Information processing method, program, and information processing system

Abstract

To present a suitable M & A destination without requiring a complicated operation.SOLUTION: An information processing method according to an embodiment includes an acquisition step of acquiring a plurality of feature amounts in a company, a calculation step of calculating a similarity between a plurality of companies with respect to the acquired plurality of feature amounts, a weighting step of weighting the calculated similarity and calculating a weighted average, and an extraction step of extracting an M & A candidate company based on the weighted average of the similarity calculated in the weighting step.SELECTED DRAWING: Figure 6

Description

[Technical Field]

[0001] The present invention relates to an information processing method, a program, and an information processing system. [Background technology]

[0002] Patent Document 1 discloses an information processing system that presents candidates for M&A (Mergers and Acquisitions) partners that are suitable for a user company. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2023-102690 Summary of the Invention [Problem to be solved by the invention]

[0004] In the case of the above-mentioned prior art, potential M&A partners are presented to user companies, who evaluate them positively or negatively, and the evaluation results are fed back to retrain the M&A partner search algorithm. However, this requires the user companies to take the time to evaluate them positively or negatively.

[0005] In consideration of the above, the present invention aims to provide an information processing method, program, and information processing system that can present suitable M&A partners without requiring complicated operations. [Means for solving the problem]

[0006] According to one embodiment of the information processing method, the method includes an acquisition step of acquiring a plurality of feature quantities for a company, a calculation step of calculating similarities between a plurality of companies with respect to the acquired plurality of feature quantities, a weighting step of weighting the calculated similarities and calculating a weighted average, and an extraction step of extracting M&A candidate companies based on the weighted average of the similarities calculated in the weighting step.

[0007] According to one embodiment of the program, an information processing device is caused to execute an information processing method including an acquisition step of acquiring multiple feature quantities for a company, a calculation step of calculating similarities between multiple companies with respect to the acquired multiple feature quantities, a weighting step of weighting the calculated similarities and calculating a weighted average, and an extraction step of extracting M&A candidate companies based on the weighted average of the similarities calculated in the weighting step.

[0008] According to one embodiment, the information processing system is executed by an information processing device and performs an acquisition step of acquiring multiple feature quantities for companies, a calculation step of calculating similarities between multiple companies regarding the acquired multiple feature quantities, a weighting step of weighting the calculated similarities and calculating a weighted average, and an extraction step of extracting M&A candidate companies based on the weighted average of the similarities calculated in the weighting step. [Effects of the Invention]

[0009] According to one embodiment, it is possible to present suitable M&A partners without requiring complicated operations. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram illustrating an example of a configuration of an information processing system according to an embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of a hardware configuration of a server according to an embodiment. [Figure 3] FIG. 2 is a diagram illustrating an example of a hardware configuration of a user terminal according to the embodiment. [Figure 4] FIG. 2 is a diagram illustrating an example of a functional configuration of a server according to an embodiment. [Figure 5] FIG. 2 is a diagram illustrating an example of a functional configuration of a user terminal according to the embodiment. [Figure 6] 10 is a flowchart illustrating an example of a process for extracting an M&A partner, which is executed by the information processing system according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] An embodiment of an information processing system according to the present invention will be described below with reference to Figures 1 to 5. In each drawing, the same or equivalent components and parts are denoted by the same reference numerals. Also, the dimensional proportions in the drawings are exaggerated for the sake of explanation and may differ from the actual proportions.

[0012] (System Overview) First, an overview of an information processing system 10 according to this embodiment will be described. The information processing system 10 according to this embodiment is a system that presents potential M&A (Mergers and Acquisitions) partners. In this embodiment, the information processing system 10 is a system that can present suitable M&A partners based on a plurality of characteristics (e.g., industry, traded products, distribution channels, etc.). Specifically, the user can list M&A candidate companies that are expected to create synergies through M&A for a selling company (or a buying company) without performing any complicated operations.

[0013] (System Configuration) Fig. 1 is a diagram showing an example of the configuration of an information processing system 10 according to this embodiment. As shown in Fig. 1, the information processing system 10 according to this embodiment includes a server device 1 and a user terminal 2, which are connected to each other so as to be able to communicate with each other via a network N. The network N is, for example, a wired local area network (LAN), a wireless LAN, the Internet, a public line network, a mobile data communication network, or a combination thereof. In the example of Fig. 1, the information processing system 10 includes one server device 1 and one user terminal 2, but may include multiple of each.

[0014] The server device 1 is an example of an information processing device that receives information on each corporation's industry, financial status, representative, executives, business items, business partners, etc. from the user terminal 2, and uses this information as features to present suitable M&A partners to the user terminal 2. The server device 1 may be a PC (Personal Computer), a smartphone, a tablet terminal, a server device, a microcomputer, or a combination of these. The specific configuration and operation of the server device 1 will be described later.

[0015] The user terminal 2 is an example of an information processing device that performs operations for inputting and displaying various information. The user terminal 2 may be a PC (Personal Computer), a smartphone, a tablet terminal, a server device, a microcomputer, a wearable device, or a combination of these. In this embodiment, an information processing device that can receive information on each corporation and display M&A counterparties is used as an example.

[0016] (Hardware configuration - Server) 2 is a block diagram showing the hardware configuration of the server device 1. The server device 1 includes a processor 101, a memory 102, a storage 103, and a communication I / F 104, which are communicably connected to each other via a bus B.

[0017] The processor 101 controls each component of the server device 1 and realizes the functions of the server device 1 by loading various programs stored in the storage 103 into the memory 102 and executing them. The programs executed by the processor 101 include, but are not limited to, an OS (Operating System) and various programs described below. Execution of these programs by the processor 101 realizes part of the state visualization method according to this embodiment. The processor 101 is, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), a GPU (Graphics Processing Unit), an ASIC (Application Specific Integrated Circuit), a DSP (Digital Signal Processor), or a combination thereof.

[0018] The memory 102 is, for example, a read-only memory (ROM), a random access memory (RAM), or a combination thereof. The ROM is, for example, a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a combination thereof. The RAM is, for example, a dynamic random access memory (DRAM), a static random access memory (SRAM), a magnetoresistive random access memory (MRAM), or a combination thereof.

[0019] The storage 103 stores an OS, various programs (described later), and various data. The storage 103 is, for example, a flash memory, a hard disk drive (HDD), a solid state drive (SSD), a storage class memory (SCM), or a combination of these.

[0020] The communication I / F 104 is an interface for connecting the server device 1 to external devices including the user terminal 2 via the network N and controlling communication. The communication I / F 104 is, for example, an adapter compliant with Bluetooth (registered trademark), Wi-Fi (registered trademark), ZigBee (registered trademark), Ethernet (registered trademark), or optical communication (e.g., Fibre Channel), but is not limited to these.

[0021] (Hardware configuration - user terminal) 3 is a block diagram showing the hardware configuration of the user terminal 2. The user terminal 2 includes a processor 201, a memory 202, a storage 203, a communication I / F 204, an input / output I / F 205, an input device 206, and an output device 207, which are communicably connected to each other via a bus B. The communication I / F 204 is an interface for connecting the user terminal 2 to external devices including the server device 1 via a network N and for controlling communication. The communication I / F 204 is, for example, an adapter compliant with Bluetooth (registered trademark), Wi-Fi (registered trademark), ZigBee (registered trademark), Ethernet (registered trademark), or optical communication (e.g., Fibre Channel), but is not limited to these.

[0022] The input / output I / F 205 is an interface for connecting an input device 206 and an output device 207 to the user terminal 2. The input device 206 is, for example, a mouse, a keyboard, a touch panel, a microphone, a scanner, a camera, various sensors, operation buttons, or a combination of these. The output device 207 as a user interface is, for example, a display, a projector, a printer, a speaker, a vibrator, or a combination of these. In this embodiment, as an example, the output device 207 and the input device 206 are an integrally configured touch panel display.

[0023] In this embodiment, the program may be written to the memory 202 or the storage 203 during the manufacturing stage of the server device 1, or may be provided to the server device 1 via the network N. Alternatively, the program may be provided to the server device 1 via a non-transitory computer-readable recording medium such as a disk medium (not shown).

[0024] (Functional Configuration - Server) Next, the functional configuration of the server device 1 will be described. Fig. 4 is a diagram showing an example of the functional configuration of the server device 1. When executing various programs, the server device 1 realizes various functions using the above-mentioned hardware resources. The server device 1 has a communication unit 11, a storage unit 12, and a control unit 13 as functional configurations realized by the server device 1. Each functional configuration is realized by the processor 101 reading and executing a program stored in the memory 102 or storage 103.

[0025] The storage unit 12 also stores, for each corporation, industry data 121, transaction product data 122, and transaction status 123 as multiple feature quantities for the corporation. The industry data 121 is data related to the corporation's industry and may be information including, for example, an industry code or industry classification. The transaction product data 122 is information related to the products or services handled by the corporation. The transaction status 123 includes two types of information, described below, that indicate the corporation's position in the commercial flow. In this manner, in this embodiment, four pieces of information (industry data 121, transaction product data 122, and transaction status 123 (including two types of information)) are included as feature quantities.

[0026] In this embodiment, two learning models (e.g., Node2Vec and Poincare Embeddings) are used to obtain a transaction status 123 representing two types of commercial flow positions (two types of information). Here, the transaction status 123 representing commercial flow positions is information that aggregates information on a group of companies surrounding a certain company in a transaction network. Companies with similar supplier companies or buyer companies tend to have similar information. Note that the learning model used is not limited to the above, and any learning model that can obtain information that reveals a company's commercial flow position can be used. Note that in this embodiment, M&A counterparties can be extracted even if data on industry 121 or transaction product 122 is missing. Details of this case will be described later.

[0027] The control unit 13 includes an acquisition unit 131 that acquires multiple feature quantities, namely, industry data 121, transaction product data 122, and transaction status 123, and a calculation unit 132 that calculates similarities between the multiple feature quantities. The control unit 13 also includes a weighting unit 133 that weights each similarity and calculates a weighted average, and an extraction unit 134 that extracts M&A counterparties. These will be described in detail later.

[0028] (Functional configuration - User terminal) Next, the functional configuration of the user terminal 2 will be described. Fig. 5 is a diagram showing an example of the functional configuration of the user terminal 2. When executing various programs, the user terminal 2 realizes various functions using the above-mentioned hardware resources. The user terminal 2 has, as functional components realized by the user terminal 2, a communication unit 21, a storage unit 22 in which a program 221 is stored, and a control unit 23. Each functional component is realized by the processor 201 reading and executing the program 221 stored in the memory 202 or the storage 203. The control unit 23 includes an information acquisition control unit 231 that acquires information sent from the server device 1, and a display unit 232 that displays the acquired information on the output device 207.

[0029] Next, the flow of processing of the information processing system according to this embodiment will be described with reference to Fig. 6. Fig. 6 is a flowchart showing an example of processing for extracting M&A counterparties executed by the information processing system 10 according to this embodiment. Specifically, the processing for listing potential buyer companies that are expected to create synergies for a seller company through M&A will be described.

[0030] First, in step S101, the acquisition unit 131 acquires, for each corporation, the industry data 121, the transaction product data 122, and the transaction status 123, which are company features, and stores them in the storage unit 12. At this time, the acquired feature data is data on the features of multiple corporations, including the seller company. Next, in step S102, the calculation unit 132 calculates the similarity of each feature (industry data 121, transaction product data 122, and transaction status 123) between companies, including the seller company. Next, in step S103, the weighting unit 132 weights each similarity. Then, in step S104, the weighting unit 132 calculates a weighted average. Next, in step S105, the extraction unit 134 extracts M&A candidate companies (candidate buyer companies) based on the weighted average of each feature. For the extracted M&A counterparties (candidate buyer companies), information on the M&A candidate companies is sent from the server device 1 to be displayed on the user terminal 2.

[0031] As described above, according to this embodiment, candidate buyer companies that are expected to create synergies with a seller company through M&A are extracted from a weighted average of the similarities calculated for the industry data 121, the transaction product data 122, and the transaction status 123, which are characteristic quantities of the company. Therefore, suitable M&A partners can be extracted even without training data. Furthermore, unlike conventional technologies, the user (e.g., the seller company) does not need to evaluate the presented candidates positively or negatively, eliminating the need for complicated user operations. Furthermore, by acquiring the transaction status 123 as the company's position in the supply chain, it is not necessary to prepare data on past performance, such as a learning model that uses past M&A performance as training data.

[0032] In this embodiment, candidate buyer companies are extracted for a seller company, but this is not limited thereto, and candidate seller companies can be extracted for a buyer company. That is, the feature quantities acquired in step S101 are data on the feature quantities of multiple corporations, including the buyer company. Next, the similarity calculated in step S102 is the similarity between the feature quantities of each of the companies, including the buyer company. Then, in step S105, candidate seller companies are extracted as M&A candidate companies. In this way, not only can candidate buyer companies be extracted for a seller company, but candidate seller companies can also be extracted for a buyer company.

[0033] Furthermore, in this embodiment, M&A candidates are extracted from data including four pieces of information (industry data 121, transaction product data 122, and transaction status 123 (including two types of information)) as company feature quantities. However, when acquiring data, the industry data 121 or transaction product data 122 may be missing. Even in this case, transaction information 123 can be obtained without relying on these pieces of data. That is, in this embodiment, similarity weights are assigned to the remaining feature quantities, and M&A candidates are extracted based on the weighted average. Therefore, even if the industry data 121 or transaction product data 122 is missing, the missing data can be complemented by weighting the transaction information 123 and calculating the weighted average, making it possible to extract suitable M&A candidates.

[0034] Furthermore, in this embodiment, two learning models (for example, Node2Vec and Poincare Embeddings) are used to obtain the transaction status 123 as the position in two types of commercial flows. At this time, if the commercial flows are vectorized and stored in the storage unit 12 as two types of vectors, companies having vectors close (similar) to the vector of the seller company (or buyer company) may be extracted as candidates for M&A.

[0035] As described above, according to this embodiment, the user can list potential buyer companies (seller companies) that are expected to create synergies through M&A with the seller company (buyer company) without having to perform complicated operations.

[0036] Although one embodiment of the present invention has been described above, the present invention is not limited to the above-described embodiment, and modifications, improvements, etc. within the scope of achieving the object of the present invention are included in the present invention.

[0037] Furthermore, for example, the above-described series of processes can be executed by hardware or software. In other words, the functional configuration is merely an example and is not particularly limited. That is, it is sufficient that the information processing system has the function of being able to execute the above-described series of processes as a whole, and there is no particular limit to the type of functional block used to realize this function. Furthermore, the location of the functional block is also not particularly limited and may be arbitrary. For example, a functional block of a server may be transferred to a user terminal, etc. Conversely, a functional block of a user terminal may be transferred to a server, etc. Furthermore, one functional block may be configured as a single piece of hardware, a single piece of software, or a combination thereof.

[0038] Furthermore, for example, when a series of processes is executed by software, the programs constituting the software are installed onto a computer or the like from a network or a recording medium. The computer may be a computer incorporated into dedicated hardware. Furthermore, the computer may be a computer capable of executing various functions by installing various programs thereon, such as a server, a general-purpose smartphone, or a personal computer.

[0039] Furthermore, for example, the recording medium containing such a program may be configured not only as a removable medium (not shown) that is distributed separately from the device main body in order to provide the program to the user, but also as a recording medium that is provided to the user in a state that is pre-installed in the device main body.

[0040] In this specification, the steps of describing a program to be recorded on a recording medium include not only processes that are performed chronologically in accordance with the order, but also processes that are not necessarily performed chronologically but are performed in parallel or individually. In addition, in this specification, the term "system" refers to an overall device that is made up of a plurality of devices, a plurality of means, etc. [Explanation of symbols]

[0041] 10 Information Processing Systems 1 server 2 user terminals 131 Acquisition Department 132 Calculation Unit 133 Weighting section 134 Extraction part

Claims

1. An information processing method executed by an information processing device, An acquisition step of acquiring a plurality of features in a company; a calculation step of calculating similarities between a plurality of companies with respect to the acquired plurality of feature amounts; a weighting step of weighting the calculated similarities and calculating a weighted average; an extraction step of extracting M&A candidate companies based on the weighted average of the similarities calculated in the weighting step; An information processing method including:

2. the plurality of feature amounts include business type data, transaction product data, and a position in the distribution channel of the company; The position in the commercial flow is information that aggregates information on the group of companies surrounding the company in the trading network. The information processing method according to claim 1 .

3. In the extraction step, when extracting M&A candidate companies for a single company, the information is used to extract M&A candidate companies based on a weighted average of similarities between multiple companies including the single company. The information processing method according to claim 2 .

4. In the extraction step, if the industry data or traded product data of the company is missing, the M&A candidate company is extracted based on a weighted average of similarities calculated for the plurality of feature quantities excluding the missing data from among the plurality of feature quantities.

4. The information processing method according to claim 2 or 3.

5. In the information processing device, An acquisition step of acquiring a plurality of features in a company; a calculation step of calculating similarities between a plurality of companies with respect to the acquired plurality of feature amounts; a weighting step of weighting the calculated similarities and calculating a weighted average; an extraction step of extracting M&A candidate companies based on the weighted average of the similarities calculated in the weighting step; A program for executing an information processing method including the steps of:

6. An information processing system executed by an information processing device, An acquisition step of acquiring a plurality of features in a company; a calculation step of calculating similarities between a plurality of companies with respect to the acquired plurality of feature amounts; a weighting step of weighting the calculated similarities and calculating a weighted average; an extraction step of extracting M&A candidate companies based on the weighted average of the similarities calculated in the weighting step; An information processing system that performs the following:

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