CN116307607A

CN116307607A - Insurance core system monitoring system and method

Info

Publication number: CN116307607A
Application number: CN202310298944.0A
Authority: CN
Inventors: 李展宏
Original assignee: Probe Protection Network Technology Guangzhou Co ltd
Current assignee: Probe Protection Network Technology Guangzhou Co ltd
Priority date: 2023-03-24
Filing date: 2023-03-24
Publication date: 2023-06-23

Abstract

The invention is applicable to the field of insurance, and provides an insurance core system monitoring system and method, wherein the system comprises: the system comprises a data acquisition module, an event recording module, a data comparison module and an event early warning module. According to the system, the core service history information is recorded, and the automatic approval model is built according to the recorded core service history information, so that the system is provided with a set of judgment rules, the application can be automatically divided before the application enters the manual review, the approval speed of the application is greatly increased, the approval process is reduced, the efficiency is improved, the personnel consumption is also reduced, the practicability is high, and meanwhile, the judgment rules built by the automatic approval model can be automatically updated along with the continuous update of data, the judgment accuracy is ensured, and the precision is improved.

Description

Insurance core system monitoring system and method

Technical Field

The invention belongs to the field of insurance, and particularly relates to an insurance core system monitoring system and method.

Background

Insurance refers to the business insurance of paying insurance fee to insurers according to contract agreements, wherein the insurers bear the liability of reimbursement for insurance fund for property loss caused by possible accidents of the contract agreements, or the insurers die, disabled and suffer from diseases or have the liability of paying insurance fund when reaching the conditions of age, period and the like of the contract agreements.

From an economic perspective, insurance is a financial arrangement that accounts for the loss of accidents; from a legal point of view, insurance is a contractual behavior, which is a contractual arrangement in which one party agrees to compensate for the loss of the other party; from the social perspective, insurance is an important component of a socioeconomic performance system; from a risk management perspective, insurance is one method of risk management.

The insurance claim settlement means that when the insurance label happens and the property of the insured person is lost or the life of the person is damaged, or other insurance accidents agreed by the insurance policy occur and the insurance price needs to be paid, the insurance company performs the action of compensation or responsibility payment according to the contract regulation, and directly reflects the insurance function and the work of performing the insurance responsibility.

In short, insurance claims are the act of an insurer processing claims made by the insured after a risk accident of the insured life. In insurance management, insurance claims are a specific implementation of insurance compensation functions.

At present, in the process of processing insurance business claim application, a plurality of processes are needed, firstly, customers are needed to be manually contacted, business demands are known, business information and customer information are collected, then, the information is manually screened for the first time, case types are compared one by one, the information is divided into corresponding processing departments according to the types, the processing departments are used for qualitative analysis of the cases, finally, the step of manually rechecking is carried out, the whole process is complicated, the manual qualitative analysis has great subjectivity, qualitative personnel are needed to have abundant experience, and the efficiency and the accuracy are not beneficial to improvement.

Disclosure of Invention

The embodiment of the invention aims to provide an insurance core system monitoring system, which aims to solve the technical problems in the prior art determined in the background art.

The embodiment of the invention is realized in such a way that an insurance core system monitoring system comprises:

the data acquisition module is used for acquiring business handling data and customer information and carrying out matching association on the business handling data and the customer information;

the event recording module is used for recording the business event in which the claim payment has occurred and the business event in which the claim payment is applied, simultaneously establishing a neural network model, and establishing an automatic approval model according to the business event information in which the claim payment has occurred or the claim payment is refused;

the data comparison module is used for auditing the business event information applied for reimbursement through the automatic approval model, setting the business event information which cannot pass through the automatic approval model as an in-doubt state, and uploading the business event information and the conforming event information;

the event early warning module is used for sending early warning to the service event information in the suspicious state and selecting and sending the early warning information according to the matching degree with the matched information.

As a further aspect of the present invention, the data acquisition module includes:

the business data acquisition unit is used for recording all insurance business information through the insurance system, wherein the business information comprises, but is not limited to, business types, business deposit coverage and business pay coverage;

the system comprises a client information acquisition unit, a service management unit and a service management unit, wherein the client information acquisition unit is used for recording all participating client information through an insurance system, and the participating client information comprises, but is not limited to, personal data of clients, participating service types and insurance amounts;

and the association matching unit is used for classifying the participating and protecting client information according to the acquired insurance service information and listing repeated participating and protecting clients as key clients.

As a further aspect of the present invention, the event recording module includes:

the historical data recording unit is used for recording service information which has paid in the insurance system and simultaneously recording client information associated with the service information;

the application data recording unit is used for recording application information of the application of the claim, wherein the application information comprises service information of the claim application, personal information of the applicant and the insured person and application reason information;

the model building unit is used for building a neural network model, recording the service information of the sent pay, and building an automatic approval model according to the pay margin in the service information and the actual event information.

As a further aspect of the present invention, the data comparison module includes:

the data auditing unit is used for auditing the business event information applying for the payment through the automatic approval model, and uploading the business event information and the failed information if the auditing is failed; if the verification is passed, comparing the business event information of applying for the payment with the business event information which is stored in the automatic verification model and has the payment or refuses the payment, and if the comparison result is that no match information exists, uploading the business event information and the verification passing information; if the comparison result shows that the matching information exists, the business event information is set to be in an in-doubt state;

and the data uploading unit is used for synchronously uploading the service event information in the suspicious state, and the service information and the client information which are acquired in the data acquisition module and matched with the service event.

As a further aspect of the present invention, the event early warning module includes:

the event matching unit is used for carrying out secondary comparison on the service event information set in the suspicious state and the data information in the data acquisition module, and generating matching degree according to the comparison result;

and the early warning sending unit is used for automatically sending corresponding early warning information to the insurance system according to the matching degree.

Another object of an embodiment of the present invention is to provide a method for monitoring an insurance core system, the method including:

collecting business handling data and customer information, and carrying out matching association on the business handling data and the customer information;

recording the business event of which the payment has occurred and the business event of which the payment is applied, simultaneously establishing a neural network model, and establishing an automatic approval model according to the business event information of which the payment has occurred or the payment is refused;

auditing service event information applied for reimbursement through an automatic approval model, setting the service event information which cannot pass through the automatic approval model as a suspicious state, and uploading the service event information and the conforming event information;

and sending early warning to the service event information in the suspicious state, and selecting and sending the early warning information according to the matching degree with the matched information.

As a further scheme of the invention, the method for collecting the business handling data and the client information and carrying out matching association on the business handling data and the client information specifically comprises the following steps:

recording all insurance service information by an insurance system, wherein the service information comprises, but is not limited to, service types, service deposit ranges and service payment ranges;

recording all participating and protecting client information through an insurance system, wherein the participating and protecting client information comprises, but is not limited to, personal data of clients, participating and protecting business types and insurance amounts;

classifying the participating and protecting client information according to the collected insurance service information, and listing repeated participating and protecting clients as key clients.

As a further scheme of the invention, the method records the business event of which the payment has occurred and the business event of which the payment has been applied, establishes a neural network model at the same time, and establishes an automatic approval model according to the business event information of which the payment has occurred or the payment has been refused, and specifically comprises the following steps:

recording business information of the insurance system, which has paid, and simultaneously recording customer information associated with the business information;

recording application information of a claim application currently being submitted, wherein the application information comprises service information of the claim application, personal information of an applicant and an insured person and application reason information;

and establishing a neural network model, recording service information of transmitted reimbursement, and establishing an automatic approval model according to the reimbursement margin in the service information and the actual event information.

As a further scheme of the invention, the method comprises the steps of auditing the business event information applied for the payment through the automatic approval model, setting the business event information which cannot pass through the automatic approval model as an in-doubt state, and uploading the business event information and the conforming event information, and specifically comprises the following steps:

checking the business event information applying for the payment through an automatic approval model, and uploading the business event information and the failed information if the checking fails; if the verification is passed, comparing the business event information of applying for the payment with the business event information which is stored in the automatic verification model and has the payment or refuses the payment, and if the comparison result is that no match information exists, uploading the business event information and the verification passing information; if the comparison result shows that the matching information exists, the business event information is set to be in an in-doubt state;

and uploading the service event information in the suspicious state, and synchronously uploading the customer information and the service information and the customer information which are acquired in the data acquisition module and matched with the service event.

As a further scheme of the invention, the needle sends out early warning to the service event information in the suspicious state, and selects and sends out the early warning information according to the matching degree with the conforming information, and the method specifically comprises the following steps:

performing secondary comparison on the service event information set in the suspicious state and the data information in the data acquisition module, and generating a matching degree according to a comparison result;

and according to the matching degree, automatically sending corresponding early warning information to the insurance system.

The embodiment of the invention has the beneficial effects that:

according to the system, the core service history information is recorded, and the automatic approval model is built according to the recorded core service history information, so that the system is provided with a set of judgment rules, the application can be automatically divided before the application enters the manual review, the approval speed of the application is greatly increased, the approval process is reduced, the efficiency is improved, the personnel consumption is also reduced, the practicability is high, and meanwhile, the judgment rules built by the automatic approval model can be automatically updated along with the continuous update of data, the judgment accuracy is ensured, and the precision is improved.

Drawings

FIG. 1 is a block diagram of an insurance core system monitoring system according to an embodiment of the present invention;

FIG. 2 is a block diagram of a data acquisition module according to an embodiment of the present invention;

FIG. 3 is a block diagram illustrating an event logging module according to an embodiment of the present invention;

FIG. 4 is a block diagram of a data comparison module according to an embodiment of the present invention;

FIG. 5 is a block diagram illustrating an event early warning module according to an embodiment of the present invention;

FIG. 6 is a flowchart of an insurance core system monitoring method according to an embodiment of the present invention;

FIG. 7 is a flowchart for collecting business transaction data and customer information and matching and associating the two according to an embodiment of the present invention;

FIG. 8 is a flowchart of recording a service event in which a claim has occurred and a service event in which a claim is applied, and building a neural network model, and building an automatic approval model according to the service event information in which a claim has occurred or the claim is refused, according to the embodiment of the present invention;

FIG. 9 is a flowchart of auditing service event information applied for reimbursement through an automatic approval model, setting service event information which cannot pass through the automatic approval model as in-doubt, and uploading the service event information and the conforming event information, provided by the embodiment of the invention;

FIG. 10 is a flowchart of sending early warning to service event information in doubtful state and selecting to send early warning information according to matching degree with the matched information according to the embodiment of the invention;

Detailed Description

The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.

It will be understood that the terms "first," "second," and the like, as used herein, may be used to describe various elements, but these elements are not limited by these terms unless otherwise specified. These terms are only used to distinguish one element from another element. For example, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script, without departing from the scope of the present application.

Fig. 1 is a block diagram of an insurance core system monitoring system according to an embodiment of the present invention, as shown in fig. 1, an insurance core system monitoring system, where the system includes:

the data acquisition module 100 is used for acquiring business handling data and customer information and carrying out matching association on the business handling data and the customer information;

in the present module, the service information includes, but is not limited to, policy information, service type, service policy scope, and service pay scope; customer information includes, but is not limited to, the customer's profile, the type of participating service, and the amount of the insurance coverage. When the client information is collected, the historical participating information and the historical paying information of the client are synchronously collected, and if the paying condition occurs for a plurality of times, the client is listed as a key object;

and classifying the clients according to the participation information of the clients and combining the service information, and classifying the clients handling the same service into the same class so as to audit the client information.

The event recording module 200 is configured to record a service event in which a claim has occurred and a service event in which a claim is applied, and establish a neural network model, and establish an automatic approval model according to the service event information in which the claim has occurred or the claim is refused;

in the module, the recorded business event information of the claim or the claim refusing mainly comprises the final reason of judging the claim or the claim refusing, the final payment judging amount and the like, the neural network model can continuously learn according to the recorded business event information of the claim or the claim refusing, a set of rules for judging whether the claim is or not is automatically formed, namely an automatic approval model, and the model can realize automatic updating along with more and more business event information of the claim or the claim refusing.

The data comparison module 300 is configured to audit the service event information applied for reimbursement through the automatic approval model, place the service event information that cannot pass through the automatic approval model into an in-doubt state, and upload the service event information and the corresponding event information;

in the module, when new claim application information appears, an automatic approval model automatically approves the application information according to the established claim rule, and carries out multiple judgment according to an auditing result, and if the auditing is not passed, service event information and failed information are uploaded; if the verification is passed, comparing the business event information of applying for the payment with the business event information which is stored in the automatic verification model and has the payment or refuses the payment, and if the comparison result is that no match information exists, uploading the business event information and the verification passing information; if the comparison result shows that the matching information exists, the business event information is set to be in an in-doubt state;

whether the verification is passed or not, the verification is needed to be manually checked finally, and the difference is that for the application information of the uploading business event information and the failed information, the main task of the manual check is to recheck the judgment result made by the automatic verification model again, and if the recheck results are consistent, the claims are paid; if the rechecking results are inconsistent, rechecking the application, and simultaneously, feeding back the rechecking results and the information which does not pass the rechecking to the automatic approval model so as to adjust and update the automatic approval model according to the approval mode of the cases. For the service event information set in the in-doubt state, the main task of the manual review is to determine whether the in-doubt is established, and divide the nature of the cases according to the in-doubt condition (such as determining whether the case is repeatedly applied for, whether a cheat protection condition exists, etc.).

The event early warning module 400 is used for sending early warning to the service event information in the suspicious state, and selecting and sending early warning information according to the matching degree with the matched information.

In the module, secondary auditing is mainly performed on service event information which is put into a suspicious state, matching degree detection is performed on service transaction data acquired by a data acquisition module according to specific event conditions, event types and the like in the event during auditing to obtain a similar historical information processing method, meanwhile, matching degree detection is performed on applicant information (namely client information) of the event and client information acquired by the data acquisition module, on one hand, similar clients with high matching degree can be detected so as to record and recommend interesting products to clients subsequently, on the other hand, historical participation and payment conditions of the clients can be detected, whether repeated application or frequent payment occurs is judged, and whether the possibility of cheating protection exists is judged.

Fig. 2 is a block diagram of a data acquisition module according to an embodiment of the present invention, and as shown in fig. 2, the data acquisition module 100 includes:

a service data acquisition unit 110 for recording all insurance service information including, but not limited to, service type, service guard range and service pay range by an insurance system;

a customer information collection unit 120 for recording all the participating customer information including, but not limited to, personal data of the customer, participating service type and insurance amount through the insurance system;

the association matching unit 130 is configured to classify the participating clients according to the collected insurance service information, and list the repeated participating clients as key clients.

In the unit, when collecting client information, the historical participating information and the historical paying information of the client are synchronously collected, and if the paying condition occurs for a plurality of times, the client is listed as a key object;

Fig. 3 is a block diagram of an event recording module according to an embodiment of the present invention, and as shown in fig. 3, the event recording module 200 includes:

a history data recording unit 210 for recording service information that has been paid for in the insurance system, and recording customer information associated with the service information;

in the present unit, the recorded business event information in which the payment has occurred or the payment has been refused mainly includes determination of the final cause of the payment or refusal of the payment, final determination of the amount of the payment, and the like;

an application data recording unit 220, configured to record application information that is currently submitting a claim application, where the application information includes service information for applying the claim, personal information of the applicant and the insured person, and application reason information;

the model building unit 230 is configured to build a neural network model, record service information that has sent the payoff, and build an automatic approval model according to the payoff margin in the service information and the actual event information.

In the unit, the neural network model continuously learns according to the recorded business event information of the claims or refusing the claims, automatically forms a set of rules for judging whether the claims are paid or not, namely an automatic approval model, and automatically updates the model along with more and more business event information of the claims or refusing the claims.

Fig. 4 is a block diagram of a data comparison module according to an embodiment of the present invention, as shown in fig. 4, the data comparison module 300 includes:

the data auditing unit 310 is configured to audit the service event information for applying for reimbursement through an automatic approval model, and if the audit is not passed, upload the service event information and the failed information; if the verification is passed, comparing the business event information of applying for the payment with the business event information which is stored in the automatic verification model and has the payment or refuses the payment, and if the comparison result is that no match information exists, uploading the business event information and the verification passing information; if the comparison result shows that the matching information exists, the business event information is set to be in an in-doubt state;

and the data uploading unit 320 is used for synchronously uploading the service event information in the suspicious state, and the service information and the client information which are acquired in the data acquisition module and matched with the service event.

In the unit, whether the verification is passed or not, the verification is needed to be manually verified finally, and the difference is that for the application information of the uploading business event information and the failed information, the main task of the manual verification is to re-verify the judgment result made by the automatic verification model, and if the verification result is consistent, the payment is required; if the rechecking results are inconsistent, rechecking the application, and simultaneously, feeding back the rechecking results and the information which does not pass the rechecking to the automatic approval model so as to adjust and update the automatic approval model according to the approval mode of the cases. For the service event information set in the in-doubt state, the main task of the manual review is to determine whether the in-doubt is established, and divide the nature of the cases according to the in-doubt condition (such as determining whether the case is repeatedly applied for, whether a cheat protection condition exists, etc.).

Fig. 5 is a block diagram of an event early-warning module according to an embodiment of the present invention, as shown in fig. 5, the event early-warning module 400 includes:

the event matching unit 410 is configured to perform secondary comparison on the service event information set in the in-doubt state and the data information in the data acquisition module, and generate a matching degree according to a comparison result;

in the unit, secondary auditing is mainly performed on service event information which is put into a suspicious state, matching degree detection is performed on service transaction data acquired by a data acquisition module according to specific event conditions, event types and the like in the event during auditing to obtain a similar historical information processing method, meanwhile, matching degree detection is performed on applicant information (namely client information) of the event and client information acquired by the data acquisition module, on one hand, similar clients with high matching degree can be detected so as to record and recommend interesting products to clients subsequently, on the other hand, historical participation and payment conditions of the clients can be detected, whether repeated application or frequent payment occurs is judged, and whether the possibility of cheating protection exists is judged.

The early warning sending unit 420 is configured to automatically send corresponding early warning information to the insurance system according to the matching degree.

Fig. 6 is a flowchart of an insurance core system monitoring method according to an embodiment of the present invention, as shown in fig. 6, where the method includes:

s100, collecting business handling data and customer information, and carrying out matching association on the business handling data and the customer information;

in this step, the service information includes, but is not limited to, policy information, service type, service policy range, and service pay range; customer information includes, but is not limited to, the customer's profile, the type of participating service, and the amount of the insurance coverage. When the client information is collected, the historical participating information and the historical paying information of the client are synchronously collected, and if the paying condition occurs for a plurality of times, the client is listed as a key object;

s200, recording the business event of which the claim is paid and the business event of which the claim is applied, simultaneously establishing a neural network model, and establishing an automatic approval model according to the business event information of which the claim is paid or refused;

in this step, the recorded business event information of the claim or the claim refusing mainly comprises the final reason of the claim or the claim refusing, the final amount of the claim, etc., the neural network model can continuously learn according to the recorded business event information of the claim or the claim refusing, automatically form a set of rules for judging whether the claim is or not, namely, an automatic approval model, and the model can realize automatic updating along with more and more business event information of the claim or the claim refusing.

S300, auditing the business event information applied for reimbursement through an automatic approval model, setting the business event information which cannot pass through the automatic approval model as an in-doubt state, and uploading the business event information and the conforming event information;

in the step, when new claim application information appears, an automatic approval model automatically approves the application information according to the established claim rule, and carries out multiple judgment according to an auditing result, and if the auditing is not passed, service event information and failed information are uploaded; if the verification is passed, comparing the business event information of applying for the payment with the business event information which is stored in the automatic verification model and has the payment or refuses the payment, and if the comparison result is that no match information exists, uploading the business event information and the verification passing information; if the comparison result shows that the matching information exists, the business event information is set to be in an in-doubt state;

S400, giving early warning to the service event information in the suspicious state, and selecting and sending the early warning information according to the matching degree with the matched information.

In this step, the secondary audit is mainly performed on the service event information set as the in-doubt state, and during the audit, the matching degree detection is performed on the service transaction data collected by the data collection module according to the specific event condition, event type and the like in the event, so as to obtain a similar historical information processing method, and meanwhile, the matching degree detection is performed on the applicant information (i.e. the client information) of the event and the client information collected by the data collection module, so that on one hand, a similar client with high matching degree can be detected, and the record and recommendation of the interested product can be performed to the client subsequently, and on the other hand, the historical participation and payment condition of the client can be detected, so as to judge whether repeated application or frequent payment occurs, so as to judge whether the possibility of cheating protection exists.

Fig. 7 is a flowchart of collecting and matching and associating business transaction data and customer information provided in an embodiment of the present invention, as shown in fig. 7, where the collecting and matching and associating business transaction data and customer information specifically includes:

s110, recording all insurance service information through an insurance system, wherein the service information comprises, but is not limited to, service types, service deposit ranges and service payment ranges;

s120, recording all participating and protecting client information through an insurance system, wherein the participating and protecting client information comprises, but is not limited to, personal data of clients, participating and protecting business types and insurance amounts;

s130, classifying the participating and protecting client information according to the acquired insurance service information, and listing repeated participating and protecting clients as key clients.

In the step, when collecting client information, the historical participating information and the historical paying information of the client are synchronously collected, and if the paying condition occurs for a plurality of times, the client is listed as a key object;

fig. 8 is a flowchart of recording a service event in which a claim has occurred and a service event in which a claim has been applied, and simultaneously establishing a neural network model, and establishing an automatic approval model according to service event information in which a claim has occurred or a claim has been denied, as shown in fig. 8, where the recording of a service event in which a claim has occurred and a service event in which a claim has been applied, and simultaneously establishing a neural network model, and establishing an automatic approval model according to service event information in which a claim has occurred or a claim has been denied, and specifically includes:

s210, recording service information of the insurance system, which has paid, and simultaneously recording customer information associated with the service information;

in this step, the recorded business event information in which the payment has occurred or the payment has been refused mainly includes determination of the final cause of the payment or refusal of the payment, final determination of the amount of the payment, and the like;

s220, recording application information of the application of the claim, wherein the application information comprises service information of applying the claim, personal information of an applicant and an insured person and application reason information;

s230, building a neural network model, recording service information of transmitted reimbursement, and building an automatic approval model according to the reimbursement margin in the service information and the actual event information.

In this step, the neural network model continuously learns according to the recorded service event information of the claim or refusing the claim, automatically forms a set of rules for judging whether the claim is paid or not, namely an automatic approval model, and automatically updates the model along with more and more service event information of the claim or refusing the claim.

Fig. 9 is a flowchart of auditing service event information applied for reimbursement through an automatic approval model, setting service event information which cannot pass through the automatic approval model as an in-doubt state, and uploading the service event information and the corresponding event information, as shown in fig. 9, wherein the auditing service event information applied for reimbursement through the automatic approval model, setting service event information which cannot pass through the automatic approval model as an in-doubt state, and uploading the service event information and the corresponding event information, and specifically includes:

s310, auditing the business event information applying for the payment through an automatic approval model, and uploading the business event information and the failed information if the auditing fails; if the verification is passed, comparing the business event information of applying for the payment with the business event information which is stored in the automatic verification model and has the payment or refuses the payment, and if the comparison result is that no match information exists, uploading the business event information and the verification passing information; if the comparison result shows that the matching information exists, the business event information is set to be in an in-doubt state;

s320, service event information which is set to be in an in-doubt state is synchronously uploaded, and service information and customer information which are acquired in the data acquisition module and matched with the service event are synchronously uploaded.

In the step, in the unit, no matter whether the verification is passed or not, the verification is needed to be manually verified, and the difference is that for the application information of the uploading business event information and the failed information, the main task of the manual verification is to re-verify the judgment result made by the automatic verification model, and if the verification result is consistent, the payment is required; if the rechecking results are inconsistent, rechecking the application, and simultaneously, feeding back the rechecking results and the information which does not pass the rechecking to the automatic approval model so as to adjust and update the automatic approval model according to the approval mode of the cases. For the service event information set in the in-doubt state, the main task of the manual review is to determine whether the in-doubt is established, and divide the nature of the cases according to the in-doubt condition (such as determining whether the case is repeatedly applied for, whether a cheat protection condition exists, etc.).

Fig. 10 is a flowchart of sending early warning for service event information in an in-doubt state by a needle pair according to the matching degree with matching information, and selecting to send early warning information, as shown in fig. 10, where the sending early warning for service event information in an in-doubt state by a needle pair according to the matching degree with matching information, and specifically includes:

s410, carrying out secondary comparison on the service event information set in the in-doubt state and the data information in the data acquisition module, and generating a matching degree according to a comparison result;

And S420, automatically sending corresponding early warning information to the insurance system according to the matching degree.

It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in various embodiments may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.

Those skilled in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, where the program may be stored in a non-volatile computer readable storage medium, and where the program, when executed, may include processes in the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.

The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The foregoing examples illustrate only a few embodiments of the invention and are described in detail herein without thereby limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.

The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.

Claims

1. An insurance core system monitoring system, said system comprising:

2. The insurance core system monitoring system of claim 1, wherein said data acquisition module includes:

3. The insurance core system monitoring system of claim 1, wherein said event logging module includes:

4. The insurance core system monitoring system of claim 1, wherein said data comparison module includes:

5. The insurance core system monitoring system of claim 1, wherein said event early warning module includes:

6. A method of insurance core system monitoring, the method comprising:

7. The method for monitoring an insurance core system according to claim 6, wherein the collecting business transaction data and customer information and matching and associating the business transaction data and customer information comprises:

8. The method for monitoring an insurance core system according to claim 6, wherein said recording the service event in which the payment has occurred and the service event in which the payment has been applied, while establishing a neural network model, and establishing an automatic approval model based on the service event information in which the payment has occurred or the payment has been refused, specifically comprises:

9. The method for monitoring the insurance core system according to claim 6, wherein the auditing of the business event information applied for reimbursement by the automatic approval model, the setting of the business event information which cannot pass the automatic approval model as in-doubt state, and the uploading of the business event information and the conforming event information specifically comprise:

10. The method for monitoring an insurance core system according to claim 6, wherein said sending an early warning to the service event information in the in-doubt state by said needle, and selecting to send the early warning information according to the matching degree with the matching information, specifically comprises: