Information processing system, information processing method, and program

Abstract

To provide a mechanism for supporting the preparation of a document for evaluating the business property of an enterprise by using a generation AI.SOLUTION: A first acquiring unit that instructs a generating AI to output input information to input items of the document for evaluating the business viability for the designated business operator, and acquires the output input information; a first acquiring unit that instructs a generating AI to output input information to input items of the document for evaluating the business viability for the designated business operator, and acquires the output input information; The information processing system includes second acquisition means for acquiring the output question sentence, and first output means for outputting the acquired question sentence.SELECTED DRAWING: Figure 5

Description

[Technical Field]

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

[0002] Non-Patent Document 1 is a document disclosing background technology in this technical field. Non-Patent Document 1 states, "The system supports activities in accordance with the Regional Business Support Package (Cabinet Office) and the Basic Policy on Financial Monitoring (Financial Services Agency). It can be used to strengthen the ability to appropriately evaluate the business content and growth potential of companies at various life stages." Furthermore, this non-patent document 1 states, "By efficiently creating business feasibility assessment sheets and importing financial data, attribute information, etc., the administrative burden of assisting in the creation of business overviews is reduced." [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] Information Planning Co., Ltd., “Business Evaluation Support System”, [online], [Retrieved July 19, 2024], Internet<URL:https: / / www.jyohokikaku.co.jp / loan-solution / 129.html> Summary of the Invention [Problem to be solved by the invention]

[0004] The above-mentioned Non-Patent Document 1 describes that, in relation to the creation of a business feasibility assessment sheet, the administrative burden of supporting the creation of a business overview can be reduced by importing financial data, attribute information, etc. However, Non-Patent Document 1 does not mention the use of generative AI. The present invention has been made in consideration of these circumstances, and provides a mechanism that uses generation AI to support the creation of documents for evaluating the business viability of businesses. [Means for solving the problem]

[0005] In order to solve the above problems, for example, the configurations described in the claims are adopted. The present application includes multiple means for solving the above-mentioned problem, and one example is an information processing system that supports the creation of documents for evaluating the business viability of businesses, comprising: a first reception means for receiving the designation of a business; a first acquisition means for instructing a generation AI to output input information for input fields in a document for evaluating the business viability of the designated business and acquiring the output input information; a second acquisition means for instructing the generation AI to output a question sentence for acquiring missing information from the designated business regarding the acquired input information and acquiring the output question sentence; and a first output means for outputting the acquired question sentence. [Effects of the Invention]

[0006] According to the present invention, a mechanism can be provided that uses a generation AI to support the creation of documents for evaluating the business viability of a company. Problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 shows an example of the configuration of an information processing system 100. As shown in FIG. [Figure 2] FIG. 2 shows an example of the configuration of the business support server 101. [Figure 3] FIG. 3 shows an example of the configuration of the LLM server 102. [Figure 4] FIG. 4 shows an example of the configuration of the user terminal 103. [Figure 5] FIG. 5 shows an example of a business support process 500. [Figure 6] FIG. 6 shows an example of a business operator designation screen 600. [Figure 7]FIG. 7 shows an example of input information 700 corresponding to the input item "Company Overview." [Figure 8] FIG. 8 shows an example of input information 800 corresponding to the input item "commercial flow." [Figure 9] FIG. 9 shows an example of input information 900 corresponding to the input item "market." [Figure 10] FIG. 10 shows an example of input information 1000 corresponding to the input item "3C analysis." [Figure 11] FIG. 11 shows an example of input information 1100 corresponding to the input item "5-force analysis." [Figure 12] FIG. 12 shows an example of input information 1200 corresponding to the input item "SWOT analysis." [Figure 13] FIG. 13 shows an example of input information 1300 corresponding to the input item "management system." [Figure 14] FIG. 14 shows an example of input information 1400 corresponding to the input item "financial summary." [Figure 15] FIG. 15 shows an example of input information 1500 corresponding to the input item "management issue." [Figure 16] FIG. 16 shows an example of input information 1600 corresponding to the input item "management policy." [Figure 17] FIG. 17 shows an example of a question list 1700 related to the input item "Five Forces Analysis." [Figure 18] FIG. 18 shows an example of a question list 1800 related to the input item "SWOT analysis." [Figure 19] FIG. 19 shows an example of the configuration of the business support server 1900. [Figure 20] FIG. 20 shows an example of a business support process 2000. [Figure 21] FIG. 21 shows an example of a business support process 2000. [Figure 22] FIG. 22 shows an example of a question list 2200 related to the input item "Five Forces Analysis." [Figure 23] FIG. 23 shows an example of a business support process 2300. DETAILED DESCRIPTION OF THE INVENTION

[0008] 1. Example Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0009] 1-1.Configuration FIG. 1 shows an example of the configuration of an information processing system 100 according to this embodiment. The information processing system 100 includes a business support server 101, an LLM server 102, and multiple user terminals 103. This information processing system 100 is a system for supporting the creation of documents for evaluating the business viability of a company. The devices constituting this system are connected via a wired or wireless network and are capable of sending and receiving information to and from each other.

[0010] Of the devices that make up this system, the business support server 101 is a server that supports the creation of a business feasibility evaluation sheet by the user. The LLM server 102 is a server that receives prompts from the business support server 101 and outputs answers corresponding to the received prompts. The plurality of user terminals 103 are terminal devices used by respective users. Each user creates a business feasibility evaluation sheet using the business support server 101. In this embodiment, a bank employee is assumed as an example of a user.

[0011] Each of these devices includes a processor that executes an operating system, applications, programs, etc., a main storage device such as RAM (Random Access Memory), an auxiliary storage device such as an IC card, hard disk drive, SSD (Solid State Drive), flash memory, etc., a communication control unit such as a network card, wireless communication module, mobile communication module, etc., an input device such as a touch panel, keyboard, mouse, voice input, or input based on motion detection captured by a camera unit, and an output device such as a monitor, display, etc. The output device may also be a device or terminal that transmits information to be output to an external monitor, display, printer, device, etc.

[0012] The main memory stores various programs and applications (modules), and the processor executes these programs and applications to realize the various functional elements of the overall system. Each module may be implemented in hardware, such as by integration. Each module may be an independent program or application, or may be implemented as a subprogram or function within a single integrated program or application.

[0013] In this specification, each module is described as a subject that performs processing, but in reality, the processing is performed by a processor that processes various programs, applications, etc. (modules).

[0014] Various databases (DBs) are stored in the auxiliary storage device. A "database" is a functional element (storage unit) that stores a set of data so that it can accommodate any data manipulation (e.g., extraction, addition, deletion, overwriting, etc.) from a processor or an external computer. There are no limitations on how the database is implemented; for example, it can be a database management system, spreadsheet software, or a text file such as XML or JSON.

[0015] 1-1-1. Business support server 101 FIG. 2 shows an example of the configuration of the business support server 101. The business support server 101 is configured, for example, by one or more servers arranged on a cloud. The main memory device 201 of this server stores programs and applications such as a first receiving module 210, a first acquisition module 211, a second acquisition module 212, and a first output module 213. These programs and applications are executed by the processor 203 to realize the respective functional elements of the business support server 101. Each module will be described below.

[0016] The first reception module 210 receives a designation of a business operator from a user.

[0017] The first acquisition module 211 instructs the generation AI to output input information for input items in a document for evaluating the business viability of a business designated via the first reception module 210. Then, the module acquires the input information output from the generation AI. In this case, the module can instruct the generation AI to output the input information for the input fields for the specified business operator based on at least one of the specified business operator's accounting information and financial statement data.

[0018] The document for assessing business feasibility referred to here specifically refers to a business feasibility assessment sheet, for example. This business feasibility assessment sheet is primarily prepared by financial institutions and is used to determine whether or not to grant a loan. Although the name "business feasibility assessment sheet" is used here, documents with different names can also be processed in the same way as in this document, as long as they are used to assess business feasibility. The input items referred to here specifically refer to the input items on the business feasibility assessment sheet, which may include at least one of the following: company overview, distribution channel, market, 3C analysis, 5 forces analysis, SWOT analysis, management structure, financial summary, management issues, and management measures. The generating AI referred to here specifically refers to the generating AI module 310, which will be described later.

[0019] Next, the second acquisition module 212 instructs the generation AI to output a question for acquiring missing information from a designated business operator regarding the input information acquired by the first acquisition module 211. Then, this module acquires the question output from the generation AI. At that time, the module instructs the generation AI to identify the missing information based on the input information for the above input items previously output by the generation AI.

[0020] The input information for the above input items previously output by the generation AI is specifically model input information, which may be generated by a veteran bank employee using the generation AI or created by the veteran bank employee himself. The generating AI referred to here specifically refers to the generating AI module 310, which will be described later.

[0021] Next, the first output module 213 outputs the question acquired by the second acquisition module 212. Specifically, this module causes the acquired question to be displayed on the display of the user terminal 103.

[0022] Next, the auxiliary storage device 202 will be described. The auxiliary storage device 202 stores an accounting information DB 220, a company information DB 221, a financial statement DB 222, a public relations memo DB 223, a corporate statistics DB 224, an industry-specific audit dictionary DB 225, an audit manual DB 226, an industry trend information DB 227, and an input item table 228. Each DB will be described below.

[0023] The accounting information DB 220 is a database that stores accounting information for each business. The accounting information stored in this DB includes information on the balances and details of deposits and withdrawals for one or more accounts of the business, as well as information on invoices issued or received by the business. The accounting information for each business is stored in association with the business ID.

[0024] The company information DB221 is a database that stores company information for each business. The company information stored in this DB includes the company's name, address, telephone number, representative name, capital, number of employees, industry ID, business type, business content, products and services, history, bases, major business partners, shareholders, corporate philosophy, and future vision. The company information for each business is stored in association with the business ID.

[0025] The financial statement DB 222 is a database that stores financial statement data for each business. The financial statement data stored in this DB includes data for balance sheets, income statements, and cash flow statements. The financial statement data for each business is stored in association with a business ID.

[0026] The public relations memo DB223 is a database that stores public relations memos for each business. The public relations memos stored in this DB include a history of negotiations between the business and the bank. This negotiation history includes documents, emails, and conversations exchanged between the two parties. The public relations memos for each business are stored in association with the business ID.

[0027] The corporate statistics DB 224 is a database that stores corporate statistics for each industry. The corporate statistics stored in this DB include the results of the Corporate Statistics Survey conducted by the Ministry of Finance. These survey results include sales, operating profits, ordinary profits, and capital investments. Corporate statistics for each industry are stored in association with an industry ID.

[0028] The Industry Examination Dictionary DB225 is a database that stores industry information for each industry. The industry information stored in this DB includes information from the Industry Examination Dictionary published by the Financial Affairs Research Institute, a general incorporated association. This information includes industry characteristics, market size, regional characteristics, demand trends, issues and prospects, product knowledge, production methods, transaction methods, capital needs, how to read financial statements, key points for management support, relevant laws and regulations, institutional loans, and industry associations. The industry information for each industry is stored in association with an industry ID.

[0029] The examination manual DB226 is a database that stores loan examination manuals for each industry. The loan examination manuals stored in this DB include the loan examination manuals of each financial institution and the viewpoints of industry-specific support issued by the Financial Services Agency. The loan examination manuals for each industry are stored in association with the industry ID.

[0030] The industry trend information DB 227 is a database that stores trend information for each industry. The trend information stored in this DB includes industry trend information issued by government agencies or private research companies. The trend information for each industry is stored in association with an industry ID.

[0031] The input item table 228 is a table for managing the correspondence between the input items on the business feasibility evaluation sheet and the DBs. This table is used to identify the DBs corresponding to each input item. Note that, since the format (including input items) of the business feasibility assessment sheet usually differs for each financial institution, it is conceivable that the correspondence between the input items and the DB may differ for each financial institution. Therefore, before starting the business support process 500 described below, the business support server 101 sets the format of the business feasibility assessment sheet for the financial institution and the correspondence between the input items and the DB (i.e., the input item table 228). In this table, for example, the input item "company overview" is associated with the accounting information DB 220 and the company information DB 221. As another example, the input item "SWOT analysis" is associated with the company information DB 221, financial statements DB 222, public relations memo DB 223, corporate statistics DB 224, and industry audit dictionary DB 225.

[0032] 1-1-2.LLM Server 102 FIG. 3 shows an example of the configuration of the LLM server 102. The LLM server 102 is configured, for example, by one or more servers arranged on a cloud. The server's main memory device 301 stores programs and applications such as a generation AI module 310. The processor 303 executes these programs and applications to realize the various functional elements of the LLM server 102.

[0033] Among the functional elements realized, the generative AI module 310 is a deep learning model trained in advance using a large-scale data set. This module is, in other words, an LLM (large-scale language model). This module outputs a response to an input prompt (in other words, a command sentence). This module is a deep learning model that has been trained in advance using a large dataset, so it can be used without training data or additional training.

[0034] 1-1-3. User terminal 103 FIG. 4 shows an example of the configuration of the user terminal 103. The user terminal 103 is, for example, a terminal device such as a smartphone, a tablet terminal, a notebook PC, a desktop PC, etc. In this embodiment, a bank employee is assumed as an example of the user.

[0035] The terminal's main memory device 401 stores programs and applications such as a browser module 410. The processor 403 executes these programs and applications to realize the various functional elements of the user terminal 103.

[0036] The browser module 410 exchanges information with the business support server 101 .

[0037] 1-2.Operation Next, the business support process 500 executed by the business support server 101 will be described with reference to Fig. 5. Fig. 5 is a flow diagram showing an example of the business support process 500. The process shown in the figure supports the creation of a business feasibility evaluation sheet. As described above, the business support server 101 is configured with the format of the business feasibility evaluation sheet for the financial institution and the input item table 228 before starting the business support process 500 described below.

[0038] First, the first reception module 210 receives a request for the business operator specification screen 600 from the user terminal 103 (step 501). In response to this request, the first reception module 210 causes the user terminal 103 to display the business operator specification screen 600 (step 502).

[0039] 6 shows an example of a business designation screen 600. The screen shown in the figure includes a company name input field 601, a website information input field 602, and a creation instruction button 603. Of these display elements, the company name input field 601 is where the name of the business for which the business feasibility evaluation sheet is to be created is input. In the HP information input field 602, the HP address (URL) of the business operator for which the business feasibility evaluation sheet is to be created is input. The creation instruction button 603 is a button for instructing the creation of a business feasibility evaluation sheet. 6 includes only a company name input field 601, a website information input field 602, and a creation instruction button 603, but the present invention is not limited to this. For example, it is also possible to have the user input an ID (an ID managed by CRM: Customer Relationship Management) in a database of company information held by the bank as information for identifying the company. In this case, if information such as company names and website addresses is managed in the database of company information, it is not necessarily necessary to provide the company name input field 601 and the website information input field 602.

[0040] On this screen, the user inputs the business name and website address and selects the creation instruction button 603. As a result, the input information is sent from the user terminal 103 to the business support server 101, and the first receiving module 210 acquires the input information (step 503). After acquiring the input information, the first receiving module 210 searches the company information DB 221 to identify the company ID and industry ID corresponding to the acquired company name (step 504).

[0041] Next, the first acquisition module 211 selects input items to be processed from among the input items of the business feasibility assessment sheet to be created (step 505). The business feasibility assessment sheet to be finally created includes a total of 10 input items, for example, company overview, distribution channel, market, 3C analysis, 5 forces analysis, SWOT analysis, management structure, financial summary, management issues, and management measures.

[0042] Next, the first acquisition module 211 refers to the input item table 228 to identify a DB corresponding to the selected input item (step 506). The module then refers to the identified DB to acquire information on the target business and information on the industry to which the target business belongs (step 507). In doing so, the module acquires information corresponding to the business ID or industry ID identified in step 504 from each DB. Hereinafter, the information acquired in this step will be referred to as "reference information."

[0043] Next, the first acquisition module 211 generates a prompt to be input to the generation AI module 310 (step 508). The generated prompt (in other words, a command sentence) includes the following information: (1) The website address of the business operator obtained in step 503 (2) Detailed items that make up the input items to be processed (3) Reference information obtained in step 507 (4) A statement instructing the business operator specified by the website address in (1) to output the input information corresponding to the detailed items in (2) by referring to the reference information in (3).

[0044] The detailed items in (2) are, for example, the company name, representative, industry, business details, base, number of employees, business history, and history in the case of the input item "Company Overview" (see Figure 7).

[0045] Next, the first acquisition module 211 inputs the generated prompt to the generation AI module 310 (step 509). The generation AI module 310 outputs an answer corresponding to the input prompt. The output answer (in other words, input information) is acquired by the first acquisition module 211 (step 510). The first acquisition module 211 inputs the acquired input information into the corresponding input item field of the business feasibility assessment sheet (step 511).

[0046] Next, the second acquisition module 212 receives the output of the input information and generates a prompt to be input to the generation AI module 310 (step 512). The generated prompt includes the following information: (1) Input information acquired in step 510 (2) Model input information (3) A statement ordering the output of questions to obtain information missing from the information entered in (1) from the target business operator in light of the information entered in (2).

[0047] The input information in (2) refers to one or more pieces of input information for the input items to be processed that have been previously output by the generation AI module 310. This input information is, for example, input information generated by a veteran bank employee using the generation AI module 310.

[0048] Next, the second acquisition module 212 inputs the generated prompt to the generation AI module 310 (step 513). The generation AI module 310 outputs an answer corresponding to the input prompt. The output answer is acquired by the second acquisition module 212 (step 514). If the acquired answer includes a question, the second acquisition module 212 inputs the question into the corresponding input item field on the questionnaire (step 515).

[0049] Next, the first acquisition module 211 determines whether all input items have been processed (step 516). If the result of this determination is that all input items have not been processed (NO in step 516), the module returns to step 505 and selects the next input item. On the other hand, if the result of this determination is that all input items have been processed (YES in step 516), the first output module 213 displays the generated business feasibility assessment sheet and questionnaire sheet on the user terminal 103 (step 517).

[0050] The user can then modify and complete the displayed business feasibility assessment sheet as needed. At that time, the user can use the displayed questionnaire to obtain missing information from the target business. The user can then complete the business feasibility assessment sheet by completing the information obtained.

[0051] In the above example, steps 505 to 515 are performed for all input items, but this is not a limitation. For example, after acquiring input information in step 510 and entering the input information into a business feasibility evaluation sheet in step 511, it is possible to consider whether there is any information deficiency, and then perform processing related to the second acquisition module 212 from step 512 onwards only if there is any information deficiency. In this case, it is possible to determine whether there is a deficiency in the amount of information by studying business feasibility evaluation sheets with sufficient information and business feasibility evaluation sheets with insufficient information, both of which were created by experienced bank employees. This also applies to the flows in Figures 20 to 21 and 23 below.

[0052] Alternatively, after determining whether there is a lack of information, when outputting the questionnaire in step 517, it is also possible to distinguish between questions about input items that are determined to have sufficient information (i.e., questions to improve the input) and questions about input items that are determined to have insufficient information (questions that need to be confirmed to make up for the lack of information). This also applies to the flows in Figures 20 to 21 and 23 below.

[0053] An example of the business feasibility assessment sheet and the question sheet displayed on the user terminal 103 will be described below with reference to Figures 7 to 18. First, the business feasibility assessment sheet will be described for each input item.

[0054] 7 shows an example of input information 700 corresponding to the input item "Company Overview." The input information 700 shown in the figure is composed of multiple pieces of input information for multiple detailed items. The multiple detailed items include the company name, representative, industry, business content, bases, number of employees, business history, and history.

[0055] Figure 8 shows an example of input information 800 corresponding to the input item "commercial flow." The input information 800 shown in the figure is composed of multiple pieces of input information for multiple detailed items. The multiple detailed items include the business model, main business, sub-business, suppliers, subcontractors, sales destinations, and consumer demographics. The underlined text contains links to related websites. Users can check the links as needed to confirm whether the content is correct and prevent hallucination from occurring. The same applies to the website links in the examples from Figure 10 onwards.

[0056] 9 shows an example of input information 900 corresponding to the input item "market." The input information 900 shown in the figure is composed of multiple pieces of input information for multiple detailed items. The multiple detailed items include market size, TAM (Total Addressable Market), SAM (Serviceable Available Market), SOM (Serviceable Obtainable Market), and industry trends.

[0057] Figure 10 shows an example of input information 1000 corresponding to the input item "3C analysis." The input information 1000 shown in the figure is composed of multiple pieces of input information for multiple detailed items. The multiple detailed items include customers, competitors, and the company itself. The underlined text contains links to related websites.

[0058] Figure 11 shows an example of input information 1100 corresponding to the input item "Five Forces Analysis." The input information 1100 shown in the figure is composed of multiple pieces of input information for multiple detailed items. The multiple detailed items include competitors, sellers, buyers, new entrants, and substitutes. The underlined text contains links to related websites.

[0059] 12 shows an example of input information 1200 corresponding to the input item "SWOT analysis." The input information 1200 shown in the figure is composed of multiple pieces of input information for multiple detailed items. The multiple detailed items include strengths, weaknesses, opportunities, threats, strengths*opportunities, weaknesses*opportunities, strengths*threats, and weaknesses*threats. The underlined text contains links to related websites.

[0060] 13 shows an example of input information 1300 corresponding to the input item "management structure." The input information 1300 shown in the figure is composed of multiple pieces of input information for multiple detailed items. The multiple detailed items include the management vision, organizational structure, and key people. The underlined text contains links to related websites.

[0061] 14 shows an example of input information 1400 corresponding to the input item "financial summary." The input information 1400 shown in the drawing is made up of an income statement 1401 and a balance sheet 1402. Income Statement 1401 shows sales, cost of goods sold, gross profit, selling expenses, operating income, ordinary income, and EBITDA (Earnings Before Interest Taxes Depreciation and Amortization) for December 2020 through 2024. On the other hand, balance sheet 1402 shows cash and cash equivalents, fixed assets, total assets, long-term borrowings, equity capital, and CF (Cash Flow) ratio for December 2020 to 2024.

[0062] In addition, the input information corresponding to the input item "Financial Summary" is merely information copied from the income statement and balance sheet, so it may be generated by the business support server 101 rather than by the generation AI module 310.

[0063] Next, Fig. 15 shows an example of input information 1500 corresponding to the input item "management issues." The input information 1500 shown in Fig. 15 is composed of multiple pieces of input information for multiple detailed items. The multiple detailed items include short-term issues and long-term issues.

[0064] 16 shows an example of input information 1600 corresponding to the input item "management measures." The input information 1600 shown in the figure is made up of multiple pieces of input information for multiple detailed items. The multiple detailed items include personnel measures, business measures, financial measures, and DX (Digital Transformation) measures.

[0065] Next, we will explain the questionnaire sheet. As an example, we will only explain the input items "5 Forces Analysis" and "SWOT Analysis".

[0066] Fig. 17 shows an example of a question list 1700 for the input item "Five Forces Analysis." The question list 1700 shown in Fig. 17 is composed of multiple questions about multiple question items. The multiple question items include company overview, market environment, supply chain, customer information, barriers to new entry, and substitutes.

[0067] 18 shows an example of a question list 1800 for the input item "SWOT analysis." The question list 1800 shown in the figure is made up of multiple questions for multiple question items. The multiple question items include strengths, weaknesses, opportunities, threats, strengths*opportunities, weaknesses*opportunities, strengths*threats, and weaknesses*threats. The above is the explanation of the business support process 500.

[0068] According to the business support process 500 described above, a business feasibility evaluation sheet can be created using a generation AI, which reduces the time and effort required for information gathering and document creation that was previously required to create a business feasibility evaluation sheet.

[0069] Furthermore, according to this business support process 500, reference information such as accounting information and financial statement data can be included in prompts depending on the input item to be generated, thereby improving the accuracy of the input information output from the generation AI.

[0070] Furthermore, according to this business support process 500, if there is missing information in the input information that has been output, a question is output to elicit the missing information from the business. The bank employee can use this question to elicit the missing information from the business and complete the contents of the business feasibility evaluation sheet. This allows even bank employees with poor document creation skills or poor interview skills to create high-quality business feasibility evaluation sheets. As a result, variation in the quality of business feasibility evaluation sheets between bank employees is reduced.

[0071] 2. Variations The above embodiment may be modified as follows: The following modifications may be combined with each other.

[0072] 2-1. Business feasibility evaluation sheet The business feasibility evaluation sheet created in the above embodiment is an example of a document for evaluating the business feasibility of a business. Any document with a different name (for example, a business plan) may be created as long as it is used to evaluate the business feasibility of a business.

[0073] 2-2. First Reception Module 210 In the above embodiment, the first receiving module 210 receives input of a business name as information for identifying the target business (see step 503 in FIG. 5). However, the business name is merely one example of information for identifying the target business. Instead of the business name, the first receiving module 210 may receive other identification information such as a corporate number, a CIF (Customer Information File) number, a location, or a representative's name. The first receiving module 210 may then search the company information DB 221 to identify the business ID and industry ID corresponding to the received identification information.

[0074] 2-3. How to obtain input information In the above-described business support process 500, input information and a question are acquired for each input item. However, such an acquisition method is not necessarily required. As another acquisition method, input information, etc. may be acquired for each of multiple input items. For example, input information, etc. may be acquired for two input items, "Company Overview" and "Commercial Flow," at once. As another example, input information, etc. may be acquired for all input items at once. In this case, the first acquisition module 211 may include format information for the business feasibility evaluation sheet in the prompt and instruct the generation AI module 310 to output the business feasibility evaluation sheet according to the format information.

[0075] 2-4. Generative AI Module 310 In the above-described business support process 500, the second prompt includes model input information (see step 512 in FIG. 5). This enables the generation AI module 310 to identify missing information in the input information once generated. However, the method for identifying missing information is not limited to this. Another method is to fine-tune the generation AI module 310. Specifically, the generation AI module 310 is made to learn multiple pairs of input items and input information for those input items. This enables the generation AI module 310 to identify missing information in light of the learned input information.

[0076] 2-5. Revise the business feasibility assessment sheet In the above-described business support process 500, if there is missing information, the user modifies the business feasibility assessment sheet. However, such a modification method is not necessarily required. As an alternative modification method, the generation AI module 310 may modify the business feasibility assessment sheet.

[0077] In this case, the business support server 101 further includes a second receiving module 1901, a third acquisition module 1902, and a second output module 1903. Hereinafter, the business support server 101 including these modules will be referred to as the business support server 1900. FIG. 19 shows an example of the configuration of this business support server 1900.

[0078] A second reception module 1901 shown in the figure receives an answer to the output question from the user. The third acquisition module 1902 inputs the answer received by the second reception module 1901 into the generation AI to acquire input information with missing information supplemented. The generation AI referred to here specifically refers to the generation AI module 310, which will be described later. The second output module 1903 outputs the input information acquired by the third acquisition module 1902. Specifically, this module displays the acquired input information on the display of the user terminal 103.

[0079] Next, the operation of the business support server 1900 will be described. The operation to be described is business support processing 2000 that supports the creation of a business feasibility evaluation sheet. FIGS. 20 and 21 are flow diagrams showing an example of this processing. Processing 2000 shown in these figures is common to processing 500 shown in FIG. 5 in that it includes steps 501 to 516. Description of these steps will be omitted below.

[0080] In the business support process 2000, step 2001 is executed following step 516. In step 2001, the first output module 213 displays the generated business feasibility evaluation sheet and question sheet on the user terminal 103. At this time, the displayed question sheet has an answer input field for each question.

[0081] 22 shows an example of a question list 2200 relating to the input item "5-force analysis" from the displayed questionnaire sheet. The question list 2200 shown in the figure has an answer input field 2201 for each question.

[0082] The user uses the questions in this question list 2100 to obtain the missing information from the business. The user then enters the obtained information into the answer input field 2201. Hereinafter, the information entered into the answer input field 2201 and the corresponding question will be referred to as "additional information."

[0083] The user fills in the answer input fields 2201 for the other input items in the same manner. Then, the user selects a correction instruction button (not shown). This correction instruction button is a button for instructing correction of the business feasibility evaluation sheet. By selecting this button, the entered additional information is sent from the user terminal 103 to the business support server 1900, and the second reception module 1901 acquires the additional information (step 2002).

[0084] Next, the third acquisition module 1902 selects the input item to be processed from the input items of the business feasibility assessment sheet to be corrected (step 2003). Then, the module generates a prompt for the selected input item to be input to the generation AI module 310 (step 2004). The generated prompt includes the following information: (1) Input information for the input items to be processed, acquired in step 510 (2) Additional information about the input items to be processed (3) Model input information (4) A statement ordering the correction of the information entered in (1) based on the information entered in (3) and the additional information entered in (2).

[0085] The input information in (2) refers to one or more pieces of input information for the input items to be processed that have been previously output by the generation AI module 310. This input information is, for example, input information generated by a veteran bank employee using the generation AI module 310.

[0086] Next, the third acquisition module 1902 inputs the generated prompt to the generation AI module 310 (step 2005). The generation AI module 310 outputs an answer corresponding to the input prompt. The output answer (in other words, input information) is acquired by the third acquisition module 1902 (step 2006). The third acquisition module 1902 inputs the acquired input information into the corresponding input item field of the business feasibility assessment sheet (step 2007). At that time, the module replaces the old input information already entered in that field with the new input information.

[0087] Next, the third acquisition module 1902 determines whether all input items have been processed (step 2008). If the result of this determination is that all input items have not been processed (NO in step 2008), the module returns to step 2003 and selects the next input item. On the other hand, if the result of this determination is that all input items have been processed (YES in step 2008), the second output module 1903 displays the corrected business feasibility assessment sheet on the user terminal 103 (step 2009). The above is the explanation of the business support process 2000.

[0088] According to the business support process 2000 described above, the business feasibility evaluation sheet can be corrected by the generation AI module 310. This makes it possible to save the effort and time required for correction.

[0089] In the above process, the user manually inputs the additional information, but the method for inputting the additional information is not limited to this. As another input method, for example, an image of the additional information captured by a camera may be uploaded to the business support server 1900. As another method, audio data of the additional information may be uploaded to the business support server 1900.

[0090] Furthermore, in the above process, the user (i.e., the bank employee) inputs the additional information, but this additional information may also be input by the business operator. In this case, the business support server 1900 may display only the questionnaire on the user terminal 103 used by the business operator, and acquire the additional information from the business operator's terminal. This saves the bank employee the trouble of inputting the additional information.

[0091] 2-6. Conditions for outputting questions In the above-described business support process 500, the second prompt commands the output of a question (see step 512 in FIG. 5). At this time, the second acquisition module 212 may specifically specify the condition for outputting the question.

[0092] For example, the second acquisition module 212 may instruct the generation AI to output a specified question when the input information acquired by the first acquisition module 211 is information regarding the economic situation of the business operator and changes in that economic situation satisfy specified conditions.

[0093] In this case, the information relating to the business's economic situation is, for example, information input to the input item "financial summary." The predetermined condition of a change in economic circumstances is, for example, when the financial indicators (for example, sales) of the business operator have decreased by a predetermined value or a predetermined percentage or more compared to the previous year. The predetermined question is a question for obtaining information on the cause of the change in economic situation from the target business as missing information. Specifically, the generation AI is a generation AI module 310, which will be described later.

[0094] By outputting questions when a business's financial indicators deteriorate, the user is prompted to investigate the cause of the deterioration. The user can then use the information obtained from the business to revise the business feasibility assessment sheet.

[0095] 2-7. Number of times to enter prompts In the above-described business support process 500, two prompts are input for each input item to the generation AI module 310. The first prompt generates input information, and the second prompt generates a question to acquire missing information. However, inputting two prompts is not necessarily required; both the input information and the question may be generated using only one prompt.

[0096] In this case, the first acquisition module 211 instructs the generation AI to output a question for acquiring, from the specified business, information that is missing when generating input information for input items in a document for evaluating the business viability of the specified business via the first reception module 210. Then, the module acquires the question output from the generation AI. The specific operation of this first acquisition module 211 will be described below.

[0097] Fig. 23 is a flow diagram showing an example of a business support process 2300 according to this modification. The process 2300 shown in Fig. 23 is common to the process 500 shown in Fig. 5 in that it includes steps 501 to 507. A description of these steps will be omitted below.

[0098] In the business support process 2300, step 2301 is executed following step 507. In step 2301, the first acquisition module 211 generates a prompt to be input to the generation AI module 310. The generated prompt includes the following information: (1) The website address of the business operator obtained in step 503 (2) Detailed items that make up the input items to be processed (3) Reference information obtained in step 507 (4) A statement instructing the business operator specified by the website address in (1) to output the input information corresponding to the detailed items in (2) by referring to the reference information in (3). (5) Model input information (6) A statement that commands the output of questions to obtain from the target business entity any information that is missing in the input information output in accordance with the command in (4) in light of the input information in (5).

[0099] The detailed items in (2) are, for example, the company name, representative, industry, business details, base, number of employees, business history, and history in the case of the input item "Company Overview" (see Figure 7). The input information (5) is one or more pieces of input information for the input items to be processed that have been previously output by the generation AI module 310. This input information is, for example, input information generated by a veteran bank employee using the generation AI module 310.

[0100] Next, the first acquisition module 211 inputs the generated prompt to the generation AI module 310 (step 2302). The generation AI module 310 outputs an answer corresponding to the input prompt. The output answer (in other words, the input information and question) is acquired by the first acquisition module 211 (step 2303). The first acquisition module 211 inputs the acquired input information into the corresponding input item field of the business feasibility assessment sheet (step 2304). Furthermore, if the acquired answer includes a question, the module inputs the question into the corresponding input item field of the question sheet (step 2305).

[0101] Next, the first acquisition module 211 determines whether all input items have been processed (step 2306). If the result of this determination is that all input items have not been processed (NO in step 2306), the module returns to step 505 and selects the next input item. On the other hand, if the result of this determination is that all input items have been processed (YES in step 2306), the first output module 213 displays the generated business feasibility assessment sheet and questionnaire sheet on the user terminal 103 (step 2307). This concludes the explanation of the business support process 2300.

[0102] The above-described process also allows the creation of a business feasibility assessment sheet and a questionnaire sheet.

[0103] 2-8. Creator of the business feasibility evaluation sheet In the above embodiment, a bank employee is assumed to be the creator of the business feasibility assessment sheet. However, a bank employee is merely one example of a creator. The business feasibility assessment sheet may also be created by another creator, for example, a business operator.

[0104] 2-9. Types of reference information In the above-described business support process 500, information on the target business is acquired as reference information (see step 507 in FIG. 5). The acquired reference information may include information on the business of the business (in other words, business data).

[0105] In this case, the business support server 101 further includes a business information DB. This business information DB is a database that stores information about the business of each business. The information stored in this DB includes information about the attendance of employees employed by the business. The business information of each business is stored in association with the business ID.

[0106] 5, the first acquisition module 211 acquires business data of the target business entity from the business information DB in the subsequent step 507. The first acquisition module 211 then instructs the generation AI module 310 to output input information for the input items based on the acquired business data.

[0107] 2-10. How to select reference information In the above-described business support process 500, the DB from which reference information is obtained is identified by referring to the input item table 228 (see step 506 in FIG. 5). In other words, the DB from which reference information is obtained is changed for each input item. However, this change in DB is not necessarily required. In another embodiment, reference information may be obtained from the same DB for all input items. Even in this embodiment, a business feasibility evaluation sheet can be created.

[0108] 2-11. Example input information In the above-described business support process 500, model input information is included in the second prompt (see step 512 in FIG. 5). This model input information may be changed according to the attributes of the target business. For example, it may be changed according to the industry of the target business. In that case, the selected input information is input information that has been previously output for a business in the same industry as the target business. As another example, it may be changed according to the scale of the target business. In that case, the selected input information is input information that has been previously output for a business of the same size as the target business. By making the model input information variable in this way, the accuracy of the answer output from the generation AI module 310 is improved.

[0109] 2-12. Management of business feasibility evaluation sheets In the above embodiment, a business feasibility evaluation sheet is created, but when the information on the created business feasibility evaluation sheet becomes outdated, an alert may be output to the user, so that the user can notice that the information on the business feasibility evaluation sheet has become outdated.

[0110] Specifically, the business support server 101 records the creation date of the financial statement data used as reference when creating the business feasibility evaluation sheet along with the created business feasibility evaluation sheet. The server then outputs an alert to the user when a predetermined period of time has passed since the creation date. This allows the user to realize that the information on the business feasibility evaluation sheet they created has become outdated.

[0111] 2-13.Functional layout In the above embodiment, the business support process 500 is executed by two servers, the business support server 101 and the LLM server 102. However, this functional arrangement is merely an example. The functions of each server may be arranged as appropriate depending on the execution environment of the business support process 500. For example, some or all of the functions of the LLM server 102 may be provided in the business support server 101.

[0112] 2-14. System Components Each device constituting the information processing system 100 may be, for example, a portable terminal (mobile terminal) such as a smartphone, tablet, mobile phone, or personal digital assistant (PDA), or may be a wearable terminal such as glasses, a wristwatch, or clothing. Each device may also be a stationary or portable computer, or a server located on the cloud or a network. Each device may also function as a VR (Virtual Reality) terminal, an AR (Augmented Reality) terminal, or an MR (Mixed Reality) terminal. Alternatively, a combination of multiple of these terminals may be used. For example, a combination of one smartphone and one wearable terminal may logically function as a single terminal. Other information processing terminals may also be used.

[0113] 2-15.Other The present invention is not limited to the above-described embodiments and includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, or to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to add, delete, or replace part of the configuration of each embodiment with other configurations.

[0114] Furthermore, the above-described configurations, functions, processing units, processing means, etc. may be partially or entirely implemented in hardware, for example, by designing them as integrated circuits. The above-described configurations, functions, etc. may also be implemented in software, with a processor interpreting and executing a program that implements each function. Information such as the programs, tables, and files that implement each function can be stored in a memory, a recording device such as a hard disk or SSD (Solid State Drive), or a recording medium such as an IC card, SD card, or DVD.

[0115] In addition, the control lines and information lines shown are those that are considered necessary for the explanation, and do not necessarily show all the control lines and information lines in the product. In reality, it can be assumed that almost all components are interconnected. The above-described embodiments disclose at least the configurations described in the claims. [Explanation of symbols]

[0116] 100...information processing system, 101...business support server, 102...LLM server, 103...user terminal

Claims

1. An information processing system that supports the creation of documents for evaluating the business viability of a business operator, a first receiving means for receiving a designation of a business operator; A first acquisition means for instructing a generation AI to output input information for input items in a document for evaluating the business viability of the specified business and acquiring the output input information; A second acquisition means for instructing the generation AI to output a question for acquiring missing information from the specified business operator regarding the acquired input information, and acquiring the output question; a first output means for outputting the acquired question sentence; An information processing system comprising:

2. The second acquisition means instructs the generation AI to identify the missing information based on input information for the input items previously output by the generation AI. The information processing system according to claim 1 .

3. The generation AI is a language model that has learned a plurality of pairs of the input items and input information for the input items in order to identify the missing information. The information processing system according to claim 1 .

4. a second receiving means for further receiving an answer to the question; a third acquisition means for inputting the answer to the generating AI and acquiring another input information in which the missing information is supplemented; a second output means for outputting the acquired other input information; The information processing system of claim 1 , further comprising:

5. The first acquisition means instructs the generation AI to output input information for the input items for the specified business operator based on at least one of accounting information and financial statement data of the specified business operator. The information processing system according to claim 1 .

6. The input items are any of company overview, distribution channel, market, 3C analysis, 5 forces analysis, SWOT analysis, management structure, financial summary, management issues, and management measures. The information processing system according to claim 1 .

7. The second acquisition means instructs the generation AI to output a question to acquire, as the missing information, information on the cause of the change from the designated business operator when the acquired input information is information on the economic situation of the designated business operator and a change in the economic situation satisfies a predetermined condition. The information processing system according to claim 1 .

8. An information processing method executed by a computer to support the creation of a document for evaluating the business viability of a business, comprising: accepting the designation of the business; A step of instructing a generation AI to output input information for input items in a document for evaluating the business viability of the specified business operator, and acquiring the output input information; Instructing the generation AI to output a question for acquiring missing information from the specified business operator for the acquired input information, and acquiring the output question; outputting the acquired question sentence; An information processing method including:

9. A program that supports the creation of documents for evaluating the business feasibility of a business operator, On the computer, accepting the designation of the business; A step of instructing a generation AI to output input information for input items in a document for evaluating the business viability of the specified business operator, and acquiring the output input information; Instructing the generation AI to output a question for acquiring missing information from the specified business operator for the acquired input information, and acquiring the output question; outputting the acquired question sentence; A program to execute.

10. An information processing system that supports the creation of documents for evaluating the business viability of a business operator, A receiving means for receiving the designation of the business operator; An acquisition means for instructing a generation AI to output a question sentence for acquiring missing information from the designated business when generating input information for an input item of a document for evaluating the business viability of the designated business, and acquiring the output question sentence; an output means for outputting the acquired question sentence; An information processing system comprising:

Images