Methods, devices, electronic equipment, and storage media for determining claims settlement plans

Abstract

This disclosure provides a method, apparatus, electronic device, and storage medium for determining a claims settlement plan, relating to the field of insurance information technology. The specific implementation involves: obtaining basic information about the insured and payment rules for the current claims settlement plan; determining corresponding claims cases from historical data based on this basic information; calculating the current payment data based on the claims case and the payment rules; and, if the current payment data meets the expected value, using the current claims settlement plan as the target claims settlement plan. Using this method, claims cases with high reference value can be selected from historical data, and then calculated in conjunction with the current payment rules to obtain the most accurate payment data. Based on this data, a reasonable target claims settlement plan can be determined. This method does not rely on manual intervention, the determination process is fast and efficient, and the results are highly reliable.

Description

Technical Field

[0001] This disclosure relates to the field of insurance information technology, and in particular to a method, apparatus, electronic device and storage medium for determining a claims settlement plan. Background Technology

[0002] When designing insurance products, it is often necessary to formulate a claims plan tailored to each user's characteristics and current situation, and to estimate whether the newly formulated claims plan meets the compensation requirements. In related technologies, this step is highly dependent on manual labor: quotation personnel need to first find the company's historical insurance data in the database, then combine experience to develop specific compensation plans and predict the compensation outcome. This method not only requires a significant amount of time to retrieve and read historical data, but also carries considerable risk due to inaccurate historical data selection or human estimation errors, leading to unreasonable claims plan design. Summary of the Invention

[0003] This disclosure provides a method, apparatus, electronic device, and storage medium for determining a claims settlement plan.

[0004] According to one aspect of this disclosure, a method for determining a claims settlement plan is provided, comprising:

[0005] Obtain basic information and payout rules for the insured under the current claims plan; determine the corresponding claims case from historical data based on the basic information; calculate the current payout data based on the claims case and the payout rules; if the current payout data meets the expected value, use the current claims plan as the target claims plan.

[0006] According to another aspect of this disclosure, an apparatus for determining a claims settlement plan is provided, comprising:

[0007] The acquisition module is used to obtain basic information about the insured and the compensation rules for the current claims plan.

[0008] The case identification module is used to identify the corresponding claim cases from historical data based on this basic information;

[0009] The calculation module is used to calculate the current compensation data based on the claim case and the compensation rule information;

[0010] The first solution module is used to select the current claim settlement plan as the target claim settlement plan if the current claim settlement data meets the expected value.

[0011] According to another aspect of this disclosure, an electronic device is provided, comprising:

[0012] At least one processor; and

[0013] The memory is communicatively connected to the at least one processor; wherein,

[0014] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the methods in any embodiment of this disclosure.

[0015] According to another aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions for causing a computer to perform the methods of any embodiment of this disclosure.

[0016] This approach allows for the selection of high-value claim cases from historical data, which are then combined with current payout rules to calculate the most accurate payout data. Based on this data, a reasonable target payout plan can be determined. This approach is independent of manual processes, making the determination process fast, efficient, and highly reliable.

[0017] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0018] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein:

[0019] Figure 1 This is a flowchart illustrating a method for determining a claims settlement plan according to an embodiment of the present disclosure;

[0020] Figure 2 This is a flowchart illustrating a method for determining a claims settlement scheme according to another embodiment of this disclosure;

[0021] Figure 3 This is a flowchart illustrating a claims settlement data input method according to an embodiment of the present disclosure;

[0022] Figure 4 This is a schematic flowchart of a calculation method according to an embodiment of the present disclosure;

[0023] Figure 5 This is a schematic diagram of the structure of a claims settlement scheme determination device according to an embodiment of the present disclosure;

[0024] Figure 6 This is a schematic diagram of the structure of a claims settlement scheme determination device according to another embodiment of the present disclosure;

[0025] Figure 7 A block diagram of an electronic device used to implement the method for determining a claims settlement scheme according to embodiments of the present disclosure. Detailed Implementation

[0026] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0027] In this document, the term "and / or" merely describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. The term "at least one" in this document indicates any combination of at least two of a plurality of elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C. The terms "first" and "second" in this document refer to and distinguish between multiple similar technical terms, not to restrict the order or to limit there to only two. For example, "first feature" and "second feature" refer to two categories / two features; the first feature can be one or more, and the second feature can also be one or more.

[0028] Furthermore, to better illustrate this disclosure, numerous specific details are set forth in the following detailed description. Those skilled in the art will understand that this disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of this disclosure.

[0029] This disclosure provides a method for determining a claims settlement plan, such as... Figure 1 As shown, the method includes:

[0030] Step S101: Obtain the basic information of the insured and the compensation rules for the current claims plan;

[0031] Step S102: Determine the corresponding claim cases from historical data based on this basic information;

[0032] Step S103: Calculate the current payout data based on the claim case and the payout rules information;

[0033] Step S104: If the current payout data meets the expected value, the current claim settlement plan shall be taken as the target claim settlement plan.

[0034] In one example, the current claims settlement plan in step S101 is also called the predicted claims settlement plan. The insured is the policyholder, who can be an individual or a group. Basic information refers to various data describing the characteristics of the insured. If it is an individual, the basic information of the insured can be the policyholder's age, gender, occupation, etc.; if the insured is a group, the basic information can be the group's business type, number of people, gender ratio, specific occupations, etc. Claims rule information refers to various claims details in the claims settlement plan, such as the agreed sum insured, deductible, payout ratio, number of payouts, etc.

[0035] Next, in step S102, based on the basic information, relevant claim cases are selected from historical data as the basic calculation data. Claim cases are case materials for claims that have been filed or have already been paid out, such as doctor's diagnosis certificates, hospital invoices, etc. The user objects corresponding to the above claim cases need to have certain commonalities with the insured objects so that the compensation data calculated using the claim cases has high reference value. The specific scope of claim cases can be flexibly set according to the actual situation. It can be that all the reimbursement application documents of a certain type of user in one year are used as claim cases, or relevant documents from the past five years can be used as claim cases.

[0036] Then, in step S103, based on the claims case, the payout rules information in the current claims plan is used to calculate, that is, the new current claims plan is assigned to the historical claims case to obtain specific payout data, which includes payout ratio, premium ratio, etc.

[0037] Finally, in step S104, the obtained compensation data is compared with the expected compensation data. If the compensation data meets the expected range, the current compensation plan can be considered to meet the requirements and can be reported to the customer as a mature target compensation plan.

[0038] Of course, you can also slightly adjust the parameters in the compensation rules information according to the actual situation, and use the above scheme to calculate the corresponding compensation data, observe the impact of parameter changes on the actual compensation data, and thus obtain a reasonable and optimal target compensation plan.

[0039] In the process of predicting insurance claim settlement plans, existing technologies generally involve directly finding the payout rules for similar users and applying them directly or with slight modifications. However, this method struggles to meet the personalized needs of insured users and can easily lead to unsatisfactory payout data. The approach described above, instead of using historical payout rules, identifies valuable claim cases as historical data. These cases are then used as historical data to apply new payout rules, and specific payout data is calculated. The reasonableness of this payout data is then used to determine the target claim settlement plan. This method predicts payout data without relying on manual experience-based estimation, efficiently generating reasonable claim settlement plans, obtaining more accurate predictions, and demonstrating high reliability.

[0040] This disclosure provides another method for determining a claims settlement plan, such as... Figure 2 As shown, the method includes:

[0041] Step S201: Obtain the basic information of the insured and the compensation rules for the current claims plan;

[0042] Step S202: Determine the corresponding claim cases from historical data based on this basic information;

[0043] Step S203: Calculate the current payout data based on the claim case and the payout rules information;

[0044] Step S204: If the current payout data meets the expected value, then use the current claim settlement plan as the target claim settlement plan;

[0045] Step S205: If the current payout data does not meet the expected value, adjust the payout rule information and determine the target claim settlement plan based on the adjusted payout rule information.

[0046] The specific implementation methods of steps S201-S204 are similar to those of steps S101-S104, and will not be repeated here.

[0047] In one example, in step S205, if the current payout data does not meet the expected value, the parameters in the current payout rule are adjusted. Then, using the claim case obtained in step S202, the adjusted payout rule is used to calculate the new payout data, which is then compared with the expected value. This process is repeated until the payout data meets the expected value. During the adjustment process, the adjustment range of each parameter in the payout rule can be calculated based on the calculation method, and adjustments can then be made within that range. If multiple adjustment results are obtained, BI (Business Intelligence) visualization can be used to compare multiple payout rules and their corresponding payout data in the form of reports, allowing relevant personnel to more intuitively and clearly select the optimal solution. Using the above example, when the payout does not meet expectations, relevant parameters can be flexibly adjusted to ultimately obtain payout data that meets the preset payout plan.

[0048] In one embodiment, step S205 may further include the following steps:

[0049] Based on the comparison between the current payout data and the expected value, different parameters in the payout rule information are adjusted to obtain multiple adjusted payout rule information.

[0050] Based on the revised compensation rules and the claims case, the corresponding revised compensation data were calculated.

[0051] By comparing the adjusted claim data from multiple sources, a target claims settlement plan can be determined.

[0052] By following the steps described above, we can first determine which parameters in the payout rules need adjustment and the range of adjustment based on the gap between the current payout data and the expected value; or directly provide the optimal payout ratio or optimal number of payouts as a reference. Within the given adjustment range, the parameters can be flexibly adjusted to obtain multiple adjusted payout rule information. For example, in the current payout rules, the payout ratio for general outpatient services is 50%, and the payout ratio for inpatient services is 30%. Calculations show that the payout data corresponding to this rule does not meet the requirements. To meet the requirements, the payout ratio for general outpatient services should be reduced to 40%, or the payout ratio for inpatient services should be reduced to 10%. Based on this, we can adjust the relevant parameters to obtain multiple adjusted payout rule information. Then, using the claim cases obtained from historical data in step S202 above, we can obtain different payout data based on different adjusted payout rules. By comparing these different payout data, we can select the optimal payout data and its corresponding payout rule to obtain the target claim plan. During the screening process, we can also use BI visualization to perform horizontal comparisons to facilitate screening. Using the above embodiment, multiple adjustment options can be selected simultaneously within a reasonable range, and the optimal option can be chosen as the target claim settlement plan through horizontal comparison. This eliminates the need for manual, aimless adjustments and repetitive calculations, significantly improving the overall efficiency of the claims process.

[0053] In one embodiment, step S102 or S202 specifically includes:

[0054] Based on this basic information, multiple reference objects are identified from historical data; among these multiple reference objects, those that meet the criteria for similarity to the insured are identified; and claims cases of the eligible reference objects are obtained.

[0055] Specifically, the process begins by filtering historical data to identify reference targets that share commonalities with the insured. For example, if the insured is an internet company with approximately 100 employees and a male-to-female ratio of 9:1, then an internet company with approximately 110 employees and an unclear male-to-female ratio could also serve as a reference target. Similarly, an import / export company with approximately 100 employees could also be considered. Multiple reference targets sharing commonalities with the insured are selected based on this. Then, reference targets meeting the similarity criteria are chosen from these multiple reference targets. Here, similarity can be quantified for filtering. For instance, for group insured individuals, the number of insured individuals, their male-to-female ratio, and industry type are all considered attributes of the insured. Each attribute is pre-assigned a weight, which can be flexibly set according to different insurance plans. Then, based on the shared attributes and corresponding weights between the insured and reference targets, the degree of similarity is quantified. By applying a pre-set similarity threshold, reference targets meeting the threshold are identified as eligible reference targets. Then, based on the payout rules or forecasting needs, relevant claim cases for eligible reference targets are obtained. For example, to forecast payout data within one year, claim cases within one year are obtained. This method allows for flexible selection of reference targets based on current plan information, thereby choosing the most comprehensive and accurate claim cases from historical data. Furthermore, it avoids the risk of data leakage caused by manually extracting system data.

[0056] In one example, the step "determine multiple reference objects from historical data based on the basic information" can specifically include: determining multiple attributes of the insured object based on the basic information; determining multiple reference objects from historical data, where the multiple attributes of each reference object at least partially overlap with the multiple attributes of the insured object. In practice, multiple specific attributes can be obtained from the insured object's basic information through manual input or intelligent reading, such as industry attributes, age attributes (mainly referring to age distribution ranges), gender ratio attributes, etc. After obtaining the multiple attributes of the insured object, reference objects with overlapping attributes are searched among the massive number of users included in the historical data. Overlap refers to attribute values ​​or attribute ranges being the same or similar, which can be understood as attributes having "commonality." For example, in the "age attribute," ages between 15 and 20 years old are considered overlapping age attributes. The definition of overlap can be flexibly determined according to the actual situation. Generally speaking, the insured object may have N attributes, and each user in the historical data has M attributes. If at least one attribute overlaps between N and M, the user can be used as a reference object.

[0057] In one example, suppose we need to design a claims plan for a new education and training company with 100 employees. While there's no historical data on companies of similar size and industry size, the database contains data on tens of thousands of employees in the education and training sector. We can filter this company by certain attributes (such as gender or age) and use these 100 employees as references to obtain relevant claims cases. Alternatively, we can use other companies in the database with a size of 100 as references. This approach allows for flexible selection of multiple users most closely related to the insured as references, ensuring the most accurate claims data calculated based on these references.

[0058] In one example, the claims rules information may include liability information and special provisions. Liability information includes outpatient liability, inpatient liability, accident liability, etc., and may include one or more items; these are standard insurance provisions. Special provisions are additional supplementary information, such as "dental care can be reimbursed up to 3 times," which is outside the scope of standard insurance coverage. Special provisions can be linked to liability information; when there is a conflict between "special provisions" and "liability information," the special provisions take precedence over the liability information.

[0059] Specifically, when obtaining the insured information and compensation information of the current claims settlement plan in the above steps S101 or S201, it is generally done by manual input, such as... Figure 3 As shown, you should first enter the basic information of the current claim plan. The basic information should include at least the information of the insured, and may also include other basic information, such as the claim company, the claim type, etc.

[0060] In one example, the system can automatically generate corresponding liability information and alternative special agreements based on the input basic information, allowing users to complete the input by selecting options. This prevents omissions and improves input efficiency. In another example, the liability information and special agreements can also be entered manually. In this example, the input order of the basic information, liability information, and special agreements for the current claims plan is not restricted.

[0061] In one example, when performing specially agreed-upon input, a "template-based" input method can also be used to ensure that the input process is convenient, easy, and complete.

[0062] After entering the basic information and compensation rules, corresponding claim cases can be found from historical data. If the coverage of claim cases is insufficient, the "similarity" threshold can be adjusted to include claim cases with lower similarity to ensure high data coverage. Then, the data is aggregated and combined, which involves combining historical claim cases with the new compensation rules information in the current plan to calculate the current compensation data.

[0063] In the prior art, claims prediction is usually based only on routine liability. In this disclosure, the claims rules are divided into routine liability information and special agreements. The intelligent input can better combine with the actual claims scenarios and ensure that the claims data calculated using the claims rules is more accurate.

[0064] In one embodiment, the step of calculating the current compensation data in step S103 or S203 specifically includes: obtaining the invoice information and / or medical record information of the claim case; generating a claims settlement rule based on the basic compensation rule and / or special compensation rule, wherein the basic compensation rule is obtained based on the regular liability information, and the special compensation rule is obtained based on the special agreement information; and calculating the current compensation data based on the invoice information and / or medical record information using the claims settlement rule. Specifically, as shown... Figure 4 As shown, before calculation, basic data needs to be obtained, such as all invoice information, medical records, etc., initiated by all users of similar-sized insurance plans within the previous year, as basic settlement data. Then, standard liability information and special agreement information are determined. Basic compensation rules are derived from the standard liability information, and special compensation rules are derived from the special agreement information. The basic and special compensation rules are combined to generate settlement rules (settlement methods). It is important to emphasize that these settlement rules may include more than one settlement method, such as annual deductible settlement, per-claim settlement, tiered per-claim settlement, allowance settlement, etc. Then, specific settlement calculations are performed according to different settlement methods to obtain the settlement results. If there are multiple settlement methods, they can be calculated in parallel. Finally, the settlement results are summarized to obtain the current settlement data. Using the above scheme, accurate settlement calculations can be performed by combining standard liability information and special agreement information, resulting in highly reliable settlement data.

[0065] In summary, the methods for determining any of the above-mentioned claims settlement options first involve mining relevant claims cases from historical data as basic settlement data. Then, this basic settlement data is assigned the current claims rule information to be evaluated. This claims rule information includes liability information (sum insured, deductible, payout ratio) and special provisions information (such as the hospital visited, number of claims, whether medical insurance is used for settlement, etc.). Both claims cases and claims rule information are factors that significantly influence the claims data results. Selecting them through the above method ensures that the claims cases and claims rule information are optimal, resulting in the most accurate claims data, and allows for a relatively precise assessment of the impact of changes in liability and special provisions on the claims data (mainly the payout ratio).

[0066] like Figure 5 As shown, an embodiment of this disclosure provides a claims settlement plan determination device 500, the device comprising:

[0067] The acquisition module 501 is used to acquire basic information about the insured and the compensation rules for the current claims plan.

[0068] The case determination module 502 is used to determine the corresponding claim cases from historical data based on the basic information.

[0069] The calculation module 503 is used to calculate the current compensation data based on the claims case and the compensation rule information;

[0070] The first solution module 504 is used to select the current claim settlement plan as the target claim settlement plan when the current claim settlement data meets the expected value.

[0071] like Figure 6 As shown, an embodiment of this disclosure provides an apparatus 600 for determining another claims settlement plan, the apparatus comprising:

[0072] The acquisition module 601 is used to acquire the basic information of the insured and the compensation rules information of the current claims plan;

[0073] The case determination module 602 is used to determine the corresponding claim cases from historical data based on the basic information.

[0074] The calculation module 603 is used to calculate the current compensation data based on the claims case and the compensation rule information;

[0075] The first solution module 604 is used to take the current claim settlement plan as the target claim settlement plan when the current claim settlement data meets the expected value.

[0076] The second solution module 605 is used to adjust the compensation rule information and determine the target compensation solution based on the adjusted compensation rule information when the current compensation data does not meet the expected value.

[0077] In one example, the second scheme module is used for:

[0078] Based on the comparison between the current payout data and the expected value, different parameters in the payout rule information are adjusted to obtain multiple adjusted payout rule information.

[0079] Based on the multiple adjusted compensation rules and the claims cases, the corresponding multiple adjusted compensation data are calculated respectively;

[0080] By comparing the multiple adjusted claim data, a target claim settlement plan is determined.

[0081] In any of the above devices, the case determination module is used for:

[0082] Based on the aforementioned basic information, multiple corresponding reference objects are determined from historical data;

[0083] Among the plurality of reference objects, identify reference objects that meet the criteria for similarity to the insured object;

[0084] Obtain claim cases of the eligible reference objects.

[0085] In any of the above device examples, determining the corresponding multiple reference objects from historical data based on the basic information includes:

[0086] Based on the basic information, multiple attributes of the insured object are determined;

[0087] Multiple reference objects are identified from historical data, and multiple attributes of each reference object at least partially overlap with multiple attributes of the insured object.

[0088] In any of the above device examples, the compensation rule information includes general liability information and / or special agreement information.

[0089] In any of the above device examples, the computing module is used for:

[0090] Obtain the invoice information and / or medical record information of the claims case;

[0091] Claims settlement rules are generated based on basic claims settlement rules and / or special claims settlement rules, wherein the basic claims settlement rules are obtained based on the general liability information, and the special claims settlement rules are obtained based on the special agreement information;

[0092] Based on the invoice information and / or medical record information, the current compensation data is calculated using the compensation rules.

[0093] The functions of each module in the apparatus of this disclosure embodiment can be found in the corresponding description in the above method, and will not be repeated here.

[0094] The acquisition, storage, and application of user personal information involved in the technical solution disclosed herein comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0095] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0096] Figure 7A schematic block diagram of an example electronic device 700 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0097] like Figure 7 As shown, device 700 includes a computing unit 701, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 702 or a computer program loaded from storage unit 708 into random access memory (RAM) 703. RAM 703 may also store various programs and data required for the operation of device 700. The computing unit 701, ROM 702, and RAM 703 are interconnected via bus 704. Input / output (I / O) interface 705 is also connected to bus 704.

[0098] Multiple components in device 700 are connected to I / O interface 705, including: input unit 706, such as keyboard, mouse, etc.; output unit 707, such as various types of monitors, speakers, etc.; storage unit 708, such as disk, optical disk, etc.; and communication unit 709, such as network card, modem, wireless transceiver, etc. Communication unit 709 allows device 700 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0099] The computing unit 701 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 701 performs the various methods and processes described above, such as the method for determining a claims settlement. For example, in some embodiments, the method for determining a claims settlement may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 708. In some embodiments, part or all of the computer program may be loaded and / or installed on device 700 via ROM 702 and / or communication unit 709. When the computer program is loaded into RAM 703 and executed by the computing unit 701, one or more steps of the method for determining a claims settlement described above may be performed. Alternatively, in other embodiments, the computing unit 701 may be configured to perform the method for determining a claims settlement by any other suitable means (e.g., by means of firmware).

[0100] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0101] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0102] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0103] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0104] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0105] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other.

[0106] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0107] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for determining a claims settlement plan, comprising: Obtain basic information and compensation rules information of the insured in the current claims settlement plan. The compensation rules information includes general liability information and / or special agreement information. When there is a conflict between the special agreement information and the general liability information, the special agreement information takes precedence over the general liability information. Based on the aforementioned basic information, the corresponding claim cases are determined from historical data; Based on the claims cases and the claims rules information, the current claims data is calculated; If the current payout data meets the expected value, the current claim settlement plan will be used as the target claim settlement plan; If the current payout data does not meet the expected value, adjust the payout rule information and determine the target claim settlement plan based on the adjusted payout rule information; The process of adjusting the compensation rule information and determining the target claims settlement plan based on the adjusted compensation rule information includes: Based on the comparison between the current payout data and the expected value, different parameters in the payout rule information are adjusted to obtain multiple adjusted payout rule information. Based on the multiple adjusted compensation rules and the claims cases, the corresponding multiple adjusted compensation data are calculated respectively; By comparing the multiple adjusted claim data, a target claim settlement plan is determined.

2. The method according to claim 1, wherein, The step of determining the corresponding claim case from historical data based on the basic information includes: Based on the aforementioned basic information, multiple corresponding reference objects are determined from historical data; Among the plurality of reference objects, identify reference objects that meet the criteria for similarity to the insured object; Obtain claim cases of the eligible reference objects.

3. The method according to claim 2, wherein, The step of determining multiple reference objects from historical data based on the basic information includes: Based on the basic information, multiple attributes of the insured object are determined; Multiple reference objects are identified from historical data, and multiple attributes of each reference object at least partially overlap with multiple attributes of the insured object.

4. The method according to claim 1, wherein, The calculation of the current compensation data based on the claims cases and the compensation rule information includes: Obtain the invoice information and / or medical record information of the claims case; Claims settlement rules are generated based on basic claims settlement rules and / or special claims settlement rules, wherein the basic claims settlement rules are obtained based on the general liability information, and the special claims settlement rules are obtained based on the special agreement information; Based on the invoice information and / or medical record information, the current compensation data is calculated using the compensation rules.

5. A device for determining a claims settlement plan, comprising: The acquisition module is used to acquire basic information and compensation rule information of the insured object of the current claims plan. The compensation rule information includes regular liability information and / or special agreement information. When there is a conflict between the special agreement information and the regular liability information, the special agreement information takes precedence over the regular liability information. The case determination module is used to determine the corresponding claim cases from historical data based on the basic information. The calculation module is used to calculate the current compensation data based on the claims case and the compensation rule information; The first solution module is used to select the current claim settlement plan as the target claim settlement plan when the current claim settlement data meets the expected value. The second solution module is used to adjust the compensation rule information when the current compensation data does not meet the expected value, and to determine the target compensation solution based on the adjusted compensation rule information. The second scheme module is used for: Based on the comparison between the current payout data and the expected value, different parameters in the payout rule information are adjusted to obtain multiple adjusted payout rule information. Based on the multiple adjusted compensation rules and the claims cases, the corresponding multiple adjusted compensation data are calculated respectively; By comparing the multiple adjusted claim data, a target claim settlement plan is determined.

6. The apparatus according to claim 5, wherein, The case determination module is used for: Based on the aforementioned basic information, multiple corresponding reference objects are determined from historical data; Among the plurality of reference objects, identify reference objects that meet the criteria for similarity to the insured object; Obtain claim cases of the eligible reference objects.

7. The apparatus according to claim 6, wherein, The step of determining multiple reference objects from historical data based on the basic information includes: Based on the basic information, multiple attributes of the insured object are determined; Multiple reference objects are identified from historical data, and multiple attributes of each reference object at least partially overlap with multiple attributes of the insured object.

8. The apparatus according to claim 5, wherein, The calculation module is used for: Obtain the invoice information and / or medical record information of the claims case; Claims settlement rules are generated based on basic claims settlement rules and / or special claims settlement rules, wherein the basic claims settlement rules are obtained based on the general liability information, and the special claims settlement rules are obtained based on the special agreement information; Based on the invoice information and / or medical record information, the current compensation data is calculated using the compensation rules.

9. An electronic device, comprising: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-4.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-4.

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