CN111523793A - Risk monitoring and early warning method and system in credit lease service - Google Patents
Risk monitoring and early warning method and system in credit lease service Download PDFInfo
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Abstract
The embodiment of the invention discloses a risk monitoring and early warning method and a system in credit lease service, wherein the method comprises the following steps: collecting internal and external data of a client associated with each deposit-free application in a credit lease service; monitoring the behavior of the client according to internal and external data of the client, and identifying fraud and operation risk of the client in the credit lease service according to the behavior of the client; and taking corresponding treatment action according to the fraud and the client operation risk. The embodiment of the invention carries out monitoring, evaluating and early warning on cheating lease and operation risk of the credit lease service, can monitor customer behavior timely, comprehensively and accurately, and identifies cheating lease and operation risk of the customer in the credit lease service.
Description
Technical Field
The invention relates to the field of credit lease, in particular to a risk monitoring and early warning method and system in a credit lease service.
Background
In recent years, the number of credit rental businesses has increased rapidly at a rate of about 30% per year, and the number of rental economy services has exceeded hundreds of millions. Credit lease means that a deposit can be exempted or even lower by credit. For high-net-value rental single products, deposit free means high risk, and if the credit threshold is too low, higher risks of bad credit, no return to the future and malicious overdue can be borne; however, if the auditing threshold is too high, the passing rate is low, and the service development is limited. Therefore, in order to guarantee larger passenger capacity and continuous increase of service scale, a plurality of credit rentals are gradually converted from the original wind control mode of admission and examination before re-renting into the wind control mode of monitoring and early warning of the behavior of the client in the re-renting.
The monitoring of the behavior in the renting refers to the management of the whole process from the moment the renting contract takes effect, the beginning of the renting behavior to the moment the renting contract is finished and the return of the rented objects, and during the renting period of the client, the behavior of the client needs to be monitored, and the early warning is carried out on the user with the risk possibility.
However, in the prior art, most of the existing management frames are standardized loan management frames designed based on traditional credit products, so that the applicability to credit rental services is poor, and the problems of few customer information channels, untimely updating, and insufficiently sensitive response mechanisms exist.
Disclosure of Invention
The present invention provides a method and system for risk monitoring and pre-warning in a credit rental business that overcomes or at least partially solves the above-mentioned problems.
According to a first aspect of the present invention, a risk monitoring and early warning method in a credit lease service is provided, which includes:
collecting internal and external data of a client associated with each deposit-free application in a credit lease service;
monitoring the behavior of the client according to internal and external data of the client, and identifying fraud and operation risk of the client in the credit lease service according to the behavior of the client;
and taking corresponding treatment action according to the fraud and the client operation risk.
On the basis of the technical scheme, the invention can be further improved as follows.
Optionally, the client internal and external data includes client internal data and client external data;
the client internal data comprises basic information data and client behavior data of the client;
the external data of the client at least comprises corporate public opinion data, industrial and commercial data, judicial finance and tax data and multi-debt data based on natural people.
Optionally, in the credit lease service, after collecting external data in the client associated with each deposit exemption application, the method further includes:
summarizing and fusing internal and external data of each client associated with the deposit-free application to form an original data set of each client;
and removing obviously wrong or repeated data according to the original data set of each client.
Optionally, the monitoring the customer behavior according to the internal and external data of the customer, and the identifying cheating lease and the customer operation risk in the credit lease service according to the customer behavior includes:
monitoring the client behavior according to internal and external data of the client;
and analyzing the customer behaviors, and determining a risk label of each customer, wherein the risk label is a fraud risk label or an operation risk label.
Optionally, after analyzing the customer behavior and determining the risk label of each customer, the method further includes:
and setting corresponding batch running frequency according to different types of risk labels of each client.
Optionally, the output result of the fraud risk tag is yes or no according to the determination criterion, and the output result of the operation risk tag and the determination criterion are severity.
Optionally, the business risk label calculates a score according to each type of business risk factor and the corresponding weight.
Optionally, the various risk factors include an industry risk factor, a regional risk factor, an operation transaction risk factor, and a public opinion risk factor;
determining an industry risk factor in the tenant operation risk factors according to the extracted industry policy, industry dynamic and capital environment;
calculating according to regional economic trends and regional industry policy change index data, and determining regional risk factors in the tenant operation risk factors;
calculating according to the extracted company moving, referee and high management change index data, and determining an operation abnormal risk factor in the lessee operation risk factors;
and calculating according to the extracted client public opinion information transaction and the major event public opinion transaction index data of the client enterprises to determine the public opinion risk factors in the lessee operation risk factors.
Optionally, the method further includes:
and calculating scores according to the various operation risk factors and the corresponding weights to determine the severity of the operation risk label, wherein the severity comprises high risk, medium risk and low risk.
According to a second aspect of the present invention, there is provided a risk monitoring and early warning system in a credit rental business, comprising:
the collecting module is used for collecting internal and external data of the client associated with each deposit-free application in the credit lease service;
the identification module is used for monitoring the client behavior according to the internal and external data of the client and identifying fraud and client operation risk in the credit lease service according to the client behavior;
and the handling module is used for taking corresponding handling actions according to the fraud and the client operation risk.
According to a third aspect of the present invention, there is provided a non-transitory computer readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements a risk monitoring and warning method in a credit rental business.
The risk monitoring and early warning method and the risk monitoring and early warning system in the credit lease service provided by the embodiment of the invention can monitor, evaluate and early warn the cheat lease and the operation risk of the credit lease service, can timely, comprehensively and accurately monitor the customer behavior, and can identify the cheat lease and the operation risk of the customer in the credit lease service.
Drawings
Fig. 1 is a flowchart of a risk monitoring and early warning method in a credit rental business according to an embodiment of the present invention;
fig. 2 is a connection block diagram of a risk monitoring and early warning system in a credit rental service according to an embodiment of the present invention;
fig. 3 is a block diagram of an entity structure of an electronic device according to an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
Referring to fig. 1, a risk monitoring and early warning method in a credit rental service according to an embodiment of the present invention is provided, including:
s1, collecting internal and external data of client associated with each deposit free application in credit lease service;
s2, monitoring the client behavior according to the internal and external data of the client, and identifying the fraud and the operation risk of the client in the credit lease service according to the client behavior;
and S3, taking corresponding treatment action according to the fraud and the client operation risk.
It can be understood that the credit lease service has a great risk, and in order to ensure the normal operation of the credit lease service, the embodiment of the invention provides a risk monitoring method in the credit lease service. And analyzing the client behaviors according to the collected internal and external data of the client associated with each free deposit application from the moment that the lease contract takes effect, the moment that the lease behavior starts until the lease contract finishes and the lease article returns, identifying the risks in the credit lease service according to the client behaviors, and making corresponding disposal actions according to different types and different risk degrees of the risks.
The embodiment of the invention can monitor the client behavior timely, comprehensively and accurately and identify the cheating lease and the operation risk of the client in the credit lease service by monitoring, evaluating and early warning the cheating lease and the operation risk of the credit lease service.
As an alternative embodiment, before identifying the risk in the credit lease service, internal data and external data of the client are collected and stored, wherein the internal data of the client comprises basic information data and behavior data of the client; the external data of the client at least comprises corporate-based public opinion data, industrial and commercial data, judicial finance and tax data and natural-person-based multi-debt data.
As an alternative embodiment, the method further comprises, after collecting the client internal and external data associated with each deposit exemption application in the credit lease service:
summarizing and fusing internal and external data of each client associated with the deposit-free application to form an original data set of each client;
and removing obviously wrong or repeated data according to the original data set of each client.
It can be understood that, in the step of fusing, cleaning and extracting the monitoring basic data (i.e. internal and external data of the client), the personal information, company information, transaction information, product information, etc. of the client associated with each deposit-free application are fused into a table to form an original data set generated around each client, and the original data is initially processed to remove obvious errors and repeated data therein, such as the following single address and contact way, and the contact information, invalid or temporary receiving address, etc. which have been verified to be out of work are removed from the data.
As an alternative embodiment, the monitoring of the client behavior according to internal and external data of the client, and the identification of cheating lease and client operation risk in the credit lease service according to the client behavior comprises:
monitoring the client behavior according to internal and external data of the client;
and analyzing the customer behaviors, and determining a risk label of each customer, wherein the risk label is a fraud risk label or an operation risk label.
It can be understood that the monitoring indexes given into the participation based on the business logic and the customer behavior attributes are labeled with risk direction or understood as classifying the risk labels according to the attributes, namely, whether the risk is directed to cheating rent or maloperation. If the high-price equipment of the customer is a label for indicating fraud risk, the possibility that the customer turns out the leased goods is indicated, and the condition that the customer is in bad operation cannot be indicated; the batch lease returning of the client is the label pointed by the operation risk, and the equipment leased by the cheating tenant generally has no return and can not be returned.
As an optional embodiment, after analyzing the customer behavior and determining the risk label of each customer, the method further includes:
and setting corresponding batch running frequency according to different types of risk labels of each client. It can be understood that after the risk labels are set, the batch running frequency is set according to the attributes of different risk labels, for example, the order data can be subjected to real-time batch running and real-time triggering, external data such as industrial and commercial property tax and the like are not high in budget saving and timeliness requirements, and batch running can be performed according to the week or the month.
As an alternative embodiment, the output result of the fraud risk tag is yes or no, and the output result of the operation risk tag is severity.
It will be appreciated that, as described above, when processing the risk label, it is possible to distinguish whether the risk label is directed to fraud risk or to business risk, and the purpose is to identify and distinguish between two types of risks of fraud and business in a specific application. From the perspective of specific application and output mode, the difference lies in that the output result and the judgment standard of fraud risk are yes or no; the output result of the operation risk and the judgment standard are 'severity'.
It can be understood that, similar to the traditional credit business, the fraud risk has the characteristics of bad nature, huge loss, difficult recovery and the like, and is easy to cause extremely negative market reverberation, influence the reputation of the company, and is also a main prevention and control target in the credit lease industry. Recently, as supervision is tightened and credit is contracted, black production molecules which specially live in stripping openings can be stripped without openings gradually, attention begins to be turned to a new field, and credit lease is becoming a key target of the black production molecules, so that the elimination of the risk of cheating lease is the first step of action to be completed in the whole set of method or system.
And (4) sorting out the customers who are marked with the early warning indexes of the cheating lease labels, and pushing the customers to a manual worker to judge the manual worker to check and judge based on the hit early warning labels, wherein if the cheating lease can be eliminated, the risk labels are cancelled, and the whole troubleshooting process is finished.
If the risk cannot be eliminated or the fraud is confirmed, the related client will be directly pushed to the asset security department for subsequent asset recovery or even related treatment such as lawsuits.
The operation condition of a lessee as an enterprise client is constantly changed, so that the client can operate well and have financial health when approval is given, but the operation financial condition of the client is greatly and disadvantageously changed due to the influence of industrial policies, client management, upstream and downstream supply chains and the like. The management risk management is to track the business of the client, the upstream and downstream of the client and the management financial conditions of the client including the change of business credit, and continuously monitor the operation conditions of the enterprise.
The business condition of the enterprise is graded in stages, so that the judgment of yes and no is not carried out, but the judgment of the severity is carried out.
And (3) the client who is marked with the 'management' risk label also pushes the secondary judgment to the manual work, specifically, the operator judges the effectiveness of the index, if the risk exists, the index is confirmed to be effective, and if no risk exists, the index is confirmed to be invalid. If the risk label of 'batch leaseback' is verified manually, the label can be cancelled if the normal equipment replacement of the client is not operated and causes a problem, and if the risk label is verified to be that the redundant equipment caused by the referee returns, the risk label can be cancelled.
Unlike the "cheat rent" risk label, the "business" risk label needs to be further processed after being manually determined and confirmed for the second time.
As an alternative embodiment, the business risk label calculates the score according to various business risk factors and corresponding weights.
It can be understood that when the operation risk labels are determined, the operation risk labels of the early warning clients are gathered, weights are set for various types of risk labels, and scores are accumulated, wherein the higher the score is, the higher the risk grade is, and the corresponding treatment measures are stronger.
As an optional embodiment, the various risk factors include an industry risk factor, a regional risk factor, an operation transaction risk factor, and a public opinion risk factor;
determining an industry risk factor in the tenant operation risk factors according to the extracted industry policy, industry dynamic and capital environment;
calculating according to regional economic trends and regional industry policy change index data, and determining regional risk factors in the tenant operation risk factors;
calculating according to the extracted company moving, referee and high management change index data, and determining an operation abnormal risk factor in the lessee operation risk factors;
and calculating according to the extracted client public opinion information transaction and the major event public opinion transaction index data of the client enterprises to determine the public opinion risk factors in the lessee operation risk factors.
It can be understood that, based on the above various types of business risk factors, the evaluation is performed, for example, the calculated sizes of the industry risk factor, the regional risk factor, and the business transaction risk factor and the public opinion risk factor are 3, 2, 3, and 1, respectively, and then the weights of the industry development transaction factor, the regional development transaction factor, the enterprise management transaction factor, the enterprise business transaction factor, and the enterprise public opinion transaction factor are 0.3, 0.2, and 0.1, respectively, then the business risk factors are: 3 × 0.3+2 × 0.3+3 × 0.2+1 × 0.1 ═ 2.2.
Note that, in the present embodiment, the weight (0.3, 0.2, 0.1) and the value of the fluctuation range of 20% (or 30%) out of the standard value are defined as (1 or 0), which are merely exemplary, and may be other values, and the present invention is not limited thereto.
As an optional embodiment, further comprising:
and calculating scores according to the various operation risk factors and the corresponding weights to determine the severity of the operation risk label, wherein the severity comprises high risk, medium risk and low risk.
It can be understood that the following three risk ratings, high risk, medium risk and low risk are output according to the final score of the operation risk factor, and corresponding handling actions are set based on the respective business needs, for example, the risk rating is high risk, relatively severe handling measures such as termination of cooperation can be taken, the deposit exemption proportion can be adjusted and the risk rating is low risk, and the like.
Referring to fig. 2, a risk monitoring and early warning system in a credit rental service according to an embodiment of the present invention is provided, including:
a collecting module 21, configured to collect internal and external data of the client associated with each deposit-free application in the credit lease service;
the identification module 22 is used for monitoring the client behaviors according to the internal and external data of the client and identifying fraud and client operation risks in the credit lease service according to the client behaviors;
and the handling module 23 is used for taking corresponding handling actions according to fraud and customer operation risks.
The risk monitoring and early warning system in the credit rental service provided by the embodiment of the present invention corresponds to the risk monitoring and early warning method in the credit rental service provided by the foregoing embodiments, and the relevant technical features of the risk monitoring and early warning system in the credit rental service may refer to the relevant technical features of the risk monitoring and early warning method in the credit rental service, which is not described herein again.
Fig. 3 is a schematic entity structure diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 3, the electronic device may include: a processor (processor)310, a communication Interface (communication Interface)320, a memory (memory)330 and a communication bus 340, wherein the processor 310, the communication Interface 320 and the memory 330 communicate with each other via the communication bus 340. Processor 310 may invoke logic instructions in memory 330 to perform the various steps of the risk monitoring and warning method in the credit rental business described above.
In addition, the logic instructions in the memory 330 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The embodiment of the present invention further provides a non-transitory computer readable storage medium, on which a computer program is stored, where the computer program is implemented to execute the risk monitoring and early warning method in the credit rental business provided by the above embodiments when executed by a processor.
The embodiment of the invention provides a risk monitoring and early warning method and system in a credit lease service, which can monitor, evaluate and early warn cheating lease and operation risk of the credit lease service, can timely, comprehensively and accurately monitor customer behaviors and identify the cheating lease and the operation risk of a customer in the credit lease service.
The above-described system embodiments are merely illustrative, and the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A risk monitoring and early warning method in credit lease service is characterized by comprising the following steps:
collecting internal and external data of a client associated with each deposit-free application in a credit lease service;
monitoring the behavior of the client according to internal and external data of the client, and identifying fraud and operation risk of the client in the credit lease service according to the behavior of the client;
and taking corresponding treatment action according to the fraud and the client operation risk.
2. The risk monitoring and pre-warning method according to claim 1, wherein the client internal and external data comprises client internal data and client external data;
the client internal data comprises basic information data and client behavior data of the client; the external data of the client at least comprises corporate public opinion data, industrial and commercial data, judicial finance and tax data and multi-debt data based on natural people.
3. The risk monitoring and pre-warning method according to claim 2, wherein the collecting the client internal and external data associated with each deposit exemption application in the credit lease service further comprises:
summarizing and fusing internal and external data of each client associated with the deposit-free application to form an original data set of each client;
and removing obviously wrong or repeated data according to the original data set of each client.
4. The risk monitoring and early warning method according to claim 3, wherein the monitoring of the client behavior according to internal and external data of the client, and the identification of cheated lease and the client operation risk in the credit lease service according to the client behavior comprises:
monitoring the client behavior according to internal and external data of the client;
and analyzing the customer behaviors, and determining a risk label of each customer, wherein the risk label is a fraud risk label or an operation risk label.
5. The risk monitoring and pre-warning method according to claim 4, wherein the analyzing the customer behavior and determining the risk label of each customer further comprises:
and setting corresponding batch running frequency according to different types of risk labels of each client.
6. The risk monitoring and warning method according to claim 4, wherein the output result of the fraud risk label is yes or no, and the output result of the operation risk label is severity.
7. The risk monitoring and pre-warning method according to claim 4 or 6, wherein the business risk label calculates a score according to various business risk factors and corresponding weights.
8. The risk monitoring and early warning method according to claim 7, wherein the risk factors include industry risk factors, regional risk factors, business transaction risk factors, and public opinion risk factors; determining an industry risk factor in the tenant operation risk factors according to the extracted industry policy, industry dynamic and capital environment;
calculating according to regional economic trends and regional industry policy change index data, and determining regional risk factors in the tenant operation risk factors;
calculating according to the extracted company moving, referee and high management change index data, and determining an operation abnormal risk factor in the lessee operation risk factors;
and calculating according to the extracted client public opinion information transaction and the major event public opinion transaction index data of the client enterprises to determine the public opinion risk factors in the lessee operation risk factors.
9. The risk monitoring and pre-warning method according to claim 7, further comprising:
and calculating scores according to the various operation risk factors and the corresponding weights to determine the severity of the operation risk label, wherein the severity comprises high risk, medium risk and low risk.
10. A risk monitoring and early warning system in credit lease service is characterized by comprising:
the collecting module is used for collecting internal and external data of the client associated with each deposit-free application in the credit lease service;
the identification module is used for monitoring the client behavior according to the internal and external data of the client and identifying fraud and client operation risk in the credit lease service according to the client behavior;
and the handling module is used for taking corresponding handling actions according to the fraud and the client operation risk.
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