CN115439204A - Regional illegal collective resource risk assessment equipment - Google Patents
Regional illegal collective resource risk assessment equipment Download PDFInfo
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- CN115439204A CN115439204A CN202211080195.6A CN202211080195A CN115439204A CN 115439204 A CN115439204 A CN 115439204A CN 202211080195 A CN202211080195 A CN 202211080195A CN 115439204 A CN115439204 A CN 115439204A
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Abstract
The present disclosure relates to a regional illegal fundraising risk assessment device. After the equipment acquires enterprise information of registered enterprises in a target area, enterprise risk early warning indexes judged by a system, manually judged enterprise risk early warning indexes and occurred illegal collective resource case information, a first risk index corresponding to the enterprise in which the illegal collective resource case has occurred in the target area, a second risk index corresponding to other main bodies except the enterprise in which the illegal collective resource case has occurred, a third risk index corresponding to the enterprise in which the enterprise risk early warning indexes are judged manually and a fourth risk index corresponding to the enterprise in which the enterprise risk early warning indexes are judged by the system are determined according to the information, and a comprehensive risk index is determined according to the risk indexes, so that the illegal collective resource risks in the area can be quantitatively evaluated automatically through the equipment, participation of personnel in the illegal collective resource risk evaluation is reduced, the accuracy of the illegal collective resource risk evaluation is improved, and the efficiency of the illegal collective resource risk evaluation is also improved.
Description
Technical Field
The disclosure relates to the field of financial security, in particular to regional illegal funding risk assessment equipment.
Background
With the development of science and technology, the number of various financing platforms is increased explosively. Aiming at various financing platforms, the existing supervision measures are not sound enough, so that the phenomena of disordered financing market and illegal violation are frequent, and huge risks and hidden dangers are brought to the economy of China.
In the related technology, the national financial supervision department and the local financial supervision department mainly count the information of illegal collective resources, such as the amount of cases, the amount of cases and the like which have occurred in the jurisdiction according to the past working experience by related professionals so as to realize the evaluation of the illegal collective resources risk in the jurisdiction. However, this method relies on manual statistics and processing, which results in inaccurate evaluation results and low evaluation efficiency.
Disclosure of Invention
In order to solve the above technical problem or at least partially solve the above technical problem, the present disclosure provides a regional illegal fundraising risk assessment device, including a communication component, a first processor, and a second processor:
the communication component sends the acquired enterprise information of the registered enterprises in the target area, the enterprise risk early warning index judged by the system, the enterprise risk early warning index judged manually and the information of the illegal collective investment cases to the first processor;
the first processor determines a first risk index corresponding to an enterprise in which an illegal funding case has occurred in the target area and a second risk index corresponding to other main bodies except the enterprise in which the illegal funding case has occurred based on enterprise information of the registered enterprise in the target area and information of the illegal funding case that has occurred; determining a third risk index corresponding to the enterprise of which the enterprise risk early warning index is artificially judged based on enterprise information of the registered enterprise in the target area and the artificially judged enterprise risk early warning index; determining a fourth risk index corresponding to the enterprise of which the enterprise risk early warning index is judged by the system based on enterprise information of the registered enterprise in the target area and the enterprise risk early warning index judged by the system; sending the first risk index, the second risk index, the third risk index, and the fourth risk index to a second processor;
and the second processor determines a comprehensive risk index of illegal funding of the target area based on the first risk index, the second risk index, the third risk index and the fourth risk index.
The equipment for evaluating the risk of illegal regional fundraising provided by the embodiment of the disclosure has the following advantages:
after acquiring enterprise information of an enterprise registered in a target area, an enterprise risk early warning index judged by a system, an enterprise risk early warning index judged by a manual and information of an illegal collective resource case, determining a first risk index corresponding to the enterprise in which the illegal collective resource case has occurred in the target area, a second risk index corresponding to other main bodies except the enterprise in which the illegal collective resource case has occurred, a third risk index corresponding to the enterprise in which the enterprise risk early warning index is judged by the manual and a fourth risk index corresponding to the enterprise in which the enterprise risk early warning index is judged by the system according to the information, and determining a comprehensive risk index according to the risk indexes, the illegal collective resource risk in the area can be quantitatively evaluated automatically through the equipment, participation of personnel in the illegal collective resource risk evaluation is reduced, accuracy of the illegal collective resource risk evaluation is improved, and efficiency of the illegal collective resource risk evaluation is improved.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and components are not necessarily drawn to scale.
Fig. 1 is a schematic structural diagram of a device for assessing risk of illegal funding in a region according to an embodiment of the present disclosure;
fig. 2 is a schematic processing flow diagram of an illegal fundamentation risk assessment device in a region according to an embodiment of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be understood that the various steps recited in method embodiments of the present disclosure may be performed in a different order, and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
The term "include" and variations thereof as used herein are open-ended, i.e., "including but not limited to". The term "based on" is "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
Under the normal condition, when the national financial supervision department and the local financial supervision department evaluate the risk of illegal collected resources in the jurisdiction, related professionals mainly count the amount of illegal collected resources, the amount of cases and other information which have occurred in the jurisdiction according to the past work experience so as to realize the evaluation of the risk of illegal collected resources in the jurisdiction. However, this method relies on manual statistics and processing according to human labor, which results in inaccurate evaluation results and low evaluation efficiency.
In order to solve the above problem, an embodiment of the present disclosure provides a device for assessing risk of illegal fundraising in a region.
In the embodiment of the present disclosure, the regional illegal funding risk assessment device may be an electronic device or a server. The electronic devices include, but are not limited to, smart phones, palm computers, tablet computers, wearable devices with display screens, desktop computers, notebook computers, all-in-one machines, smart home devices, and the like. The server can be an independent server or a cluster of a plurality of servers, and can comprise a server built in the local and a server built in the cloud.
As shown in fig. 1, the regional illegal fundraising risk assessment device includes a communication component, a first processor, and a second processor.
And the communication component sends the acquired enterprise information of the registered enterprises in the target area, the enterprise risk early warning index judged by the system, the enterprise risk early warning index judged manually and the illegal funding case information which has occurred to the first processor.
In some embodiments, the target area may be a national area, a provincial area, a city area, etc., which is not limited by the disclosed embodiments.
In some embodiments, the business information of the registered business includes, but is not limited to, information including business name, business listing type, business details, business establishment date, approval date, business start time, business end time, business address, business status, business registered capital, and the like.
The enterprise information of the registered enterprise may be obtained by interfacing with an enterprise information query platform, or may be obtained by using related data disclosed by a business database, and the like, which is not limited in the embodiment of the present disclosure.
In some embodiments, the enterprise risk early warning index determined by the system is a risk early warning index for all enterprises in the target area automatically determined by the system or randomly selected part of enterprises or part of enterprises selected according to requirements with illegal funding risks.
Optionally, the enterprise risk early warning index determined by the system may be a numerical value within a range of [0-100 ].
Optionally, the enterprise risk early warning index determined by the system may be determined by a preset illegal funding risk rule or by an illegal funding risk machine early warning model.
The method comprises the following steps of determining an enterprise risk early warning index through a preset illegal funding risk rule, wherein the step of determining the enterprise risk early warning index through the preset illegal funding risk rule is as follows: for any enterprise, enterprise information is collected from multiple dimensions such as enterprise public opinion risks, judicial risks, management risks, associated risks and complaint reporting risks, and risk values corresponding to all the dimensions are determined according to the collected information.
Further, a preset weight rule corresponding to each dimension is obtained. And calculating the enterprise risk early warning index according to the risk value corresponding to each dimension and the weight corresponding to each dimension.
The enterprise risk early warning index is calculated by the risk value corresponding to each dimension and the weight corresponding to each dimension, and the enterprise risk early warning index can be calculated by multiplying the risk value corresponding to each dimension and the weight corresponding to each dimension, summing the multiplied values, and calculating.
Or multiplying the risk value corresponding to each dimension by the weight corresponding to each dimension, summing the multiplied numerical values, averaging, and calculating to obtain the enterprise risk early warning index.
Or by other calculation methods, which is not limited in the embodiments of the present disclosure.
The method for determining the enterprise risk early warning index through the illegal funding risk machine early warning model specifically comprises the following steps: according to any enterprise, enterprise information is collected from multiple dimensions of enterprise public opinion risks, judicial risks, management risks, associated risks, complaint reporting risks and the like, the collected enterprise information is input to a trained illegal collective risk machine early warning model, and the model directly outputs an enterprise risk early warning index according to the input enterprise information.
In some embodiments, the artificially determined enterprise risk early warning index may be determined by determining, by the relevant business experts, that there is an illegal funding risk based on the systematically determined enterprise risk early warning index, and modifying the systematically determined enterprise risk early warning index. Optionally, the manually determined enterprise risk early warning index is data with a value range of [0-100 ].
Specifically, after the risk early warning indexes of the enterprises are judged by the system, relevant business experts further randomly select part of the enterprises or select part of the enterprises as required, judge whether the enterprises judged by the system have illegal resource collection risks, and further determine whether the enterprise risk early warning indexes judged by the system are correct after determining that the enterprises really have the illegal resource collection risks. If the enterprise risk early warning indexes are correct, relevant business experts do not process the enterprise risk early warning indexes, and the enterprise risk early warning indexes are also enterprise risk early warning indexes judged by the system. If not, the related business experts can correct the enterprise risk early warning index judged by the system. And after the enterprise risk early warning index of the enterprise is corrected by the related business experts, taking the corrected risk early warning index as the manually judged enterprise risk early warning index.
It should be noted that, in some embodiments, when the related business experts determine that the enterprise determined by the system does not have a risk, it is determined that the enterprise has no enterprise risk early warning index determined by the system and an enterprise risk early warning index determined manually.
In some embodiments, the illegal fundamentation information that has occurred is information of an illegal fundamentation that has occurred. The illegal collecting case information which has occurred includes but is not limited to case name, case place, case criminal name, case setting organization, case setting time, case relating subject, case relating amount, number of persons participating in collecting case, whether or not case is across provinces, and the like.
The information of the illegal collecting and funding case can be obtained by connecting with a national supervision department and a local supervision department and by the information of the illegal collecting and funding case collected by the national supervision department and the local supervision department.
And after the communication component acquires the enterprise information of the registered enterprise, the enterprise risk early warning index judged by the system, the enterprise risk early warning index judged by the manual work and the information of the illegal collective resource case, the contents are sent to the first processor.
After receiving the information, the first processor determines a first risk index, a second risk index, a third risk index and a fourth risk index based on the information.
It should be noted that, before determining the first risk index, the second risk index, the third risk index, and the fourth risk index, the first processor needs to preset the weight of the enterprise information of the registered enterprise and part of information included in the information of the occurred illegal funding case.
Specifically, the weight of part of information included in the enterprise information of the registered enterprise is set as follows:
the business registered capital is divided into different levels. Illustratively, the business registered capital can be divided into 5 levels, respectively (0-100 ten thousand ], (100-200 ten thousand ], (200-500 ten thousand ], (500-1000 ten thousand), and more than 1000 ten thousand, and different levels are set corresponding to different weights.
The establishment years of the enterprise are divided into different levels. Illustratively, the establishment years may be classified into 5 levels, which are (0-1 year ], (1 year-5 years ], (5 years-10 years ], (10 years-15 years), and more than 15 years, and different establishment years are set with different weights.
And setting the corresponding weight of each listed enterprise and each unlawful enterprise.
Marking the type of the head office or the branch office for the registered enterprise, and setting the respective corresponding weights of the head office and the branch office. Wherein the marking of the head office or branch office type for the registered enterprise of the target area may be determined based on a preset rule. For example, the preset rule is based on whether the business name contains the word "division". If the name of the enterprise contains the word 'division', the enterprise is marked as a division, otherwise, the enterprise is marked as a head office.
The weight of the partial information included in the information of the illegal fundamentation case that has occurred is set as follows:
the involved money is divided into different levels, illustratively, the involved money is divided into 3 levels, namely three levels of (0-5000 ten thousand yuan), (5000 ten thousand yuan-1 hundred million yuan) and more than 1 hundred million yuan, and different levels are set to correspond to different weights.
The number of people who participate in case collecting resources is divided into different levels, illustratively, the number of people who participate in case collecting resources is divided into 4 levels which are respectively (0-1000 people ], (1000-5000 people ], (5000-10000 people) and 100 ten thousand people, and the number of people who participate in case collecting resources with different levels is set to be correspondingly different weights.
And setting the occurred cases as the weights corresponding to the trans-provincial cases and the non-trans-provincial cases respectively.
Further, after receiving the enterprise information of the registered enterprise in the target area, the enterprise risk early warning index determined by the system, the enterprise risk early warning index determined by the manual determination, and the illegal collective-funding case information sent by the communication component, the first processor needs to process the enterprise information of the registered enterprise and the illegal collective-funding case information.
Specifically, the enterprise information of the registered enterprise is processed as follows:
in order to determine which businesses are in the same target area, it is necessary to extract province, city, district/county information in the business address included in the business information of the registered business.
The illegal fundamentation case information that has occurred is processed as follows:
when the case involved body included in the information of the illegal collective file is not marked, namely the case involved body is empty, the case involved body is supplemented. The concrete supplementary mode can be that the enterprise name is extracted from the case name included in the illegal investment case information which has occurred, and the extracted enterprise name is used as the case-related main body of the illegal investment case which has occurred.
After the weight setting of the partial information, the enterprise information of the registered enterprise and the occurred illegal funding case information are processed, a first risk index, a second risk index, a third risk index and a fourth risk index can be determined, and the first risk index, the second risk index, the third risk index and the fourth risk index are determined respectively.
A. A first risk index is determined.
In an embodiment of the present disclosure, determining the first risk index specifically includes:
and determining a first risk index corresponding to the enterprise in which the illegal funding case has occurred in the target area according to the enterprise information of the registered enterprise in the target area and the information of the illegal funding case.
Specifically, the first processor firstly matches the enterprise name included in the enterprise information of the registered enterprise in the target area with the case-involved main body included in the occurred illegal collective file information; if the enterprise name is successfully matched with the case-involved main body, determining the case-involved main body as the enterprise in which the illegal funding case occurs; if the enterprise name is not matched with the case-involved main body successfully, the case-involved main body is determined to be the other main bodies except the enterprise, in which the illegal funding case occurs.
The matching success may be determined by determining whether the enterprise name is identical to the subject involved in the case, or by determining whether the similarity between the enterprise name and the subject involved in the case is greater than a preset threshold, or by other methods, which is not limited in the embodiment of the present disclosure.
The other subjects except for the enterprise may refer to individuals or subjects who cannot determine the subject involved in the case due to inaccurate reporting. For example, the case-involved body included in the information of the illegal collective asset is Zhang III, and Zhang III is an individual, so the case-involved body is the other body except the enterprise. For another example, the illegal investment case information that has occurred includes an investment body 2022.06.13 illegal investment case in Nanjing city, jiangsu province, which may not be determined due to inaccurate filling, and thus is a subject other than an enterprise.
It should be noted that, after the enterprise name is successfully matched with the case-involved subject, the enterprise information of the registered enterprise and the illegal collective file information that has occurred need to be associated according to the enterprise name and the case-involved subject, so that the enterprise information of the registered enterprise and the illegal collective file information that has occurred can be associated.
Secondly, the first processor determines a first risk index corresponding to the enterprise in which the illegal collecting file occurs based on the enterprise information of the registered enterprise in the target area and the illegal collecting file information of the enterprise in which the illegal collecting file occurs.
Specifically, the first processor determines the case-involved amount, the number of participating funding persons, whether the target area is a trans-provincial case, enterprise registered capital information included in enterprise information of registered enterprises, enterprise listing category information, enterprise establishment date information, and enterprise general affiliate category information of the enterprise in which the illegal funding case has occurred, based on case-involved amount information, the number of participating funding persons, whether the target area is a trans-provincial case, enterprise registered capital, enterprise listing category, enterprise establishment period, and first weights corresponding to the enterprise general affiliate category; determining the first risk index based on the first weight.
Specifically, the first processor determines the grade of the involved amount of each enterprise having illegal collecting case according to the involved amount included in the illegal collecting case information of the enterprise having illegal collecting case information and the grade of the preset involved amount, and further determines the weight corresponding to the grade of the involved amount of each enterprise having illegal collecting case information.
And determining the number grade of the case participation and fundation persons of each enterprise having illegal fundation cases according to the number of the case participation and fundation persons included in the illegal fundation case information and the preset grade of the number of the case participation and fundation persons, and further determining the weight corresponding to the grade of the case participation and fundation persons of each enterprise having illegal fundation cases.
And determining the weight of each trans-provincial case or non-trans-provincial case of the enterprise in which the illegal collecting cases occur according to whether the illegal collecting case information comprises the trans-provincial case and the preset weights corresponding to the trans-provincial case and the non-trans-provincial case.
And determining the enterprise registered capital grade of each enterprise which has undergone illegal funding according to the enterprise registered capital included in the enterprise information of the registered enterprise and the preset enterprise registered capital grade, and further determining the weight corresponding to the enterprise registered capital grade of each enterprise which has undergone illegal funding.
And determining the listed or unlined weight of each enterprise in which the illegal funding case occurs according to the enterprise listed type included in the enterprise information of the registered enterprise and the preset respective corresponding weights of the listed enterprise and unlined enterprise.
And calculating the establishment period of each enterprise in which the illegal funding case occurs according to the difference value between the establishment date and the current time of the enterprise included in the enterprise information of the registered enterprise. And determining the grade of the establishment age of each enterprise which has generated illegal funding according to different grades of the preset establishment ages, and further determining the weight corresponding to the grade of each enterprise which has generated illegal funding.
And determining the total company or branch company weight of each enterprise in which the illegal funding case occurs according to the total branch company type of the enterprise included in the enterprise information of the registered enterprise and the preset weight corresponding to the total company and the branch company.
The determined weight is used as a first weight.
After determining the first weight corresponding to each of the information, the first processor determines a first risk index based on the first weight. The method specifically comprises the following steps:
wherein, score 1 Is the first risk index, n is the number of enterprises in the target area that have undergone illegal funding, 100 is the initial risk index for each enterprise that has undergone illegal funding, w1 i For the ith enterprise referred-amount level weight, w2, where illegal funding has occurred i The number of persons participating in collecting capital for the ith enterprise who has illegal collecting capital case, w3 i Registering capital weights for the i-th enterprise that has committed an illegal funding case, w4 i Enterprise listing class weight for the ith enterprise that has committed the illegal funding case, w5 i Enterprise establishment age weight for the ith enterprise that has committed the illegal funding case, w6 i Weight of the i-th enterprise that has been illegally funded, w7 i And (4) the enterprise total branch category weight of the ith enterprise in which the illegal funding case occurs.
B. A second risk index is determined.
In an embodiment of the present disclosure, determining the second risk index specifically includes:
and the first processor determines a second risk index corresponding to other main bodies except the enterprises of which the target area has illegal funding cases based on the enterprise information of the registered enterprises of the target area and the information of the illegal funding cases.
Specifically, the first processor determines a second risk index corresponding to the other main bodies except the enterprise, in which the illegal funding case has occurred, based on the enterprise information of the registered enterprise in the target area and the illegal funding case information of the other main bodies except the enterprise, in which the illegal funding case has occurred.
Wherein the other subjects than enterprises that determined that an illegal funding case has occurred may be the other subjects than enterprises that determined the illegal funding case has occurred in the above-described determination of first risk index.
The first processor determines the case-involved amount and the second weight corresponding to the number of persons participating in the collection of illegal collection files except for enterprises on the basis of the case-involved amount information and the number of persons participating in the collection information included in the illegal collection file information of the other subjects except for enterprises where the illegal collection files have occurred in the target area; based on the second weight, a second risk index is determined.
Specifically, the first processor determines the grade of the involved amount of the other main bodies except the enterprise of each illegal collective file according to the involved amount included in the illegal collective file information of the other main bodies except the enterprise in which the illegal collective file occurs and the grade of the preset involved amount, and further determines the weight corresponding to the grade of the involved amount of the other main bodies except the enterprise in which the illegal collective file occurs.
And determining the level of the number of persons participating in the collection of the illegal collection of the files except the enterprise according to the number of persons participating in the collection of the illegal collection of the files and the preset level of the number of persons participating in the collection of the files, and further determining the weight corresponding to the level of the number of persons participating in the collection of the other bodies except the enterprise of the files where the illegal collection of the files occurs.
And taking the determined weight as a second weight.
After determining the second weight corresponding to each of the information, the first processor determines a second risk index based on the second weight, which may specifically be:
wherein, score 2 For the second risk index, k is the number of other subjects than the enterprise within the target area that have had illegal funding cases, 100 is the initial risk index, w1, for each subject other than the enterprise that has committed an illegal funding case j The case-related amount of money class weight of the jth subject other than the enterprise who has committed the illegal funding case, w2 j The number of persons participating in the funding for the subject except the enterprise who has the illegal funding case j is weighted by 0.8 which is a constant.
C. A third risk index is determined.
In an embodiment of the present disclosure, determining the third risk index specifically includes:
and determining a third risk index corresponding to the enterprise of which the enterprise risk early warning index is artificially judged based on the enterprise information of the registered enterprise in the target area and the artificially judged enterprise risk early warning index.
Specifically, first, the first processor determines an enterprise for which the enterprise risk early warning index is manually determined, based on enterprise information of registered enterprises in the target area and the manually determined enterprise risk early warning index.
Specifically, the first processor searches for an enterprise corresponding to the manually determined enterprise risk index in enterprise information of registered enterprises, and uses the searched enterprise as the enterprise of which the enterprise risk early warning index is manually determined.
Secondly, determining the enterprise registered capital, the enterprise listing category, the enterprise establishment period and the third weight corresponding to the enterprise general branch category of the enterprise of which the enterprise risk early warning index is artificially judged based on the enterprise registered capital information, the enterprise listing category information, the enterprise establishment date information and the enterprise general branch category information which are included in the enterprise information of the enterprise of which the enterprise risk early warning index is artificially judged; and determining the third risk index based on the enterprise risk early warning index of the enterprise of which the enterprise risk early warning index is artificially determined and the third weight.
Specifically, the first processor determines the enterprise registered capital level of the enterprise risk early warning index determined manually according to the enterprise registered capital included in the enterprise information of the enterprise of which the enterprise risk early warning index is determined by the system and the preset enterprise registered capital level, and further determines the weight corresponding to the level of the enterprise of which the enterprise risk early warning index is determined manually.
And determining the listed or unlawful weight of the enterprise of which the enterprise risk early warning index is artificially judged according to the enterprise listed type included in the enterprise information of the registered enterprise and the preset respective corresponding weights of the listed enterprise and the unlawful enterprise.
And calculating the establishment period of each enterprise in which the illegal funding case occurs according to the difference value between the establishment date and the current time of the enterprise included in the enterprise information of the registered enterprise. And determining the grade of the establishment age of the enterprise of which the enterprise risk early warning index is manually judged according to different grades of the preset establishment age, and further determining the weight corresponding to the grade of the establishment age of the enterprise of which the enterprise risk early warning index is manually judged.
And determining the total company or branch company weight of the enterprise of which the enterprise risk early warning index is manually judged according to the enterprise total branch company type included in the enterprise information of the registered enterprise and the preset weight corresponding to the total company and the branch company.
The determined weight is used as a third weight.
After determining the third weight corresponding to each of the above information, the first processor may determine, based on the enterprise risk early warning index of the enterprise and the third weight determined manually, the third weight, specifically:
wherein, score 3 For the third risk index, m is the number of enterprises for which the target area has been artificially determined to be the enterprise risk pre-warning index, scorematual q W3 for the qth enterprise risk early warning index of the enterprise for which the enterprise risk early warning index was manually determined q Registering capital weights for the qth enterprise by manually determining the enterprise Risk Warning index, w4 q The risk early warning index of the enterprise is judged for the qth by manpowerBusiness listing category weight of the business, w5 q W7 Enterprise formation age weight for the qth Enterprise with artificially determined Enterprise Risk Warning index q And the category weight of the enterprise total branch company of the qth enterprise of which the enterprise risk early warning index is manually determined.
D. A fourth risk index is determined.
In an embodiment of the present disclosure, determining the fourth risk index specifically includes:
and the second processor determines a comprehensive risk index of illegal funding of the target area based on the first risk index, the second risk index, the third risk index and the fourth risk index.
Specifically, first, the first processor determines an enterprise of which the enterprise risk early warning index is determined by the system based on enterprise information of registered enterprises in the target area and the enterprise risk early warning index determined by the system.
Specifically, the first processor searches the enterprise corresponding to the enterprise risk index judged by the system in the enterprise information of the registered enterprise, and uses the searched enterprise as the enterprise of which the enterprise risk early warning index is judged by the system.
Secondly, determining the enterprise registered capital, the enterprise listing category, the enterprise establishment period and the fourth weight corresponding to the enterprise general branch category of the enterprise of which the enterprise risk early warning index is judged by the system based on the enterprise registered capital information, the enterprise listing category information, the enterprise establishment date information and the enterprise general branch category information which are included in the enterprise information of the enterprise of which the enterprise risk early warning index is judged by the system; and determining the fourth risk index based on the enterprise risk early warning index of the enterprise of which the enterprise risk early warning index is determined by the system and the fourth weight.
Specifically, the first processor determines the enterprise registered capital level of the enterprise risk early warning index determined by the system according to the enterprise registered capital included in the enterprise information of the enterprise of which the enterprise risk early warning index is determined by the system and the preset enterprise registered capital level, and further determines the weight corresponding to the level of the enterprise of which the enterprise risk early warning index is determined by the system.
And determining the listed or unlawful weight of the enterprise of which the enterprise risk early warning index is judged by the system according to the enterprise listed type included in the enterprise information of the registered enterprise and the preset respective corresponding weights of the listed enterprise and the unlawful enterprise.
And calculating the establishment period of each enterprise in which the illegal funding case occurs according to the difference value between the establishment date and the current time of the enterprise included in the enterprise information of the registered enterprise. And determining the grade of the establishment age of the enterprise of which the enterprise risk early warning index is judged by the system according to the different grades of the preset establishment ages, and further determining the weight corresponding to the grade of the establishment age of the enterprise of which the enterprise risk early warning index is judged by the system.
And determining the total company or branch company weight of the enterprise of which the risk early warning index of the enterprise is judged by the system according to the total branch company category of the enterprise included in the enterprise information of the registered enterprise and the preset corresponding weights of the total company and the branch company.
The weight determined above is taken as a fourth weight.
Determining the fourth risk index based on the enterprise risk early warning index and the fourth weight of the enterprise of which the enterprise risk early warning index is determined by the system, wherein the fourth risk index may be specifically:
wherein, score 4 Scoremachine as fourth Risk index g Enterprise risk early warning index for the enterprise for which the system determines the enterprise risk early warning index, m is the number of enterprises for which the system determines the enterprise risk early warning index, w3 g Registering capital weight, w4, for the g-th enterprise for which the system determines the enterprise Risk Warning index g For the g enterprise listing category weight of the enterprise for which the system determines the enterprise risk early warning index, w5 g For the enterprise age weight of the enterprise for which the system determines the enterprise risk pre-warning index,w7 g and g, the enterprise total branch category weight of the enterprise of which the enterprise risk early warning index is determined by the system.
It should be noted that, in some scenarios, when an enterprise belongs to two types or three types among an enterprise in which an illegal funding case has occurred, an enterprise in which an enterprise risk early warning index has been manually determined, and an enterprise in which an enterprise risk early warning index has been determined by a system, the unique type to which the enterprise belongs is determined according to the preset priority of the enterprise in which an illegal funding case has occurred > the enterprise in which an enterprise risk early warning index has been manually determined > the enterprise in which an enterprise risk early warning index has been determined by the system.
Meanwhile, it should be noted that the disclosed embodiments do not limit the order of determining the first risk index, the second risk index, the third risk index, and the fourth risk index.
In some embodiments, before determining a first risk index corresponding to an enterprise in which an illegal funding case has occurred in the target region and a second risk index corresponding to a subject other than the enterprise in which the illegal funding case has occurred, based on enterprise information of the registered enterprise in the target region and information of the illegal funding case that has occurred, the first processor may determine a case setting time included in the information that the illegal funding case has occurred in the target region, and screen the information that the illegal funding case has occurred in a case setting time greater than a preset time.
Because the illegal fundamentals occurring at the latest time are more referential, the first wind index and the second risk index are more accurate to determine according to the case information of the illegal fundamentals occurring at the latest time. Illustratively, the information of the illegal funding case that has occurred with a filing time greater than 1 month and 1 day of 2021 may be screened.
In some embodiments, the first processor may determine business status information included in the business information of the registered business; and screening the enterprise information of the enterprise in the normal operation state from the registered enterprise information of the enterprise.
In general, an enterprise has different operation states, for example, the enterprise has a normal operation state, an abnormal operation state, an immigration state, and an immigration state. Wherein, the normal operation state comprises the states of existence, operation and presence; the abnormal operation state comprises a logout state, a suspension sale state, a shutdown state and a withdrawal state. Because the third risk index and the fourth risk index are determined more accurately according to the enterprises in the normal operating state and the enterprises in the immigration state, in the embodiment of the disclosure, before the third risk index and the fourth risk index are determined, the enterprise information corresponding to the enterprises in the normal operating state and the enterprises in the immigration state respectively can be screened from the enterprise information of the registered enterprises.
After the first processor determines the first risk index, the second risk index, the third risk index and the fourth risk index, the first risk index, the second risk index, the third risk index and the fourth risk index are sent to the second processor.
And the second processor determines a comprehensive risk index of illegal funding of the target area according to the received first risk index, the second risk index, the third risk index and the fourth risk index.
Specifically, the second processor multiplies each risk index by a preset weight corresponding to each risk index to obtain a target risk index corresponding to each risk index; and summing the target risk indexes corresponding to each risk index to obtain the comprehensive risk index of illegal funding of the target area.
The specific calculation formula may be:
wherein Score is the comprehensive risk index, score h For any of the first risk index, the second risk index, the third risk index, and the fourth risk index, w, calculated above h And the weight corresponding to any risk index.
In some embodiments, the regional illegal funding risk assessment device further comprises a third processor.
Specifically, after the second processor determines the comprehensive risk index of illegal fundation of the target area, the comprehensive risk index of illegal fundation of the target area is sent to the third processor.
Furthermore, the third processor can determine the risk level of illegal funding in the target area according to the preset corresponding relation between the comprehensive risk index and the risk level of illegal funding in the target area after receiving the comprehensive risk index.
Specifically, in the embodiment of the present disclosure, a corresponding relationship between the comprehensive risk index and a risk level of occurrence of an illegal funding risk is preset, and then a risk level corresponding to the comprehensive risk index of the target area is determined.
Optionally, in order to accurately and comprehensively evaluate the severity of the current illegal funding risk in a region and facilitate the risk classification, the comprehensive risk indexes of multiple regions may be used as Normalization reference samples, for example, the comprehensive risk indexes of 31 provinces (municipalities and municipalities) and Xinjiang production and construction groups in China or the comprehensive risk indexes of some provinces (municipalities and municipalities) are used as Normalization reference samples, and the comprehensive risk indexes of multiple regions are normalized by using a dispersion Normalization (Min-Max Normalization), a zero-mean Normalization (Z-score Normalization), or a Power Normalization (Power Normalization) method, so as to normalize the comprehensive risk index interval to [0, 100].
The basic principle of normalization processing of the comprehensive risk index by using the dispersion normalization method is to perform linear transformation on the comprehensive risk index, map a result value between [0 and 1], and then multiply the result value by 100 so as to normalize a comprehensive risk index interval between [0 and 100], wherein the specific calculation method is as follows:
wherein x is new Is a normalized comprehensive risk index, x is a comprehensive risk index of an area to be normalized, max is the maximum value of the comprehensive illegal funding risk indexes of a plurality of areas, and min is an illegal funding risk summary of the plurality of areasMinimum of the sum index.
The principle of zero-mean normalization is the normalization of the composite risk index by the mean and standard deviation of the composite risk index. The processed comprehensive risk index conforms to the standard normal distribution, that is, the average value is 0, the standard deviation is 1, and then the average value is multiplied by 100, so that the comprehensive risk index interval is normalized to be between [0 and 100], and the specific calculation method is as follows:
wherein x is new The risk index is a normalized comprehensive risk index, x is a comprehensive risk index of an area to be normalized, mu is a mean value of illegal funding risk comprehensive indexes of a plurality of areas, and sigma is a standard deviation of the illegal funding risk comprehensive indexes of the plurality of areas.
The principle of the power normalization method is to normalize the composite risk index by using power operation to obtain a value of [0-1], and then multiply the value by 100 to normalize the composite risk index interval to be between [0 and 100], and the specific calculation method is as follows:
x new ＝x α *100
wherein x is new Is the integrated risk index after normalization, x is the integrated risk index of the region to be normalized, and alpha is a power value and is [0-1]]A value in between.
It should be noted that, in other embodiments, other normalization processing methods may also be adopted, and this is not limited in this disclosure.
After the comprehensive risk index is normalized, a corresponding relationship between the normalized comprehensive risk index and the risk level may be set, and the set corresponding relationship is as follows:
setting the comprehensive risk index as 0, setting the corresponding risk grade as no risk grade, setting the comprehensive risk index in the interval of [ 1-60), setting the corresponding risk index as low risk, setting the comprehensive risk index in the interval of [ 60-85), setting the corresponding risk index as medium risk, and setting the comprehensive risk index in the interval of [85-100], setting the corresponding risk index as high risk.
Furthermore, in this disclosure, the third processor may determine the risk level of illegal funding of the target area according to the comprehensive risk index of the target area and the correspondence between the normalized comprehensive risk index and the risk level.
By determining the risk level of illegal funding of the target area, the severity of the risk of the target area can be visually seen, and further, different disposal strategies can be adopted by related departments for different risk levels.
The area illegal fundamentation risk assessment device provided by the embodiment of the present disclosure is described again with reference to the processing flow diagram of the area illegal fundamentation risk assessment device shown in fig. 2.
As shown in fig. 2, the communication component obtains enterprise information of registered enterprises in the target area, enterprise risk early warning indexes judged by the system, enterprise risk early warning indexes judged by the human, and illegal funding case information that has occurred, and sends the information to the first processor.
The above described acquisition mode can be adopted for acquiring the enterprise information of the registered enterprise in the target area, the enterprise risk early warning index judged by the system, the enterprise risk early warning index judged by the manual method, and the illegal funding case information which has occurred, and details are not repeated herein.
Further, the first processor processes the enterprise information of the registered enterprise and the information of the illegal collective file which occurs.
The above-described technical solution can be referred to for processing the enterprise information of the registered enterprise and the information of the illegal fundamentation case, and details are not described herein.
Further, the first processor determines a first risk index, a second risk index, a third risk index, and a fourth risk index, and sends the first risk index, the second risk index, the third risk index, and the fourth risk index to the second processing device.
The first risk index, the second risk index, the third risk index, and the fourth risk index may be determined by referring to the scheme for determining the first risk index, the second risk index, the third risk index, and the fourth risk index described above, which is not described herein again.
Further, the second processor determines a composite risk index according to the first risk index, the second risk index, the third risk index and the fourth risk index, and sends the composite risk index to the third processor.
The determination of the comprehensive risk index according to the first risk index, the second risk index, the third risk index and the fourth risk index may be determined by referring to the above-described technical scheme for determining the comprehensive risk index, and details are not repeated here.
Further, the third processor determines the risk level of illegal funding of the target area according to the corresponding relation between the comprehensive risk index and the risk level of the target area.
The above-described method may be referred to in the scheme of determining the risk level of illegal funding of the target region according to the corresponding relationship between the comprehensive risk index and the risk level of the target region, and details are not repeated here.
Therefore, after acquiring the enterprise information of the registered enterprise in the target area, the enterprise risk early warning index judged by the system, the enterprise risk early warning index judged by the manual and the information of the generated illegal collective resource case, the regional illegal collective resource risk assessment device provided by the embodiment of the disclosure determines the first risk index corresponding to the enterprise in which the illegal collective resource case has occurred in the target area, the second risk index corresponding to the other main bodies except the enterprise in which the illegal collective resource case has occurred, the third risk index corresponding to the enterprise in which the enterprise risk early warning index is judged by the manual and the fourth risk index corresponding to the enterprise in which the enterprise risk early warning index is judged by the system according to the information, and determines the comprehensive risk index according to the risk indexes, so that the regional illegal collective resource risk can be quantitatively assessed automatically through the device, the participation of personnel in the illegal collective resource risk assessment is reduced, the accuracy of the illegal collective resource risk assessment is improved, and the efficiency of the illegal collective resource risk assessment is also improved.
Claims (10)
1. A regional illegal fundraising risk assessment device, comprising: a communication component, a first processor and a second processor;
the communication component sends the acquired enterprise information of the registered enterprises in the target area, the enterprise risk early warning index judged by the system, the enterprise risk early warning index judged by people and the information of the illegal funding case which has occurred to the first processor;
the first processor determines a first risk index corresponding to an enterprise in which the illegal funding case has occurred in the target area and a second risk index corresponding to a main body except the enterprise in which the illegal funding case has occurred in the target area based on enterprise information of the registered enterprise in the target area and the information of the illegal funding case having occurred; determining a third risk index corresponding to the enterprise of which the enterprise risk early warning index is artificially judged based on the enterprise information of the registered enterprise in the target area and the artificially judged enterprise risk early warning index; determining a fourth risk index corresponding to the enterprise of which the enterprise risk early warning index is judged by the system based on the enterprise information of the registered enterprise in the target area and the enterprise risk early warning index judged by the system; sending the first risk index, the second risk index, the third risk index, and the fourth risk index to the second processor;
and the second processor determines a comprehensive risk index of illegal funding of the target area based on the first risk index, the second risk index, the third risk index and the fourth risk index.
2. The apparatus of claim 1, wherein the first processor determines, based on the enterprise information of the registered enterprises in the target area and the information of the illegal funding cases that have occurred, a first risk index corresponding to an enterprise in which an illegal funding case has occurred in the target area and a second risk index corresponding to a subject other than the enterprise in which an illegal funding case has occurred, and comprises:
matching the enterprise name included in the enterprise information of the registered enterprise in the target area with the case-involved main body included in the occurred illegal collective file information;
if the enterprise name is successfully matched with the case-involved main body, determining that the case-involved main body is an enterprise in which an illegal case collecting occurs;
if the enterprise name is unsuccessfully matched with the case-involved main body, determining the case-involved main body as other main bodies except the enterprise, wherein the other main bodies have illegal funding cases;
determining a first risk index corresponding to the enterprise in which the illegal funding case has occurred based on the enterprise information of the registered enterprise in the target area and the illegal funding case information of the enterprise in which the illegal funding case has occurred;
and determining a second risk index corresponding to the other main bodies except the enterprise, in which the illegal fundamentation case has occurred, based on the enterprise information of the registered enterprise in the target area and the illegal fundamentation case information of the other main bodies except the enterprise, in which the illegal fundamentation case has occurred.
3. The apparatus of claim 2, wherein the first processor determines the first risk index corresponding to the enterprise having the illegal funding case based on enterprise information of the registered enterprises in the target area and illegal funding case information of the enterprise having the illegal funding case, and comprises:
the first processor determines case-related amount, number of participating funding persons, cross-provincial case information, enterprise registered capital information, enterprise listing category information, enterprise establishment date information and enterprise general branch category information of the enterprise in which the illegal funding cases have occurred based on case-related amount information, number of participating funding persons, whether the enterprise is a cross-provincial case, enterprise registered capital, enterprise listing category, enterprise establishment period and first weight corresponding to each of the enterprise general branch categories of the enterprise in which the illegal funding cases have occurred;
determining the first risk index based on the first weight.
4. The apparatus of claim 2, wherein the first processor determines the second risk index corresponding to the subject other than the enterprise for which the illegal funding has occurred based on enterprise information of the registered enterprises in the target area and illegal funding case information of the subject other than the enterprise for which the illegal funding has occurred, and comprises:
the first processor determines the case involved amount and the second weight corresponding to the number of persons participating in the collection of illegal collection files except for enterprises based on the case involved amount information and the number of persons participating in the collection information included in the illegal collection file information of the other subjects except for enterprises where the illegal collection files have occurred in the target area;
determining the second risk index based on the second weight.
5. The apparatus of claim 1, wherein the first processor determines a third risk index corresponding to the enterprise for which the enterprise risk early warning index is manually determined based on enterprise information of the registered enterprises in the target area and the manually determined enterprise risk early warning index, and comprises:
the first processor determines enterprises of which the enterprise risk early warning indexes are manually judged based on enterprise information of the registered enterprises in the target area and the manually judged enterprise risk early warning indexes;
determining a third weight corresponding to the enterprise registered capital, the enterprise listing category, the enterprise establishment deadline and the enterprise general branch category of the enterprise of which the enterprise risk early warning index is artificially determined based on enterprise registered capital information, enterprise listing category information, enterprise establishment date information and enterprise general branch category information included in the enterprise information of the enterprise of which the enterprise risk early warning index is artificially determined;
and determining the third risk index based on the enterprise risk early warning index of the enterprise of which the enterprise risk early warning index is artificially determined and the third weight.
6. The apparatus of claim 1, wherein the first processor determines a fourth risk index corresponding to a business for which an enterprise risk early warning index is determined by the system based on business information of businesses registered in the target area and the enterprise risk early warning index determined by the system, and comprises:
the first processor determines the enterprise of which the enterprise risk early warning index is judged by the system based on the enterprise information of the registered enterprise in the target area and the enterprise risk early warning index judged by the system;
determining fourth weights corresponding to the enterprise registered capital, the enterprise listing category, the enterprise establishment deadline and the enterprise general branch category of the enterprise of which the enterprise risk early warning index is judged by the system based on enterprise registered capital information, enterprise listing category information, enterprise establishment date information and enterprise general branch category information included in the enterprise information of the enterprise of which the enterprise risk early warning index is judged by the system;
and determining the fourth risk index based on the enterprise risk early warning index of the enterprise of which the enterprise risk early warning index is determined by the system and the fourth weight.
7. The apparatus of claim 1, wherein the second processor determines a composite risk index for illegal funding of the target area based on the first risk index, the second risk index, the third risk index, and the fourth risk index, comprising:
the second processor multiplies each risk index by a preset weight corresponding to each risk index to obtain a target risk index corresponding to each risk index;
and summing the target risk indexes corresponding to each risk index to obtain a comprehensive risk index of illegal funding of the target area.
8. The apparatus of claim 1, further comprising a third processor;
and the third processor determines the risk level of illegal collection of the target area based on the preset corresponding relation between the comprehensive risk index and the risk level of illegal collection of the resources.
9. The apparatus of claim 1, wherein the first processor determines, based on the enterprise information of the registered enterprises in the target area and the information of the illegal funding cases that have occurred, that a first risk index corresponding to an enterprise in which an illegal funding case has occurred in the target area and a second risk index corresponding to a subject other than the enterprise in which an illegal funding case has occurred,
the first processor determines the scheme setting time included in the illegal fundamentation case information of the target area;
and screening the information of the illegal collecting case which has occurred and has the case setting time larger than the preset time.
10. The device of claim 1, wherein the first processor determines a third risk index corresponding to a business for which an enterprise risk early warning index is manually determined based on business information of the registered business in the target area and the manually determined enterprise risk early warning index; before determining a fourth risk index corresponding to the enterprise of which the enterprise risk early warning index is judged by the system based on the enterprise information of the registered enterprises in the target area and the enterprise risk early warning index judged by the system,
the first processor determines business state information included in the enterprise information of the registered enterprise;
and screening the enterprise information of the enterprises in the normal operation state and the immigration state from the enterprise information of the registered enterprises.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211080195.6A CN115439204A (en) | 2022-09-05 | 2022-09-05 | Regional illegal collective resource risk assessment equipment |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202211080195.6A CN115439204A (en) | 2022-09-05 | 2022-09-05 | Regional illegal collective resource risk assessment equipment |
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| CN115439204A true CN115439204A (en) | 2022-12-06 |
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| CN202211080195.6A Pending CN115439204A (en) | 2022-09-05 | 2022-09-05 | Regional illegal collective resource risk assessment equipment |
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