JP5770961B2 - Credit behavior network mapping - Google Patents

Description

  The present disclosure relates to credit evaluation, and more specifically to credit behavior network mapping procedures.

  The approaches described in this section are approaches that can be pursued, but not necessarily approaches that were previously devised or pursued. Accordingly, unless indicated otherwise, the approaches described in this section cannot be prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.

  Conventional techniques for credit eligibility or credit score, such as the Fair Isaac Corporation (FICO) credit score, indicate the likelihood that a company will pay current liabilities. Lenders such as banks and credit card companies use credit scores to assess the potential risks posed by lending to consumers. The widespread use of credit scores has made credit more widely available and more accessible to consumers.

FIC O 及 beauty other similar techniques, to analyze the company financial history in order to generate a credit score. For example, FICO, the company payment history of credit of use, length of credit history, the credit of the type used, for example, installment, revolving, consumer finance and collateral, a recent survey of the credit, and Analyze special factors such as mortgages.

However, FICO assessments merely analyze a single company's financial history to generate a credit score . This is to limit the scope of the evaluation of FICO, further, it is not possible to recognize and consider factors associated with more global supply chain.

  Thus, there remains a need for a broader and global assessment of credit behavior for a company.

  Here, a credit behavior network mapping procedure is provided that evaluates cash flows, ie accounts receivable for the business.

  Receiving a first entity identifier; performing a first search of a database that returns an identifier of a second entity having a relationship with the first entity; and a second entity creditor Performing a second search of the database returning identifiers of the three entities, and a data structure defining a path between the first entity and the third entity via the second entity in the storage device There is further provided a method comprising building.

  Receiving a first entity identifier; performing a first search of a database that returns an identifier of a second entity that is a creditor of the first entity; and a creditor of the second entity. Performing a second search of a database returning an identifier of a third entity and data defining a path between the first entity and the third entity via the second entity in the storage device A method comprising building a structure is also provided.

  Receiving a first entity identifier, performing a first search of a database that returns a second entity identifier hierarchically related to the first entity, and being a creditor of the second entity A data structure defining a path between the first entity and the third entity through the second entity in the storage device, performing a second search of the database returning an identifier of the third entity Is further provided.

  Receiving a first entity identifier; performing a first search of a database that returns an identifier of a second entity that has made a credit inquiry on the first entity; and a second entity Performing a second search of a database that returns an identifier of a third entity that is a creditor of the device, and a path between the first entity and the third entity via the second entity in the storage device A method is also provided that includes building a data structure that defines

  Receiving a first entity identifier, performing a first search of a database that returns an identifier of a second entity that is a creditor of the first entity, and performing a credit inquiry on the second entity Performing a second search of the database that returns an identifier of a third entity that may be and defining a path between the first entity and the third entity via the second entity in the storage device There is further provided a method comprising:

  Receiving a first entity identifier; performing a first search of a database that returns identifiers of second entities hierarchically related to the first entity; and performing a credit query on the second entity Performing a second search of the database that returns the identifier of the third entity that has been, and in the storage device, the path between the first entity and the third entity via the second entity A method is also provided that includes building a defining data structure.

  There is further provided an apparatus for performing the method provided above. The apparatus includes a processor and a memory. The memory contains instructions that are readable by the processor and that, when read by the processor, cause the processor to perform the operations of the method steps described above.

  In addition, there are non-transitory storage media that contain instructions readable by a processor. The instructions, when read by the processor, cause the processor to perform the method operations described above.

FIG. 1 is a diagram illustrating a system for generating a credit behavior network map.

FIG. 2 is a diagram illustrating an example of the monetary relationship map.

FIG. 3 is a diagram showing another monetary relationship map.

FIG. 4 is a diagram illustrating another example of the financial relationship map.

FIG. 5 is a diagram illustrating a method for evaluating an entity's credit behavior.

FIG. 6 is a diagram illustrating a further method for evaluating an entity's credit behavior.

FIG. 7 is a diagram illustrating a further method for evaluating the credit behavior of an entity.

FIG. 8 is a diagram illustrating a further method for evaluating an entity's credit behavior.

FIG. 9 is a diagram illustrating a further method for evaluating the credit behavior of an entity.

  Components or features common to two or more drawings are indicated using the same reference numerals in each of the drawings.

The present disclosure describes a method and system for providing a forward-looking credit network map that provides financial data about a subject company by a plurality of monitoring companies with different degrees of separation thereto. The forward-looking credit network map, for example, to identify the credit failure at different points of the credit supply chain can associate their failure to the final impact on the company's management of the subject, to provide a financial model .

Referring to the drawings, and in particular in FIG. 1, a system 100 for generating a credit behavior network map is provided. The system 100 includes a computer 105 connected to a user terminal 130 and a plurality of databases via a network 135.

The database can be one or more physical databases. Collectively, the database includes credit reference 137, transaction data 140, business association 145, business parameters 150, multiple financial network maps 155, and output parameters 160.

Computer 105 includes a processor 110 that communicates with a memory 115. The memory 115 includes a program module 120. The processor 110 is configured by a logic circuit that executes an instruction in response to the instruction. The term “module” is used herein to describe a functional operation that may be embodied as either a stand-alone component or an integrated configuration of multiple subcomponents.

  Although system 100 is described herein as having instructions for the disclosed method installed in memory 115, instructions are stored on an external computer readable storage medium 125 for later loading into memory 115. Can be tangible and embodied. Storage medium 125 includes, but is not limited to, floppy disk, compact disk, magnetic tape, read-only memory, optical storage medium, universal serial bus (USB) flash drive, digital versatile disk, or zip drive. It can be any conventional storage medium that is not. The instructions may also be incorporated into random access memory or other types of electronic storage residing on the remote storage system and coupled to memory 115.

Further, although program module 120 is described herein as being installed in memory 115 and consequently implemented in software, program module 120 is hardware (eg, electronic circuitry), firmware, software Or any combination thereof.

The credit inquiry 137 typically stores data such as a request by a lending institution, landowner, or business owner seeking to examine the credit history for the subject company. In addition, the credit inquiry 137 may include requests from third parties for credit history, for example, future lenders. The credit query 137 typically stores data indexed by the company for which credit history is requested, eg, the target company.

  Transaction data 140 includes financial data about the company, such as account receivable data. Accounts receivable data is information such as the amount to be paid to a particular company's debtor. In addition, the receivable data identifies the entity as a debtor to the creditor and indicates the amount of credit. Accounts receivable data is typically indexed according to creditor information, and in particular includes accounts receivable for the target company's suppliers. The processor 110 receives account receivable data from the company under the instruction of the program module 120 and inputs it into the transaction data 140.

The business association 145 includes business relationship data regarding the target company. The business relationship data is a hierarchical relationship between affiliates of the target company and also between affiliates of the target company's suppliers. For example, the business relationship 145 includes a hierarchical relationship identifier such as a parent company, a subsidiary, a branch, a business partner, and an affiliated company that is neither a parent company nor a subsidiary, eg, a company that has a common parent company.

Business parameters 150, including about a company, bankruptcy data, company of demographic data, query data, and the market capitalization data. Bankruptcy data includes indicators about suppliers that are bankrupt. Company demographic data includes company data such as number of employees, industry type and size. The inquiry data includes information about companies that make inquiries about the target company, and the number of companies that make inquiries about the target company, for example, numerical values. Market capitalization data includes company market capitalization information for various time periods, eg, daily, weekly, and monthly.

The plurality of financial network maps 155 includes a financial relationship map for the target company and related companies separated by different degrees of separation. Typically, a financial relationship map represents cash flow signals and trends for suppliers and supplier suppliers related to the target company. Supplier is a company that provides goods or services to the target company. Suppliers include utilities, temporary staffing agencies, and office suppliers. In addition, the financial relationship map may include hierarchically related companies, as well as hierarchically related company suppliers and supplier suppliers. 2 to 4 discussed below are examples of financial relationship maps .

The output parameter 160 is a result of evaluation of the target entity . For example, the output parameter 160 may include a change in market capitalization or a delta value for the subject entity .

  The user terminal 130 is an input / output device that can receive input from the user and output the result to the user. For example, user terminal 130 may include a keyboard or voice recognition subsystem that allows the user to communicate information and command selections to processor 110. The user terminal 130 also includes an output device such as a display or a printer. A cursor control, such as a mouse, trackball, or joystick, allows the user to manipulate the cursor on the display to communicate additional information and command selections to the processor 110.

  FIG. 2 is an example of a financial relationship map, for example, a credit network map 200. Credit network map 200 shows a supply of credit associated with a global supply chain, eg, a particular company of interest, ie, entity 205. Credit network map 200 specifically shows companies that share different degrees of separation in relation to entity 205. Financial information provided by various points in the global supply chain of credit, such as a company, ultimately affects the financial health of entity 205, eg, credit risk of entity 205.

  Companies in the global supply chain that share different degrees of separation for entities 205 include companies such as creditors, hierarchically related companies, and industry peers. The financial health for each of these companies in turn can provide an early credit risk warning for entity 205.

The creditors of entity 205 include entity 210 and entity 220 . Credit network map 200 comprises further a plurality of companies in the global supply chain, for example, a plurality of creditors creditors. Entity 215 is a creditor of entity 210, entity 225 is a creditor of entity 220, and entity 240 is a creditor of entity 235. Entity 215, entity 225, and are each connected dashed entity 240, creditors in the global supply chain, representing the number of unrestricted plurality of creditors. That is, the credit network map 200 can be expanded to include related companies of any desired depth or width.

  A company having a hierarchical relationship with entity 205 includes entity 230. This hierarchical relationship may include a parent company relationship, a subsidiary relationship, or an affiliate relationship that is neither a parent company nor a subsidiary. As shown, entity 230 is a subsidiary of entity 205.

  In addition, the credit network map 200 includes a peer 250 that is the peer of the entity 205. The peer 250 is a company from the same industry as the entity 205 and is summarized as a comparison group with the entity 205.

Processor 110 executes instructions from program module 120 to create a financial network map 155, such as a credit network map 200.

  For example, instructions from program module 120 cause processor 110 to receive an identifier of a first entity and perform a first search of a database that returns an identifier of a second entity that has a relationship with the first entity. , Causing a second search of the database to return the identifier of the third entity that is the creditor of the second entity. The instructions further cause the processor 110 to construct a data structure in the storage device that defines a path between the first entity and the third entity via the second entity.

Referring to credit network map 200, the first entity can be entity 205, the second entity can be entity 210, and the third entity can be entity 215. First search is to return the identifier of the entity 210, a second search is to return an identifier of the entity 215, entity 215 as described above, for example, the third entity, the entity 210, for example, the second entity Creditors. The relationship between entity 210 and entity 205 is that entity 210 is an entity 205 creditor. Credit network map 200 further illustrates a data structure that defines a path between entity 205 and entity 215 via entity 210.

Program modules 120 instructions from further directs the processor 110, a third entity, for example the entity 21 5, characteristic, for example in accordance with the cash flow of the first entity, for example entity 205, properties such evaluation credit risk Can be.

In addition, the first search, a second entity, for example, from an entity 210, a first entity, for example to give Shi returns the first amount of donated credit entity 205, a second search, the third entity, for example, from an entity 215, may return the second entity, for example, the second amount of credits granted to the entity 210.

In further embodiments, the second entity may be hierarchically related to the first entity. For example, the second entity may be entity 230, a subsidiary of entity 205. Accordingly, the processor 110 executes the first search database, to return the identifier of the second entity, the processor 110 to return the identifier of the entity 2 3 0, execution processor 110 a second search of the database However, if returning the identifier of the third entity, the processor returns the identifier of the entity 235.

  FIG. 3 shows another financial relationship map, for example, a credit network map 300.

Credit network map 300 is another embodiment of a global financial chain associated with entity 205. In particular, the credit network map 300 further shows a referral company that demonstrates interest in the entity 205 or the entity 230 by a credit inquiry, and also a company associated with the referral company, eg, a creditor of the referral company. In the credit network map 300, the entity 305 is a person who makes a credit inquiry of the entity 205, and the entity 310 is a creditor of the entity 305. Entity 315 is also the person making the credit inquiry of entity 205, and entity 320 is the creditor of entity 315. The entity 325 is a person who performs a credit inquiry of the entity 230, and the entity 330 is a creditor of the entity 325.

  The processor 110 executes instructions from the program module 120 to create a financial network map 155 such as the credit network map 300. The instructions from the program module 120 that cause the processor 110 to create the credit network map 200 described above are similarly used to create the credit network map 300.

  In particular, the instructions cause processor 110 to receive an identifier of a first entity, perform a first search of a database that returns an identifier of a second entity that has a relationship with the first entity, and the second entity Performing a second search of the database that returns the identifier of the third entity that is the creditor of the bank, and defining a path between the first entity and the third entity via the second entity in the storage device To build a data structure. Further, the instructions may cause the processor 110 to evaluate the characteristics of the first entity according to a function of the characteristics of the third entity.

For example, the identifier of the first entity may be the identifier of entity 205. The first search returns an identifier of an entity 305, eg, a second entity that has a relationship with the first entity. The relationship between the entity 205 and the entity 305 is that the entity 305 is a person who makes a trust inquiry for the entity 205. A second search of the database returns an identifier of the third entity that is the creditor of the entity 310, eg, the second entity. In addition, the second search returns the amount of credit granted from entity 310 to entity 305. Credit network map 300 further illustrates a data structure that defines a path between entity 205, eg, a first entity, and entity 310, eg, a third entity, via entity 305, eg, a second entity. Credit network map 300 may further include an identifier for entity 205, an identifier for entity 305, an identifier for entity 310, and an amount of credit awarded from entity 310 to entity 305.

  In a further embodiment, instructions from program module 120 cause processor 110 to receive an identifier of a first entity and to return an identifier of a second entity that is hierarchically related to the first entity. Causing the search to perform a second search of the database that returns an identifier of a third entity that has made a credit query for the second entity, and the first through the second entity at the storage device Build a data structure that defines the path between the entity and the third entity. Further, the instructions may cause the processor 110 to evaluate characteristics for the first entity according to a function of the characteristics of the third entity.

For example, the first entity is entity 205 and the second entity is 230. Since entity 230 is a subsidiary of entity 205, entity 230 is hierarchically related to entity 205. Second search, because the entity 325 makes a credit inquiry on entity 230 may return an identifier of an entity 325. The credit network map 300 shows a data structure that defines a path between an entity 205, eg, a first entity, and an entity 325, eg, a third entity, via the entity 230, eg, a second entity. Further, the characteristic may be a credit risk of entity 205 that follows a function of the characteristic of entity 325.

  FIG. 4 is another example of a financial relationship map, for example, a credit network map 400.

  Credit network map 400 shows the global supply chain, eg, the supply of credits, associated with a particular company of interest, ie entity 205. Credit network map 400 specifically shows companies that share different degrees of separation in relation to entity 205, such as entity 405 and entity 410. The entity 405 is a creditor of the entity 205, and the entity 410 is a person who makes a credit inquiry about the entity 405.

The processor 110 executes instructions from the program module 120 to create the credit network map 400.

  In particular, the instructions cause the processor 110 to receive the identifier of the first entity, perform a first search of the database that returns the identifier of the second entity that is the creditor of the first entity, and the second entity Performing a second search of the database that returns an identifier of a third entity that has made a credit inquiry on the storage device, between the first entity and the third entity via the second entity in the storage device Build a data structure that defines the path of the.

  For example, referring to FIG. 4, the identifier of the first entity is entity 205. The first search returns an identifier of entity 405, eg, the creditor of the first entity. The second search returns an identifier of a third entity that has made a credit inquiry for entity 410, eg, entity 405 (second entity). In addition, FIG. 4 shows a data structure that defines the path between the entity 205 and the entity 410 via connection lines, constructed in the storage device.

In further embodiments, the instructions may further cause the processor 110 to evaluate the characteristics of the first entity according to a function of the characteristics of the third entity. In addition, the first search may also if obtained Shi returns a first value of credits from the second entity is provided to the first entity, the processor builds a data structure, the processor further includes a first An entity identifier, a second entity identifier, a third entity identifier, and a credit amount may be included.

  For example, the processor 110 may evaluate the credit risk characteristics of the entity 205, ie, the first entity, according to a function of the credit risk of the entity 410, ie, the third entity.

  FIG. 5 is a method 500 for evaluating the credit behavior of an entity.

  In particular, the method 500 relates to the relationships between entities shown in the financial relationship map 200 of FIG. In particular, method 500 relates to the relationship between entity 205, entity 210, and entity 215. Entity 210 is a creditor of entity 205, and entity 215 is a creditor of entity 210.

  Method 500 begins at step 505. Step 505 provides for receiving an identifier of a first entity, eg, entity 205. After step 505, method 500 proceeds to step 510.

  Step 510 provides searching the database for a second entity that is a creditor of the first entity, eg, entity 210. After step 510, method 500 proceeds to step 515.

  Step 515 provides searching the database for a third entity that is a creditor of the second entity, eg, entity 215. After step 515, method 500 proceeds to step 520.

  Step 520 provides for building a data structure that defines a path between the first entity and the third entity via the second entity. After step 510, method 500 proceeds to step 525.

  Step 525 provides for evaluating the characteristics of the first entity according to a function of the characteristics of the third entity. After step 525, method 500 ends.

  FIG. 6 is a further method, namely a method 600 for evaluating the credit behavior of an entity.

  In particular, the method 600 relates to the relationships between entities shown in the financial relationship map 200 of FIG. In particular, method 600 relates to the relationship between entity 205, entity 230, and entity 235. Entity 230 is hierarchically related to entity 205, and entity 235 is a creditor of entity 230.

  Method 600 begins at step 605. Step 605 provides for receiving an identifier of a first entity, eg, entity 205. After step 605, method 600 proceeds to step 610.

  Step 610 provides searching the database for a second entity that is hierarchically related to the first entity, eg, entity 230. After step 610, method 600 proceeds to step 615.

  Step 615 provides searching the database for a third entity that is a creditor of the second entity, eg, entity 235. After step 615, method 600 proceeds to step 620.

  Step 620 provides for building a data structure that defines a path between the first entity and the third entity via the second entity. After step 620, method 600 proceeds to step 625.

  Step 625 provides for evaluating the characteristics of the first entity according to a function of the characteristics of the third entity. After step 625, method 600 ends.

  FIG. 7 is a further method for evaluating the credit behavior of an entity.

  In particular, the method 700 relates to the relationship between entities shown in the financial relationship map 300 of FIG. In particular, method 700 relates to the relationship between entity 205, entity 305 and entity 310. The entity 305 is a person who makes a credit inquiry about the entity 205, and the entity 310 is a creditor of the entity 305.

  Method 700 begins at step 705. Step 705 provides for receiving an identifier of a first entity, eg, entity 205. After step 705, method 700 proceeds to step 710.

  Step 710 provides searching the database for a second entity, such as entity 305, that has made a credit inquiry for the first entity. After step 710, method 700 proceeds to step 715.

  Step 715 provides searching the database for a third entity that is a creditor of the second entity, eg, entity 310. After step 715, method 700 proceeds to step 720.

  Step 720 provides for building a data structure that defines a path between the first entity and the third entity via the second entity. After step 720, method 700 proceeds to step 725.

  Step 725 provides evaluating the characteristics of the first entity according to a function of the characteristics of the third entity. After step 725, method 700 ends.

  FIG. 8 is a further method for evaluating the credit behavior of an entity.

  In particular, the method 800 relates to the relationships between entities shown in the financial relationship map 400 of FIG. In particular, method 800 relates to the relationship between entity 205, entity 405, and entity 410. The entity 405 is a creditor of the entity 205, and the entity 410 is a person who makes a credit inquiry about the entity 405.

  Method 800 begins at step 805. Step 800 provides for receiving an identifier of a first entity, eg, entity 205. After step 805, method 800 proceeds to step 810.

  Step 810 provides searching the database for a second entity that is a creditor of the first entity, eg, entity 405. After step 810, method 800 proceeds to step 815.

  Step 815 provides searching the database for a third entity, such as entity 410, that has made a credit inquiry for the second entity. After step 815, method 800 proceeds to step 820.

  Step 820 provides for building a data structure that defines a path between the first entity and the third entity via the second entity. After step 820, method 800 proceeds to step 825.

  Step 825 provides for evaluating the characteristics of the first entity according to a function of the characteristics of the third entity. After step 825, method 800 ends.

  FIG. 9 is a further method for evaluating the credit behavior of an entity.

  In particular, the method 900 relates to the relationship between entities shown in the financial relationship map 300 of FIG. In particular, method 900 relates to the relationship between entity 205, entity 230, and entity 325. Entity 230 is hierarchically related to entity 205, and entity 325 is a person who makes a credit inquiry for entity 230.

  Method 900 begins at step 905. Step 905 provides for receiving an identifier of a first entity, eg, entity 205. After step 905, method 900 proceeds to step 910.

  Step 910 provides searching the database for a second entity that is hierarchically related to the first entity, eg, entity 230. After step 910, method 900 proceeds to step 915.

  Step 915 provides searching the database for a third entity that has made a credit inquiry for the second entity, eg, entity 325. After step 915, method 900 proceeds to step 920.

  Step 920 provides for building a data structure that defines a path between the first entity and the third entity via the second entity. After step 920, method 900 proceeds to step 925.

  Step 925 provides for evaluating the characteristics of the first entity according to a function of the characteristics of the third entity. After step 925, method 900 ends.

The techniques described herein are illustrative and should not be construed as implying any particular limitation to the present disclosure. It should be understood that various alternatives, combinations, and modifications can be devised by those skilled in the art. For example, the steps associated with the processes described herein may be performed in any order unless otherwise explicitly or otherwise indicated by the steps themselves. The present disclosure is intended to include all such alternatives, modifications and variations that fall within the scope of the appended claims.

Claims (40)

A computer-implemented method for creating a credit behavior network map between a plurality of entities, the method comprising:
Receiving an identifier of the first entity;
And performing a first search of the at least one database returns an identifier of the first entity and the second entity Ru creditors der chromatic vital the business relationship first entity,
And performing a second search of the at least one database returns an identifier of the third entity Ru creditors der of the second entity,
In a storage device, defining the credit behavior network map based on the identifier of the first entity, the identifier of the second entity, and the identifier of the third entity; and Building a data structure comprising a path between the first entity and the third entity via an entity;
Using the processor of the computer according to instructions read from the memory of the computer associated with the processor for determining the risk of the first entity based on the financial characteristics of the third entity A method comprising: A computer-implemented method for creating a credit behavior network map between a plurality of entities, the method comprising:
Receiving an identifier of the first entity;
And performing a first search of the at least one database returns an identifier of the first entity and the second entity Ru creditors der chromatic vital the business relationship first entity,
And performing a second search of the at least one database returns an identifier of the third entity Ru creditors der of the second entity,
In the storage device, and the identifier of the first entity, and the identifier of the second entity, based on said identifier of the third entity, to define the credit behavior network map, the second Building a data structure comprising a path between the first entity and the third entity via an entity. A computer-implemented method for creating a credit behavior network map between a plurality of entities, the method comprising:
Receiving an identifier of the first entity;
And performing a first search of the at least one database returns an identifier of the second entity you hierarchically related business on relationship with the first entity to the chromatic vital the first entity,
Performing a second search of the at least one database that returns an identifier of a third entity that is a creditor of the second entity;
In the storage device, and the identifier of the first entity, and the identifier of the second entity, based on said identifier of the third entity, to define the credit behavior network map, the second comprising a path between the first entity via the entity and the third entity, a method and a building a data structure. A computer-implemented method for creating a credit behavior network map between a plurality of entities, the method comprising:
Receiving an identifier of the first entity;
Performing a first search of the at least one database database returns an identifier of the first entity and Kotogaa Ru second entity a business relationship was credit authorization for chromatic vital said first entity To do
Performing a second search of the at least one database that returns an identifier of a third entity that is a creditor of the second entity;
In a storage device, the first entity via the second entity based on the identifier of the first entity, the identifier of the second entity, and the identifier of the third entity how comprising this and city where the path defines the between the third entity, constructing a data structure. A computer-implemented method for creating a credit behavior network map between a plurality of entities, the method comprising:
Receiving an identifier of the first entity;
Performing a first search of at least one database that returns an identifier of a second entity that is a creditor of the first entity;
Performing a second search of the at least one database that returns an identifier of a third entity that has made a credit inquiry on the second entity;
In the storage device, and the identifier of the first entity, and the identifier of the second entity, based on said identifier of the third entity, to define the credit behavior network map, the second comprising a path between the first entity via the entity and the third entity, a method and a building a data structure. A computer-implemented method for creating a credit behavior network map between a plurality of entities, the method comprising:
Receiving an identifier of the first entity;
Performing a first search of at least one database that returns an identifier of a second entity hierarchically related to the first entity;
Performing a second search of the at least one database that returns an identifier of a third entity that has made a credit inquiry on the second entity;
In the storage device, and the identifier of the first entity, and the identifier of the second entity, based on said identifier of the third entity, to define the credit behavior network map, and the second Building a data structure comprising a path between the first entity and the third entity via a plurality of entities. The relationship is that the second entity has made a credit inquiry for the first entity.
The method according to claim 1 or 2. The first search further returns a first amount of credits granted to the first entity from the second entity;
The second search further returns a second amount of credits provided from the third entity to the second entity;
To the building, in the data structure, (a) the identifier of the first entity, (b) the identifier of the second entity, (c) the identifier of the third entity, (d) A first amount of the credit; and (e) a second amount of the credit.
The method according to claim 1. The second search further returns an amount of credits from the third entity to the second entity;
The constructing includes: (a) the identifier of the first entity; (b) the identifier of the second entity; (c) the identifier of the third entity; and (d ) Including the amount of the credit,
The method according to claim 1. The first search further returns a first amount of credits granted to the first entity from the second entity;
The second search further returns a second amount of credits provided from the third entity to the second entity;
The constructing includes a first amount of the credit and a second amount of the credit in the data structure;
The method according to claim 1. The first search may further return the amount of credits granted to the first entity from the second entity, or
The second search further returns an amount of credits from the third entity to the second entity;
The constructing includes an amount of the credit in the data structure;
The method according to claim 1. The method according to any of claims 1 to 11, further comprising: evaluating the characteristics of the first entity according to a function of the characteristics of the third entity.   13. A method according to any of claims 1 to 12, wherein the risk of the first entity is a credit risk of the first entity. 14. A method as claimed in any preceding claim, wherein the data structure represents a plurality of financial relationship maps showing cash flow signals and trends for the target company's suppliers and supplier suppliers. A processor;
When readable by the processor and read by the processor, the processor
Receiving the identifier of the first entity;
Performing a first search of the at least one database returns an identifier of the first entity and the second entity Ru creditors der chromatic vital the business relationship first entity,
Performing a second search of the at least one database that returns an identifier of a third entity that is a creditor of the second entity;
In the storage device, and the identifier of the first entity, and the identifier of the second entity, based on said identifier of the third entity, to define the credit behavior network map, the second Constructing a data structure comprising a path between the first entity and the third entity via an entity;
And a memory containing instructions for performing an operation to determine a risk of the first entity based on financial characteristics of the third entity. A processor;
When readable by the processor and read by the processor, the processor
Receiving the identifier of the first entity;
Performing a first search of the at least one database returns an identifier of the first has a business on the relationship between the entity and the second entity Ru creditors der of the first entity,
Performing a second search of the at least one database that returns an identifier of a third entity that is a creditor of the second entity;
In a storage device, a credit behavior network map is defined based on the identifier of the first entity, the identifier of the second entity, and the identifier of the third entity, and the second entity An apparatus comprising: a memory containing instructions for performing an operation to construct a data structure, comprising a path between the first entity and the third entity through an entity. A processor;
When readable by the processor and read by the processor, the processor
Receiving the identifier of the first entity;
Performing a first search of at least one database that returns an identifier of a second entity hierarchically related to the first entity;
Performing a second search of the at least one database that returns an identifier of a third entity that is a creditor of the second entity;
In a storage device, a credit behavior network map is defined based on the identifier of the first entity, the identifier of the second entity, and the identifier of the third entity, and the second entity An apparatus comprising: a memory containing instructions for performing an operation to construct a data structure, comprising a path between the first entity and the third entity through an entity. A processor;
When readable by the processor and read by the processor, the processor
Receiving the identifier of the first entity;
Performing a first search of the at least one database returns an identifier of the second entity may be performed credit authorization for said first entity,
Performing a second search of the at least one database that returns an identifier of a third entity that is a creditor of the second entity;
In a storage device, a credit behavior network map is defined based on the identifier of the first entity, the identifier of the second entity, and the identifier of the third entity, and the second entity An apparatus comprising: a memory containing instructions for performing an operation to construct a data structure, comprising a path between the first entity and the third entity through an entity. A processor;
When readable by the processor and read by the processor, the processor
Receiving the identifier of the first entity;
Performing a first search of at least one database that returns an identifier of a second entity that is a creditor of the first entity;
Performing a second search of the at least one database that returns an identifier of a third entity that has made a credit inquiry about the second entity;
In a storage device, a credit behavior network map is defined based on the identifier of the first entity, the identifier of the second entity, and the identifier of the third entity, and the second entity An apparatus comprising: a memory containing instructions for performing an operation to construct a data structure, comprising a path between the first entity and the third entity through an entity. A processor;
When readable by the processor and read by the processor, the processor
Receiving the identifier of the first entity;
Performing a first search of at least one database that returns an identifier of a second entity hierarchically related to the first entity;
Performing a second search of the at least one database that returns an identifier of a third entity that has made a credit inquiry about the second entity;
In a storage device, a credit behavior network map is defined based on the identifier of the first entity, the identifier of the second entity, and the identifier of the third entity, and the second entity An apparatus comprising: a memory containing instructions for performing an operation to construct a data structure, comprising a path between the first entity and the third entity through an entity. The relationship is that the second entity has made a credit inquiry for the first entity.
The apparatus according to claim 15 or 16. The first search further returns a first amount of credits granted to the first entity from the second entity;
The second search further returns a second amount of credits provided from the third entity to the second entity;
The constructing includes a first amount of the credit and a second amount of the credit in the data structure;
Device according to any of claims 15 to 21. The first search may further return the amount of credits granted to the first entity from the second entity, or
The second search further returns an amount of credits from the third entity to the second entity;
The constructing includes an amount of the credit in the data structure;
Device according to any of claims 15 to 21. The instructions are sent to the processor,
24. The apparatus according to any one of claims 15 to 23, further causing an operation to evaluate a characteristic of the first entity according to a function of the characteristic of the third entity.   25. The apparatus according to any of claims 15 to 24, wherein the risk of the first entity is a credit risk of the first entity. 26. An apparatus according to any of claims 15 to 25, wherein the data structure represents a plurality of financial relationship maps showing cash flow signals and trends for a target company supplier and supplier supplier. When readable by and read by the processor, the processor
Receiving the identifier of the first entity;
Performing a first search of the at least one database returns an identifier of the first has a business on the relationship between the entity and the second entity Ru creditors der of the first entity,
Performing a second search of the at least one database that returns an identifier of a third entity that is a creditor of the second entity;
In a storage device, the first entity via the second entity based on the identifier of the first entity, the identifier of the second entity, and the identifier of the third entity defining a torque credit behavior network map comprises a route between the third entity and to build a data structure,
A non-transitory storage medium comprising instructions for performing an operation to determine a risk of the first entity based on financial characteristics of the third entity. When readable by and read by the processor, the processor
Receiving the identifier of the first entity;
Performing a first search of the at least one database returns an identifier of the first has a business on the relationship between the entity and the second entity Ru creditors der of the first entity,
Performing a second search of the at least one database that returns an identifier of a third entity that is a creditor of the second entity;
In a storage device, a credit behavior network map is defined based on the identifier of the first entity, the identifier of the second entity, and the identifier of the third entity, and the second entity A non-transitory storage medium comprising instructions for performing an operation of constructing a data structure comprising a path between the first entity and the third entity via an entity. When readable by and read by the processor, the processor
Receiving the identifier of the first entity;
Performing a first search of at least one database that returns an identifier of a second entity hierarchically related to the first entity;
Performing a second search of the at least one database that returns an identifier of a third entity that is a creditor of the second entity;
In a storage device, a credit behavior network map is defined based on the identifier of the first entity, the identifier of the second entity, and the identifier of the third entity, and the second entity A non-transitory storage medium comprising instructions for performing an operation of constructing a data structure comprising a path between the first entity and the third entity via an entity. When readable by and read by the processor, the processor
Receiving the identifier of the first entity;
Performing a first search of the at least one database returns an identifier of the second entity may be performed credit authorization for said first entity,
Performing a second search of the at least one database that returns an identifier of a third entity that is a creditor of the second entity;
In a storage device, a credit behavior network map is defined based on the identifier of the first entity, the identifier of the second entity, and the identifier of the third entity, and the second entity comprising a path between the first entity via the entity and the third entity, it builds a data structure
Non-transitory storage medium comprising instructions to execute the operation. When readable by and read by the processor, the processor
Receiving the identifier of the first entity;
Performing a first search of at least one database that returns an identifier of a second entity that is a creditor of the first entity;
Performing a second search of the at least one database that returns an identifier of a third entity that has made a credit inquiry about the second entity;
In a storage device, a credit behavior network map is defined based on the identifier of the first entity, the identifier of the second entity, and the identifier of the third entity, and the second entity A non-transitory storage medium comprising instructions for performing an operation of constructing a data structure comprising a path between the first entity and the third entity via an entity. When readable by and read by the processor, the processor
Receiving the identifier of the first entity;
Performing a first search of at least one database that returns an identifier of a second entity hierarchically related to the first entity;
Performing a second search of the at least one database that returns an identifier of a third entity that has made a credit inquiry about the second entity;
In a storage device, a credit behavior network map is defined based on the identifier of the first entity, the identifier of the second entity, and the identifier of the third entity, and the second entity A non-transitory storage medium comprising instructions for performing an operation of constructing a data structure comprising a path between the first entity and the third entity via an entity. The relationship is that the second entity has made a credit inquiry for the first entity.
The non-transitory storage medium according to claim 27 or 28. The first search further returns a first amount of credits granted to the first entity from the second entity;
The second search further returns a second amount of credits provided from the third entity to the second entity;
To the building, in the data structure, (a) the identifier of the first entity, (b) the identifier of the second entity, (c) the identifier of the third entity, (d) A first amount of the credit; and (e) a second amount of the credit.
The non-transitory storage medium according to any one of claims 27 to 33. The second search further returns an amount of credits from the third entity to the second entity;
The constructing includes: (a) the identifier of the first entity; (b) the identifier of the second entity; (c) the identifier of the third entity; and (d ) Including the amount of the credit,
The non-transitory storage medium according to any one of claims 27 to 33. The first search further returns a first amount of credits granted to the first entity from the second entity;
The second search further returns a second amount of credits provided from the third entity to the second entity;
The constructing includes a first amount of the credit and a second amount of the credit in the data structure;
The non-transitory storage medium according to any one of claims 27 to 33. The first search may further return the amount of credits granted to the first entity from the second entity, or
The second search further returns an amount of credits from the third entity to the second entity;
The constructing includes an amount of the credit in the data structure;
The non-transitory storage medium according to any one of claims 27 to 33. The instructions are sent to the processor,
38. A non-transitory storage medium according to any of claims 27 to 37, further causing an operation to evaluate a characteristic of the first entity according to a function of the characteristic of the third entity.   39. A non-transitory storage medium according to any of claims 27 to 38, wherein the risk of the first entity is a credit risk of the first entity. 40. A non-transitory storage medium according to any of claims 27 to 39, wherein the data structure represents a plurality of financial relationship maps indicating cash flow signals and trends for the target company's suppliers and supplier suppliers.

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