user customer group category changes.
  • the acquisition methods for the second business flow include but are not limited to three types: one is that each customer group category corresponds to an independent business flow, and when the customer group category changes, the The stored second business flow is passed to the workflow engine, so that the workflow engine executes the second business flow; one is to share the reference node between business flows corresponding to different customer groups, and maintain the correspondence of each business flow separately
  • the difference node can be dynamically assembled into the current workflow to be executed, and the difference node of the original business flow is set to the skip state.
  • the next service flow that is, the second service flow, is acquired.
  • the other is to pre-assemble the reference node and the difference nodes corresponding to each service flow, and when determining the service flow to be executed, the corresponding second service flow can be obtained by dynamically adjusting the state of each difference node.
  • steps S203 to S204 may be repeatedly performed until the process cut-off point is entered, so as to complete the credit granting process.
  • the customer group category selected by the user according to the preset customer group category classification conditions is obtained in advance, and the process node in the first business flow corresponding to the customer group category is first executed.
  • the process node in the first business flow corresponding to the customer group category is first executed.
  • perform category analysis according to the collected personal information to determine whether the user's customer group category has changed, and when the customer group category has changed, obtain the second business flow corresponding to the changed target customer group category, and Control the workflow engine to execute the second business flow, so as to dynamically determine the credit granting process that conforms to the user, so as to ensure the smooth execution of the credit granting process and realize pricing differentiation in the case of blank or faulty user information.
  • the customer group selected by the user is inaccurate, the user can make a dynamic judgment based on the collected personal information to finally determine the credit granting process that conforms to the user, so as to achieve the purpose of risk control and fraud prevention.
  • both the first service flow and the second service flow include a plurality of reference nodes executed in sequence; the first difference node is set at two adjacent reference nodes in the first service flow. between; the method also includes the following steps:
  • S302 Use the next adjacent reference node of the first difference node in the first service flow as the target execution node; the target execution node is used to indicate the start execution node in the second service flow.
  • S303 Transfer the target execution node to the workflow engine, so that the current execution node of the workflow engine is transferred to the second service flow, and control the workflow engine to execute the second service flow from the starting execution node.
  • the customer group category detection program is bound to the first difference node. Since the first difference node can be set between two adjacent reference nodes, when the execution flow of the workflow engine flows, it can be directly connected with the first difference node.
  • the next reference node adjacent to a difference node is used as the initial execution node of the next business process, so as to realize the continuous execution of the process, and realize the purpose that the user does not perceive when the business flow changes.
  • the second service flow when the first service flow includes process nodes executed in sequence, that is, A (reference node)-B (reference node)-C (first difference node)-D (reference node); the second service flow also includes Process nodes A (reference node)-B (reference node)-C' (second difference node)-D (reference node) executed in sequence, when the workflow engine executes to the first difference node, if the user category changes , at this time, the next reference node D adjacent to the first difference node in the first service flow can be used as the target execution node, so that the current execution node of the workflow engine flows to the second service flow corresponding to the target execution node
  • the reference node is D, and the workflow engine is controlled to execute the second service flow from the reference node corresponding to the target execution node.
  • the first business flow includes a plurality of reference nodes that are executed in sequence; in step S204, that is, when the customer group category changes, obtain the second corresponding to the changed target customer group category.
  • business flow, and control the workflow engine to execute the second business flow which specifically includes the following steps:
  • S402 Acquire the second difference node corresponding to the target customer group category and the upper and lower levels of the node corresponding to the second difference node.
  • S403 Assemble the reference node and the second difference node according to the upper and lower levels of the nodes, so as to reconstruct the first service flow on the basis of the first service flow, and obtain the second service flow.
  • the second difference node refers to the personalized process node of the business flow corresponding to the changed target customer group category.
  • the reference nodes can be shared among the business flows corresponding to different customer groups, and the difference nodes corresponding to each business flow can be maintained separately.
  • the difference nodes can be dynamically assembled by dynamically assembling To the currently executed service flow, and setting the difference node of the current service flow to the skip state, the next service flow, that is, the second service flow can be obtained.
  • the skip state is used to indicate that the current node can skip in the currently executed service flow and does not need to be executed.
  • the node states of all process nodes assembled into the currently executing service flow are the active state, that is, the state that needs to be executed, and cannot be skipped.
  • the node state corresponding to the first difference node corresponding to the first business flow is set to a skip state; the second difference node corresponding to the target customer group category and the second difference node corresponding to the target customer group category are obtained.
  • Node upper and lower levels that is, the upper-level inflow node and the lower-level outflow node of the second difference node, so that the second difference node is assembled into the first service flow according to the upper and lower levels of the node, so as to obtain the second service flow, so as to realize the sharing of reference nodes , there is no need to create a business flow separately, saving resources.
  • the second difference node When assembling the second difference node, it can also be judged whether the upper-level inflow node of the second difference node is the next adjacent reference node of the first difference node in the first service flow or the next adjacent reference node after the next adjacent reference node. Process node, if it is, then assemble it into the first service flow, if not, because when the second service flow is executed subsequently, it is not necessary to execute the reference node before the first difference node, in order to improve the system performance and ensure the validity of the assembly , the second difference node can be judged, if it meets the conditions, it will be assembled, otherwise, no assembly will be required.
  • the first service flow further includes a second difference node corresponding to the target customer group category and a plurality of reference nodes executed in sequence; the second difference node is set on two adjacent reference nodes. between nodes; the first difference node is set between two adjacent reference nodes; in step S204, that is, when the customer group category changes, the second service flow corresponding to the changed target customer group category is obtained, which specifically includes the following step:
  • S502 Set the node state of the second difference node to the active state to acquire the second service flow.
  • the reference node is pre-assembled with the difference nodes corresponding to each service flow, and when the service flow to be executed, that is, the second service flow, is determined, the state of each difference node is dynamically adjusted to obtain the corresponding and second service flow. business flow.
  • the first business flow includes a second difference node corresponding to the target customer group category and a plurality of reference nodes executed in sequence; the second difference node is set between two adjacent reference nodes; the first difference node is set between two Between two adjacent reference nodes; the first difference node and the second difference node can be set at the same or different positions. When set at the same position, due to the uniqueness of the workflow engine execution, that is, according to the currently executed business If the flow is different, the corresponding difference node is executed, so it will not affect the normal execution of the workflow.
  • the business flows corresponding to different customer groups are pre-assembled into a complete workflow, so that when the subsequent process changes, the node status can be dynamically adjusted without the need to maintain the reference node and the difference node separately.
  • the method further includes the following steps:
  • S601 Acquire a service flow configuration request; wherein, the service flow configuration request includes the customer group category to be configured.
  • S602 Display a business flow configuration table corresponding to the customer group category; wherein, the business flow configuration table includes configurable process nodes and node flow directions.
  • S603 Receive a target configuration parameter configured by a user according to the service flow configuration table; wherein, the target configuration parameter includes a target node and a target node flow direction corresponding to each target node.
  • S604 Assemble the business flow corresponding to the customer group category according to the target node and the flow direction of the target node corresponding to each target node.
  • the user can trigger a business flow configuration request through the front end, so that the server responds to the business flow configuration request and displays the business flow configuration table corresponding to the customer group category, where the business flow configuration table includes configurable process nodes and nodes of the process nodes.
  • the flow direction of the node includes the upper-level inflow node and the lower-level outflow node of the process node.
  • the configurable process nodes include but are not limited to information verification, basic information collection, customer group qualification collection, initial credit extension by customer group, asset classification credit enhancement, contact information input, lending bank card binding, submission and approval (STP/ Manual approval), rollback of supplementary documents, internal and external blacklist nodes, access risk control nodes, credit query nodes, customer group scoring nodes, etc.
  • the specific content of the node can also be configured, such as the basic credit information field corresponding to the credit query node and the preset credit threshold, by setting the corresponding decision rule or judgment for the node. Conditions, to determine whether the user's customer group category has changed when the business flow needs to be executed later.
  • the business processes corresponding to the customer group categories are assembled according to the target process node and the target node flow direction corresponding to each target process node.
  • attributes of business products can also be configured, and different customer group category judgment conditions can be set for different products according to actual conditions, which is not limited here.
  • product attributes include but are not limited to accounting terms, sales terms, interest rate settings, transaction settings, fee settings, and repayment order, which can be further configured for different product attributes.
  • accounting terms can also be used for product accounting, product transaction accounting, and product Transaction allocation, etc. are configured.
  • step S202 the method further includes the following steps:
  • S701 Format the personal information, generate message data, and push it to a message queue.
  • this method can collect the basic information, credit information, loan information and other personal information of the user by connecting multiple channels. Specifically, after the personal information of the user is collected, the format of the personal information can be converted to generate message data and push it to the message queue (ie, message middleware, such as kafka).
  • message middleware such as kafka
  • a storage program can be preset for a unified data format, such as json format.
  • the user's personal information can be stored through a production-consumption architecture, that is, the producer can produce data and push it to the message queue, so that the consumer can consume the data in the message queue, which can realize multi-thread concurrency.
  • S702 Perform data cleaning on the data in the message queue to obtain cleaned message data.
  • the data cleaning can use the SparkStreaming program to implement ETL cleaning of message data, and integrate scattered, messy, and non-uniform data together to facilitate subsequent storage and storage.
  • ETL is the process of loading the data of the business system into the data warehouse after extraction, cleaning and transformation.
  • the clear process of ETL includes data extraction, data cleaning and transformation, and data loading.
  • S703 Perform a dequeuing operation on the cleaned message data in the message queue, and store the message data in a database.
  • the cleaned message data in the message queue may be dequeued in a queue polling manner, so as to store the message data in the database.
  • step S202 the method further includes the following steps:
  • S802 Based on multiple risk control rule entries, construct a user's target risk control model, and store it in association with the user.
  • different customer group categories correspond to different risk control rule entries.
  • multiple risk control rule entries for the user can be determined according to the target customer group category, and based on multiple risk control rules Rule entry, build the user's target risk control model, and store it in association with the user, so that when the user performs the credit process again, the target risk control model can be directly called for risk assessment without executing all the preset risk control rule entries.
  • a service flow processing apparatus is provided, and the service flow processing apparatus is in one-to-one correspondence with the service flow processing method in the above-mentioned embodiment.
  • the business flow processing apparatus includes an initial customer group category acquisition module 10 , a personal information collection module 20 , a customer group category detection module 30 and a second business flow acquisition and execution module 40 .
  • the detailed description of each functional module is as follows:
  • the initial customer group category acquisition module 10 is configured to acquire the customer group category selected by the user according to the preset customer group category classification conditions.
  • the personal information collection module 20 is used for invoking the workflow engine to execute the first business flow corresponding to the customer group category, so as to collect the personal information of the user synchronously; wherein, the first business flow includes the first difference node.
  • the customer group category detection module 30 is configured to perform category analysis according to the currently collected personal information when executing to the first difference node in the first business flow, to determine whether the user group category has changed.
  • the second business flow acquisition and execution module 40 is configured to acquire the second business flow corresponding to the changed target customer group category when the customer group category changes, and control the workflow engine to execute the second business flow.
  • both the first service flow and the second service flow include a plurality of reference nodes executed in sequence; the first difference node is set between two adjacent reference nodes in the first service flow;
  • the service flow processing apparatus further includes a second service flow acquisition module, a target execution node acquisition module and a second service flow execution module.
  • the second business flow obtaining module is configured to obtain the second business flow corresponding to the target customer group category from the database when the change result is that the customer group category has changed.
  • the target execution node obtaining module is configured to use the next adjacent reference node of the first difference node in the first service flow as the target execution node; the target execution node is used to indicate the start execution node in the second service flow.
  • the second service flow execution module is used to transfer the target execution node to the workflow engine, make the current execution node of the workflow engine flow to the second service flow, and control the workflow engine to execute the second service from the initial execution node flow.
  • the first service flow includes a plurality of reference nodes that are executed in sequence; the service flow processing apparatus further includes a node state adjustment module, a second difference node acquisition module, and a first service flow reconstruction module.
  • the node state adjustment module is configured to set the node state corresponding to the first difference node to the skip state when the customer group category changes.
  • the second difference node obtaining module is configured to obtain the second difference node corresponding to the target customer group category and the node superiors and subordinates corresponding to the second difference node.
  • the first service flow reconstruction module is configured to assemble the reference node and the second difference node according to the upper and lower levels of the nodes, so as to reconstruct the first service flow on the basis of the first service flow and obtain the second service flow.
  • the first service flow further includes a second difference node corresponding to the target customer group category and a plurality of reference nodes executed in sequence; the second difference node is set between two adjacent reference nodes; the first difference node is set between two adjacent datum nodes.
  • the service flow processing apparatus further includes a node state adjustment module and a second service flow acquisition module.
  • a node state adjustment module configured to set the node state corresponding to the first difference node corresponding to the first service flow to a skip state when the change result is a change in the category of the customer group;
  • the second service flow obtaining module is configured to set the node state of the second difference node to the active state to obtain the second service flow.
  • the service flow processing apparatus further includes a service flow configuration request acquisition module, a service flow configuration table display module, a target configuration parameter receiving module, and a second service flow assembly module.
  • the business flow configuration request obtaining module is used for obtaining the business flow configuration request; wherein, the business flow configuration request includes the customer group category to be configured.
  • the business flow configuration table display module is used to display the business flow configuration table corresponding to the customer group category; wherein, the business flow configuration table includes configurable process nodes and node flow directions.
  • the target configuration parameter receiving module is configured to receive the target configuration parameters configured by the user according to the service flow configuration table; wherein, the target configuration parameters include target nodes and the target node flow direction corresponding to each target node.
  • the second business flow assembling module is configured to assemble the business flow corresponding to the customer group category according to the target node and the flow direction of the target node corresponding to each target node.
  • the service flow processing apparatus further includes a format conversion module, a data cleaning module and a storage module.
  • the format conversion module is used to format the personal information, generate message data, and push it to the message queue.
  • the data cleaning module is used to clean the data in the message queue to obtain the cleaned message data.
  • the storage module is used for dequeuing the cleaned message data in the message queue and storing the message data in the database.
  • the business flow processing apparatus further includes a risk control rule entry determination module and a model construction module.
  • the risk control rule entry determination module is used to determine multiple risk control rule entries of the user according to the target customer group category when the customer group category changes.
  • the model building module is used to construct the user's target risk control model based on multiple risk control rule entries, and store it in association with the user.
  • Each module in the above service flow processing apparatus may be implemented in whole or in part by software, hardware and combinations thereof.
  • the above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.
  • a computer device is provided, and the computer device may be a server, and its internal structure diagram may be as shown in FIG. 10 .
  • the computer device includes a processor, memory, a network interface, and a database connected by a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities.
  • the memory of the computer device includes a computer storage medium and an internal memory.
  • the computer storage medium stores an operating system, a computer program and a database.
  • the internal memory provides an environment for the execution of the operating system and computer programs in the computer storage medium.
  • the database of the computer device is used for storing data generated or acquired during the execution of the business flow processing method, such as the personal information of the user.
  • the network interface of the computer device is used to communicate with an external terminal through a network connection.
  • the computer program when executed by the processor, implements a method for processing a business stream.
  • a computer device including a memory, a processor, and a computer program stored in the memory and running on the processor, and the processor implements the service flow processing method in the above embodiment when the processor executes the computer program steps, such as steps S201-S204 shown in FIG. 2 , or steps shown in FIG. 3 to FIG. 8 .
  • the processor executes the computer program
  • the function of each module/unit in this embodiment of the service flow processing apparatus is realized, for example, the function of each module/unit shown in FIG. 9 is not repeated here to avoid repetition.
  • a computer storage medium is provided, and a computer program is stored on the computer storage medium, and when the computer program is executed by the processor, the steps of the service flow processing method in the above-mentioned embodiment are implemented, for example, step S201 shown in FIG. 2 . -S204, or the steps shown in FIG. 3 to FIG. 8, are not repeated here in order to avoid repetition.
  • the functions of each module/unit in the embodiment of the above-mentioned service flow processing apparatus such as the functions of each module/unit shown in FIG. 9 , are not repeated here in order to avoid repetition.
  • the computer-readable storage medium may be non-volatile or volatile.
  • Nonvolatile memory may include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory.
  • Volatile memory may include random access memory (RAM) or external cache memory.
  • RAM is available in various forms such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous chain Road (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM) and so on.
  • SRAM static RAM
  • DRAM dynamic RAM
  • SDRAM synchronous DRAM
  • DDRSDRAM double data rate SDRAM
  • ESDRAM enhanced SDRAM
  • SLDRAM synchronous chain Road (Synchlink) DRAM
  • SLDRAM synchronous chain Road (Synchlink) DRAM
  • Rambus direct RAM
  • DRAM direct memory bus dynamic RAM
  • RDRAM memory bus dynamic RAM
  • the blockchain referred to in this application is a new application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, and encryption algorithm.
  • Blockchain essentially a decentralized database, is a series of data blocks associated with cryptographic methods. Each data block contains a batch of network transaction information to verify its Validity of information (anti-counterfeiting) and generation of the next block.
  • the blockchain can include the underlying platform of the blockchain, the platform product service layer, and the application service layer.

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Abstract

本申请涉及基架运维技术领域，尤其涉及一种业务流处理方法、装置、设备及存储介质。该业务流处理方法包括获取用户根据预设的客群类别划分条件选择的客群类别；调用工作流引擎执行客群类别对应的第一业务流，以同步采集用户的个人信息；其中，第一业务流包括第一差异节点；当执行到第一业务流中的第一差异节点时，根据当前采集到的个人信息进行类别分析，确定用户的客群类别是否变化；当客群类别变化时，获取变化后的目标客群类别对应的第二业务流，并控制工作流引擎的执行第二业务流。该方法可实现在用户信息空白或断层的情况下，保证业务流的顺利执行的目的。本申请还涉及区块链技术领域，用户的个人信息还可进一步存储至区块链中。

Description

业务流处理方法、装置、计算机设备及存储介质
本申请以2020年12月24日提交的申请号为202011547099.9，发明名称为“业务流处理方法、装置、计算机设备及存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
 
技术领域
本申请涉及基架运维技术领域，尤其涉及一种业务流处理方法、装置、计算机设备及存储介质。
 背景技术
东南亚市场作为近年来中国金融科技出海的热门地区，具有约6亿客群基础、具有发展相对稳定的网络基建建设、具备移动互联网及智能手机基础覆盖能力。
目前，由于东南亚市场的地域特点，当地民众的信息采集受到安全性和地域性的影响，导致用户基础信息数据化、个人信用信息收集、个人信用信息持续的存储更新迭代等还存在着巨大的信息空白与信息断层，使得在传统单一的业务流处理流程中当用户信息出现断层或空白时，无法正常执行。
 技术问题
本申请实施例提供一种业务流处理方法、装置、计算机设备及存储介质，以解决现有的传统单一的业务流处理流程中当用户信息出现断层或空白时，无法正常执行的问题。
 技术解决方案
一种业务流处理方法，包括：
获取用户根据预设的客群类别划分条件选择的客群类别；
调用工作流引擎执行所述客群类别对应的第一业务流，以同步采集所述用户的个人信息；其中，所述第一业务流包括第一差异节点；
当执行到所述第一业务流中的第一差异节点时，根据当前采集到的所述个人信息进行类别分析，确定所述用户的客群类别是否变化；
当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，并控制所述工作流引擎的执行所述第二业务流。
一种业务流处理装置，包括：
初始客群类别获取模块，用于获取用户根据预设的客群类别划分条件选择的客群类别；
个人信息采集模块，用于调用工作流引擎执行所述客群类别对应的第一业务流，以同步采集所述用户的个人信息；其中，所述第一业务流包括第一差异节点；
客群类别检测模块，用于当执行到所述第一业务流中的第一差异节点时，根据当前采集到的所述个人信息进行类别分析，确定所述用户的客群类别是否变化；
第二业务流获取和执行模块，用于当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，并控制所述工作流引擎的执行所述第二业务流。
一种计算机设备，包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现如下步骤：
获取用户根据预设的客群类别划分条件选择的客群类别；
调用工作流引擎执行所述客群类别对应的第一业务流，以同步采集所述用户的个人信息；其中，所述第一业务流包括第一差异节点；
当执行到所述第一业务流中的第一差异节点时，根据当前采集到的所述个人信息进行类别分析，确定所述用户的客群类别是否变化；
当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，并控制所述工作流引擎的执行所述第二业务流。
一种计算机存储介质，所述计算机存储介质存储有计算机程序，所述计算机程序被处理器执行时实现如下步骤：
获取用户根据预设的客群类别划分条件选择的客群类别；
调用工作流引擎执行所述客群类别对应的第一业务流，以同步采集所述用户的个人信息；其中，所述第一业务流包括第一差异节点；
当执行到所述第一业务流中的第一差异节点时，根据当前采集到的所述个人信息进行类别分析，确定所述用户的客群类别是否变化；
当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，并控制所述工作流引擎的执行所述第二业务流。
 有益效果
上述业务流处理方法、装置、计算机设备及存储介质中，通过预先获取用户根据预设的客群类别划分条件选择的客群类别，并通过首先执行客群类别对应第一业务流中的流程节点，当执行到第一业务流中的第一差异节点时，以根据采集到的个人信息，进行类别分析，确定用户的客群类别是否变化，当客群类别变化时，获取变化后的目标客群类别对应的第二业务流，并控制工作流引擎的执行第二业务流，从而实现动态确定符合用户的授信流程，以在用户信息空白或断层的情况下，保证业务流的顺利执行。此外在用户自行选取的客群类别不准确的情况下，可通过动态根据采集到的个人信息进行判断，以最终确定符合用户的业务流。
 附图说明
为了更清楚地说明本申请实施例的技术方案，下面将对本申请实施例的描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1是本申请一实施例中业务流处理方法的一应用环境示意图；
图2是本申请一实施例中业务流处理方法的一流程图；
图3是本申请一实施例中业务流处理方法的一流程图；
图4是本申请一实施例中业务流处理方法的一流程图；
图5是本申请一实施例中业务流处理方法的一流程图；
图6是本申请一实施例中业务流处理方法的一流程图；
图7是本申请一实施例中业务流处理方法的一流程图；
图8是本申请一实施例中业务流处理方法的一流程图；
图9是本申请一实施例中业务流处理装置的一示意图；
图10是本申请一实施例中计算机设备的一示意图。
 本发明的实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
该业务流处理方法可应用在如图1的应用环境中，其中，计算机设备通过网络与服务器进行通信。计算机设备可以但不限于各种个人计算机、笔记本电脑、智能手机、平板电脑和便携式可穿戴设备。服务器可以用独立的服务器来实现。
在一实施例中，如图2所示，提供一种业务流处理方法，以该方法应用在图1中的服务器为例进行说明，包括如下步骤：
S201：获取用户根据预设的客群类别划分条件选择的客群类别。
其中，本方法可应用在一种智能授信系统，用于在用户信息空白或断层的情况下，通过执行业务流中的流程节点，以同步采集用户的个人信息，并根据采集到的个人信息，动态确定符合用户的授信流程，以保证授信流程的顺利执行并实现定价差异化。此外在用户自行选取的客群类别不准确的情况下，可通过动态根据采集到的个人信息进行判断，以最终确定符合用户的授信流程，实现风控以及防欺诈的目的。
其中，由于东南亚市场的地域特点，当地民众的信息采集受到安全性和地域性的影响，导致用户信息的空白与信息断层，故授信流程的初期可先通过用户根据系统预设的客群类别划分条件（如用户是否有办理信用卡），自行选择其所对应的客群类别。本实施例中，该客群类别可根据实际需要设置多个，例如好、一般、差等。
可以理解地，不同的客群类别对应不同的客户评分，该客户评分可通过多个判断条件的分值组合得到，例如判断条件A，当判断为是时，其对应的分值为a,否为b，判断条件B，当判断为是时，其对应的分值为c,否为d；用户根据自身实际情况将每一个判断分支对应的分支累加，得到最终分值（客户评分），以便根据该客户评分，选择其所属的客群类别。
S202：调用工作流引擎执行客群类别对应的第一业务流，以同步采集用户的个人信息；其中，第一业务流包括第一差异节点。
其中，不同的客群类别设置有不同的业务流，该业务流可指授信流程或其他业务流程，此处不做限定。第一业务流指当前客群类别对应的业务流。具体地，当用户根据预设的客群类别划分条件选择的客群类别后，服务器会调用工作流程引擎执行客群类别对应的第一业务流，并同步采集用户的个人信息，以便后续根据用户的个人信息的更新，动态分析确定符合用户的授信流程。其中，用户的个人信息包括但不限于用户的基础信息以及资质信息，该基础信息可指用户的姓名、年龄、性别等基础信息。资质信息可指用户的信用信息，例如是否逾期还款、征信信息、借贷信息等。
需要强调的是，为进一步保证上述用户的个人信息的私密和安全性，上述用户的个人信息还可以存储于一区块链的节点中。
具体地，第一业务流包括第一差异节点，该第一差异节点指该第一业务流与其他客群类别对应的业务流程之间的个性化流程节点，例如征信查询节点、内外部黑名单节点。可以理解地是，不同的业务流均包括一基准流，该基准流包括多个按顺序执行的基准节点，例如信息核实、基本信息采集、客群资质收集、分客群初始授信、资产分类增信、联系人信息录入、放款银行卡绑定、提交审批（STP/人工审批）、回退补件。该第一差异节点可设置在两个相邻的基准节点之间。
S203：当执行到第一业务流中的第一差异节点时，根据当前采集到的个人信息进行类别分析，确定用户的客群类别是否变化。
其中，客群类别的变化结果包括变化或不变，当客群类别发生变化时，可包括客户类别等级提升或下降，此处不做限定。具体地，工作流引擎按顺序执行第一业务流中的每一流程节点，当执行到第一业务流中的第一差异节点时，则触发一客群类别分析程序，即根据当前采集到的个人信息进行分析，确定用户的客群类别是否变化，当发生变化 ，则获取变化后的目标客群类别对应的第二业务流，并控制工作流引擎的执行第二业务流。
具体地，根据当前采集到的个人信息，按照该第一差异节点对应的预设决策条件（例如用户信用评分是否满足条件、拒绝率是否大于阈值），对当前的个人信息进行类别分析，动态确定当前用户的目标客群类别，从而确定该用户的客群类别是否发生变化，以通过先采集客户选择的客群类别，并根据该用户的个人信息动态确定目标客群类别，以使工作流引擎执行目标客群类别对应的第二业务流。
S204：当客群类别变化时，获取变化后的目标客群类别对应的第二业务流，并控制工作流引擎的执行第二业务流。
其中，第二业务流指客群类别发生变化时的下一时刻需要执行的业务流。具体地，当客群类别变化时，获取变化后的目标客群类别对应的第二业务流，并控制工作流引擎执行第二业务流，以通过对不同的客群类别设置对应的业务流，以在用户客群类别变化时，执行对应的业务流。
进一步地，本实施例中对于第二业务流的获取方式包括但不限于三种：一种是每一客群类别对应一独立的业务流，在客群类别发生变化时，可直接读取预先存储的第二业务流，并传递给工作流引擎，使工作流引擎执行该第二业务流；一种是不同客群类别对应的业务流之间共用基准节点，并单独维护每一业务流对应的差异节点，当需要将当前工作流流转至下一业务流时，通过将差异节点动态组装至当前所需执行的工作流中，并将原始业务流的差异节点置为跳过状态，即可获取下一业务流即第二业务流。另一种是预先将基准节点与各业务流对应的差异节点组装，并在确定所需执行的业务流时，通过动态调整各差异节点的状态，即可获取对应的第二业务流。
可以理解地是，该在步骤S204之后，还可重复执行步骤S203至S204，直至进入流程截止点，以完成授信流程。
本实施例中，通过预先获取用户根据预设的客群类别划分条件选择的客群类别，并通过首先执行客群类别对应第一业务流中的流程节点，当执行到第一业务流中的第一差异节点时，以根据采集到的个人信息，进行类别分析，确定用户的客群类别是否变化，当客群类别变化时，获取变化后的目标客群类别对应的第二业务流，并控制工作流引擎的执行第二业务流，从而实现动态确定符合用户的授信流程，以在用户信息空白或断层的情况下，保证授信流程的顺利执行并实现定价差异化。此外在用户自行选取的客群类别不准确的情况下，可通过动态根据采集到的个人信息进行判断，以最终确定符合用户的授信流程，实现风控以及防欺诈的目的。
在一实施例中，如图3所示，第一业务流和第二业务流均包括多个按顺序执行的基准节点；第一差异节点设置在第一业务流中两个相邻的基准节点之间；该方法还包括如下步骤：
S301：当变化结果为客群类别变化时，从数据库中获取目标客群类别对应的第二业务流。
S302：将第一差异节点在第一业务流中的下一相邻的基准节点作为目标执行节点；目标执行节点用于指示第二业务流中的起始执行节点。
S303：将目标执行节点传递给工作流引擎，使工作流引擎的当前执行节点流转至第二业务流中，并控制工作流引擎从起始执行节点开始执行第二业务流。
其中，该客群类别检测程序与第一差异节点绑定，由于第一差异节点可设置在两个相邻的基准节点之间，故工作流引擎的执行流程流转时，可直接将与该第一差异节点相邻的下一基准节点作为下一业务流程的起始执行节点，实现流程的可持续执行，且在业务流变化时，可实现用户无感知的目的。
示例性地，当第一业务流包括按顺序执行的流程节点，即A（基准节点）-B（基准节点）-C（第一差异节点）-D（基准节点）；第二业务流也包括按顺序执行的流程节点A（基准节点）-B（基准节点）-C’（第二差异节点）-D（基准节点），当工作流引擎执行到第一差异节点时，若用户类别发生变化，此时可将第一业务流中与该第一差异节点相邻的下一基准节点即D作为目标执行节点，使工作流引擎的当前执行节点流转至第二业务流中与目标执行节点对应的基准节点即D，并控制工作流引擎从目标执行节点对应的基准节点开始执行第二业务流。
在一实施例中，如图4所示，第一业务流包括多个按顺序执行的基准节点；步骤S204中，即当客群类别变化时，获取变化后的目标客群类别对应的第二业务流，并控制工作流引擎的执行第二业务流，具体包括如下步骤：
S401：当客群类别变化时，将第一差异节点对应的节点状态置为跳过状态。
S402：获取目标客群类别对应的第二差异节点以及第二差异节点对应的节点上下级。
S403：根据节点上下级，组装基准节点与第二差异节点，以在第一业务流程的基础上重构第一业务流，获取第二业务流。
其中，第二差异节点指变化后的目标客群类别对应业务流的个性化流程节点。不同客群类别对应的业务流之间可共用基准节点，并单独维护每一业务流对应的差异节点，当需要将当前工作流的执行进程流转至下一业务流时，通过将差异节点动态组装至当前执行的业务流中，并将当前业务流的差异节点置为跳过状态，即可获取下一业务流即第二业务流。可以理解地，该跳过状态用于指示当前节点可在当前执行的业务流中跳过，无需执行。于本实施方式中默认将组装至当前执行的业务流中的所有流程节点的节点状态为活动状态，即需要执行的状态，不可跳过。
具体地，当客群类别发生变化时，则将第一业务流对应的第一差异节点对应的节点状态置为跳过状态；获取目标客群类别对应的第二差异节点以及第二差异节点的节点上下级，即该第二差异节点的上级流入节点和下级流出节点，以便根据节点上下级将第二差异节点组装至第一业务流中，以获取第二业务流，以实现基准节点的共用，无需单独创建一业务流，节省资源。
在组装第二差异节点时，还可判断该第二差异节点的上级流入节点是否为第一差异节点在第一业务流中的下一相邻的基准节点或下一相邻的基准节点之后的流程节点，若是，则将其组装至第一业务流中，若不是，则由于后续执行第二业务流时，无需执行第一差异节点之前的基准节点，则为了提高系统性能，保证组装有效性，可对第二差异节点进行判断，在符合条件时，则组装，反之则无需组装。
在一实施例中，如图5所示，第一业务流还包括目标客群类别对应的第二差异节点以及多个按顺序执行的基准节点；第二差异节点设置在两个相邻的基准节点之间；第一差异节点设置在两个相邻的基准节点之间；步骤S204中，即当客群类别变化时，获取变化后的目标客群类别对应的第二业务流，具体包括如下步骤：
S501：当变化结果为客群类别变化时，将第一业务流对应的第一差异节点对应的节点状态置为跳过状态。
S502：将第二差异节点的节点状态置为活动状态，以获取第二业务流。
具体地，通过预先将基准节点与各业务流对应的差异节点组装，并在确定所需执行的业务流即第二业务流时，通过动态调整各差异节点的状态，以获取对应的而第二业务流。
其中，第一业务流包括目标客群类别对应的第二差异节点以及多个按顺序执行的基准节点；第二差异节点设置在两个相邻的基准节点之间；第一差异节点设置在两个相邻的基准节点之间；该第一差异节点和第二差异节点可设置在相同或不同的位置，当设置在相同位置时，由于工作流引擎执行的唯一性，即根据当前执行的业务流的不同，执行对应的差异节点，因此不会对工作流的正常执行造成影响。
具体地，通过将不同客群类别对应的业务流预先组装成一完整的工作流，以便在后续流程变动时，通过动态调整节点状态，无需单独维护基准节点和差异节点。
在一实施例中，如图6所示，步骤S201之前，该方法还包括如下步骤：
S601：获取业务流配置请求；其中，业务流配置请求包括待配置的客群类别。
S602：显示客群类别对应的业务流配置表；其中，业务流配置表包括可配置的流程节点以及节点流向。
S603：根据业务流配置表，接收用户配置的目标配置参数；其中，目标配置参数包括目标节点以及每一目标节点对应的目标节点流向。
S604：根据目标节点以及每一目标节点对应的目标节点流向，组装客群类别对应的业务流。
其中，在获取用户根据预设的客群类别划分条件选择的初始客群类别之前，还可实现对每一客群类别对应的业务流进行可视化配置。具体地，通过将不同流程节点作为一独立的流程节点组件，以供用户选择配置，针对不同的业务流无需重新开发一套独立的系统，可实现在同一系统下的多个业务流交叉执行的目的，降低开发成本。
具体地，用户可通过前端触发业务流配置请求，以使服务器响应该业务流配置请求，显示客群类别对应的业务流配置表，该业务流配置表包括可配置的流程节点以及流程节点的节点流向，该节点流向包括流程节点的上级流入节点以及下级流出节点。其中，可配置的流程节点包括但不限于信息核实、基本信息采集、客群资质收集、分客群初始授信、资产分类增信、联系人信息录入、放款银行卡绑定、提交审批（STP/人工审批）、回退补件、内外部黑名单节点、准入风控节点、征信查询节点、客群评分节点等。可以理解地是，对于每一流程节点还可对节点的具体内容进行配置，例如征信查询节点对应的征信基础信息字段以及预设征信阈值，通过对该节点设置对应的决策规则或判断条件，以边后需执行业务流时确定用户的客群类别是否发生变化。
具体地，通过对不同客群类别对应的业务流进行可视化配置，以根据目标流程节点以及每一目标流程节点对应的目标节点流向组装客群类别对应的业务流程。
更进一步地，本实施例中还可针对业务产品的属性进行配置，不同的产品可根据实际情况设置不同的客群类别判断条件，此处不做限定。其中，产品属性包括但不限于核算条款、销售条款、利率设置、交易设置、费用设置以及还款顺序，针对不同的产品属性还进一步配置，例如核算条款还可针对产品核算、产品交易核算以及产品交易分配等进行配置。
在一实施例中，如图7所示，步骤S202之后，该方法还包括如下步骤：
S701：对个人信息进行格式转换，生成消息数据并推送至消息队列。
其中，本方法可通过对接多渠道，以采集用户的基础信息、征信信息、借贷信息等个人信息。具体地，在采集到用户的个人信息后，可对该个人信息进行格式转换，生成消息数据并推送至消息队列（即消息中间件，如kafka）。
其中，可预先设定一入库程序，用于统一数据格式，例如json格式。本实施例中，可通过生产-消费的架构实现用户的个人信息的存储，即通过生产者生产数据推送至消息队列，以使消费端消费该消息队列中的数据，可实现多线程并发。
S702：对消息队列中的数据进行数据清洗，得到清洗后的消息数据。
具体地，该数据清洗可借助SparkStreaming 程序实现对消息数据进行ETL清洗处理，将分散、零乱、标准不统一的数据整合到一起，方便后续入库存储。
其中，ETL是将业务系统的数据经过抽取、清洗转换之后加载到数据仓库的过程。ETL的清晰过程包括数据抽取、数据的清洗转换以及数据的加载。
S703：对消息队列内中清洗后的消息数据进行出列操作，将消息数据存储到数据库中。
本实施例中，可通过队列轮询方式对消息队列内中清洗后的消息数据进行出列操作，以将消息数据存储到数据库中。
在一实施例中，如图8所示，步骤S202之后，该方法还包括如下步骤：
S801：当客群类别变化时，根据目标客群类别，确定用户的多个风控规则条目。
S802：基于多个风控规则条目，构建用户的目标风控模型，并与用户关联存储。
具体地，不同的客群类别对应不同的风控规则条目，当该用户的客群类别发生变化时，可根据目标客群类别，确定用户的多个风控规则条目，并基于多个风控规则条目，构建用户的目标风控模型，并与用户关联存储，以便对该用户再次执行授信流程时，可直接调用该目标风控模型进行风险评估，无需执行全部预设的风控规则条目。
应理解，上述实施例中各步骤的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本申请实施例的实施过程构成任何限定。
在一实施例中，提供一种业务流处理装置，该业务流处理装置与上述实施例中业务流处理方法一一对应。如图8所示，该业务流处理装置包括初始客群类别获取模块10、个人信息采集模块20、客群类别检测模块30和第二业务流获取和执行模块40。各功能模块详细说明如下：
初始客群类别获取模块10，用于获取用户根据预设的客群类别划分条件选择的客群类别。
个人信息采集模块20，用于调用工作流引擎执行客群类别对应的第一业务流，以同步采集用户的个人信息；其中，第一业务流包括第一差异节点。
客群类别检测模块30，用于当执行到第一业务流中的第一差异节点时，根据当前采集到的个人信息进行类别分析，确定用户的客群类别是否变化。
第二业务流获取和执行模块40，用于当客群类别变化时，获取变化后的目标客群类别对应的第二业务流，并控制工作流引擎的执行第二业务流。
具体地，第一业务流和第二业务流均包括多个按顺序执行的基准节点；第一差异节点设置在第一业务流中两个相邻的基准节点之间；
该业务流处理装置还包括第二业务流获取模块、目标执行节点获取模块和第二业务流执行模块。
第二业务流获取模块，用于当变化结果为客群类别变化时，从数据库中获取目标客群类别对应的第二业务流。
目标执行节点获取模块，用于将第一差异节点在第一业务流中的下一相邻的基准节点作为目标执行节点；目标执行节点用于指示第二业务流中的起始执行节点。
第二业务流执行模块，用于将目标执行节点传递给工作流引擎，使工作流引擎的当前执行节点流转至第二业务流中，并控制工作流引擎从起始执行节点开始执行第二业务流。
具体地，第一业务流包括多个按顺序执行的基准节点；该该业务流处理装置还包括节点状态调整模块、第二差异节点获取模块以及第一业务流重构模块。
节点状态调整模块，用于当客群类别变化时，将第一差异节点对应的节点状态置为跳过状态。
第二差异节点获取模块，用于获取目标客群类别对应的第二差异节点以及第二差异节点对应的节点上下级。
第一业务流重构模块，用于根据节点上下级，组装基准节点与第二差异节点，以在第一业务流程的基础上重构第一业务流，获取第二业务流。
具体地，第一业务流还包括目标客群类别对应的第二差异节点以及多个按顺序执行的基准节点；第二差异节点设置在两个相邻的基准节点之间；第一差异节点设置在两个相邻的基准节点之间。
该业务流处理装置还包括节点状态调整模块和第二业务流获取模块。
节点状态调整模块，用于当变化结果为客群类别变化时，将第一业务流对应的第一差异节点对应的节点状态置为跳过状态；
第二业务流获取模块，用于将第二差异节点的节点状态置为活动状态，以获取第二业务流。
具体地，该业务流处理装置还包括业务流配置请求获取模块、业务流配置表显示模块、目标配置参数接收模块以及第二业务流组装模块。
业务流配置请求获取模块，用于获取业务流配置请求；其中，业务流配置请求包括待配置的客群类别。
业务流配置表显示模块，用于显示客群类别对应的业务流配置表；其中，业务流配置表包括可配置的流程节点以及节点流向。
目标配置参数接收模块，用于根据业务流配置表，接收用户配置的目标配置参数；其中，目标配置参数包括目标节点以及每一目标节点对应的目标节点流向。
第二业务流组装模块，用于根据目标节点以及每一目标节点对应的目标节点流向，组装客群类别对应的业务流。
具体地，该业务流处理装置还包括格式转换模块、数据清洗模块以及存储模块。
格式转换模块，用于对个人信息进行格式转换，生成消息数据并推送至消息队列。
数据清洗模块，用于对消息队列中的数据进行数据清洗，得到清洗后的消息数据。
存储模块，用于对消息队列中的清洗后的消息数据进行出列操作，将消息数据存储到数据库中。
具体地，该业务流处理装置还包括风控规则条目确定模块和模型构建模块。
风控规则条目确定模块，用于当客群类别变化时，根据目标客群类别，确定用户的多个风控规则条目。
模型构建模块，用于基于多个风控规则条目，构建用户的目标风控模型，并与用户关联存储。
关于业务流处理装置的具体限定可以参见上文中对于业务流处理方法的限定，在此不再赘述。上述业务流处理装置中的各个模块可全部或部分通过软件、硬件及其组合来实现。上述各模块可以硬件形式内嵌于或独立于计算机设备中的处理器中，也可以以软件形式存储于计算机设备中的存储器中，以便于处理器调用执行以上各个模块对应的操作。
在一个实施例中，提供了一种计算机设备，该计算机设备可以是服务器，其内部结构图可以如图10所示。该计算机设备包括通过系统总线连接的处理器、存储器、网络接口和数据库。其中，该计算机设备的处理器用于提供计算和控制能力。该计算机设备的存储器包括计算机存储介质、内存储器。该计算机存储介质存储有操作系统、计算机程序和数据库。该内存储器为计算机存储介质中的操作系统和计算机程序的运行提供环境。该计算机设备的数据库用于存储执行业务流处理方法过程中生成或获取的数据，如用户的个人信息。该计算机设备的网络接口用于与外部的终端通过网络连接通信。该计算机程序被处理器执行时以实现一种业务流处理方法。
在一个实施例中，提供了一种计算机设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，处理器执行计算机程序时实现上述实施例中的业务流处理方法的步骤，例如图2所示的步骤S201-S204，或者图3至图8中所示的步骤。或者，处理器执行计算机程序时实现业务流处理装置这一实施例中的各模块/单元的功能，例如图9所示的各模块/单元的功能，为避免重复，这里不再赘述。
在一实施例中，提供一计算机存储介质，该计算机存储介质上存储有计算机程序，该计算机程序被处理器执行时实现上述实施例中业务流处理方法的步骤，例如图2所示的步骤S201-S204，或者图3至图8中所示的步骤，为避免重复，这里不再赘述。或者，该计算机程序被处理器执行时实现上述业务流处理装置这一实施例中的各模块/单元的功能，例如图9所示的各模块/单元的功能，为避免重复，这里不再赘述。所述计算机可读存储介质可以是非易失性，也可以是易失性。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机程序来指令相关的硬件来完成，的计算机程序可存储于一非易失性计算机可读取存储介质中，该计算机程序在执行时，可包括如上述各方法的实施例的流程。其中，本申请所提供的各实施例中所使用的对存储器、存储、数据库或其它介质的任何引用，均可包括非易失性和/或易失性存储器。非易失性存储器可包括只读存储器（ROM）、可编程ROM（PROM）、电可编程ROM（EPROM）、电可擦除可编程ROM（EEPROM）或闪存。易失性存储器可包括随机存取存储器（RAM）或者外部高速缓冲存储器。作为说明而非局限，RAM以多种形式可得，诸如静态RAM（SRAM）、动态RAM（DRAM）、同步DRAM（SDRAM）、双数据率SDRAM（DDRSDRAM）、增强型SDRAM（ESDRAM）、同步链路（Synchlink） DRAM（SLDRAM）、存储器总线（Rambus）直接RAM（RDRAM）、直接存储器总线动态RAM（DRDRAM）、以及存储器总线动态RAM（RDRAM）等。
本申请所指区块链是分布式数据存储、点对点传输、共识机制、加密算法等计算机技术的新型应用模式。区块链(Blockchain)，本质上是一个去中心化的数据库，是一串使用密码学方法相关联产生的数据块，每一个数据块中包含了一批次网络交易的信息，用于验证其信息的有效性(防伪)和生成下一个区块。区块链可以包括区块链底层平台、平台产品服务层以及应用服务层等。
所属领域的技术人员可以清楚地了解到，为了描述的方便和简洁，仅以上述各功能单元、模块的划分进行举例说明，实际应用中，可以根据需要而将上述功能分配由不同的功能单元、模块完成，即将装置的内部结构划分成不同的功能单元或模块，以完成以上描述的全部或者部分功能。
以上实施例仅用以说明本申请的技术方案，而非对其限制，尽管参照前述实施例对本申请进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的精神和范围，均应包含在本申请的保护范围之内。

Claims (20)

1.一种业务流处理方法，其中，包括：
获取用户根据预设的客群类别划分条件选择的客群类别；
调用工作流引擎执行所述客群类别对应的第一业务流，以同步采集所述用户的个人信息；其中，所述第一业务流包括第一差异节点；
当执行到所述第一业务流中的第一差异节点时，根据当前采集到的所述个人信息进行类别分析，确定所述用户的客群类别是否变化；
当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，并控制所述工作流引擎的执行所述第二业务流。
2.如权利要求1所述业务流处理方法，其中，所述第一业务流和所述第二业务流均包括多个按顺序执行的基准节点；第一差异节点设置在所述第一业务流中两个相邻的所述基准节点之间；
所述当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，包括：
当所述变化结果为客群类别变化时，从数据库中获取所述目标客群类别对应的第二业务流；
所述控制所述工作流引擎的执行所述第二业务流，包括：
将所述第一差异节点在所述第一业务流中的下一相邻的基准节点作为目标执行节点；所述目标执行节点用于指示所述第二业务流中的起始执行节点；
将所述目标执行节点传递给所述工作流引擎，使所述工作流引擎的当前执行节点流转至所述第二业务流中，并控制所述工作流引擎从所述起始执行节点开始执行所述第二业务流。
3.如权利要求1所述业务流处理方法，其中，所述第一业务流包括多个按顺序执行的基准节点；
所述当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，包括；
当所述客群类别变化时，将所述第一差异节点对应的节点状态置为跳过状态；
获取所述目标客群类别对应的第二差异节点以及所述第二差异节点对应的节点上下级；
根据所述节点上下级，组装所述基准节点与所述第二差异节点，以在所述第一业务流程的基础上重构所述第一业务流，获取所述第二业务流。
4.如权利要求1所述业务流处理方法，其中，所述第一业务流还包括所述目标客群类别对应的第二差异节点以及多个按顺序执行的基准节点；第二差异节点设置在两个相邻的所述基准节点之间；第一差异节点设置在两个相邻的所述基准节点之间；
所述当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，包括：
当所述变化结果为客群类别变化时，将所述第一业务流对应的第一差异节点对应的节点状态置为跳过状态；
将所述第二差异节点的节点状态置为活动状态，以获取所述第二业务流。
5.如权利要求1所述业务流处理方法，其中，在所述获取用户根据预设的客群类别划分条件选择的初始客群类别之前，所述业务流处理方法还包括：
获取业务流配置请求；其中，所述业务流配置请求包括待配置的客群类别；
显示所述客群类别对应的业务流配置表；其中，所述业务流配置表包括可配置的流程节点以及节点流向；
根据所述业务流配置表，接收用户配置的目标配置参数；其中，所述目标配置参数包括目标节点以及每一所述目标节点对应的目标节点流向；
根据所述目标节点以及每一目标节点对应的目标节点流向，组装所述客群类别对应的业务流。
6.如权利要求1所述业务流处理方法，其中，在所述同步采集所述用户的个人信息之后，所述业务流处理方法还包括：
对所述个人信息进行格式转换，生成消息数据并推送至消息队列；
对所述消息队列中的数据进行数据清洗，得到清洗后的消息数据；
对所述消息队列内中所述清洗后的消息数据进行出列操作，将所述消息数据存储到数据库中。
7.如权利要求1所述业务流处理方法，其中，在所述当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，并控制所述工作流引擎的执行所述第二业务流之后，所述业务流处理方法还包括：
当所述客群类别变化时，根据所述目标客群类别，确定所述用户的多个风控规则条目；
基于所述多个风控规则条目，构建所述用户的目标风控模型，并与所述用户关联存储。
8.一种业务流处理装置，其中，包括：
初始客群类别获取模块，用于获取用户根据预设的客群类别划分条件选择的客群类别；
个人信息采集模块，用于调用工作流引擎执行所述客群类别对应的第一业务流，以同步采集所述用户的个人信息；其中，所述第一业务流包括第一差异节点；
客群类别检测模块，用于当执行到所述第一业务流中的第一差异节点时，根据当前采集到的所述个人信息进行类别分析，确定所述用户的客群类别是否变化；
第二业务流获取和执行模块，用于当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，并控制所述工作流引擎的执行所述第二业务流。
9.一种计算机设备，包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，其中，所述处理器执行所述计算机程序时实现如下步骤：
获取用户根据预设的客群类别划分条件选择的客群类别；
调用工作流引擎执行所述客群类别对应的第一业务流，以同步采集所述用户的个人信息；其中，所述第一业务流包括第一差异节点；
当执行到所述第一业务流中的第一差异节点时，根据当前采集到的所述个人信息进行类别分析，确定所述用户的客群类别是否变化；
当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，并控制所述工作流引擎的执行所述第二业务流。
10.如权利要求9所述的计算机设备，其中，所述第一业务流和所述第二业务流均包括多个按顺序执行的基准节点；第一差异节点设置在所述第一业务流中两个相邻的所述基准节点之间；
所述当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，包括：
当所述变化结果为客群类别变化时，从数据库中获取所述目标客群类别对应的第二业务流；
所述控制所述工作流引擎的执行所述第二业务流，包括：
将所述第一差异节点在所述第一业务流中的下一相邻的基准节点作为目标执行节点；所述目标执行节点用于指示所述第二业务流中的起始执行节点；
将所述目标执行节点传递给所述工作流引擎，使所述工作流引擎的当前执行节点流转至所述第二业务流中，并控制所述工作流引擎从所述起始执行节点开始执行所述第二业务流。
11.如权利要求9所述的计算机设备，其中，所述第一业务流包括多个按顺序执行的基准节点；
所述当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，包括；
当所述客群类别变化时，将所述第一差异节点对应的节点状态置为跳过状态；
获取所述目标客群类别对应的第二差异节点以及所述第二差异节点对应的节点上下级；
根据所述节点上下级，组装所述基准节点与所述第二差异节点，以在所述第一业务流程的基础上重构所述第一业务流，获取所述第二业务流。
12.如权利要求9所述的计算机设备，其中，所述第一业务流还包括所述目标客群类别对应的第二差异节点以及多个按顺序执行的基准节点；第二差异节点设置在两个相邻的所述基准节点之间；第一差异节点设置在两个相邻的所述基准节点之间；
所述当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，包括：
当所述变化结果为客群类别变化时，将所述第一业务流对应的第一差异节点对应的节点状态置为跳过状态；
将所述第二差异节点的节点状态置为活动状态，以获取所述第二业务流。
13.如权利要求9所述的计算机设备，其中，在所述获取用户根据预设的客群类别划分条件选择的初始客群类别之前，所述业务流处理方法还包括：
获取业务流配置请求；其中，所述业务流配置请求包括待配置的客群类别；
显示所述客群类别对应的业务流配置表；其中，所述业务流配置表包括可配置的流程节点以及节点流向；
根据所述业务流配置表，接收用户配置的目标配置参数；其中，所述目标配置参数包括目标节点以及每一所述目标节点对应的目标节点流向；
根据所述目标节点以及每一目标节点对应的目标节点流向，组装所述客群类别对应的业务流。
14.如权利要求9所述的计算机设备，其中，在所述当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，并控制所述工作流引擎的执行所述第二业务流之后，所述业务流处理方法还包括：
当所述客群类别变化时，根据所述目标客群类别，确定所述用户的多个风控规则条目；
基于所述多个风控规则条目，构建所述用户的目标风控模型，并与所述用户关联存储。
15．一种计算机存储介质，所述计算机存储介质存储有计算机程序，其中，所述计算机程序被处理器执行时实现如下步骤：
获取用户根据预设的客群类别划分条件选择的客群类别；
调用工作流引擎执行所述客群类别对应的第一业务流，以同步采集所述用户的个人信息；其中，所述第一业务流包括第一差异节点；
当执行到所述第一业务流中的第一差异节点时，根据当前采集到的所述个人信息进行类别分析，确定所述用户的客群类别是否变化；
当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，并控制所述工作流引擎的执行所述第二业务流。
16.如权利要求15所述的计算机存储介质，其中，所述第一业务流和所述第二业务流均包括多个按顺序执行的基准节点；第一差异节点设置在所述第一业务流中两个相邻的所述基准节点之间；
所述当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，包括：
当所述变化结果为客群类别变化时，从数据库中获取所述目标客群类别对应的第二业务流；
所述控制所述工作流引擎的执行所述第二业务流，包括：
将所述第一差异节点在所述第一业务流中的下一相邻的基准节点作为目标执行节点；所述目标执行节点用于指示所述第二业务流中的起始执行节点；
将所述目标执行节点传递给所述工作流引擎，使所述工作流引擎的当前执行节点流转至所述第二业务流中，并控制所述工作流引擎从所述起始执行节点开始执行所述第二业务流。
17.如权利要求15所述的计算机存储介质，其中，所述第一业务流包括多个按顺序执行的基准节点；
所述当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，包括；
当所述客群类别变化时，将所述第一差异节点对应的节点状态置为跳过状态；
获取所述目标客群类别对应的第二差异节点以及所述第二差异节点对应的节点上下级；
根据所述节点上下级，组装所述基准节点与所述第二差异节点，以在所述第一业务流程的基础上重构所述第一业务流，获取所述第二业务流。
18.如权利要求15所述的计算机存储介质，其中，所述第一业务流还包括所述目标客群类别对应的第二差异节点以及多个按顺序执行的基准节点；第二差异节点设置在两个相邻的所述基准节点之间；第一差异节点设置在两个相邻的所述基准节点之间；
所述当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，包括：
当所述变化结果为客群类别变化时，将所述第一业务流对应的第一差异节点对应的节点状态置为跳过状态；
将所述第二差异节点的节点状态置为活动状态，以获取所述第二业务流。
19.如权利要求15所述的计算机存储介质，其中，在所述获取用户根据预设的客群类别划分条件选择的初始客群类别之前，所述业务流处理方法还包括：
获取业务流配置请求；其中，所述业务流配置请求包括待配置的客群类别；
显示所述客群类别对应的业务流配置表；其中，所述业务流配置表包括可配置的流程节点以及节点流向；
根据所述业务流配置表，接收用户配置的目标配置参数；其中，所述目标配置参数包括目标节点以及每一所述目标节点对应的目标节点流向；
根据所述目标节点以及每一目标节点对应的目标节点流向，组装所述客群类别对应的业务流。
20.如权利要求15所述的计算机存储介质，其中，在所述当所述客群类别变化时，获取变化后的目标客群类别对应的第二业务流，并控制所述工作流引擎的执行所述第二业务流之后，所述业务流处理方法还包括：
当所述客群类别变化时，根据所述目标客群类别，确定所述用户的多个风控规则条目；
基于所述多个风控规则条目，构建所述用户的目标风控模型，并与所述用户关联存储。
 
PCT/CN2021/091691 2020-12-24 2021-04-30 业务流处理方法、装置、计算机设备及存储介质 WO2022134424A1 (zh)

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