Loan examination device, loan examination method, and loan examination program

Abstract

To reduce a burden on an operator due to loan screening.SOLUTION: A detection unit refers, on the basis of a type of loan included in a loan screening request, to a storage unit to detect a screening pattern corresponding to the type of the loan, the storage unit storing a plurality of screening patterns corresponding to types of loans, including programs for causing a computer to execute jobs related to loan screening, and settings as to whether each of the jobs is to be executed. A job execution unit executes a program for a job set to be executed, out of the jobs in the detected screening pattern corresponding to the type of the loan, to execute screening on the loan corresponding to the loan screening request. Accordingly, loan screening corresponding to the type of the loan can be automatically executed, thereby reducing a burden on an operator due to the loan screening.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present invention relates to a loan examination device, a loan examination method, and a loan examination program. [Background technology]

[0002] Nowadays, when a financial institution provides a loan, it is necessary to examine whether the loan applicant is a person who can be granted a loan without any problems. As a prior art related to such loans, Patent Document 1 (JP 2022-145702 A) discloses a loan intermediation system that acts as an intermediary between a loan applicant and a financial institution.

[0003] This loan intermediation system is composed of an intermediary server equipped with a loan application acceptance unit, a financial institution information storage unit, a financial institution selection unit, an application information display unit, an offer selection acceptance unit, and a notification unit. The loan application acceptance unit accepts application information, including attribute information and loan request information, from loan applicants. The financial institution information storage unit stores plan information regarding loan plans for each financial institution.

[0004] The financial institution selection unit generates a list of financial institutions that will provide application information from the application information and plan information, and the application information display unit displays a list of multiple application information on the financial institution's terminal along with score information based on the borrower's attribute information.The offer selection reception unit receives from the financial institution a selection of application information for which an offer will be made, as well as a selection of plan information.The notification unit then notifies the borrower of the financial institution information and plan information upon receiving the offer selection.This makes it possible to provide a loan intermediation system that is highly convenient not only for borrowers but also for financial institutions. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Publication No. 2022-145702 Summary of the Invention [Problem to be solved by the invention]

[0006] However, in the past, when providing a loan, the business operator had to manually conduct a complex screening process based on the financial institution's own criteria, including checking the amount of loans taken out by other companies and past overdue payments, to determine whether the loan would be possible. This resulted in a problem of placing a heavy burden on the business operator.

[0007] The present invention has been made in consideration of the above-mentioned problems, and aims to provide a loan examination device, a loan examination method, and a loan examination program that can reduce the burden placed on business operators due to loan examinations. [Means for solving the problem]

[0008] In order to solve the above-mentioned problems and achieve the objectives, the loan screening device of the present invention has a detection unit that detects the screening pattern corresponding to the loan type by referring to a memory unit in which a program for causing a computer to execute multiple jobs related to loan screening, which are multiple screening patterns corresponding to each loan type based on the loan type included in the loan screening request, and screening patterns that are set to be executed or not executed for each job, and a job execution unit that executes the loan screening corresponding to the loan screening request by executing the program of the job that is set to be executed among the jobs of the screening pattern corresponding to the detected loan type.

[0009] In addition, in order to solve the above-mentioned problems and achieve the object, the loan screening method of the present invention includes a detection step in which a detection unit detects a screening pattern corresponding to a loan type based on the loan type included in the loan screening request, by referring to a memory unit in which a program for causing a computer to execute each of a plurality of jobs related to the loan screening and a screening pattern in which execution or non-execution is set for each job are stored, and a job execution step in which a job execution unit executes a program for a job in the screening pattern corresponding to the detected loan type that is set to be executed, thereby executing a loan screening corresponding to the loan screening request.

[0010] In addition, in order to solve the above-mentioned problems and achieve the objective, the loan screening program of the present invention causes a computer to function as a job execution unit that executes a loan screening corresponding to a loan screening request by referring to a memory unit in which a program for causing the computer to execute multiple jobs related to the loan screening, each of which is a multiple screening pattern corresponding to each loan type based on the type of loan included in the loan screening request, and a detection unit that detects the screening pattern corresponding to the loan type by referring to a memory unit in which screening patterns that are set to be executed or not executed for each job are stored, and by executing the program of the job that is set to be executed among the jobs of the screening pattern corresponding to the detected loan type. [Effects of the Invention]

[0011] The present invention can reduce the burden placed on business operators due to loan screening. [Brief explanation of the drawings]

[0012] [Figure 1] FIG. 1 is a block diagram showing the hardware configuration of a loan examination device according to an embodiment. [Figure 2] FIG. 2 is a diagram showing an example of the automatic examination pattern classification master. [Figure 3] FIG. 3 is a diagram illustrating an example of the automatic examination target master. [Figure 4]FIG. 4 is a diagram illustrating an example of the automatic examination job master. [Figure 5] FIG. 5 is a flowchart showing the flow of loan examination operations in the loan examination device according to the embodiment. [Figure 6] FIG. 6 is a diagram illustrating an example of the cooperation management data. [Figure 7] FIG. 7 is a diagram illustrating an example of the case status data. [Figure 8] FIG. 8 is a diagram showing an example of cooperation management data corresponding to each job of the first examination pattern. [Figure 9] FIG. 9 is a diagram showing an example of case status data in a state where the case status has changed from "received" to "automatic review in progress" as a result of the start of review. [Figure 10] FIG. 10 is a diagram showing the collaboration management data in which the status classification of the optional examination execution job has been changed from "unprocessed" to "in progress." [Figure 11] FIG. 11 is a diagram showing cooperation management data in which the status category of the job subsequent to the job in which the error occurred is assigned the status category of "not executed." [Figure 12] FIG. 12 is a diagram showing how the status classification of the cooperation management data for the automatic circuit determination job is changed from "unprocessed" to "in progress" and the automatic circuit determination job is started. [Figure 13] FIG. 13 is a diagram showing the examination result data generated by executing a job. [Figure 14] FIG. 14 is a diagram showing the cooperation management data in which the status category has been updated to "executed (normal)" as a result of the job being executed normally. [Figure 15] Figure 15 shows collaboration management data in which "Not executed" is entered as the status classification for each job for automatic approval and external system collaboration when it is determined that automatic execution of each job for automatic approval and external system collaboration subsequent to the job for automatic circuit determination is not possible. [Figure 16] FIG. 16 is a diagram showing the case status data in which the case status has been updated to "automatic review manual response determination" because subsequent processing is not automatically executed. [Figure 17] FIG. 17 shows the cooperation management data in which the records of each job are rearranged in order of update date for display on the screen. [Figure 18] FIG. 18 is a diagram showing an example of a job execution status list screen displayed based on the cooperation management data sorted in order of update date. [Figure 19] FIG. 19 is a diagram showing an example in which a new examination pattern is added to the automatic examination pattern classification master. [Figure 20] FIG. 20 is a diagram showing the automatic examination target master in which each job corresponding to the newly added examination pattern and execution or non-execution is set at the top of each job. DETAILED DESCRIPTION OF THE INVENTION

[0013] A loan examination device according to an embodiment of the present invention will be described in detail below with reference to the accompanying drawings, although the present invention is not limited to the following embodiment.

[0014] (Hardware configuration) As shown in Figure 1, the loan screening device 1 of the embodiment includes a memory unit 2, a control unit 3, a communication interface unit 4, and an input / output interface unit 5. An input device 6 and an output device 7 are connected to the input / output interface unit 5. The output device 7 corresponds to a display unit of a monitor device (including a home television), a printer, a speaker device, etc. The input device 6 can be a keyboard device, a mouse device, a microphone device, etc., as well as a monitor device that cooperates with a mouse device to realize a pointing device function.

[0015] The communication interface unit 4 is connected to a network 35, which may be a wide area network such as the Internet or a private network such as a local area network (LAN). Connected to this network 35 is a client terminal device 31 of an external system that requests a loan examination from the loan examination device 1. This allows the loan examination device 1 to link with the external system (client terminal device 31) via the network 35.

[0016] The storage unit 2 may be, for example, a storage device such as a ROM (Read Only Memory), a RAM (Random Access Memory), an HDD (Hard Disk Drive), or an SSD (Solid State Drive). The storage unit 2 stores a loan examination program for automatically examining a loan requested by the client terminal device 31. This loan examination program includes a job program for each job included in an examination pattern set according to the service (type of loan).

[0017] The job program also stores an individual calculation processing program, a personal credit inquiry program, a loan detail confirmation program, a discretionary screening execution program, an automatic response determination program, an automatic approval program, and an external system linkage program, which correspond to jobs for automatic loan screening. The control unit 3 executes these programs to perform automatic loan screening.

[0018] The storage unit 2 also stores an automatic screening pattern classification master 11, an automatic screening target master 12, and an automatic screening job master 13. The storage unit 2 also stores collaboration management data and case status data that are generated by executing each screening job.

[0019] Desired screening patterns for various services (types of loans) are set in the automatic screening pattern classification master 11. That is, the automatic screening pattern classification master 11 stores the screening category, request type, request category, service, use of funds, and target pattern number of the screening pattern in association with each other, as shown in Figure 2.

[0020] The screening category is a category that indicates the type of loan screening, such as "1: Preliminary screening" or "2: Main screening." The request type is the type of request, such as "1: New," "2: Change of conditions," or "3: Credit renewal." The request category is the category of request, such as "1: Request," "2: Cancel request," or "3: Add additional documents." The service indicates the type of loan, such as "Home loan (general type)," "Card loan," "My car loan (general type A)," or "Multipurpose loan (general type A)." The use of funds indicates the use of the loaned money, such as "Housing," "Education," "Car," or "Other."

[0021] The target pattern number of the screening pattern is the number of the screening pattern set for each service. In this example, the screening patterns are Pattern 1 to Pattern 4, with Pattern 1 set for the "Home Loan (General Type)," Pattern 2 set for the "Card Loan," Pattern 3 set for the "Car Loan (General Type A)," and Pattern 4 set for the "Multipurpose Loan (General Type A)." Each pattern includes screening jobs executed by the individual calculation processing program, personal credit inquiry program, loan detail confirmation program, discretionary screening execution program, automatic response determination program, automatic approval program, and external system linkage program, as described below. In addition, by setting an "execution category" of execution or non-execution for each job, it is possible to create a desired job configuration for a desired screening pattern.

[0022] As shown in Figure 3, the automatic screening target master 12 stores the target pattern number, job number, job name, execution category, and execution order of each screening pattern, each associated with the other. Of these, the "job name" is not used by the program, but a box is provided to make it easier to understand during setup. Specifically, the job with job number "1" is given the job name "Individual Calculation Processing," and the job with job number "2" is given the job name "Individual Credit Inquiry." Furthermore, the job with job number "3" is given the job name "Loan Detail Confirmation," and the job with job number "4" is given the job name "Optional Screening Execution." Furthermore, the job with job number "5" is given the job name "Automatic Response Determination," and the job with job number "6" is given the job name "Automatic Approval." Furthermore, the job with job number "7" is given the job name "External System Linkage."

[0023] The execution category indicates whether or not the job is to be executed. In the loan examination device 1 of the embodiment, by setting this execution category for each job, it is possible to set the desired job configuration for the desired examination pattern. That is, in the example of Figure 3, "1: Execute" is set for all jobs of the first pattern: "Individual calculation processing," "Individual credit inquiry," "Loan detail confirmation," "Optional examination execution," "Automatic response determination," "Automatic approval," and "External system linkage."

[0024] Similarly, in the example of Figure 3, "2: Do not execute" is set for all jobs in the second pattern: "Individual calculation processing," "Individual credit inquiry," "Loan details confirmation," "Optional review execution," "Automatic response determination," "Automatic approval," and "External system integration."

[0025] It is also possible to set some jobs to be executed, and for the third pattern, "2: Do not execute" is set for "Individual calculation processing," "Individual credit inquiry," "Loan detail confirmation," "Optional screening execution," and "Automatic response judgment," and "1: Execute" is set for the "Automatic approval" and "External system linkage" jobs. In this case, only the "Automatic approval" and "External system linkage" jobs will be executed.

[0026] Similarly, for the fourth pattern, "1: Execute" is set for "Individual calculation process," "Individual credit inquiry," "Loan detail confirmation," "Optional screening execution," and "Automatic response determination," and "2: Do not execute" is set for the jobs "Automatic approval" and "External system linkage." In this case, the jobs "Individual calculation process," "Individual credit inquiry," "Loan detail confirmation," "Optional screening execution," and "Automatic response determination" are executed.

[0027] The execution order indicates the order in which each job is executed. In the example in Figure 3, the execution order of "Individual Calculation Process" is set to "1," the execution order of "Individual Credit Inquiry" is set to "2," the execution order of "Loan Detail Check" is set to "3," the execution order of "Optional Screening Execution" is set to "4," the execution order of "Automatic Response Determination" is set to "5," the execution order of "Automatic Approval" is set to "6," and the execution order of "External System Linkage" is set to "7." Therefore, each job is executed in the following order: "Individual Calculation Process" → "Individual Credit Inquiry" → "Loan Detail Check" → "Optional Screening Execution" → "Automatic Response Determination" → "Automatic Approval" → "External System Linkage."

[0028] In the example of Fig. 3, the execution order of "individual calculation process" is set to "1st" in the first to fourth patterns, and the execution order of "personal mail inquiry" is set to "2nd" in the first to fourth patterns, and so on, so that the execution order of each job is set to the same in the first to fourth patterns. However, in the first pattern, it is also possible to set a desired execution order for a desired job, such as setting the execution order of "individual calculation process" to "5th" and the execution order of "personal mail inquiry" to "1st."

[0029] The automatic screening job master 13 is a master that associates the internal processing numbers assigned separately within the program with the job numbers of jobs used in automatic screening, and stores the job numbers, job names, and linked internal processing codes in association with each other, as shown in Figure 4. In this example, the linked internal processing code "110" is set for the "individual calculation processing" job with job number "1," and the linked internal processing code "120" is set for the "individual mail inquiry" job with job number "2."

[0030] (Functional configuration of the loan screening device) Next, the control unit 3 executes the loan screening program stored in the memory unit 2, and thereby functions as a data generation unit 21, a detection unit 22, an acquisition unit 23, a job execution unit 24, a display control unit 25, a memory control unit 26, and a communication control unit 27, as shown in Figure 1.

[0031] The data generation unit 21 generates linkage management data including the examination category, request type, request classification, service (type of loan), and use of funds based on the loan examination request received from the client terminal device 31.

[0032] The detection unit 22 detects the pattern number of the screening pattern corresponding to the service (type of loan) for which screening has been requested by referring to the automatic screening pattern classification master 11, which is an example of a storage unit. The acquisition unit 23 acquires the job number, execution order, and execution classification (executed or not executed) of each job of the screening pattern of the detected pattern number by referring to the automatic screening target master 12.

[0033] The job execution unit 24 automatically reviews the loan corresponding to the loan review request by executing the program of the job (individual calculation processing, personal credit inquiry, etc.) that has the execution category set to "execute" from among the jobs of the review pattern corresponding to the detected type of loan.

[0034] Furthermore, the data generation unit 21 generates, for each job of the examination pattern, cooperation management data including at least a status class indicating that the job has been executed normally, a status class indicating that an error has occurred during execution of the job, and a status class indicating that the job has not been executed. The display control unit 25 displays a list of the status classes of each job via the output device 7 (an example of a display unit) based on the generated cooperation management data.

[0035] Furthermore, each time a job is executed, the data generation unit 21 generates review result data including manual flag information indicating that the job was executed normally or manual flag information indicating that a manual review is required due to an error occurring during execution. When the data generation unit 21 generates manual flag information indicating that a manual review is required due to an error occurring during execution, the data generation unit 21 generates cooperation management data in which the status category of the job in which the error occurred during execution is set to a status category indicating that an "error" occurred during execution of this job, and the status category of one or more jobs scheduled to be executed after the job in which the error occurred during execution is set to a status category of "not executed."

[0036] The memory control unit 26 controls and stores the screening pattern specified when adding a loan type, each job corresponding to the specified screening pattern, and the execution category indicating whether each job is executed or not in the automatic screening target master 12 as the screening pattern and job of the loan type being added.

[0037] The communication control unit 27 receives an examination request from the client terminal device 31, and communicates with external systems, such as returning examination results.

[0038] (Loan screening operation) Next, the loan examination operation in the loan examination device 1 having such a configuration will be explained using the flowchart in Fig. 5. In the flowchart in Fig. 5, processing starts when a loan examination request is received from the client terminal device 31 of the external system shown in Fig. 1, and processing is executed in order from step S1.

[0039] In step S1, the data generation unit 21 generates the linkage management data illustrated in Fig. 6 based on the review request data received from the client terminal device 31 of the external system. As shown in Fig. 6, the linkage management data includes the creation date and time, internal identification number (internal ID), update date and time, linkage internal processing code, status classification, message, case number, review classification, request type, request classification, service (type of loan), use of funds, and automatic review processing identification number (automatic review processing ID).

[0040] In other words, the loan review request received from the requester terminal device 31 includes the review category such as "1: Preliminary review" or "2: Main review" as explained using Figure 2, the request type such as "1: New", "2: Change of conditions", or "3: Credit renewal", the request category such as "1: Request", "2: Cancel request", or "3: Add additional documents", the service (type of loan) such as "Home loan (general type)", "Card loan", "Personal car loan (general type A)", or "Multipurpose loan (general type A)", and various information indicating the use of funds such as "Housing", "Education", "Car", or "Other".

[0041] The data generation unit 21 generates the linkage management data by inputting the information on the screening category, request type, request category, service, and use of funds contained in the received loan screening request into the respective columns of the screening category, request type, request category, service, and use of funds of the linkage management data. The example in Figure 6 is an example in which "1: Pre-screening" is input into the screening category column of the linkage management data, "1: New" is input into the request type column, "1: Request" is input into the request category column, "Mortgage loan (general type)" is input into the service column, and "Housing" is input into the use of funds column.

[0042] In addition, since automatic loan review has not been performed at the stage when the data generation unit 21 receives the loan review request, it enters "0: Unprocessed" in the status classification column of the linked management data and "Automatic review judgment" in the linked internal processing code column.

[0043] Furthermore, the data generation unit 21 generates case status data including a case status and an examination category, using the same case number as the case number in the linkage management data, as shown in Figure 7. This case status data is data indicating the current status of the case, such as "received" or "automatic examination in progress." Since automatic examination of the loan has not yet begun at the stage when this loan examination request is received, the data generation unit 21 enters "31: received" in the case status field and "1: preliminary examination" in the examination category field.

[0044] Next, in step S2 of the flowchart in Figure 5, the detection unit 22 detects from the automatic screening pattern classification master 11 the target pattern number of the screening pattern corresponding to the screening category, request type, request category, service, and use of funds of the collaboration management data generated by the data generation unit 21.

[0045] As a result, if the target pattern number of the screening pattern corresponding to the screening category, request type, request classification, service and use of funds of the linked management data generated by the data generation unit 21 is stored in the automatic screening pattern classification master 11, it can be determined that the loan screening request is a screening request that is subject to automatic screening.Furthermore, if the target pattern number of the screening pattern corresponding to the screening category, request type, request classification, service and use of funds of the linked management data generated by the data generation unit 21 is not stored in the automatic screening pattern classification master 11, it can be determined that the loan screening request is a screening request that is not subject to automatic screening, or a screening pattern that is not registered in the automatic screening pattern classification master 11 (automatic screening judgment).

[0046] In step S3, the acquisition unit 23 refers to the automatic inspection target master 12 shown in Fig. 3 based on the target pattern number detected by the detection unit 22, and acquires the job number, execution category, and execution order of each job corresponding to the target pattern number. The acquisition unit 23 also refers to the automatic inspection job master 13 shown in Fig. 4 and acquires the coordination internal processing code corresponding to each job number (master acquisition). The data generation unit 21 generates coordination management data for each job corresponding to the target pattern number, as shown in Fig. 8.

[0047] The example in Fig. 8 is an example of the linkage management data for each job whose target pattern number is the first pattern. In the case of the first pattern, the screening pattern executes the following jobs in the order of job number: "Individual calculation processing," "Individual credit inquiry," "Loan detail confirmation," "Optional screening execution," "Automatic response determination," "Automatic approval," and "External system linkage." As an image, the data generation unit 21 generates linkage management data for each job of the detected target pattern number by arranging the records of each job in the order of columns as shown in Fig. 8.

[0048] At this stage, since the execution of each job has not yet started the automatic loan screening, the data generation unit 21 inputs "0: Unprocessed" for the status classification of each job.

[0049] 9(a) and 9(b), the data generation unit 21 changes the case status of the case status data from "31: Accepted" to "101: Automatic review in progress." This starts the automatic review of the loan.

[0050] Next, in step S4, the job execution unit 24 determines whether the number of subjects of the review to be automatically performed is "0". As described above, if the target pattern number of the review pattern corresponding to the review category, request type, request classification, service, and use of funds of the collaboration management data generated by the data generation unit 21 is not stored in the automatic review pattern classification master 11, and if it is not registered in the automatic review pattern classification master 11, it is determined that the loan review request is an review request that is not subject to automatic review. In this case, the job execution unit 24 determines that the number of subjects of the review to be automatically performed is "0" (step S4: Yes), and immediately terminates the processing of the flowchart in Figure 5. In this case, if a loan review is required, the business operator will perform the review manually.

[0051] On the other hand, in step S4, if the job execution unit 24 determines that the number of items to be automatically examined is not "0" (step S4: No), the processes of steps S5 to S7 are repeatedly executed for each job.

[0052] Specifically, in step S5, the job execution unit 24 executes jobs in order, starting with "individual calculation processing," which is the job with job number "1" in the collaboration management data shown in Fig. 8. The programs for each job are stored in the job program of the loan examination program, as shown in Fig. 1. The job execution unit 24 executes each job based on these programs.

[0053] When the job execution unit 24 executes a job, the data generation unit 21 updates the update date and time of the cooperation management data to the date and time of the job execution, as shown in Figures 10(a) and 10(b). The data generation unit 21 also updates the status classification of the cooperation management data from "0: Unprocessed" to "1: In Progress".

[0054] In this way, the job execution unit 24 executes each job in the execution order, but an error such as data fraud or a business error may occur during execution. In this case, in step S6, the job execution unit 24 determines that automatic execution of the screening cannot be continued (step S6: No). In this case, the processing of the flowchart in FIG. 5 ends, and the screening corresponding to the subsequent job is manually executed by the business operator.

[0055] Furthermore, when an error occurs during the execution of a job in this manner, the data generation unit 21 sets the status category of the job in which the error occurred among the jobs in the cooperation management data to "Executed (Error)" and sets the status category of the job subsequent to the job in which the error occurred to "Executed (Not Executed)," as shown in Figures 11(a) and 11(b). This status category of "Executed (Error)" means that the screening of the screening pattern has been executed, but an error has occurred in a job marked with "Executed (Error)" among the jobs in the screening pattern. Also, the status category of "Executed (Not Executed)" means that the screening of the screening pattern has been executed, but a job marked with "Executed (Not Executed)" among the jobs in the screening pattern has not been executed.

[0056] The example in Figure 11(b) is an example in which, when each job of the first pattern was executed, an error occurred during the execution of the "Optional Review Execution" job, so "Executed (Error)" was entered in the status category of the "Optional Review Execution" job. Also, the example in Figure 11(b) is an example in which, when each job of the first pattern was executed, an error occurred during the execution of the "Optional Review Execution" job, so "Executed (Not Executed)" was entered in the status category of the "Automatic Response Determination," "Automatic Approval," and "External System Linkage" jobs that follow the "Optional Review Execution" job.

[0057] In this case, the business operator will have to manually execute the "Optional Review Execution" job in which the error occurred, as well as the remaining subsequent jobs, "Automatic Response Determination," "Automatic Approval," and "External System Integration."

[0058] Next, if no error occurs when the job is executed, the job can be automatically executed (step S6: Yes), and the process proceeds to step S7. In step S7, the job execution unit 24 determines whether there is a next job to execute. In FIG. 11(a), for example, if the job "execute optional review" is completed without any error, the job "automatic response determination" exists after this job "execute optional review" (step S7: Yes). Therefore, the job execution unit 24 returns the process to step S5 and continues to execute the job "automatic response determination".

[0059] 11(a), for example, when the "External System Linkage" job is completed, all jobs for that screening pattern are completed, and no subsequent jobs exist. In this case (Step S7: No), the loop process of Steps S5 to S7 ends, and the process of the flowchart in FIG. 5 also ends.

[0060] (Automatic answer judgment operation) Next, the operation of the "automatic response determination" job will be described. When the automatic response determination job starts, the data generation unit 21 updates the status classification of the cooperation management data for the automatic response determination job from "0: unprocessed" to "1: in progress" as shown in Figures 12(a) and 12(b).

[0061] When the automatic review of each job is executed, the review result data shown in Figure 13 is generated for each job. This review result data is the review result data for the "Execute optional review" job, and is composed of the case number, review category number, optional review confirmation date and time, optional review finalizer ID, optional review finalizer name, optional review judgment result, optional review supplementary conditions, and optional review manual flag. Of these, the optional review manual flag is information that indicates whether the "Execute optional review" job was performed manually (True) or not (False). In other words, if the "Execute optional review" job is executed without an error, the optional review manual flag is "False," and if an error occurs in the "Execute optional review" job and the subsequent review is performed manually, the optional review manual flag is "True."

[0062] If the manual optional review flag of this review result data is "False," it means that the "Optional Review Execution" job was executed normally. Therefore, if the "Automatic Response Determination" job determines that the subsequent "Automatic Approval" and "External System Linkage" jobs can also be automatically executed, the data generation unit 21 updates the status classification of the linkage management data for the "Automatic Response Determination" job from "1: In Progress" to "99: Executed (Normal)," as shown in FIG. 14.

[0063] In contrast, when the manual optional review flag in the review result data is "True," it means that an error occurred during the execution of the "Perform optional review" job, and the subsequent review was performed manually by the business operator, and that the "Automatic approval" and "External system collaboration" jobs that follow the "Automatic response determination" job are performed manually. Therefore, as shown in Figures 15(a) and 15(b), the data generation unit 21 updates the status classification of the collaboration management data for the "Automatic response determination" job to "99: Executed (Normal)," and updates the status classification of the collaboration management data for the "Automatic approval" and "External system collaboration" jobs that follow the "Automatic response determination" job to "97: Executed (Not yet executed)."

[0064] In addition, since the jobs "automatic approval" and "external system integration" that follow the job "automatic response determination" are not automatically executed, the data generation unit 21 generates case status data that updates the case status from "101: automatic review in progress" to "103: automatic review manual response determination," as shown in Figures 16(a) and 16(b).

[0065] (Displays a list of the status of each job) Next, the loan examination device 1 of the embodiment is capable of displaying a list of the execution status (status classification) of each job based on the linkage management data of each job shown in Fig. 17. That is, when the business operator specifies a list display of the execution status (status classification) of each job via the input device 6, the display control unit 25 displays the job execution status list screen shown in Fig. 18 via the output device 7. This job execution status list screen includes an input field for the desired update date and time, a selection field for the linkage internal processing code (internal processing name), a selection field for the status classification to be displayed, and an input field for the case number.

[0066] The business operator inputs the desired update date and time and case number into each of these fields via the input device 6, and selects the linkage internal processing code (internal processing name) and status classification. As a result, the data generation unit 21 generates linkage management data in which the records of each job corresponding to the input and selection by the business operator are arranged in order of update date and time, as shown in Fig. 17. Based on this linkage management data, the display control unit 25 displays the linkage management data for each job in the detail display field of the job execution status list screen, as shown in Fig. 18, with the records arranged in order of update date and time. This allows the business operator to recognize at a glance the current execution status of each job of each screening pattern.

[0067] For example, the "Status" of the top record shown in FIG. 18 is "In Progress." Therefore, in the screening of this screening pattern, it can be seen that the "Loan Detail Confirmation" job is currently "In Progress." Furthermore, the data generation unit 21 adds a message, such as "Failed to calculate ~," to the collaboration management data of the job in which the error occurred. As shown in FIG. 18, the display control unit 21 displays "Executed (Error)" in the "Status" column of the job in which the error occurred, and also displays the message, such as "Failed to calculate ~," that was added to the collaboration management data in the "Message" column. This allows the business operator to recognize that an error has occurred in the job and manually execute the subsequent job.

[0068] (Additional setting of review pattern) Next, we will explain the operation of the loan examination device when a new examination pattern is added by a business operator. In this case, the business operator inputs the examination category, request type, request classification, service, and use of funds of the newly added examination pattern into the examination pattern addition screen (not shown), and also specifies the target pattern number of the examination pattern similar to the newly added examination pattern.

[0069] The data generation unit 21 generates a new record in the automatic screening pattern classification master 11, as shown in Figures 19(a) and 19(b), and inputs into the newly generated record the screening category, request type, request classification, service, and use of funds of the new screening pattern specified by the business operator. The example in Figure 19(b) is an example in which "1: Pre-screening" is input as the screening category of the new screening pattern, "1: New" is input as the request type, "1: Request" is input as the request classification, "Home loan (refinancing support type)" is input as the service, and "Housing" is input as the use of funds.

[0070] In addition, the data generation unit 21 temporarily stores the target pattern number of the screening pattern specified by the business operator that is similar to the newly added screening pattern, and instead inputs the consecutive target pattern number following the target pattern number of the existing screening pattern as the target pattern number of the newly generated record.

[0071] That is, suppose that the business operator specifies "1: first pattern" as the target pattern number of an examination pattern similar to the examination pattern to be newly added. In this case, the data generation unit 21 temporarily stores the target pattern number of "1: first pattern" specified by the business operator in the storage unit 2. Then, as shown in FIG. 19(b), the data generation unit 21 inputs the target pattern number of "5: fifth pattern" which is consecutive to the existing "4: fourth pattern" as the target pattern number of the record of the examination pattern to be newly added.

[0072] At the same time, the acquisition unit 23 refers to the automatic inspection target master 12 shown in Fig. 3 based on the target pattern number designated by the business operator and temporarily stored in the storage unit 2, and acquires the job number, execution category, and execution order of each job corresponding to the target pattern number designated by the business operator. That is, when the business operator designates the target pattern number of "1: first pattern," the acquisition unit 23 acquires the job number, execution category, and execution order of each job of the first pattern shown in Fig. 3.

[0073] The data generation unit 21 adds the job number, execution category, and execution order of each job of the acquired first pattern to the automatic screening target master 12 as the job number, execution category, and execution order of the fifth pattern added this time, as shown in Figures 20(a) and 20(b). As a result, when adding a new screening pattern, the execution category, etc. of each job of the new screening pattern can be added to the automatic screening target master 12 simply by specifying a similar screening pattern.

[0074] Furthermore, the business operator can change the execution classification of each job newly added to the automatic screening target master 12 in this way to a desired execution classification. That is, the business operator performs an operation to change the execution classification of the job "individual calculation processing" that has an execution classification of "execute" to "not execute." By this change specification operation, the data generation unit 21 changes the execution classification of the job "individual calculation processing" of the fifth pattern from "execute" to "not execute," as shown in FIG. 20(b). This allows the execution classification of the job of the newly added screening pattern to be set to a desired execution classification.

[0075] Finally, the communication control unit 27 shown in Fig. 1 returns the loan examination results to the requester terminal device 31 via the network 35. This allows the business operator of the requester terminal device 31 to automatically and easily obtain the loan examination results for the user to whom the loan is being provided.

[0076] (Effects of the embodiment) When a financial institution provides a loan, it must screen the applicant to determine whether there are any problems with providing the loan. This screening process is carried out manually based on the financial institution's own criteria, taking into account the amount of loans taken out by other companies and past delinquency information, and determining whether the loan is feasible. As a result, the processing flow for registering the screening information required for loan decisions differs depending on the service (type of loan) or the situation of the case, making it a very complicated process.

[0077] In addition, the screening information required for loan decisions was entered by the business operator via screen operation. Therefore, when there were a large number of loan applications, the screening information had to be entered one by one via screen operation, which was a heavy burden on the business operator and could lead to manual input errors.

[0078] Furthermore, because the screening process was performed manually by a business operator, the screening process took a long time, which resulted in delays in the loan process and hindered the speedy provision of loans.

[0079] Therefore, the loan examination device 1 of the embodiment makes examinations more efficient by flexibly setting the scope of the examination workflow to be automatically executed based on the main items in the master, which reduces the burden on the operator during loan examinations, prevents operational errors, and enables quick loan decisions.

[0080] Specifically, the loan examination device 1 of the embodiment organizes the business flow and automates the examination flow using the following five items.

[0081] 1. Examination category: Preliminary examination or final examination 2. Request type: New, change of conditions, credit renewal 3. Request category: Request, request cancellation, etc. 4. Services: Home loans or card loans, etc. 5. Use of funds: Housing, cars, education, etc.

[0082] In this way, automating the review process can achieve the following effects:

[0083] 1. Master settings allow you to change the screening pattern to be implemented based on key items. This allows you to flexibly set the combination of screening processes and execute all screening automatically. This significantly reduces the burden placed on business operators due to screening. It also minimizes human error by business operators, improving the accuracy of screening. Furthermore, because loan screening can be automated, it reduces the time required for screening results and differentiates you from competitors who conduct all screening manually.

[0084] 2. For example, if you have already made a loan and are making an additional loan, you can start the review process partway through by setting the job to run or not run.

[0085] 3. For example, if an operational error occurs due to data fraud, or if manual review by visual inspection is required for the review, the automatic execution of subsequent processing will be stopped and subsequent processing will be performed manually. This will enable accurate review even if an error occurs during the review (ensuring accurate review).

[0086] 4. The execution status of each job can be checked at a glance by displaying a list of the job execution status on the job execution status list screen. Therefore, for example, if an error occurs during job execution as described above, it is possible to identify at a glance which jobs in the screening pattern have been executed and which have not been executed.

[0087] 5. Based on the data of the linked case, the necessary review jobs are selected and executed, so even if the review pattern includes jobs that are not executed, if the processing proceeds normally to the end, it is possible to automatically approve and respond with the results.

[0088] 6. When adding a new service (type of loan) to be screened, select and set the screening pattern set for a service similar to the newly added service. As a result, each job included in the selected screening pattern is added as a job for the newly added service. This makes it possible to easily add new services and provide a loan screening device with high maintainability.

[0089] [Contribution to the United Nations-led Sustainable Development Goals (SDGs)] This embodiment can contribute to improving business efficiency and promoting appropriate management decisions by companies, thereby contributing to the achievement of Goals 8 and 9 of the SDGs.

[0090] Furthermore, this embodiment can contribute to reducing waste and promoting paperless and electronic systems, thereby contributing to the achievement of SDGs Goals 12, 13, and 15.

[0091] Furthermore, this embodiment can contribute to strengthening control and governance, which can contribute to the achievement of Goal 16 of the SDGs.

[0092] [Other embodiments] The present invention may be implemented in various different embodiments other than those described above within the scope of the technical concept set forth in the claims.

[0093] For example, among the processes described in the embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically using known methods.

[0094] Furthermore, the processing procedures, control procedures, specific names, information including parameters such as registered data and search conditions for each process, screen examples, and database configurations shown in this specification and drawings can be changed as desired unless otherwise specified.

[0095] Furthermore, with regard to the loan examination device 1, the components shown in the figure are functional concepts, and do not necessarily have to be physically configured as shown in the figure.

[0096] For example, all or any part of the processing functions of the loan examination device 1, particularly the control unit 3 and each processing function performed by the control unit 3, may be implemented by a CPU (Central Processing Unit) and a program interpreted and executed by the CPU, or may be implemented as hardware using wired logic. The program is recorded on a non-transitory computer-readable recording medium containing programmed instructions for causing the information processing device to execute the processing described in this embodiment, and is mechanically read by the loan examination device 1 as needed. That is, a storage unit such as a ROM or HDD stores a computer program that works in cooperation with the OS to issue instructions to the CPU and perform various processing. This computer program is executed by being loaded into RAM and works in cooperation with the CPU to form the control unit 3.

[0097] In addition, the loan examination program of this loan examination device 1 may be stored in another server device connected to the loan examination device 1 via any network, and all or part of it may be downloaded as needed.

[0098] The loan screening program for executing the process described in this embodiment may be stored in a non-transitory computer-readable recording medium or configured as a program product. Here, the term "recording medium" includes any portable physical medium, such as a memory card, a Universal Serial Bus (USB) memory, a Secure Digital (SD) card, a flexible disk, a magneto-optical disk, a ROM, an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable and Programmable Read Only Memory (EEPROM), a Compact Disk Read Only Memory (CD-ROM), a Magneto-Optical Disk (MO), a Digital Versatile Disk (DVD), and a Blu-ray Disc (Blu-ray).

[0099] Furthermore, a "program" is a data processing method written in any language or description method, regardless of the format, such as source code or binary code. Note that a "program" is not necessarily limited to a single structure, but also includes a structure that is distributed as multiple modules or libraries, or a structure that achieves its function by working in conjunction with a separate program, such as an OS. Note that the specific configuration and reading procedure for reading a recording medium in the loan screening device 1 shown in the embodiment, as well as the installation procedure after reading, can use well-known configurations and procedures.

[0100] The memory unit 2 is a storage means such as a memory device such as RAM or ROM, a fixed disk device such as a hard disk, a flexible disk, or an optical disk, and stores various programs, tables, databases, and web page files used for various processes and providing websites.

[0101] The loan examination device 1 may be configured as an information processing device such as a known personal computer or workstation, or may be configured as an information processing device connected to any peripheral device. The information processing device may also be implemented by installing software (including programs or data) that realizes the processing described in this embodiment.

[0102] Furthermore, the specific form of distribution and integration of the devices is not limited to that shown in the drawings, and all or part of them can be configured by functionally or physically distributing and integrating them in any unit according to various additions or functional loads. In other words, the above-described embodiments can be implemented in any combination, or embodiments can be implemented selectively. [Industrial Applicability]

[0103] The present invention is suitable for use in, for example, financial loan screening. [Explanation of symbols]

[0104] 1. Loan screening device 2 Storage section 3. Control Unit 4. Communication interface section 5 Input / Output Interface Section 6 Input Devices 7 Output Devices 11 Automatic screening pattern classification master 12 Automatic review target master 13 Automatic Screening Job Master 21 Data Generation Unit 22 Judgment section 23 Acquisition Department 24 Job Execution Unit 25 Display control unit 26 Memory control unit 31 Client terminal device 35 Network

Claims

1. a detection unit that detects the screening pattern corresponding to the type of loan by referring to a storage unit that stores a program for causing a computer to execute a plurality of jobs related to the screening of the loan, each of which is a plurality of screening patterns corresponding to the type of loan included in the screening request for the loan, and a screening pattern that is set to be executed or not executed for each job; a job execution unit that executes a program of the job that is set to be executed among the jobs of the examination pattern corresponding to the detected type of loan, thereby executing a loan examination corresponding to the loan examination request; A loan examination device having the above.

2. a data generating unit that generates, for each job of the examination pattern, cooperation management data including at least a status category indicating that the job has been executed normally, a status category indicating that an error has occurred during the execution of the job, and a status category indicating that the job has not been executed; a display control unit that displays a list of the status classifications of each of the jobs on a display unit based on the cooperation management data; 2. The loan examination device according to claim 1,

3. The data generation unit Each time the job is executed, generate review result data including manual flag information indicating that the job has been executed normally or manual flag information indicating that an error has occurred during execution and that manual review is required; When manual flag information requiring manual review is generated due to an error occurring during the execution, the status classification of the job in which the error occurred during the execution is set to a status classification indicating that an error occurred during the execution of the job, and the status classification of one or more jobs scheduled to be executed after the job in which the error occurred during the execution is set to the status classification of not executed, 3. The loan examination device according to claim 2, wherein:

4. Further comprising a storage control unit that stores and controls the examination pattern designated when adding the loan type, the jobs corresponding to the designated examination pattern, and the execution or non-execution of each job in the storage unit as the examination pattern and job of the loan type to be added; 4. The loan examination device according to claim 1, wherein:

5. a detection step in which the detection unit detects the screening pattern corresponding to each type of loan based on the type of loan included in the loan screening request, by referring to a memory unit that stores a program for causing a computer to execute each of a plurality of jobs related to the loan screening, and a screening pattern that is set to be executed or not executed for each job; a job execution step in which a job execution unit executes a program of the job set to be executed among the jobs of the examination pattern corresponding to the detected type of loan, thereby executing a loan examination corresponding to the loan examination request; A loan screening method that has the following features.

6. Computer, a detection unit that detects the screening pattern corresponding to the type of loan by referring to a storage unit that stores a program for causing a computer to execute a plurality of jobs related to the screening of the loan, each of which is a plurality of screening patterns corresponding to the type of loan included in the screening request for the loan, and a screening pattern that is set to be executed or not executed for each job; functioning as a job execution unit that executes a loan examination corresponding to the loan examination request by executing a program of the job that is set to be executed among the jobs of the examination pattern corresponding to the detected type of loan; A loan screening program featuring:

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