Resource circulation method and device based on insurance service decision, electronic equipment and storage medium

Abstract

The invention discloses a resource circulation method and device based on an insurance service decision, electronic equipment and a storage medium, relates to the technical field of financial and service risk control, and aims at resource circulation in an insurance service to realize risk pre-identification and improve the success rate and the security while avoiding missing an execution opportunity. The method comprises the following steps: in response to a resource transfer request, obtaining a target insurance order of a to-be-executed resource transfer operation, and generating a scene state vector in combination with the target insurance order and a business scene where the target insurance order is located; carrying out resource quantity verification on the target insurance order by adopting a preset resource verification rule, and carrying out multi-dimensional risk assessment on the scene state vector under the condition that the verification is passed, so as to generate a risk assessment result; and under the condition that the risk assessment result indicates low risk, determining an optimal resource transfer path, and under the condition that the target insurance order passes the final security verification, executing resource transfer operation by adopting the optimal resource transfer path.

Description

Technical Field

[0001] This application relates to the field of financial and business risk control technology, and in particular to a resource transfer method, apparatus, electronic device and storage medium based on insurance business decisions. Background Technology

[0002] In the insurance business operation system, resource flow is a core link, covering key business scenarios such as surrender payment, claims payment, dividend distribution and renewal deduction. Its efficient, accurate and safe execution is directly related to the insurance company's operational efficiency, risk management capabilities and customer satisfaction.

[0003] In related technologies, to address the complex needs of insurance business resource flow, rule engines and process automation technologies are introduced to construct a resource flow processing model of "static rules + batch execution." Specifically, fixed rules are pre-set to classify and process various resource flow businesses, and resource payment, deduction, and other operations are executed in batches according to preset time periods or business trigger conditions. For example, for surrender payments, fixed approval processes and payment time nodes are set; for claims disbursements, payments are made in batches after review is completed, based on established claims rules and processes.

[0004] However, the applicant recognizes that the relevant technology has at least the following technical problems in its implementation: On the one hand, insufficient dynamic response capabilities prevent real-time perception of dynamic information such as changes in customer behavior, policy stage evolution, and external market fluctuations, leading to rigid resource transfer strategies that are difficult to adjust flexibly according to actual conditions, missing the optimal time for resource transfer execution, and affecting resource utilization efficiency. On the other hand, lagging risk control mechanisms mean that abnormal behavior is often only discovered after resource transfer has been executed, which can easily lead to risks such as resource transfer errors and fraud. At the same time, it may also result in penalties for violating regulatory requirements, leading to frequent problems such as high resource transfer failure rates, uncertain arrival times, and lack of transparency regarding the reasons for failure. Summary of the Invention

[0005] In view of this, this application provides a resource transfer method, device, electronic device and storage medium based on insurance business decision-making. The main purpose is to solve the problems that are currently difficult to adjust flexibly according to the actual situation, miss the optimal execution time of resource transfer, affect the efficiency of resource use, and cause high failure rate, uncertain arrival time and lack of transparency of failure reasons.

[0006] According to the first aspect of this application, a resource transfer method based on insurance business decisions is provided, the method comprising: In response to a resource transfer request, the target insurance order for which the resource transfer operation is to be performed is obtained, and a scenario state vector is generated by combining the target insurance order and the business scenario in which the target insurance order is located. The target insurance order is verified for resources using preset resource verification rules. If the verification is successful, a multi-dimensional risk assessment is performed on the scenario state vector to generate a risk assessment result. If the risk assessment results indicate low risk, the optimal resource transfer path is determined, and if the target insurance order passes the final security check, the resource transfer operation is performed using the optimal resource transfer path.

[0007] According to a second aspect of this application, a resource transfer device based on insurance business decisions is provided, the device comprising: The generation module is used to respond to resource transfer requests, obtain the target insurance order to be executed for resource transfer operations, and generate a scenario state vector by combining the target insurance order and the business scenario in which the target insurance order is located. The evaluation module is used to verify the resource quantity of the target insurance order using preset resource verification rules. If the verification is successful, a multi-dimensional risk assessment is performed on the scenario state vector to generate a risk assessment result. The resource transfer module is used to determine the optimal resource transfer path when the risk assessment result indicates low risk, and to perform resource transfer operations using the optimal resource transfer path when the target insurance order passes the final security verification.

[0008] According to a third aspect of this application, an electronic device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in any of the first aspects above.

[0009] According to a fourth aspect of this application, a storage medium is provided that stores a computer program thereon, which, when executed by a processor, implements the steps of the method described in any one of the first aspects above.

[0010] By utilizing the above technical solutions, this application provides a resource transfer method, apparatus, electronic device, and storage medium based on insurance business decisions. This application addresses resource transfer in insurance business by identifying the business scenario of insurance orders, achieving dynamic fusion of user behavior data and external environmental data related to insurance orders. This ensures real-time perception of changes in user behavior and the external environment of the policy, and incorporates these perceived changes during the resource transfer process. This enhances the flexibility of the resource transfer strategy, allowing for flexible adjustments based on actual conditions. While avoiding missing optimal resource transfer execution opportunities and improving resource utilization efficiency, multiple risk assessments enable proactive risk identification, reducing the frequency of issues such as uncertain arrival times and opaque reasons for failure, further improving the success rate and security of resource transfer.

[0011] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0012] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 This is a schematic diagram of an application environment for a resource transfer method based on insurance business decision-making in one embodiment of the present invention; Figure 2 This is a flowchart illustrating a resource transfer method based on insurance business decisions in one embodiment of the present invention; Figure 3 This is a flowchart illustrating a specific implementation of step S10; Figure 4 This is a flowchart illustrating a specific implementation of step S20; Figure 5 This is a flowchart illustrating a specific implementation of step S30; Figure 6 This is another flowchart illustrating the resource transfer method based on insurance business decisions in one embodiment of the present invention; Figure 7 This is a schematic diagram of a resource transfer device based on insurance business decision-making in one embodiment of the present invention; Figure 8 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention; Figure 9This is another structural schematic diagram of an electronic device according to one embodiment of the present invention. Detailed Implementation

[0013] 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.

[0014] The resource transfer method based on insurance business decisions provided in this invention can be applied to, for example... Figure 1 In this application environment, the client communicates with the server via a network. The server responds to the client's resource transfer request by obtaining the target insurance order for which the resource transfer operation is to be performed. Combining the target insurance order with its business scenario, the server generates a scenario state vector. It then verifies the resource quantity of the target insurance order using preset resource verification rules. If the verification passes, the server performs a multi-dimensional risk assessment on the scenario state vector, generating a risk assessment result. If the risk assessment result indicates low risk, the server determines the optimal resource transfer path. Finally, if the target insurance order passes the final security check, the server executes the resource transfer operation using the optimal resource transfer path.

[0015] In this invention, for resource transfer in insurance business, by identifying the business scenario of insurance orders, dynamic fusion of user behavior data and external environmental data related to insurance orders is achieved. This ensures real-time perception of changes in user behavior and the external environment of the policy, and incorporates these perceived changes into the resource transfer process. This enhances the flexibility of the resource transfer strategy, allowing for flexible adjustments based on actual conditions. While avoiding missing optimal resource transfer execution opportunities and improving resource utilization efficiency, multiple risk assessments enable proactive risk identification, reducing the frequency of issues such as uncertain arrival times and opaque reasons for failures, further improving the success rate and security of resource transfer. The client can be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server can be implemented using a standalone server or a server cluster consisting of multiple servers. The invention will be described in detail below through specific embodiments.

[0016] Please see Figure 2 As shown, Figure 2 A flowchart illustrating a resource transfer method based on insurance business decisions provided in an embodiment of the present invention includes the following steps: S10: In response to the resource transfer request, obtain the target insurance order for the resource transfer operation to be performed, and generate a scenario state vector by combining the target insurance order and the business scenario in which the target insurance order is located.

[0017] The resource transfer method based on insurance business decisions provided by this invention can be applied to resource transfer systems in various application scenarios. These systems are typically implemented through a server that can receive resource transfer requests initiated by clients in real time. In practical applications, a payment center can be set up within the resource transfer system. Payments triggered by online connections, counter transactions, asynchronous tasks, etc., all need to be registered with the payment center so that the resource transfer system can receive resource transfer requests based on the payment center. These resource transfer requests can be counter fund transfer requests, online fund transfer requests, asynchronous business task requests, etc.

[0018] When the resource transfer system receives a resource transfer request, it first needs to locate the target insurance order corresponding to the resource transfer operation to be executed. Specifically, it can extract key information from the requests registered with the payment center, such as the policy number and payment type, to identify the target insurance order. Subsequently, the resource transfer system combines the specific information of the target insurance order and its business scenario to construct a multi-dimensional scenario state vector. The scenario state vector is a data structure containing multiple dimensions to comprehensively describe the current state of the insurance order, including but not limited to policy type fields (such as pension insurance, health insurance), policy stage fields (such as underwriting, effective), policy time fields (such as days remaining until maturity), policy user behavior fields (such as the number of cancellation applications in the past 30 days), and policy environment fields (such as changes in central bank interest rates, updates to regulatory policies). The selection of dimensions in the scenario state vector aims to dynamically capture changes in user behavior and the external environment of the policy, ensuring that the system can perceive and respond to these changes in real time.

[0019] In this way, by constructing scenario state vectors, the resource flow system can achieve a comprehensive and dynamic description of insurance orders and their business environment, providing a rich and accurate data foundation for subsequent resource quantity verification and risk assessment, thereby improving the flexibility and adaptability of resource flow strategies. For example, suppose the resource flow system receives a request to cancel a health insurance policy. The system first locates the policy and extracts information such as its policy number and payment type (cancellation). Then, the system combines external environmental information such as the policy being in the "effective" stage, having one year remaining until maturity, the customer having no cancellation application record in the past 30 days, and the current central bank interest rate remaining unchanged to generate a scenario state vector containing these dimensions.

[0020] Among them, such as Figure 3As shown, in step S10, that is, in response to the resource transfer request, the target insurance order to be executed for resource transfer operation is obtained, and a scenario state vector is generated by combining the target insurance order and the business scenario in which the target insurance order is located, including the following steps: S11: When a resource transfer request is received, the target insurance order is determined based on the order identifier carried in the resource transfer request.

[0021] In this embodiment of the invention, when the resource transfer system receives a resource transfer request, it first parses the request and extracts the order identifier carried within it. The order identifier is a string or number combination that uniquely identifies an insurance order and is usually associated with the creation or management process of the insurance order. The resource transfer system uses this order identifier to query the database or order management system to locate the target insurance order corresponding to the identifier. This ensures that the resource transfer system can accurately and quickly identify the insurance orders that need to be processed, improving the efficiency and accuracy of the resource transfer system in processing resource transfer requests, and providing a basis for subsequent resource quantity verification and risk assessment.

[0022] For example, suppose the resource transfer system receives a resource transfer request that carries an order identifier "POL123456789". The resource transfer system parses the request, extracts the order identifier, and queries the database to find the health insurance policy corresponding to the identifier. This policy is the target insurance order.

[0023] S12: Obtain the basic policy information of the target insurance order, and obtain the basic scenario information of the target insurance order based on the business scenario in which the target insurance order is located.

[0024] In this embodiment of the invention, after identifying the target insurance order, the resource transfer system further acquires the basic policy information of the order, including but not limited to the policy number, policy type (such as pension insurance, health insurance), policy amount, and policyholder information. Simultaneously, based on the business scenario of the target insurance order, such as application, renewal, or surrender, the resource transfer system acquires basic information for that scenario, such as the current stage (e.g., in progress, effective, or surrender period) and the time remaining until key events (e.g., days remaining until maturity). This information collectively constitutes a complete profile of the target insurance order, enabling the resource transfer system to comprehensively understand the status and environment of the target insurance order, providing data support for subsequent risk assessment and path planning.

[0025] Continuing with the example above, after the resource flow system determines that the target insurance order is the health insurance policy corresponding to "POL123456789", it further obtains the basic information of the policy, such as the policy type being "health insurance" and the policy amount being "100,000 yuan". At the same time, based on the business scenario of the policy being in the "surrender period", it obtains the basic scenario information such as the current stage being "in the process of surrendering" and the number of days remaining until the expiration date being "30 days".

[0026] S13: Split the policy basic information and scenario basic information into multiple basic information fields.

[0027] In this embodiment of the invention, the resource transfer system performs field splitting on the acquired basic policy information and scenario information, decomposing the complex information structure into multiple independent basic information fields. These multiple basic information fields include, but are not limited to, policy type fields (e.g., "health insurance"), policy stage fields (e.g., "in the process of surrendering the policy"), policy time fields (e.g., "30 days remaining until maturity"), policy user behavior fields (e.g., "no surrender application record in the past 30 days"), and policy environment fields (e.g., "central bank interest rate has not changed"). Through field splitting, the complex information structure is transformed into multiple independent, processable basic information fields, which helps the system process and analyze information more precisely, improves the flexibility and efficiency of information processing, and facilitates the subsequent construction of multi-dimensional state vectors.

[0028] In the above example, the resource transfer system splits the obtained basic policy information and scenario information into multiple basic information fields, such as the policy type field being "health insurance", the policy stage field being "in the process of surrendering the policy", the policy time field being "30 days remaining until the maturity date", the policy user behavior field being "no surrender application record in the past 30 days", and the policy environment field being "the central bank interest rate has not changed".

[0029] S14: Construct a multidimensional state vector using multiple basic information fields, and use the multidimensional state vector as the scene state vector.

[0030] In this embodiment of the invention, the resource transfer system utilizes multiple basic information fields obtained from the decomposition to construct a multi-dimensional state vector. This vector is a data structure containing multiple dimensions, each corresponding to a basic information field, such as policy type, policy stage, and policy time. Subsequently, the resource transfer system uses this multi-dimensional state vector as a scenario state vector for subsequent steps such as resource quantity verification, risk assessment, and path planning. In practical applications, the scenario state vector can be as follows:

[0031] in, Represents the scene state vector; This field indicates the policy type, such as pension insurance, health insurance, or annuity insurance. The policy stage field indicates the current stage of the target insurance order, such as underwriting, cooling-off period, effective, 30 days before maturity, maturity date, surrender period, etc. The policy time field indicates the time remaining until a key event, such as the number of days until the expiry date. This field represents the policyholder behavior and is used to indicate the recent behavior of the user of the target insurance order, such as the number of times the user has applied for policy cancellation, the frequency of login, and the frequency of information modification in the past 30 days. The policy environment field is used to represent the external environment of the target insurance order, such as changes in central bank interest rates, updates to regulatory policies, and the status of payment channels.

[0032] In this way, by constructing a multidimensional state vector and using it as the scenario state vector, a comprehensive and dynamic description of the target insurance order and its business environment can be achieved. This provides a rich and accurate data foundation for subsequent steps, thereby improving the flexibility and adaptability of resource transfer strategies. In the example above, the resource transfer system uses several basic information fields obtained from the decomposition, such as "health insurance," "in the process of surrendering the policy," "30 days remaining until maturity," "no surrender application record in the past 30 days," and "central bank interest rate has not changed," to construct a multidimensional state vector. This multidimensional state vector is then used as the scenario state vector for subsequent steps such as resource quantity verification, risk assessment, and determination of the optimal resource transfer path.

[0033] S20: Verify the resource quantity of the target insurance order using preset resource verification rules. If the verification is successful, perform a multi-dimensional risk assessment on the scenario state vector and generate a risk assessment result.

[0034] In this embodiment of the invention, the resource transfer system uses preset resource verification rules to verify the resource quantity of the target insurance order. These rules include, but are not limited to, whether a single payment exceeds the account's daily limit and whether the refund amount exceeds the limit. Specifically, the verification process can be implemented through a rule engine. The rule engine can configure and calculate rule sets and business verification rule sets according to different scenario IDs, and verify the resource quantity of the target insurance order according to the determined rules.

[0035] After verification, the resource transfer system conducts a multi-dimensional risk assessment of the scenario state vector. The assessment dimensions include user credit (constructed based on historical payment records, number of overdue payments, policy value, etc.), user behavior (based on recent operation frequency, time distribution, and deviation of operation paths from normal patterns), policy compliance (determined by the rules engine whether regulatory policies are violated), and resource transfer risk (including amount, payee type, region, time window, etc.). For each dimension, the resource transfer system establishes corresponding scoring standards and weights, ultimately generating a comprehensive risk assessment result.

[0036] In this way, through pre-defined resource verification rules and multi-dimensional risk assessment, the resource transfer system can proactively identify potential risks before resource transfer, reducing the frequency of issues such as mispayment, fraud, or regulatory penalties caused by unidentified risks. Continuing with the example of the health insurance cancellation request, the resource transfer system first verifies the policy's resource volume to confirm that the cancellation amount does not exceed the account's daily limit. Then, it performs a multi-dimensional risk assessment on the scenario's state vector, finding that the user has a high credit score (no overdue records, moderate policy value), no abnormal user behavior (no recent cancellation requests), a perfect compliance score (no violation of any regulatory policies), and low transaction risk (payee is a personal account, not from a high-risk country). Ultimately, a low-risk risk assessment result is generated.

[0037] Among them, such as Figure 4 As shown, in step S20, the resource quantity of the target insurance order is verified using preset resource verification rules. If the verification is successful, a multi-dimensional risk assessment is performed on the scenario state vector to generate a risk assessment result, including the following steps: S21: Extract the scenario identifier of the business scenario and query the preset resource verification rules associated with the scenario identifier.

[0038] In this embodiment of the invention, the resource transfer system first extracts a unique scenario identifier from the business scenario in which the target insurance order is located. The scenario identifier is a specific code or name used to distinguish different business scenarios; it can be a scenario ID. It represents the specific business stage the insurance order is currently in, such as insurance application, renewal, claims, or cancellation. Next, the resource transfer system queries a pre-set rule base based on the scenario identifier to find the associated resource verification rules. These rules are a series of pre-defined conditions for different business scenarios, used to determine whether the resource quantity of the target insurance order meets the requirements. The rule base is pre-created. Specifically, when creating the rule base, it's necessary to configure calculation rule sets and business verification rule sets based on different scenario IDs. For example, if the policy type is accident insurance, the payment type is policy surrender, and the coverage period is one year, a policy surrender calculation rule set with ID ACCI_SURR_RULES is configured. Under this CODE, policy surrender calculation rules and business verification rules can be configured. For instance, if multiple payments occur within 3 days under the same policy, resulting in duplicate payments, counter approval is required. Simultaneously, the rule base supports rule registration and version management, enabling rule creation, deletion, modification, querying, and version control. Furthermore, the rule base has rule orchestration and scheduling functions, supporting triggering corresponding rule sets by scenario ID, policy type, and other dimensions. Additionally, the rule base sets up an execution verification mechanism, including a rule test sandbox providing rule test interfaces to support input sample verification output, rule execution logs recording the hit status of each rule, and rule validity verification performing syntax checks and dependency checks (such as the existence of referenced functions).

[0039] In this way, by extracting scenario identifiers and querying associated resource verification rules, the resource flow system can adopt different verification standards for different business scenarios, improving the accuracy and relevance of resource quantity verification and providing a reliable basis for subsequent processes. For example, in a car insurance policy cancellation scenario, the resource flow system extracts the scenario identifier "car insurance cancellation," and then queries the rule base to find the resource verification rules associated with this identifier. The rules stipulate conditions such as the policy's cash value must be greater than zero at the time of cancellation.

[0040] S22: Extract at least one resource quantity information related to the resource quantity from the target insurance order, and call the rule engine to verify at least one resource quantity information according to the resource verification rules.

[0041] In this embodiment of the invention, the resource transfer system extracts information related to resource quantity from the target insurance order. This resource quantity information may include the policy's cash value, premium amount, claim amount, etc., depending on the business scenario and resource verification rules. After extracting the resource quantity information, the resource transfer system calls the rule engine. The rule engine is a software component that can process and judge input data according to preset rules. The rule engine verifies the extracted resource quantity information one by one according to the resource verification rules. The verification mainly determines whether each resource quantity exceeds the resource quantity range set by the resource verification rules. For example, if the rule stipulates that a certain resource quantity should be within the range of A to B, the rule engine will check whether the actual value of the resource quantity falls within this range.

[0042] In this way, by automating the verification of resource quantity information through a rules engine, it is possible to quickly and accurately determine whether the resource quantity meets the requirements, thereby improving verification efficiency and accuracy and reducing the possibility of human error. For example, in the above-mentioned car insurance cancellation scenario, if the cash value extracted from the policy is 5,000 yuan, the rules engine determines, based on the resource verification rules, that the cash value is greater than zero, thus meeting the cash value requirement in the cancellation conditions.

[0043] S23: If it is confirmed that none of the resource quantity information exceeds the resource quantity range set by the resource verification rules, the target insurance order is determined to have passed the resource quantity verification.

[0044] In this embodiment of the invention, after the rule engine completes the verification of all resource quantity information, the resource transfer system checks the verification results. If it finds that none of the resource quantity information exceeds the resource quantity range set by the resource verification rule for it, that is, all verification conditions are met, the resource transfer system determines that the target insurance order has passed the resource quantity verification, meaning that the policy's resource quantity complies with relevant regulations in the current business scenario, and subsequent risk assessment and resource transfer operations can be carried out.

[0045] In this way, the above process ensures that only insurance orders with sufficient resources can proceed to the next stage. This guarantees the rationality and security of resource flow from a resource quantity perspective, avoiding flow failures or risks due to resource quantity issues. Continuing with the example of car insurance policy cancellation, since the cash value of 5,000 yuan meets the rule requirements, the car insurance policy has passed the resource quantity verification and can proceed to the subsequent risk assessment stage.

[0046] It should be noted that in practical applications, if verification determines that at least one resource quantity exceeds the resource quantity range set by the resource verification rules, and the target insurance order fails the resource quantity verification, a resource flow warning message needs to be generated and pushed to the preset information recipient. Specifically, for the rule engine, if an abnormal amount is found after execution (such as the refund amount exceeding the limit), it will automatically mark risk_flag: "HIGH" in the business document and record the reason for the abnormality (such as "the refund amount exceeds the premium amount"). At the same time, it will write to the event log and the database. The workflow engine will trigger the workflow to push the task to the risk control platform or counter operation system. After the counter staff reviews the abnormality details, they will provide supplementary explanations or approve / reject the application. Finally, the status will be written back to the rule engine to complete the closed loop.

[0047] S24: Determine the preset multidimensional risk assessment strategy, calculate multiple vector scores for the scenario state vector according to the multidimensional risk assessment strategy, integrate the multiple vector scores to obtain the risk score, and use the risk score as the risk assessment result.

[0048] In this embodiment of the invention, the resource transfer system will continue to perform risk assessment on the scene state vector to obtain a risk assessment result. Specifically, the resource transfer system will first calculate multiple vector scores for the scene state vector according to a multi-dimensional risk assessment strategy, and then integrate the multiple vector scores to obtain a risk score. The specific process of generating the risk score is as follows: First, policy user behavior fields are extracted from the scenario state vector. These fields record various behavioral information of users in the insurance business, such as the number of insurance applications, the number of claims, and payment records. Based on a multi-dimensional risk assessment strategy, the policy user behavior fields are scored to obtain user credit scores and user behavior scores. The user credit score can be used... This indicates that the system is built upon historical payment records, number of overdue payments, policy value, credit history, etc. Specifically, a level can be set for each type of abnormal behavior, and a user's credit score is calculated through relevant credit parameters, ranging from 0 to 100. The specific dimensions, indicators, and calculation methods are shown in Table 1 below: Table 1

[0049] As shown in Table 1, historical payment records involve payment success rate and number of delayed days, calculated using a weighted average, with a score range of 0-100 points; the number of overdue payments is based on the number of overdue payments in the past 12 months, with 0 overdue payments receiving 100 points, ≥3 overdue payments receiving 0 points, and linear interpolation in between; the policy value is scored in segments based on the total value of the current valid policy, with low (<50,000) receiving 60 points, medium (50,000 - 200,000) receiving 80 points, and high (>200,000) receiving 100 points; the credit history is based on whether there are historical fraud / complaint records, with 0 points for those and 100 points for those without.

[0050] User behavior scoring can be used This indicates that user behavior scoring is used to indicate the degree of abnormality in customer behavior. In practical applications, the degree of deviation of user behavior can be calculated based on recent operation frequency, time distribution, operation path and normal pattern as user behavior score, and dynamic Z-score standardization is adopted to make its range from 0 to 100.

[0051] Next, the resource flow system extracts the policy environment field from the scenario state vector. This field contains external environmental information related to the policy, such as changes in market interest rates and policy / regulatory adjustments. Based on a multi-dimensional risk assessment strategy, the system scores the policy environment field to obtain a policy compliance score. In practical applications, the policy compliance score can be used... It is stated that the specific determination can be made by the rules engine, which assesses whether there is a violation of regulatory policies (such as the threshold for reporting large transactions), with a value range of 0 to 100. Specifically, a score can be set for each rule, and points will be deducted if any of the following conditions are triggered. If 100 points are deducted, the issue will be pushed to the risk control platform or counter operation system. These conditions include: a single transaction amount > 50,000 yuan (large transaction), the recipient is a high-risk country / region, the recipient is a blacklisted account, and the same customer makes more than 10 payments in 24 hours.

[0052] Then, the resource transfer system continues to extract multiple risk factors from the multi-dimensional risk assessment strategy. Risk factors are various factors affecting resource transfer risk, such as amount, payee type, region, and time window. The resource transfer system evaluates the factor score corresponding to each risk factor on the scenario state vector, obtaining multiple factor scores. Based on the factor weight of each risk factor in the multi-dimensional risk assessment strategy, the system performs a weighted calculation on these multiple factor scores, and uses the result as the resource transfer risk score. In practical applications, the resource transfer risk score can be used... The risk factors include amount, payee type, region, time window, whether multiple payments were made within a few days, and account type. Each risk factor has a corresponding set of rules and weights to calculate a weighted average of the factor scores for each risk factor, resulting in a resource transfer risk score. The resource transfer risk score ranges from 0 to 100. The rule set and weights for each risk factor are shown in Table 2 below. Table 2

[0053] In Table 2, the amount factor (R1, weight 20%) focuses on anomalies where a single transaction exceeds RMB 100,000 or exceeds the account limit; the payee type factor (R2, weight 15%) distinguishes the risk differences between personal accounts, corporate accounts, and unknown / anonymous accounts; the geographical factor (R3, weight 20%) focuses on identifying fund flows involving high-risk countries; the time window factor (R4, weight 10%) captures cross-border payment behavior during non-working hours (e.g., 00:00-06:00); the multiple payment factor (R5, weight 20%) monitors situations where the same payee makes 3 or more payments within 7 days; and the account type factor (R6, weight 15%) marks newly registered accounts, inactive accounts, and suspected test accounts for risk assessment. The rule sets of each factor are weighted to generate a comprehensive score as a resource flow risk score, achieving quantitative identification of transaction risk.

[0054] Finally, the resource transfer system queries the weights of user credit score, user behavior score, policy compliance score, and resource transfer risk score in the multi-dimensional risk assessment strategy. Using these weights, it performs a weighted calculation on the user credit score, user behavior score, policy compliance score, and resource transfer risk score, and uses the result as the risk score. Specifically, the risk score can be calculated using the following formula: Formula 1:

[0055] in, Indicates risk score, Indicates the user's credit score. This indicates the weighting of the user's credit score. Indicates user behavior rating, This indicates the rating weight corresponding to the user behavior score. Indicates the policy compliance score. This indicates the weighting of the policy compliance score. Indicates the risk score for resource transfer. This indicates the scoring weight corresponding to the resource transfer risk score. In practical applications, , , , The sum of is 1.

[0056] S30: If the risk assessment results indicate low risk, determine the optimal resource transfer path, and if the target insurance order passes the final security check, execute the resource transfer operation using the optimal resource transfer path.

[0057] In this embodiment of the invention, when the risk assessment result indicates low risk, the resource transfer system enters the optimal resource transfer path determination stage. Under the premise of meeting five-dimensional constraints—amount, risk level, account type, channel availability, and timeliness requirements—it automatically identifies and recommends a "comprehensively optimal" payment path. Specifically, determining the optimal resource transfer path requires considering multiple factors such as transaction fees, arrival time, and risk score. It uses hard constraint filtering (such as channel availability, account limit matching, and timeliness requirements) and comprehensive score calculation to determine the optimal resource transfer path. After determining the optimal resource transfer path, the resource transfer system performs a final security verification, including amount consistency verification and dual verification of account authenticity. Upon successful verification, the resource transfer system executes the resource transfer operation using the optimal resource transfer path.

[0058] In this way, by determining the optimal resource transfer path and performing final security checks, the resource transfer system can achieve efficient resource transfer while ensuring security, improving resource utilization efficiency and reducing operational risks. In the example of the health insurance cancellation request mentioned above, the resource transfer system determined that the request was low-risk based on the risk assessment results. Subsequently, the resource transfer system used the optimal payment path planning algorithm to find a payment path with the lowest handling fee and the fastest arrival time while satisfying various constraints. After passing final security checks such as amount consistency verification and dual verification of account authenticity, the system used this optimal path to execute the transfer operation of the cancellation funds, ensuring that the funds reach the user's designated account safely and quickly.

[0059] Among them, such as Figure 5 As shown, in step S30, that is, when the risk assessment result indicates low risk, the optimal resource transfer path is determined, and when the target insurance order passes the final security verification, the resource transfer operation is performed using the optimal resource transfer path, including the following steps: S31: Query the target risk level matched by the risk assessment results. If the target risk level indicates low risk, confirm that the risk assessment results indicate low risk.

[0060] In this embodiment of the invention, the resource flow system is equipped with risk level standards, which may include low risk level, medium risk level, and high risk level. When the risk score in the risk assessment result is 0 to 30, it hits the low risk level, indicating that the risk assessment is passed and the workflow continues. When the risk score in the risk assessment result is 31 to 70, it hits the medium risk level, and the task needs to be pushed to the manual workbench for manual review. When the risk score in the risk assessment result is 71 to 100, it hits the high risk level, and it needs to be intercepted and an alarm is generated to notify the risk control team.

[0061] Therefore, the resource flow system queries the target risk level matched by the risk assessment results. If the target risk level indicates low risk, it confirms that the risk assessment result also indicates low risk, avoiding missing the optimal execution opportunity due to an overly conservative interception strategy, and providing a safe foundation for subsequent path selection. For example, after a risk assessment, a health insurance cancellation order has a risk score of 20 points, which is considered low risk and allows it to enter the path selection stage.

[0062] S32: Obtain multiple candidate flow paths and obtain the path indicators corresponding to each candidate flow path.

[0063] In this embodiment of the invention, the resource transfer system acquires multiple candidate transfer paths, such as bank transfers and third-party payment channels. Each candidate transfer path is associated with multi-dimensional path indicators, such as resource consumption (handling fee rate, exchange rate difference), latency (predicted arrival time), and path risk (channel stability, compliance history). These path indicators are dynamically updated through historical transaction data and real-time monitoring to ensure that they reflect the current status of the channel. In practical applications, the path indicators corresponding to each candidate transfer path are shown in Table 3. Table 3

[0064] The path indicators shown in Table 3 include basic performance indicators such as transaction fee F(P) (actual transaction fee amount, in yuan) and arrival delay D(P) (estimated arrival time of funds, in hours or minutes), as well as key decision-making elements such as risk score R(P) (a comprehensive score integrating anti-fraud, anti-money laundering and compliance risks, ranging from 0 to 100 points), channel availability A(P) (0 / 1 indicates whether the channel is available), limit matching L(P) (0 / 1 judges whether the transaction limit is met), and timeliness compliance Treq(P) (0 / 1 verifies whether the timeliness requirement is met). The path indicators in Table 3 provide multi-dimensional data support for resource flow path selection by quantifying payment costs, efficiency, risks, and compliance. Among them, handling fees and arrival time directly affect resource consumption and user experience, risk dynamics integrate external regulatory requirements and internal risk control strategies, channel availability and limit matching constitute hard constraints, and timeliness guarantees business response speed. Together, they form a complete evaluation framework covering economy, security, compliance, and timeliness to ensure optimal path decision-making in insurance order resource flow.

[0065] In this way, collecting indicators from multiple paths provides data support for subsequent screening, and combining dynamic data avoids rigid path selection caused by static configuration. For example, the candidate paths for insurance cancellation orders include "bank transfer (0.5% handling fee, 2-hour delay)" and "third-party payment (1% handling fee, 10-minute delay)," and the advantages and disadvantages of both need to be comprehensively evaluated.

[0066] S33: Based on the preset hard constraints, evaluate the path indicators corresponding to each candidate flow path, filter out the candidate flow paths whose path indicators do not meet the hard constraints, and obtain multiple other candidate flow paths.

[0067] In this embodiment of the invention, the resource transfer system is equipped with preset hard constraints. Candidate transfer paths are pre-filtered based on the preset hard constraints to ensure that only paths that fully meet all mandatory requirements are retained for subsequent scoring.

[0068] In practical applications, other candidate transfer paths entering subsequent scoring must simultaneously meet three core hard constraints: Channel availability A(P) must be 1, meaning the payment channel is currently available and not disabled; Account limit matching L(P) must be 1, indicating that the transaction limit supported by the path fully covers the amount of the target insurance order, avoiding transfer failure due to insufficient limit; and Timeliness compliance Treq(P) must be 1, ensuring that the estimated arrival time of the path meets the timeliness requirements of the business scenario (e.g., insurance cancellation must be completed within T+1 days). Specifically, the resource transfer system will query the path indicators of each candidate transfer path in real time and verify these three indicators for each candidate transfer path item by item. If any indicator is not met (i.e., the corresponding function value is 0), the path will be immediately eliminated, preventing it from entering the weighted scoring stage of performance indicators such as resource consumption and latency.

[0069] This rigid filtering mechanism constructs a fundamental feasibility barrier for resource flow from three dimensions: channel availability, capital capacity, and business timeliness. It avoids execution risks caused by unavailable channels or insufficient limits, and prevents invalid paths from interfering with the selection of optimal solutions. This provides a high-quality candidate set for subsequent path optimization based on a cost-efficiency-risk balance. For example, in the candidate paths for a large insurance refund order, if a bank channel's L(P)=0 due to reaching its daily transaction limit, or a third-party payment channel's A(P)=0 due to system maintenance, the system will directly filter such paths, retaining only those paths that simultaneously meet the requirements of availability, sufficient limits, and timely delivery for the comprehensive scoring stage.

[0070] S34: Calculate the resource consumption score, delay score, and path risk score for each other candidate flow path, and perform a weighted calculation on the resource consumption score, delay score, and path risk score for each other candidate flow path to obtain the final path score corresponding to each other candidate flow path.

[0071] In this embodiment of the invention, the resource flow system performs multi-dimensional quantitative scoring on other candidate flow paths filtered by hard constraints, and unifies heterogeneous indicators such as resource consumption, latency, and path risk into comparable percentage values ​​through a dynamic range normalization method. Among these, the resource consumption score... The range can be calculated using the standardization formula shown in Formula 2 below, with values ​​ranging from 0 to 100: Formula 2:

[0072] Formula 2 can be used to calculate the actual handling fee. The index is mapped to "lower is better", where and This represents the fee boundary value for all candidate paths.

[0073] Delayed payment rating Timeliness can be quantified using the following formula 3, aiming for the quantified indicator to be as low as possible, with a value ranging from 0 to 100: Formula 3:

[0074] Among them, in formula 3 This indicates the estimated arrival time of funds via the specified path. and This represents the time-sensitive extreme value.

[0075] Risk Score The following formula (4) can be used to dynamically calculate and integrate risk dimensions such as anti-fraud and compliance to achieve a conversion of "the lower the value, the safer it is," with a value ranging from 0 to 100: Formula 4:

[0076] in, Indicates path risk, This represents the lowest risk value among all other candidate flow paths. This indicates the highest risk value among all other candidate flow paths.

[0077] Subsequently, the resource transfer system uses the following formula 5 to weight and calculate the resource consumption score, delay score, and path risk score of each other candidate transfer path to obtain the final path score: Formula 5:

[0078] In formula 5, Indicates the final score of the path. Indicates resource consumption score, This indicates the weight corresponding to the resource consumption score. Indicates delayed scoring. This indicates the weight corresponding to the delayed score. Indicates path risk score, This represents the weight corresponding to the path risk score. In practical applications, , , The sum of the values ​​is 1, and the weights can be determined by the business scenario. For example, large payments are weighted towards risk, while small, fast payments are weighted towards timeliness. See Table 4 below for details: Table 4

[0079] Table 4 shows the weights of resource consumption scores that are dynamically adjusted for different business scenarios. Weights corresponding to delayed scoring Weights corresponding to path risk scores The allocation strategy aims to achieve precise optimization of resource flow paths. In daily small-amount payment scenarios, the weight corresponding to the delay score (0.5) dominates, reflecting the priority demand for fast arrival, while balancing the weight corresponding to the resource consumption score (0.3) and the weight corresponding to the path risk score (0.2). In large-amount corporate payment scenarios, the weight corresponding to the path risk score is strengthened (0.5) to ensure the compliance of large-amount transactions, while balancing the weight corresponding to the resource consumption score (0.2) and the weight corresponding to the delay score (0.3). In emergency fund transfer scenarios, the weight corresponding to the delay score is increased to 0.6, highlighting the core demand for rapid fund response. In cross-border compliance sensitive transaction scenarios, the weight corresponding to the path risk score is significantly increased (0.7) to strictly respond to regulatory requirements such as regional sanctions, while the weights corresponding to the resource consumption score and delay score are reduced accordingly. All scenarios meet the constraint that the total weight is 1. Through the rule engine, the weight combination is dynamically adapted to flexibly match diverse business needs, such as emergency payments with priority timeliness and cross-border transactions with enhanced risk control, thereby accurately reflecting the scenario-based strategy orientation in the path score and improving the efficiency and security of resource flow.

[0080] In this way, through the above process, the final score of each path is calculated by weighting to balance cost efficiency and risk, which not only eliminates the difference in dimensions but also reflects the strategy preference, providing an accurate decision-making basis for the selection of the optimal path.

[0081] S35: Select the candidate path with the lowest final score from among multiple other candidate paths as the optimal resource transfer path.

[0082] In this embodiment of the invention, the resource transfer system arranges candidate paths in ascending order according to the final score of the path, and selects the path with the lowest score as the optimal solution. This path achieves the optimal balance among cost, timeliness, and risk, ensuring that resource transfer is both economical and efficient as well as safe and reliable. It realizes the dynamic adaptation of resource transfer strategy and improves the efficiency of fund use and the certainty of fund receipt.

[0083] For example, the system selects the bank transfer route with a comprehensive score of 79.5 as the optimal solution because its overall cost-effectiveness is higher than that of third-party payment routes and it meets the user's preference for low cost.

[0084] S36: Obtain the preset order security verification rules, perform final security verification on the target insurance order in accordance with the order security verification rules, and if the target insurance order passes the final security verification, call the resource transfer interface and execute the resource transfer operation according to the optimal resource transfer path.

[0085] In this embodiment of the invention, after determining the optimal resource transfer path, the resource transfer system initiates a triple security execution verification mechanism as the final risk control barrier for transaction execution. Specifically, the resource transfer system first calls the order analysis model indicated by the order security verification rules to calculate the resource quantity of the target insurance order, obtaining the model-estimated resource quantity. If the model-estimated resource quantity is the same as the resource quantity to be transferred indicated by the target insurance order, the system matches the order user information of the target insurance order and verifies the authenticity of the order user information to complete the final security verification of the target insurance order. If the order user information passes the authenticity verification, the resource transfer system determines that the target insurance order has passed the final security verification, generates an operation log for this verification process, and stores the operation log. If the order user information fails the authenticity verification, the system determines that the target insurance order has failed the final security verification.

[0086] In practical applications, the resource transfer system can perform consistency checks on the amount based on the verification rules configured in the rule repository. It compares the user-confirmed payment amount with the final amount output by the intelligent order analysis model in real time (including handling fees, exchange rates, and the actual execution amount after path optimization). If any discrepancy exists, a blocking mechanism is immediately triggered to prevent financial losses caused by data tampering or calculation anomalies. At the same time, it ensures the authenticity of accounts through dual verification. On the one hand, it connects to authoritative databases such as identity authentication to verify the authenticity and timeliness of the account's real-name information. On the other hand, it combines enhanced verification methods such as biometrics or dynamic tokens (as required by the rule engine configuration) to eliminate the risk of fake or impersonated accounts. During this process, the resource transfer system generates encrypted operation logs for key nodes throughout the entire process, such as path confirmation, amount verification, and authorization operations, and persists them for evidence storage. This ensures that the entire transaction process is auditable, traceable, and non-repudiable, meeting financial-grade compliance and regulatory requirements. Only when the triple verification of amount, account, and logs passes will the system call the payment interface to execute resource transfer according to the optimal path, achieving dual protection of security and efficiency.

[0087] It should be noted that when the resource transfer system determines that a target insurance order has failed the final security verification, it will generate a review work order for the target insurance order, assign a work order level label to the review work order, determine the reviewer skill label that matches the work order level label, select a target reviewer based on the reviewer skill label, and push the review work order to the target reviewer for review. In other words, after completing security verification and payment execution, the resource transfer system achieves full-chain transparency and risk controllability of payment results through a closed-loop feedback mechanism, building a two-way trust system between users and institutions. In successful scenarios, the resource transfer system, based on an event-driven architecture, triggers multi-channel notification services in real time. Through an asynchronous message queue, it pushes payment success events to the App push service and SMS gateway, ensuring users receive immediate notifications including transaction amount, fee details, and optimized path indicators (e.g., "Your health insurance refund of 10,000 yuan has been transferred through the [Bank Preferred Channel], expected to arrive within 2 hours, with a 5 yuan fee discount"). This detailed feedback not only enhances users' awareness of fund flow but also increases system trust by showcasing path optimization results. Simultaneously, the resource transfer system dynamically adjusts the arrival time based on the estimated latency score during the path selection phase and the current real-time channel congestion status, utilizing distributed caching to update the estimated timeliness in user sessions, achieving dynamic expectation management.

[0088] When verification fails or risk control rules are triggered, the resource flow system immediately activates an early warning and isolation mechanism: based on the risk thresholds preset in the rule engine (such as transaction amount exceeding 300% of the user's historical behavior baseline, or indirect association between the payee and a blacklisted account), it automatically generates an audit work order with a risk tag, and allocates processing resources according to a "risk level - skill tag" matrix through the intelligent routing engine. For example, low-risk work orders are routed to ordinary customer service, while high-risk work orders are prioritized and assigned to certified risk control experts. It also supports prioritizing urgent work orders by marking them as priority. The entire work order processing process can use blockchain notarization or audit log encryption storage technology to record all elements of information such as dispatch timestamp, processor's digital signature, rule version number, and handling actions, ensuring that any operation meets financial-grade traceability requirements. If a work order is not closed within 24 hours, the resource flow system automatically triggers an escalation mechanism, notifies the superior supervisor, and marks the timeout risk.

[0089] In addition, during practical application, a dual-channel approach is uniformly adopted for feedback. Regardless of whether the review is approved or rejected, structured feedback is simultaneously pushed through the App's message center and SMS: Successful scenarios display detailed breakdown of funds and the final arrival time (e.g., "Funds have been transferred out through the [Compliant Low-Risk Channel], with actual arrival of 9980 yuan after deducting handling fees, expected to be completed before 14:30"); Failed scenarios clearly indicate the rule hit (e.g., "Transaction blocked due to the payee's regional risk score exceeding the threshold"), the associated risk type, the manual review entry, and the appeal material submission path. For example, a cross-border insurance claim triggered an alert because the payee was located in a high-risk country list. The work order was marked as "High Risk - Cross-border Compliance" and assigned to an expert. After manual verification to eliminate the risk, the resource flow system pushed feedback: "After review, the payee's compliance has passed enhanced due diligence, and the funds will be re-executed, with an expected delay of 45 minutes." This ensures security while reducing user anxiety through a transparent handling process, forming a complete risk control closed loop of "alert-handling-feedback-improvement".

[0090] In summary, the logical process of the technical solution proposed in this invention is summarized as follows: See Figure 6 When the payment center receives a payment request triggered by counter, online, or asynchronous business tasks, it first performs intelligent identification of the insurance business scenario. If identification fails, it triggers manual review and risk control warning. If identification is successful, it enters the configuration-based dynamic amount verification stage based on the rule engine. If verification fails, it also transfers to manual review. If verification is successful, it further judges whether the amount fluctuation exceeds 5%. If it exceeds the limit, it triggers manual review intervention. Otherwise, it assesses the risk through a multi-dimensional risk scoring model. When the risk score exceeds 80 points, it forces the manual review process. If it does not exceed the threshold, it calls the optimal transfer path planning algorithm to select multiple paths. Then, it starts a security execution verification mechanism to implement triple verification (amount consistency, account authenticity, and operation log storage). After verification, it executes resource transfer operations and provides feedback on the results (if successful, it notifies the user to complete the transfer; if it fails, it refuses to execute and pushes a review work order). Any failure in the review at any stage will be pushed to the manual handling process through a work order, forming a closed-loop control system of "intelligent identification - dynamic verification - risk decision - path optimization - security verification - result feedback".

[0091] The method provided in this application, targeting resource transfer in insurance business, dynamically integrates user behavior data and external environment data related to insurance orders by identifying the business scenario of the insurance order. This ensures real-time perception of changes in user behavior and the external environment of the policy, and incorporates these perceived changes into the resource transfer process. This enhances the flexibility of the resource transfer strategy, allowing for flexible adjustments based on actual conditions. While avoiding missing the optimal execution opportunity for resource transfer and improving resource utilization efficiency, the method also achieves proactive risk identification through multiple risk assessments, reducing the frequency of issues such as uncertain arrival times and opaque reasons for failure, thereby further improving the success rate and security of resource transfer.

[0092] Furthermore, as Figure 1 In a specific implementation of the method, this application provides a resource transfer device based on insurance business decisions, such as... Figure 7 As shown, the device includes: a generation module 701, an evaluation module 702, and a transfer module 703.

[0093] The generation module 701 is used to respond to a resource transfer request, obtain the target insurance order to be executed for resource transfer operation, and generate a scenario state vector by combining the target insurance order and the business scenario in which the target insurance order is located. The evaluation module 702 is used to verify the resource quantity of the target insurance order using preset resource verification rules. If the verification is successful, a multi-dimensional risk assessment is performed on the scenario state vector to generate a risk assessment result. The resource transfer module 703 is used to determine the optimal resource transfer path when the risk assessment result indicates low risk, and to perform resource transfer operations using the optimal resource transfer path when the target insurance order is determined to have passed the final security verification.

[0094] In a specific application scenario, the generation module 701 is used to, upon receiving the resource transfer request, determine the target insurance order based on the order identifier carried in the resource transfer request; obtain the basic policy information of the target insurance order, and obtain the basic scenario information of the target insurance order based on the business scenario in which the target insurance order is located; perform field splitting on the basic policy information and the basic scenario information to obtain multiple basic information fields, wherein the multiple basic information fields include a policy type field, a policy stage field, a policy time field, a policy user behavior field, and a policy environment field; construct a multi-dimensional state vector using the multiple basic information fields, and use the multi-dimensional state vector as the scenario state vector.

[0095] In a specific application scenario, the evaluation module 702 is used to extract the scenario identifier of the business scenario, query the preset resource verification rules associated with the scenario identifier; extract at least one resource quantity information related to the resource quantity from the target insurance order, and call the rule engine to verify the at least one resource quantity information according to the resource verification rules. The verification of the at least one resource quantity information includes verifying whether each resource quantity information exceeds the resource quantity range set by the resource verification rules for it; and if the verification determines that none of the resource quantity information exceeds the resource quantity range set by the resource verification rules for it... In this case, it is determined that the target insurance order passes the resource quantity verification; a preset multi-dimensional risk assessment strategy is determined, and multiple vector scores are calculated for the scenario state vector according to the multi-dimensional risk assessment strategy, and the multiple vector scores are integrated to obtain a risk score, which is used as the risk assessment result; wherein, if the verification determines that at least one of the resource quantity information exceeds the resource quantity range set by the resource verification rule for it, it is determined that the target insurance order fails the resource quantity verification, a resource flow warning message is generated, and the resource flow warning message is pushed to a preset information recipient.

[0096] In a specific application scenario, the evaluation module 702 is used to extract a policy user behavior field from the scenario state vector, and calculate a score for the policy user behavior field according to the multi-dimensional risk assessment strategy to obtain a user credit score and a user behavior score; extract a policy environment field from the scenario state vector, and calculate a score for the policy environment field according to the multi-dimensional risk assessment strategy to obtain a policy compliance score; extract multiple risk factors from the multi-dimensional risk assessment strategy, evaluate the factor score corresponding to each risk factor in the scenario state vector to obtain multiple factor scores, and perform a weighted calculation on the multiple factor scores according to the factor weight corresponding to each risk factor in the multi-dimensional risk assessment strategy, and use the calculated result as a resource flow risk score; query the score weights corresponding to the user credit score, the user behavior score, the policy compliance score, and the resource flow risk score in the multi-dimensional risk assessment strategy, and use the queried score weights to perform a weighted calculation on the user credit score, the user behavior score, the policy compliance score, and the resource flow risk score, and use the calculated result as the risk score.

[0097] In a specific application scenario, the workflow module 703 is used to query the target risk level matched by the risk assessment result, and if the target risk level indicates low risk, determine that the risk assessment result indicates low risk; obtain multiple candidate workflow paths and obtain the path indicators corresponding to each candidate workflow path; evaluate the path indicators corresponding to each candidate workflow path according to preset hard constraints, filter out candidate workflow paths whose path indicators do not meet the hard constraints, and obtain multiple other candidate workflow paths; calculate the resource consumption score and latency score of each other candidate workflow path. The system performs a path risk score and a weighted calculation of the resource consumption score, delay score, and path risk score for each of the other candidate transfer paths to obtain the final path score for each of the other candidate transfer paths. It then selects the candidate transfer path with the lowest final path score from among the multiple other candidate transfer paths as the optimal resource transfer path. Finally, it obtains preset order security verification rules, performs a final security verification on the target insurance order according to these rules, and, if the target insurance order passes the final security verification, calls the resource transfer interface to execute the resource transfer operation according to the optimal resource transfer path.

[0098] In a specific application scenario, the transfer module 703 is used to call the order analysis model indicated by the order security verification rules to calculate the resource quantity of the target insurance order and obtain the model-evaluated resource quantity. If the model-evaluated resource quantity is the same as the transfer resource quantity indicated by the target insurance order, the order user information of the target insurance order is matched, and the authenticity of the order user information is verified to complete the final security verification of the target insurance order. Specifically, if the order user information passes the authenticity verification, the target insurance order is determined to have passed the final security verification, an operation log is generated for this verification process, and the operation log is stored. If the order user information fails the authenticity verification, the target insurance order is determined to have failed the final security verification.

[0099] In specific application scenarios, the device further includes: The push module is used to generate an audit work order for the target insurance order when it is determined that the target insurance order has failed the final security verification, set a work order level tag for the audit work order, determine the audit personnel skill tag that matches the work order level tag, select a target audit personnel based on the audit personnel skill tag, and push the audit work order to the target audit personnel for work order review.

[0100] The apparatus provided in this application, targeting resource transfer in insurance business, dynamically integrates user behavior data and external environment data related to insurance orders by identifying the business scenario of the insurance order. This ensures real-time perception of changes in user behavior and the external environment of the policy, and incorporates these perceived changes into the resource transfer process. This enhances the flexibility of the resource transfer strategy, allowing for flexible adjustments based on actual conditions. While avoiding missing the optimal execution opportunity for resource transfer and improving resource utilization efficiency, it also achieves proactive risk identification through multiple risk assessments, reducing the frequency of issues such as uncertain arrival times and opaque reasons for failure, further improving the success rate and security of resource transfer.

[0101] Specific limitations regarding the resource transfer device based on insurance business decisions can be found in the limitations of the resource transfer method based on insurance business decisions mentioned above, and will not be repeated here. Each module in the aforementioned resource transfer device based on insurance business decisions 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 the electronic device in hardware form, or stored in the memory of the electronic device in software form, so that the processor can call and execute the operations corresponding to each module.

[0102] In one embodiment, an electronic device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 8 As shown, the electronic 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 the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs stored 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 server-side functions or steps of a resource transfer method based on insurance business decisions.

[0103] In one embodiment, an electronic device is provided, which may be a client, and its internal structure diagram may be as follows: Figure 9As shown, the electronic device includes a processor, memory, network interface, display screen, and input devices 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 the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored 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 client-side functions or steps of a resource transfer method based on insurance business decisions.

[0104] In one embodiment, an electronic 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: In response to a resource transfer request, the target insurance order for which the resource transfer operation is to be performed is obtained, and a scenario state vector is generated by combining the target insurance order and the business scenario in which the target insurance order is located. The target insurance order is verified for resources using preset resource verification rules. If the verification is successful, a multi-dimensional risk assessment is performed on the scenario state vector to generate a risk assessment result. If the risk assessment results indicate low risk, the optimal resource transfer path is determined, and if the target insurance order passes the final security check, the resource transfer operation is performed using the optimal resource transfer path.

[0105] In one embodiment, a storage medium is provided having a computer program stored thereon, which, when executed by a processor, performs the following steps: In response to a resource transfer request, the target insurance order for which the resource transfer operation is to be performed is obtained, and a scenario state vector is generated by combining the target insurance order and the business scenario in which the target insurance order is located. The target insurance order is verified for resources using preset resource verification rules. If the verification is successful, a multi-dimensional risk assessment is performed on the scenario state vector to generate a risk assessment result. If the risk assessment results indicate low risk, the optimal resource transfer path is determined, and if the target insurance order passes the final security check, the resource transfer operation is performed using the optimal resource transfer path.

[0106] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or electronic 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.

[0107] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this invention are all information and data authorized by the user or fully authorized by all parties.

[0108] 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.

[0109] 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.

[0110] 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 resource transfer method based on insurance business decision-making, characterized in that, include: In response to a resource transfer request, the target insurance order for which the resource transfer operation is to be performed is obtained, and a scenario state vector is generated by combining the target insurance order and the business scenario in which the target insurance order is located. The target insurance order is verified for resources using preset resource verification rules. If the verification is successful, a multi-dimensional risk assessment is performed on the scenario state vector to generate a risk assessment result. If the risk assessment results indicate low risk, the optimal resource transfer path is determined, and if the target insurance order passes the final security check, the resource transfer operation is performed using the optimal resource transfer path.

2. The method according to claim 1, characterized in that, In response to a resource transfer request, the system obtains the target insurance order for which the resource transfer operation is to be performed, and generates a scenario state vector by combining the target insurance order and the business scenario in which the target insurance order is located, including: When the resource transfer request is received, the target insurance order is determined based on the order identifier carried in the resource transfer request; Obtain the basic policy information of the target insurance order, and obtain the basic scenario information of the target insurance order based on the business scenario in which the target insurance order is located; The basic policy information and the basic scenario information are split into multiple basic information fields, including policy type field, policy stage field, policy time field, policy user behavior field, and policy environment field. A multidimensional state vector is constructed using the aforementioned multiple basic information fields, and the multidimensional state vector is used as the scene state vector.

3. The method according to claim 1, characterized in that, The method employs preset resource verification rules to verify the resource quantity of the target insurance order. If the verification passes, a multi-dimensional risk assessment is performed on the scenario state vector to generate a risk assessment result, including: Extract the scenario identifier of the business scenario, and query the preset resource verification rules associated with the scenario identifier; Extract at least one resource quantity information related to the resource quantity from the target insurance order, and call the rule engine to verify the at least one resource quantity information according to the resource verification rule. The verification of the at least one resource quantity information includes verifying whether each resource quantity information exceeds the resource quantity range set by the resource verification rule for it. If the verification confirms that none of the resource quantity information exceeds the resource quantity range set by the resource verification rule, the target insurance order is determined to have passed the resource quantity verification. A preset multidimensional risk assessment strategy is determined. According to the multidimensional risk assessment strategy, multiple vector scores are calculated for the scenario state vector. The multiple vector scores are integrated to obtain a risk score, and the risk score is used as the risk assessment result. Specifically, if the verification determines that one of the resource quantity information exceeds the resource quantity range set by the resource verification rule, the target insurance order is determined to have failed the resource quantity verification, a resource flow warning message is generated, and the resource flow warning message is pushed to a preset information recipient.

4. The method according to claim 3, characterized in that, The process of calculating multiple vector scores for the scenario state vector according to the multidimensional risk assessment strategy, and integrating the multiple vector scores to obtain a risk score, includes: Extract policy user behavior fields from the scenario state vector, and score the policy user behavior fields according to the multi-dimensional risk assessment strategy to obtain user credit score and user behavior score. Extract the policy environment field from the scenario state vector, and score the policy environment field according to the multi-dimensional risk assessment strategy to obtain the policy compliance score; Multiple risk factors are extracted from the multidimensional risk assessment strategy, the factor score corresponding to each risk factor of the scenario state vector is evaluated to obtain multiple factor scores, and the multiple factor scores are weighted according to the factor weight corresponding to each risk factor in the multidimensional risk assessment strategy. The calculated result is used as the resource flow risk score. The user credit score, user behavior score, policy compliance score, and resource transfer risk score are each queried for their corresponding weights in the multidimensional risk assessment strategy. Using the queried weights, the user credit score, user behavior score, policy compliance score, and resource transfer risk score are weighted and calculated. The calculated result is used as the risk score.

5. The method according to claim 1, characterized in that, The process of determining the optimal resource transfer path when the risk assessment result indicates low risk, and executing the resource transfer operation using the optimal resource transfer path when the target insurance order passes the final security verification, includes: Query the target risk level matched by the risk assessment result, and if the target risk level indicates low risk, determine that the risk assessment result indicates low risk; Obtain multiple candidate flow paths, and obtain the path index corresponding to each candidate flow path; Based on preset hard constraints, the path indicators corresponding to each candidate flow path are evaluated, and the candidate flow paths whose path indicators do not meet the hard constraints are filtered out to obtain multiple other candidate flow paths. Calculate the resource consumption score, delay score, and path risk score for each of the other candidate flow paths, and perform a weighted calculation on the resource consumption score, delay score, and path risk score for each of the other candidate flow paths to obtain the final path score corresponding to each of the other candidate flow paths; Among the multiple other candidate resource transfer paths, the candidate transfer path with the lowest final score is selected as the optimal resource transfer path. Obtain the preset order security verification rules, perform a final security verification on the target insurance order in accordance with the order security verification rules, and if it is determined that the target insurance order passes the final security verification, call the resource transfer interface and execute the resource transfer operation according to the optimal resource transfer path.

6. The method according to claim 5, characterized in that, The final security verification of the target insurance order, referring to the order security verification rules, includes: The order analysis model indicated by the order security verification rule is invoked to calculate the resource quantity of the target insurance order, and the model-estimated resource quantity is obtained. If the amount of resources evaluated by the model is the same as the amount of resources to be transferred indicated by the target insurance order, the order user information of the target insurance order is matched, and the authenticity of the order user information is verified to complete the final security verification of the target insurance order. Specifically, if the order user information passes the authenticity verification, the target insurance order passes the final security verification. An operation log is generated for this verification process and stored. If the order user information fails the authenticity verification, the target insurance order fails the final security verification.

7. The method according to claim 1, characterized in that, The method further includes: If it is determined that the target insurance order has failed the final security check, an audit work order is generated for the target insurance order, and a work order level label is set for the audit work order. Determine the reviewer skill tag that matches the work order level tag, select the target reviewer based on the reviewer skill tag, and push the review work order to the target reviewer for work order review.

8. A resource transfer device based on insurance business decision-making, characterized in that, include: The generation module is used to respond to resource transfer requests, obtain the target insurance order to be executed for resource transfer operations, and generate a scenario state vector by combining the target insurance order and the business scenario in which the target insurance order is located. The evaluation module is used to verify the resource quantity of the target insurance order using preset resource verification rules. If the verification is successful, a multi-dimensional risk assessment is performed on the scenario state vector to generate a risk assessment result. The resource transfer module is used to determine the optimal resource transfer path when the risk assessment result indicates low risk, and to perform resource transfer operations using the optimal resource transfer path when the target insurance order passes the final security verification.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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