JP2023060970A - Information processing apparatus, information processing method, and program - Google Patents

Abstract

To provide an information processing apparatus that determines a commission rate for transfer of accounts receivable, an information processing method, and a program.SOLUTION: In an information processing system including a server device and a client device which are connected to communicate with each other over a network, the server device serving as an information processing apparatus includes a control unit. The control unit acquires customer data of a user, inputs the acquired customer data to a trained model which is trained by receiving, as input data, customer data of a user and outputting data indicating whether an absence of payment may occur on the user, and determines a commission rate for transfer of accounts receivable regarding the user, based on the probability of the absence of payment of the user output from the trained model.SELECTED DRAWING: Figure 5

Description

The present invention relates to an information processing device, an information processing method, and a program.

There is a factoring service that buys accounts receivable from creditors and collects accounts receivable from debtors. Patent Document 1 discloses a factoring system.

JP 2015-204063 A

The fee rate for the transfer of receivables was determined manually based on years of experience.

According to one aspect of the present invention, an information processing device is provided. This information processing device has a control unit. The control unit acquires the user's customer data. Input the acquired customer data of the user into the trained model. A trained model is a trained model that has been trained using customer data of a user as input data and output data as to whether or not the user has a non-payment. Based on the probability that the user will not make a payment output from the trained model, the user's receivables transfer fee rate is calculated.

FIG. 1 is a diagram showing an example of the system configuration of an information processing system. FIG. 2 is a diagram illustrating an example of a hardware configuration of a server device; FIG. 3 is a diagram illustrating an example of a hardware configuration of a client device; FIG. 4 is a diagram illustrating an example of a functional configuration of a server device; FIG. 5 is an activity diagram showing an example of information processing in the server device. FIG. 6 is a diagram illustrating an example of customer data of a user acquired by an acquisition unit; FIG. 7 is a diagram for explaining an outline of processing in the server device. FIG. 8 is a diagram showing an example of a screen containing recommended commission rates.

Embodiments of the present invention will be described below with reference to the drawings. Various features shown in the embodiments shown below can be combined with each other.

In this specification, the term "unit" may include, for example, a combination of hardware resources implemented by circuits in a broad sense and software information processing that can be specifically realized by these hardware resources. In addition, although various information is handled in this embodiment, this information is represented by the level of the signal value as a binary bit aggregate composed of 0 or 1, and communication and calculation are performed on a circuit in a broad sense. can be

A circuit in a broad sense is a circuit implemented by appropriately combining at least circuits, circuits, processors, memories, and the like. Application Specific Integrated Circuits (ASICs); Programmable Logic Devices (e.g., Simple Programmable Logic Devices (SPLDs); Complex Programmable Logic Devices (CPLDs); and field It includes a programmable gate array (Field Programmable Gate Array: FPGA).

<Embodiment 1>
1. System Configuration FIG. 1 is a diagram showing an example of the system configuration of an information processing system 1000. As shown in FIG. As shown in FIG. 1, an information processing system 1000 includes a server device 100 and a client device 110 as a system configuration. The server device 100 is a server device that executes the processing of this embodiment. The client device 110 is, for example, a PC (Personal Computer) that accesses the server device 100 and uses the functions provided by the server device 100 . The server device 100 and client device 110 are communicably connected via a network 150 .

In FIG. 1, only one client device 110 is shown in the information processing system 1000 for simplification of explanation. However, multiple client devices may be included in the information processing system 1000 and communicatively connected to the server device 100 .
Also, the client device 110 is not limited to a PC, and may be a tablet computer, a smart phone, or the like. Server device 100 is an example of an information processing device.

2. Hardware Configuration (1) Hardware Configuration of Server Device 100 FIG. 2 is a diagram showing an example of the hardware configuration of the server device 100. As shown in FIG. The server device 100 includes a control unit 201, a storage unit 202, and a communication unit 203 as a hardware configuration. The control unit 201 is a CPU (Central Processing Unit) or the like, and controls the server device 100 as a whole. The storage unit 202 is a HDD (Hard Disk Drive), a ROM (Read Only Memory), a RAM (Random Access Memory), an SSD (Solid State Drive), or any combination thereof, and the program and the control unit 201 store the program Stores data and the like used when executing processing based on The control unit 201 executes processing based on a program stored in the storage unit 202, so that the functions of the server device 100 as shown in FIG. 4 and an activity diagram as shown in FIG. and the like are realized. The communication unit 203 is a NIC (Network Interface Card) or the like, connects the server device 100 to the network 150, and controls communication with other devices. Storage unit 202 is an example of a storage medium.

(2) Hardware Configuration of Client Device 110 FIG. 3 is a diagram showing an example of the hardware configuration of the client device 110. As shown in FIG. The client device 110 includes a control unit 301, a storage unit 302, an imaging unit 303, an input unit 304, an output unit 305, and a communication unit 306 as a hardware configuration. The control unit 301 is a CPU or the like, and controls the entire client device 110 . The storage unit 302 is a ROM, RAM, SSD, or any combination thereof, and stores data and the like used when the program and the control unit 301 execute processing based on the program. The functions of the client device 110 are implemented by the control unit 301 executing processing based on the programs stored in the storage unit 302 . The image capturing unit 303 is a camera or the like, and captures an image of a subject. The input unit 304 is a keyboard, mouse, etc., and inputs information to the control unit 301 according to user operations. The output unit 305 is a display or the like, and outputs a result of processing by the control unit 301 or the like. A communication unit 306 is a NIC or the like, connects the client device 110 to the network 150, and controls communication with other devices.

3. Functional Configuration FIG. 4 is a diagram showing an example of the functional configuration of the server device 100. As shown in FIG. The server device 100 includes an acquisition unit 401, a processing unit 402, and a display control unit 403 as functional configurations.

(Acquisition unit 401)
The acquisition unit 401 acquires customer data of the user of the client device 110 in response to a request from the client device 110 or the like. More specifically, the acquisition unit 401 acquires the user's customer data from the linked customer management system. Here, the customer management system is a system that retains and manages customer information about customers of users, history information of interactions with customers, and the like. Customer data is data relating to a user's customer. A more specific example of the customer data will be described later with reference to FIGS. 6, 7, and the like.

(Processing unit 402)
The processing unit 402 obtains the probability that the user will not make a payment based on the user's customer data acquired by the acquisition unit 401 . More specifically, the processing unit 402 inputs the acquired customer data of the user into the learned model. Then, the processing unit 402 acquires the probability that the user will not make a payment, which is output from the trained model. Here, the learned model is a learned model that has been learned using the user's customer data as input data and two values as output data, ie, whether or not the user has not received a payment. A trained model is stored in the storage unit 202, for example. In addition, the processing unit 402 obtains the user's credit transfer fee rate based on the probability that the user will not receive payment output from the learned model.

(Display control unit 403)
The display control unit 403 controls to display the screen of the client device 110 that requested the display including the fee rate for the assignment of the user's claim.

4. Information Processing FIG. 5 is an activity diagram showing an example of information processing in the server device 100 .
In A501, the acquisition unit 401 acquires customer data of the user. As described above, the acquisition unit 401 acquires the user's customer data from the linked customer management system. Here, the customer management system may operate on the server device 100, or may operate on another server device or the like. FIG. 6 is a diagram showing an example of user customer data acquired by the acquisition unit 401 . Customer data includes the amount of receivables (maximum transfer amount), average unit price, number of claims, ratio of sole proprietors, maximum unit price, minimum unit price, whether the project type is enterprise, whether the target business is an existing business, and the screening method is customer screening. Whether it is a type, etc. are included. The average unit price is an example of the average unit price for the user's customers. The sole proprietorship percentage is an example of the sole proprietorship percentage for the user's customers.

Note that the user's customer data shown in FIG. 6 is an example. FIG. 7 is a diagram explaining an outline of processing in the server apparatus 100. As shown in FIG. 701 in FIG. 7 is customer data. In order to simplify the explanation, FIG. 7 shows the average unit price and the proportion of sole proprietors among the customer data.

In A502, the processing unit 402 inputs the user's customer data acquired by the acquiring unit 401 into the learned model.
Reference numeral 702 in FIG. 7 indicates a machine learning model with customer data as an explanatory variable and whether or not there will be unpaid payments within several months (binary value) as an objective function. That is, the trained model predicts whether or not there will be unpaid bills from the customer data.
At A503, the processing unit 402 acquires the probability of non-payment of money for the user from the learned model.

At A504, the processing unit 402 obtains the fee rate for the user's credit transfer based on the probability that the user will not receive payment.
703 in FIG. 7 indicates that the processing unit 402 creates groups of sellers with similar characteristics from the customer data, and obtains the average non-payment rate of each group (only those who have accepted more than a certain amount). The processing unit 402 determines to which group the customer data of the seller to be predicted is assigned, and obtains the average non-payment rate of the determined group.
The processing unit 402 obtains the user's receivable transfer fee rate based on the probability of non-payment of the user obtained in A504 and the average non-payment rate of other users with similar customer data characteristics ( 704 in FIG. 7).

In addition, the processing unit 402 adjusts the numerical value obtained by the above formula to the actual commission rate range.

Then, the processing unit 402 sets the adjusted value as the recommended commission rate (705 in FIG. 7).

In A505, the display control unit 403 generates a screen containing the commission rate obtained in A504, and controls the screen to be displayed on the output unit 305 of the client device 110 that made the request.
FIG. 8 is a diagram showing an example of a screen containing recommended commission rates. FIG. 8 includes a recommended commission rate 801 that has been obtained.

As described above, according to the present embodiment, it is possible to automatically obtain the commission rate for the claim to be transferred. In addition, as a result, the commission rate for assignment of claims can be made more accurate.

(Modification)
A modification of the first embodiment will be described.
The processing unit 402 may obtain the user's claim transfer fee rate based on the user's non-payment probability output from the trained model and the user's past record of payment. Here, the server device 100 may acquire and manage the past payment results of users who use services other than the target transaction. In such a configuration, the processing unit 402 also considers the past payment results of users who use services other than the target transaction as the user's past payment results, and obtains the fee rate for the transfer of the claim. .
Also, for example, the processing unit 402 may change the commission interest rate based on contract terms and the like.
For example, the processing unit 402 may add a predetermined value such as +m% to the fee rate each time the desired transfer date is n business days earlier than the specified date. n and m are defined values.
In the case of “introduction (agency)”, the processing unit 402 may add a predetermined value such as +p% to the commission rate. p is a defined value.
<Appendix>
The invention may be provided in each of the aspects described below.
In the information processing device, the customer data of the user includes an average unit price of customers of the user.
In the information processing device, the customer data of the user includes a sole proprietorship percentage of the customer of the user.
In the information processing device, the control unit acquires customer data of the user from a linked customer management system.
In the information processing device, the control unit controls to display a screen including a charge rate for assigning a claim relating to the user.
In the information processing device, the control unit obtains a credit transfer fee rate for the user based on the probability of non-payment of the user output from the learned model and the user's past record of payment. , information processing equipment.
In the information processing device, the control unit controls the user based on the probability of non-payment of the user output from the learned model and the average non-payment rate of other users whose customer data features are similar. An information processing device that obtains a commission rate for assignment of receivables related to.
An information processing method executed by an information processing device, which acquires customer data of a user, inputs the acquired customer data of the user into a trained model, and the trained model inputs the customer data of the user as input data, A trained model that has been trained using output data indicating whether or not the user has failed to make a payment, and based on the probability that the user has failed to make a payment output from the learned model, the fee rate for the assignment of claims relating to the user is calculated. Ask for information processing methods.
A program for causing a computer to function as a control section of the information processing apparatus.
Of course, this is not the only case.

For example, the program for realizing the above software may be provided as a computer-readable non-transitory recording medium (Non-Transitory Computer-Readable Medium), or may be provided downloadably from an external server. Alternatively, it may be provided so that the program is activated by an external computer and the function is realized by the client terminal (so-called cloud computing).
Further, the embodiment and modifications described above may be arbitrarily combined and implemented.
In the above-described embodiment, the server device 100 generates a screen and transmits it to the client device 110 . However, the server device 100 transmits data for generating the screen to the client device 110 . Then, the client device 110 may generate and display a screen based on the data received from the server device 100 .

Also, the functions provided by the server device described above may be provided by a system configured by a plurality of server devices.

Finally, while various embodiments of the invention have been described, these have been presented by way of example and are not intended to limit the scope of the invention. The novel embodiments can be embodied in various other forms, and various omissions, replacements, and modifications can be made without departing from the scope of the invention. Embodiments and modifications thereof are included in the scope and gist of the invention, and are included in the scope of the invention described in the claims and equivalents thereof.

100 : Server device 110 : Client device 150 : Network 201 : Control unit 202 : Storage unit 203 : Communication unit 301 : Control unit 302 : Storage unit 303 : Imaging unit 304 : Input unit 305 : Output unit 306 : Communication unit 401 : Acquisition Unit 402 : Processing unit 403 : Display control unit 801 : Recommended commission rate 1000 : Information processing system

Claims (9)

An information processing device,
having a control unit,
The control unit
Get the user's customer data,
Input the acquired customer data of the user into the trained model,
The learned model is a learned model that has been learned using customer data of the user as input data and output data as to whether or not the user will be unpaid,
Obtaining a fee rate for the transfer of receivables related to the user based on the probability of non-payment of the user output from the trained model;
Information processing equipment. In the information processing device according to claim 1,
the user's customer data includes an average unit price for the user's customers;
Information processing equipment. In the information processing apparatus according to claim 1 or claim 2,
the user's customer data includes a sole proprietorship percentage for the user's customers;
Information processing equipment. In the information processing apparatus according to any one of claims 1 to 3,
The control unit
Acquiring customer data of said user from a linked customer management system,
Information processing equipment. In the information processing apparatus according to any one of claims 1 to 4,
The control unit
control to display a screen containing a fee rate for the transfer of claims related to the user;
Information processing equipment. In the information processing apparatus according to any one of claims 1 to 5,
The control unit
Obtaining a fee rate for the transfer of receivables related to the user based on the probability of non-payment of the user output from the trained model and the actual value of the past payment of the user;
Information processing equipment. In the information processing apparatus according to any one of claims 1 to 6,
The control unit
Based on the probability of non-payment of said user output from said trained model and the average non-payment rate of other users whose customer data features are similar, obtaining the fee rate of transfer of receivables related to said user;
Information processing equipment. An information processing method executed by an information processing device,
Get the user's customer data,
Input the acquired customer data of the user into the trained model,
The learned model is a learned model that has been learned using customer data of the user as input data and output data as to whether or not the user will be unpaid,
Obtaining a fee rate for the transfer of receivables related to the user based on the probability of non-payment of the user output from the trained model;
Information processing methods. a program,
A program for causing a computer to function as a control unit of the information processing apparatus according to any one of claims 1 to 7.

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