CN112668886A - Method, device and equipment for monitoring risks of rental business and readable storage medium - Google Patents
Method, device and equipment for monitoring risks of rental business and readable storage medium Download PDFInfo
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Abstract
The invention discloses a method, a device, equipment and a readable storage medium for monitoring risks of a rental service, wherein the method comprises the following steps: when a loan application request of a client is received, acquiring house information corresponding to the loan application of the client; acquiring the number of houses matched with the house information in a relation network corresponding to historical house information and historical customer information, wherein the historical house information corresponds to the historical customer information in the relation network; determining whether actual building information corresponding to the address information exists or not based on the address information corresponding to the house information; and if the actual floor information corresponding to the address information exists, determining the credit risk of the customer based on the number of the houses, and processing the loan application request based on the credit risk. The invention solves the technical problem that cheating loan is difficult to find when the house data is maliciously made by a leasing agency of a partner.
Description
Technical Field
The invention relates to the technical field of fraud risk management, in particular to a method, a device, equipment and a readable storage medium for risk monitoring of rental business.
Background
At present, a tenant often needs to apply for a tenant loan from a loan institution for fund transfer. The existing process of sending loan to a client is mainly characterized in that a leasing institution of a partner feeds back house data for loan to a loan institution, and the loan institution compares the house data fed back by the leasing institution with the house data, for example, the house number is provided by the leasing institution, and the loan institution compares whether the house number has a persistent loan or not to judge whether the house has a condition of multiple loans in one house or not.
However, when the house data is maliciously manufactured by a leasing agency of a partner, the judgment of whether the house has one house and multiple loans according to the house data fed back by the leasing agency leads to the deviation of the authenticity of a subsequent data verification result, and the leasing agency is difficult to find the cheating and loan problem.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide a method, a device, equipment and a readable storage medium for monitoring the risk of a rental business, and aims to solve the technical problem that cheating and loan are difficult to find when house data are maliciously made by a rental agency of a partner.
In order to achieve the above object, the present invention provides a method for monitoring risk of a rental service, which comprises the following steps:
when a loan application request of a client is received, acquiring corresponding house information used for applying for a loan by the client;
acquiring the number of houses matched with the house information in a relational network corresponding to the historical house information of the transacted loan service and the historical customer information of the transacted loan service, wherein the historical house information corresponds to the historical customer information in the relational network;
determining whether actual building information corresponding to the address information exists or not based on the address information corresponding to the house information;
and if the actual floor information corresponding to the address information exists, determining the credit risk of the customer based on the number of the houses, and processing the loan application request based on the credit risk.
Optionally, when a loan application request of a customer is received, the step of obtaining the house information corresponding to the customer for applying for a loan includes:
when a loan application request of a customer is received, obtaining corresponding loan application materials for applying for a loan by the customer, wherein the loan application materials comprise personal information of the customer and a house lease contract;
and analyzing the text of the house leasing contract to obtain the house information in the house leasing contract.
Optionally, the step of performing text parsing on the house lease contract to obtain the house information in the house lease contract includes:
performing text analysis on the house leasing contract based on an OCR (optical character recognition) model, and determining character contents in the house leasing contract;
and extracting the house information in the house leasing contract from the text content.
Optionally, the step of text parsing the house rental contract based on the OCR model, and determining the text content in the house rental contract includes:
identifying the house leasing contract based on a text box detection model in an OCR (optical character recognition) model, and determining a text box area where characters in the house leasing contract are located;
identifying the text box area in the house rental contract based on a character recognition model in the OCR model to determine character content in the house rental contract.
Optionally, the step of determining whether there is actual floor information corresponding to the address information based on the address information corresponding to the house information includes:
determining target floor information corresponding to the address information based on the address information corresponding to the house information;
and determining whether actual building information corresponding to the address information exists or not based on the target building information.
Optionally, the step of determining whether there is actual floor information corresponding to the address information based on the target floor information includes:
inquiring whether the target building information exists in a preset electronic map;
if the target building information exists, actual building information corresponding to the address information exists;
and if the target building information does not exist, the actual building information corresponding to the address information does not exist.
Optionally, the step of determining the credit risk of the customer based on the number of houses comprises:
if the number of the houses is larger than or equal to a preset number threshold, determining that the credit risk of the customer is high risk, and outputting the credit risk of the customer;
and if the number of the houses is smaller than a preset number threshold, determining that the credit risk mark of the customer is low risk, and outputting the credit risk of the customer.
In addition, in order to achieve the above object, the present invention further provides a risk monitoring device for a rental business, including:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring house information corresponding to a loan applied by a client when the client receives the loan application request;
the second acquisition module is used for acquiring the number of houses matched with the house information in a relational network corresponding to the historical house information of the loan transaction and the historical customer information of the loan transaction, wherein the historical house information corresponds to the historical customer information in the relational network;
the determining module is used for determining whether actual building information corresponding to the address information exists or not based on the address information corresponding to the house information;
and the processing module is used for determining the credit risk of the customer based on the number of the houses if the actual floor information corresponding to the address information exists, and processing the loan application request based on the credit risk.
In addition, in order to achieve the above object, the present invention further provides a risk monitoring device for a rental business, including: the system comprises a memory, a processor and a risk monitoring program of the rental business, wherein the risk monitoring program of the rental business is stored on the memory and can run on the processor, and when being executed by the processor, the risk monitoring program of the rental business realizes the steps of the risk monitoring method of the rental business.
In addition, in order to achieve the above object, the present invention further provides a readable storage medium, where a risk monitoring program of a rental business is stored, and when the risk monitoring program of the rental business is executed by a processor, the steps of the method for monitoring the risk of the rental business are implemented.
The method comprises the steps of obtaining house information corresponding to a loan applied by a client when the request for applying the loan is received; acquiring the number of houses matched with the house information in a relational network corresponding to the historical house information of the transacted loan service and the historical customer information of the transacted loan service, wherein the historical house information corresponds to the historical customer information in the relational network; determining whether actual building information corresponding to the address information exists or not based on the address information corresponding to the house information; and if the actual floor information corresponding to the address information exists, determining the credit risk of the customer based on the number of the houses, and processing the loan application request based on the credit risk. In the embodiment, when a loan institution receives a loan application request of a client, house information used for loan application by the client is acquired, then the number of houses corresponding to the house information is determined according to a pre-constructed relationship network corresponding to the client information and the house information, whether the houses really exist in reality or not is detected, if the houses really exist, credit risk of the client is determined according to the number of the houses, whether the loan application request of the client passes or not is further judged according to the credit risk of the client, so that the problems that a rental structure forges house data and one house has multiple loans are solved, and the problem that the loan is difficult to find is solved when a partner rental institution maliciously kneads house data.
Drawings
FIG. 1 is a schematic structural diagram of a risk monitoring device for a rental business of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flowchart of a risk monitoring method for rental business according to a first embodiment of the present invention;
fig. 3 is a flowchart illustrating a risk monitoring method for rental business according to a second embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, fig. 1 is a schematic structural diagram of a risk monitoring device for a rental business of a hardware operating environment according to an embodiment of the present invention.
The risk monitoring device of the rental service in the embodiment of the present invention may be a PC, or may be a mobile terminal device having a display function, such as a smart phone, a tablet computer, an electronic book reader, an MP3(Moving Picture Experts Group Audio Layer III, motion video Experts compression standard Audio Layer 3) player, an MP4(Moving Picture Experts Group Audio Layer IV, motion video Experts compression standard Audio Layer 4) player, a portable computer, and the like.
As shown in fig. 1, the risk monitoring device of the rental business may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, a communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.
Optionally, the risk monitoring device for the rental business may further include a camera, a Radio Frequency (RF) circuit, a sensor, an audio circuit, a WiFi module, and the like. Such as light sensors, motion sensors, and other sensors. Specifically, the light sensor may include an ambient light sensor that adjusts the brightness of the display screen according to the brightness of ambient light, and a proximity sensor that turns off the display screen and/or the backlight when the risk monitoring device for the rental business moves to the ear. As one type of motion sensor, the gravity acceleration sensor can detect the magnitude of acceleration in each direction (generally three axes), can detect the magnitude and direction of gravity when stationary, and can be used for identifying applications of the posture of the risk monitoring equipment for rental business (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration identification related functions (such as pedometer and tapping), and the like; of course, the risk monitoring device for the rental business may also be configured with other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which are not described herein again.
Those skilled in the art will appreciate that the configuration of the risk monitoring device for a rental business illustrated in FIG. 1 does not constitute a limitation of the risk monitoring device for a rental business, and may include more or fewer components than illustrated, or some components in combination, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and a risk monitoring program of a rental business.
In the risk monitoring device for rental business shown in fig. 1, the network interface 1004 is mainly used for connecting to a background server and performing data communication with the background server; the user interface 1003 is mainly used for connecting a client (user side) and performing data communication with the client; and processor 1001 may be used to invoke a risk monitoring program for the rental business stored in memory 1005.
In this embodiment, the risk monitoring device for the rental business includes: a memory 1005, a processor 1001, and a risk monitoring program for rental business stored in the memory 1005 and operable on the processor 1001, wherein the processor 1001, when calling the risk monitoring program for rental business stored in the memory 1005, performs the following operations:
when a loan application request of a client is received, acquiring corresponding house information used for applying for a loan by the client;
acquiring the number of houses matched with the house information in a relational network corresponding to the historical house information of the transacted loan service and the historical customer information of the transacted loan service, wherein the historical house information corresponds to the historical customer information in the relational network;
determining whether actual building information corresponding to the address information exists or not based on the address information corresponding to the house information;
and if the actual floor information corresponding to the address information exists, determining the credit risk of the customer based on the number of the houses, and processing the loan application request based on the credit risk.
Further, processor 1001 may call the risk monitoring program for the rental business stored in memory 1005, and also perform the following operations:
when a loan application request of a customer is received, obtaining corresponding loan application materials for applying for a loan by the customer, wherein the loan application materials comprise personal information of the customer and a house lease contract;
and analyzing the text of the house leasing contract to obtain the house information in the house leasing contract.
Further, processor 1001 may call the risk monitoring program for the rental business stored in memory 1005, and also perform the following operations:
performing text analysis on the house leasing contract based on an OCR (optical character recognition) model, and determining character contents in the house leasing contract;
and extracting the house information in the house leasing contract from the text content.
Further, processor 1001 may call the risk monitoring program for the rental business stored in memory 1005, and also perform the following operations:
identifying the house leasing contract based on a text box detection model in an OCR (optical character recognition) model, and determining a text box area where characters in the house leasing contract are located;
identifying the text box area in the house rental contract based on a character recognition model in the OCR model to determine character content in the house rental contract.
Further, processor 1001 may call the risk monitoring program for the rental business stored in memory 1005, and also perform the following operations:
determining target floor information corresponding to the address information based on the address information corresponding to the house information;
and determining whether actual building information corresponding to the address information exists or not based on the target building information.
Further, processor 1001 may call the risk monitoring program for the rental business stored in memory 1005, and also perform the following operations:
inquiring whether the target building information exists in a preset electronic map;
if the target building information exists, actual building information corresponding to the address information exists;
and if the target building information does not exist, the actual building information corresponding to the address information does not exist.
Further, processor 1001 may call the risk monitoring program for the rental business stored in memory 1005, and also perform the following operations:
if the number of the houses is larger than or equal to a preset number threshold, determining that the credit risk of the customer is high risk, and outputting the credit risk of the customer;
and if the number of the houses is smaller than a preset number threshold, determining that the credit risk mark of the customer is low risk, and outputting the credit risk of the customer.
The invention also provides a method for monitoring the risk of the rental business, and referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of the method for monitoring the risk of the rental business.
In this embodiment, the method for monitoring risk of rental business includes the following steps:
step S10, when receiving a loan application request of a client, obtaining corresponding house information used for applying loan by the client;
in this embodiment, the method for monitoring the risk of the rental business provided by the present invention is applied to a terminal device of a rental housing loan business, where the terminal device may be a housing platform of the rental business or a loan institution of the rental business, and it should be noted that a client may initiate a loan application request through a client platform corresponding to the terminal device, and upload loan application materials for applying for a loan on the client platform before initiating the loan application request. When a client platform-based loan application request is received by the terminal equipment, namely the client's loan application request is received, the client obtains loan application materials for applying for loan based on the loan application request, and determines house information for applying for loan in the loan application materials based on the loan application materials, wherein the loan application materials comprise the client's personal information and the client's house information for applying for loan.
Step S20, acquiring the number of houses matched with the house information in a relational network corresponding to the historical house information of the loan transaction and the historical customer information of the loan transaction, wherein the historical house information corresponds to the historical customer information in the relational network;
the historical house is a house which has applied for lease loan service at the loan institution, and the historical client is a client who has applied for lease loan service at the loan institution; correspondingly, the historical customer information is personal information of a historical customer corresponding to the loan service transacted by the loan institution, the historical customer information comprises related information such as the name, the identity card information, the contact telephone or the residence and the like of the historical customer, the historical house information is house data corresponding to the historical customer information corresponding to the loan service transacted by the loan institution, and the historical house information can be historical houses.
In this embodiment, the loan institution collects the house information of the transacted loan transaction and the client information of the transacted loan transaction in real time to construct a relationship network corresponding to the house information of the transacted loan transaction and the client information of the transacted loan transaction. The loan institution collects or automatically collects the historical house information of the transacted loan service and the historical customer information of the transacted loan service in advance, and the loan institution records the personal information of the historical customer, namely the historical customer information and the historical house information when transacting the loan application of the historical customer. And then, constructing a corresponding relation network of the historical customer information and the historical house information according to the corresponding relation of the historical customer information and the historical house information, wherein in the corresponding relation network of the historical customer information and the historical house information, the historical customer information corresponds to the historical house information, and one piece of historical customer information can correspond to a plurality of pieces of historical house information. When a loan application request of a client is received, house information corresponding to the loan application of the client is obtained, the house information is matched with all historical house information in a relation network according to the established relation network corresponding to the historical house information and the historical client information, the historical house information matched with the house information is inquired in the relation network, and the number of houses matched with the house information is determined.
Step S30, determining whether actual building information corresponding to the address information exists or not based on the address information corresponding to the house information;
in the embodiment, after house information corresponding to a client for applying for a loan is acquired, address information corresponding to a house for applying for a loan in the house information is determined; after the number of the houses matched with the house information is determined, whether the actual floor information corresponding to the address information exists or not is inquired according to the address information corresponding to the house information, and whether the house information used for applying for loan by the client exists or not is determined. If the actual floor information corresponding to the address information exists, the fact that the house information used for applying for the loan by the client exists really is indicated, and the actual floor information contains the house information used for applying for the loan by the client; if the actual floor information corresponding to the address information does not exist, it is indicated that the house information used for applying for the loan by the client is not necessarily present in reality and needs to be checked or determined on the spot, and the actual floor information does not include the house information used for applying for the loan by the client.
And step S40, if the actual floor information corresponding to the address information exists, determining the credit risk of the client based on the number of the houses, and processing the loan application request based on the credit risk.
In this embodiment, if there is actual floor information corresponding to the address information, which indicates that the house information used by the client for applying for loan is actually present, the credit risk of the client is determined based on the number of houses, and the credit risk of the client is output, so that the staff of the lending institution processes the loan application request of the client according to the credit risk or directly processes the loan application request of the client by the terminal device according to the credit risk, for example, if the credit risk of the client is high, the loan application request is rejected; if the credit risk of the customer is low, the loan application request is approved.
Further, the credit risk of the client can be determined according to the comparison result of the number of houses and the preset number condition by comparing the number of houses matched with the house information with the preset number condition; the number of houses can be input into a pre-trained enterprise credit model to determine the credit risk of the customer according to the enterprise credit model, wherein the enterprise credit model is a mathematical statistics model for quantifying the credit risk into scores.
According to the risk monitoring method for the rental business, when a loan application request of a customer is received, house information corresponding to the customer for applying for a loan is acquired; acquiring the number of houses matched with the house information in a relational network corresponding to the historical house information of the transacted loan service and the historical customer information of the transacted loan service, wherein the historical house information corresponds to the historical customer information in the relational network; determining whether actual building information corresponding to the address information exists or not based on the address information corresponding to the house information; and if the actual floor information corresponding to the address information exists, determining the credit risk of the customer based on the number of the houses, and processing the loan application request based on the credit risk. In the embodiment, when a loan institution receives a loan application request of a client, house information used for loan application by the client is acquired, then the number of houses corresponding to the house information is determined according to a pre-constructed relationship network corresponding to the client information and the house information, whether the houses really exist in reality or not is detected, if the houses really exist, credit risk of the client is determined according to the number of the houses, whether the loan application request of the client passes or not is further judged according to the credit risk of the client, so that the problems that a rental structure forges house data and one house has multiple loans are solved, and the problem that the loan is difficult to find is solved when a partner rental institution maliciously kneads house data.
Based on the first embodiment, a second embodiment of the risk monitoring method for rental business of the present invention is provided, and referring to fig. 3, in this embodiment, step S10 includes:
step S11, when receiving a loan application request of a customer, obtaining loan application materials corresponding to the customer for applying for a loan, wherein the loan application materials comprise personal information of the customer and a house lease contract;
and step S12, performing text analysis on the house leasing contract to obtain house information in the house leasing contract.
In the embodiment, when a loan institution receives a loan application request of a client, loan application materials for applying for a loan by the client are obtained based on the loan application request, wherein the loan application materials comprise personal information of the client and a house leasing contract for applying for the loan of the client, and the house leasing contract comprises house information for applying for the loan. After loan application materials for applying for loan are obtained, house lease contracts in the loan application materials are obtained, text analysis is conducted on the house lease contracts to identify house information contained in the house lease contracts, and the house lease contracts can be subjected to text analysis through an optical character recognition model to identify the house information contained in the house lease contracts.
Further, the step of performing text analysis on the house lease contract to obtain the house information in the house lease contract includes:
step S121, performing text analysis on the house leasing contract based on an OCR model, and determining character contents in the house leasing contract;
and S122, extracting the house information in the house leasing contract from the text content.
In this embodiment, after obtaining the loan application material for applying for the loan, the house lease contract in the loan application material is obtained, and text analysis is performed on the house lease contract according to the pre-trained OCR model to identify the text content in the house lease contract. After the text content contained in the house leasing contract is identified, the house information in the house leasing contract is extracted from the text content. The OCR model is an optical character recognition model and can recognize characters contained in an electronic document or a paper document, and the OCR model comprises a text box detection model and a character recognition model.
Further, the step of performing text parsing on the house leasing contract based on the OCR model and determining the text content in the house leasing contract comprises:
step S1211, based on a text box detection model in the OCR model, identifying the house leasing contract, and determining a text box area where characters in the house leasing contract are located;
step S1212, based on the character recognition model in the OCR model, recognizing the text box area in the house rental contract to determine the character content in the house rental contract.
In this embodiment, the OCR model includes a text box detection model and a character recognition model, where the text box detection model is used to identify a character area contained in a document, and the character recognition model is used to identify a character content contained in the character area identified by the text box detection model. Based on the OCR model, performing text analysis on the house leasing contract to identify character contents contained in the house leasing contract, specifically, inputting the house leasing contract into a text box detection model in the OCR model to allow the text box detection model to identify the house leasing contract and determine a text box area where characters in the house leasing contract are located; and then, the text box detection model outputs the house leasing contract marked with the text box area to a character recognition model in the OCR model, so that the character recognition model recognizes the text box area in the house leasing contract, and the character content in the house leasing contract is recognized.
Further, the step of determining whether there is actual floor information corresponding to the address information based on the address information corresponding to the house information includes:
step S31, determining target floor information corresponding to the address information based on the address information corresponding to the house information;
and step S32, determining whether actual floor information corresponding to the address information exists or not based on the target floor information.
In the embodiment, after house information corresponding to a client for applying for a loan is acquired, address information corresponding to a house for applying for a loan in the house information is determined; after the number of houses matched with the house information is determined, determining target floor information corresponding to the address information according to the address information corresponding to the house information; and then determining whether actual floor information corresponding to the address information exists according to the target floor information so as to determine whether the house information used for applying for loan by the customer exists in reality.
Further, the step of determining whether there is actual floor information corresponding to the address information based on the target floor information includes:
step S321, inquiring whether the target floor information exists in a preset electronic map;
step S322, if the target building information exists, actual building information corresponding to the address information exists;
and step S323, if the target building information does not exist, actual building information corresponding to the address information does not exist.
In this embodiment, after the target floor information corresponding to the address information is determined, whether the target floor information exists is inquired in a preset electronic map, if the target floor information exists in the preset electronic map, actual floor information corresponding to the address information exists, which indicates that the house information used for applying for loan by the customer really exists in reality; if the target floor information does not exist in the preset electronic map, the actual floor information corresponding to the address information does not exist in the preset electronic map, which shows that the house information used for applying for loan by the client does not necessarily exist in reality, and needs to be checked or determined in the field.
Further, the step of determining a credit risk for the customer based on the number of premises comprises:
step S41, if the house number is larger than or equal to a preset number threshold, determining the credit risk of the customer is high risk, and outputting the credit risk of the customer;
and step S42, if the house number is smaller than a preset number threshold, determining that the credit risk of the customer is marked as low risk, and outputting the credit risk of the customer.
In this embodiment, when the preset number condition is a preset number threshold, the number of houses matching the house information is compared with the preset number threshold, so as to determine the credit risk of the customer according to the comparison result of the number of houses and the preset number threshold. Specifically, if the number of houses is greater than or equal to a preset number threshold, determining that the credit risk of the client is high risk, and outputting the credit risk of the client so that a staff of a loan supply structure can process a loan application request according to the credit risk of the client; and if the number of the houses is less than the preset number threshold, determining that the credit risk mark of the client is low risk, and outputting the credit risk of the client so that a staff of the loan supply structure can process the loan application request according to the credit risk of the client.
In the risk monitoring method for the rental business provided by the embodiment, when a loan application request of a customer is received, loan application materials corresponding to the customer for applying for a loan are acquired, wherein the loan application materials include personal information of the customer and a house rental contract; and analyzing the text of the house leasing contract to obtain the house information in the house leasing contract. In this embodiment, when a loan institution receives a loan application request from a customer, obtaining loan application materials corresponding to the customer for applying for loan, performing text analysis on a house lease contract in the loan application materials, identifying house information therein for subsequent determination of the number of houses corresponding to the house information, and detecting whether the houses really exist in reality, thereby avoiding the problems of forged house data of a lease structure and multiple loans in one house, and solving the problem that the cheating loan is difficult to find when a partner lease institution maliciously pinches house data.
In addition, an embodiment of the present invention further provides a risk monitoring device for a rental business, where the risk monitoring device for the rental business includes:
when a loan application request of a client is received, acquiring corresponding house information used for applying for a loan by the client;
the second acquisition module is used for acquiring the number of houses matched with the house information in a relational network corresponding to the historical house information of the loan transaction and the historical customer information of the loan transaction, wherein the historical house information corresponds to the historical customer information in the relational network;
the determining module is used for determining whether actual building information corresponding to the address information exists or not based on the address information corresponding to the house information;
and the processing module is used for determining the credit risk of the customer based on the number of the houses if the actual floor information corresponding to the address information exists, and processing the loan application request based on the credit risk.
Further, the first obtaining module is further configured to:
when a loan application request of a customer is received, obtaining corresponding loan application materials for applying for a loan by the customer, wherein the loan application materials comprise personal information of the customer and a house lease contract;
and analyzing the text of the house leasing contract to obtain the house information in the house leasing contract.
Further, the first obtaining module is further configured to:
performing text analysis on the house leasing contract based on an OCR (optical character recognition) model, and determining character contents in the house leasing contract;
and extracting the house information in the house leasing contract from the text content.
Further, the first obtaining module is further configured to:
identifying the house leasing contract based on a text box detection model in an OCR (optical character recognition) model, and determining a text box area where characters in the house leasing contract are located;
identifying the text box area in the house rental contract based on a character recognition model in the OCR model to determine character content in the house rental contract.
Further, the determining module is further configured to:
determining target floor information corresponding to the address information based on the address information corresponding to the house information;
and determining whether actual building information corresponding to the address information exists or not based on the target building information.
Further, the determining module is further configured to:
inquiring whether the target building information exists in a preset electronic map;
if the target building information exists, actual building information corresponding to the address information exists;
and if the target building information does not exist, the actual building information corresponding to the address information does not exist.
Further, the processing module is further configured to:
if the number of the houses is larger than or equal to a preset number threshold, determining that the credit risk of the customer is high risk, and outputting the credit risk of the customer;
and if the number of the houses is smaller than a preset number threshold, determining that the credit risk mark of the customer is low risk, and outputting the credit risk of the customer.
In addition, an embodiment of the present invention further provides a readable storage medium, where a risk monitoring program of a rental business is stored on the readable storage medium, and when executed by a processor, the method for monitoring a risk of a rental business implements the steps of any one of the methods for monitoring a risk of a rental business.
The specific embodiment of the readable storage medium of the present invention is basically the same as the embodiments of the risk monitoring method for rental business, and will not be described in detail herein.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. 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 (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A risk monitoring method for a rental business is characterized by comprising the following steps:
when a loan application request of a client is received, acquiring corresponding house information used for applying for a loan by the client;
acquiring the number of houses matched with the house information in a relational network corresponding to the historical house information of the transacted loan service and the historical customer information of the transacted loan service, wherein the historical house information corresponds to the historical customer information in the relational network;
determining whether actual building information corresponding to the address information exists or not based on the address information corresponding to the house information;
and if the actual floor information corresponding to the address information exists, determining the credit risk of the customer based on the number of the houses, and processing the loan application request based on the credit risk.
2. The risk monitoring method for rental business of claim 1, wherein the step of acquiring the house information corresponding to the loan application of the customer when receiving the loan application request of the customer comprises:
when a loan application request of a customer is received, obtaining corresponding loan application materials for applying for a loan by the customer, wherein the loan application materials comprise personal information of the customer and a house lease contract;
and analyzing the text of the house leasing contract to obtain the house information in the house leasing contract.
3. The risk monitoring method for rental business of claim 2, wherein the step of text parsing the house rental contract to obtain house information in the house rental contract comprises:
performing text analysis on the house leasing contract based on an OCR (optical character recognition) model, and determining character contents in the house leasing contract;
and extracting the house information in the house leasing contract from the text content.
4. The risk monitoring method for rental business of claim 3, wherein said step of text parsing said house rental contract based on OCR model, determining the text content in said house rental contract comprises:
identifying the house leasing contract based on a text box detection model in an OCR (optical character recognition) model, and determining a text box area where characters in the house leasing contract are located;
identifying the text box area in the house rental contract based on a character recognition model in the OCR model to determine character content in the house rental contract.
5. The risk monitoring method for rental business of claim 1, wherein the step of determining whether there is actual floor information corresponding to the address information based on the address information corresponding to the house information comprises:
determining target floor information corresponding to the address information based on the address information corresponding to the house information;
and determining whether actual building information corresponding to the address information exists or not based on the target building information.
6. The risk monitoring method for rental business of claim 5, wherein the step of determining whether there is actual floor information corresponding to the address information based on the target floor information comprises:
inquiring whether the target building information exists in a preset electronic map;
if the target building information exists, actual building information corresponding to the address information exists;
and if the target building information does not exist, the actual building information corresponding to the address information does not exist.
7. The risk monitoring method for rental business of any one of claims 1 to 6, wherein the step of determining the credit risk of the customer based on the number of houses comprises:
if the number of the houses is larger than or equal to a preset number threshold, determining that the credit risk of the customer is high risk, and outputting the credit risk of the customer;
and if the number of the houses is smaller than a preset number threshold, determining that the credit risk mark of the customer is low risk, and outputting the credit risk of the customer.
8. A risk monitoring device for a rental business, comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring house information corresponding to a loan applied by a client when the client receives the loan application request;
the second acquisition module is used for acquiring the number of houses matched with the house information in a relational network corresponding to the historical house information of the loan transaction and the historical customer information of the loan transaction, wherein the historical house information corresponds to the historical customer information in the relational network;
the determining module is used for determining whether actual building information corresponding to the address information exists or not based on the address information corresponding to the house information;
and the processing module is used for determining the credit risk of the customer based on the number of the houses if the actual floor information corresponding to the address information exists, and processing the loan application request based on the credit risk.
9. A rental business risk monitoring device, comprising: memory, a processor and a risk monitoring program of a rental business stored on the memory and executable on the processor, the risk monitoring program of a rental business, when executed by the processor, implementing the steps of the risk monitoring method of a rental business as claimed in any one of claims 1 to 7.
10. A readable storage medium, on which a risk monitoring program of a rental business is stored, which when executed by a processor implements the steps of the method of risk monitoring of a rental business as claimed in any one of claims 1 to 7.
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Application publication date: 20210416 |