Insurance channel data sharing and benefit transparent distribution coordination system

Abstract

The present application relates to the technical field of insurance data processing, in particular to an insurance channel data sharing and benefit transparent distribution collaborative system, comprising a data acquisition module, a verification and chain module, a contribution calculation module and an intelligent distribution module. The data acquisition module collects customer reach records, sales process records and premium payment result records of each insurance sales channel through multiple consensus nodes of a blockchain network; the verification and chain module cross- verifies and time-stamps the original data, generates a channel contribution event sequence with consistency proof, and stores it in a blockchain distributed ledger; the contribution calculation module uses an improved contribution quantification algorithm, combines event type weight and time decay factor, and calculates the quantitative contribution value of each channel; the intelligent distribution module automatically generates an initial benefit distribution scheme for each channel according to the quantitative contribution value and the smart contract rules. The system can realize the trusted sharing of insurance channel data, and make the benefit distribution consistent with the actual channel contribution.

Description

Technical Field

[0001] This invention relates to the field of insurance data processing technology, and in particular to a collaborative system for data sharing and transparent distribution of benefits across insurance channels. Background Technology

[0002] In the insurance industry's multi-channel collaborative operation scenarios, channel behavior data generally adopts a centralized collection model. Customer outreach, sales process execution, and premium payment information are centrally collected by a single platform, and data verification relies on internal audit mechanisms. Channel contribution assessment often relies on manual statistics or fixed-ratio calculations, and profit distribution is calculated according to preset proportions. Data from each channel is stored independently, lacking a unified and reliable carrier for information exchange. Original behavior records are susceptible to tampering and falsification, the timeline of behavior cannot be effectively solidified, and inter-channel data verification lacks an immutable reference, making it difficult for the authenticity and completeness of the data to be mutually recognized by all parties.

[0003] The channel contribution calculation model is overly simplified, only breaking down the overall transaction results for calculation, failing to adequately differentiate the contributions of different behavioral events throughout the sales process. The impact of the sequence of events on contribution levels is not incorporated into the calculation system, and time decay factors are not reflected in the algorithm, leading to discrepancies between actual channel participation and the calculated results. The profit distribution process lacks transparent execution logic, and the basis for distribution cannot be fully traced. The existing system architecture and processing logic cannot meet the needs of cross-validating and time-sequentially solidifying channel behavior data using blockchain multi-consensus nodes, constructing a reliable channel contribution event sequence, and introducing event type weights and time decay factors to achieve refined contribution quantification. Consequently, reliable data sharing and accurate profit distribution cannot be achieved simultaneously. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by proposing a collaborative system for data sharing and transparent distribution of benefits in insurance channels.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a collaborative system for data sharing and transparent profit distribution in insurance channels, comprising: The data acquisition module is used to collect raw channel behavior data from different insurance sales channels through multiple consensus nodes in the blockchain network. The raw channel behavior data includes at least customer contact records, sales process records, and premium payment result records. The on-chain verification module is used to cross-validate and timestamp the original data of the channel behavior using the consensus node, generate a channel contribution event sequence with a consistency proof, and record the channel contribution event sequence in the distributed ledger of the blockchain network. The contribution calculation module is used to calculate the quantitative contribution value of each insurance sales channel in a single or multiple policy transactions based on the channel contribution event sequence stored in the distributed ledger, using an improved contribution quantification algorithm. The improved contribution quantification algorithm is calculated based on the type weight and time decay factor of each event in the channel contribution event sequence. The intelligent allocation module is used to automatically calculate and generate an initial profit allocation scheme for each channel on the blockchain network based on the quantitative contribution value of each insurance sales channel and the profit allocation rules pre-set in the smart contract.

[0006] As a further aspect of the present invention, the consensus node is used to cross-validate and timestamp the original channel behavior data to generate a channel contribution event sequence with a consistency proof, including: Each consensus node receives raw data on channel behavior uploaded by one or more insurance sales channel nodes associated with it; By comparing the raw data uploaded by different insurance sales channel nodes involved in the same policy transaction, we can identify differences in the description of the same operation or event. For operations or events with discrepancies in description, the system calls the preset business rule base and the historical arbitration case base to perform logical arbitration on the discrepancies and form a universally recognized and unique event description. The original channel behavior data, after being processed for differences, is sorted according to the business process timeline of the policy transaction; Generate a cryptographic hash value for each event in the sorted event stream, and associate the cryptographic hash value with the hash value of the previous event; The associated hash value chain, event occurrence time, and participating node identity identifiers are packaged together to form an immutable data block. After consensus by all consensus nodes, this block is written into the distributed ledger, thereby completing the generation of the channel contribution event sequence.

[0007] As a further aspect of the present invention, the improved contribution metric algorithm is calculated based on the type weight and time decay factor of each event in the channel contribution event sequence, including: Read the channel contribution event sequence from the distributed ledger, and extract the attributes of each event in the sequence. The attributes include at least the event type code, the timestamp of the event occurrence, and the unique identifier of the channel initiating the event. Based on the preset event type-contribution weight mapping table, query the static contribution weight value corresponding to each event type code; For each event, its time decay factor is calculated. The calculation method is as follows: obtain the time difference between the timestamp of the event and the timestamp of the final underwriting of the policy, substitute the time difference into the negative exponential decay function for calculation, and obtain the time decay coefficient of the event. The actual contribution weight of an event is obtained by multiplying the static contribution weight value of each event by the corresponding time decay coefficient. The actual contribution weights of all events belonging to the same insurance sales channel are summed, and the sum is the quantitative contribution value of the insurance sales channel for the single or multiple policy transactions. For policy transactions completed through cross-channel collaboration, the quantitative contribution values ​​of all participating channels are normalized to ensure that the sum of the contribution values ​​of all channels is a fixed constant.

[0008] As a further aspect of the present invention, the actual contribution weight of the event is obtained by multiplying the static contribution weight value of each event by the corresponding time decay coefficient, including: Obtain the solidified channel contribution event sequence from the distributed ledger, and parse out the event type code and the first timestamp of the event occurrence from it; Based on the event type code, query the event type-contribution weight mapping table pre-set in the blockchain network to obtain the static contribution weight value bound to the event type code; Obtain the underwriting completion timestamp of the policy transaction associated with the event to be calculated from the distributed ledger, and use it as the second timestamp for calculating time decay; Calculate the absolute time difference between the first timestamp and the second timestamp, and convert the absolute time difference into a standardized time interval measured in a preset time unit; The standardized time interval is used as an input variable and substituted into a predefined negative exponential decay function to calculate the time decay coefficient, wherein the expression of the negative exponential decay function is configured such that the coefficient value is negatively correlated with the standardized time interval. Within the consensus node of the blockchain network, a multiplication operation logic is executed to multiply the static contribution weight value by the calculated time decay coefficient. The result of multiplication is used as the actual contribution weight of the event, and the event is encapsulated with a unique identifier and stored back in the extended attribute field corresponding to the event in the distributed ledger.

[0009] As a further aspect of the present invention, based on the quantified contribution value of each insurance sales channel and the profit distribution rules pre-set in the smart contract, an initial profit distribution scheme for each channel is automatically calculated and generated on the blockchain network, including: Read the total distributable benefit amount of the current policy transaction from the state database of the blockchain network; The smart contract for profit distribution deployed on the blockchain network is invoked. The smart contract for profit distribution encodes a tiered distribution ratio function corresponding to different product types and different channel levels. The total distributable profit amount, the quantitative contribution value of each insurance sales channel, and the channel's level identifier are used as input parameters and passed into the profit distribution smart contract. The profit distribution smart contract calculates the absolute value of the profit share that each channel should receive based on its internal logic. The calculation process follows the principle that channels with higher quantitative contribution values ​​should receive a higher proportion, and the proportion calculation conforms to the principle of a preset ladder function. The calculated absolute values ​​of the profit share of each channel, the quantitative contribution values ​​on which the calculation is based, and the allocation ratio are collectively packaged into a structured allocation record to form the initial profit allocation scheme. The initial profit distribution plan is temporarily stored in the pending transaction pool of the blockchain network in the form of a pre-written log, and a unique digest hash of the initial profit distribution plan is generated.

[0010] As a further aspect of the present invention, the system further includes: The consensus confirmation module is used to trigger a preset multi-party confirmation process after the initial benefit distribution plan is generated, and to push the initial benefit distribution plan to the relevant insurance institution nodes and insurance sales channel nodes for joint confirmation. An automatic execution module is used to automatically execute the initial benefit distribution plan by the blockchain network after the joint signature confirmation is completed, transferring the corresponding share of digital assets from the insurance institution's locked account to the designated settlement account of each insurance sales channel.

[0011] As a further aspect of the present invention, after the initial profit distribution plan is generated, a preset multi-party confirmation process is triggered to push the initial profit distribution plan to relevant insurance institution nodes and insurance sales channel nodes for joint confirmation, including: When a new initial benefit distribution scheme is detected in the unconfirmed transaction pool, the coordination service component of the blockchain network generates a set of corresponding digital confirmation requests based on the insurance institution node identifier and insurance sales channel node identifier involved in the scheme. Through the message routing service of the blockchain network, the digital confirmation request, along with the digest hash and full content copy of the initial benefit distribution scheme, is pushed to the client interfaces of the relevant insurance institution nodes and insurance sales channel nodes, respectively. Each node's client interface displays the complete content of the initial profit distribution plan locally and launches a confirmation timer window with a preset validity period; Within the confirmation time window, the relevant nodes need to use their private keys to digitally sign the digest hash of the initial benefit distribution scheme, and return the signature result as a confirmation receipt to the coordination service component of the blockchain network. The coordination service component collects the digital signatures of all relevant nodes and verifies the validity of the signatures. The initial benefit distribution scheme is deemed to have been jointly confirmed only when all the required signatures have been effectively collected and verified.

[0012] As a further aspect of the present invention, once the joint signature confirmation is completed, the blockchain network automatically executes the initial profit distribution plan, transferring the corresponding share of digital assets from the insurance institution's locked account to the designated settlement account of each insurance sales channel, including: After the initial profit distribution plan is jointly confirmed, the consensus nodes of the blockchain network automatically extract the execution instructions corresponding to the initial profit distribution plan from the pending transaction pool; According to the execution instruction, the digital assets corresponding to the total distributable benefit amount recorded in the initial benefit distribution plan that should be paid by the insurance institution are locked and transferred from the insurance institution's locked account to the temporary custody contract address of the blockchain network. The smart contract generates a series of parallel fund transfer transactions according to the profit share of each channel recorded in the initial profit distribution plan. At the preset execution time or when the preset execution conditions are met, the smart contract atomically executes all fund transfer transactions, transferring the amount of digital assets from the temporary escrow contract address to the designated settlement accounts of each insurance sales channel. After each successful fund transfer transaction, a corresponding fund settlement record is generated in the distributed ledger. The fund settlement record includes the transferring account, the receiving account, the amount, the timestamp, and the associated policy transaction number. Once all fund transfer transactions have been completed, the smart contract records the final completion status of the initial profit distribution plan in the distributed ledger.

[0013] As a further aspect of the present invention, the system further includes a weight adjustment module for performing channel data contribution quality assessment and dynamic weight adjustment, including: After the preset evaluation period ends, the channel contribution event sequence of all records within the evaluation period is extracted from the distributed ledger; Statistical analysis was performed on the extracted channel contribution event sequences to calculate the total number of contribution events for each insurance sales channel, the number of valid insurance policies involved, and the frequency of the contribution events being cited in subsequent claims verification. Based on the statistical analysis results, the evaluation indicators for each insurance sales channel were calculated in three dimensions: data accuracy, data value density, and collaborative integrity during the evaluation period. The three evaluation indicators, namely data accuracy, data value density and collaborative integrity, are input into a preset dynamic weight adjustment model. The dynamic weight adjustment model outputs the adjustment coefficient of the static contribution weight value of the insurance sales channel in the event type-contribution weight mapping table in the next evaluation period. Using the adjustment coefficient, update the static contribution weight values ​​of various events belonging to the insurance sales channel in the event type-contribution weight mapping table; The updated static contribution weight values ​​are synchronized to all consensus nodes for use in the calculation of the improved contribution metric algorithm in the next evaluation cycle.

[0014] As a further aspect of the present invention, the step of statistically analyzing the extracted channel contribution event sequences to calculate the total number of contribution events for each insurance sales channel, the number of valid policies involved, and the frequency with which the contribution events are cited in subsequent claims verification includes: For an evaluation period, the distributed ledger is scanned to filter out all events contributed by the event initiator to a specific insurance sales channel; The selected events are counted to obtain the total number of events contributing to the specific insurance sales channel; From the selected events, extract the unique policy transaction number, deduplicate the policy transaction number, and count the number of valid policies involved in the specific insurance sales channel; In the distributed ledger, query the records of claims verification requests initiated within the assessment period, and in each claims verification request record, parse out the unique hash identifier of the channel contribution event referenced as verification evidence; The parsed hash identifier is matched with the hash identifiers of all events contributed by the specific insurance sales channel in this period, and the number of successful matches is counted. The number of successful matches is the frequency with which the contributed event is referenced in subsequent claims verification.

[0015] Compared with the prior art, the advantages and positive effects of the present invention are as follows: By collecting customer outreach records, sales process logs, and premium payment results from different insurance sales channels through multiple consensus nodes in the blockchain network, the raw data on channel behavior can be cross-verified by multiple parties and time-stamped for solidification, forming a sequence of channel contribution events with a proof of consistency. This sequence of events is recorded in the blockchain distributed ledger, and the data content has multi-party confirmation characteristics. The record state can remain stable in the long term, and no single participant can tamper with or delete the information on the chain. The generation, verification, and storage of channel behavior data all leave complete temporal traces. All participants have a unified and non-repudiable reference standard when reviewing and verifying data, and information deviations and trust disagreements during data interaction can be effectively mitigated.

[0016] Based on the channel contribution event sequence stored in the distributed ledger, an improved contribution quantification algorithm is used, combining event type weights and time decay factors, to calculate the quantitative contribution value of each insurance sales channel in a single or multiple policy transactions. The differences in the impact of different types of channel behavior on transaction completion can be clearly distinguished, and the influence of the timing of behavior can be reasonably reflected through the time decay factor. The calculation results closely match the actual participation level of the channels. An initial profit distribution plan is automatically generated based on pre-set rules in smart contracts and the quantitative contribution values. The distribution logic is fully transparent and traceable, the calculation process is free from human intervention, and the distribution results directly correspond to the actual contributions of the channels. The distribution execution process is consistent and objective, and the share received by each channel matches its actual contribution. Attached Figure Description

[0017] Figure 1 This is a sequence diagram of the collaborative system for data sharing and transparent profit distribution in the insurance channel as described in this invention; Figure 2 A flowchart illustrating the process of contributing event sequence generation to the channel; Figure 3 A flowchart illustrating the computational process for improving the contribution metric. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0019] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0020] See Figure 1 This invention provides a collaborative system for data sharing and transparent profit distribution in insurance channels. The specific system includes: The data acquisition module collects raw channel behavior data from various insurance sales channel nodes connected to the blockchain network through multiple consensus nodes. This raw channel behavior data must include at least customer contact records, a complete sales process record, and premium payment result records. Next, the verification and on-chain module is activated. This module uses the consensus nodes in the blockchain network to cross-validate and timestamp the collected raw channel behavior data, generating a channel contribution event sequence with a consistency proof, and permanently recording this sequence in the distributed ledger of the blockchain network. The contribution calculation module, based on the channel contribution event sequence stored in the distributed ledger, calculates the quantified contribution value of each insurance sales channel in one or more policy transactions using an improved contribution metric algorithm. This algorithm is designed to comprehensively calculate based on the type weight and time decay factor of each event in the channel contribution event sequence. The smart allocation module, based on the quantified contribution value calculated for each insurance sales channel and combined with the profit allocation rules pre-set in the blockchain smart contract, automatically calculates and generates an initial profit allocation scheme for each participating channel on the blockchain network, thus completing the entire process from data acquisition to profit allocation scheme generation.

[0021] In one embodiment of the present invention, the implementation method for verifying the on-chain module to generate a channel contribution event sequence with a consistency proof is as follows. See also... Figure 2Each consensus node receives raw data on channel behavior uploaded by one or more insurance sales channel nodes associated with it. The consensus node performs a horizontal comparison of the raw data uploaded by different insurance sales channel nodes involved in the same policy transaction, identifying discrepancies in the descriptions of the same operation or event. For operations or events with discrepancies, the system invokes a pre-set business rule base and a historical arbitration case base to logically arbitrate the discrepancies, forming a universally accepted and unique event description. The raw data on channel behavior after discrepancy processing is then sorted according to the business process timeline of the policy transaction. A cryptographic hash value is generated for each event in the sorted event stream, and this hash value is associated with the hash value of the previous event. The associated hash value chain, the event occurrence time, and the identity identifiers of the participating nodes are packaged together to form an immutable data block, which is then written into the distributed ledger after consensus by all consensus nodes, thus completing the generation of the channel contribution event sequence.

[0022] In its implementation, the on-chain verification module of the insurance sales channel data sharing and transparent profit distribution collaborative system generates a sequence of channel contribution events with a consistency proof through a process involving multi-party data comparison and consensus. In the blockchain network, each consensus node receives raw channel behavior data uploaded by one or more insurance sales channel nodes associated with it. For example, an online agent node uploads raw channel behavior data including "customer clicks on an advertisement link, completes online health declaration Q&A, and successfully pays premium," while an offline agent node for the same policy might upload raw channel behavior data including "contacting the customer by phone, explaining the terms face-to-face, assisting the customer in completing the health declaration, and confirming payment." The consensus node, based on a unique policy transaction number, places the raw channel behavior data from online and offline agent nodes together for horizontal comparison. The purpose of this horizontal comparison is to identify discrepancies in the descriptions of the same operation or event. For example, "customer completes online health declaration Q&A" recorded by an online agent node and "assisting the customer in completing the health declaration" recorded by an offline agent node may refer to the same business action, but the perspective and level of detail in the description differ.

[0023] In some embodiments, for operations or events with identified discrepancies in description, the system invokes a preset business rule base and a historical arbitration case base to logically arbitrate the discrepancies. The business rule base defines standardized event description templates, while the historical arbitration case base stores records and results of past rulings on similar discrepancies. The logical arbitration process compares the descriptions of "completing online health declaration Q&A" and "assisting customers in completing health declarations" based on these knowledge bases, potentially invoking the rule "customer-initiated operation as primary, agent-assisted action as secondary," and referencing historical cases to ultimately form a universally accepted and unique event description, such as "customer-led completion of health declaration, agent present to provide assistance." It can be understood that the horizontal comparison and arbitration mechanism ensures consistency in key factual descriptions of raw channel behavior data uploaded from different channels, laying the foundation for subsequent contribution calculations.

[0024] In practical implementation, the raw channel behavior data, after differentiation processing, is sorted according to the business process timeline of the policy transaction. The system extracts the timestamp information from each event and arranges the events in ascending order to form a coherent event flow. For example, the sorted event flow might be "contacting the customer by phone," "customer clicking on an advertising link," "explaining the terms face-to-face," "customer completing health disclosure with the agent providing assistance," and "successful premium payment." A cryptographic hash value is generated for each event in the sorted event flow. The algorithm used to generate the hash value can be SHA-256. The generation of the cryptographic hash value follows a specific chain association rule, that is, the hash value of the current event is associated with the hash value of the previous event. One association calculation method can be expressed as the formula: in: Indicates the first The hash value of an event. Represents a hash function. Indicates the first The hash value of an event. This represents a string concatenation operation. Indicates the first Unique event description data for each event Indicates the first The timestamp of each event. This association method ensures that any tampering with data in a historical event will change the hash value of all subsequent events, making it easily detectable.

[0025] In implementation, the associated hash value chain, event occurrence time, and participating node identity identifiers are packaged together to form an immutable data block. The data block contains the complete hash value chain generated from the aforementioned event stream, the precise timestamp of each event, and digital identity information identifying online and offline agent nodes. This data block is broadcast to all consensus nodes in the blockchain network, where all consensus nodes reach a consensus on the validity and order of the data block according to a predetermined consensus algorithm, such as the Practical Byzantine Fault Tolerance algorithm. Once the data block receives confirmation from a sufficient number of consensus nodes, it is formally written into the distributed ledger of the blockchain network, thus completing the generation of the channel contribution event sequence for this policy transaction. In some embodiments, writing to the distributed ledger means that the channel contribution event sequence becomes a permanent, transparent, and traceable record that any node can query but cannot unilaterally modify. Optionally, the consensus process may include additional verification of the logical order of timestamps to ensure that the chronological order of the event stream conforms to business logic. Optionally, the participating node identity identifiers are encrypted before packaging to strike a balance between auditability and privacy protection.

[0026] In one embodiment of the present invention, the improved contribution metric algorithm in the contribution calculation module is implemented as follows. See also... Figure 3The algorithm reads a sequence of channel contribution events from a distributed ledger, extracting attributes for each event. These attributes include at least an event type code, a timestamp of the event occurrence, and a unique identifier for the channel initiating the event. Based on a pre-defined event type-contribution weight mapping table, it queries the static contribution weight value corresponding to each event type code. For each event, it calculates its time decay factor by obtaining the time difference between the event's timestamp and the policy's final underwriting completion timetamp, substituting this time difference into a negative exponential decay function to obtain the event's time decay coefficient. It retrieves a sequence of channel contribution events that has been solidified from the distributed ledger and parses the event type code and the first timestamp of the event to be calculated. Based on the event type code, it queries the pre-defined event type-contribution weight mapping table in the blockchain network to obtain the static contribution weight value bound to the event type code. It retrieves the underwriting completion timestamp of the policy transaction associated with the event to be calculated from the distributed ledger as the second timestamp for calculating time decay. It calculates the absolute time difference between the first and second timestamps and converts this absolute time difference into a standardized time interval measured in a pre-defined time unit. Using the standardized time interval as an input variable, a predefined negative exponential decay function is substituted to calculate the time decay coefficient. The expression for the negative exponential decay function is configured such that the coefficient value is negatively correlated with the standardized time interval. Within the consensus nodes of the blockchain network, a multiplication operation is performed, multiplying the static contribution weight value by the calculated time decay coefficient. The result of this multiplication is used as the actual contribution weight of the event, encapsulated with a unique identifier for the event, and stored back in the extended attribute field corresponding to the event in the distributed ledger. The actual contribution weights of all events belonging to the same insurance sales channel are summed, and the sum is the quantified contribution value of that insurance sales channel for a single or multiple policy transactions. For policy transactions completed through cross-channel collaboration, the quantified contribution values ​​of all participating channels are normalized to ensure that the sum of the contribution values ​​of all channels is a fixed constant.

[0027] In practice, the contribution calculation module uses an improved contribution quantification algorithm to calculate the quantitative contribution value of each insurance sales channel in one or more policy transactions, based on the channel contribution event sequence stored in the distributed ledger. Taking a specific life insurance policy transaction as an example, its channel contribution event sequence might include "customer clicks on an advertisement" and "completes an online health questionnaire" events contributed by online agent nodes, and "telephone communication and explanation" and "on-site submission of a medical examination report" events contributed by offline agent nodes. After reading this channel contribution event sequence from the distributed ledger, the algorithm extracts the attributes of each event in the sequence. These attributes explicitly include the event type code, the timestamp of the event occurrence, and the unique identifier of the initiating channel. For example, the "customer clicks on an advertisement" event might have the event type code "AD_CLICK" and the specific timestamp "2023-10-26 10:30:00," and its initiating channel's unique identifier is "Channel_Online_001."

[0028] In some embodiments, the system queries the static contribution weight value corresponding to each event type code according to a preset event type-contribution weight mapping table. The event type-contribution weight mapping table exists in the blockchain network in a configured form. For example, the event type code "AD_CLICK" may be mapped to a static contribution weight value of 1.0, and the event type code "PHONE_CONSULT" may be mapped to a static contribution weight value of 1.5. For each event, its time decay factor needs to be calculated. The calculation method is to obtain the time difference between the timestamp of the event occurrence and the timestamp of the final underwriting of the policy, substitute this time difference into the negative exponential decay function, and obtain the event's time decay coefficient. The system retrieves the solidified channel contribution event sequence from the distributed ledger and parses out the event type code and the first timestamp of the event to be calculated. For example, the first timestamp of the event "on-site submission of medical examination report" is "2023-10-28 14:20:00". Based on the event type code "REPORT_SUBMIT", query the pre-built event type-contribution weight mapping table in the blockchain network to obtain the static contribution weight value bound to this event type code, such as 2.0.

[0029] In practical implementation, the underwriting completion timestamp of the policy transaction associated with the event to be calculated is obtained from the distributed ledger and used as the second timestamp for calculating time decay, for example, "2023-11-05 09:00:00". The absolute time difference between the first timestamp "2023-10-28 14:20:00" and the second timestamp "2023-11-05 09:00:00" is calculated and converted into a standardized time interval measured in a preset time unit "day", resulting in 7.78 days. The standardized time interval is used as an input variable and substituted into a predefined negative exponential decay function to calculate the time decay coefficient, where the expression of the negative exponential decay function is configured such that the coefficient value is negatively correlated with the standardized time interval. A functional expression for calculating the time decay coefficient can be expressed as: in: Indicates the first The time decay coefficient of an event, It is a natural constant. It is the preset decay rate constant. It is the first The standardized time interval of each event. Assume... A value of 0.1 indicates the time decay coefficient for this event. Calculated as Within the consensus nodes of the blockchain network, a multiplication operation is performed, combining the static contribution weight value of 2.0 with the calculated time decay coefficient. The values ​​are multiplied. The result of this multiplication is the actual contribution weight of the "on-site submission of medical examination report" event, which is then encapsulated with a unique identifier and stored back in the distributed ledger as the corresponding extended attribute field. The actual contribution weights of all events belonging to the same insurance sales channel are summed, and the resulting total is the quantified contribution value of the insurance sales channel to this single policy transaction.

[0030] In some embodiments, for policy transactions completed through cross-channel collaboration, the quantitative contribution values ​​of all participating channels are normalized to ensure that the sum of the contribution values ​​of all channels is a fixed constant. For example, the sum of the quantitative contribution values ​​calculated by online agent nodes is 8.5, the sum of the quantitative contribution values ​​calculated by offline agent nodes is 6.5, and the fixed constant is set to 100. After normalization, the final quantitative contribution value of the online agent node is adjusted to (8.5 / (8.5+6.5)). 100 = 56.7, the final quantitative contribution value of the offline agent node is adjusted to (6.5 / (8.5+6.5)). 100 = 43.3. Optionally, the fixed constant can be set according to different benefit distribution bases. Optionally, the normalization process is executed in a smart contract, and its result is recorded in a distributed ledger.

[0031] In one embodiment of the present invention, the intelligent allocation module generates the initial profit allocation scheme as follows: The module reads the total distributable profit amount of the current policy transaction from the state database of the blockchain network. It then calls the profit allocation smart contract deployed on the blockchain network, which encodes a tiered allocation ratio function corresponding to different product types and channel levels. The total distributable profit amount, the quantified contribution value of each insurance sales channel, and the channel level identifier are input parameters into the profit allocation smart contract. The profit allocation smart contract calculates the absolute value of the profit share that each channel should receive according to its internal logic. The calculation process follows the principle that channels with higher quantified contribution values ​​receive a higher proportion, and the proportion calculation conforms to the preset tiered function. The calculated absolute values ​​of the profit shares for each channel, the quantified contribution values ​​used for calculation, and the allocation ratios are collectively encapsulated into a structured allocation record to form the initial profit allocation scheme. The initial profit allocation scheme is temporarily stored in the pending transaction pool of the blockchain network in the form of a pre-written log, and a unique digest hash of the initial profit allocation scheme is generated.

[0032] In practice, the intelligent allocation module automatically calculates and generates an initial profit allocation plan for each channel on the blockchain network based on the quantified contribution value of each insurance sales channel and the profit allocation rules pre-set in the smart contract. Assume a whole life insurance policy has a total distributable profit of 15,000 yuan, involving two sales channels: an "online digital marketing channel" and an "offline exclusive agent channel." The intelligent allocation module reads the total distributable profit of 15,000 yuan for the current policy transaction from the blockchain network's state database. It then calls the profit allocation smart contract deployed on the blockchain network. This smart contract encodes a tiered allocation ratio function corresponding to different product types and channel levels. For example, for a "whole life insurance" product, the allocation ratio function stipulates that the basic allocation ratio is determined based on the quantified contribution value, but is adjusted by a coefficient according to the channel level.

[0033] In some embodiments, the smart allocation module takes the total distributable profit amount, the quantified contribution value of each insurance sales channel, and the channel's level identifier as input parameters and passes them to the profit allocation smart contract. For specific input data, please refer to Table 1: Table 1: Input and Output Table for Initial Profit Distribution Scheme Calculation The profit-sharing smart contract calculates the absolute value of the profit share that each channel should receive based on its internal logic. The calculation process follows the principle that channels with higher quantified contribution values ​​receive a higher proportion, and the proportion calculation conforms to a pre-defined step function. The calculation logic of a step-based distribution proportion function can be expressed as follows: in: Indicates the first The calculated allocation ratio for each channel, It is a quantified contribution value The step function of the independent variable is used to calculate the basic proportion. It is a channel level identifier This is a function of adjustment coefficients for the parameters. It can be understood that for online digital marketing channels, the quantitative contribution value of 56.7 is higher than that of offline channels (43.3), therefore... The calculation yields a higher base ratio; simultaneously, because its channel level A is higher than level B, it achieves this through... The function may receive an adjustment factor greater than 1.0, resulting in a final allocation ratio of 58.5% that is higher than its quantified contribution ratio (56.7 / (56.7+43.3)=56.7%).

[0034] In implementation, the profit distribution smart contract encapsulates the calculated absolute values ​​of profit shares from each channel, the quantified contribution values ​​used in the calculation, and the distribution ratios into a structured distribution record. This structured distribution record contains the complete information fields shown in Table 1, forming the initial profit distribution scheme for this policy transaction. The initial profit distribution scheme is temporarily stored in the blockchain network's pending transaction pool as a pre-written log, and a unique digest hash of the initial profit distribution scheme is generated, such as a SHA-256 hash value "a1b2c3d4e5...". Optionally, the format of the pre-written log follows the transaction structure agreed upon by the blockchain network. Optionally, the unique digest hash will be used in the subsequent consensus confirmation process to verify the completeness and consistency of the distribution scheme.

[0035] In one embodiment of the present invention, the consensus confirmation module and the automatic execution module are implemented as follows. After the initial benefit distribution scheme is generated, the system triggers a preset multi-party confirmation process. When a new initial benefit distribution scheme is detected in the transaction pool to be confirmed, the coordination service component of the blockchain network generates a set of corresponding digital confirmation requests based on the insurance institution node identifier and insurance sales channel node identifier involved in the scheme. Through the message routing service of the blockchain network, the digital confirmation requests, along with the digest hash and a complete copy of the initial benefit distribution scheme, are pushed to the client interfaces of the relevant insurance institution nodes and insurance sales channel nodes, respectively. The client interfaces of each node display the complete content of the initial benefit distribution scheme locally and start a confirmation timeout window with a preset validity period. Within the confirmation timeout window, the relevant nodes need to use their private keys to digitally sign the digest hash of the initial benefit distribution scheme and return the signature result as a confirmation receipt to the coordination service component of the blockchain network. The coordination service component collects the digital signatures of all relevant nodes and verifies the validity of the signatures. The initial benefit distribution scheme is determined to have been jointly confirmed only when all the necessary signatures have been effectively collected and verified. Once the joint signature confirmation is complete, the consensus nodes of the blockchain network automatically extract the execution instructions corresponding to the initial profit distribution plan from the pending confirmation transaction pool. According to the execution instructions, the digital assets corresponding to the total distributable profit amount recorded in the initial profit distribution plan and payable by the insurance institution are locked and transferred from the insurance institution's locked account to the temporary escrow contract address on the blockchain network. The smart contract generates a series of parallel fund transfer transactions according to the profit shares of each channel recorded in the initial profit distribution plan. At the preset execution time or when the preset execution conditions are met, the smart contract atomically executes all fund transfer transactions, transferring the corresponding amount of digital assets from the temporary escrow contract address to the designated settlement accounts of each insurance sales channel. After each successful fund transfer transaction, a corresponding fund settlement record is generated in the distributed ledger, containing the sending account, receiving account, amount, timestamp, and associated policy transaction number. When all fund transfer transactions are completed, the smart contract records the final completion status of the initial profit distribution plan in the distributed ledger.

[0036] In practical implementation, the consensus confirmation module of the insurance channel data sharing and transparent profit distribution collaborative system triggers a pre-defined multi-party confirmation process after the initial profit distribution plan is generated. When an initial profit distribution plan containing a total allocation of 15,000 yuan is detected in the transaction pool to be confirmed, the coordination service component of the blockchain network generates a set of corresponding digital confirmation requests based on the insurance institution node identifier "Insurer_Node_A" and the insurance sales channel node identifiers "Channel_Online_001" and "Channel_Offline_002" involved in the plan. Through the message routing service of the blockchain network, the digital confirmation requests, along with the digest hash "a1b2c3d4e5..." of the initial profit distribution plan and a complete copy of the content, are pushed to the client interfaces of the relevant insurance institution node and the two insurance sales channel nodes, respectively.

[0037] In some embodiments, the client interface of each node locally displays the complete content of the initial profit distribution scheme, including the total amount, the amount allocated to each channel, and the calculation basis, and initiates a confirmation timeout window with a preset validity period of 24 hours. Within the confirmation timeout window, the relevant nodes need to digitally sign the digest hash "a1b2c3d4e5..." of the initial profit distribution scheme using their private keys, and return the signature result as a confirmation receipt to the coordination service component of the blockchain network. The process of generating the digital signature can be formally represented as follows: in: Indicates the first The signature results returned by each node. Indicates the signature function, Indicates the first The private key of each node, This represents the digest hash of the initial profit distribution scheme. The coordination service component collects the digital signatures of all relevant nodes. The coordination service component verifies the validity of the signatures, which involves decrypting the signatures using the public keys published by each node and comparing them with the original digest hash. The coordination service component determines that the initial benefit distribution scheme has been jointly confirmed only if all three digital signatures from the insurance institution node and the two sales channel nodes have been effectively collected and verified.

[0038] In practice, once the joint signature confirmation is completed, the consensus nodes of the blockchain network automatically extract the execution instructions corresponding to the initial profit distribution plan from the pending transaction pool. According to the execution instructions, the digital assets corresponding to the total distributable profit of 15,000 yuan recorded in the initial profit distribution plan and payable by the insurance institution are locked and transferred from the locked account of the insurance institution "Insurer_Node_A" to the temporary escrow contract address "Escrow_Contract_XYZ" of the blockchain network. The smart contract generates a series of parallel fund transfer transactions according to the profit shares of each channel recorded in the initial profit distribution plan, as shown in Table 2. Table 2: List of Fund Transfer Transactions At the preset execution time or when preset execution conditions are met, such as the next hour after all participants confirm, the smart contract atomically executes all fund transfer transactions, transferring digital assets of 8775 yuan and 6225 yuan respectively from the temporary escrow contract address "Escrow_Contract_XYZ" to the designated settlement accounts of the insurance sales channels "Channel_Online_001" and "Channel_Offline_002". After each successful fund transfer transaction, a corresponding fund settlement record is generated in the distributed ledger, including the transferring account, the receiving account, the amount, the timestamp, and the associated policy transaction number. Optionally, atomic execution ensures that all sub-transactions either all succeed or all fail, preventing intermediate states. After all fund transfer transactions have been executed, the smart contract records the final completion status of this initial profit distribution plan as "settled" in the distributed ledger.

[0039] In one embodiment of the present invention, the implementation method of the weight adjustment module for performing channel data contribution quality assessment and dynamic weight adjustment is as follows: After the preset assessment period ends, the weight adjustment module extracts the channel contribution event sequence of all records within the assessment period from the distributed ledger. Statistical analysis is performed on the extracted channel contribution event sequence to calculate the total number of contribution events for each insurance sales channel, the number of valid policies involved, and the frequency of the contribution events being cited in subsequent claims verification. For an assessment period, the distributed ledger is scanned to filter out all channel contribution events whose initiator is a specific insurance sales channel. The filtered events are counted to obtain the total number of contribution events for that specific insurance sales channel. From the filtered events, a unique policy transaction number is extracted, and the policy transaction number is deduplicated to obtain the number of valid policies involved in that specific insurance sales channel. In the distributed ledger, the records of claims verification requests initiated within the assessment period are queried, and in each claims verification request record, the unique hash identifier of the channel contribution event cited as verification evidence is parsed out. The parsed hash identifiers are matched with the hash identifiers of all events contributed by the specific insurance sales channel in this period, and the number of successful matches is counted. This number represents the frequency with which the contributed events are referenced in subsequent claims verification. Based on the statistical analysis results, evaluation indicators for each insurance sales channel are calculated in three dimensions: data accuracy, data value density, and collaborative integrity within the evaluation period. These three evaluation indicators are input into a pre-defined dynamic weight adjustment model. The dynamic weight adjustment model outputs the adjustment coefficients for the static contribution weight values ​​of the insurance sales channel in the event type-contribution weight mapping table for the next evaluation period. Using the adjustment coefficients, the static contribution weight values ​​of various events belonging to the insurance sales channel in the event type-contribution weight mapping table are updated. The updated static contribution weight values ​​are synchronized to all consensus nodes for use in calculating the improved contribution metric algorithm for the next evaluation period.

[0040] In practical implementation, the weight adjustment module of the insurance channel data sharing and transparent profit distribution collaborative system is used to perform channel data contribution quality assessment and dynamic weight adjustment. After a preset assessment period ends, such as the end of a quarter, the weight adjustment module extracts all channel contribution event sequences recorded within the assessment period from the distributed ledger. Taking a specific insurance sales channel, "online digital marketing channel," as an example, the extracted channel contribution event sequences are statistically analyzed to calculate the total number of contribution events for "online digital marketing channel," the number of valid policies involved, and the frequency with which the contribution events are cited in subsequent claims verification. For the assessment period of "fourth quarter of 2023," the distributed ledger is scanned to filter out all channel contribution events initiated by "online digital marketing channel." The filtered events are counted to obtain the total number of contribution events for "online digital marketing channel," for example, 1500. From the filtered events, a unique policy transaction number is extracted, and the policy transaction numbers are deduplicated to obtain the number of valid policies involved in "online digital marketing channel," for example, 300. In the distributed ledger, query the claim verification request records initiated within the "Fourth Quarter of 2023". For each claim verification request record, extract the unique hash identifier of the channel contribution event cited as verification evidence. Match the extracted hash identifier with the hash identifiers of all events contributed by the "Online Digital Marketing Channel" during this period, and count the number of successful matches (e.g., 45 times). This number represents the frequency with which the contribution event is cited in subsequent claim verifications.

[0041] In some embodiments, based on statistical analysis results, evaluation indicators for each insurance sales channel are calculated in three dimensions: data accuracy, data value density, and collaborative integrity, within the evaluation period. Data accuracy can be calculated by comparing the difference rate between events reported by the channel and those confirmed through consensus; data value density can be reflected by the ratio of "citation frequency / total number of contributing events"; collaborative integrity can be measured by the proportion of events initiated by the channel within the evaluation period that are modified or rejected by the arbitration mechanism. The three evaluation indicators—data accuracy, data value density, and collaborative integrity—are input into a pre-defined dynamic weight adjustment model. The dynamic weight adjustment model outputs the adjustment coefficient for the static contribution weight value of the insurance sales channel in the event type-contribution weight mapping table for the next evaluation period. One calculation of the adjustment coefficient can be expressed as: in: This represents the calculated adjustment factor. This represents the accuracy evaluation metric for normalized data. This represents the normalized data value density assessment index. This represents the normalized collaborative integrity assessment index. These are the preset weight parameters for the corresponding indicators. It can be understood that the dynamic weight adjustment model combines the evaluation results of the three dimensions into an adjustment coefficient based on the above formula. For example, the adjustment coefficient for "online digital marketing channels" is calculated. It is 1.15.

[0042] In implementation, adjustment coefficients are used to update the static contribution weight values ​​of various events belonging to the insurance sales channel in the event type-contribution weight mapping table. For example, the original static contribution weight value of the "customer clicks on an ad" event in the "online digital marketing channel" is 1.0. After multiplying by the adjustment coefficient of 1.15, the new static contribution weight value is updated to 1.15. Similarly, the weights of other event types in this channel are also adjusted synchronously. The updated static contribution weight values ​​are synchronized to all consensus nodes for calculation of the improved contribution metric algorithm in the next evaluation cycle. Optionally, the weight adjustment process can be automatically triggered periodically by an independent on-chain smart contract. Optionally, the updated weights take effect immediately in the next evaluation cycle and are used for the contribution calculation of all newly generated events.

[0043] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A collaborative system for data sharing and transparent profit distribution in insurance channels, characterized in that: include: The data acquisition module is used to collect raw channel behavior data from different insurance sales channels through multiple consensus nodes in the blockchain network. The raw channel behavior data includes at least customer contact records, sales process records, and premium payment result records. The on-chain verification module is used to cross-validate and timestamp the original data of the channel behavior using the consensus node, generate a channel contribution event sequence with a consistency proof, and record the channel contribution event sequence in the distributed ledger of the blockchain network. The contribution calculation module is used to calculate the quantitative contribution value of each insurance sales channel in a single or multiple policy transactions based on the channel contribution event sequence stored in the distributed ledger, using an improved contribution quantification algorithm. The improved contribution quantification algorithm is calculated based on the type weight and time decay factor of each event in the channel contribution event sequence. The intelligent allocation module is used to automatically calculate and generate an initial profit allocation scheme for each channel on the blockchain network based on the quantitative contribution value of each insurance sales channel and the profit allocation rules pre-set in the smart contract.

2. The collaborative system for data sharing and transparent profit distribution in the insurance channel according to claim 1, characterized in that, The consensus node is used to cross-validate and timestamp the raw data of the channel behavior, generating a sequence of channel contribution events with a consistency proof, including: Each consensus node receives raw data on channel behavior uploaded by one or more insurance sales channel nodes associated with it; By comparing the raw data uploaded by different insurance sales channel nodes involved in the same policy transaction, we can identify differences in the description of the same operation or event. For operations or events with discrepancies in description, the system calls the preset business rule base and the historical arbitration case base to perform logical arbitration on the discrepancies and form a universally recognized and unique event description. The original channel behavior data, after being processed for differences, is sorted according to the business process timeline of the policy transaction; Generate a cryptographic hash value for each event in the sorted event stream, and associate the cryptographic hash value with the hash value of the previous event; The associated hash value chain, event occurrence time, and participating node identity identifiers are packaged together to form an immutable data block. After consensus by all consensus nodes, this block is written into the distributed ledger, thereby completing the generation of the channel contribution event sequence.

3. The collaborative system for data sharing and transparent profit distribution in insurance channels according to claim 1, characterized in that, The improved contribution metric algorithm is calculated based on the type weight and time decay factor of each event in the channel contribution event sequence, including: Read the channel contribution event sequence from the distributed ledger, and extract the attributes of each event in the sequence. The attributes include at least the event type code, the timestamp of the event occurrence, and the unique identifier of the channel initiating the event. Based on the preset event type-contribution weight mapping table, query the static contribution weight value corresponding to each event type code; For each event, its time decay factor is calculated. The calculation method is as follows: obtain the time difference between the timestamp of the event and the timestamp of the final underwriting of the policy, substitute the time difference into the negative exponential decay function to calculate the time decay coefficient of the event. The actual contribution weight of an event is obtained by multiplying the static contribution weight value of each event by the corresponding time decay coefficient. The actual contribution weights of all events belonging to the same insurance sales channel are summed, and the sum is the quantitative contribution value of the insurance sales channel for the single or multiple policy transactions. For policy transactions completed through cross-channel collaboration, the quantitative contribution values ​​of all participating channels are normalized to ensure that the sum of the contribution values ​​of all channels is a fixed constant.

4. The collaborative system for data sharing and transparent profit distribution in insurance channels according to claim 3, characterized in that, The actual contribution weight of an event is obtained by multiplying the static contribution weight value of each event by the corresponding time decay coefficient, including: Obtain the solidified channel contribution event sequence from the distributed ledger, and parse out the event type code and the first timestamp of the event occurrence from it; Based on the event type code, query the event type-contribution weight mapping table pre-set in the blockchain network to obtain the static contribution weight value bound to the event type code; Obtain the underwriting completion timestamp of the policy transaction associated with the event to be calculated from the distributed ledger, and use it as the second timestamp for calculating time decay; Calculate the absolute time difference between the first timestamp and the second timestamp, and convert the absolute time difference into a standardized time interval measured in a preset time unit; The standardized time interval is used as an input variable and substituted into a predefined negative exponential decay function to calculate the time decay coefficient, wherein the expression of the negative exponential decay function is configured such that the coefficient value is negatively correlated with the standardized time interval. Within the consensus node of the blockchain network, a multiplication operation logic is executed to multiply the static contribution weight value by the calculated time decay coefficient. The result of multiplication is used as the actual contribution weight of the event, and the event is encapsulated with a unique identifier and stored back in the extended attribute field corresponding to the event in the distributed ledger.

5. The collaborative system for data sharing and transparent profit distribution in insurance channels according to claim 1, characterized in that, Based on the quantified contribution value of each insurance sales channel and the profit distribution rules pre-set in the smart contract, an initial profit distribution plan for each channel is automatically calculated and generated on the blockchain network, including: Read the total distributable benefit amount of the current policy transaction from the state database of the blockchain network; The smart contract for profit distribution deployed on the blockchain network is invoked. The smart contract for profit distribution encodes a tiered distribution ratio function corresponding to different product types and different channel levels. The total distributable profit amount, the quantitative contribution value of each insurance sales channel, and the channel's level identifier are used as input parameters and passed into the profit distribution smart contract. The profit distribution smart contract calculates the absolute value of the profit share that each channel should receive based on its internal logic. The calculation process follows the principle that channels with higher quantitative contribution values ​​receive a higher proportion, and the proportion calculation conforms to the principle of a preset ladder function. The calculated absolute values ​​of the profit share of each channel, the quantitative contribution values ​​on which the calculation is based, and the allocation ratio are collectively packaged into a structured allocation record to form the initial profit allocation scheme. The initial profit distribution plan is temporarily stored in the pending transaction pool of the blockchain network in the form of a pre-written log, and a unique digest hash of the initial profit distribution plan is generated.

6. The collaborative system for data sharing and transparent profit distribution in insurance channels according to claim 1, characterized in that, The system also includes: The consensus confirmation module is used to trigger a preset multi-party confirmation process after the initial benefit distribution plan is generated, and to push the initial benefit distribution plan to the relevant insurance institution nodes and insurance sales channel nodes for joint confirmation. An automatic execution module is used to automatically execute the initial benefit distribution plan by the blockchain network after the joint signature confirmation is completed, transferring the corresponding share of digital assets from the insurance institution's locked account to the designated settlement account of each insurance sales channel.

7. The insurance channel data sharing and transparent profit distribution collaborative system according to claim 6, characterized in that, After the initial profit distribution plan is generated, a preset multi-party confirmation process is triggered to push the initial profit distribution plan to relevant insurance institution nodes and insurance sales channel nodes for joint confirmation, including: When a new initial benefit distribution scheme is detected in the unconfirmed transaction pool, the coordination service component of the blockchain network generates a set of corresponding digital confirmation requests based on the insurance institution node identifier and insurance sales channel node identifier involved in the scheme. Through the message routing service of the blockchain network, the digital confirmation request, along with the digest hash and full content copy of the initial benefit distribution scheme, is pushed to the client interfaces of the relevant insurance institution nodes and insurance sales channel nodes, respectively. Each node's client interface displays the complete content of the initial profit distribution plan locally and launches a confirmation timer window with a preset validity period; Within the confirmation time window, the relevant nodes need to use their private keys to digitally sign the digest hash of the initial benefit distribution scheme, and return the signature result as a confirmation receipt to the coordination service component of the blockchain network. The coordination service component collects the digital signatures of all relevant nodes and verifies the validity of the signatures. The initial benefit distribution scheme is deemed to have been jointly confirmed only when all the required signatures have been effectively collected and verified.

8. The collaborative system for data sharing and transparent profit distribution in insurance channels according to claim 6, characterized in that, Once the joint signatures are confirmed, the blockchain network automatically executes the initial profit distribution plan, transferring the corresponding share of digital assets from the insurance institution's locked account to the designated settlement accounts of each insurance sales channel, including: After the initial profit distribution plan is jointly confirmed, the consensus nodes of the blockchain network automatically extract the execution instructions corresponding to the initial profit distribution plan from the unconfirmed transaction pool; According to the execution instruction, the digital assets corresponding to the total distributable benefit amount recorded in the initial benefit distribution plan that should be paid by the insurance institution are locked and transferred from the insurance institution's locked account to the temporary custody contract address of the blockchain network. The smart contract generates a series of parallel fund transfer transactions according to the profit share of each channel recorded in the initial profit distribution plan. At the preset execution time or when the preset execution conditions are met, the smart contract atomically executes all fund transfer transactions, transferring the amount of digital assets from the temporary escrow contract address to the designated settlement accounts of each insurance sales channel. After each successful fund transfer transaction, a corresponding fund settlement record is generated in the distributed ledger. The fund settlement record includes the transferring account, the receiving account, the amount, the timestamp, and the associated policy transaction number. Once all fund transfer transactions have been completed, the smart contract records the final completion status of the initial profit distribution plan in the distributed ledger.

9. The collaborative system for data sharing and transparent profit distribution in insurance channels according to claim 1, characterized in that, The system also includes a weight adjustment module for performing channel data contribution quality assessment and dynamic weight adjustment, including: After the preset evaluation period ends, the channel contribution event sequence of all records within the evaluation period is extracted from the distributed ledger; Statistical analysis was performed on the extracted channel contribution event sequences to calculate the total number of contribution events for each insurance sales channel, the number of valid insurance policies involved, and the frequency of the contribution events being cited in subsequent claims verification. Based on the statistical analysis results, the evaluation indicators for each insurance sales channel were calculated in three dimensions: data accuracy, data value density, and collaborative integrity during the evaluation period. The three evaluation indicators, namely data accuracy, data value density and collaborative integrity, are input into a preset dynamic weight adjustment model. The dynamic weight adjustment model outputs the adjustment coefficient of the static contribution weight value of the insurance sales channel in the event type-contribution weight mapping table in the next evaluation period. Using the adjustment coefficient, update the static contribution weight values ​​of various events belonging to the insurance sales channel in the event type-contribution weight mapping table; The updated static contribution weight values ​​are synchronized to all consensus nodes for use in the calculation of the improved contribution metric algorithm in the next evaluation cycle.

10. The insurance channel data sharing and transparent profit distribution collaborative system according to claim 9, characterized in that, The statistical analysis of the extracted channel contribution event sequences calculates the total number of contribution events for each insurance sales channel, the number of valid policies involved, and the frequency with which the contribution events are cited in subsequent claims investigations, including: For an evaluation period, the distributed ledger is scanned to filter out all events contributed by the event initiator to a specific insurance sales channel; The selected events are counted to obtain the total number of events contributing to the specific insurance sales channel; From the selected events, extract the unique policy transaction number, deduplicate the policy transaction number, and count the number of valid policies involved in the specific insurance sales channel; In the distributed ledger, query the records of claims verification requests initiated within the assessment period, and in each claims verification request record, parse out the unique hash identifier of the channel contribution event referenced as verification evidence; The parsed hash identifier is matched with the hash identifiers of all events contributed by the specific insurance sales channel in this period, and the number of successful matches is counted. The number of successful matches is the frequency with which the contributed event is referenced in subsequent claims verification.

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