CN113077349A - Pending claim fund preparing fund prediction method, device, equipment and storage medium - Google Patents
Pending claim fund preparing fund prediction method, device, equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention provides a pending claims fund preparing fund prediction method, a pending claims fund preparing fund prediction device, pending claims fund preparing fund prediction equipment and a pending claims fund preparing fund storage medium, wherein the pending claims fund preparing fund prediction method comprises the following steps: receiving a claim settlement request sent by terminal equipment; responding to the claim settlement request, and determining an initial claim amount according to the vehicle insurance information; according to the vehicle insurance information, at least one first preset loss estimation factor matched with the claim settlement object and at least one second preset loss estimation factor matched with the accident information are searched from a preset loss estimation factor data table; determining the estimated compensation amount of the pending compensation fund corresponding to the claim object according to the initial compensation amount, the at least one first preset loss estimation factor and the at least one second preset loss estimation factor; and displaying the estimated compensation amount of the pending compensation fund to a user through the terminal equipment. The method provided by the embodiment can effectively estimate the pending claim fund in time, thereby avoiding the problem of insufficient pending claim fund.
Description
Technical Field
The embodiment of the invention relates to the technical field of insurance, in particular to a pending claims fund forecasting method, a pending claims fund forecasting device, pending claims fund forecasting equipment and a pending claims fund forecasting storage medium.
Background
With the development of science and technology and economy, the insurance industry is getting larger and larger, and various insurance widely appears in the lives of people.
With the enhancement of insurance awareness, the related problem of pending claim fund is also more and more appreciated by the insured, and how to scientifically and accurately estimate the pending claim fund is of great significance. Currently, when a user has an insurance accident and requests insurance funds from an insurance company, a series of claims checking processes are required, and in the claims checking processes, the insurance company needs to extract the reserve funds for dealing with the unpaid insurance funds.
The conventional insurance fund deposit is usually carried out initial estimation according to past experience and the like under the condition that a case is not investigated and damaged, a pending claim fund of vehicle insurance is calculated simply, and more accurate damage estimation calculation is carried out such as investigation and damage determination along with the progress of the case. However, the prior art causes great damage assessment deviation in the reporting link, and causes insufficient preparation funds of pending claims.
Disclosure of Invention
The embodiment of the invention provides a pending claims fund prediction method, a pending claims fund prediction device, equipment and a storage medium, which are used for overcoming the problem that pending claims fund is insufficient due to the fact that pending claims fund cannot be timely and effectively predicted in the prior art.
In a first aspect, an embodiment of the present invention provides a pending claims fund prediction method, including:
receiving a claim settlement request sent by terminal equipment, wherein the claim settlement request carries case information of a claim settlement case, and the case information comprises a claim settlement object, vehicle insurance information of the claim settlement object and accident information;
responding to the claim settlement request, and determining an initial compensation amount according to the vehicle insurance information;
according to the vehicle insurance information, at least one first preset loss estimation factor matched with the claim settlement object and at least one second preset loss estimation factor matched with the accident information are searched from a preset loss estimation factor data table;
determining the estimated compensation amount of the pending compensation fund corresponding to the claim object according to the initial compensation amount, the at least one first preset loss estimation factor and the at least one second preset loss estimation factor;
and displaying the estimated compensation amount of the pending compensation fund to a user through the terminal equipment.
Optionally, the vehicle insurance information includes a vehicle insurance risk category and at least one risk category corresponding to the vehicle insurance risk category;
determining an initial reimbursement amount according to the vehicle insurance information, comprising:
if the vehicle insurance risk is a strong insurance, acquiring a plurality of historical insurance policy information stored in a preset database, wherein each historical insurance policy information records a historical reimbursement amount;
averaging a plurality of historical benefits corresponding to the plurality of historical insurance policy information to obtain a first benefit corresponding to the strong insurance;
taking a first payment amount corresponding to the forced insurance as the initial payment amount;
if the vehicle insurance risk is business insurance, determining at least one loss type corresponding to the accident information, and setting the number of the initial reimbursement amount to be at least one;
if at least one target risk matched with the at least one loss type exists in the at least one risk, acquiring a second claim amount corresponding to each target risk from the preset database, wherein the preset database also stores the mapping relationship between each risk and the second claim amount corresponding to each risk;
and taking the second compensation amount corresponding to each target risk as the initial compensation amount.
Optionally, if the vehicle risk category is a forced risk, the at least one first preset loss estimation factor includes: the first vehicle usage property factor corresponding to the claim object, and the at least one second preset loss estimation factor comprises: the first is whether the three are human injury factors;
if the vehicle insurance risk category is a commercial risk and the target risk category is any one of vehicle loss insurance, on-board personnel responsibility insurance and on-board cargo responsibility insurance, the at least one first preset loss estimation factor comprises: the second vehicle usage property factor corresponding to the claim object, the agency factor to which the first vehicle corresponding to the claim object belongs, the first vehicle age factor corresponding to the claim object, and the first vehicle actual value factor corresponding to the claim object, where the at least one second preset loss estimation factor includes: the first risk-taking time factor and the second injury factor are the three factors;
if the vehicle insurance risk category is a business risk and the target risk category is a third party liability insurance, the at least one first preset loss estimation factor comprises: the third vehicle usage property factor corresponding to the claim object, the organization factor to which the second vehicle belongs corresponding to the claim object, and the second vehicle age factor corresponding to the claim object, where the at least one second preset loss estimation factor includes: the second risk time factor and the third risk factor.
Optionally, if the vehicle insurance risk is a heavy insurance, the determining the pending claims fund estimated claim amount corresponding to the claim object includes:
the first claim payment amount, the first vehicle use property factor and the first person injury factor are accumulated to obtain a first estimated claim payment amount;
and taking the first estimated compensation amount as the estimated compensation amount of the pending compensation fund corresponding to the claim object.
Optionally, if the vehicle insurance risk is a commercial insurance, the determining the pending claims fund preparation fund estimated claim amount corresponding to the claim object includes:
multiplying each second claims amount, the at least one first preset loss estimation factor and the at least one second preset loss estimation factor corresponding to each second claims amount to obtain at least one second estimated claims amount;
and overlapping the at least one second estimated claims amount to obtain the pending claims fund estimated claims amount corresponding to the claim object.
Optionally, if the vehicle insurance risk category includes the strong insurance and the business insurance, the determining the pending claim preparation fund estimated claim amount corresponding to the claim object includes:
and superposing the first estimated claim payment amount and the at least one second estimated claim payment amount to obtain the pending claim payment preparatory fund estimated claim payment amount corresponding to the claim object.
Optionally, after determining the estimated amount of the claim by the pending claims fund corresponding to the claim object, the method further includes:
and storing the estimated claims and payment amount of the pending claims fund corresponding to the claim object in the preset database for updating the preset database.
In a second aspect, an embodiment of the present invention provides a pending claims fund prediction apparatus, including:
the system comprises a claim settlement request receiving module, a claim settlement request sending module and a service processing module, wherein the claim settlement request carries claim information of a claim settlement case, and the claim information comprises a claim settlement object, vehicle insurance information of the claim settlement object and accident information;
the initial reimbursement amount determining module is used for responding to the claim settlement request and determining an initial reimbursement amount according to the vehicle insurance information;
the loss estimation factor determining module is used for searching at least one first preset loss estimation factor matched with the claim settlement object and at least one second preset loss estimation factor matched with the accident information from a preset loss estimation factor data table according to the vehicle insurance information;
the estimated claim payment amount determining module is used for determining the estimated claim payment amount of the pending claim fund corresponding to the claim object according to the initial claim payment amount, the at least one first preset loss estimation factor and the at least one second preset loss estimation factor;
and the display module is used for displaying the estimated compensation amount of the pending compensation preparatory fund to a user through the terminal equipment.
In a third aspect, an embodiment of the present invention provides a pending claims fund prediction apparatus, including: at least one processor and memory;
the memory stores computer-executable instructions;
the at least one processor executing the computer-executable instructions stored by the memory causes the at least one processor to perform the pending claims fund prediction method as described above in the first aspect and in various possible designs of the first aspect.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, the pending claims fund prediction method according to the first aspect and various possible designs of the first aspect is implemented.
The pending claims fund predicting method, apparatus, device and storage medium provided in this embodiment receive a claim request sent by a terminal device, and then determine a claim object of the claim case, vehicle insurance information and accident information of the claim object application according to claim case entry information of the claim case carried in the claim request, since different pieces of vehicle insurance information correspond to different claim schemes, an initial claim amount can be determined according to the vehicle insurance information, and then a loss factor matching the entry information is searched from a preset loss prediction factor data table, where the loss prediction factor may include at least one first preset loss prediction factor associated with the claim object and at least one second preset loss prediction factor associated with the accident information, and then a preset functional relationship between the initial claim amount and the loss factor is passed, the estimated payment amount of the pending claims fund is obtained and displayed to the service personnel, and the service personnel can prepare the pending claims fund in advance by effectively estimating the pending claims fund in time, and the estimated pending claims fund has high accuracy. Through the technical means, the pending claim fund preparation fund can be effectively estimated in time without case survey and damage assessment completion, and the estimation method considers various information influencing the pending claim fund preparation fund, can ensure the accuracy of the pending claim fund preparation fund estimation, ensures that the pending claim fund preparation fund is sufficient, and further improves the satisfaction degree of users.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic flow chart of a pending claims fund prediction method according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart illustrating a pending claims fund prediction method according to another embodiment of the present invention;
FIG. 3 is a schematic flow chart illustrating a pending claims fund prediction method according to another embodiment of the present invention;
FIG. 4 is a flowchart illustrating a pending claims fund prediction method according to yet another embodiment of the present invention;
FIG. 5 is a schematic structural diagram of a pending claims fund forecasting apparatus according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a pending claims fund forecasting device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In the prior art, when the claims case does not survey and settle the damage, the calculation of the pending claims fund of the car insurance is too simple, and the final payment amount is too different from the initially calculated pending claims fund. In order to solve the above technical problem, an embodiment of the present invention provides a pending claims fund prediction method to solve the above problem.
Fig. 1 is a schematic flow chart of a pending claims fund prediction method according to an embodiment of the present invention, where an execution main body in this embodiment may be a terminal or a server, and the execution main body is not limited herein.
Referring to fig. 1, the pending claims fund prediction method includes:
s101, receiving a claim settlement request sent by a terminal device, wherein the claim settlement request carries entry information of a claim settlement case, and the entry information comprises a claim settlement object, vehicle insurance information of the claim settlement object and accident information.
In practical application, the execution subject can be a pre-built claim settlement platform. The loss settlement mark for the vehicle insurance mainly comprises the loss of the vehicle, the casualty of a driver on the vehicle, the casualty of passengers on the vehicle, the loss of goods on the vehicle, the casualty of people on the three vehicles, the loss of vehicles of the three vehicles, the loss of property of the three vehicles, the casualty of a third party and the loss of property of the third party, wherein different loss types are usually paid corresponding to different risks.
In this embodiment, the terminal, the server, or the claim settlement platform may receive the claim information sent by the user end (terminal device) in real time, where the claim information may refer to related information of the claim settlement case, such as the claim settlement object, the insurance information of the claim settlement object, and the accident information. The vehicle insurance information can be used for representing insurance information covered by the claim settlement object, such as insurance category and the like; the accident information is used for representing field information in an accident occurrence time period, such as the time of occurrence of an accident, the area of occurrence of the accident and whether a human injury case exists in the accident, and the received case information is used for analyzing and solving the claim case.
And S102, responding to the claim settlement request, and determining an initial payment amount according to the vehicle insurance information.
In this embodiment, the car insurance information includes car insurance risk types, and different car insurance risk types correspond to different claim settlement manners, wherein how to determine the initial claim amount needs to be determined according to the car insurance risk types specifically applied to the claim settlement object. Specifically, the initial amount of the claim may be calculated from historical insurance policy information stored in a preset database or may be matched with the car insurance risk, so that the initial amount of the claim may be one or more, for example, a plurality of risk classes are covered in a certain risk class, and one risk class corresponds to one initial amount of the claim.
S103, according to the vehicle insurance information, at least one first preset loss estimation factor matched with the claim settlement object and at least one second preset loss estimation factor matched with the accident information are searched from a preset loss estimation factor data table.
In practical applications, the information having an influence on the pending claims fund may be the assessment loss factor or the loss assessment loss factor, wherein the influence on the pending claims fund may include: the area of the accident, the time of the accident, the nature of the vehicle usage, whether or not there is a human injury, the age of the vehicle (vehicle age), the actual value of the vehicle, etc., the loss estimation factor may include at least one of: the vehicle service property factor, the vehicle affiliated mechanism factor, the vehicle age factor, the vehicle actual value factor, the time of occurrence factor and the factor of whether the three are hurt by people.
Specifically, the loss estimation factors are determined by performing machine learning on the historical insurance policy information, training, and storing the trained loss estimation factors into a preset loss estimation factor data table, wherein the loss estimation factors include at least one first preset loss estimation factor and at least one second preset loss estimation factor, and since the first preset loss estimation factor is an influence factor associated with the claim object and the second preset loss estimation factor is an influence factor associated with the accident information, the preset loss estimation factor data table stores a first preset mapping relationship between the claim object and the first preset loss estimation factor and a second preset mapping relationship between the accident information and the second preset loss estimation factor, and according to the determined claim object and the accident information, the corresponding mapping relationships are passed through in the preset loss estimation factor data table, at least one first preset loss estimation factor matched with a claim object in the claim case and at least one second preset loss estimation factor matched with accident information in the claim case can be searched and obtained. Therefore, the initial compensation amount can be accurately and effectively adjusted through the loss estimation factor, and the problem that the preparation fund of the pending compensation is insufficient due to large estimation deviation is avoided.
S104, determining the estimated compensation amount of the pending compensation preparatory fund corresponding to the claim object according to the initial compensation amount, the at least one first preset loss estimation factor and the at least one second preset loss estimation factor;
and S105, displaying the estimated compensation amount of the pending compensation fund to a user through the terminal equipment.
In this embodiment, different car insurance risk types have different calculation methods for the estimated claims amount of pending claims fund, each car insurance risk type or each risk class corresponds to a claim method, for example, a certain car insurance risk type includes multiple risk classes for insurance application, first obtaining the loss estimation factor corresponding to each risk class, then the product operation is carried out on the initial compensation amount corresponding to the risk and the loss estimation factor corresponding to the risk, then the results after the products corresponding to each risk category are superposed to obtain the estimated compensation amount corresponding to the vehicle risk category, namely the estimated compensation amount of the pending compensation preparation fund, and in the same way, if the number of the vehicle insurance risk types applied to the claim settlement object is multiple, the estimated claim amount corresponding to each vehicle insurance risk type is calculated in a superposition mode, and the sum of the estimated claim amounts is the estimated claim amount of the pending claim amount. Therefore, the loss estimation factor is added in the estimated amount of the pending claims fund predicted by the pending claims fund prediction method in combination with the actual application scene, so that the estimation accuracy is higher, the problem of insufficient pending claims fund is avoided, and the satisfaction degree of the user is improved.
The pending claim fund preparing fund prediction method can replace manual work for processing the problem of the claim case and predicting the claim fund, and improves the working efficiency. Meanwhile, the feedback is timely, the satisfaction degree of the user can be improved, and the claim settlement platform is suitable for IT service in an internet mode and can provide related service in non-working time. Therefore, the method and the device can effectively predict the pending claim fund in time, so that the problem of insufficient pending claim fund is avoided, the work efficiency is improved by replacing manpower with intelligence, and the prediction accuracy is ensured.
Referring to fig. 2, fig. 2 is a schematic flow chart of a pending claims fund prediction method according to another embodiment of the present invention. In the present embodiment, S102 is explained in detail based on the above-described embodiment, for example, based on the embodiment shown in fig. 1. The vehicle insurance information can comprise vehicle insurance risk types, and the vehicle insurance risk types applied by the claim settlement objects can comprise strong insurance and/or business insurance; determining an initial reimbursement amount according to the vehicle insurance information, comprising:
s201, if the vehicle insurance risk is a heavy insurance, acquiring a plurality of historical insurance policy information stored in a preset database, wherein each historical insurance policy information records a historical reimbursement amount;
s202, averaging a plurality of historical paying amounts corresponding to the plurality of historical insurance policy information to obtain a first paying amount corresponding to the forced insurance;
s203, taking a first payment amount corresponding to the forced insurance as the initial payment amount;
s204, if the car insurance risk is business insurance, determining at least one loss type corresponding to the accident information, wherein the number of the initial reimbursement amount is at least one;
s205, if at least one target risk matched with the at least one loss type exists in the at least one risk, acquiring a second claims amount corresponding to each target risk from the preset database, wherein the preset database also stores mapping relations between the risks and the second claims amounts corresponding to the risks;
s206, taking the second paying amount corresponding to each target risk as the initial paying amount;
and S207, if the vehicle insurance risk is strong insurance and business insurance, the initial compensation amount comprises a first compensation amount and at least one second compensation amount.
In this embodiment, the terminal or the server may determine the car insurance risk category related to the claim case or the risk category included in the car insurance risk category by analyzing the car insurance information.
And if the vehicle insurance risk category of the vehicle insurance information obtained by analysis is the insurance, predicting the reserve money of the insurance. In practical application, through analysis of the report information, when loss except the vehicle (including the vehicle, the object and the person) exists and the claim settlement object guarantees the insurance, the pending claim fund corresponding to the insurance is estimated and calculated.
Specifically, a plurality of historical insurance policy information is acquired from a preset database, wherein the plurality of historical insurance policy information is the actual payment amount of the historical insurance, then according to the plurality of historical insurance policy information, the average value of the actual payment amount of the historical insurance, namely the average payment amount of the historical insurance, is taken as the initial payment amount corresponding to the insurance, and the initial payment amount is the initial pending payment reserve money. For example, the insurance risk is marked as A, and A is 2400 obtained by calculating the average value of the actual paid amount of the insurance risk over the past years.
And if the vehicle insurance risk type of the vehicle insurance information obtained by analysis is a commercial insurance, predicting the reserve of the commercial insurance. In practical application, the estimation of the insurance business risk is similar to the estimation of the strong insurance, except that the business risk can be divided into a plurality of risk categories, such as vehicle loss insurance, on-board personnel responsibility insurance (drivers), on-board personnel responsibility insurance (passengers), on-board cargo responsibility insurance, third party responsibility insurance and the like, for the estimation of the business risk, the terminal or the server firstly analyzes which risk category is ensured, and then determines the initial payment amount corresponding to each risk category aiming at each risk category.
Specifically, when determining that the car insurance risk type is a business risk, first determining a loss type corresponding to the accident information, where the loss type may include: the vehicle damage, the driver casualty on the vehicle, the passenger casualty on the vehicle, the goods loss on the vehicle, the personal casualty on the three vehicles, the vehicle loss of the three vehicles, the goods loss on the three vehicles, the third party casualty, the third party property loss and the like, wherein each dangerous category corresponds to a dangerous category name, for example, the vehicle damage corresponds to the vehicle loss insurance, the driver casualty on the vehicle corresponds to the vehicle personal insurance (driver), the passenger casualty on the vehicle corresponds to the vehicle personal insurance (passenger), the goods loss on the vehicle corresponds to the vehicle personal insurance, and the personal casualty on the three vehicles, the vehicle loss on the three vehicles, the goods loss on the three vehicles, the third party personal casualty and the third party property loss all correspond to the third party personal insurance.
Then, according to the loss type and the insurance risk, the depreciable (to be depreciated) risk is found, namely, whether at least one target risk matched with the at least one loss type exists in at least one risk is judged. For example, the loss types are vehicle loss of the vehicle and cargo loss on the vehicle, the insurance levels of the application are vehicle loss insurance and vehicle personnel responsibility insurance (drivers), and the insurance level of the application object does not apply the insurance level corresponding to the cargo loss on the vehicle, namely the vehicle cargo responsibility insurance, so that the claim settlement platform does not need to calculate the pending claim fund estimated claim amount corresponding to the vehicle cargo responsibility insurance, and meanwhile, the loss types do not include the loss types corresponding to the vehicle personnel responsibility insurance (drivers), namely the loss types corresponding to the vehicle personnel responsibility insurance (drivers) do not relate to the claim settlement case, so the claim settlement platform also does not need to calculate the pending claim fund estimated claim amount corresponding to the insurance level of the vehicle personnel insurance (drivers). Therefore, for the above case, the vehicle loss insurance is the target risk.
Because the preset database also stores the mapping relationship between each risk and the second claims corresponding to each risk, according to the determined at least one target risk, the terminal or the server or the claim settlement platform may obtain the second claims corresponding to each target risk from the preset database, where each risk corresponds to one initial claims. The initial payout amount here includes a second payout amount, i.e., a plurality of second payout amounts, corresponding to each target risk. For example, each risk is identified as B, different risks may be represented by B1 … Bn, and the different risks have different values corresponding to B, for example, the vehicle loss insurance is B1 ═ 5000, the vehicle personnel responsibility insurance (driver) is B2 ═ 10000, the vehicle personnel responsibility insurance (passenger) is B3 ═ 20000, the vehicle cargo responsibility insurance is B4 ═ 5000, and the third party responsibility insurance B5 is 40000.
If the vehicle insurance risk types of the vehicle insurance information obtained by analysis include two risk types, namely, strong insurance and business insurance, the terminal or the server or the claim settlement platform can respectively obtain a first claim amount corresponding to the strong insurance and at least one second claim amount corresponding to the business insurance, and how to determine the first claim amount and the at least one second claim amount is consistent with the above-mentioned obtaining mode of determining the first claim amount and the at least one second claim amount is not described herein again.
In this embodiment, the car insurance risk obtained through analysis is used to determine the initial reimbursement amount, so that the estimation deviation of the reporting link can be reduced, and a basis can be provided for timely and effectively estimating the pending reimbursement fund.
In order to accurately estimate the pending claim fund, the initial payment amount can be corrected through the loss estimation factor, and the estimation accuracy of the pending claim fund is ensured. Wherein, different vehicle risk types correspond to different loss estimation factors.
Optionally, if the vehicle risk category is a forced risk, the at least one first preset loss estimation factor includes: the first vehicle usage property factor corresponding to the claim object, and the at least one second preset loss estimation factor comprises: the first is whether the three are human injury factors.
In this example, as shown in table 1:
TABLE 1
Optionally, if the vehicle insurance risk category is a commercial risk and the target risk category is any one of vehicle loss insurance, on-board personnel responsibility insurance and on-board cargo responsibility insurance, the at least one first preset loss estimation factor includes: the second vehicle usage property factor corresponding to the claim object, the agency factor to which the first vehicle corresponding to the claim object belongs, the first vehicle age factor corresponding to the claim object, and the first vehicle actual value factor corresponding to the claim object, where the at least one second preset loss estimation factor includes: the first risk-taking time factor and the second injury factor.
In this example, as shown in table 2:
TABLE 2
Optionally, if the vehicle insurance risk category is a business risk and the target risk category is a third party liability insurance, the at least one first preset loss estimation factor comprises: the third vehicle usage property factor corresponding to the claim object, the organization factor to which the second vehicle belongs corresponding to the claim object, and the second vehicle age factor corresponding to the claim object, where the at least one second preset loss estimation factor includes: the second risk time factor and the third risk factor.
In this example, as shown in table 3:
TABLE 3
Thus, the terminal or server or the benefits platform may look up from a pre-set database coefficients matching the loss prediction factors for pending claims reserves that impact the deal or business risk.
After determining the initial claims amount and the corresponding loss estimation factors, how to obtain the estimated claims amount of the pending claims fund corresponding to the claim object is shown in fig. 3 and fig. 4, respectively, this embodiment details step S104 based on the above embodiment, for example, based on the embodiment described in fig. 2. The calculation of the estimated claims and payment amount of the pending claims fund can be realized through at least three scenes:
scene one: the dangerous type of the car insurance is the traffic insurance.
The determining the estimated compensation amount of the pending compensation fund corresponding to the claim object comprises:
s301, multiplying the first claim payment amount, the first vehicle use property factor and the first person injury factor to obtain a first estimated claim payment amount;
s302, the first estimated compensation amount is used as the estimated compensation amount of the pending compensation preparatory money corresponding to the claim object.
In this embodiment, if the vehicle insurance risk is a duty, the first estimated claims amount (the pending claims preparatory funds estimated claims amount corresponding to the duty) is the first claims amount and the first vehicle usage property factor, and the first estimated claims amount is the pending claims preparatory funds estimated claims amount corresponding to the subject to be claimed.
Scene two: the car insurance risk is commercial risk.
The determining the estimated compensation amount of the pending compensation fund corresponding to the claim object comprises:
s401, multiplying each second claims amount, the at least one first preset loss estimation factor corresponding to each second claims amount and the at least one second preset loss estimation factor to obtain at least one second estimated claims amount;
s402, overlapping the at least one second estimated claims to obtain the estimated pending claims fund claims corresponding to the claim object.
In this embodiment, the car insurance risk is a commercial risk, and the insurance application in the commercial risk includes a plurality of risk categories, and the second estimated claims and payments corresponding to the plurality of risk categories may be B1, B2, …, Bn, where n is greater than or equal to 1; the pending claim fund estimated pay amount corresponding to the claim object (pending claim fund estimated pay amount corresponding to the business risk) ═ B1 × B1 product of at least one first preset loss estimation factor corresponding to B1 product of at least one second preset loss estimation factor corresponding to + … + Bn × Bn product of at least one first preset loss estimation factor corresponding to Bn product of at least one second preset loss estimation factor corresponding to Bn. For example, in a claim case, the vehicle insurance risk is a commercial risk, the target insurance of the insurance is vehicle loss insurance, on-board personnel responsibility insurance and third party responsibility insurance, second estimated loss amounts B1, B2 and B3 corresponding to the vehicle loss insurance C1, the on-board personnel responsibility insurance C2 and the third party responsibility insurance C3 respectively are obtained by searching from a preset database, loss factors D1 and D2 corresponding to the vehicle loss insurance C1 and the on-board personnel responsibility insurance C2 respectively are obtained by searching from table 2 (the loss estimation factors include a first preset loss estimation factor and a second preset loss estimation factor, that is, D1 includes D11, … and D1m, m is not less than 1, D2 includes D21, …, D2k, k is not less than 1), loss factors D3 corresponding to the third party liability insurance C3 are obtained by searching from table 3, and D2 includes D56, 69553 and 82863 i; and calculating the estimated lost amount of the pending claims preparation fund corresponding to the claim object, wherein the estimated lost amount is B1D 11 … D1m + B2D 21 … D2m + B3D 31D … D3 m.
Scene three: the car insurance risk includes the strong risk and the business risk.
The determining the estimated compensation amount of the pending compensation fund corresponding to the claim object comprises:
and superposing the first estimated claim payment amount and the at least one second estimated claim payment amount to obtain the pending claim payment preparatory fund estimated claim payment amount corresponding to the claim object.
In this embodiment, if the vehicle risk type includes the deal risk and the business risk, the pending estimated loss fund payment amount corresponding to the claim object is the first estimated payment amount (the pending estimated loss fund payment amount corresponding to the deal risk + the pending estimated loss fund payment amount corresponding to the business risk): the first payment amount is the product of the at least one second predetermined loss estimation factor corresponding to the no three injury factor + B1B 1 and the product of the at least one first predetermined loss estimation factor corresponding to B1 + the product of the at least one second predetermined loss estimation factor corresponding to the no three injury factor + B … + Bn.
For example, the accident report of a certain passenger car in Beijing area, the vehicle is in heavy traffic, loss of car protection and responsibility of the third party, the vehicle age is 2 years, the vehicle value is 10 thousands, the limit of the responsibility of the third party is 300000, the accident time is 21 pm, and the number of the third party casualties is 1. Calculating the estimated compensation amount of the pending claims fund by a pending claims fund prediction method:
the estimated amount of the claim 2400, 1.80, 8.00 and 34560 of the pending claim fund corresponding to the strong insurance; since the accident only involves the loss of the vehicle and the loss of the third-party personnel, the business insurance has the benefits of vehicle loss insurance and third-party responsibility insurance: the pending estimated payout amount of the pending fund preparation corresponding to the business risk + the pending estimated payout amount of the pending fund preparation corresponding to the vehicle loss risk + the pending estimated payout amount of the pending fund preparation corresponding to the third liability risk is 5000 × 1.80 × 1.20 × 1.1.80 × 0.80 × 1+3000 × 1.80 × 1.20 × 1.80 × 5 × 8460+46656 × 55116. Therefore, the pending claim fund reserve corresponding to the claim object estimates the amount of the claim 34560+55116 to 89676.
Through the technical means, the pending claim fund preparation fund can be effectively estimated in time without case survey and damage assessment completion, and the estimation method considers various information influencing the pending claim fund preparation fund, can ensure the accuracy of the pending claim fund preparation fund estimation, ensures that the pending claim fund preparation fund is sufficient, and further improves the satisfaction degree of users.
Optionally, after obtaining the estimated compensation amount of the pending claims fund corresponding to the claim object, the method may further include:
storing the estimated claims and payment amount of the pending claims fund corresponding to the claim object in the preset database for updating the preset database; and performing machine learning on the historical paying amount of the historical insurance policy information and the accident information of the insurance stored in the preset database again, and training to obtain a new initial paying amount.
The method may further comprise: and obtaining a new loss estimation factor for updating the preset loss estimation factor data table.
Therefore, the data, including the predetermined database and the predetermined loss estimation factor data table, can be continuously updated in this embodiment to ensure the accuracy of predicting the pending claims fund.
In order to implement the pending claims fund prediction method, the embodiment provides a pending claims fund prediction device. Referring to fig. 5, fig. 5 is a schematic structural diagram of a pending claims fund prediction apparatus according to an embodiment of the present invention; the pending claims fund predicting apparatus 50 includes: a claim settlement request receiving module 501, an initial claim amount determining module 502, a loss estimation factor determining module 503, an estimated claim amount determining module 504 and a display module 505; the claim settlement request receiving module 501 is configured to receive a claim settlement request sent by a terminal device, where the claim settlement request carries entry information of a claim case, and the entry information includes a claim settlement object, vehicle insurance information for applying the claim settlement object, and accident information; an initial reimbursement amount determining module 502, configured to determine an initial reimbursement amount according to the vehicle insurance information in response to the claim settlement request; a loss prediction factor determining module 503, configured to search, according to the vehicle insurance information, at least one first preset loss prediction factor matched with the claim settlement object and at least one second preset loss prediction factor matched with the accident information from a preset loss prediction factor data table; the estimated claim payment amount determining module 504 is configured to determine an estimated claim payment amount of the pending claim fund corresponding to the claim object according to the initial claim payment amount, the at least one first preset loss estimation factor, and the at least one second preset loss estimation factor; a display module 505, configured to display the estimated claims amount of the pending claims fund to the user through the terminal device.
In this embodiment, a claim settlement request receiving module 501, an initial claim amount determining module 502, a loss estimation factor determining module 503, an estimated claim amount determining module 504 and a display module 505 are provided, and configured to receive a claim settlement request sent by a terminal device, determine a claim object of the claim case, vehicle insurance information and accident information of a claim object application according to claim case information carried in the claim settlement request, and determine an initial claim amount according to the vehicle insurance information since different pieces of vehicle insurance information correspond to different claim schemes, and then search for a loss estimation factor matched with the claim information from a preset loss estimation factor data table, where the loss estimation factor may include at least one first preset loss estimation factor associated with the claim object and at least one second preset loss estimation factor associated with the accident information, and then the estimated compensation amount of the pending compensation fund is obtained through a preset functional relation between the initial compensation amount and the loss estimation factor and is displayed to business personnel, and the pending compensation fund is effectively estimated in time, so that the business personnel can prepare the pending compensation fund in advance, and the estimated pending compensation fund has high accuracy. Through the technical means, the pending claim fund preparation fund can be effectively estimated in time without case survey and damage assessment completion, and the estimation method considers various information influencing the pending claim fund preparation fund, can ensure the accuracy of the pending claim fund preparation fund estimation, ensures that the pending claim fund preparation fund is sufficient, and further improves the satisfaction degree of users.
The apparatus provided in this embodiment may be used to implement the technical solutions of the above method embodiments, and the implementation principles and technical effects are similar, which are not described herein again.
Optionally, the initial payout amount determining module 502 includes: the system comprises a historical insurance policy information acquisition unit and a first payment amount determination unit; the system comprises a historical insurance policy information acquisition unit, a vehicle insurance policy management unit and a vehicle insurance policy management unit, wherein the historical insurance policy information acquisition unit is used for acquiring a plurality of pieces of historical insurance policy information stored in a preset database when the vehicle insurance risk is strong insurance, and each piece of historical insurance policy information records a historical compensation amount; and the first payment amount determining unit is used for averaging a plurality of historical payment amounts corresponding to the plurality of historical insurance policy information to obtain a first payment amount corresponding to the strong insurance, and taking the first payment amount corresponding to the strong insurance as the initial payment amount.
Optionally, if the vehicle risk category is a forced risk, the at least one first preset loss estimation factor includes: the first vehicle usage property factor corresponding to the claim object, and the at least one second preset loss estimation factor comprises: the first is whether the three are human injury factors.
Optionally, the predicted claim amount determining module 504 includes: a first estimated claim amount determining unit; and the first estimated compensation amount determining unit is used for taking the first compensation amount, the first vehicle use property factor and the first human injury factor of whether or not as a product to obtain a first estimated compensation amount when the vehicle risk is strong risk, and taking the first estimated compensation amount as an estimated compensation amount of pending compensation preparatory money corresponding to the compensation object.
Optionally, the vehicle insurance information includes at least one security risk corresponding to the vehicle insurance security risk; the initial payout amount determination module 502 further includes: a loss type determining unit and a second payout amount determining unit; the loss type determining unit is used for determining at least one loss type corresponding to the accident information when the car insurance risk is a business risk, and the number of the initial reimbursement amount is at least one; a second payment amount determining unit, configured to, when there is at least one target risk that matches the at least one loss type in the at least one risk, obtain, from the preset database, a second payment amount corresponding to each target risk, where the preset database further stores a mapping relationship between each risk and the second payment amount corresponding to each risk, and use the second payment amount corresponding to each target risk as the initial payment amount.
Optionally, the initial payout amount determining module 502 further includes: and the initial compensation amount determining unit is used for determining the initial compensation amount when the vehicle insurance risk is strong insurance and business insurance, and the initial compensation amount comprises a first compensation amount and at least one second compensation amount.
Optionally, if the vehicle insurance risk category is a commercial risk and the target risk category is any one of vehicle loss insurance, on-board personnel responsibility insurance and on-board cargo responsibility insurance, the at least one first preset loss estimation factor includes: the second vehicle usage property factor corresponding to the claim object, the agency factor to which the first vehicle corresponding to the claim object belongs, the first vehicle age factor corresponding to the claim object, and the first vehicle actual value factor corresponding to the claim object, where the at least one second preset loss estimation factor includes: the first risk-taking time factor and the second injury factor are the three factors; if the vehicle insurance risk category is a business risk and the target risk category is a third party liability insurance, the at least one first preset loss estimation factor comprises: the third vehicle usage property factor corresponding to the claim object, the organization factor to which the second vehicle belongs corresponding to the claim object, and the second vehicle age factor corresponding to the claim object, where the at least one second preset loss estimation factor includes: the second risk time factor and the third risk factor.
Optionally, the predicted claim amount determining module 504 further includes: a second estimated claims amount determination unit; and the second estimated claim amount determining unit is used for taking the product of each second claim amount, the at least one first preset loss estimation factor corresponding to each second claim amount and the at least one second preset loss estimation factor to obtain at least one second estimated claim amount when the vehicle insurance risk is commercial insurance, and overlapping the at least one second estimated claim amount to obtain the estimated claim amount of pending claim fund corresponding to the claim object.
Optionally, the predicted claim amount determining module 504 further includes: and the estimated claim amount determining unit is used for superposing the first estimated claim amount and the at least one second estimated claim amount to obtain the estimated claim amount of the pending claim fund preparation fund corresponding to the claim object when the vehicle insurance risk type comprises the strong insurance and the business insurance.
Optionally, the pending claims fund predicting device further includes: presetting a database updating module; the preset database updating module is used for storing the estimated claims and payment amount of the pending claims fund corresponding to the claim settlement object into the preset database so as to update the preset database; and performing machine learning on the historical paying amount of the historical insurance policy information and the accident information of the insurance stored in the preset database again, and training to obtain a new initial paying amount.
Optionally, the pending claims fund predicting device further includes: a preset loss estimation factor data table updating module; and the preset loss estimation factor data table updating module is used for acquiring a new loss estimation factor and updating the preset loss estimation factor data table.
In order to implement the pending claims fund prediction method, the present embodiment provides a pending claims fund prediction apparatus. Fig. 6 is a schematic structural diagram of a pending claims fund forecasting device according to an embodiment of the present invention. As shown in fig. 6, the pending claims preparing money predicting apparatus 60 of the present embodiment includes: a processor 601 and a memory 602; a memory 602 for storing computer-executable instructions; the processor 601 is configured to execute the computer-executable instructions stored in the memory to implement the steps performed in the above embodiments. Reference may be made in particular to the description relating to the method embodiments described above.
The embodiment of the invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when a processor executes the computer-executable instructions, the pending-claim-fund prediction method is implemented.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, and for example, the division of the modules is only one logical division, and other divisions may be realized in practice, for example, a plurality of modules may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may be in an electrical, mechanical or other form. In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each module may exist alone physically, or two or more modules are integrated into one unit. The unit formed by the modules can be realized in a hardware form, and can also be realized in a form of hardware and a software functional unit.
The integrated module implemented in the form of a software functional module may be stored in a computer-readable storage medium. The software functional module is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present invention. It should be understood that the Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.
The memory may comprise a high-speed RAM memory, and may further comprise a non-volatile storage NVM, such as at least one disk memory, and may also be a usb disk, a removable hard disk, a read-only memory, a magnetic or optical disk, etc. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, the buses in the figures of the present invention are not limited to only one bus or one type of bus. The storage medium may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an Application Specific Integrated Circuits (ASIC). Of course, the processor and the storage medium may reside as discrete components in an electronic device or host device.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A pending claims fund prediction method, comprising:
receiving a claim settlement request sent by terminal equipment, wherein the claim settlement request carries case information of a claim settlement case, and the case information comprises a claim settlement object, vehicle insurance information of the claim settlement object and accident information;
responding to the claim settlement request, and determining an initial compensation amount according to the vehicle insurance information;
according to the vehicle insurance information, at least one first preset loss estimation factor matched with the claim settlement object and at least one second preset loss estimation factor matched with the accident information are searched from a preset loss estimation factor data table;
determining the estimated compensation amount of the pending compensation fund corresponding to the claim object according to the initial compensation amount, the at least one first preset loss estimation factor and the at least one second preset loss estimation factor;
and displaying the estimated compensation amount of the pending compensation fund to a user through the terminal equipment.
2. The method of claim 1, wherein the vehicle insurance information includes a vehicle insurance risk category and at least one risk category corresponding to the vehicle insurance risk category;
determining an initial reimbursement amount according to the vehicle insurance information, comprising:
if the vehicle insurance risk is a strong insurance, acquiring a plurality of historical insurance policy information stored in a preset database, wherein each historical insurance policy information records a historical reimbursement amount;
averaging a plurality of historical benefits corresponding to the plurality of historical insurance policy information to obtain a first benefit corresponding to the strong insurance;
taking a first payment amount corresponding to the forced insurance as the initial payment amount;
if the vehicle insurance risk is business insurance, determining at least one loss type corresponding to the accident information, and setting the number of the initial reimbursement amount to be at least one;
if at least one target risk matched with the at least one loss type exists in the at least one risk, acquiring a second claim amount corresponding to each target risk from the preset database, wherein the preset database also stores the mapping relationship between each risk and the second claim amount corresponding to each risk;
taking the second compensation amount corresponding to each target risk as the initial compensation amount;
if the vehicle insurance risk is a strong insurance and a business insurance, the initial payment amount comprises a first payment amount and at least one second payment amount.
3. The method according to claim 2, wherein the at least one first predetermined loss estimation factor comprises, if the vehicle risk category is a traffic risk: the first vehicle usage property factor corresponding to the claim object, and the at least one second preset loss estimation factor comprises: the first is whether the three are human injury factors;
if the vehicle insurance risk category is a commercial risk and the target risk category is any one of vehicle loss insurance, on-board personnel responsibility insurance and on-board cargo responsibility insurance, the at least one first preset loss estimation factor comprises: the second vehicle usage property factor corresponding to the claim object, the agency factor to which the first vehicle corresponding to the claim object belongs, the first vehicle age factor corresponding to the claim object, and the first vehicle actual value factor corresponding to the claim object, where the at least one second preset loss estimation factor includes: the first risk-taking time factor and the second injury factor are the three factors;
if the vehicle insurance risk category is a business risk and the target risk category is a third party liability insurance, the at least one first preset loss estimation factor comprises: the third vehicle usage property factor corresponding to the claim object, the organization factor to which the second vehicle belongs corresponding to the claim object, and the second vehicle age factor corresponding to the claim object, where the at least one second preset loss estimation factor includes: the second risk time factor and the third risk factor.
4. The method of claim 3, wherein if the vehicle insurance risk is a heavy insurance, the determining the pending claims fund estimate claim amount corresponding to the claim object comprises:
the first claim payment amount, the first vehicle use property factor and the first person injury factor are accumulated to obtain a first estimated claim payment amount;
and taking the first estimated compensation amount as the estimated compensation amount of the pending compensation fund corresponding to the claim object.
5. The method of claim 4, wherein if the vehicle insurance risk is a business insurance, the determining the pending claims fund estimate claim amount corresponding to the claim object comprises:
multiplying each second claims amount, the at least one first preset loss estimation factor and the at least one second preset loss estimation factor corresponding to each second claims amount to obtain at least one second estimated claims amount;
and overlapping the at least one second estimated claims amount to obtain the pending claims fund estimated claims amount corresponding to the claim object.
6. The method of claim 5, wherein if the vehicle insurance risk category includes the strong and commercial insurance, the determining the pending benefits preparation fund estimate claim amount corresponding to the claim object comprises:
and superposing the first estimated claim payment amount and the at least one second estimated claim payment amount to obtain the pending claim payment preparatory fund estimated claim payment amount corresponding to the claim object.
7. The method according to any one of claims 4-6, wherein after determining the amount of the predicted claims of the pending claims fund corresponding to the claim object, the method further comprises:
and storing the estimated claims and payment amount of the pending claims fund corresponding to the claim object in the preset database for updating the preset database.
8. A pending claims fund prediction apparatus, comprising:
the system comprises a claim settlement request receiving module, a claim settlement request sending module and a service processing module, wherein the claim settlement request carries claim information of a claim settlement case, and the claim information comprises a claim settlement object, vehicle insurance information of the claim settlement object and accident information;
the initial reimbursement amount determining module is used for responding to the claim settlement request and determining an initial reimbursement amount according to the vehicle insurance information;
the loss estimation factor determining module is used for searching at least one first preset loss estimation factor matched with the claim settlement object and at least one second preset loss estimation factor matched with the accident information from a preset loss estimation factor data table according to the vehicle insurance information;
the estimated claim payment amount determining module is used for determining the estimated claim payment amount of the pending claim fund corresponding to the claim object according to the initial claim payment amount, the at least one first preset loss estimation factor and the at least one second preset loss estimation factor;
and the display module is used for displaying the estimated compensation amount of the pending compensation preparatory fund to a user through the terminal equipment.
9. A pending claims fund prediction apparatus, comprising: at least one processor and memory;
the memory stores computer-executable instructions;
the at least one processor executing the computer-executable instructions stored by the memory causes the at least one processor to perform the pending claims fund prediction method of any one of claims 1 to 7.
10. A computer-readable storage medium having computer-executable instructions stored thereon which, when executed by a processor, implement the pending claims fund prediction method of any one of claims 1 to 7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116091246A (en) * | 2022-12-21 | 2023-05-09 | 中国人民财产保险股份有限公司 | Disaster event insurance fund expenditure prediction method, electronic equipment and storage medium |
| CN116777648A (en) * | 2023-08-23 | 2023-09-19 | 山东远硕上池健康科技有限公司 | Intelligent management method for injury claim information of vehicle accident person |
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2020
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116091246A (en) * | 2022-12-21 | 2023-05-09 | 中国人民财产保险股份有限公司 | Disaster event insurance fund expenditure prediction method, electronic equipment and storage medium |
| CN116777648A (en) * | 2023-08-23 | 2023-09-19 | 山东远硕上池健康科技有限公司 | Intelligent management method for injury claim information of vehicle accident person |
| CN116777648B (en) * | 2023-08-23 | 2023-11-03 | 山东远硕上池健康科技有限公司 | Intelligent management method for injury claim information of vehicle accident person |
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