JP5149671B2 - Individual project risk management device - Google Patents

Description

  The present invention relates to a technology for managing risk for each business case in progress with a business partner company.

In order for companies to start and continue business with other companies, it is important to manage the credit of the partner companies. This is because problems such as the inability to collect accounts receivable occur if the financial condition of a partner company deteriorates or causes a scandal and the credit of the company decreases. 2. Description of the Related Art Conventionally, it has been widely practiced to collect various data on the business performance and reputation of each business partner company and to provide credit to business partners based on such data. For example, Patent Literature 1 discloses a credit judgment support system that transmits credit information about a business partner from a credit server to a client terminal.
JP 2002-7738 A

  However, with the technology of Patent Document 1, credit information can be obtained in units of business partners, but credit management cannot be performed in units of individual business cases with the business partners. In reality, it is considered that there is a considerable difference in the size of the risk even among multiple projects that are in progress with a single business partner, so the degree of risk can be judged for each individual business project. A system is desired.

  The present invention has been made in view of such circumstances, and an object of the present invention is to provide a technology that enables risk management for each individual case for a plurality of business cases that are in progress with a business partner company. There is.

  One aspect of the present invention is an individual case risk management apparatus. This device receives information that identifies the ongoing business case, and obtains credit information about the business partner company of each business case, and between each business case and the business partner company The risk of calculating the risk judgment score, which is an index that represents the stability of the business case and the certainty of the price collection based on the credit information and the transaction transition information, and the transaction transition holding section that holds the transaction transition information related to the degree of transaction progress A determination score calculation unit.

  According to this aspect, the risk judgment score is calculated based on the transaction transition information for a plurality of business cases managed by each department of the company and the credit information of the business partner company related to each business case. This makes it possible to manage risk on a business project basis.

  The Transaction Transition Holding Department holds scheduled dates and execution dates for multiple milestones, which are events related to contracts and billing that pass through as business progresses, and the number of milestones completed and delays from scheduled dates A failure degree calculation unit that calculates a failure degree determined according to the number of times may be further provided, and the risk determination score calculation unit may calculate a risk determination score using the failure degree. According to this, the degree of failure is calculated according to the number of completed milestones and the number of delays, and is reflected in the risk judgment score. Therefore, the greater the risk judgment score is calculated for the business cases where the execution of milestones is often delayed from the scheduled date. can do.

  The failure degree calculation unit may count the number of days that the execution date of the milestone is delayed from the scheduled date, and add the count value to the failure degree. According to this, a risk judgment score can be calculated larger for a business case having a larger number of days delayed from the scheduled date of the milestone.

  An information collection unit that collects multiple document data including the name of the supplier company from the outside via the network, and presets as terms that may reduce the trust of the company when used together with the company name in the document data A negative word holding unit that holds a plurality of negative words, a risk degree holding unit that holds a risk degree obtained by quantifying the degree of credit deterioration due to detection of each negative word in the document data, and document data A document search unit that detects negative words contained in the risk search unit, and a risk aggregation unit that calculates a cumulative risk by summing up the risk levels given to the detected negative words with reference to the risk level holding unit. May be. In this case, the credit information acquisition unit may acquire the cumulative risk as the credit information of the business partner company, and the risk judgment score calculation unit may calculate the risk judgment score using the cumulative risk of the business partner company. According to this, by using the cumulative risk calculated based on negative words appearing in documents collected via the network as credit information of the counterparty company, it is possible to respond to changes in the business performance and reputation of the counterparty company. The value of the risk judgment score can be updated at any time.

  An accounting database in which accounting information related to business cases is recorded, a graph creation unit that creates a risk display graph that positions each business case on a two-dimensional graph using a risk judgment score and accounting information for each business case; May be further provided. According to this, it is possible to easily grasp the overall risk state of a plurality of business cases managed by the department.

  A response policy determination unit that outputs, to the user terminal, advice prepared in advance regarding the response policy for the business item according to the position that each business item occupies in the risk display graph.

  It should be noted that any combination of the above-described components and a representation of the present invention by a method, apparatus, system, recording medium, and computer program are also effective as an aspect of the present invention.

  According to the present invention, risk management for each individual case can be realized by reflecting the latest transaction state and credit information of each company for a plurality of business cases in progress with a business partner company.

Embodiment 1 FIG.
One embodiment of the present invention obtains document data including information related to a business partner company from a network, and calculates a cumulative risk obtained by quantifying the degree of credit deterioration of the business partner company based on the document data. It is a supplier risk management device that can be used for

  FIG. 1 is an overall schematic diagram of a supplier risk management system 50 according to an embodiment of the present invention. The supplier risk management apparatus 10 is connected to a network 12 such as the Internet or a LAN (Local Area Network), and can access various websites. An operating terminal 18 that is typically a personal computer is connected to the supplier risk management apparatus 10. Using the operation terminal 18, the user can give the supplier risk management device 10 the name of the survey target company and the necessary conditions described later.

  The supplier risk management device 10 accesses the servers 16 of a plurality of websites designated in advance via the network 12. Then, reference is made to news data about the survey target company, document data existing on a website that provides investment information, credit information, etc., and the credit risk of the survey target company is calculated based on them. The calculated risk can be used as data such as credit. The supplier risk management apparatus 10 according to the present embodiment is characterized in that the risk of the survey target company is calculated based on the constantly updated document data provided on the network.

  The supplier risk management apparatus 10 also provides company information that provides, as data, company names or individual names (hereinafter referred to as “summary information”) that are closely related to a plurality of companies or individuals via the network 12. The database 14 is also accessed. Information on affiliated companies, officers, shareholders, etc. of the survey target company is acquired and used for the above-described risk calculation. The company information database 14 may be locally connected to the supplier risk management apparatus 10, but is preferably operated by another entity.

  FIG. 2 is a functional block diagram showing a detailed configuration of the supplier risk management device 10 of FIG. These configurations can be realized in hardware by elements such as a CPU and a memory of a computer, and in terms of software, it is realized by a computer program or the like that has the functions described below and is loaded into a memory. Here, it is depicted as a functional block realized by such cooperation. Therefore, those skilled in the art will understand that these functional blocks can be realized in various forms by hardware only, software only, or a combination thereof.

  The target company setting unit 26 holds the name of the target company of the risk survey input from the user by the operation terminal 18. The negative word holding unit 28 holds a plurality of negative words input from the user by the operation terminal 18. Here, the “negative word” refers to a phrase that may be used together with a company name in document data to reduce the trust of the company. A specific example of the negative word will be described with reference to FIG.

  The risk level holding unit 38 holds the risk level input from the user by the operation terminal 18. Here, the “risk level” is a numerical value of the degree of credit deterioration due to detection of each negative word in the document data. The degree of risk is preferably set so that the negative word, which is considered to have greater credit concerns for the surveyed company, has a higher value. A specific example of the risk level will also be described with reference to FIG.

The information collecting unit 20 collects a large number of document data including a description about the survey target company from the network. The information collection unit 20 includes a crawling unit 22 and a summary information acquisition unit 24.
The crawling unit 22 receives the survey target company name from the target company setting unit 26 and collects a large number of document data including the company name. “Document data” in this specification refers to data including text information such as text data, HTML, XML, and XHTML files, but the data format is not limited.

The crawling unit 22 may collect document data from an arbitrary website on the network, but can also collect document data only from a site designated in advance by the user. In this case, shorten the time required for information collection and subsequent risk aggregation, and avoid the possibility that the risk level will become inaccurate due to the collection of document data created by individuals and socially unreliable organizations. It is possible to perform a search focusing on the above. The designated site includes a newspaper company site, a news providing site, a site providing credit information, and the like. In addition, since the risk of a supplier changes every day, it is preferable to select a site where data is updated more than a certain frequency. The collected document data is temporarily stored in a memory (not shown).
The summary information acquisition unit 24 acquires summary information of the survey target company from the company information database 14.

  The document search unit 30 detects a negative word included in the document data including the survey target company name accumulated in the information collection unit 20. The document search unit 30 includes a sentence decomposition unit 32 and a matching unit 34.

  The sentence decomposition unit 32 analyzes the document data stored in the information collection unit 20 according to a predetermined rule, and extracts the constituent elements of the sentence. The sentence decomposition unit 32 can use any of the known sentence decomposition algorithms. As an example, the target sentence may be decomposed into morphemes, a morphological analysis for determining a utilization form, original form, and part of speech for each element may be performed, and an element determined as a noun may be compared with a negative word. Since morphological analysis itself is a well-known technique, further explanation is omitted.

The matching unit 34 performs matching between the element that is a noun by the sentence decomposing unit 32 and the negative word in the negative word holding unit 28, and outputs the matched negative word as a search result. The detected negative word is output to the word storage unit 40.
Note that the matching unit 34 may detect a negative word by simply performing a full-text search on document data without using the result of morphological analysis.

  The word accumulation unit 40 accumulates negative words detected from the document data for each survey target company. As will be described later, the word accumulation unit 40 accumulates negative words detected for each item when document data is collected for affiliated companies, officers, shareholders, etc. of the survey target company.

The risk totaling unit 44 refers to the risk degree holding unit 38 and calculates a cumulative risk obtained by adding the risks assigned to the negative words stored in the word storage unit 40. This cumulative risk is calculated for each surveyed company.
In addition, as described later, when a negative word search is conducted for affiliated companies, officers, shareholders, etc. of the surveyed company, the risks assigned to each negative word are aggregated and the total number of surveyed companies is accumulated. Calculate the total cumulative risk added to the risk. Therefore, if the search range for negative words is expanded, such as the affiliated company of the surveyed company and the affiliated company, the cumulative risk increases each time.

  The survey range determination unit 48 compares the total cumulative risk with a predetermined threshold value and determines the survey range of the negative word. Specifically, this will be described with reference to FIG.

  The credit judgment unit 46 receives the total accumulated risk of the survey target company, calculates a credit score reflecting the score for each company and the score of the transaction history with the company, and outputs the credit score to the operation terminal 18. . The user can use this credit score for credit work.

  In the above description, it has been described that the crawling unit 22 first collects document data including the name of the survey target company and searches for negative words from the collected document data. Document data including both the name and any negative word may be collected from the network.

FIG. 3 shows a company-specific data structure 54 provided by the company information database 14. The data structure 54 includes a company name, a parent company name, an affiliated company name, an officer name, a major shareholder name, and a major business partner name. Data other than these, for example, a company address or a representative name may be included in the data. Data is prepared for each company, and necessary information can be obtained using the company name as a key. Further, by executing a search using the officer name as a key, the name of the company in which the person serves as the officer can be searched. Similarly, by executing a search using a shareholder name as a key, it is possible to search for the name of a company in which an individual who is a shareholder serves as an officer, or the name of a company having a company that is a shareholder as an affiliated company.
Needless to say, the company information database 14 may be configured differently from the above. For example, even if company information data, officer data, shareholder data, and business partner data are individually created in a database, the databases are provided in the form of a relational database that is related to each other by company code or person code. Good.

  FIG. 4 is a table 60 showing an example of negative words and risk levels. The negative word 62 and the risk degree 64 are set by the user inputting words and numerical values in a dedicated format displayed on the operation terminal 18. The negative word 62 includes, for example, words and phrases related to financial risks such as bad loans, words and phrases related to crimes such as financial settlement, bribery, and arrest, and phrases related to reputations such as suspicion and fraud. There is no limit to the number of negative words that can be set.

  The risk degree 64 is determined by the user in the range of 1 to 5 as an example. In the example of FIG. 4, a negative word related to crimes such as powder settlement, bribery, and arrest is assigned a risk level of “5”, and other negative words are assigned a risk level of 1 or 2. .

  The negative word and risk level may be the same for all surveyed companies, different for each industry type, or different for each company. Good.

FIG. 5 is a diagram for explaining the relationship between a certain survey target company and summary information about the company, developed according to the database of FIG.
In FIG. 5, it is assumed that the survey target company is company A. With reference to the above-described company information database, information on the affiliated company 74, the officers 76, and the shareholders 78 can be acquired for A company. Therefore, it can be said that each data of the affiliated company 74, the officer 76, and the shareholder 78 is data located in a lower hierarchy than the company A. In the present embodiment, these data directly derived from the survey target company are referred to as first layer data.

Focusing on the “a1” company among the affiliated companies 74, information on the affiliated company 80, the officers 82, and the shareholders 84 can be acquired by referring to the company information database for the a1 company. In this way, data derived from the data of the first hierarchy is called data of the second hierarchy. For the other affiliated companies a2 and a3, the affiliated company, officers and shareholders can be similarly expanded as the second hierarchy data. As for the first-level officers 76, another company name in which the person serves as an officer and the company name in which the person is a shareholder can be expanded as second-tier data. Further, for the first-tier shareholders 78, if the shareholders are individuals, the second-tier data includes the name of another company in which the person serves as an officer and the name of the company in which the person is a shareholder. Can be deployed as When the shareholder is a corporation, the affiliated company, officer, and shareholder of the company can be developed as data in the second hierarchy.
For affiliated companies, officers, and shareholders in the second hierarchy, data can be expanded to a lower hierarchy.
Thus, it can be seen that the company name, officer name, and shareholder name related to the survey target company increase rapidly each time the hierarchy is traced down.

  FIG. 6 is a diagram illustrating an example of negative word search and risk tabulation results for a survey target company. The column 92 represents the name of the survey target company. A column 94 represents negative words retrieved from document data including the company name in the column 92. Column 96 represents the degree of risk assigned to the negative word in column 94. A column 98 represents the cumulative risk obtained by adding the risk level of the negative word searched for each survey target company. In FIG. 6, it can be seen that the cumulative risk for company A is “15” and the cumulative risk calculated for company B is “35”.

  In the example of FIG. 6, no matter how many times the same negative word is detected in the document data, the degree of risk assigned to that word is one negative word. As another embodiment, an appearance frequency column may be provided in the table 90, the number of each negative word appearing in the document data may be counted, and the risk degree may be multiplied by the count number.

  FIG. 7 is a diagram illustrating a reference example 100 for the investigation range determination unit 48 to determine whether or not to further expand the risk investigation range to a lower hierarchy. A column 102 represents a range in which a negative word search should be executed by the information collection unit 20 and the document search unit 30. Column 104 represents threshold values for the cumulative risk up to the first hierarchy. A column 106 represents a threshold value for the cumulative risk calculated at the end of the investigation up to the second hierarchy. Note that the threshold value is also determined for each layer 3 and below.

  For example, if the cumulative risk up to the first hierarchy is 50 or more, the document search unit 30 performs a survey on the lower hierarchy. That is, a negative word search is performed on document data including companies, officers, and shareholders related to each affiliated company, officer, and shareholder in the first hierarchy in FIG. When the cumulative risk up to the first hierarchy is 21 or more and 49 or less, the document search unit 30 performs a survey on a part of the lower hierarchy. That is, a negative word search is performed on document data including companies, officers, and shareholders related to the related companies in the first hierarchy in FIG. Searches are not performed for subordinates of officers and shareholders. If the cumulative risk up to the first level is 20 or less, the survey is ended up to the first level.

For the cumulative risk up to the second level, the survey range is determined based on the table 100 in the same manner as described above. In addition, it is preferable that the threshold value for determining the investigation range is a different value for each hierarchy. The reason for this is as follows. In other words, if negative word surveys are executed up to the lower hierarchy, a large number of negative words are inevitably detected, and the cumulative risk is higher than that of the upper hierarchy. Therefore, if the same value is used without changing the threshold value of the lower hierarchy in accordance with it, the threshold value is always exceeded after a certain hierarchy, and the investigation is not completed.
Note that the threshold value as described above may not be set, and it may be set so that the investigation is always executed up to a predetermined hierarchy.

FIG. 8 and FIG. 9 are flowcharts for explaining the flow of executing risk judgment of a business partner company according to the present embodiment.
First, the information collecting unit 20 receives a survey target company name from the operation terminal 18, and the document search unit 30 receives a negative word from the negative word holding unit 28 (S10). The crawling unit 22 collects document data including the survey target company name from the server 16 of the designated site via the network (S12). The document search unit 30 searches the collected document data for negative words (S14), and the word storage unit 40 stores the searched negative words for each survey target company (S16). The risk totaling unit 44 acquires the risk level assigned to the accumulated negative word from the risk level holding unit 38, and calculates a cumulative risk obtained by adding them (S18).

Moving to FIG. 9, the information collection unit 20 and the document search unit 30 proceed to the investigation on the first hierarchy. First, the summary information acquisition unit 24 in the information collection unit 20 accesses the company information database 14 and acquires summary information regarding the survey target company, specifically, the affiliated company name, officer name, and shareholder name (S20). . The crawling unit 22 collects document data including the acquired affiliate name, officer name, or shareholder name, and temporarily stores them (S22).
The document search unit 30 performs a negative word search for the document data for each item of the affiliated company name, officer name, and shareholder name accumulated in the information collecting unit 20 (S24), and the detected negative word Are stored in the word storage unit 40 by item (S26). The risk totaling unit 44 acquires the risk level assigned to the negative word from the risk level holding unit 38, and totals the negative word risk accumulated for each item (S28). Furthermore, the risk totaling unit 44 adds the total risk for each item of the first layer summary information to the previously calculated cumulative risk of the survey target company (S30). The total accumulated risk thus obtained is passed to the survey range determination unit 48.

  The survey range determination unit 48 compares the total accumulated risk with the threshold value in the column 104 shown in FIG. 7 (S32). If the total cumulative risk is equal to or greater than a predetermined threshold, for example, “21” (Y in S32), the information collection unit 20 and the document search unit 30 will further expand the investigation range to a lower hierarchy. (S34), S20 to S30 are repeated. If the total cumulative risk is less than the predetermined threshold (N in S32), the negative word survey is completed up to the current level, and the total cumulative risk is output to the credit determination unit 46 (S36).

FIG. 10 is a conceptual diagram for explaining the situation when risk aggregation is performed by the supplier risk management device 10 for the three companies of Company A, Company B, and Company C.
Assume that the cumulative risks of Company A, Company B, and Company C are “15”, “35”, and “17”, respectively, based on negative word search results for document data collected for Company A, Company B, and Company C. Regardless of the total risk level, the first word summary information directly derived from the database of the target company is searched for negative words by the information collection unit 20 and the document search unit 30.

  The box 118 in the figure indicates that, for the company A, the summary information acquisition unit 24 has acquired two affiliated companies, two officers, and one shareholder. A box 120 indicates that Company B has been acquired by the summary information acquisition unit 24 as two affiliated companies, two officers, two shareholders, and a negative word survey target. A box 122 represents that Company C has been acquired by the summary information acquisition unit 24 as one of the affiliated companies, one officer, two shareholders, and the negative word survey target.

  Each box 118-122 also shows the risk level of the negative word detected for each of the summary information. For example, the box 120 indicates that the risk level of the negative word detected for the affiliated company b1 is 5, and the risk level of the negative word detected for the affiliated company b2 is 5. The risk totaling unit 44 adds the calculated risk degree to the cumulative risk obtained for the upper hierarchy, that is, the original survey target company. As a result, the total accumulated risks of Company A, Company B, and Company C are “17”, “52”, and “20”, respectively.

  The survey range determination unit 48 compares the total cumulative risk with a predetermined threshold value and determines whether or not to further expand the negative word survey range. Here, it is compared with the threshold value defined in the column 104 of FIG. As a result, for Company A and Company C, the total cumulative risk is 20 or less, so the negative word survey is stopped here. For Company B, the total cumulative risk is 50 or more, so the negative word survey is expanded further down the hierarchy.

  The summary information acquisition unit 24 acquires summary information about affiliated companies, officers, and shareholders in the box 120. The result is shown in box 124 in the figure. That is, for the affiliated company b1, one affiliated company, one officer, and one shareholder are acquired. For the shareholder b5, one affiliated company and one officer have been acquired. The box 124 also indicates the risk level of the negative word detected for each of the summary information.

The risk tabulation unit 44 adds the degree of risk given to each summary information of the second hierarchy, and further adds to the total accumulated risk of the original survey target company. As a result, it is assumed that the total cumulative risk up to the second hierarchy is 70. The survey range determination unit 48 compares the threshold value set in the column 106 in FIG. 7 with the total accumulated risk. Since the total accumulated risk is 70 or more, the negative word survey is expanded to the third level below for Company B.
In this way, the negative word search is executed until the total cumulative risk obtained in the survey up to each level falls below a predetermined threshold value or until the predetermined upper limit number of surveys is completed. .

  In a survey target company (for example, Company B in FIG. 10) whose survey scope has been expanded to a lower hierarchy, the total cumulative risk increases as the survey progresses. As described above, in this embodiment, the risk investigation target can be automatically expanded to a wider range for a company with a high risk. It should be noted that when the total cumulative risk of the survey target company reaches a predetermined upper limit value, it is possible to set a mechanism such as that the subsequent search is terminated because the company is not appropriate as a target for transactions.

  As described above, according to the present embodiment, a negative word that is considered to affect the trust of the survey target company is defined in advance, and the document data including the survey target company name collected via the network is included in the document data. To search for negative words. Then, a cumulative risk representing the degree of credit deterioration is calculated based on the searched negative word. The user can use this accumulated risk for credit management.

  In addition, since the cumulative risk is calculated based on document data collected from outside via the network, information updated daily can be reflected in the cumulative risk. Further, since the cumulative risk is calculated based on the presence or absence of negative words in the document data, the user does not need to confirm the contents of the document data.

  In addition, negative words are detected from document data including affiliated companies, officer names, shareholder names, etc. related to the surveyed company, and the degree of risk assigned to the detected negative word is calculated for the original surveyed company. Added to the cumulative risk. Accordingly, the cumulative risk is calculated by referring not only to the superficial information of the survey target company but also to information on affiliated companies having a capital relationship or personal relationship. Therefore, the reliability of the cumulative risk in credit management is improved.

  Note that the crawling unit 22 may refer to the newness of the document data when collecting the document data from the network. For example, the crawling unit 22 may collect only document data created within a predetermined period (such as one week).

Embodiment 2. FIG.
In the first embodiment, it has been described that the risk of a supplier company is grasped by calculating the cumulative risk for each supplier company. In the second embodiment, an individual case risk management apparatus that can grasp the risk of each business case in progress with each business partner company will be described.

  FIG. 11 is an overall schematic diagram of the individual case risk management system 150 according to the present embodiment. The individual item risk management device 160 is a device that manages the risk of a plurality of business items that are progressing under responsibility management in a certain department within the company. The individual case risk management device 160 is connected to the supplier risk management device 10 according to the first embodiment, and receives the total accumulated risk of the supplier company calculated by the device 10. Further, the individual case risk management apparatus 160 can connect to the company information database 14 via the network 12 and acquire information on the supplier company. In the accounting database 152, accounting information about business matters with each business partner company is recorded. This accounting information may be recorded in another location, for example, a supplier risk management device.

Using the operation terminal 18, the user inputs information related to the business case in progress with the business partner company to the individual case risk management device 160. This information mainly relates to the scheduled date and execution date of the event that passes when proceeding with the transaction. The individual case risk management device 160 mainly takes into account when processing the case for each business case using the total accumulated risk and rating information of the business partner company and the information on the business case input from the user. A risk judgment score that is an index representing the stability of the project and the certainty of the price collection is calculated. Then, based on the risk determination score, the user is provided with advice on what policy should be approached for each case.
In the present embodiment, the following description is given assuming a business in a system development department that performs system consultation, development, and operation based on a request from a customer.

  FIG. 12 is a functional block diagram showing a detailed configuration of the individual case risk management device 160 of FIG. Also in this figure, each functional block can be realized in various forms by hardware only, software only, or a combination thereof.

The risk degree acquisition unit 172 acquires the total cumulative risk calculated for each supplier company from the supplier risk management device 10 and passes it to the risk determination score calculation unit 178.
The rating acquisition unit 174 accesses the company information database 14 to acquire rating information about each business partner company, and passes it to the risk determination score calculation unit 178.
The transaction history holding unit 176 holds information relating to business cases that have already been completed with each business partner company (hereinafter referred to as “transaction history”). This transaction history includes, for example, the total sales amount by business partner company and the total number of completed business matters.

The contract request information management unit 180 manages the transition of events such as transaction contracts and billing for business cases currently in progress with each business partner company. Contract request information management unit 180 includes a transaction transition holding unit 182 and a failure degree calculation unit 184.
The transaction transition holding unit 182 records a scheduled date and an execution date for a predetermined event such as a contract conclusion date and a billing date for each business case. These dates are obtained from the accounting database 152. Alternatively, it may be input from the user using the operation terminal 18. Based on the information recorded in the transaction transition holding unit 182, the failure degree calculation unit 184 calculates a failure degree that serves as an index indicating whether the event has smoothly changed or has been difficult as the transaction progresses. To do. The calculated failure degree is sent to the risk determination score calculation unit 178. The transaction transition holding unit 182 and the failure degree calculation unit 184 will be described in detail with reference to FIGS. 14 and 15.

  The risk determination score calculation unit 178 receives information for identifying an ongoing business case, and calculates a risk determination score for each business case that is ongoing with a business partner company. The calculation of the risk determination score P is performed as follows.

Received from the risk obtaining section 172 the overall cumulative risk of each customer company is referred to as P _A. The overall cumulative risk P _A, which may be the same value is used for all business transactions with each business partner company.

The risk determination score calculation unit 178 calculates a rating risk P _B based on the rating for each client company received from the rating acquisition unit 174. This rating risk P _B is set such that the lower the rating, the larger P _B becomes. For example, if the rating has 5 levels of A to E with A as the higher rank, the rating risk P _B is set to 1 to 5. If the rating is more detailed, the rating risk P _B is set accordingly. In this case, the rating risk P _B may not increase linearly. For example, the rating risk P _B may increase in a quadratic function as the rating becomes lower. Rating risk P _B is, the same value is used for all business transactions with each business partner company.

Also, the risk determination score calculating unit 178, based on the transaction history received from the transaction history holding unit 176, calculates the historical risk P _C. For example, if transaction history is total sales, total large transaction earlier, is set as history risk P _C is reduced. Alternatively, total sets history risk P _C of the fixing for the suppliers below a predetermined threshold, the total amount may be zero history risk P _C for more suppliers threshold. This is because it is considered that there is a small risk that the price of a business case cannot be collected for a business partner with a large total sales volume in the past.
Even if the transaction history is the total number of business projects, the total number is often traded earlier, set to history risk P _C becomes smaller. Alternatively, the total number of business transactions sets the historical risk P _C of the fixing for the suppliers below the threshold, the total number may be zero history risk P _C for more suppliers threshold. This is also because in this case, it is considered that the risk that the price cannot be collected for the business case is small for the business partner who has already completed the business case.
Here, also for the history risk P _C, the same value is used for all business transactions with each business partner company.

Furthermore, the risk determination score calculating unit 178 receives the failure of _{P D} from the failure calculator 184. Method will be described later calculation of disability P _D.

The risk determination score calculation unit 178 calculates a risk determination score P according to the following formula and outputs the risk determination score P to the graph creation unit 188.
P = P _A + P _B + P _C + P _D
Incidentally, the risk determination score calculating unit 178 may calculate the risk determination score P based on any one 1 to 3 out of the above-described P _A to P _D. As an example, it may calculate the risk determination score P using only entire cumulative risk P _A and disability P _D.

  The graph creation unit 188 receives the risk determination score P of each business case, and requests the accounting information acquisition unit 186 to obtain information on the transaction amount and profit rate of each case. The accounting information acquisition unit 186 refers to the accounting database 152 based on the case name, searches for the transaction amount and the profit rate, and passes them to the graph creation unit 188. The graph creation unit 188 creates a graph that can confirm the risk for a plurality of business cases under the management of the department, using the risk determination score, the transaction amount, and the profit rate. This graph will be described with reference to FIGS.

  Based on the position of the business case in the graph created by the graph creation unit 188, the response policy determination unit 190 determines a response policy such as whether to continue the business case or review the contract including cancellation of the contract. The determination result is sent to the operation terminal 18 and is useful for the user's determination.

  The individual item information display unit 192 creates transaction transition information in response to an instruction from the operation terminal 18 for the business item displayed on the graph. This transaction transition information is sent to the operation terminal 18.

FIG. 13 is a table showing an example of service type classification. The service forms are divided into a large section 202 and a medium section 204. In this embodiment, each business case is always associated with one of the medium sections. Further, the middle category 204 is associated with a category 206 of any account item in the accounting database 152. As described above, the transaction amount of the business item can be acquired from the database by linking the service form with the classification of the account item in the accounting database.
In addition, the rating of a business partner company may be given for every said service form. In this case, the risk determination score calculation unit 178 may receive the rating corresponding to the service form of the business case from the rating acquisition unit 174 with reference to the service form of the business case.

  FIG. 14 is a table showing an example of the transaction transition information 210 held by the transaction transition holding unit 182. The transaction transition information is created for each business case, and includes the supplier company name and the business case name 218 as data. The transaction transition information 210 includes milestone 212, scheduled date 214, and execution date 216 as data. As milestones, events that occur between the start of a business transaction with a business partner and the completion of the transaction are selected that affect the stability of the business transaction and the collection of payment. In this embodiment, the opening date of an accounting unit opened in response to a business case (unit opening date), the date on which a business case was approved (final approval date), the relevant business case with a business partner company Provisional contract date, contract information registration date, contract conclusion date, collection date of confirmation (confirmation collection date) confirming that the product or service has been delivered to the business partner for the business case, date of billing for the product or service , And 8 payment dates are set as milestones. Of course, the types and number of milestones are not limited to those described above, and various milestones can be adopted according to the type of business of the client company and the contents of the business project. The scheduled date 214 is a scheduled date set with the business partner company for each milestone, and is input by the operation terminal 18. The implementation date 216 is a date when the company or a business partner actually executes an action related to each milestone for each milestone, and is input by the operation terminal 18.

Figure 15 is a diagram for explaining a method of calculating the fault degree P _D based on the transaction transition information. In the figure, a column 220 corresponds to the milestone 212 shown in FIG. 14, and is arranged in chronological order from the start to the end of the transaction from the bottom to the top. Failure calculation unit 184, for each business matters, every time one pass through the milestones, incremented by one disability P _D. Specifically, the implementation date for each milestone of FIG. 14 is input by the user, the failure calculator 184 determines that it has passed the milestone, increments the failure of P _D. Further, fault calculation unit 184 is incremented by one disability P _D may implementation of the milestone is behind schedule date.

It is assumed that lines 222, 224, and 226 in FIG. 15 have passed through milestones for different business cases. In the figure, an upward arrow indicates that the implementation date of the milestone 220 on the left side of the figure is the scheduled date or before the scheduled date. The arrow pointing to the right indicates that the implementation date of the milestone 220 has been delayed from the scheduled date, and the length of the arrow represents the number of days delayed. Since the business case represented by the line 222 has completed all eight milestones before the scheduled date, the line 222 is composed only of an upward arrow. Therefore, the failure degree P _D is calculated as P _D = 8 corresponding to eight milestones. Because the business case represented by line 224 was delayed from the scheduled date for two milestones on the billing date and payment date, line 224 includes a total of two right-pointing arrows in the billing date and payment date portions. It consists of ten arrows. Therefore, failure of P _D is to be incremented each twice delayed eight milestone is calculated as P D ₌ 10. The business case represented by line 226 includes two right-pointing arrows in the provisional contract date and billing date sections because the implementation date was delayed from the scheduled date for two milestones on the provisional contract date and billing date. It consists of a total of 10 arrows. Therefore, failure of P _D is to be incremented each twice delayed eight milestone is calculated as P D ₌ 10.

FIG. 15 also shows the number of days delayed for each business item. The business case represented by the line 224 indicates that the billing date is delayed by d ₁ day and the payment date is delayed by d ₂ days. Also, business transactions, represented by line 226, the temporary contract date is delayed d ₃ days, indicating that the invoice date is delayed d ₄ days. However, the failure degrees calculated by the failure degree calculation unit 184 are both equal to 10. In think the risk of business transactions, the risk determination score the greater the number of days delay increases, i.e. preferably disability P _D is calculated greatly.

Therefore, the failure level calculation unit 184 may calculate the failure level in consideration of the number of days of delay in the implementation of the milestone. As an example, M the total number of milestones, the delay times of the milestone embodiment W, when the sum of days late was as D, fault calculation unit 184 may calculate the disability P _D according to the following equation.
P _D = M + W + D
Note that fault calculator 184, M, W, instead of simply adding the D, may be calculated disability P _D by weighting to adding or other computing.

FIG. 16 shows an example of a case risk display graph. The graph creation unit 188 determines points on the coordinates by taking the risk judgment score of each business item on the horizontal axis and the profit rate of each business item on the vertical axis. Then, centering on this point, a circle with a radius corresponding to the transaction amount of each business case is drawn.
In FIG. 16, four circles corresponding to four business cases are drawn. A case with a higher risk judgment score is placed on the left side, and a case with a lower risk judgment score is placed on the right side. Also, projects with higher profit margins are placed on the upper side, and projects with lower profit margins are placed on the lower side. In this way, by creating a project risk display graph that changes its placement in the graph according to the risk judgment score and profit ratio of the business project, the user can see the status of the business project currently held in the department at a glance. It becomes possible to grasp by. In addition, since the size of the yen changes according to the transaction amount of the business item, the user can easily grasp how large the business item is in the department.

  FIG. 17 is a diagram for explaining the response policy determination based on the position of each case in the graph by the response policy determination unit 190. FIG. 17 shows that the case risk display graph is divided into four areas A to D by setting the threshold value Tx on the horizontal axis and the threshold value Ty on the vertical axis. Among these, the business case located in the region B is a case with a small risk judgment score and a high degree of security and a high profit rate. Therefore, the response policy determination unit 190 can determine that the business case located in the region B is a good case. Further, the business case located in the area C is a case having a large risk judgment score and a high degree of anxiety about collecting the price, and has a low profit rate. Therefore, the response policy determination unit 190 can determine that the business case located in the area C is a case that should be taken into consideration for reviewing and canceling the contract while cautioning the person in charge. Since the business cases located in the areas A and D have a problem in either the risk determination score or the profit rate, it can be determined that the business case needs to be examined. The response policy determination unit 190 outputs an advice message prepared in advance for each case to the operation terminal 18.

  The response policy determination unit 190 receives information related to the service form of each business case from the accounting information acquisition unit 186, and considers this service form together with the case risk display graph to make a more realistic determination. can do. For example, it is assumed that the service form of the business case is “consultation”. Consultation is expected to close the business relationship in a relatively short period of time, so even if the risk assessment score is somewhat high, the impact on the business performance of the department is considered to be relatively small. Accordingly, the response policy determination unit 190 can determine that a business case located in the area A is a relatively preferable case because the profit rate is high even if the risk determination score is large. Also, considering the case where the service type is “operational service”, it is considered that the operational service has a long-lasting business relationship. Therefore, even if the profit ratio is low, select the one with a low risk judgment score. Can give a sense of stability to the performance of the department. Therefore, the response policy determination unit 190 can determine that a business item located in the region D is a relatively preferable item.

  FIG. 18 is a diagram for explaining the modification of the case risk display graph. As described above, the meanings of the areas A to D are different depending on the service form of each business case. Therefore, the graph creating unit 188 may move the positions of the threshold values Tx and Ty when the business cases displayed in the graph belong to the same service form. For example, if the service form is “consultation”, a relatively large risk judgment score is acceptable, so it is possible to shift the threshold value Tx to the left in the figure to increase the area occupied by the region B. It is done. Further, if the service form is “operation service”, it is preferable that the risk determination score is small. Therefore, the threshold Tx may be shifted to the right in the figure to reduce the area occupied by the region B.

In FIG. 16, and it represents the horizontal axis projects risk graphically as a risk determination score P, the horizontal axis across the aforementioned cumulative risk P _A, rated risk P _B, the history risk P _C or disability P _D You may make it display either. In addition, the user may select a value to be displayed on the horizontal axis from the above. The values displayed on the horizontal axis may be switched at predetermined intervals. Each time the displayed value is switched to P _A , P _B , P _C , P _D , P, by observing the transition of the position occupied by the business case in the graph, which value affects the risk judgment score P You can consider whether it has a lot to do.

FIG. 19 is a flowchart for explaining the flow of risk determination for each business case according to the present embodiment.
First, the risk determination score calculation unit 178 displays the total cumulative risk of the business partner company from the risk degree acquisition unit 172, the rating information of the business partner company from the rating acquisition unit 174, and the transaction history of the business partner company from the transaction history holding unit 176. Is acquired (S50). The failure degree calculation unit 184 calculates the failure degree of each business case based on the transaction change of each business case held in the transaction change holding unit 182 (S52). The risk determination score calculation unit 178 calculates the risk determination score of each business case using the total accumulated risk, rating information, transaction history, and failure degree (S54). The graph creation unit 188 acquires the profit rate and transaction amount of the business case for which the risk determination score is calculated from the accounting information acquisition unit 186 (S56). The graph creation unit 188 creates a case risk display graph with the business case risk determination score on the horizontal axis and the profit rate on the vertical axis, and outputs it to the operation terminal 18 (S58). The response policy determination unit 190 outputs advice on a future response policy to the operation terminal 18 based on the position of the business item in the item risk display graph (S60).

As described above, according to the present embodiment, the risk judgment score is based on the transaction transition information of a plurality of business cases managed by each department of the company and the credit information of the business partner company of each business case. Was calculated. As a result, it is possible to perform risk management in units of business projects in the department by reflecting the latest transaction status and credit information of each company. In addition, since the business cases under management are displayed on the risk display graph using the risk judgment score and the profit margin, the risk of the business case is predicted for the manager of the department, and future response policy Can provide a means of thinking.
In addition, multiple milestones that are events related to contracts and billing that pass through as the business progresses are set, and the degree of failure is calculated using the number of milestones completed, the number of delays from the scheduled date, and the number of days delayed The degree of disability is reflected in the risk judgment score. As a result, the degree of progress of each business case can be reflected in the risk determination score.

In embodiments, transaction history holding unit 176 is trading history with the business partner company holds the example total number of total sales and business transactions, etc., it mentioned calculating a historical risk P _C using these. Instead, the transaction history holding unit 176 may hold the failure degree P _D ′ of a past business item that has already been completed for each business partner company. In this case, the risk determination score calculating unit 178 may use the average value of the failure of P _{D 'of} past business transactions as history risk P _C.

  Further, the transaction history holding unit 176 may hold a graph representing a correlation between the risk judgment score P of a past business case that has already been completed and the total sales amount for a business partner company related to each business case. . In this case, when the risk determination score calculation unit 178 newly calculates the risk determination score P of the business case, the risk determination score calculation unit 178 acquires the total sales amount of the business partner company related to the business case, and refers to the graph to determine a predetermined amount. P may be corrected using a calculation formula.

  The present invention has been described based on some embodiments. It is understood by those skilled in the art that these embodiments are exemplifications, and that various modifications can be made to combinations of the respective constituent elements and processing processes, and such modifications are also within the scope of the present invention. By the way.

  It should also be understood by those skilled in the art that the functions to be fulfilled by the constituent elements recited in the claims are realized by the individual functional blocks shown in the present embodiment or their linkage.

1 is an overall schematic diagram of a supplier risk management system according to an embodiment of the present invention. It is a functional block diagram which shows the detailed structure of the supplier risk management apparatus of FIG. It is a figure which shows the data structure according to company provided with a company information database. It is a figure which shows an example of a negative word and a risk degree. It is a figure explaining the relationship between a certain investigation object company and each item of the outline information of the company developed according to the database of FIG. It is a figure which shows an example of the result of having searched the negative word about the investigation object company, and totaling risk. It is a figure which shows the example of a reference | standard for an investigation range determination part determining whether the range of a risk investigation is extended further to a lower hierarchy. It is a flowchart explaining the flow which implements risk determination of a supplier company according to one Embodiment. It is a flowchart explaining the flow which implements risk determination of a supplier company according to one Embodiment. It is a conceptual diagram explaining a mode when risk totalization is implemented with a supplier risk management apparatus about three companies, A company, B company, and C company. It is a whole schematic diagram of the individual case risk management system concerning another embodiment of the present invention. It is a block diagram which shows the detailed structure of the individual case risk management apparatus of FIG. It is a figure which shows an example of a service form division. It is a figure which shows an example of the transaction transition information hold | maintained at a transaction transition holding part. It is a figure explaining the calculation method of the failure degree based on transaction transition information. It is a figure which shows an example of a case risk display graph. It is a figure for demonstrating the response policy determination based on the position of each case in a case risk display graph. It is a figure for demonstrating correction of a project risk display graph. It is a flowchart explaining the flow which calculates the risk determination score of an individual case according to another embodiment of this invention.

Explanation of symbols

  10 supplier risk management device, 12 network, 14 company information database, 16 designated site server, 18 operation terminal, 20 information collection unit, 22 crawling unit, 24 summary information acquisition unit, 26 target company setting unit, 28 negative word holding unit , 30 document search unit, 32 sentence decomposition unit, 34 matching unit, 38 risk degree holding unit, 40 word storage unit, 44 risk aggregation unit, 46 credit judgment unit, 48 survey range determination unit, 152 accounting database, 160 individual project risk Management device, 172 Risk level acquisition unit, 174 Rating acquisition unit, 176 Transaction history storage unit, 178 Risk judgment score calculation unit, 180 Contract request information management unit, 182 Transaction transition storage unit, 184 Disability level calculation unit, 186 Acquire accounting information Part 18 8 graph creation unit, 190 response policy determination unit, 192 individual case information display unit.

Claims (6)

A credit information acquisition unit that receives information identifying the business case in progress, and acquires credit information about the business partner company of each business case from an external database ;
A transaction transition holding unit that holds a scheduled date and an execution date for each of a plurality of milestones that are events related to a contract to be passed and a charge request as the business case progresses ,
A failure degree calculating unit that counts the number of times each business case has passed the milestone and the number of times the execution date of the milestone is delayed from the scheduled date, and adds these to calculate the degree of failure;
A risk judgment score, which is an index representing the stability of the business case and the certainty about price collection , by calculating a rating risk preset for the credit information and adding the rating risk and the failure degree A risk determination score calculation unit for calculating
An individual item risk management device characterized by comprising: The individual case risk management apparatus according to claim 1 , wherein the failure degree calculation unit counts the number of days that the execution date of the milestone is delayed from a scheduled date, and adds a count value to the failure degree. An information collection unit for collecting a plurality of document data including business partner names from the outside via a network;
A negative word holding unit that holds a plurality of negative words set in advance as words that may decrease the trust of the company by being used together with the company name in the document data;
A risk degree holding unit for holding a risk degree obtained by quantifying the degree of credit deterioration due to detection of each of the negative words in the document data;
A document search unit for detecting the negative word included in the document data;
Referring to the risk level holding unit, a risk totaling unit for calculating the cumulative risk by summing the risk levels given to the detected negative words;
Further comprising
The credit information acquisition unit further acquires the cumulative risk as credit information of a client company,
The risk determination score calculating unit, individual projects risk management system according to claim 1 or 2 using the cumulative risk of the business partner company and calculates the risk determination score. An accounting database in which accounting information related to the business case is recorded;
A graph creating unit that creates a risk display graph that positions each business case on a two-dimensional graph using the risk determination score and the accounting information for each of the business cases;
Further claims 1, characterized in that it comprises a to individual projects risk management apparatus according to any one of 3. The system further comprises a response policy determination unit that outputs, to a user terminal, advice prepared in advance regarding a response policy for a business item according to a position that each of the business items occupies in the risk display graph. 4. The individual case risk management device according to 4. A function to receive information identifying the ongoing business case and obtain credit information about the business partner company of each business case from an external database ;
A function of storing a scheduled date and an execution date in a memory for each of a plurality of milestones that are events related to a contract to be passed and a charge request as the business case progresses ;
A failure degree calculating unit that counts the number of times each business case has passed the milestone and the number of times the execution date of the milestone is delayed from the scheduled date, and adds these to calculate the degree of failure;
A risk judgment score, which is an index representing the stability of the business case and the certainty about price collection , by calculating a rating risk preset for the credit information and adding the rating risk and the failure degree A function for calculating
An individual project risk management program characterized in that a computer is executed.

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