CN117036009B - Full-period management method and system for security service - Google Patents
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Abstract
The present disclosure provides a full period management method and system for a policy service, and relates to the technical field of policy service management, where the method includes: collecting service information of a current warranty service to be managed; invoking the security record data of the creditor and the debtor; calculating and acquiring a first credit parameter, a second credit parameter, a third credit parameter and a fourth credit parameter of the warranty service; training a warranty analyzer to obtain a plurality of analysis results; and carrying out consistency verification, carrying out management decision of the security service based on the qualified analysis results, and managing the security service. According to the method and the device for managing the security service, the technical problem that the efficiency of managing the security service according to the evaluation is low due to the fact that the efficiency of evaluating the security service risk of both sides of the transaction is low in the prior art can be solved, the goal of improving the efficiency of evaluating the security service risk of both sides of the transaction is achieved, and the technical effect of improving the efficiency of managing the security service according to the evaluation is achieved.
Description
Technical Field
The disclosure relates to the technical field of management of security services, in particular to a full-period management method and system of the security services.
Background
The insurance management service is that the seller transfers the liability generated based on the sales contract with the buyer to the bank according to the contract relation, and the bank provides service medium items such as trade financing, sales ledger management, receivability deposit and credit risk control, bad account guarantee and the like for the seller aiming at the assigned receivability deposit to carry out comprehensive financial service. When the security service is carried out, the risk of the security service is judged by evaluating the operation condition of the buyer and the personal credit, but the risk evaluation efficiency of the security service in the prior art is lower, so that the technical problem that the efficiency of the security service management according to the evaluation is lower because the efficiency of evaluating the risk of the security service carried out by both transaction parties is lower in the prior art is solved.
Disclosure of Invention
The disclosure provides a full-period management method and system for a security service, which are used for solving the technical problem in the prior art that the efficiency of security service management according to evaluation is low due to the fact that the efficiency of evaluating risks of security services carried out by both sides of a transaction is low.
According to a first aspect of the present disclosure, there is provided a full cycle management method of a security service, including: collecting service information of a current security service to be managed, wherein the service information comprises creditor information, debtor information, debt amount information and financing amount information; according to the creditor information and the debtor information, invoking security record data of the creditor and the debtor; according to the security record data, the debt limit information and the financing limit information of the creditors and the debt persons, and in combination with the historical security service management data, calculating and obtaining a first credit parameter, a second credit parameter, a third credit parameter and a fourth credit parameter of the security service; training a warranty analyzer based on historical warranty business record data, wherein the warranty analyzer comprises a plurality of warranty analysis channels, and each warranty analysis channel comprises a risk degree analysis branch and a feasibility degree analysis branch; adopting the warranty analyzer to analyze the first credit parameter, the second credit parameter, the third credit parameter and the fourth credit parameter to obtain a plurality of analysis results, wherein each analysis result comprises risk and feasibility; and carrying out consistency verification on a plurality of analysis results, calculating to obtain comprehensive risk and comprehensive feasibility based on a plurality of qualified analysis results meeting consistency requirements, carrying out management decision of the security service, obtaining a management scheme, and managing the security service.
According to a second aspect of the present disclosure, there is provided a full cycle management system of a policy service, including: the system comprises a service information acquisition module, a service information management module and a service information management module, wherein the service information acquisition module is used for acquiring service information of a current to-be-managed warranty service, wherein the service information comprises creditor information, debtor information, debt amount information and financing amount information; the warranty record data acquisition module is used for calling warranty record data of the creditor and the debtor according to the creditor information and the debtor information; the first credit parameter obtaining module is used for calculating and obtaining a first credit parameter, a second credit parameter, a third credit parameter and a fourth credit parameter of a security service according to security record data, debt credit information and financing credit information of the creditor and the debt, and by combining with historical security service management data; the risk degree analysis branch acquisition module is used for training a warranty analyzer based on historical warranty business record data, wherein the warranty analyzer comprises a plurality of warranty analysis channels, and each warranty analysis channel comprises a risk degree analysis branch and a feasibility degree analysis branch; the analysis result obtaining module is used for analyzing the first credit parameter, the second credit parameter, the third credit parameter and the fourth credit parameter by adopting the warranty analyzer to obtain a plurality of analysis results, wherein each analysis result comprises risk and feasibility; the management scheme obtaining module is used for carrying out consistency verification on a plurality of analysis results, calculating and obtaining comprehensive risk and comprehensive feasibility based on a plurality of qualified analysis results meeting consistency requirements, carrying out management decision of the security service, obtaining a management scheme and managing the security service.
One or more technical solutions provided in the present disclosure have at least the following technical effects or advantages: according to the service information of the security service to be managed currently, the service information comprises creditor information, debtor information, debt amount information and financing amount information; according to the creditor information and the debtor information, invoking security record data of the creditor and the debtor; according to the security record data, the debt limit information and the financing limit information of the creditors and the debt persons, and in combination with the historical security service management data, calculating and obtaining a first credit parameter, a second credit parameter, a third credit parameter and a fourth credit parameter of the security service; training a warranty analyzer based on historical warranty business record data, wherein the warranty analyzer comprises a plurality of warranty analysis channels, and each warranty analysis channel comprises a risk degree analysis branch and a feasibility degree analysis branch; adopting the warranty analyzer to analyze the first credit parameter, the second credit parameter, the third credit parameter and the fourth credit parameter to obtain a plurality of analysis results, wherein each analysis result comprises risk and feasibility; the consistency verification is carried out on a plurality of analysis results, the comprehensive risk degree and the comprehensive feasibility degree are calculated and obtained based on a plurality of qualified analysis results meeting the consistency requirement, the management decision of the insurance service is carried out, the management scheme is obtained, the insurance service is managed, the technical problem that the efficiency of the insurance service management according to the evaluation is low due to the fact that the efficiency of the insurance service management according to the evaluation is low in the prior art is solved, the goal of improving the insurance service risk efficiency of the evaluation and the insurance service management according to the evaluation is achieved, and the technical effect of improving the insurance service management efficiency according to the evaluation is achieved.
It should be understood that the description of this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.
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For a clearer description of the present disclosure or of the prior art, the drawings used in the description of the embodiments or of the prior art will be briefly described, it being obvious that the drawings in the description below are only exemplary and that other drawings may be obtained, without inventive effort, by a person skilled in the art, from the provided drawings.
Fig. 1 is a flow chart of a full cycle management method of a security service according to an embodiment of the disclosure;
fig. 2 is a schematic flow chart of training and obtaining a policy analyzer in a full-period management method of a policy service according to an embodiment of the disclosure;
fig. 3 is a schematic structural diagram of a full-period management system for a security service according to an embodiment of the disclosure.
Reference numerals illustrate: the system comprises a service information obtaining module 11, a warranty record data obtaining module 12, a first credit parameter obtaining module 13, a risk analysis branch obtaining module 14, an analysis result obtaining module 15 and a management scheme obtaining module 16.
Detailed Description
Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Example 1
The embodiment of the disclosure provides a full-period management method for a security service, and description is made with reference to fig. 1, where the method includes:
the method provided by the embodiment of the disclosure comprises the following steps:
collecting service information of a current security service to be managed, wherein the service information comprises creditor information, debtor information, debt amount information and financing amount information;
specifically, service information of a warranty service to be managed currently is collected through information extraction. The business information comprises creditor information, debtor information, debt limit information and financing limit information. Wherein the creditor transfers his receivables to the commercial bank and the debtor pays the debt to the commercial bank. For example, the debt line, financing line may be determined based on the manner in which the creditor grants credit to the debtor. The creditor information and the debtor information can acquire the operation scale information, the harvest information and the like of the two parties.
According to the creditor information and the debtor information, invoking security record data of the creditor and the debtor;
specifically, the creditor information and the debtor information can be used for obtaining the historical warranty business records of the creditor and the debtor through a method for extracting the information in a commercial bank system. In the history security service records, the abnormal records such as delay and credit loss of the creditor and the debtor are respectively extracted, the abnormal records are counted, and the obtained counting results are combined to obtain the security record data.
According to the security record data, the debt limit information and the financing limit information of the creditors and the debt persons, and in combination with the historical security service management data, calculating and obtaining a first credit parameter, a second credit parameter, a third credit parameter and a fourth credit parameter of the security service;
specifically, the average number of liability anomalies, average liability amount information, and average financing amount information of a plurality of liability persons and a plurality of liability persons with anomalies in the history warranty business management data are acquired. And acquiring the number of abnormal creditor rights, abnormal creditor number, debt amount information and financing amount information of the creditor. The average abnormal number of the liability and the abnormal number of the liability are compared, the average liability limit information and the liability limit information are compared, the average financing limit information and the financing limit information are compared, comparison results are respectively obtained, and the comparison difference is respectively used as a first credit parameter, a second credit parameter, a third credit parameter and a fourth credit parameter of the security service.
Training a warranty analyzer based on historical warranty business record data, wherein the warranty analyzer comprises a plurality of warranty analysis channels, and each warranty analysis channel comprises a risk degree analysis branch and a feasibility degree analysis branch;
specifically, according to the historical warranty business record data, a historical first credit parameter set, a historical second credit parameter set, a historical third credit parameter set and a historical fourth credit parameter set are obtained. And respectively taking the historical first credit parameter set, the historical second credit parameter set, the historical third credit parameter set and the historical fourth credit parameter set as a sample first credit parameter set, a sample second credit parameter set, a sample third credit parameter set and a sample fourth credit parameter set. And evaluating and acquiring a sample risk degree set and a sample feasibility degree set according to the sample first credit degree parameter set, the sample second credit degree parameter set, the sample third credit degree parameter set and the sample fourth credit degree parameter set. And training the warranty analyzer through the sample first credit parameter set, the sample second credit parameter set, the sample third credit parameter set, the sample fourth credit parameter set, the sample risk set and the sample feasibility set. The warranty analyzer comprises a plurality of warranty analysis channels, and each warranty analysis channel comprises a risk analysis branch and a feasibility analysis branch. The training data of the plurality of warranty analysis channels is different. The risk degree analysis branch is used for training a first credit degree parameter set of a sample, a second credit degree parameter set of the sample, a third credit degree parameter set of the sample, a fourth credit degree parameter set of the sample and a risk degree set of the sample. The feasibility analysis branch is used for training a first confidence parameter set of a sample, a second confidence parameter set of the sample, a third confidence parameter set of the sample, a fourth confidence parameter set of the sample and a feasibility set of the sample.
Adopting the warranty analyzer to analyze the first credit parameter, the second credit parameter, the third credit parameter and the fourth credit parameter to obtain a plurality of analysis results, wherein each analysis result comprises risk and feasibility;
specifically, the first credit parameter, the second credit parameter, the third credit parameter and the fourth credit parameter are input into a plurality of warranty analysis channels in a warranty analyzer for analysis, and different analysis results are obtained through the plurality of warranty analysis channels. Wherein, each analysis result comprises a risk degree and a feasibility degree.
And carrying out consistency verification on a plurality of analysis results, calculating to obtain comprehensive risk and comprehensive feasibility based on a plurality of qualified analysis results meeting consistency requirements, carrying out management decision of the security service, obtaining a management scheme, and managing the security service.
Specifically, the risk and feasibility are integers less than 1. For example, the risk and feasibility are converted into percentages, the risk is 30%, and the risk is 0.3. Further, consistency verification is carried out on the risk degree and the feasibility degree in each analysis result in the plurality of analysis results, whether the consistency requirement is met or not is judged, and a consistency verification result is obtained. Wherein, the requirement of consistency check is that the sum of risk degree and feasibility degree is 1. Further, when the consistency check result meets the consistency requirement, a qualified analysis result is obtained.
The method and the device can solve the technical problem that in the prior art, the efficiency of carrying out the security service management according to the evaluation is low due to the fact that the efficiency of carrying out the security service risk by the evaluation transaction parties is low, achieve the aim of improving the efficiency of carrying out the security service risk by the evaluation transaction parties, and achieve the technical effect of improving the efficiency of carrying out the security service management according to the evaluation.
The method provided by the embodiment of the disclosure further comprises the following steps:
according to the creditor information and the debtor information, the abnormal times of the creditor and the debtor in the preset historical time range when carrying out the security service are called, and the abnormal times of the creditor and the abnormal times of the debt are obtained;
and taking the abnormal times of the creditor and the abnormal times of the debt as the warranty record data of the creditor and the debt to obtain the creditor record data and the debt record data.
Specifically, according to the creditor information and the debtor information, the abnormal times of the creditor and the debtor when the creditor and the debtor perform the security service in the preset historical time range are called, counting is carried out, and the abnormal times of the creditor and the abnormal times of the debtor are obtained. For example, the preset history time range is the past month. Wherein, the abnormality is an abnormality such as delay, belief loss, etc. For example, an exception is a criterion that is against a contract.
Further, the right record data and the liability record data are obtained by adding and serving as the right person and the liability person's warranty record data according to the right abnormality times and the liability abnormality times.
And judging the cooperation reliability of the cooperation parties by acquiring the credited record data and the liability record data, thereby improving the management efficiency of the security service.
The method provided by the embodiment of the disclosure further comprises the following steps:
acquiring a plurality of creditors, a plurality of debt abnormal times set of the creditors, a plurality of debt abnormal times set, a debt amount information set and a financing amount information set of a normal insurance business according to the insurance business record data in the history time;
calculating the average value of the abnormal number of the debt, the information set of the debt and the information set of the financing line to obtain the average abnormal number of the debt, the average debt information and the average financing line information;
constructing a security feature data matrix based on the average right abnormal times, the average debt amount information, the average financing amount information, the right abnormal times, the debt amount information and the financing amount information;
And according to the warranty feature data matrix, calculating and acquiring a first credit parameter, a second credit parameter, a third credit parameter and a fourth credit parameter.
Specifically, according to the security business record data in the history time, the abnormal times of the debt of the plurality of creditors and the abnormal times of the debt of the plurality of debts are obtained and used as a set of abnormal times of the debt and a set of abnormal times of the debt, and a set of debt and financing amount information of the normal security business. The abnormal times of the plurality of creditor and the plurality of debt abnormal times are obtained by abnormal calculation of a plurality of different creditors and debtors of the security service in the historical time and are used for evaluating the credit of the creditor and the debtor corresponding to the security service record data.
Further, average values are calculated for the abnormal number of debt times set, the information set of debt amount and the information set of financing amount respectively, and average abnormal number of debt, average abnormal number of debt amount, average information of debt amount and average financing amount are obtained in sequence.
Further, a warranty feature data matrix is constructed, and the average right abnormal times, the average debt amount information, the average financing amount information, the right abnormal times, the debt amount information and the financing amount information are added to the warranty feature data matrix. The first column data in the warranty feature data matrix sequentially comprise average right abnormal times, average debt amount information and average financing amount information, the second column data sequentially comprises right abnormal times, debt amount information and financing amount information, and the first column data and the second column data are in one-to-one correspondence.
Further, according to the warranty feature data matrix, the first column data and the second column data are compared to obtain four groups of comparison results, and the four groups of comparison results are sequentially used as a first credit parameter, a second credit parameter, a third credit parameter and a fourth credit parameter. The first credit parameter is a comparison difference value of average right-of-debt abnormal times and right-of-debt abnormal times.
The first credit parameter, the second credit parameter, the third credit parameter and the fourth credit parameter are calculated and acquired, the average level of the warranty business is evaluated, and then the current warranty business is evaluated.
The method provided by the embodiment of the disclosure further comprises the following steps:
according to the warranty feature data matrix, a first credit parameter is calculated as follows:
；
wherein,for the first credit parameter,/a>For average number of credited anomalies, +.>The number of the right-of-debt anomalies is;
and continuing to calculate and obtain a second credit parameter, a third credit parameter and a fourth credit parameter.
Specifically, according to the warranty feature data matrix, a first credit parameter is calculated as follows:
；
wherein,for the first credit parameter,/a>For average number of credited anomalies, +.>Is the number of abnormal credited times.
Further, continuing to calculate to obtain a second credit parameter, a third credit parameter and a fourth credit parameter, wherein the following formula is as follows:
；
Wherein,for the second credit parameter, +.>For average debt anomaly count +.>Is the abnormal number of debt.
；
Wherein,for the third credit parameter, +.>For average debt amount information +.>Is debt amount information.
；
Wherein,for the fourth credit parameter, +.>For average financing amount information +.>And information about financing amount.
And calculating the first credit parameter, the second credit parameter, the third credit parameter and the fourth credit parameter through a formula, so that the accuracy of evaluating the average level of the warranty service is improved.
The method provided by the embodiment of the disclosure further comprises the following steps:
based on the warranty business record data in the history time, processing and acquiring a first credit parameter set of a sample, a second credit parameter set of the sample, a third credit parameter set of the sample and a fourth credit parameter set of the sample;
evaluating and acquiring a sample risk level set and a sample feasibility level set according to the sample first credit level parameter set, the sample second credit level parameter set, the sample third credit level parameter set and the sample fourth credit level parameter set;
and training the warranty analyzer by adopting the first sample credit parameter set, the second sample credit parameter set, the third sample credit parameter set, the fourth sample credit parameter set, the sample risk set and the sample feasibility set as training data sets.
Specifically, as shown in fig. 2, based on the warranty business record data in the history time, the first credit parameter set, the second credit parameter set, the third credit parameter set and the fourth credit parameter set of the sample are obtained by processing.
Further, according to the first credit parameter set of the sample, the second credit parameter set of the sample, the third credit parameter set of the sample and the fourth credit parameter set of the sample, the risk degree set of the sample and the feasibility degree set of the sample are estimated and obtained. The method comprises the steps of setting a preset first credit parameter set threshold, a preset second credit parameter set threshold, a preset third credit parameter set threshold and a preset fourth credit parameter set threshold. The setting mode is set by a person skilled in the art based on actual conditions. Further, whether the first confidence coefficient parameter set of the sample meets a preset first confidence coefficient parameter set threshold value is judged, the sample risk degree is obtained, and the sample feasibility degree is obtained according to the sample risk degree. And respectively judging whether the second confidence coefficient parameter set of the sample, the third confidence coefficient parameter set of the sample and the fourth confidence coefficient parameter set of the sample accord with a threshold value or not to obtain a plurality of sample risk degrees and a plurality of sample feasibility degrees. When the first confidence coefficient parameter set of the sample meets a preset first confidence coefficient parameter set threshold, the corresponding sample risk degree is lower, and the feasibility of the sample is higher. Further, a plurality of sample risk degrees are combined to obtain a sample risk degree set, and a plurality of sample feasibility degrees are combined to obtain a sample feasibility degree set.
Further, a first confidence parameter set of the sample, a second confidence parameter set of the sample, a third confidence parameter set of the sample, a fourth confidence parameter set of the sample, a risk set of the sample and a feasibility set of the sample are used as training data sets to train a warranty analyzer. The first credit parameter set, the second credit parameter set, the third credit parameter set and the fourth credit parameter set are used as input data in a training data set, and the risk degree set and the feasibility degree set are used as output data and supervision data in the training data set. Further, the training data set includes M sets of training data, each set of training data including a randomly extracted first confidence parameter of a sample, a second confidence parameter of a sample, a third confidence parameter of a sample, a fourth confidence parameter of a sample, a risk set of samples, and a feasibility of a sample.
Wherein, training to obtain the warranty analyzer can improve the efficiency and the accuracy of evaluating the warranty business.
The method provided by the embodiment of the disclosure further comprises the following steps:
randomly extracting the set of the training data with a put-back ground to obtain a first training data set, and dividing the first training data set to obtain a first risk training data set and a first feasible training data set;
Adopting the first risk training data set and the first feasible training data set to construct a risk degree analysis branch and a feasibility degree analysis branch in a first maintenance analysis channel, and performing supervision training until meeting convergence conditions;
continuously randomly extracting the set with the place back in the training data set to obtain a second training data set, and dividing the second training data set to obtain a second risk training data set and a second feasible training data set;
continuously training a risk degree analysis branch and a feasibility degree analysis branch in the second warranty analysis channel;
and continuing to construct training to obtain a plurality of warranty analysis channels to obtain the warranty analyzer.
As shown in fig. 2, in particular, a first training data set is obtained by random extraction with a put back in the training data set. The first training data set is a random plurality of groups of data in input data and output data and supervision data in the training data set. Further, the first training data set includes a first sample first confidence parameter, a first sample second confidence parameter, a first sample third confidence parameter, a first sample fourth confidence parameter, a first sample risk and a first sample feasibility that are randomly obtained, and further includes a second sample first confidence parameter, a second sample second confidence parameter, a second sample third confidence parameter, a second sample fourth confidence parameter, a second sample risk and a second sample feasibility that are randomly obtained, and further includes a randomly obtained nth sample first confidence parameter, an nth sample second confidence parameter, an nth sample third confidence parameter, an nth sample fourth confidence parameter, an nth sample risk and an nth sample feasibility. Further, the first training data set is N groups of training data obtained by randomly extracting M groups of training data. Wherein the number of N sets of training data in the first training data set is less than the number of M sets of training data, so N is less than M. For example, the first training data set is a first set of training data, a third set of training data, and a fifth set of training data obtained by random extraction.
Further, the first training data set is partitioned into a first risk training data set and a first viable training data set. The first risk training data set comprises N sample first confidence parameters, N sample second confidence parameters, N sample third confidence parameters, N sample fourth confidence parameters and N sample risk degrees in N groups of training data. The first feasible training data set comprises N samples of first confidence parameters, N samples of second confidence parameters, N samples of third confidence parameters, N samples of fourth confidence parameters and N samples of feasibility in the N groups of training data.
Further, the warranty analyzer includes a plurality of warranty analysis channels, and randomly extracts one warranty analysis channel as the first warranty analysis channel. Each warranty analysis channel is provided with a risk analysis branch and a feasibility analysis branch. Further, a first risk training data set and a first feasible training data set are adopted to construct a risk degree analysis branch and a feasibility degree analysis branch in a first maintenance analysis channel, and supervision training is carried out on the risk degree analysis branch and the feasibility degree analysis branch according to the first risk training data set and the first feasible training data set respectively until convergence conditions are met. And randomly selecting a group of first risk training data from the first risk training data set, and performing supervised training on the risk degree analysis branch according to the first risk training data to obtain a first output result of the risk degree analysis branch. And then comparing the first output result with the first risk training data. And when the comparison results are consistent, inputting and supervising the training of another group of first risk training data randomly selected in the first risk training data set. When the comparison results are inconsistent, calculating the deviation between the first output result and the first risk training data, optimizing the risk degree analysis branch according to the deviation, and performing supervision training on the other group of first risk training data randomly selected in the first risk training data set. And performing iterative supervision training through training the first risk training data set until the output result of the risk degree analysis branch tends to be in a convergence state. Further, according to the method for acquiring the risk degree analysis branch, the feasibility degree analysis branch is acquired correspondingly. And performing supervised training on the first feasible training data set until the output result of the feasibility analysis branch tends to be in a convergence state. Further, combining the training risk degree analysis branch and the feasibility degree analysis branch to obtain a first maintenance analysis channel.
Further, random extraction with a put back in the training data set is continued to obtain a second training data set, and the second risk training data set and the second feasible training data set are obtained through division. Further, the second training data set includes Q sets of training data randomly extracted from the M sets of training data. Wherein the number of Q sets of training data in the second training data set is less than the number of M sets of training data, and therefore Q is less than M. For example, the second training data set is a first set of training data, a fourth set of training data, a fifth set of training data, and a seventh set of training data obtained by random extraction. Further, the second risk training data set includes Q sample first confidence parameters, Q sample second confidence parameters, Q sample third confidence parameters, Q sample fourth confidence parameters, and Q sample risk degrees in the Q sets of training data. The second feasible training data set comprises Q sample first confidence parameters, Q sample second confidence parameters, Q sample third confidence parameters, Q sample fourth confidence parameters and Q sample feasibility in the Q group training data.
Further, the second warranty analysis channel is obtained by randomly extracting from the warranty analyzer. And continuing to train the risk degree analysis branch and the feasibility degree analysis branch in the second warranty analysis channel through the second training data set until the convergence condition is met.
Further, the training data set is continuously extracted, a plurality of warranty analysis channels are constructed and trained to obtain, and the warranty analysis channels are combined to obtain the warranty analyzer.
The construction data of each warranty analysis channel are not identical, so that the performances of each channel are different, different outputs can be obtained for the same input, the outputs of a plurality of warranty analysis channels are integrated, the output accuracy of the warranty analyzer is improved, and meanwhile, the construction data of each warranty analysis channel are relatively less and are easier to converge.
The method provided by the embodiment of the disclosure further comprises the following steps:
consistency verification is carried out based on the risk degree and the feasibility degree in each analysis result, and whether the consistency requirement is met is judged;
calculating a mean value according to a plurality of risk degrees and a plurality of feasibility degrees in a plurality of qualified analysis results meeting consistency requirements to obtain comprehensive risk degrees and comprehensive feasibility degrees;
acquiring a sample risk degree set, a sample feasibility degree set and a sample management scheme set based on the warranty business management data in the history time;
based on the decision tree, a sample risk degree set, a sample feasibility degree set and a sample management scheme set are adopted to construct a management decision path;
And acquiring a management scheme for managing the insurance business, wherein the management scheme is obtained by inputting the comprehensive risk degree and the comprehensive feasibility degree into a management decision path for decision.
Specifically, the risk and feasibility are integers less than 1. And carrying out consistency check on the risk degree and the feasibility degree in each analysis result in the plurality of analysis results, judging whether the consistency requirement is met, and obtaining a consistency check result. Wherein the consistency requirement is that the sum of the risk degree and the feasibility degree is 1. Further, when the consistency check result does not meet the consistency requirement, namely the sum of the risk degree and the feasibility degree is not 1, the model analysis is inaccurate or other problems occur, and the output data of the warranty analyzer is not credible. Correspondingly, when the consistency check result meets the consistency requirement, namely the sum of the risk degree and the feasibility degree is 1, a qualified analysis result is obtained.
Further, for a plurality of risk degrees and a plurality of feasibility degrees in a plurality of qualified analysis results meeting the consistency requirement, respectively calculating the average value to respectively obtain the comprehensive risk degrees and the comprehensive feasibility degrees.
Further, based on the insurance business management data in the historical time, a sample risk degree set, a sample feasibility degree set and a sample management scheme set are obtained by obtaining a sample first credit degree parameter set, a sample second credit degree parameter set, a sample third credit degree parameter set and a sample fourth credit degree parameter set and calculating.
Further, the sample risk degree set and the sample feasibility degree set are used as decision input, the sample management scheme set is used as decision output, and a built management decision path comprises a plurality of layers of decision nodes. The method can be used for judging and classifying according to the risk degree in the input sample risk degree set or the feasibility degree in the sample feasibility degree set, and obtaining a corresponding management scheme after multi-layer judgment and classification. The management scheme comprises not accepting the insurance business, accepting but adjusting the insurance business, accepting the insurance business, and the like.
Further, the comprehensive risk and the comprehensive feasibility are input into a management decision path, a management scheme is obtained after multi-layer judgment and classification, and the management service is managed according to the management scheme. The decision scheme is acquired through the decision path so as to improve the reliability of the acquired management scheme.
Example two
Based on the same inventive concept as the full-period management method of a security service in the foregoing embodiment, the disclosure will be described with reference to fig. 3, and the disclosure further provides a full-period management system of a security service, where the system includes:
the service information obtaining module 11 is configured to collect service information of a warranty service to be managed currently, where the service information includes creditor information, debtor information, debt amount information, and financing amount information;
A warranty record data obtaining module 12, where the warranty record data obtaining module 12 is configured to retrieve warranty record data of the creditor and the debtor according to the creditor information and the debtor information;
the first credit parameter obtaining module 13 is configured to calculate and obtain a first credit parameter, a second credit parameter, a third credit parameter and a fourth credit parameter of a security service according to security record data, debt amount information and financing amount information of the creditor and the debt, and by combining with historical security service management data;
the risk analysis branch obtaining module 14 is configured to train a warranty analyzer based on the historical warranty business record data, where the warranty analyzer includes a plurality of warranty analysis channels, and each warranty analysis channel includes a risk analysis branch and a feasibility analysis branch;
the analysis result obtaining module 15 is configured to analyze the first credit parameter, the second credit parameter, the third credit parameter, and the fourth credit parameter by using the warranty analyzer to obtain a plurality of analysis results, where each analysis result includes a risk degree and a feasibility degree;
The management scheme obtaining module 16 is configured to perform consistency verification on a plurality of analysis results, calculate and obtain a comprehensive risk degree and a comprehensive feasibility degree based on a plurality of qualified analysis results meeting a consistency requirement, perform a management decision of a management service, obtain a management scheme, and manage the management service.
Further, the system further comprises:
the right and liability anomaly number acquisition module is used for acquiring the abnormal number of times of the right and liability people when carrying out security service in a preset historical time range according to the right and liability people information, and acquiring the right and liability anomaly number of times;
the right record data obtaining module is used for obtaining right record data and liability record data by taking the right abnormal times and liability abnormal times as security record data of right people and liability people.
Further, the system further comprises:
the right abnormal times collection obtaining module is used for obtaining right abnormal times collection and right abnormal times collection of a plurality of right people and a plurality of debtors, and a right amount information collection and a financing amount information collection of normal right service according to the data of the right abnormal times collection and right abnormal times collection of the right people and the debtors in the history time;
The average value calculating module is used for calculating the average value of the right-of-debt abnormal times set, the debt amount information set and the financing amount information set to obtain average right-of-debt abnormal times, average debt amount information and average financing amount information;
the warranty feature data matrix obtaining module is used for constructing a warranty feature data matrix based on average credit abnormal times, average credit limit information, average financing limit information, credit abnormal times, debt limit information and financing limit information;
the first credit parameter obtaining module is used for calculating and obtaining a first credit parameter, a second credit parameter, a third credit parameter and a fourth credit parameter according to the warranty feature data matrix.
Further, the system further comprises:
the first credit parameter calculation module is used for calculating a first credit parameter according to the warranty feature data matrix, and the formula is as follows:
；
A first credit parameter processing module is provided,the first credit parameter processing module is used for the first credit parameter processing module,for the first credit parameter,/a>For average number of credited anomalies, +.>The number of the right-of-debt anomalies is;
and the continuous calculation module is used for continuously calculating and obtaining the second credit parameter, the third credit parameter and the fourth credit parameter.
Further, the system further comprises:
the system comprises a sample first credit parameter set obtaining module, a sample second credit parameter set obtaining module and a sample third credit parameter set, wherein the sample first credit parameter set obtaining module is used for processing and obtaining a sample first credit parameter set, a sample second credit parameter set, a sample third credit parameter set and a sample fourth credit parameter set based on the warranty business record data in the history time;
the sample risk degree set obtaining module is used for evaluating and obtaining a sample risk degree set and a sample feasibility degree set according to the sample first credit degree parameter set, the sample second credit degree parameter set, the sample third credit degree parameter set and the sample fourth credit degree parameter set;
and the warranty analyzer training module is used for training the warranty analyzer by adopting the first sample credit parameter set, the second sample credit parameter set, the third sample credit parameter set, the fourth sample credit parameter set, the sample risk set and the sample feasibility set as training data sets.
Further, the system further comprises:
the first risk training data set obtaining module is used for randomly extracting a first training data set with a place in the training data set, and dividing the first risk training data set and a first feasible training data set;
the monitoring training module is used for constructing a risk degree analysis branch and a feasibility degree analysis branch in a first management analysis channel by adopting the first risk training data set and the first feasible training data set, and performing monitoring training until meeting convergence conditions;
the second risk training data set obtaining module is used for continuing to randomly extract the second risk training data set with a place in the training data set to obtain a second training data set, and dividing the second risk training data set and a second feasible training data set;
the risk degree analysis branch obtaining module is used for continuously training the risk degree analysis branch and the feasibility degree analysis branch in the second warranty analysis channel;
and the warranty analyzer obtaining module is used for continuing to construct training to obtain a plurality of warranty analysis channels so as to obtain the warranty analyzer.
Further, the system further comprises:
the consistency verification module is used for carrying out consistency verification based on the risk degree and the feasibility degree in each analysis result and judging whether the consistency requirement is met;
the comprehensive risk degree obtaining module is used for calculating a mean value according to a plurality of risk degrees and a plurality of feasibility degrees in a plurality of qualified analysis results meeting consistency requirements to obtain a comprehensive risk degree and a comprehensive feasibility degree;
the sample risk degree set obtaining module is used for obtaining a sample risk degree set, a sample feasibility degree set and a sample management scheme set based on the management data of the insurance business in the history time;
the management decision path obtaining module is used for constructing a management decision path by adopting a sample risk degree set, a sample feasibility degree set and a sample management scheme set based on a decision tree;
the management scheme decision module is used for acquiring a management scheme and managing the security service, and the management scheme is acquired by inputting the comprehensive risk and the comprehensive feasibility into a management decision path decision.
The specific example of the full-period management method for a security service in the first embodiment is also applicable to the full-period management system for a security service in the present embodiment, and those skilled in the art can clearly know the full-period management system for a security service in the present embodiment through the foregoing detailed description of the full-period management method for a security service, so that the description is omitted herein for brevity. The device disclosed in the embodiment corresponds to the method disclosed in the embodiment, so that the description is simpler, and the relevant points refer to the description of the method.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel or sequentially or in a different order, provided that the desired results of the technical solutions of the present disclosure are achieved, and are not limited herein.
The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.
Claims (4)
1. A full cycle management method for a security service, the method comprising:
collecting service information of a current security service to be managed, wherein the service information comprises creditor information, debtor information, debt amount information and financing amount information;
according to the creditor information and the debtor information, invoking security record data of the creditor and the debtor;
according to the security record data, the debt limit information and the financing limit information of the creditors and the debt persons, and in combination with the historical security service management data, calculating and obtaining a first credit parameter, a second credit parameter, a third credit parameter and a fourth credit parameter of the security service;
training a warranty analyzer based on historical warranty business record data, wherein the warranty analyzer comprises a plurality of warranty analysis channels, and each warranty analysis channel comprises a risk degree analysis branch and a feasibility degree analysis branch;
inputting the first credit parameter, the second credit parameter, the third credit parameter and the fourth credit parameter into a plurality of warranty analysis channels in a warranty analyzer for analysis to obtain a plurality of analysis results, wherein each analysis result comprises risk degree and feasibility degree;
Performing consistency verification on a plurality of analysis results, calculating to obtain comprehensive risk and comprehensive feasibility based on a plurality of qualified analysis results meeting consistency requirements, performing management decision of the security service, obtaining a management scheme, and managing the security service;
consistency verification is carried out based on the risk degree and the feasibility degree in each analysis result, and whether the consistency requirement is met is judged;
calculating a mean value according to a plurality of risk degrees and a plurality of feasibility degrees in a plurality of qualified analysis results meeting consistency requirements to obtain comprehensive risk degrees and comprehensive feasibility degrees;
acquiring a sample risk degree set, a sample feasibility degree set and a sample management scheme set based on the warranty business management data in the history time;
based on the decision tree, a sample risk degree set, a sample feasibility degree set and a sample management scheme set are adopted to construct a management decision path;
acquiring a management scheme for managing the insurance business, wherein the management scheme is obtained by inputting the comprehensive risk degree and the comprehensive feasibility degree into a management decision path for decision;
the calculating to obtain the first credit parameter, the second credit parameter, the third credit parameter and the fourth credit parameter of the warranty service includes:
According to the creditor information and the debtor information, the abnormal times of the creditor and the debtor in the preset historical time range when carrying out the security service are called, and the abnormal times of the creditor and the abnormal times of the debt are obtained;
taking the abnormal times of the creditor and the abnormal times of the debt as the warranty record data of the creditor and the debt to obtain the creditor record data and the debt record data;
acquiring a plurality of creditors, a plurality of debt abnormal times set of the creditors, a plurality of debt abnormal times set, a debt amount information set and a financing amount information set of a normal insurance business according to the insurance business record data in the history time;
calculating the average value of the abnormal number of the debt, the information set of the debt and the information set of the financing line to obtain the average abnormal number of the debt, the average debt information and the average financing line information;
constructing a security feature data matrix based on the average right abnormal times, the average debt amount information, the average financing amount information, the right abnormal times, the debt amount information and the financing amount information;
According to the warranty feature data matrix, calculating and obtaining a first credit parameter, a second credit parameter, a third credit parameter and a fourth credit parameter;
according to the warranty feature data matrix, a first credit parameter is calculated as follows:
wherein k is 1 For the first confidence parameter, x 1 To average the number of abnormal creditor times, y 1 The number of the right-of-debt anomalies is;
continuing to calculate and obtain a second credit parameter, a third credit parameter and a fourth credit parameter, wherein the following formula is as follows:
wherein k is 2 For the second credit parameter, x 2 To average the abnormal times of debt, y 2 The number of debt anomalies;
wherein k is 3 For the third credit parameter, x 3 For average debt amount information, y 3 Is debt amount information;
wherein k is 4 For the fourth credit parameter, x 4 For average financing amount information, y 4 And information about financing amount.
2. The method according to claim 1, characterized in that the method comprises:
based on the warranty business record data in the history time, processing and acquiring a first credit parameter set of a sample, a second credit parameter set of the sample, a third credit parameter set of the sample and a fourth credit parameter set of the sample;
evaluating and acquiring a sample risk level set and a sample feasibility level set according to the sample first credit level parameter set, the sample second credit level parameter set, the sample third credit level parameter set and the sample fourth credit level parameter set;
And training the warranty analyzer by adopting the first sample credit parameter set, the second sample credit parameter set, the third sample credit parameter set, the fourth sample credit parameter set, the sample risk set and the sample feasibility set as training data sets.
3. The method according to claim 2, characterized in that the method comprises:
randomly extracting the set of the training data with a put-back ground to obtain a first training data set, and dividing the first training data set to obtain a first risk training data set and a first feasible training data set;
adopting the first risk training data set and the first feasible training data set to construct a risk degree analysis branch and a feasibility degree analysis branch in a first maintenance analysis channel, and performing supervision training until meeting convergence conditions;
continuously randomly extracting the set with the place back in the training data set to obtain a second training data set, and dividing the second training data set to obtain a second risk training data set and a second feasible training data set;
continuously training a risk degree analysis branch and a feasibility degree analysis branch in the second warranty analysis channel;
and continuing to construct training to obtain a plurality of warranty analysis channels to obtain the warranty analyzer.
4. A full-period management system for a security service, characterized by implementing a full-period management method for a security service according to any one of claims 1 to 3, the system comprising:
The system comprises a service information acquisition module, a service information management module and a service information management module, wherein the service information acquisition module is used for acquiring service information of a current to-be-managed warranty service, wherein the service information comprises creditor information, debtor information, debt amount information and financing amount information;
the warranty record data acquisition module is used for calling warranty record data of the creditor and the debtor according to the creditor information and the debtor information;
the first credit parameter obtaining module is used for calculating and obtaining a first credit parameter, a second credit parameter, a third credit parameter and a fourth credit parameter of a security service according to security record data, debt credit information and financing credit information of the creditor and the debt, and by combining with historical security service management data;
the risk degree analysis branch acquisition module is used for training a warranty analyzer based on historical warranty business record data, wherein the warranty analyzer comprises a plurality of warranty analysis channels, and each warranty analysis channel comprises a risk degree analysis branch and a feasibility degree analysis branch;
the analysis result obtaining module is used for inputting the first credit parameter, the second credit parameter, the third credit parameter and the fourth credit parameter into a plurality of warranty analysis channels in the warranty analyzer for analysis to obtain a plurality of analysis results, wherein each analysis result comprises risk and feasibility;
The management scheme obtaining module is used for carrying out consistency verification on a plurality of analysis results, calculating and obtaining comprehensive risk and comprehensive feasibility based on a plurality of qualified analysis results meeting consistency requirements, carrying out management decision of the security service, obtaining a management scheme and managing the security service.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108171602A (en) * | 2017-06-28 | 2018-06-15 | 永辉青禾商业保理(重庆)有限公司 | The method for building up and device of accounts receivable factoring business risk model |
| CN111932383A (en) * | 2019-04-27 | 2020-11-13 | 深圳前海星概念信息技术有限公司 | Warranty service management platform |
| CN113822488A (en) * | 2021-09-29 | 2021-12-21 | 平安国际融资租赁有限公司 | Risk prediction method and device for financing lease, computer equipment and storage medium |
| CN114581212A (en) * | 2022-02-14 | 2022-06-03 | 深圳宏景动力信息技术有限公司 | Warranty service management method and system |
| CN115496370A (en) * | 2022-09-26 | 2022-12-20 | 广州鼎盛商业保理有限公司 | Warranty service management system and management method |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070255647A1 (en) * | 2006-03-30 | 2007-11-01 | Adattive Alpha, Llc | System, method and computer program product for evaluating and rating counterparty risk using experiential business process performance and financial data, and applications thereof |
| WO2015056256A1 (en) * | 2013-10-17 | 2015-04-23 | Orange Money Ezbob Israel Ltd | Method of automating a business loan life cycle |
-
2023
- 2023-10-09 CN CN202311295074.8A patent/CN117036009B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108171602A (en) * | 2017-06-28 | 2018-06-15 | 永辉青禾商业保理(重庆)有限公司 | The method for building up and device of accounts receivable factoring business risk model |
| CN111932383A (en) * | 2019-04-27 | 2020-11-13 | 深圳前海星概念信息技术有限公司 | Warranty service management platform |
| CN113822488A (en) * | 2021-09-29 | 2021-12-21 | 平安国际融资租赁有限公司 | Risk prediction method and device for financing lease, computer equipment and storage medium |
| CN114581212A (en) * | 2022-02-14 | 2022-06-03 | 深圳宏景动力信息技术有限公司 | Warranty service management method and system |
| CN115496370A (en) * | 2022-09-26 | 2022-12-20 | 广州鼎盛商业保理有限公司 | Warranty service management system and management method |
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