KR102464057B1 - Device and method for providing credit score-based rental service using artificial intelligent - Google Patents

Abstract

According to embodiments, a device and method for providing a rental service based on credit rating are provided. The method for providing a rental service according to embodiments comprises the steps of: receiving, by a processor, subscription information of a user from a user terminal; requesting, by the processor, credit information of the user from an external server based on the subscription information, and receiving the credit information according to the request from the external server; extracting, by the processor, a credit score of the user based on the credit information; calculating, by the processor, a TR score based on the credit score using an attention mechanism; and generating, by the processor, rental condition information for the user based on the TR score and transmitting the rental condition information to the user terminal. In addition, the rental condition information includes a rental target product, a rental period, and a rental cost. The rental cost of the user with the high credit score is less than the rental cost of the user with the low credit score. Accordingly, a risk of cost loss in a process of providing a rental service can be effectively reduced.

Description

Apparatus and method for providing rental service based on credit score using artificial intelligence {DEVICE AND METHOD FOR PROVIDING CREDIT SCORE-BASED RENTAL SERVICE USING ARTIFICIAL INTELLIGENT}

Embodiments of the present invention relate to an apparatus and method for providing a rental service based on a credit score, and more specifically, to a service providing apparatus and method for differentially calculating a rental service fee based on a consumer's credit score using artificial intelligence. will be.

A rental contract means a contract in which the lessee pays rent and provides the object to be used for the duration of the contract in return. In the rental service method, it is possible to use the product while paying a price for a very long period compared to the installment purchase method, so that it is possible to use expensive goods while paying a relatively small amount.

In addition, as we enter the era of the 4th industrial revolution, the value of collecting data from the real world (data acquisition), analyzing it in the virtual world to extract knowledge (data analysis), and applying it back to the real world (applying it to reality) Paying attention to the creation method, the development of intelligent information technology related to AI, big data, IoT, block chain, cloud computing, mobile, etc. is in progress as various SW fields beyond the conventional information and communication technology (ICT).

As such, according to the era of the 4th industrial revolution, there is a need for technology to calculate rental cost and rental period by applying data analysis technology using artificial intelligence to the rental service provision method, but the conventional rental service does not meet that need. It is not possible.

The background art described above is possessed or acquired by the inventor in the process of deriving the disclosure of the present application, and cannot necessarily be said to be a known technology disclosed to the general public prior to the present application.

Embodiments provide a rental service providing apparatus and method for differentially calculating rental costs based on a user's credit score.

The technical problems to be achieved in the embodiments are not limited to those mentioned above, and other technical problems not mentioned may be considered by those of ordinary skill in the art from various embodiments to be described below. can

A rental service providing method according to an embodiment of the present invention includes, by a processor, receiving user's subscription information from a user terminal; requesting, by the processor, the credit information of the user to an external server based on the subscription information, and receiving the credit information according to the request from the external server; extracting, by the processor, the credit score of the user based on the credit information; calculating, by the processor, a TR score based on the credit score using an attention mechanism; Including, by the processor, generating rental condition information for the user based on the TR score and transmitting the rental condition information to the user terminal; , and a rental cost, wherein the rental cost of the user with the high credit score is smaller than the rental cost of the user with the low credit score.

In an embodiment, calculating the TR score using an attention mechanism includes, by the processor, calculating the TR score based on the credit score and the user's confidence score, and the reliability The score may be calculated based on the user's rental overdue history information and the user's health insurance information.

In an embodiment, calculating the TR score using the attention mechanism may include: correcting the credit score by adding a weight to the credit score based on a weighting matrix; calculating the TR score based on the corrected credit score and the confidence score , and a plurality of sections including a fourth section, and an element value of a weighting matrix classified into the third section is greater than an element value of a weighting matrix classified into the second section and the fourth section can do.

In one embodiment, calculating the loss grade of the rental target product; further comprising; generating the rental condition information includes, by the processor, the rental based on the loss grade of the rental target product Determining the cost; may include.

In one embodiment, the method further comprises: correcting the TR score using a TR score prediction model, wherein the TR score prediction model includes an input layer, one or more hidden layers, and an output layer, and the corrected credit score and a plurality of training data related to the confidence score is input to the input layer of the TR score prediction model and passes through the one or more hidden layers and output layers to output an output vector, and the output vector is a loss connected to the output layer Input to the function layer, the loss function layer outputs a loss value using a loss function that compares the output vector with the correct vector for each training data, and the parameter of the TR score prediction model has a small loss value It can be learned in a losing direction.

According to embodiments, the rental service providing apparatus and method for differentially calculating rental costs based on a credit score may provide rental condition information obtained by differentially calculating rental costs based on a user's credit score to a user terminal.

In addition, it is possible to effectively reduce the risk of cost loss in the process of providing a rental service by differentially calculating the rental cost based on the possibility of damage to the rental product and the user's reliability score.

Effects obtainable from the embodiments are not limited to the effects mentioned above, and other effects not mentioned are clearly derived and understood by those of ordinary skill in the art based on the following detailed description. can be

BRIEF DESCRIPTION OF THE DRAWINGS The accompanying drawings, which are included as part of the detailed description to aid understanding of the embodiments, provide various embodiments and, together with the detailed description, explain technical features of the various embodiments.
1 is a diagram illustrating a configuration of an electronic device according to an embodiment of the present invention.
2 is a diagram showing the configuration of a program according to an embodiment of the present invention.
3 is a diagram schematically illustrating a network environment to which a rental service providing apparatus is connected according to an embodiment of the present invention.
FIG. 4 is a block diagram for explaining the structure of the server of FIG. 3 .
5 is a flowchart illustrating a method of providing a rental service according to an embodiment of the present invention.

The following embodiments combine elements and features of the embodiments in a predetermined form. Each component or feature may be considered optional unless explicitly stated otherwise. Each component or feature may be implemented in a form that is not combined with other components or features. In addition, various embodiments may be configured by combining some components and/or features. The order of operations described in various embodiments may be changed. Some features or features of one embodiment may be included in another embodiment, or may be replaced with corresponding features or features of another embodiment.

In the description of the drawings, procedures or steps that may obscure the gist of various embodiments are not described, and procedures or steps that can be understood at the level of those of ordinary skill in the art are also not described. did.

Throughout the specification, when a part is said to "comprising or including" a certain component, it does not exclude other components unless otherwise stated, meaning that other components may be further included. do. In addition, terms such as "... unit", "... group", and "module" described in the specification mean a unit that processes at least one function or operation, which is hardware or software or a combination of hardware and software. can be implemented as Also, "a or an", "one", "the" and like related terms are used herein in the context of describing various embodiments (especially in the context of the claims that follow). Unless otherwise indicated or clearly contradicted by context, it may be used in a sense including both the singular and the plural.

Hereinafter, embodiments according to various embodiments will be described in detail with reference to the accompanying drawings. DETAILED DESCRIPTION The detailed description set forth below in conjunction with the appended drawings is intended to describe exemplary embodiments of various embodiments, and is not intended to represent the only embodiments.

In addition, specific terms used in various embodiments are provided to help the understanding of various embodiments, and the use of these specific terms may be changed to other forms without departing from the technical spirit of various embodiments. .

1 is a diagram illustrating a configuration of an electronic device according to an embodiment of the present invention.

1 is a block diagram of an electronic device 101 in a network environment 100, according to various embodiments. Referring to FIG. 1 , in a network environment 100 , an electronic device 101 communicates with an electronic device 102 through a first network 198 (eg, a short-range wireless communication network) or a second network 199 . It may communicate with at least one of the electronic device 104 and the server 108 through (eg, a long-distance wireless communication network). According to an embodiment, the electronic device 101 may communicate with the electronic device 104 through the server 108 . According to an embodiment, the electronic device 101 includes a processor 120 , a memory 130 , an input module 150 , a sound output module 155 , a display module 160 , an audio module 170 , and a sensor module ( 176), interface 177, connection terminal 178, haptic module 179, camera module 180, power management module 188, battery 189, communication module 190, subscriber identification module 196 , or an antenna module 197 . In some embodiments, at least one of these components (eg, the connection terminal 178 ) may be omitted or one or more other components may be added to the electronic device 101 . In some embodiments, some of these components (eg, sensor module 176 , camera module 180 , or antenna module 197 ) are integrated into one component (eg, display module 160 ). can be The electronic device 101 may also be referred to as a client, a terminal, or a peer.

The processor 120, for example, executes software (eg, a program 140) to execute at least one other component (eg, a hardware or software component) of the electronic device 101 connected to the processor 120. It can control and perform various data processing or operations. According to one embodiment, as at least part of data processing or operation, the processor 120 converts commands or data received from other components (eg, the sensor module 176 or the communication module 190 ) to the volatile memory 132 . may be stored in , process commands or data stored in the volatile memory 132 , and store the result data in the non-volatile memory 134 . According to an embodiment, the processor 120 is the main processor 121 (eg, a central processing unit or an application processor) or a secondary processor 123 (eg, a graphic processing unit, a neural network processing unit (eg, a graphic processing unit, a neural network processing unit) a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor). For example, when the electronic device 101 includes the main processor 121 and the sub-processor 123 , the sub-processor 123 uses less power than the main processor 121 or is set to be specialized for a specified function. can The auxiliary processor 123 may be implemented separately from or as a part of the main processor 121 .

The secondary processor 123 may, for example, act on behalf of the main processor 121 while the main processor 121 is in an inactive (eg, sleep) state, or when the main processor 121 is active (eg, executing an application). ), together with the main processor 121, at least one of the components of the electronic device 101 (eg, the display module 160, the sensor module 176, or the communication module 190) It is possible to control at least some of the related functions or states. According to an embodiment, the coprocessor 123 (eg, an image signal processor or a communication processor) may be implemented as part of another functionally related component (eg, the camera module 180 or the communication module 190 ). have. According to an embodiment, the auxiliary processor 123 (eg, a neural network processing device) may include a hardware structure specialized for processing an artificial intelligence model. Artificial intelligence models can be created through machine learning. Such learning may be performed, for example, in the electronic device 101 itself on which the artificial intelligence model is performed, or may be performed through a separate server (eg, the server 108). The learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but in the above example not limited The artificial intelligence model may include a plurality of artificial neural network layers. Artificial neural networks include deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), restricted boltzmann machines (RBMs), deep belief networks (DBNs), bidirectional recurrent deep neural networks (BRDNNs), It may be one of deep Q-networks or a combination of two or more of the above, but is not limited to the above example. The artificial intelligence model may include, in addition to, or alternatively, a software structure in addition to the hardware structure.

The memory 130 may store various data used by at least one component (eg, the processor 120 or the sensor module 176 ) of the electronic device 101 . The data may include, for example, input data or output data for software (eg, the program 140 ) and instructions related thereto. The memory 130 may include a volatile memory 132 or a non-volatile memory 134 .

The program 140 may be stored as software in the memory 130 , and may include, for example, an operating system 142 , middleware 144 , or an application 146 .

The input module 150 may receive a command or data to be used by a component (eg, the processor 120 ) of the electronic device 101 from the outside (eg, a user) of the electronic device 101 . The input module 150 may include, for example, a microphone, a mouse, a keyboard, a key (eg, a button), or a digital pen (eg, a stylus pen).

The sound output module 155 may output a sound signal to the outside of the electronic device 101 . The sound output module 155 may include, for example, a speaker or a receiver. The speaker can be used for general purposes such as multimedia playback or recording playback. The receiver can be used to receive incoming calls. According to one embodiment, the receiver may be implemented separately from or as part of the speaker.

The display module 160 may visually provide information to the outside (eg, a user) of the electronic device 101 . The display module 160 may include, for example, a control circuit for controlling a display, a hologram device, or a projector and a corresponding device. According to an embodiment, the display module 160 may include a touch sensor configured to sense a touch or a pressure sensor configured to measure the intensity of a force generated by the touch.

The audio module 170 may convert a sound into an electric signal or, conversely, convert an electric signal into a sound. According to an embodiment, the audio module 170 acquires a sound through the input module 150 , or an external electronic device (eg, a sound output module 155 ) connected directly or wirelessly with the electronic device 101 . The electronic device 102) (eg, a speaker or headphones) may output a sound.

The sensor module 176 detects an operating state (eg, power or temperature) of the electronic device 101 or an external environmental state (eg, a user state), and generates an electrical signal or data value corresponding to the sensed state. can do. According to an embodiment, the sensor module 176 may include, for example, a gesture sensor, a gyro sensor, a barometric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biometric sensor, It may include a temperature sensor, a humidity sensor, or an illuminance sensor.

The interface 177 may support one or more specified protocols that may be used by the electronic device 101 to directly or wirelessly connect with an external electronic device (eg, the electronic device 102 ). According to an embodiment, the interface 177 may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

The connection terminal 178 may include a connector through which the electronic device 101 can be physically connected to an external electronic device (eg, the electronic device 102 ). According to an embodiment, the connection terminal 178 may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (eg, a headphone connector).

The haptic module 179 may convert an electrical signal into a mechanical stimulus (eg, vibration or movement) or an electrical stimulus that the user can perceive through tactile or kinesthetic sense. According to an embodiment, the haptic module 179 may include, for example, a motor, a piezoelectric element, or an electrical stimulation device.

The camera module 180 may capture still images and moving images. According to an embodiment, the camera module 180 may include one or more lenses, image sensors, image signal processors, or flashes.

The power management module 188 may manage power supplied to the electronic device 101 . According to an embodiment, the power management module 188 may be implemented as, for example, at least a part of a power management integrated circuit (PMIC).

The battery 189 may supply power to at least one component of the electronic device 101 . According to one embodiment, battery 189 may include, for example, a non-rechargeable primary cell, a rechargeable secondary cell, or a fuel cell.

The communication module 190 is a direct (eg, wired) communication channel or a wireless communication channel between the electronic device 101 and an external electronic device (eg, the electronic device 102, the electronic device 104, or the server 108). It can support establishment and communication performance through the established communication channel. The communication module 190 may include one or more communication processors that operate independently of the processor 120 (eg, an application processor) and support direct (eg, wired) communication or wireless communication. According to one embodiment, the communication module 190 is a wireless communication module 192 (eg, a cellular communication module, a short-range communication module, or a global navigation satellite system (GNSS) communication module) or a wired communication module 194 (eg, : It may include a local area network (LAN) communication module, or a power line communication module). A corresponding communication module among these communication modules is a first network 198 (eg, a short-range communication network such as Bluetooth, wireless fidelity (WiFi) direct, or infrared data association (IrDA)) or a second network 199 (eg, legacy It may communicate with the external electronic device 104 through a cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network (eg, a telecommunication network such as a LAN or a WAN). These various types of communication modules may be integrated into one component (eg, a single chip) or may be implemented as a plurality of components (eg, multiple chips) separate from each other. The wireless communication module 192 uses subscriber information (eg, International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module 196 within a communication network such as the first network 198 or the second network 199 . The electronic device 101 may be identified or authenticated.

The wireless communication module 192 may support a 5G network after a 4G network and a next-generation communication technology, for example, a new radio access technology (NR). NR access technology includes high-speed transmission of high-capacity data (eMBB (enhanced mobile broadband)), minimization of terminal power and access to multiple terminals (mMTC (massive machine type communications)), or high reliability and low latency (URLLC (ultra-reliable and low-latency) -latency communications)). The wireless communication module 192 may support a high frequency band (eg, mmWave band) to achieve a high data rate, for example. The wireless communication module 192 uses various techniques for securing performance in a high-frequency band, for example, beamforming, massive multiple-input and multiple-output (MIMO), all-dimensional multiplexing. It may support technologies such as full dimensional MIMO (FD-MIMO), an array antenna, analog beam-forming, or a large scale antenna. The wireless communication module 192 may support various requirements defined in the electronic device 101 , an external electronic device (eg, the electronic device 104 ), or a network system (eg, the second network 199 ). According to an embodiment, the wireless communication module 192 may include a peak data rate (eg, 20 Gbps or more) for realizing eMBB, loss coverage (eg, 164 dB or less) for realizing mMTC, or U-plane latency for realizing URLLC ( Example: Downlink (DL) and uplink (UL) each 0.5 ms or less, or round trip 1 ms or less) can be supported.

The antenna module 197 may transmit or receive a signal or power to the outside (eg, an external electronic device). According to an embodiment, the antenna module 197 may include an antenna including a conductor formed on a substrate (eg, a PCB) or a radiator formed of a conductive pattern. According to an embodiment, the antenna module 197 may include a plurality of antennas (eg, an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network such as the first network 198 or the second network 199 is connected from the plurality of antennas by, for example, the communication module 190 . can be selected. A signal or power may be transmitted or received between the communication module 190 and an external electronic device through the selected at least one antenna. According to some embodiments, other components (eg, a radio frequency integrated circuit (RFIC)) other than the radiator may be additionally formed as a part of the antenna module 197 .

According to various embodiments, the antenna module 197 may form a mmWave antenna module. According to one embodiment, the mmWave antenna module comprises a printed circuit board, an RFIC disposed on or adjacent to a first side (eg, bottom side) of the printed circuit board and capable of supporting a designated high frequency band (eg, mmWave band); and a plurality of antennas (eg, an array antenna) disposed on or adjacent to a second side (eg, top or side) of the printed circuit board and capable of transmitting or receiving signals of the designated high frequency band. can do.

At least some of the components are connected to each other through a communication method between peripheral devices (eg, a bus, general purpose input and output (GPIO), serial peripheral interface (SPI), or mobile industry processor interface (MIPI)) and a signal ( e.g. commands or data) can be exchanged with each other.

According to an embodiment, the command or data may be transmitted or received between the electronic device 101 and the external electronic device 104 through the server 108 connected to the second network 199 . Each of the external electronic devices 102 or 104 may be the same as or different from the electronic device 101 . According to an embodiment, all or a part of operations executed in the electronic device 101 may be executed in one or more external electronic devices 102 , 104 , or 108 . For example, when the electronic device 101 needs to perform a function or service automatically or in response to a request from a user or other device, the electronic device 101 may perform the function or service itself instead of executing the function or service itself. Alternatively or additionally, one or more external electronic devices may be requested to perform at least a part of the function or the service. One or more external electronic devices that have received the request may execute at least a part of the requested function or service, or an additional function or service related to the request, and transmit a result of the execution to the electronic device 101 . The electronic device 101 may process the result as it is or additionally and provide it as at least a part of a response to the request. For this purpose, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used. The electronic device 101 may provide an ultra-low latency service using, for example, distributed computing or mobile edge computing. In another embodiment, the external electronic device 104 may include an Internet of things (IoT) device. The server 108 may be an intelligent server using machine learning and/or neural networks. According to an embodiment, the external electronic device 104 or the server 108 may be included in the second network 199 . The electronic device 101 may be applied to an intelligent service (eg, smart home, smart city, smart car, or health care) based on 5G communication technology and IoT-related technology.

The server 108 is connected to the electronic device 101 and may provide a service to the connected electronic device 101 . In addition, the server 108 may store and manage various types of information of users who are registered as members by proceeding with a membership registration procedure, and may provide various ordering and payment functions related to services. Also, the server 108 may share execution data of a service application executed in each of the plurality of electronic devices 101 in real time so that the service can be shared among users. The server 108 may have the same configuration as a typical web server (Web Server) or WAP server (WAP Server) in terms of hardware. However, in terms of software, it may include a program module that is implemented through any language such as C, C++, Java, Visual Basic, or Visual C and performs various functions. In addition, the server 108 is generally connected to an unspecified number of clients and/or other servers through an open computer network such as the Internet, receives a request to perform a task from a client or other server, and derives and provides the work result. It means a computer system and the computer software (server program) installed therefor. In addition, the server 108, in addition to the above-described server program, a series of application programs (Application Program) operating on the server 108 and in some cases, various databases (DB: Database, hereinafter " DB") should be understood as a broad concept including. Accordingly, the server 108 classifies, stores and manages member registration information, various information and data about the game in a DB, and this DB may be implemented inside or outside the server 108 . In addition, the server 108 uses a server program that is provided in various ways according to operating systems such as DOS, Windows, Linux, UNIX, and Macintosh in general server hardware. As a representative example, a website used in a Windows environment, Internet Information Server (IIS), and CERN, NCSA, APPACH, etc. used in a Unix environment may be used. In addition, the server 108 may interwork with an authentication system and a payment system for user authentication of a service or an order payment related to a service.

The first network 198 and the second network 199 are a connection structure capable of exchanging information between respective nodes such as terminals and servers, or a network connecting the server 108 and the electronic devices 101 and 104 . (Network). The first network 198 and the second network 199 are Internet (Internet), LAN (Local Area Network), Wireless LAN (Wireless Local Area Network), WAN (Wide Area Network), PAN (Personal Area Network), 3G , 4G, LTE, 5G, Wi-Fi, and the like. The first network 198 and the second network 199 may be the closed first network 198 and the second network 199 such as a LAN or a WAN, but preferably an open type such as the Internet. The Internet is a TCP/IP protocol and several services existing in its upper layers, namely HTTP (HyperText Transfer Protocol), Telnet, FTP (File Transfer Protocol), DNS (Domain Name System), SMTP (Simple Mail Transfer Protocol), SNMP ( Simple Network Management Protocol), NFS (Network File Service), and NIS (Network Information Service) means a worldwide open computer first network 198 and second network 199 structure.

The database may have a general data structure implemented in a storage space (hard disk or memory) of a computer system using a database management program (DBMS). The database may have a data storage form in which data can be freely searched (extracted), deleted, edited, added, and the like. Database is a relational database management system (RDBMS) such as Oracle, Infomix, Sybase, DB2, or object-oriented database management such as Gemston, Orion, O2, etc. It can be implemented for the purpose of an embodiment of the present disclosure by using a system (OODBMS) and an XML-only database (XML Native Database) such as Excelon, Tamino, and Sekaiju, and its function It may have an appropriate field or elements to achieve .

2 is a diagram showing the configuration of a program according to an embodiment of the present invention.

2 is a block diagram 200 illustrating a program 140 in accordance with various embodiments. According to an embodiment, the program 140 executes an operating system 142 , middleware 144 , or an application 146 executable in the operating system 142 for controlling one or more resources of the electronic device 101 . may include Operating system 142 may include, for example, Android™, iOS™, Windows™, Symbian™, Tizen™, or Bada™. At least some of the programs 140 are, for example, preloaded into the electronic device 101 at the time of manufacture, or an external electronic device (eg, the electronic device 102 or 104 ), or a server (eg, the electronic device 102 or 104 ) when used by a user ( 108)) or may be updated. All or part of the program 140 may include a neural network.

The operating system 142 may control management (eg, allocation or retrieval) of one or more system resources (eg, a process, memory, or power) of the electronic device 101 . The operating system 142 may additionally or alternatively include other hardware devices of the electronic device 101 , for example, the input module 150 , the sound output module 155 , the display module 160 , and the audio module 170 . , sensor module 176 , interface 177 , haptic module 179 , camera module 180 , power management module 188 , battery 189 , communication module 190 , subscriber identification module 196 , or It may include one or more driver programs for driving the antenna module 197 .

The middleware 144 may provide various functions to the application 146 so that functions or information provided from one or more resources of the electronic device 101 may be used by the application 146 . The middleware 144 includes, for example, an application manager 201 , a window manager 203 , a multimedia manager 205 , a resource manager 207 , a power manager 209 , a database manager 211 , and a package manager 213 . ), a connectivity manager 215 , a notification manager 217 , a location manager 219 , a graphics manager 221 , a security manager 223 , a call manager 225 , or a voice recognition manager 227 . can

The application manager 201 may manage the life cycle of the application 146 , for example. The window manager 203 may manage one or more GUI resources used in the screen, for example. The multimedia manager 205, for example, identifies one or more formats required for playback of media files, and encodes or decodes a corresponding media file among the media files using a codec suitable for the selected format. can be done The resource manager 207 may manage the space of the source code of the application 146 or the memory of the memory 130 , for example. The power manager 209 may, for example, manage the capacity, temperature, or power of the battery 189 , and determine or provide related information required for the operation of the electronic device 101 by using the corresponding information. . According to an embodiment, the power manager 209 may interwork with a basic input/output system (BIOS) (not shown) of the electronic device 101 .

The database manager 211 may create, retrieve, or change a database to be used by the application 146 , for example. The package manager 213 may manage installation or update of an application distributed in the form of a package file, for example. The connectivity manager 215 may manage, for example, a wireless connection or a direct connection between the electronic device 101 and an external electronic device. The notification manager 217 may provide, for example, a function for notifying the user of the occurrence of a specified event (eg, an incoming call, a message, or an alarm). The location manager 219 may manage location information of the electronic device 101 , for example. The graphic manager 221 may manage, for example, one or more graphic effects to be provided to a user or a user interface related thereto.

Security manager 223 may provide, for example, system security or user authentication. The telephony manager 225 may manage, for example, a voice call function or a video call function provided by the electronic device 101 . The voice recognition manager 227, for example, transmits the user's voice data to the server 108, and based at least in part on the voice data, a command corresponding to a function to be performed in the electronic device 101; Alternatively, the converted text data may be received from the server 108 based at least in part on the voice data. According to an embodiment, the middleware 244 may dynamically delete some existing components or add new components. According to an embodiment, at least a portion of the middleware 144 may be included as a part of the operating system 142 or implemented as software separate from the operating system 142 .

Application 146 includes, for example, home 251 , dialer 253 , SMS/MMS 255 , instant message (IM) 257 , browser 259 , camera 261 , alarm 263 . , contacts 265, voice recognition 267, email 269, calendar 271, media player 273, album 275, watch 277, health 279 (such as exercise or blood sugar) measuring biometric information), or environmental information 281 (eg, measuring atmospheric pressure, humidity, or temperature information). According to an embodiment, the application 146 may further include an information exchange application (not shown) capable of supporting information exchange between the electronic device 101 and an external electronic device. The information exchange application may include, for example, a notification relay application configured to transmit specified information (eg, call, message, or alarm) to an external electronic device, or a device management application configured to manage the external electronic device. have. The notification relay application, for example, transmits notification information corresponding to a specified event (eg, mail reception) generated in another application (eg, the email application 269 ) of the electronic device 101 to the external electronic device. can Additionally or alternatively, the notification relay application may receive notification information from the external electronic device and provide it to the user of the electronic device 101 .

The device management application is, for example, a power source (eg, turn-on or turn-off) of an external electronic device that communicates with the electronic device 101 or some components thereof (eg, a display module or a camera module of the external electronic device). ) or a function (eg brightness, resolution, or focus). The device management application may additionally or alternatively support installation, deletion, or update of an application operating in an external electronic device.

3 is a diagram schematically illustrating a network environment to which a rental service providing apparatus is connected according to an embodiment of the present invention.

Referring to FIG. 3 , a server 300 (hereinafter, referred to as a server) related to a rental service providing apparatus may provide a rental service to a user through a wireless or wired network 600 . To this end, the server 300 may exchange data with the user terminal 400 and the external server 500 . A user who wants to use the rental service provided by the server 300 connects (registers) his or her user terminal to the server 300 and provides subscription information to the server 300 through the user terminal 400. can

The server 300 may receive the user's subscription information from the user terminal 400 . The user's subscription information may include account information including a login ID and password, information corresponding to a credit inquiry agreement, user authentication information, and unique identification information. For information corresponding to the credit inquiry agreement, the server 300 requests the user's credit information from the external server 500, and the server 300 may receive the user's credit information from the external server 500 according to the request. It may include content you agree to do so. The unique identification information may be, for example, either an ID (Identification) of the user terminal 400 or a unique Internet Protocol (IP) address.

The server 300 may request the user's credit information from the external server 500 . Accordingly, the server 300 may receive credit information according to the request from the external server 500 .

The external server 500 may include a personal credit rating company server, the National Health Insurance Corporation server, and a bank server. The credit information may include the user's credit score and the user's health insurance information. Credit score refers to a score given by an individual credit rating agency after evaluating an individual's creditworthiness. The personal credit rating company may be, for example, any one of Nice Jimmy (NICE rating information) and All Credit (KCB). Health insurance information may be collected from the National Health Insurance Corporation server. The health insurance information may include at least one of a payment confirmation of insurance premiums, a confirmation of loss of qualifications, and a confirmation of health insurance copayment. The server 300 may receive information about credit payment details from a bank server.

In an embodiment, the server 300 may extract the user's credit score based on the credit information. The server 300 may generate rental condition information based on the user's credit score.

In an embodiment, the server 300 may calculate the TR score based on the user's credit score using an attention mechanism to be described later.

In one embodiment, the server 300 may calculate the TR score based on the user's credit score and the user's credit score. The user's reliability score may be calculated based on the user's rental payment overdue history information and the user's health insurance information. The user's rental payment overdue history information and the user's health insurance information may be provided from the external server 500 .

In an embodiment, the server 300 may correct the credit score by adding a weight to the user's credit score based on the weight matrix.

In an embodiment, the server 300 may calculate the TR score based on the credit score corrected based on the weight matrix and the user's credit score.

In one embodiment, the server 300 may calculate a loss grade of the rental target product based on the rental target product information. The rental target product information may include at least one of a type of a rental target product, a sales price of the rental target product, and a warranty period of the rental target product.

In an embodiment, the server 300 may calibrate the TR score using the TR score prediction model. To this end, the processor 310 may include an artificial intelligence machine learning model. When the server 300 is implemented as hardware, the processor 310 may include a hardware structure specialized for processing a machine learning model. Machine learning models can be created through artificial intelligence machine learning.

The machine learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but the above-described example is not limited to The artificial intelligence model may include a plurality of artificial neural network layers. Artificial neural networks include deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), restricted boltzmann machines (RBMs), deep belief networks (DBNs), bidirectional recurrent deep neural networks (BRDNNs), It may be one of deep Q-networks or a combination of two or more of the above, but is not limited to the above example. The artificial intelligence model may include, in addition to, or alternatively, a software structure in addition to the hardware structure.

In one embodiment, the server 300 may generate rental condition information for the user based on the TR score and the loss grade of the rental target product. The server 300 may provide rental condition information to the user terminal 400 . The rental condition information may include information corresponding to at least one of a rental target product, a rental period, and a rental cost.

The server 300 may include the same hardware module as a typical web server or a network server in hardware. The server 300 may be implemented in the form of a web server or a network server, and may be implemented as a series of application programs operating on the web server including various databases built in the tangible storage device. . Therefore, the server 300 should be understood as a broad concept that is not limited to any one of the above-described contents.

The server 300 may be implemented through a physical server. That is, the server 300 is implemented as a server including a communication device, receives data from the seller device 500 and the user terminal 400 , and also transmits data to the seller device 500 and the user terminal 400 . You may. The server 300 includes a workstation, a data center, an internet data center (IDC), a direct attached storage (DAS) system, a storage area network (SAN) system, a network attached storage (NAS) system, It may be implemented as at least one of a RAID (redundant array of inexpensive disks, or redundant array of independent disks) system and an EDMS (Electronic Document Management) system, but the present embodiment is not limited thereto.

When the server 300 is implemented through a physical server, the server 300 may transmit or receive data through the network 700 connected wirelessly or wiredly. The network 700 may include a network based on a wired Internet technology, a wireless Internet technology, and a short-range communication technology. Wired Internet technology may include, for example, at least one of a local area network (LAN) and a wide area network (WAN).

Wireless Internet technology is, for example, wireless LAN (WLAN), DLNA (Digital Living Network Alliance), WiBro (Wireless Broadband: Wibro), Wimax (World Interoperability for Microwave Access: Wimax), HSDPA (High Speed Downlink Packet) Access), High Speed Uplink Packet Access (HSUPA), IEEE 802.16, Long Term Evolution (LTE), Long Term Evolution-Advanced (LTE-A), Wireless Mobile Broadband Service (WMBS) and 5G New Radio (NR) technology. However, the present embodiment is not limited thereto.

When the server 300 transmits/receives data in a wireless communication method, the server 300 may comply with technical standards and standard communication methods for mobile communication. For example, standard communication methods include Global System for Mobile communication (GSM), Code Division Multi Access (CDMA), Code Division Multi Access 2000 (CDMA2000), Enhanced Voice-Data Optimized or Enhanced Voice-Data Only (EV-DO). , at least one of Wideband CDMA (WCDMA), High Speed Downlink Packet Access (HSDPA), High Speed Uplink Packet Access (HSUPA), Long Term Evolution (LTE), Long Term Evolution-Advanced (LTEA), and 5G New Radio (NR). may include. However, the present embodiment is not limited thereto.

4 is a block diagram illustrating the structure of the server 300 of FIG. 3 .

Referring to FIG. 4 , the server 300 may include a processor 310 , a communication unit 320 , and a memory 330 .

The processor 310 typically controls the overall operation of the server 300 . The processor 310 may include one or more processors to control other components included in the server 300 . For example, the processor 310 may control the communication unit 320 and the memory 330 in general by executing programs stored in the memory 330 . In addition, the processor 310 may perform a function as a rental service providing apparatus according to an embodiment of the present invention by executing programs stored in the memory 330 .

In an embodiment, the processor 310 may receive the user's subscription information from the user terminal 400 through the communication unit 320 . Also, the processor 310 may receive credit information according to a request from the external server 500 through the communication unit 320 .

In one embodiment, the processor 310 may extract the user's credit score based on the credit information. The processor 310 may generate rental condition information based on the user's credit score.

In one embodiment, the server 300 may calculate the TR score based on the user's credit score and the user's credit score. The user's reliability score may be calculated based on the user's rental payment overdue history information and the user's health insurance information. The user's rental payment overdue history information and the user's health insurance information may be provided from the external server 500 .

In an embodiment, the processor 310 may correct the credit score by adding a weight to the user's credit score based on the weight matrix.

In one embodiment, the processor 310 may calculate the TR score based on the credit score corrected based on the weight matrix and the user's credit score.

In an embodiment, the processor 310 may calculate a loss grade of the rental target product based on the rental target product information. The rental target product information may include at least one of a type of a rental target product, a sales price of the rental target product, and a warranty period of the rental target product.

In one embodiment, the processor 310 may calibrate the TR score using the TR score prediction model.

The communication unit 320 may include one or more components that allow the server 300 to communicate with another device (not shown) and a server (not shown). The other device (not shown) may be a computing device such as the server 300 or a sensing device, but is not limited thereto. The communication unit 320 may receive a user input from another electronic device or data stored in the external device from an external device through a network.

For example, the communication unit 320 may transmit/receive a message for establishing a connection with at least one device. The communication unit 320 may transmit the information generated by the processor 310 to at least one device connected to the server 300 . The communication unit 320 may receive information from at least one device connected to the server 300 . The communication unit 320 may transmit related operation information to the at least one device in response to the information received from the at least one device.

The memory 330 may store a program for processing and controlling the processor 310 . For example, the memory 330 may store information input by a user or information received from another device through a network. Also, the memory 330 may store data obtained by the processor 310 . For example, the memory 330 may store the user's subscription information, the user's credit information, the user's rental payment overdue history information, and the user's health insurance information obtained by the processor 310 . Also, the memory 330 may store data generated by the processor 310 . For example, the memory 330 may include a credit score extracted by the processor 310 based on the user's credit information, a corrected credit score obtained by the processor 310 by correcting the credit score based on a weighting matrix, the user's credit score, TR score can be saved. The memory 330 may store information input to or output from the server 300 . For example, the memory 330 may store information about a preset time, information about a preset range, a value for a difference between internal information and optimized internal information, and set values for one or more function modules.

The memory 330 may include a flash memory type, a hard disk type, a multimedia card micro type, a card type memory (eg, SD or XD memory), and a RAM. (RAM, Random Access Memory) SRAM (Static Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), PROM (Programmable Read-Only Memory), magnetic memory, magnetic disk , may include at least one type of storage medium among optical disks.

Each component included in the server 300 may be connected to a communication path connecting a software module or a hardware module inside the device, so that they can operate organically with each other. These components may communicate using one or more communication buses or signal lines. Each component of the server 300 means a unit for processing at least one function or operation, and may be implemented as a software module, a hardware module, or a combination of software and hardware.

The configuration of the server 300 shown in FIG. 4 is not necessarily essential, and some configurations may be omitted or other configurations not shown in FIG. 4 may be added as necessary. That is, the configuration shown in FIG. 4 is for convenience of description, and embodiments are not limited thereto. Those of ordinary skill in the art will be able to modify and practice the embodiments of the present invention without departing from the scope of the present invention.

5 is a flowchart illustrating a method of providing a rental service according to an embodiment of the present invention.

Referring to FIG. 5 , first, the user's subscription information is received from the user terminal 400 by the processor 310 ( S510 ).

The user's subscription information may include account information including a login ID and password, information corresponding to a credit inquiry agreement, and user authentication information. For information corresponding to the credit inquiry agreement, the server 300 requests the user's credit information from the external server 500, and the server 300 may receive the user's credit information from the external server 500 according to the request. It may include content you agree to do so.

The processor 310 requests the user's credit information from the external server based on the user's subscription information, and receives the credit information according to the request from the external server (S520).

The external server 500 may include a personal credit rating company server, the National Health Insurance Corporation server, and a bank server. The credit information may include the user's credit score and the user's health insurance information. Credit score refers to a score given by an individual credit rating agency after evaluating an individual's creditworthiness. The personal credit rating company may be, for example, any one of Nice Jimmy (NICE rating information) and All Credit (KCB). Health insurance information may be collected from the National Health Insurance Corporation server. The health insurance information may include at least one of a payment confirmation of insurance premiums, a confirmation of loss of qualifications, and a confirmation of health insurance copayment. The server 300 may receive information about credit payment details from a bank server.

By the processor 310, the user's credit score is extracted based on the credit information (S530).

The processor 310 may extract a credit score having a value corresponding to any one of natural numbers ranging from 1 to 1000 based on the user's credit information. That is, the credit score may correspond to any one of natural numbers ranging from 1 to 1000.

In an embodiment, the processor 310 may correct the credit score by adding a weight to the user's credit score based on the weight matrix.

In one embodiment, the weight matrix may be an Nx1 matrix. The number of elements (N) in the weight matrix may be 1000. That is, the weight matrix may be expressed as (w1, w2, w3, ??, w1000). In an embodiment, the elements of the weight matrix may be classified into a plurality of sections. The plurality of sections may include a first section, a second section, a third section, and a fourth section. In an embodiment, the weight matrix m_1_ classified into the first section is (w1, ??, wx), and the weight matrix m_2 classified into the second section is (w(x+1), ??, wy), the weight matrix (m_3) classified into the third section is (w(y+1), ??, wz), and the weight matrix (m_4) classified into the fourth section is (w(z+1) , ??, w1000) (provided that x<y<z, and x, y, and z are natural numbers).

In an embodiment, all elements constituting the weight matrix may have different values. In another embodiment, some elements constituting the weight matrix may have different values.

In an embodiment, element values of the weight matrix m_3 classified into the third section may be greater than the maximum value among element values of the weight matrix m_2 classified into the second section. Also, element values of the weight matrix m_3 classified into the third section may be greater than the maximum value among element values of the weight matrix m_4 classified into the fourth section.

By the processor 310, a TR score is calculated based on the user's credit score using the attention mechanism (S540).

In an embodiment, the processor 310 may calculate the TR score based on the user's credit score and the user's credit score. The TR score may be a score for the processor 310 to generate the user's rental condition information. That is, the processor 310 may calculate the rental cost of the rental condition information based on the TR score.

The user's reliability score may be calculated based on the user's rental payment overdue history information and the user's health insurance information. The user's rental payment overdue history information may be provided from an external server. The processor 310 may calculate a delinquency score based on the user's rental payment overdue history information. The delinquency score may be calculated based on the overdue period and the unpaid amount of the overdue payment included in the rental payment overdue history information. The delinquency score may be inversely proportional to the overdue period and the unpaid amount of the overdue payment. Also, the processor 310 may calculate a premium payment score based on the user's health insurance information.

The premium payment score may be calculated based on an accumulated period in which the user normally pays the premium and the user's premium overdue period. The premium payment score may be proportional to the accumulated period in which premiums are normally paid, and may be inversely proportional to the period of delinquency in premiums. The processor 310 may calculate the user's reliability score based on the delinquency score and the premium payment score. The reliability score may be proportional to the overdue score. Also, the reliability score may be proportional to the premium payment score. In one embodiment, the confidence score may correspond to any one of a natural number ranging from 1 to 1000.

In one embodiment, the processor 310 may calculate the TR score by adding up the user's credit score and the user's credit score.

In an embodiment, the processor 310 may calculate a TR score by multiplying a value obtained by summing the user's credit score and the user's credit score by the first correction coefficient.

In one embodiment, the processor 310 may calculate the TR score using [Equation 1]. In [Equation 1], TR is a TR score, i is a natural number identifying a user, h is a first correction coefficient, r_i is a reliability score of a specific user, and c_i is a credit score of a specific user.

In one embodiment, when the user's credit score is greater than the user's credit score, the processor 310 calculates the difference between the user's credit score and the user's credit score to the sum of the user's credit score and the user's credit score. The TR score may be calculated by multiplying the proportional second correction coefficient.

In one embodiment, the processor 310 may calculate the TR score using [Equation 2]. In [Equation 2], TR is a TR score, i is a natural number identifying a user, k is a correction constant, r_i is a reliability score of a specific user, and c_i is a credit score of a specific user. Here, the correction constant k may be a preset constant for calculating the second correction coefficient.

In one embodiment, the processor 310 may calculate the TR score based on the credit score corrected based on the weight matrix and the user's credit score. The processor 310 may calculate a TR score based on the corrected credit score and the user's confidence score using [Equation 1] and [Equation 2]. In this case, the credit score c_i in [Equation 1] and [Equation 2] may mean a corrected credit score.

By the processor 310, the loss grade of the rental target product is calculated (S550).

The processor 310 may calculate a loss grade based on rental target product information. The rental target product information may include at least one of a type of a rental target product, a sales price of the rental target product, and a warranty period of the rental target product. In an embodiment, the loss grade of the rental product may correspond to any one of a natural number ranging from 1 to 10.

In an embodiment, the processor 310 may classify the rental target product into any one of a first loss grade, a second loss grade, ??, and a tenth loss grade. Here, the first loss class may correspond to a product having the lowest probability of breakage. Conversely, the tenth loss class may correspond to the product that is most likely to break. The processor 310 may determine the rental cost based on the loss grade of the rental target product.

In one embodiment, the processor 310 may calculate the TR score using [Equation 3]. In [Equation 3], TR is a TR score, i is a natural number that identifies a user, h is a first correction coefficient, r_i is a specific user's reliability score, c_i is a specific user's credit score, and b is a rental target product loss It may mean a natural number corresponding to a grade.

By the processor 310, the TR score is corrected using the TR score prediction model (S560).

In one embodiment, the processor 310 may calibrate the TR score using the TR score prediction model. To this end, the TR score prediction model may include an input layer, one or more hidden layers, and an output layer. The TR score prediction model may be trained in advance to accurately correct the TR score based on the credit score and the confidence score corrected through the learning process. To this end, a plurality of training data about the credit score and the reliability score corrected in the learning process may be input to the input layer of the TR score prediction model and pass through one or more hidden layers and output layers to output an output vector. The output vector may be input to a loss function layer connected to the output layer. The loss function layer may output a loss value using a loss function that compares the output vector with the correct vector for each training data. The parameters of the TR score prediction model may be learned in a direction in which the loss value becomes smaller.

For example, the loss function may calculate a loss value according to [Equation 4]. In [Equation 4], N is the number of a plurality of training data, n is a natural number identifying the training data, k is a natural number identifying the value of the n-th training data, nk is the k-th value of the n-th training data , t denotes correct answer data, y denotes an output vector, and E denotes a loss value.

Alternatively, the loss function may calculate a loss value according to [Equation 5]. In [Equation 5], n is the number of learning data for each class, y and j are identifiers indicating classes, C is a constant value, M is the number of classes, x_y is a probability value that the learning data belongs to class y, x_j is learning A probability value that data belongs to class j, L may mean a loss value.

To this end, the processor 310 may include an artificial intelligence machine learning model. When the server 300 is implemented as hardware, the processor 310 may include a hardware structure specialized for processing a machine learning model. Machine learning models can be created through artificial intelligence machine learning.

The machine learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but the above-described example is not limited to The artificial intelligence model may include a plurality of artificial neural network layers. Artificial neural networks include deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), restricted boltzmann machines (RBMs), deep belief networks (DBNs), bidirectional recurrent deep neural networks (BRDNNs), It may be one of deep Q-networks or a combination of two or more of the above, but is not limited to the above example. The artificial intelligence model may include, in addition to, or alternatively, a software structure in addition to the hardware structure.

The processor 310 generates rental condition information for the user based on the TR score and the loss grade of the rental target product, and transmits the rental condition information to the user terminal 400 (S570).

The rental condition information may include information corresponding to at least one of a rental target product, a rental period, and a rental cost. In an embodiment, a rental cost of rental condition information for a user with a high credit score may be smaller than a rental cost of rental condition information for a user with a low credit score.

As described above, the apparatus and method for providing a rental service based on a credit score according to an embodiment of the present invention may provide rental condition information in which the rental cost is differentially calculated based on the user's credit score to the user terminal.

In addition, it is possible to effectively reduce the risk of cost loss in the process of providing a rental service by differentially calculating the rental cost based on the possibility of damage to the rental product and the user's reliability score.

The embodiments described above may be implemented by a hardware component, a software component, and/or a combination of the hardware component and the software component. For example, the apparatus, methods and components described in the embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate (FPGA) array), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions, may be implemented using one or more general purpose or special purpose computers. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For convenience of understanding, although one processing device is sometimes described as being used, one of ordinary skill in the art will recognize that the processing device includes a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that may include For example, the processing device may include a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as parallel processors.

The software may comprise a computer program, code, instructions, or a combination of one or more thereof, which configures a processing device to operate as desired or is independently or collectively processed You can command the device. The software and/or data may be any kind of machine, component, physical device, virtual equipment, computer storage medium or device, to be interpreted by or to provide instructions or data to the processing device. , or may be permanently or temporarily embody in a transmitted signal wave. The software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored in one or more computer-readable recording media.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc. alone or in combination. The program instructions recorded on the medium may be specially designed and configured for the embodiment, or may be known and available to those skilled in the art of computer software. Examples of the computer-readable recording medium include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic such as floppy disks. - includes magneto-optical media, and hardware devices specially configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like. Examples of program instructions include not only machine language codes such as those generated by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

As described above, although the embodiments have been described with reference to the limited drawings, those skilled in the art may apply various technical modifications and variations based on the above. For example, the described techniques are performed in a different order than the described method, and/or the described components of the system, structure, apparatus, circuit, etc. are combined or combined in a different form than the described method, or other components Or substituted or substituted by equivalents may achieve an appropriate result.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

Claims (5)

In the method of providing a customized rental service based on the user's credit information,
receiving, by the processor, subscription information of the user from the user terminal;
requesting, by the processor, the credit information of the user to an external server based on the subscription information, and receiving the credit information according to the request from the external server;
extracting, by the processor, the credit score of the user based on the credit information;
calculating, by the processor, a TR score based on the credit score using an attention mechanism;
Including, by the processor, generating rental condition information for the user based on the TR score and transmitting the rental condition information to the user terminal;
The rental condition information includes a rental target product, a rental period, and a rental cost, wherein the rental cost of a user with a high TR score is smaller than the rental cost of a user with a low TR score,
The step of calculating the TR score,
Comprising, by the processor, calculating the TR score based on the credit score and the user's confidence score,
The reliability score is calculated based on the user's rental payment overdue history information and the user's health insurance information,
The step of calculating the TR score,
correcting the credit score by adding a weight to the credit score based on a weighting matrix;
Calculating the TR score based on the corrected credit score and reliability score;
The number of elements in the weight matrix is 1000,
The elements of the weight matrix are classified into a plurality of sections including a first section, a second section, a third section, and a fourth section,
The element value of the weight matrix classified into the third section is characterized in that greater than the element value of the weight matrix classified into the second section and the fourth section, and calculating the loss grade of the rental target product; including,
The step of generating the rental condition information includes:
determining, by the processor, the rental cost based on the loss grade of the rental subject product;
<Equation>

The TR score is calculated by the above equation, in which TR is the TR score, i is a natural number identifying a user, k is a correction constant, r_i is a credit score of a specific user, and c_i is a credit score of a specific user means,
How to provide rental services.
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