A dynamic insurance application process management method, device and equipment and storage medium

Abstract

The application belongs to the technical field of artificial intelligence, and is suitable for the insurance field, and discloses a dynamic insurance process management method, which comprises the following steps: acquiring an actual insurance process, and establishing an insurance process model; constructing a parameterized process template through a visual arrangement platform, defining process execution logic, and generating or adjusting the execution logic and sequence of each business node in the insurance process model; in the running process of the insurance process model, log data generated by the insurance process model is collected, and the log data is processed and cleaned based on stream computing; a log analysis engine is constructed, the processed log data is input into the log analysis engine for analysis, and process optimization suggestions are generated; the analysis results and optimization suggestions generated by the log analysis engine are fed back to the visual arrangement platform, and the process arrangement strategy is adjusted. The application solves the technical problems of difficult fault positioning and lack of intelligent disaster recovery and elastic recovery mechanism caused by high system coupling degree in the existing insurance business system.

Description

Technical Field

[0001] This invention belongs to the field of artificial intelligence technology and is applicable to the insurance field, particularly relating to a dynamic insurance application process management method, device, equipment, and storage medium. Background Technology

[0002] Modern insurance application processes rely heavily on chained calls between multiple independent systems, such as risk control platforms, product factories, and customer information systems, forming a complex distributed interactive network. When anomalies occur in cross-system interactions, the lack of end-to-end visual monitoring and accurate log tracking mechanisms makes it difficult to pinpoint the root cause within minutes, hindering operational response efficiency and business continuity assurance. Existing architectures generally lack intelligent circuit breaking, service degradation, and adaptive traffic scheduling capabilities, failing to automatically trigger backup plans or compensation logic when core services are unavailable. Therefore, there is an urgent need for an insurance application process management method that enables visualized process monitoring, intelligent anomaly recovery, and dynamic business orchestration to improve the agility and operational efficiency of insurance operations. Summary of the Invention

[0003] This invention provides a dynamic insurance application process management method, device, equipment, and storage medium, which solves the technical problems of difficult fault location and lack of intelligent disaster recovery and elastic recovery mechanisms caused by high system coupling in existing insurance business systems.

[0004] In a first aspect, the present invention provides a dynamic insurance application process management method, comprising: Obtain the actual insurance application process that includes multiple business nodes, and establish an insurance application process model based on the actual insurance application process; Based on the aforementioned insurance application process model, a parameterized process template is constructed through a visual orchestration platform, defining process execution logic that includes conditional branches and parallel execution. Based on the parameterized process template, the execution logic and order of each business node in the insurance application process model are generated or adjusted. During the operation of the insurance application process model, log data generated by the insurance application process model is collected, and the log data is processed and cleaned based on streaming computing. The log analysis engine, built on elastic search technology, takes processed log data into the engine for analysis, identifies process bottlenecks and abnormal patterns, and generates analysis results and process optimization suggestions. The analysis results and optimization suggestions generated by the log analysis engine are fed back to the visualization orchestration platform to adjust the process orchestration strategy.

[0005] Secondly, the present invention provides a dynamic insurance application process management device, comprising: The process modeling module is used to obtain the actual insurance application process that includes multiple business nodes, and to build an insurance application process model based on the actual insurance application process. The orchestration engine module is used to construct a parameterized process template through a visual orchestration platform based on the insurance process model, define the process execution logic including conditional branches and parallel execution, and generate or adjust the execution logic and order of each business node in the insurance process model based on the parameterized process template. The log collection and processing module is used to collect log data generated by the insurance process model during its operation, and to process and clean the log data based on streaming computing. The intelligent analysis module is used to build a log analysis engine based on elastic search technology. It inputs the processed log data into the log analysis engine for analysis, identifies process bottlenecks and abnormal patterns, and generates analysis results and process optimization suggestions. The feedback execution module is used to feed back the analysis results and optimization suggestions generated by the log analysis engine to the visualization orchestration platform to adjust the process orchestration strategy.

[0006] Thirdly, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the dynamic insurance application process management method.

[0007] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the dynamic insurance application process management method.

[0008] The aforementioned dynamic insurance application process management method, device, equipment, and storage medium, in their implemented solution, construct the insurance application process into a computable and traceable parameterized process template through a visual orchestration platform, and dynamically adjust the execution logic and sequence of each business node according to the process configuration strategy. Real-time processing and cleaning of log data generated during the operation of the insurance application process model are performed using streaming computing, and the data is input into a log analysis engine built based on elastic search for process bottleneck and anomaly pattern identification. Optimization suggestions are generated and fed back to the orchestration platform to form a closed-loop control. In this invention, the combination of visual orchestration and dynamic parameterized templates supports the rapid construction of complex branch processes and agile adaptation to regional businesses. Streaming computing and the log analysis engine enable minute-level location and intelligent diagnosis of operational anomalies. Through the closed-loop feedback of analysis results and orchestration strategies, continuous self-optimization and elastic recovery of the process can be achieved, significantly reducing system fault diagnosis time and manual maintenance costs, and improving the resilience, observability, and business response efficiency of the insurance application process. Attached Figure Description

[0009] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 This is a schematic diagram of an application environment for a dynamic insurance application process management method according to an embodiment of the present invention.

[0011] Figure 2 This is a flowchart illustrating a dynamic insurance application process management method according to an embodiment of the present invention.

[0012] Figure 3 yes Figure 2 A schematic diagram of a specific implementation method for step S20.

[0013] Figure 4 yes Figure 2 A flowchart illustrating a specific implementation of step S40.

[0014] Figure 5 This is a schematic diagram of a dynamic insurance application process management device in one embodiment of the present invention.

[0015] Figure 6 This is a schematic diagram of the structure of a computer device according to an embodiment of the present invention.

[0016] Figure 7 This is another structural schematic diagram of a computer device according to one embodiment of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] The dynamic insurance application process management method provided in this invention can be applied to, for example... Figure 1 In the application environment, Figure 1This is a schematic diagram of an application environment for a dynamic insurance application process management method according to an embodiment of the present invention; wherein, the client communicates with the server via a network. The server can construct the insurance application process into a computable and traceable parameterized process template through a visual orchestration platform, and dynamically adjust the execution logic and sequence of each business node according to the process configuration strategy; by performing real-time processing and cleaning of the log data generated during the operation of the insurance application process model based on streaming computing, and inputting it into a log analysis engine built based on elastic search for process bottleneck and abnormal pattern identification, generating optimization suggestions and feeding them back to the orchestration platform to form a closed-loop control. In this invention, by combining visual orchestration with dynamic parameterized templates, it can support the rapid construction of complex branch processes and agile adaptation to regional businesses. Through streaming computing and log analysis engine, it can achieve minute-level location and intelligent diagnosis of operational anomalies. Through the closed-loop feedback of analysis results and orchestration strategies, it can achieve continuous self-optimization and elastic recovery of the process, significantly reducing system fault troubleshooting time and manual maintenance costs, and improving the resilience, observability and business response efficiency of the insurance application process. The present invention will be described in detail below through specific embodiments.

[0019] Please see Figure 2 As shown, Figure 2 This is a flowchart illustrating a dynamic insurance application process management method provided in an embodiment of the present invention. The dynamic insurance application process management method specifically includes the following steps: S10 acquires the actual insurance application process, which includes multiple business nodes, and establishes an insurance application process model based on the actual process. Optionally, the actual insurance application process includes steps such as application form recording, premium calculation, disclosure, and underwriting submission as defined in industry standards. By analyzing the business logic relationships and data dependencies between these steps, a digital process representation is generated. The insurance application process model can be described using computable structures such as directed graphs and state machines. The model records metadata such as the business meaning of each node, input and output parameters, and flow conditions between nodes. By abstracting the actual business process into a structured, computable digital model, a unified data foundation is provided for subsequent dynamic orchestration and operation monitoring.

[0020] In the field of auto insurance, by acquiring multi-dimensional information such as basic vehicle information, historical accident records, driving behavior data, and regional risk characteristics, and by analyzing historical data such as vehicle usage frequency, accident rate, and maintenance costs, insurance companies can build accurate auto insurance risk pricing models and provide differentiated premium plans and personalized safety service suggestions based on driving habits, thereby optimizing risk control accuracy and enhancing customer loyalty and market competitiveness.

[0021] Based on the insurance application process model, S20 constructs a parameterized process template through a visual orchestration platform, defines the process execution logic including conditional branches and parallel execution, and generates or adjusts the execution logic and order of each business node in the insurance application process model based on the parameterized process template.

[0022] Specifically, such as Figure 3 The above, Figure 3 This is a flowchart illustrating a specific implementation of step S20, which specifically includes the following steps S21-S23: S21 configures the insurance application process model through a visual process orchestration platform, constructs a parameterized process template based on the insurance application process model and corresponding business parameters, and defines the process execution logic of the parameterized process template. Optionally, the visual process orchestration platform provides a drag-and-drop interface, allowing developers to arrange and connect various business nodes in the insurance application process model established in S10, such as premium calculation and underwriting rule verification, in the form of graphical components. The platform supports parameterized configuration of the process template based on business parameters in the policy model, such as policy number, insured age, and vehicle type, so that the same process template can be adapted to different business scenarios by adjusting parameters.

[0023] S22 configures conditional branching rules for controlling the execution path of the business nodes and parallel execution rules for controlling the concurrent execution of multiple business nodes in the process execution logic; optionally, the conditional branching rules can be defined based on policy business parameters or process runtime status, such as determining whether to trigger specific underwriting rules or rate adjustment processes based on conditions such as the insured's age and vehicle usage nature; the parallel execution rules can be used to specify multiple business nodes without dependencies, such as performing concurrent execution of customer credit inquiries and vehicle information verification at the same time, so as to improve the overall process processing efficiency.

[0024] S23 generates or adjusts the execution logic and execution order of each business node in the insurance application process model based on the parameterized process template. Optionally, the process orchestration engine parses the process execution logic defined in S22 and dynamically generates executable process instances based on the specific values ​​of the current business parameters. During this process, the engine determines the execution path of each business node according to conditional branching rules, schedules nodes without dependencies to run concurrently according to parallel execution rules, and determines the execution order of sequential nodes based on the dependencies between nodes. For a running process instance, when an update to the process template is detected or an external intervention instruction is received, the execution logic or order of subsequent nodes is dynamically adjusted without interrupting process execution.

[0025] S30 collects log data generated by the insurance application process model during its operation and processes and cleans the log data based on stream computing. Optionally, after caching and distributing the collected log data via a message queue, stream computing is used to parse, standardize the format, and filter out abnormal data in the log data to generate structured log events; wherein, the structured log events include information about associated process node identifiers and business context.

[0026] During the operation of the insurance application process model, each business node generates operation logs and system logs containing timestamps, node identifiers, execution status, input / output parameters, and exception information. This log data can be collected uniformly and sent to a message middleware for buffering. The streaming computing engine continuously consumes the log data stream from the message middleware and performs real-time parsing, format standardization, invalid field filtering, and deduplication on the raw logs, transforming them into a structured, analyzable event data stream. Through the real-time processing capabilities of streaming computing, data anomalies and formatting issues can be quickly detected, ensuring the timeliness and consistency of the log data.

[0027] In the auto insurance sector, multi-dimensional log data is collected during the insurance application process, including vehicle information verification records, driver behavior analysis data, historical accident reports, and claims processing trajectories. By performing real-time streaming processing and cleaning on this data, a complete vehicle risk profile and claims efficiency assessment model can be constructed. Auto insurance companies can dynamically adjust premium pricing based on real-time processed driving behavior data, optimize underwriting rules by analyzing historical accident patterns, and continuously improve service processes based on claims processing timeliness data, thereby enhancing the accuracy of risk pricing and optimizing the customer claims experience.

[0028] The S40 log analysis engine, built on elastic search technology, takes processed log data into the engine for analysis, identifies process bottlenecks and abnormal patterns, and generates analysis results and process optimization suggestions.

[0029] Optionally, the log analysis engine can index and store the structured log event stream processed by S30 in real time, and support pattern recognition based on business rules or machine learning algorithms. By aggregating and analyzing indicators such as node execution time, anomaly frequency, and resource consumption recorded in the logs, performance bottlenecks in the process can be identified, such as a significantly higher average execution time for a certain underwriting node than the baseline and anomaly patterns, or frequent verification failures under specific parameter combinations. Utilizing the efficient retrieval and aggregation analysis capabilities of elastic search, real-time insight and intelligent diagnosis of massive process operation logs are achieved, transforming the originally passive log viewing into proactive anomaly detection and performance optimization. Through automated bottleneck identification and root cause analysis, the time required for fault diagnosis and performance tuning is significantly reduced.

[0030] In the auto insurance sector, log analysis engines are used to conduct in-depth analysis of processed vehicle driving data, accident reports, damage assessment and repair information, and customer interaction logs. This identifies risk assessment bottlenecks in the underwriting process, abnormal delay patterns in claims processing, and breakpoints in the customer service experience. By analyzing the correlation between historical accident frequency and repair costs, auto insurance companies can optimize vehicle risk rating models; by identifying repeated rejection patterns in the claims document review process, they can improve document submission guidelines and automated verification rules; and by analyzing customer inquiry hotspots and resolution timelines, they can optimize self-service and human agent collaboration strategies to accelerate claims efficiency and improve customer service quality.

[0031] Specifically, such as Figure 4 The above, Figure 4 This is a flowchart illustrating a specific implementation of step S40, which specifically includes the following steps S41-S43: S41 matches and analyzes the processed log data against a pre-set rule base to identify abnormal patterns and obtain analysis results. Optionally, the rule base pre-defines common process abnormal patterns, such as node execution timeout thresholds, frequency of specific error codes, and business parameter compliance verification rules. The log analysis engine matches the processed log events with these rules in real time. When a log feature is detected to meet a certain rule condition, an abnormal alarm is triggered, and analysis results containing information such as rule type, trigger time, and associated nodes are generated. For example, when the underwriting node continuously experiences specific types of system errors, or when the premium calculation node takes longer than a preset threshold, the rule base can automatically identify and mark it as an abnormality.

[0032] S42 constructs a log analysis engine based on elastic search technology. The processed log data is input into the log analysis engine, and business knowledge acquired through enhanced retrieval technology is used for bottleneck analysis and decision deduction to obtain decision deduction results. Optionally, the log analysis engine can be constructed using elastic search as the core storage and retrieval engine. The structured log event stream processed by S30 is continuously written into the time series index established in the elastic search cluster according to preset index mapping rules. At the same time, business knowledge documents such as policy terms, underwriting rules, and historical optimization cases can be extracted from text and structured, and then synchronously stored in the business knowledge index of elastic search. When performing bottleneck analysis and decision deduction, the log analysis engine can utilize the synonym expansion, relevance scoring, multi-condition aggregation, and cross-index joint query provided by elastic search to enhance retrieval capabilities, quickly locate knowledge items highly relevant to the current log context from the business knowledge index, and provide domain background support for in-depth analysis. Based on the retrieved knowledge, the log analysis engine combines multi-dimensional indicators such as time consumption, status, and dependency relationships in the log to perform bottleneck root cause pattern matching and decision path simulation deduction.

[0033] Based on the analysis results and the decision deduction results, S43 generates process optimization suggestions including specific operation instructions. Optionally, the log analysis engine combines the specific abnormal patterns identified in S41, such as node A's average response time exceeding the threshold of 500ms, with the decision paths deduced in S42, such as optimizing node A's database query index or implementing asynchronous transformation of node A, to generate structured process optimization suggestions. These suggestions will include clearly defined operation objects, such as specific process nodes or components, operation actions, such as parameter adjustments, code replacement, rule updates, and expected effect assessments, such as the expected performance improvement and the scope of risk impact, and can be directly converted into system-executable configuration instructions or manual processing work orders.

[0034] S50 feeds back the analysis results and optimization suggestions generated by the log analysis engine to the visualization orchestration platform to adjust the process orchestration strategy. Optionally, the analysis results, decision inference results, and corresponding process optimization suggestions output by the log analysis engine are structured and encapsulated to form a strategy adjustment instruction that can be parsed by the process orchestration engine. The visualization orchestration platform then adjusts at least one of the following based on the strategy adjustment instruction: the node execution order, conditional branch logic, node call parameters, or parallel / serial execution mode of the current insurance application process. Without interrupting the currently executing insurance application process, the adjusted process orchestration strategy is applied to subsequently created process instances. This step achieves an automated closed loop from monitoring and analysis to process optimization, significantly improving the system's adaptability and continuous evolution capabilities. Through structured instruction transmission and automated strategy adjustment, manual decision-making and system execution are efficiently connected, reducing the cycle and operational complexity of process optimization iterations. The strategy update is designed for immediacy and backward compatibility.

[0035] In the auto insurance sector, bottlenecks in the claims process, abnormal patterns in underwriting rules, and customer service experience optimization suggestions identified by log analysis engines are structured and packaged into strategy adjustment instructions, which are then fed back to a visual orchestration platform. Based on this, the platform can dynamically adjust the parallel execution ratio of image upload nodes and manual review nodes in the vehicle damage assessment process, optimize the triggering conditions for additional inspection items in the underwriting process for high-risk vehicle models, or update the premium discount calculation parameters in the renewal process. While ensuring that the existing claims processes are not disrupted, these optimization strategies are applied in real time to newly initiated insurance, claims, and renewal business instances, thereby continuously improving the efficiency of auto insurance business processing and customer service experience.

[0036] In one embodiment of the present invention, after processing and cleaning the log data based on streaming computing, and before inputting the processed log data into a log analysis engine for analysis, the method further includes: The processed log data is written to the log analysis engine, which performs anomaly pattern recognition on the processed log data and performs root cause analysis in conjunction with the intelligent analysis module when an anomaly is detected. Based on the anomaly analysis results, a preset recovery strategy is triggered, which includes at least one of circuit breaker protection, cache degradation and default value compensation, and corresponding alarm information is output.

[0037] Optionally, after receiving and storing structured log data processed by streaming computing, the log analysis engine can perform real-time scanning and matching of the log stream based on preset anomaly detection rules, such as error code frequency thresholds and response time percentile anomalies. When an event matching an anomaly pattern is detected, the system automatically associates with intelligent analysis modules, such as a root cause analysis component integrating AIAgent, to perform in-depth analysis to locate the business node or data problem causing the anomaly. Subsequently, the system calls the corresponding recovery strategy from the policy library according to the preset anomaly type and level mapping relationship, such as triggering circuit breaker isolation for the abnormal service, enabling backup cache data for degradation processing, or using predefined default values ​​for business compensation. At the same time, the system generates and distributes alarm notifications containing information such as anomaly summary, scope of impact, and executed operations according to the alarm strategy. By embedding intelligent anomaly detection, root cause localization, and automated recovery capabilities, the system achieves an evolution from passive monitoring to proactive defense and rapid self-healing. By automating anomaly identification, intelligent analysis, policy execution, and alarm notification in a pipeline, the average recovery time from fault discovery to recovery is significantly shortened, reducing the risk of business interruption and the cost of manual intervention.

[0038] In one embodiment of the present invention, the analysis results and optimization suggestions generated by the log analysis engine are fed back to the visualization orchestration platform. When adjusting the process orchestration strategy, the method further includes executing a hot deployment emergency response, wherein the hot deployment emergency response includes: Without stopping the insurance application process, the code related to the process orchestration strategy is replaced by running a loader replacement; version management is performed on the atomic functional components or composite business components corresponding to the process orchestration strategy, and the change records of each version are stored in the version management library; after adjusting the process orchestration strategy, the updated strategy and code are deployed and verified through an automated hot deployment pipeline, and the process execution state is migrated based on the execution state snapshot when an exception occurs.

[0039] Optionally, the runtime loader replacement employs bytecode enhancement technologies such as Java Agent to dynamically modify the bytecode of loaded classes during JVM runtime, enabling uninterrupted updates to business logic. The version management library can record the version number, changes, release time, and dependencies of each component in a distributed database, supporting version rollback and difference comparison. The automated hot deployment pipeline can include steps such as environment checks, dependency verification, canary releases, health checks, and rollback contingency plans. During deployment, it takes memory snapshots of running process instances, saving their execution context and intermediate states, so that in the event of deployment failure, it can quickly restore to the snapshot state, ensuring business continuity.

[0040] As can be seen, the above solution, by combining visual orchestration with dynamic parameterized templates, can support the rapid construction of complex branch processes and agile adaptation to regional businesses. Through streaming computing and log analysis engines, it can achieve minute-level location and intelligent diagnosis of operational anomalies. Through closed-loop feedback of analysis results and orchestration strategies, it can achieve continuous self-optimization and elastic recovery of processes, significantly reducing system fault troubleshooting time and manual maintenance costs, and improving the resilience, observability and business response efficiency of the insurance process.

[0041] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0042] In one embodiment, a dynamic insurance application process management device is provided, which corresponds one-to-one with the dynamic insurance application process management method described in the above embodiments. For example... Figure 5 As shown, Figure 5 This is a schematic diagram of a dynamic insurance application process management device according to an embodiment of the present invention. The device includes a process modeling module 61, an orchestration engine module 62, a log collection and processing module 63, an intelligent analysis module 64, and a feedback execution module 65. Detailed descriptions of each functional module are as follows: Process modeling module 61 is used to obtain the actual insurance application process containing multiple business nodes and to establish an insurance application process model based on the actual insurance application process. The orchestration engine module 62 is used to construct a parameterized process template through a visual orchestration platform based on the process insurance model, define process execution logic including conditional branches and parallel execution, and generate or adjust the execution logic and order of each business node in the insurance process model based on the parameterized process template. The log collection and processing module 63 is used to collect log data generated by the insurance process model during its operation, and to process and clean the log data based on streaming computing. The intelligent analysis module 64 is used to build a log analysis engine based on elastic search technology. It inputs the processed log data into the log analysis engine for analysis, identifies process bottlenecks and abnormal patterns, and generates analysis results and process optimization suggestions. The feedback execution module 65 is used to feed back the analysis results and optimization suggestions generated by the log analysis engine to the visualization orchestration platform to adjust the process orchestration strategy.

[0043] In one embodiment, the orchestration engine module 62 is specifically used for: The insurance application process model is configured through a visual process orchestration platform. A parameterized process template is constructed based on the insurance application process model and the corresponding business parameters. The process execution logic of the parameterized process template is defined. Configure conditional branching rules for controlling the execution path of the business nodes and parallel execution rules for controlling the concurrent execution of multiple business nodes in the process execution logic; Based on the parameterized process template, generate or adjust the execution logic and execution order of each business node in the insurance application process model.

[0044] In one embodiment, the intelligent analysis module 64 is specifically used for: The processed log data is matched and analyzed against a pre-set rule base to identify abnormal patterns and obtain analysis results. A log analysis engine is built based on elastic search technology. The processed log data is input into the log analysis engine. Business knowledge obtained through enhanced retrieval technology is used to perform bottleneck analysis and decision inference to obtain decision inference results. Based on the analysis results and the decision deduction results, process optimization suggestions including specific operation instructions are generated.

[0045] In one embodiment, the dynamic insurance application process management device is further configured to: The processed log data is written to the log analysis engine, which performs anomaly pattern recognition on the processed log data and performs root cause analysis in conjunction with the intelligent analysis module when an anomaly is detected. Based on the anomaly analysis results, a preset recovery strategy is triggered, which includes at least one of circuit breaker protection, cache degradation and default value compensation, and corresponding alarm information is output.

[0046] In one embodiment, the dynamic insurance application process management device is further configured to: Execute a hot deployment emergency response, which includes: Without stopping the insurance application process, the code related to the process orchestration strategy is replaced by running a loader replacement; version management is performed on the atomic functional components or composite business components corresponding to the process orchestration strategy, and the change records of each version are stored in the version management library; after adjusting the process orchestration strategy, the updated strategy and code are deployed and verified through an automated hot deployment pipeline, and the process execution state is migrated based on the execution state snapshot when an exception occurs.

[0047] This invention provides a dynamic insurance application process management device. Through the collaboration of a process modeling module and an orchestration engine module, it transforms the traditional hard-coded insurance application process into a dynamically configurable parameterized template. Business personnel can directly adjust the process logic, rule parameters, and execution paths through a visual interface. Based on a streaming computing framework, runtime logs are cleaned and structured in real time. Combined with a log analysis engine built on elastic search in the intelligent analysis module, process bottlenecks and abnormal patterns can be located and root cause analyzed within minutes. This mechanism solves the black-box problem in traditional multi-system collaboration scenarios, enabling operations and maintenance personnel to quickly locate cross-system faults and significantly reduce the mean time to recovery. The feedback execution module automatically feeds back the optimization suggestions generated by the analysis to the process orchestration stage, forming a complete closed loop of operation-monitoring-analysis-optimization.

[0048] Specific limitations regarding the dynamic insurance application process management device can be found in the limitations of the dynamic insurance application process management method described above, and will not be repeated here. Each module in the aforementioned dynamic insurance application process management device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0049] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 6 As shown, Figure 6 This is a schematic diagram of a computer device according to an embodiment of the present invention. The computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with external clients via a network connection. When the computer program is executed by the processor, it implements the functions or steps of a data processing method for insurance business on the server side.

[0050] In one embodiment, a computer device is provided, which may be a client, and its internal structure diagram may be as follows: Figure 7 As shown, Figure 7This is another schematic diagram of a computer device according to an embodiment of the present invention. The computer device includes a processor, memory, network interface, display screen, and input device connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used to communicate with an external server via a network connection. When the computer program is executed by the processor, it implements the functions or steps on the client side of the method.

[0051] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps: Obtain the actual insurance application process that includes multiple business nodes, and establish an insurance application process model based on the actual insurance application process; Based on the aforementioned insurance application process model, a parameterized process template is constructed through a visual orchestration platform, defining process execution logic that includes conditional branches and parallel execution. Based on the parameterized process template, the execution logic and order of each business node in the insurance application process model are generated or adjusted. During the operation of the insurance application process model, log data generated by the insurance application process model is collected, and the log data is processed and cleaned based on streaming computing. The log analysis engine, built on elastic search technology, takes processed log data into the engine for analysis, identifies process bottlenecks and abnormal patterns, and generates analysis results and process optimization suggestions. The analysis results and optimization suggestions generated by the log analysis engine are fed back to the visualization orchestration platform to adjust the process orchestration strategy.

[0052] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor: Obtain the actual insurance application process that includes multiple business nodes, and establish an insurance application process model based on the actual insurance application process; Based on the aforementioned insurance application process model, a parameterized process template is constructed through a visual orchestration platform, defining process execution logic that includes conditional branches and parallel execution. Based on the parameterized process template, the execution logic and order of each business node in the insurance application process model are generated or adjusted. During the operation of the insurance application process model, log data generated by the insurance application process model is collected, and the log data is processed and cleaned based on streaming computing. The log analysis engine, built on elastic search technology, takes processed log data into the engine for analysis, identifies process bottlenecks and abnormal patterns, and generates analysis results and process optimization suggestions. The analysis results and optimization suggestions generated by the log analysis engine are fed back to the visualization orchestration platform to adjust the process orchestration strategy.

[0053] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or computer device described above can be referred to the relevant descriptions on the server side and client side in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0054] Those skilled in the art will understand 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 can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile 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. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0055] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0056] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A dynamic insurance application process management method, characterized in that, include: Obtain the actual insurance application process that includes multiple business nodes, and establish an insurance application process model based on the actual insurance application process; Based on the aforementioned insurance application process model, a parameterized process template is constructed through a visual orchestration platform, defining process execution logic that includes conditional branches and parallel execution. Based on the parameterized process template, the execution logic and order of each business node in the insurance application process model are generated or adjusted. During the operation of the insurance application process model, log data generated by the insurance application process model is collected, and the log data is processed and cleaned based on streaming computing. The log analysis engine, built on elastic search technology, takes processed log data into the engine for analysis, identifies process bottlenecks and abnormal patterns, and generates analysis results and process optimization suggestions. The analysis results and optimization suggestions generated by the log analysis engine are fed back to the visualization orchestration platform to adjust the process orchestration strategy.

2. The dynamic insurance application process management method as described in claim 1, characterized in that, The step of constructing a parameterized process template through a visual orchestration platform to generate or adjust the execution logic and order of each business node in the insurance application process model includes: The insurance application process model is configured through a visual process orchestration platform. A parameterized process template is constructed based on the insurance application process model and the corresponding business parameters. The process execution logic of the parameterized process template is defined. Configure conditional branching rules for controlling the execution path of the business nodes and parallel execution rules for controlling the concurrent execution of multiple business nodes in the process execution logic; Based on the parameterized process template, generate or adjust the execution logic and execution order of each business node in the insurance application process model.

3. The dynamic insurance application process management method as described in claim 1, characterized in that, The process of collecting log data generated by the insurance application process model and processing and cleaning the log data based on stream computing includes: After the collected log data is cached and distributed via a message queue, the log data is parsed, formatted, and anomaly filtered through streaming computing to generate structured log events. The structured log events include information about associated process node identifiers and business context.

4. The dynamic insurance application process management method as described in claim 3, characterized in that, After processing and cleaning the log data using stream computing, and before inputting the processed log data into the log analysis engine for analysis, the method further includes: The processed log data is written into the log analysis engine, and anomaly pattern recognition is performed on the processed log data. When an anomaly is detected, root cause analysis is performed in conjunction with the intelligent analysis module. Based on the anomaly analysis results, a preset recovery strategy is triggered. The preset recovery strategy includes at least one of circuit breaker protection, cache degradation and default value compensation, and corresponding alarm information is output.

5. The dynamic insurance application process management method as described in claim 4, characterized in that, The log analysis engine, built on elastic search technology, receives processed log data for analysis, identifies process bottlenecks and anomaly patterns, and generates analysis results and process optimization suggestions, including: The processed log data is matched and analyzed against a pre-set rule base to identify abnormal patterns and obtain analysis results. A log analysis engine is built based on elastic search technology. The processed log data is input into the log analysis engine. Through business knowledge obtained by enhanced retrieval technology, bottleneck analysis and decision inference are performed to obtain decision inference results. Based on the analysis results and the decision deduction results, process optimization suggestions including specific operation instructions are generated.

6. The dynamic insurance application process management method as described in claim 5, characterized in that, The step of feeding back the analysis results and optimization suggestions generated by the log analysis engine to the visualization orchestration platform to adjust the process orchestration strategy includes: The analysis results, decision inference results, and corresponding process optimization suggestions output by the log analysis engine are encapsulated in a structured manner to form a strategy adjustment instruction that can be parsed by the process orchestration engine. The visualization orchestration platform adjusts at least one of the following in accordance with the strategy adjustment instructions: the node execution order, conditional branch logic, node call parameters, or parallel / serial execution mode of the current insurance application process. Without interrupting the ongoing insurance application process, the adjusted process orchestration strategy will be applied to any newly created process instances.

7. The dynamic insurance application process management method as described in claim 6, characterized in that, When feeding back the analysis results and optimization suggestions generated by the log analysis engine to the visualization orchestration platform to adjust the process orchestration strategy, the method further includes executing a hot deployment emergency response, wherein the hot deployment emergency response includes: Without stopping the insurance application process, the code related to the process orchestration strategy is replaced by running a loader replacement; Version management is performed on the atomic functional components or composite business components corresponding to the process orchestration strategy, and the change records of each version are stored in the version management library; After adjusting the process orchestration strategy, the updated strategy and code are deployed and verified through an automated hot deployment pipeline, and the process execution state is migrated based on the execution state snapshot when an exception occurs.

8. A dynamic insurance application process management device, characterized in that, include: The process modeling module is used to obtain the actual insurance application process that includes multiple business nodes, and to build an insurance application process model based on the actual insurance application process. The orchestration engine module is used to construct a parameterized process template through a visual orchestration platform based on the insurance process model, define the process execution logic including conditional branches and parallel execution, and generate or adjust the execution logic and order of each business node in the insurance process model based on the parameterized process template. The log collection and processing module is used to collect log data generated by the insurance process model during its operation, and to process and clean the log data based on streaming computing. The intelligent analysis module is used to build a log analysis engine based on elastic search technology. It inputs the processed log data into the log analysis engine for analysis, identifies process bottlenecks and abnormal patterns, and generates analysis results and process optimization suggestions. The feedback execution module is used to feed back the analysis results and optimization suggestions generated by the log analysis engine to the visualization orchestration platform to adjust the process orchestration strategy.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the dynamic insurance application process management method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the dynamic insurance application process management method as described in any one of claims 1 to 7.

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