A customer risk management system for a workers' compensation product
By utilizing the customer risk management system and data acquisition and multi-screening technologies, the problem of inaccurate risk identification by insurance companies has been solved, enabling precise risk management for both existing and new customers, reducing underwriting risks and improving work efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- TAYLOR (SHANDONG) INSURANCE TECH CO LTD
- Filing Date
- 2024-09-20
- Publication Date
- 2026-05-15
AI Technical Summary
Insurance companies face problems such as data silos, low data quality, insufficient claims data analysis, and cumbersome manual review in customer risk management, which leads to inaccurate risk identification and affects product operating profits.
A customer risk management system is provided, including a data acquisition module, a list segmentation module, a prohibited insurance marking module, a job type screening module, and a comparison prompt module. By acquiring historical claims data, setting risk thresholds, segmenting the list and performing multiple screenings, marking prohibited insurance and providing abnormal prompts, it achieves precise risk management.
It enables precise risk management for both existing and new customers, reduces the underwriting risk for insurance companies, and improves work efficiency and the flexibility of risk management.
Smart Images
Figure CN118822748B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of insurance management technology, specifically to a customer risk management system for personal injury insurance products. Background Technology
[0002] Insurance is an important component of the social and economic security system. With the continuous development of the social economy and the increasing awareness of security among residents, the scope of insurance business is becoming wider and wider. Effective risk identification is the most critical technical issue for insurance companies in undertaking insurance business.
[0003] Currently, insurance companies face three main challenges in accurately assessing customer risk:
[0004] The insurance industry needs to share data and information across industries and departments to obtain information. However, data from various industries is scattered and fragmented, resulting in information silos and low data quality that cannot effectively meet the needs of risk identification.
[0005] Currently, insurance companies' claims data analysis dimensions are not refined enough and their model technology is insufficient. The construction and application of models that map claims data to the underwriting end of insurance companies are inadequate. When a customer makes a claim, the risk points of the customer cannot be accurately quantified, and the risk prediction of new customers is not sufficiently supported by claims data analysis.
[0006] In the underwriting and claims process, customer review and processing still rely on professional manual labor. The excessive volume of documents required for review, the cumbersome process, and the high workload, coupled with insufficient digitalization standards and practices, lead to low efficiency and make customer risk management susceptible to human factors (subjectivity or error). The lack of intelligent methods makes it impossible to accurately quantify the risks of existing and new customers, resulting in pressure on product operating profits or even losses. Summary of the Invention
[0007] To address the aforementioned problems, this invention provides a customer risk management system for personal injury insurance products, comprising a data acquisition module, a list segmentation module, a prohibited insurance marking module, a job type screening module, a data processing module, and a comparison prompt module;
[0008] The data acquisition module is used to acquire historical claims data of each cooperating insured company in the system database. The historical claims data includes five-rate information data and false information markers. The five-rate information includes the reporting rate, disability rate, disability assessment rate, case settlement rate, and payout rate.
[0009] The list segmentation module is used to set risk thresholds for each of the five rates of information based on historical claims data, as well as a threshold for the number of times false information is marked, to segment all insured companies in the system database into a gray list or a black list.
[0010] The prohibited insurance marking module is used to perform multiple screenings on newly uploaded personnel lists of insured companies, including blacklists, sensitive industry fields, prohibited insurance areas, and company qualifications, and mark them as prohibited insurance based on the screening results;
[0011] The job category screening module is used to export insured companies that have not been marked as prohibited from insurance, and to screen the job categories of the personnel list uploaded by the insured companies for prohibited jobs.
[0012] The data processing module is used to merge the insurance liability parameters and insurance underwriting parameters of various occupations in the gray list and standard comparison parameters to obtain merged data; the insurance liability parameters include disability ratio, sudden death insurance amount, traffic accident insurance amount limit and additional 24-hour limit; the insurance underwriting parameters include the proportion of over-age personnel, the proportion of personnel in the five occupational categories, the proportion of personnel in the four and five occupational categories, and the approval rate;
[0013] The comparison and prompt module is used to compare the list of personnel whose occupations are not marked as prohibited from insurance by the insured companies after screening with the insurance liability parameters or insurance application parameters in the merged data, and to provide an anomaly prompt.
[0014] The list segmentation module segments all insured companies in the system database into either a gray list or a black list. The specific method is as follows:
[0015] Step 1: Preset the risk threshold of the five rates and divide the data into gray lists;
[0016] Each of the five rates is preset with a risk threshold 1. If the historical claims rate of the insured company is greater than or equal to the risk threshold 1 for the claims rate, and the disability rate is greater than or equal to the risk threshold 1 for the disability rate, then the company will be classified into the gray list.
[0017] If the payout ratio of an insured company's historical claims data reaches 100%, it will be placed on a gray list.
[0018] If the disability assessment rate of the insured company's historical claims data is greater than or equal to the disability assessment rate risk threshold one, it will be classified into the gray list.
[0019] If the historical claims settlement rate of an insured company within the first-level time period is less than the settlement rate risk threshold one, it will be classified into the gray list.
[0020] Step 2: Obtain the historical claims data of the insured companies that have been assigned to the gray list, preset the risk threshold of the five-rate information as two, and reclassify the insured companies in the gray list into the black list.
[0021] Each of the five pre-set risk thresholds is 2. If the historical claims data of an insured company in the gray list has a disability rate greater than or equal to the disability rate risk threshold 2, and the disability assessment rate is greater than or equal to the disability assessment rate risk threshold 2, then the company will be included in the blacklist.
[0022] If the loss ratio of an insured company in the gray list reaches 100% and the claim rate is greater than or equal to the second risk threshold for claim rate, then it will be included in the blacklist.
[0023] If the loss ratio of an insured company in the gray list reaches 100% and the disability rate is greater than or equal to the second disability risk threshold, it will be included in the blacklist.
[0024] If the settlement rate of an insured company in the gray list is less than 100% within the second-level time period, it will be included in the blacklist.
[0025] Step 3: Preset two thresholds for the number of times false information is marked, and then divide the list into a gray list or a black list based on these two thresholds.
[0026] If the number of times false information is marked in the historical claims data of an insured company is greater than or equal to the threshold number one, but less than the threshold number two, then it will be included in the gray list.
[0027] If the number of times false information is marked in the historical claims data of an insured company is greater than or equal to the threshold number two, it will be included in the blacklist.
[0028] The prohibited insurance marking module performs multiple screenings on the insured companies in the uploaded personnel list, including blacklisting, sensitive industry fields, prohibited regions, and company qualifications. Based on the screening results, it marks the companies as prohibited from insurance, specifically including:
[0029] Based on the personnel list uploaded by the insured companies, the corresponding company names are determined through four dimensions: the policyholder, the insured, the labor relationship, and the actual employer. The company names are then filtered according to the blacklist. If the company name exists in the blacklist, insurance is prohibited and a prohibition mark is made.
[0030] For the list of personnel who were not insured by companies on the blacklist after screening, the company name sensitive industry fields were filtered based on four dimensions, and companies with sensitive industry fields were marked as prohibited from insurance.
[0031] Filter companies without sensitive industry fields for restricted areas;
[0032] The business registration information of insured companies after filtering out prohibited areas is obtained through a third-party data interface. The companies are then filtered based on two dimensions: company qualifications and company size. Companies with sole proprietorship qualifications or companies with fewer than the threshold number of employees are marked as prohibited from insurance.
[0033] In the specific implementation, the filtering of sensitive industry fields in enterprise names based on four dimensions, and the marking of enterprises with sensitive industry fields as prohibited from protection, are carried out as follows:
[0034] Obtain the personnel list data uploaded by the insured companies, and filter the company names in the list data based on four dimensions: policyholder, insured, labor relationship, and actual employer.
[0035] A database of sensitive industry fields is pre-set. Based on four dimensions of filtering, if a company name is found to contain sensitive industry fields, the company will be marked as prohibited from using the platform.
[0036] The comparison and prompting module compares the list of personnel from insured companies whose occupations are not marked as prohibited from insurance with the insurance liability parameters in the merged data. The specific method is as follows:
[0037] If the insured company is not on the gray list, the insurance liability parameters of various types of work are taken from the merged data and compared with the insurance liability parameters of each type of work in the personnel list of the insured company.
[0038] If the insured company is on the gray list, the data is merged, and the insurance liability parameters of each job type of the insured company in the gray list are compared with the insurance liability parameters of the corresponding job types in the insured company's personnel list.
[0039] The comparison and prompting module compares the list of personnel from insured companies whose occupations are not marked as prohibited from insurance with the insurance application parameters in the merged data. The specific method is as follows:
[0040] If the insured company is not in the gray list, the merged data takes the insurance underwriting parameters of the standard comparison parameters and compares them with the insurance underwriting parameters in the personnel list of the insured company.
[0041] If the insured company is on the gray list, the data is merged, and the insurance application parameters of the gray list are compared with the insurance application parameters in the personnel list of the insured company.
[0042] In a specific implementation, the comparison and prompting module compares the insurance liability parameters or insurance underwriting parameters in the merged data and provides an anomaly prompt. The specific method is as follows:
[0043] If any insurance liability parameter for a job in the personnel list data uploaded by the insured company is greater than the corresponding insurance liability parameter value in the merged data, an abnormal information prompt for insurance liability adjustment will be issued.
[0044] If any insurance application parameter in the personnel list data uploaded by the insured company is greater than the corresponding insurance application parameter value, an abnormal insurance application adjustment information prompt will be issued.
[0045] On the other hand, an electronic device is also provided, including a processor and a memory, wherein the processor executes program data stored in the memory to run a customer risk management system for a personal injury insurance product as described above.
[0046] Beneficial Effects: The customer risk management system for personal injury insurance products provided by this invention uses a data acquisition module to statistically analyze historical claims data of cooperating insured companies, dynamically adjusts the list based on set thresholds, and takes timely risk management measures (such as eliminating or adjusting insurance liabilities) for existing customers. For new insured companies, the system uses a disqualification marking module to perform multiple screenings and disqualification markings based on multiple dimensions such as sensitive industry fields, prohibited areas, company qualifications, and company size, effectively reducing the underwriting risk of insurance companies and making risk management more precise and efficient.
[0047] Meanwhile, the data processing module and comparison prompt module identify customers who are renewing or adding insurance, compare the original uploaded personnel list with the insurance liability parameters and insurance application parameters under each list, promptly identify potential risks, and provide abnormal prompts to effectively avoid potential losses.
[0048] Through multiple screening processes and exclusion markers, the system effectively filters and eliminates existing customers and precisely controls new insured companies, thus reducing the insurance company's risk. Furthermore, the system can dynamically adjust the list based on the customer's actual situation, making risk management more flexible and efficient. Attached Figure Description
[0049] Figure 1 A diagram of a customer risk management system for personal injury insurance products. Detailed Implementation
[0050] Exemplary embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings.
[0051] See Figure 1 This embodiment provides a customer risk management system for personal injury insurance products. The system identifies risks based on two dimensions: the insured company's and the job categories of the personnel listed. It then provides anomaly alerts for any abnormalities in the insured company's insurance liability or parameters, sending these alerts to the insurance company to enable risk management. The system includes a data acquisition module, a list segmentation module, a prohibited-insurance marking module, a job category screening module, a data processing module, and a comparison and alerting module.
[0052] The data acquisition module is used to acquire historical claims data of each insured company that has cooperated with the system database. The historical claims data includes five-rate information data and false information markers. The five-rate information includes the reporting rate, disability rate, disability assessment rate, case settlement rate, and compensation rate.
[0053] The list segmentation module is used to set risk thresholds for each of the five rates of information based on historical claims data, as well as a threshold for the number of times false information is marked, and to segment all insured companies in the system database into a gray list or a black list.
[0054] The specific method for classifying all insured companies in the system database into a gray list or a black list is as follows:
[0055] S1.1. Preset the risk threshold of the five-rate information and divide it into gray lists;
[0056] Each of the five rates is preset with a risk threshold 1. If the historical claims rate of the insured company is greater than or equal to the risk threshold 1 for the claims rate, and the disability rate is greater than or equal to the risk threshold 1 for the disability rate, then the company will be classified into the gray list.
[0057] If the payout ratio of an insured company's historical claims data reaches 100%, it will be placed on a gray list.
[0058] If the disability assessment rate of the insured company's historical claims data is greater than or equal to the disability assessment rate risk threshold one, it will be classified into the gray list.
[0059] If the historical claims settlement rate of an insured company within the first-level time period is less than the first-level risk threshold, it will be placed on the gray list; the first-level time period can be set as 30 days for non-disability-related death cases.
[0060] S1.2 Obtain historical claims data of insured companies classified into the gray list, preset the risk threshold of the five-rate information, and reclassify the insured companies in the gray list into the black list.
[0061] Each of the five pre-set risk thresholds is 2. If the historical claims data of an insured company in the gray list has a disability rate greater than or equal to the disability rate risk threshold 2, and the disability assessment rate is greater than or equal to the disability assessment rate risk threshold 2, then the company will be included in the blacklist.
[0062] If the loss ratio of an insured company in the gray list reaches 100% and the claim rate is greater than or equal to the second risk threshold for claim rate, then it will be included in the blacklist.
[0063] If the loss ratio of an insured company in the gray list reaches 100% and the disability rate is greater than or equal to the second disability risk threshold, it will be included in the blacklist.
[0064] If the settlement rate of an insured company in the gray list is less than 100% within the second-level time period, it will be included in the blacklist; the second-level time period can be set as 60 days for non-disability-related death cases.
[0065] S1.3, Preset two thresholds for the number of times false information is marked, and divide the list into gray list or black list based on the two thresholds.
[0066] If the number of times false information is marked in the historical claims data of an insured company is greater than or equal to the threshold number one, but less than the threshold number two, then it will be included in the gray list.
[0067] If the number of times false information is marked in the historical claims data of an insured company is greater than or equal to the threshold number two, it will be included in the blacklist.
[0068] The "Prohibited Insurance Marking" module is used to perform multiple screenings on newly uploaded personnel lists for insured companies, including blacklisting, sensitive industry fields, prohibited insurance regions, and company qualifications. Based on the screening results, prohibited insurance marking is applied. The specific operation is as follows:
[0069] S2.1 Based on the personnel list uploaded by the insured company, determine the corresponding company name through four dimensions: policyholder, insured, labor relationship, and actual employer. Filter the company name according to the blacklist. If the company name exists in the blacklist, insurance is prohibited and a prohibition mark is made.
[0070] S2.2. For the list of personnel who have not been insured by companies on the blacklist after screening, filter the sensitive industry fields of the company name based on four dimensions, and mark the companies with sensitive industry fields as prohibited from insurance.
[0071] Obtain the personnel list data uploaded by the insured companies, and filter the company names in the list data based on four dimensions: policyholder, insured, labor relationship, and actual employer.
[0072] A database of sensitive industry fields is pre-set. Based on four dimensions of filtering, if a company name is found to contain sensitive industry fields, the company will be marked as prohibited from using the platform.
[0073] S2.3. Select companies without sensitive industry fields and filter them for prohibited areas;
[0074] The system retrieves the actual employment locations (accurate to the county / district level) of companies that do not have sensitive industry fields after filtering. If the actual employment unit belongs to a prohibited area, it is marked as prohibited.
[0075] S2.4. Obtain the business registration information of insured companies after filtering the prohibited areas based on third-party data interfaces, and filter based on two dimensions: enterprise qualification and enterprise size. Mark enterprises with individual business qualifications and enterprises with a size less than the threshold number of employees as prohibited from insurance.
[0076] The job category screening module is used to export insured companies that have not been marked as prohibited from insurance, and to screen the job categories of the personnel list uploaded by the insured companies for prohibited jobs.
[0077] The prohibited occupations include high-risk occupations, high-accident-rate occupations, and high-loss-rate occupations. High-risk occupations typically involve highly dangerous working environments or tasks, such as working at heights, deep-sea diving, and blasting operations, which are prone to serious personal injury accidents. High-accident-rate occupations, due to the nature or conditions of the work, have a high accident rate, and insurance companies deem the underwriting risk too high and therefore refuse to provide insurance. High-loss-rate occupations are those where accidents result in substantial payouts.
[0078] The data processing module is used to merge the insurance liability parameters and insurance underwriting parameters of various occupations in the gray list and standard comparison parameters to obtain merged data; the insurance liability parameters include disability ratio, sudden death insurance amount, traffic accident insurance amount limit and additional 24-hour limit; the insurance underwriting parameters include the proportion of over-age personnel, the proportion of personnel in the five occupational categories, the proportion of personnel in the four and five occupational categories, and the approval rate;
[0079] Among them, five categories of occupations represent the highest risk and extremely dangerous occupations, such as firefighters, police officers, deep-sea divers, and pilots; four categories of occupations represent relatively high risk occupations involving heavy physical labor, working at heights, and exposure to hazardous substances, such as miners, loggers, and chemical workers.
[0080] The percentage of the number of people in the five occupational categories represents the proportion of the number of people in the five occupational categories in the total number of people in the personnel list; the percentage of the number of people in the four occupational categories and five occupational categories represents the proportion of the number of people in the four occupational categories and five occupational categories in the total number of people in the personnel list; the revision rate represents the percentage of the number of times the current policyholder has been replaced in the total number of people in the personnel list.
[0081] The comparison and prompt module is used to compare the list of personnel whose occupations are not marked as prohibited from insurance by the insured companies with the insurance liability parameters or insurance application parameters in the merged data, and to provide anomaly prompts.
[0082] The personnel list uploaded by the insured company includes different job types and their corresponding insurance liability parameters, as well as insurance application parameters.
[0083] The method for comparing the list of personnel from insured companies whose occupations are not marked as prohibited from insurance with the insurance liability parameters in the merged data is as follows:
[0084] If the insured company is not on the gray list, the insurance liability parameters of various types of work are taken from the merged data and compared with the insurance liability parameters of each type of work in the personnel list of the insured company.
[0085] If the insured company is on the gray list, the merged data will take the insurance liability parameters for each job type of the insured company in the gray list and compare them with the corresponding job type insurance liability parameters in the insured company's personnel list. If the gray list does not have insurance liability parameters for the job type of the insured company, the merged data will take the overall insurance liability parameters for the insured company in the gray list and compare them with the corresponding job type insurance liability parameters in the insured company's personnel list. The overall insurance liability parameters are uniform insurance liability parameter restrictions set for all job types of the insured company in the gray list. All job types of the company must be configured under the overall insurance liability parameters when determining the insurance liability parameters. If the gray list does not have overall insurance liability parameters for the insured company, the merged data will take the insurance liability parameters for the job type of the standard comparison parameters and compare them with the corresponding job type insurance liability parameters in the insured company's personnel list.
[0086] The personnel list is compared with the insurance underwriting parameters in the merged data, specifically as follows:
[0087] If the insured company is not in the gray list, the merged data takes the insurance underwriting parameters of the standard comparison parameters and compares them with the insurance underwriting parameters in the personnel list of the insured company.
[0088] If the insured company is on the gray list, the data is merged, and the insurance application parameters of the gray list are compared with the insurance application parameters in the personnel list of the insured company.
[0089] In this embodiment, examples of insurance liability parameters and insurance underwriting parameters in the merged data are given below:
[0090] The standard insurance liability parameters are 5% for disability ratio, 50% for sudden death coverage, 50% for traffic accident coverage, and allowance for an additional 24 hours.
[0091] The insurance liability parameters for the gray list are: 1% disability ratio, 30% coverage for sudden death, 30% limit on coverage for traffic accidents, and prohibition of additional 24-hour coverage.
[0092] The insurance underwriting parameters are: 10% of the insured are over-age, 10% of the insured are in the five occupational categories, 15% of the insured are in the four or five occupational categories, and the approval rate is 10%.
[0093] The system compares the personnel list with the insurance liability parameters or insurance application parameters in the merged data. If any insurance liability parameter for a job in the personnel list uploaded by the insured company is greater than the corresponding insurance liability parameter value in the merged data, an abnormal information prompt for insurance liability adjustment will be issued. The abnormal information prompt will be output through the customer risk management system, reminding the insured company that the insurance liability parameter for that job in the insurance plan must not exceed the insurance liability parameter in the merged data.
[0094] If any insurance application parameter in the personnel list data uploaded by the insured company exceeds the corresponding insurance application parameter value, an abnormal insurance application adjustment information prompt will be issued. This customer risk management output will alert the insured company that the relevant insurance application parameter in their insurance plan must not exceed the insurance application parameter in the merged data.
[0095] Example 2
[0096] In conjunction with the steps in Embodiment 1, in this embodiment, in order to enable insurance companies to temporarily open up to specific insured companies or restricted occupations, the list division module in the customer risk management system of the personal injury insurance product is also equipped with a whitelist. The whitelist is used to store the insured companies and restricted occupations that are temporarily open, and the companies and occupations stored in the whitelist can be temporarily unrestricted.
[0097] In this embodiment 1, the data acquisition module, the list division module, and the prohibited insurance marking module implement the aforementioned content. After the newly uploaded personnel list is screened and marked as prohibited insurance by multiple screenings, a white list of temporarily open prohibited insurance companies is set up. The prohibited insurance companies are screened through the white list and temporarily unbanned.
[0098] The job selection module exports insured companies that have not been marked as prohibited or temporarily unbanned, and filters the job categories in the personnel list uploaded by the insured companies for prohibited jobs; it sets a whitelist of temporarily open prohibited jobs, and uses the whitelist to unban prohibited jobs for insured companies that have not been marked as prohibited or temporarily unbanned.
[0099] The whitelist stores the job types and their respective insured companies after the ban is lifted.
[0100] The data processing module merges the insurance liability parameters and insurance application parameters for various occupations in the gray list, white list, and standard comparison parameters to obtain merged data. The insurance liability parameters include the disability ratio, sudden death coverage, traffic accident coverage limit, and additional 24-hour limit. The insurance application parameters include the proportion of over-age personnel, the proportion of personnel in the five occupational categories, the proportion of personnel in the four and five occupational categories, and the approval rate.
[0101] The comparison and prompt module compares the unbanned insurance markers after the unbanning process with the personnel list of temporarily unbanned insured companies with the insurance liability parameters or insurance underwriting parameters in the merged data, and provides an anomaly prompt;
[0102] If the insured company is not on the gray list or white list, the insurance liability parameters of various types of work are taken from the merged data and compared with the insurance liability parameters of each type of work in the personnel list of the insured company.
[0103] If the insured company is in the gray list or white list, then determine whether its job type is in the gray list or white list. If the job type is determined to be in the gray list, or in both the white list and the gray list, then merge the data and take the insurance liability parameters of the job type in the gray list and compare them with the insurance liability parameters of the job type in the insured company's personnel list.
[0104] If it is determined that the job type is only on the whitelist, the data is merged and the insurance liability parameters of the job type in the whitelist are compared with the insurance liability parameters of the job type in the list of personnel of the insured company.
[0105] If the job type is determined not to be in the gray list or white list, the merged data will take the overall insurance liability parameters of the insured company in the gray list and compare them with the insurance liability parameters of the job type in the personnel list of the insured company; if the overall insurance liability parameters of the insured company are not in the gray list, the merged data will take the insurance liability parameters of the job type with the standard comparison parameters and compare them with the insurance liability parameters of the job type in the personnel list of the insured company.
[0106] The personnel list is compared with the insurance underwriting parameters in the merged data, specifically as follows:
[0107] If the insured company is not in the gray list or white list, the insurance application parameters of the merged data standard comparison parameters are compared with the insurance application parameters in the personnel list of the insured company.
[0108] If the insured company is on the gray list, or is on both the gray list and the white list, the data is merged and the insurance application parameters of the gray list are compared with the insurance application parameters of the personnel list of the insured company.
[0109] If the insured company is only on the whitelist, the data is merged, and the insurance application parameters of the whitelist are compared with the insurance application parameters of the personnel list of the insured company.
[0110] In this embodiment, examples of insurance liability parameters and insurance underwriting parameters in the merged data are given below:
[0111] The standard insurance liability parameters are 5% for disability ratio, 50% for sudden death coverage, 50% for traffic accident coverage, and allowance for an additional 24 hours.
[0112] The insurance liability parameters for the gray list are: 1% disability ratio, 30% coverage for sudden death, 30% limit on coverage for traffic accidents, and prohibition of additional 24-hour coverage.
[0113] The insurance liability parameters for the whitelist are: 10% disability ratio, 100% coverage for sudden death, 100% limit on coverage for traffic accidents, and allowance for an additional 24 hours.
[0114] The insurance underwriting parameters are: 10% of the insured are over-age, 10% of the insured are in the five occupational categories, 15% of the insured are in the four or five occupational categories, and the approval rate is 10%.
[0115] The system compares the personnel list with the insurance liability parameters or insurance application parameters in the merged data. If any insurance liability parameter for a job in the personnel list uploaded by the insured company is greater than the corresponding insurance liability parameter value in the merged data, an abnormal information prompt for insurance liability adjustment will be issued. The system will output an abnormal information prompt, reminding the insured company that the insurance liability parameter for that job in the insurance plan must not exceed the insurance liability parameter in the merged data.
[0116] If any insurance application parameter in the personnel list data uploaded by the insured company exceeds the corresponding insurance application parameter value, an abnormal insurance application adjustment information prompt will be issued. The system will output an abnormal information prompt, reminding the insured company that the relevant insurance application parameter in the insurance plan must not exceed the insurance application parameter in the merged data.
[0117] Finally, an electronic device is also provided, including a processor and a memory, wherein the processor executes the customer risk management system of the personal injury insurance product as described above when executing program data stored in the memory.
Claims
1. A customer risk management system for personal injury insurance products that uses a whitelist to enforce the lifting of restrictions on coverage, characterized in that, It includes a data acquisition module, a list segmentation module, a prohibited protection marking module, a job type screening module, a data processing module, and a comparison prompt module; The data acquisition module is used to acquire historical claims data of each cooperating insured company in the system database. The historical claims data includes five-rate information data and false information markers. The five-rate information includes the reporting rate, disability rate, disability assessment rate, case settlement rate, and payout rate. The list segmentation module is used to set risk thresholds for each of the five rates of information based on historical claims data, as well as a threshold for the number of times false information is marked, to segment all insured companies in the system database into a gray list or a black list. The prohibited insurance marking module is used to perform multiple screenings on newly uploaded personnel lists of insured companies, including blacklists, sensitive industry fields, prohibited insurance areas, and company qualifications, and mark them as prohibited insurance based on the screening results; The job category screening module is used to export insured companies that have not been marked as prohibited from insurance, and to screen the job categories of the personnel list uploaded by the insured companies for prohibited jobs. The data processing module is used to merge the insurance liability parameters and insurance application parameters of various occupations in the gray list, white list, and standard comparison parameters to obtain merged data; the insurance liability parameters include disability ratio, sudden death coverage, traffic accident coverage limit and additional 24-hour limit; the insurance application parameters include the proportion of over-age personnel, the proportion of personnel in the five occupational categories, the proportion of personnel in the four and five occupational categories, and the approval rate; The comparison and prompt module is used to compare the list of personnel whose occupations are not marked as prohibited from insurance by the insured companies after screening with the insurance liability parameters or insurance application parameters in the merged data, and to provide anomaly prompts. The list segmentation module also includes a whitelist, which stores temporarily open insured companies and restricted occupations. Companies and occupations stored in the whitelist can be temporarily unblocked. After the newly uploaded personnel list is screened and marked as uninsurable, a whitelist of temporarily open uninsurable companies is set up. The whitelist is used to screen the uninsurable companies and temporarily unblock them. The job selection module exports insured companies that have not been marked as prohibited or temporarily unbanned, and selects prohibited jobs from the job categories in the personnel list uploaded by the insured companies. A whitelist of temporarily open prohibited occupations is set up. The whitelist is used to unban prohibited occupations of insured companies that are not marked as prohibited or whose prohibitions are temporarily lifted. The whitelist stores the unbanned occupations and their respective insured companies. The comparison and prompting module also includes comparing the unbanned insurance markers after the unbanning process with the personnel list of temporarily unbanned insured companies with the insurance liability parameters in the merged data, and issuing an anomaly prompt; If the insured company is not on the gray list or white list, the insurance liability parameters of various types of work are taken from the merged data and compared with the insurance liability parameters of each type of work in the personnel list of the insured company. If the insured company is in the gray list or white list, then determine whether its job type is in the gray list or white list. If the job type is determined to be in the gray list, or in both the white list and the gray list, then merge the data and take the insurance liability parameters of the job type in the gray list, and compare them with the insurance liability parameters of the job type in the insured company's personnel list. If it is determined that the job type is only on the whitelist, the data is merged and the insurance liability parameters of the job type in the whitelist are compared with the insurance liability parameters of the job type in the list of personnel of the insured company. If the job type is determined not to be in the gray list or white list, the merged data will take the overall insurance liability parameters of the insured company in the gray list and compare them with the insurance liability parameters of the job type in the personnel list of the insured company; if the overall insurance liability parameters of the insured company are not in the gray list, the merged data will take the insurance liability parameters of the job type with the standard comparison parameters and compare them with the insurance liability parameters of the job type in the personnel list of the insured company. The personnel list is compared with the insurance application parameters in the merged data. If the insured company is not in the gray list or white list, the merged data takes the standard comparison parameters of the insurance application parameters and compares them with the insurance application parameters in the personnel list of the insured company. If the insured company is on the gray list, or is on both the gray list and the white list, the data is merged and the insurance application parameters of the gray list are compared with the insurance application parameters of the insured company's personnel list; if the insured company is only on the white list, the data is merged and the insurance application parameters of the white list are compared with the insurance application parameters of the insured company's personnel list.
2. The customer risk management system for personal injury insurance products according to claim 1, characterized in that, The list segmentation module segments all insured companies in the system database into either a gray list or a black list. The specific method is as follows: Step 1: Preset the risk threshold of the five rates and divide the data into gray lists; Each of the five rates is preset with a risk threshold 1. If the historical claims rate of the insured company is greater than or equal to the risk threshold 1 for the claims rate, and the disability rate is greater than or equal to the risk threshold 1 for the disability rate, then the company will be classified into the gray list. If the payout ratio of an insured company's historical claims data reaches 100%, it will be placed on a gray list. If the disability assessment rate of the insured company's historical claims data is greater than or equal to the disability assessment rate risk threshold one, it will be classified into the gray list. If the historical claims settlement rate of an insured company within the first-level time period is less than the settlement rate risk threshold one, it will be classified into the gray list. Step 2: Obtain the historical claims data of the insured companies that have been assigned to the gray list, preset the risk threshold of the five-rate information as two, and reclassify the insured companies in the gray list into the black list. Each of the five pre-set risk thresholds is 2. If the historical claims data of an insured company in the gray list has a disability rate greater than or equal to the disability rate risk threshold 2, and the disability assessment rate is greater than or equal to the disability assessment rate risk threshold 2, then the company will be included in the blacklist. If the loss ratio of an insured company in the gray list reaches 100% and the claim rate is greater than or equal to the second risk threshold for claim rate, then it will be included in the blacklist. If the loss ratio of an insured company in the gray list reaches 100% and the disability rate is greater than or equal to the second disability risk threshold, it will be included in the blacklist. If the settlement rate of an insured company in the gray list is less than 100% within the second-level time period, it will be included in the blacklist. Step 3: Preset two thresholds for the number of times false information is marked, and then divide the list into a gray list or a black list based on these two thresholds. If the number of times false information is marked in the historical claims data of an insured company is greater than or equal to the threshold number one, but less than the threshold number two, then it will be included in the gray list. If the number of times false information is marked in the historical claims data of an insured company is greater than or equal to the threshold number two, it will be included in the blacklist.
3. The customer risk management system for personal injury insurance products according to claim 1, characterized in that, The prohibited insurance marking module performs multiple screenings on the insured companies in the uploaded personnel list, including blacklisting, sensitive industry fields, prohibited regions, and company qualifications. Based on the screening results, it marks the companies as prohibited from insurance, specifically including: Based on the personnel list uploaded by the insured companies, the corresponding company names are determined through four dimensions: the policyholder, the insured, the labor relationship, and the actual employer. The company names are then filtered according to the blacklist. If the company name exists in the blacklist, insurance is prohibited and a prohibition mark is made. For the list of personnel who were not insured by companies on the blacklist after screening, the company name sensitive industry fields were filtered based on four dimensions, and companies with sensitive industry fields were marked as prohibited from insurance. Filter companies without sensitive industry fields for restricted areas; The business registration information of insured companies after filtering out prohibited areas is obtained through a third-party data interface. The companies are then filtered based on two dimensions: company qualifications and company size. Companies with sole proprietorship qualifications or companies with fewer than the threshold number of employees are marked as prohibited from insurance.
4. The customer risk management system for personal injury insurance products according to claim 3, characterized in that, The process involves filtering companies by sensitive industry fields in their names based on four dimensions, and marking companies with sensitive industry fields as prohibited from using the platform. The specific steps are as follows: Obtain the personnel list data uploaded by the insured companies, and filter the company names in the list data based on four dimensions: policyholder, insured, labor relationship, and actual employer. A database of sensitive industry fields is pre-set. Based on four dimensions of filtering, if a company name is found to contain sensitive industry fields, the company will be marked as prohibited from using the platform.
5. The customer risk management system for personal injury insurance products according to claim 1, characterized in that, The comparison and prompting module compares the insurance liability parameters or insurance underwriting parameters in the merged data and provides an anomaly prompt. The specific method is as follows: If any insurance liability parameter for a job in the personnel list data uploaded by the insured company is greater than the corresponding insurance liability parameter value in the merged data, an abnormal information prompt for insurance liability adjustment will be issued. If any insurance application parameter in the personnel list data uploaded by the insured company is greater than the corresponding insurance application parameter value, an abnormal insurance application adjustment information prompt will be issued.
6. An electronic device, characterized in that, It includes a processor and a memory, wherein the processor executes program data stored in the memory to run a customer risk management system for a personal injury insurance product as described in any one of claims 1-5.