Patent Publication Number: US-7912865-B2

Title: System and method for linking multiple entities in a business database

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is based upon and claims the benefit of priority from U.S. Provisional Patent Application No. 60/847,177 filed on Sep. 26, 2006, the entire contents of which are incorporated herein by reference. All publications and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication or patent application was specifically and individually indicated to be incorporated by reference. 
    
    
     TECHNICAL FIELD 
     This disclosure generally relates to financial data processing, and more particularly to improved methods and systems for identifying multiple businesses owned by a single ownership entity. 
     DESCRIPTION OF RELATED ART 
     Various financial service providers provide credit accounts such as mortgages, automobile loans, credit card accounts, and the like, to consumers and businesses. In determining whether to extend credit to an applicant and under what terms, the financial service providers may rely upon financial data related to the credit activities, current assets, and current liabilities of the consumer. Commonly, this information is provided in the form of a credit score or with a report. 
     SUMMARY OF DISCLOSURE 
     A system is described to provide additional relevant information to a financial service provider in order to allow that provider to make improved decisions. According to one embodiment, the system determines whether an applicant owns multiple businesses and provides information related to those businesses. Throughout this disclosure, a single ownership entity that owns more than one business is referred to as a multiple-business owner. 
     Multiple-business owners may be inaccurately characterized in traditional credit reports. For example, an individual applying for a business loan for a first business may have little or no credit history with that business. As a result, a traditional credit score or report may indicate that the individual is a significant risk, which may limit the terms of any credit offers. If the individual owns several other businesses that have good credit histories or significant assets, that individual may actually be significantly less of a risk than the traditional report indicates. Advantageously, certain embodiments allow a financial service provider to find other businesses owned by a multiple-business owner in order to more accurately assess the level of risk associated with that applicant. Of course, the opposite situation may occur as well. If an individual that appears to have good credit is found to own several businesses that have failed to make payments, defaulted, or otherwise engaged in negative credit activities, then the financial service provider may be able to determine that fact and adjust its credit offerings accordingly. 
     Accordingly, embodiments of a system and method are described for determining whether an applicant is a multiple-business owner and for providing information related to multiple-business owners to a financial service provider or other client. According to one embodiment, business data is collected from one or more sources, and business records are stored. Business owners are associated with each business record. Those business owners associated with multiple business records are identified as potential multiple-business owners. Business records are compared with other records associated with the same ownership entity, and are filtered to remove multiple records identifying the same business. Multiple records may identify the same business when, for example, a business has multiple locations or has multiple “doing business as” names. The filtered records are stored in a database of multiple-business records. The financial service provider may request information related to one or more applicants. The serve provider&#39;s request is matched with the database of stored multiple-business records, and a report is provided to the financial service provider identifying whether the applicants are multiple-business owners and credit data related to the additional businesses. 
     According to some embodiments, a computer implemented method for filtering a business database comprising a plurality of records to determine which of the records correspond to multiple business entities having a common business owner is disclosed. The method comprises accessing the business database and selecting one of the plurality of records that is associated with a business owner. It is determined whether any of the other records are associated with the business owner, and the selected record and each of the other records determined to be associated with the business owner are extracted if it is determined that there are other records associated with the business owner. The selected record is dropped if it is determined that there are no other records associated with the business owner. These steps may be repeated for each of the records until each of the records have been extracted or dropped. A multiple-business owner data set is generated from the extracted records and at least a portion of the multiple-business owner data set is delivered to a client. 
     According to some embodiments, a computing system is disclosed. The computing system comprises a business database comprising a plurality of business records. The business records comprises a business owner field and at least one identifying field. A multiple-business owner filter is provided that is configured to access the business database and select a subset of the plurality of business records that have recurring business owner fields. The system further comprises a false-positive filter configured to access the subset and identify multiple-business owner records based at least in part on the at least one identifying field. The system additionally comprises a multiple-business owner link database configured to store the multiple-business owner records identified by the false-positive filter. 
     These and additional embodiments are discussed in greater detail below. Numerous other advantages and features of the present invention will become readily apparent from the following detailed description of the invention and the embodiments thereof, from the claims and from the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The objects, features and advantages of the present invention will be more readily appreciated upon reference to the following disclosure when considered in conjunction with the accompanying drawings and examples which form a portion of the specification, in which: 
         FIG. 1  is a block diagram of a system for linking multiple businesses owned by a single entity according to one embodiment; 
         FIG. 2A  shows sources of business data in a business identification database according to one embodiment; 
         FIG. 2B  shows sources of business association data in a business association database according to one embodiment; 
         FIGS. 3A-C  are examples of related business data entries in a business identification database according to one embodiment; 
         FIG. 4  is a system flow chart showing the processing of business records to determine related businesses according to one embodiment; 
         FIG. 5  is a flow chart showing a process for creating a business association database according to one embodiment; 
         FIG. 6  is a flow chart showing a process for filtering a business association database according to one embodiment; 
         FIG. 7  is a flow chart showing a process for creating a multiple-business owner list file according to one embodiment; 
         FIG. 8  is a visual representation of multiple businesses owned by a multiple-business owner according to one embodiment; 
         FIG. 9  is a report showing the number of records dropped and the drop criteria according to one embodiment; and 
         FIG. 10  is a report showing the distribution of businesses per business owner according to one embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     Embodiments of the invention will now be described with reference to the accompanying figures, wherein like numerals refer to like elements throughout. The terminology used in the description presented herein is not intended to be interpreted in any limited or restrictive manner, simply because it is being utilized in conjunction with a detailed description of certain specific embodiments of the invention. Furthermore, embodiments of the invention may include several novel features, no single one of which is solely responsible for its desirable attributes or which is essential to practicing the inventions herein described. 
       FIG. 1  is one embodiment of a block diagram of a computing system  100  that is in communication with a network  160  and various systems that are also in communication with the network  160 . The computing system  100  may be used to implement certain systems and methods described herein. For example, the computing system  100  may be configured to receive financial and demographic information regarding individuals and generate reports and/or alerts for one or more clients. Although the description provided herein refers to individuals, consumers, or customers, the terms “individual,” “consumer,” and “customer” should be interpreted to include applicants, or groups of individuals or customers or applicants, such as, for example, married couples or domestic partners, and business entities. The functionality provided for in the components and modules of computing system  100  may be combined into fewer components and modules or further separated into additional components and modules. 
     The computing system  100  includes, for example, a personal computer that is IBM, Macintosh, or Linux/Unix compatible. In one embodiment, the computing system  100  comprises a server, a laptop computer, a cell phone, a personal digital assistant, a kiosk, or an audio player, for example. In one embodiment, the exemplary computing system  100  includes a central processing unit (“CPU”)  105 , which may include a conventional microprocessor. The computing system  100  further includes a memory  130 , such as random access memory (“RAM”) for temporary storage of information and a read only memory (“ROM”) for permanent storage of information, and a mass storage device  120 , such as a hard drive, diskette, or optical media storage device. Typically, the modules of the computing system  100  are connected to the computer using a standards based bus system. In different embodiments, the standards based bus system could be Peripheral Component Interconnect (“PCI”), Microchannel, SCSI, Industrial Standard Architecture (“ISA”) and Extended ISA (“EISA”) architectures, for example. 
     The computing system  100  is generally controlled and coordinated by operating system software, such as Windows 95, Windows 98, Windows NT, Windows 2000, Windows XP, Windows Vista, Linux, SunOS, Solaris, or other compatible operating systems. In Macintosh systems, the operating system may be any available operating system, such as MAC OS X. In other embodiments, the computing system  100  may be controlled by a proprietary operating system. Conventional operating systems control and schedule computer processes for execution, perform memory management, provide file system, networking, I/O services, and provide a user interface, such as a graphical user interface (“GUI”), among other things. 
     The exemplary computing system  100  includes one or more commonly available input/output (I/O) devices and interfaces  110 , such as a keyboard, mouse, touchpad, and printer. In one embodiment, the I/O devices and interfaces  110  include one or more display device, such as a monitor, that allows the visual presentation of data to a user. More particularly, a display device provides for the presentation of GUIs, application software data, and multimedia presentations, for example. The computing system  100  may also include one or more multimedia devices  140 , such as speakers, video cards, graphics accelerators, and microphones, for example. 
     In the embodiment of  FIG. 1 , the I/O devices and interfaces  110  provide a communication interface to various external devices. In the embodiment of  FIG. 1 , the computing system  100  is coupled to a network  160 , such as a LAN, WAN, or the Internet, for example, via a wired, wireless, or combination of wired and wireless, communication link  115 . The network  160  communicates with various computing devices and/or other electronic devices via wired or wireless communication links. 
     According to  FIG. 1 , information is provided to computing system  100  over the network  160  from one or more data sources including, for example, one or more of the business credit database  162 , the client  164 , the demographic data source  166 , and the business database  168 . The information supplied by the various data sources may include credit data, demographic data, application information, product terms, accounts receivable data, and financial statements, for example. In addition to the devices that are illustrated in  FIG. 1 , the network  160  may communicate with other data sources or other computing devices. In addition, the data sources may include one or more internal and/or external data sources. In some embodiments, one or more of the databases or data sources may be implemented using a relational database, such as Sybase, Oracle, CodeBase and Microsoft® SQL Server as well as other types of databases such as, for example, a flat file database, an entity-relationship database, and object-oriented database, and/or a record-based database. 
     According to some embodiments, the business credit database  162  comprises data obtained from various data sources, including but not limited to tradeline data, public records data, and external client data  240 . In addition, the data may include externally stored and/or internally stored data. In other embodiments, the business credit database  162  comprises only a subset of the data available from the various data sources set forth above. Credit data obtained from business credit database  162  may be combined, verified, or otherwise utilized in conjunction with business database  168  in order to populate business identification database  172 . 
     In addition to supplying data, client  164  may further request information from the computing system  100 . For example, the client  164  may request data related to multiple businesses owned by a single ownership entity. Such a request may include consumer information identifying the ownership entity for which information is desired. 
     Business database  168  may comprise, for example, a national business database as well as other available collections of business data. The national business database comprises approximately 18 million records. The records comprise business data (for example, name, address, size, industry, etc.) and credit data (for example, credit score, activity, etc.). 
     The I/O devices and interfaces  110  further provide a communication interface to a business identification database  172  and a multiple-business owner link (“MBOL”) database  174 . The computing system  100  may be coupled to a secured network, such as a secured LAN, that communicates with the business identification database  172  and the MBOL database  174 . In some embodiments, the business identification database  172  and the MBOL database  174  are configured to communicate with additional computing devices over the network  160  or some other network, such as a LAN, WAN, or the Internet via a wired, wireless, or combination of wired and wireless, communication link. In certain embodiments, the client  164  may have access to the business identification database  172  and the MBOL database  174  through the network  160 , and/or a secured network. 
     In the embodiment of  FIG. 1 , the computing system  100  also includes a business owner link module  150  that may be executed by the CPU  105 . This module may include, by way of example, components, such as software components, object-oriented software components, class components and task components, processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays, and variables. 
     In the embodiment shown in  FIG. 1 , the computing system  100  is configured to execute the business owner link module  150 , among others, in order to determine associations between businesses owned by a single ownership entity. Business owner link module  150  is further configured to access the business database  168 , along with additional sources of information. Records in the business database are accessed, appended with at least business owner information (for example, a business owner ID), and stored in the business identification database  172 . These records are accessed by the business owner link module  150  to determine which records correspond to multiple business records, as will be described in more detail below. 
     In general, the word “module,” as used herein, refers to logic embodied in hardware or firmware, or to a collection of software instructions, possibly having entry and exit points, written in a programming language, such as, for example, Java, Lua, C or C++. A software module may be compiled and linked into an executable program, installed in a dynamic link library, or may be written in an interpreted programming language such as, for example, BASIC, Perl, or Python. It will be appreciated that software modules may be callable from other modules or from themselves, and/or may be invoked in response to detected events or interrupts. Software instructions may be embedded in firmware, such as an EPROM. It will be further appreciated that hardware modules may be comprised of connected logic units, such as gates and flip-flops, and/or may be comprised of programmable units, such as programmable gate arrays or processors. The modules described herein are preferably implemented as software modules, but may be represented in hardware or firmware. Generally, the modules described herein refer to logical modules that may be combined with other modules or divided into sub-modules despite their physical organization or storage. 
       FIG. 2A  shows a diagram illustrating that in one embodiment the business identification database  172  comprises business data obtained from a corporate business identification database  250  and from a non-corporate business identification database  260 . In some embodiments, corporate business data records may comprise different or additional data fields as compared to non-corporate records. A skilled artisan will understand that the processes described herein may be modified to accommodate different forms of ownership, such as sole proprietorships, partnerships, corporations, or the like. Records in the business identification database  172  (and in the corporate and non-corporate business identification databases  250  and  260 ) may be obtained from, for example, the business database  168 . Additional data may be obtained from other sources such as the business credit database  162 , client  164 , demographic database  166 , or some other source as described above. Some or all of these data sources may also be segmented to distinguish corporate and non-corporate data. 
       FIG. 2B  shows a diagram illustrating that in one embodiment the MBOL database  174  comprises a corporate MBOL database  270  and a non-corporate MBOL database  280 . As described above, corporate and non-corporate ownership entities may be handled differently, and the associations identified according to the processes described herein may be divided along this boundary as well. In some embodiments, corporate entities and individual owners are handled in a single database or in an identical fashion. 
       FIGS. 3A-C  are example embodiments of records  300 ,  310 , and  320  stored in a business identification database  172 . Each record stored in business identification database  172  comprises data relating to a single business and the business owner. As shown, each of the records  300 ,  310 , and  320  correspond to the same business owner. Of course, business identification database  172  may store any number of records, and multiple records may correspond to multiple owners or to a single owner. 
       FIG. 3A  shows business record  300  as stored in the business identification database  172 . Business record  300  comprises a number of data fields related to the business and the business owner. The data fields of the business record  300  are compiled by the computing system  100  (or some other computing system) from data extracted from, for example, the business credit database  162 , client  164 , demographic data source  166 , and business database  168 . 
     The business record  300  comprises business identification number (BIN) field  301 . In the embodiment shown, the BIN comprises a unique 14-digit identification number. For the business record  300 , the business identification number is “12345678901234.” In some embodiments, the BIN may be any length and may be alpha-numeric, or may be any other unique identifier. 
     Record  300  further comprises business name field  302 . In the embodiment shown the business name is “KNOBBE MARTENS OLSON AND BEAR”. 
     Business record  300  further comprises a number of fields  303  storing address data such as the street address, unit type, the zip code, and other related data. Additional descriptive business data  304  is also stored in business record  300 , such as a primary phone number, an SIC code and description, an employee size code, years in business code, and the like. As can be seen, some of the values associated with these fields may be alpha-numeric codes. Thus, the “Years In Business Code” field has a value of ‘F’, and not a number. The value ‘F’ may correspond to a specific number of years or a range of years. It will be appreciated that there are many ways to store such data according to different embodiments. 
     A business owner ID field  305  is also stored in business record  300 . As shown, the business owner ID  305  comprises a unique 10-digit identifier. The business owner ID in business record  300  is “1234567890.” A business owner ID may be determined by the computing system  100  based on, for example, the additional data associated with the business record  300 . For example, a business owner name field  306 , business owner address field  307 , and a social security number may be used to identify a particular record as being associated with an existing business owner ID, or a new business owner ID may be assigned. In a certain embodiment, the business owner ID is determined using the data extracted by the computing system  100  over network  160  when records are being written to the business identification database  172 . 
     Along with information related to the business owner such as their name  306  and address  307 , different credit data may be stored in the business record  300 . In the record  300  shown, a credit risk field  308  is included. The credit risk shown indicates a low credit risk. Credit data may additionally or alternatively include one or more scores, credit event history information, existing account information, or the like. 
       FIG. 3B  shows a business record  310 . The business record  310  comprises the same fields as business record  300 , but corresponds to a different location of the same business. The record  310  corresponds to a San Francisco, Calif. location of the business, while the record  300  corresponds to an Irvine, Calif. location. 
     Despite being the same business, the BIN field  301  and business name field  302  of record  310  both have different values than the corresponding fields in record  300 . In this case, the difference in the name field may correspond to a variation in the name input when the record  310  was first created. As will be described below, these records represent multiple records for a single business that should be filtered so that only one business is identified in the MBOL database  172 . 
       FIG. 3C  shows a business record  320 . The business record  320  comprises the same fields as  300  and  310 , but corresponds to a different business. Specifically, while records  300  and  310  correspond to a law firm, record  320  corresponds to an ice cream parlor. The business owner for all three of these records is the same, as identified by the business owner ID. The business owner ID may preferably be matched to a business owner name, address, and social security number even when, as with business records  300 ,  310 , and  320 , a variation of the name is use or a different address is provided. 
       FIG. 4  shows a process for analyzing a business identification database  172  comprising many business records such as those shown in  FIGS. 3A-C  in order to determine multiple-business owners and generate a multiple-business owner list file  450 . As an overview, records from a business identification database  172  are filtered by a multiple-business filter  420 . The results are stored in a MBOL database  174 . Results in the MBOL database  174  are matched with a client consumer file  414  and those results are used to generate a multiple-business owner list file  450 . 
     In one embodiment, business identification database  172  comprises a large number of business records. For example, business identification database  172  may comprise on the order of 100 million business records. Each business record in the business identification database  172  includes data relating to one business. As described above, the data associated with each business may be obtained from, for example, business database  168 . Additional data may be obtained from other data sources, and certain identifiers (for example, the BIN and business owner ID) may be determined by the computing system  100 . Examples of business records are described above with reference to  FIGS. 3A-3C . 
     While in some embodiments, each of the business records is associated with one business, many of the records may be associated with the same business and some of the records may be associated with the same owner. Although the records in the business identification database  172  are not necessarily sorted or organized according to the business owner, records  411 ,  412 , and  413  are shown grouped according to the business owner for the purpose of an explanation here. 
     Business records  411  in the business identification database  410  comprise a set of multiple records owned by a single entity and relating to an individual business. That is, even though multiple records  411  are associated with a single business owner or ownership entity, the combined records only refer to one business. This may be the case where, for example, multiple records are created due to a slight variation in the name entered when the record was created, multiple office locations exist for a single business, or where records are related to a single event rather than all events concerning a single business. Accordingly, the owner is not a multiple-business owner. 
     Business records  412  are those records for which there is one individual record  412  for a single owner, and that record relates to a single business. The owner of a single business is not a multiple-business owner. 
     Business records  413  in business identification database  172  are those records for which multiple records are present for a single ownership entity, and those records refer to multiple businesses. Owners associated with multiple business records  413  that represent more than one business correspond to multiple-business owners. It is desired that these owners and the multiple business records  413  be identified and extracted from the business identification database  172 . 
     In one embodiment, records in business identification database  172  are filtered by a multiple-business filter  420  in order to identify multiple business records  413 . The process employed by multiple-business filter  420  is described in more detail with respect  FIGS. 5 and 6  below. In general, multiple-business filter  420  accesses business identification database  172  and filters out those business records that do not comprise multiple businesses associated with an individual ownership entity. Thus, individual records  411  and multiple records  412  would be filtered out by multiple-business filter  420 , while business records  413  would be kept by multiple-business filter  420 . Those business records kept by multiple-business filter  420  are stored in the MBOL database  174 . MBOL database  174  therefore comprises the records from business identification database  172  for which multiple businesses are associated with a single ownership entity. For example, MBOL database  174  is shown multiple business records  413   a  corresponding to a business owner No. 1 and multiple business records  413   b  corresponding to a business owner No. 2. While only two sets of records are shown, many sets of records may be stored in MBOL database  174 . If the business identification database  172  comprises approximately 100 million records, then MBOL database  174  may comprise fewer records, for example approximately 10 million records. Of course, this is just one approximation and the precise number of records in each database will depend on the actual records stored in the business identification database  172 . 
     When the MBOL database  174  has been created, a client  164  may request information related to the MBOL database  174 . In general, this request will include a client consumer file  414 . Client consumer file  414  may comprise a list identifying one or more consumers for which the client  164  desires multiple-business information. That is, the client  164  may be interested in learning if one or more consumers are a multiple-business owner and/or the credit status of the consumers&#39; other businesses. 
     Client consumer file  414  is submitted by the client  164  to a client business owner matching module  440 . For example, client  164  may submit client consumer file  414  to system  100  via network  160 , and the client business owner matching module  440  may be implemented as part of the business owner link module  150 . In some embodiments, the client consumer file  414  is created and submitted via a web-based user interface or proprietary software application. The process executed by the client business owner matching module  440  is described in more detail with respect to  FIG. 7  below. In general, client business owner matching module  440  matches the consumers listed on the client consumer file  414  with the records contained in the MBOL database  174 . For example, if client consumer file  414  includes identification information associated with business owner No. 2, then supplying the client consumer file  414  to the client business owner matching module  440  would result in multiple business records  413   b  associated with that owner being extracted from the multi-business owner link database  174 . While in some cases every consumer identified by client consumer file  414  may have records associated therewith in the MBOL database  174 , in many cases only a fraction of those names identified on a client consumer file  414  will have records in the multiple-business owner database  174 . In one embodiment, the records associated with those consumers that are matched to the client consumer file  414  and the MBOL database  174  are returned in a multiple-business owner list file  450 , and no data is returned for those consumers listed in client consumer file  414  but not found in MBOL database  174 . The multiple-business owner list file  450  generated by the client business owner matching module  440  therefore comprises multiple business records for each of the consumers listed on the client consumer file  414  that are multiple-business owners. In  FIG. 4 , the client  164  is provided with multiple-business owner list file  450  comprising business owner No. 2 records  413   b , but not business owner No. 1 records  413   a  (not requested in client consumer file  414 ), multiple records  411  (not associated with a multiple-business owner), or individual records  412  (not associated with a multiple-business owner). Multiple business owner list file  450  is shown with only multiple-business records  413   b , but may actually comprise many records depending on client consumer file  414 . For example, multiple-business owner list file  450  may comprises on the order of 100,000 records in some embodiments. In other embodiments, the multiple business owner list file  450  may only include business owner IDs or other subsets of data from the MBOL database  174 . 
       FIG. 5  shows an example of a process  500  for filtering business identification database  174  according to one embodiment. The process  500  may be performed, for example, by the multiple-business filter  420 , which may in turn be a component of the multiple-business owner link module  150 . 
     The process  500  in  FIG. 5  begins at state  501 , where business identification database records are accessed and the BINs are extracted. As described above, in one embodiment each record in the business identification database  172  is associated with a BIN. At state  502 , each BIN is associated with a business owner ID. Each of the business records in the business identification database includes a BIN and business owner ID. These two values for each record are extracted and associated with one another. 
     At state  503  it is determined whether, for each business owner ID, the business owner is associated with multiple BINs. That is, if a business owner ID is found in more than one record in the business identification database  172 , then it may be associated with multiple BINs. However, if the business owner ID associated with multiple records is actually associated with only one BIN (because the same business identification number is found in multiple business identification database records), then it is not associated with multiple BINs. Referencing  FIG. 4 , at this stage individual records  412  are removed, along with some of the multiple records  411 . 
     Referring to  FIG. 5  at state  504 , records associated with the determined business owner identification numbers from state  503  are extracted. Again with reference to  FIG. 4 , this corresponds with extracting the multiple-business records  413  and a portion of the multiple records  411  not identified as such by having identical BINs at state  503 . 
     These extracted records are filtered for false positives at process state  505  of the process  500  in  FIG. 5 . This process state is explained in more detail below with respect to  FIG. 6 . In general, because business records from the business database  168  may be incomplete, redundant, or erroneous, the data contained in the records is checked to determine whether multiple records actually refer to the same business. With reference to  FIG. 4 , this corresponds to filtering the remaining multiple records  411 . 
     At state  506 , the remaining records are stored in the MBOL database  174 . It is preferred that the MBOL database  174  comprise only true multiple-business owner records. However, as explained below, multiple-business owner records may not be identified with perfect accuracy. Therefore, the MBOL database  174  generally stores those records most likely to be multiple-business owner records, and flags at least a portion of the remaining records with a drop code. Accordingly, the additional records are stored in the MBOL database  174 , but are not identified as multiple-business owner records. In other embodiments, records could be marked rather than stored in a separate database. 
       FIG. 6  shows one embodiment of a process for filtering false positives from a collection of potential multiple-business owner records. For example, the process  600  may be performed on records extracted from business identification database  172  for which multiple BINs are associated with a single business owner ID. Those records that are determined to be multiple business records  413  may be stored in the MBOL database  174 . Records that are determined to be multiple records  411 , corresponding to a single business, may also be stored, but are appended with a flag indicating the basis for determining that the records correspond to a single business. 
     Businesses having multiple records  411  that are actually a single business may correspond to, for example, a single business having multiple locations and/or a single business operated under multiple “doing business as” names. For example, a single business ABC Hauling may exist, and three records  411  may be present in the business identification database  172  corresponding to this single business. Two of the records may correspond to a single location with different names, such as “ABC Hauling” and “American Best Commercial Hauling.” The third record may be located at a different address. Despite these differences, these three records may be identified as a single business and filtered accordingly. 
     The process  600  begins at state  601 . A business owner ID is selected and all of the records related to that business owner ID are accessed from business identification database  172 . Each of the business owner IDs corresponding to multiple BINs may be processed according to this process or a variation thereof, as will be understood by one of skill in the art. The records corresponding to each of the business owner IDs may be processed iteratively or in parallel according to different embodiments. 
     Next, at state  602  it is determined whether any of the selected records having the same business owner ID have matching business names. If the records do have matching business names then the records correspond to a single business and the records are dropped at state  605 . If they do not have matching names then the process continues to state  603 . 
     According to some embodiments, the business name fields in records being compared are not required to be identical in order to be considered matching names. A rule set may be applied to determine a similarity level or to determine if they meet predetermined criteria and are considered to be matching. For example, a rule set may indicate that when at least 50% of the words in the names are the identical, then the names match. Certain words and characters may be filtered out of this determination. For example, common words and literals such as ‘AND’, ‘DDS’, ‘MD’, ‘&amp;’, ‘ASSOC’, ‘ASSOCS’, ‘AT’, ‘LAW’ may be removed from consideration in the name matching process. Corporate literals such as ‘LLP’, ‘LLC’, ‘CORP’, and ‘INC’ may also be removed from the name matching process. Taking business records  300 ,  310 , and  320  as an example for applying this rule set, the words ‘KNOBBE’, ‘MARTENS’, ‘OLSON’, and ‘BEAR’ would correspond to the name of the business record  300 . Business record  310  has the words ‘KNOBBE’ and ‘MARTENS’. Business record  320  has the words ‘KNOBBE’, ‘ICE’, ‘CREAM’, and ‘TREATS’. Accordingly, the business records  300  and  310  share at least 50% of the words in the two names, and are determined to have matching names. Business record  320  is determined to not match either business record  300  or  310 . In some embodiments, multiple records may be indirectly matched. For example, if a first record ‘A’ is matched to a second record ‘B’ but not to a third record ‘C’, but the record ‘B’ is matched to the record ‘C’, then ‘A’ may be indirectly matched to ‘C’ as well. Other rule sets may be used to determine whether business names match at state  602 , as will be recognized by a skilled artisan. 
     While  FIG. 6  refers to records being dropped or kept, in a preferred embodiment all of the records having different BINs but the same business owner ID are stored in the MBOL database  174 , but ‘dropped’ records are flagged with an exception. The exception flag may identify why the record is not a multiple-business record  413 . For example, records that have matching business names may be flagged indicating that they have matching business names. Thus, these records would still be available but would not be identified as a multiple business record  413 . One of the flagged records may be selected to represent the single business having multiple records. For example, in  FIGS. 3A-C , the owner owns two businesses (‘KNOBBE MARTENS OLSON AND BEAR’ and ‘KNOBBE ICE CREAM TREATS’), but one business is identified twice as records  300  and  310 . The process may be able to identify the fact that the owner owns two businesses, rather than dropping the owner completely or falsely identifying him as owning three businesses. One of the records  300  or  310  may be selected to represent the business having multiple records. 
     Moving to decision state  603 , if the records do not have matching business names, it is determined whether the records related to the single business owner have matching tax ID values. If the records do have matching tax ID values, then the records represent the same business and they are dropped at state  605 . As described above, in some embodiments dropped records may still be stored, but are flagged with an indication of why they do not correspond to multiple businesses. Thus, records found at state  603  to have matching tax ID values will be flagged to indicate that they have the same tax ID values. If the tax ID values are different, it is determined at state  603  that the records represent distinct businesses and the records are kept at state  606 . Kept records are stored in MBOL database  174  as multiple business records  413 . If at least one of the records does not indicate a tax ID, then the process  600  proceeds to decision state  604 . At decision state  604  additional rules are applied to determine whether or not records associated with a single ownership entity are multiple-business records. In the example shown, it is determined whether there are at least two fields having different values, selected from three fields. The fields may be, for example the business start year, the SIC code, and the primary phone number. Of course, other fields or a different number of fields may be used, and additional or alternative rules may be applied. In the embodiment shown, if two of the selected fields do not match, then the process  600  proceeds to state  606  and those records are kept as multiple business records stored in MBOL database  174 . If there are not at least two different fields from these selected fields, then the process drops (flags and stores) the records at state  605 . Thus, the process  600  filters false positives (different BINs representing one business) from the MBOL database  174 , allowing for a more accurate determination of multiple-business owner data. 
     An example of SQL code demonstrating one embodiment of a process for matching names in a filtering process is reproduced below: 
     
       
         
           
               
             
               
                   
               
             
            
               
                 INSERT INTO OFTB01.MBOL_UNIQUE_BUS_NAME 
               
               
                 SELECT MBO.TRUVUE_ID, MBO.BIN, MBO.SORT_BIN, MBO.BUS_NM 
               
               
                 FROM OFTB01.MBOL_BUS_NAME MBO 
               
               
                 WHERE MBO.BIN NOT IN (SELECT BIN FROM 
               
               
                  ( 
               
            
           
           
               
               
            
               
                   
                 SELECT T1.BIN, 
               
            
           
           
               
               
            
               
                   
                 T1.SORT_BIN, 
               
               
                   
                 T1.TRUVUE_ID, 
               
               
                   
                 T1.BUS_NM, 
               
               
                   
                 DEC(T1.WORD_CT, 5, 2) as WORD_CT, 
               
               
                   
                 T2.BIN as BIN2, 
               
               
                   
                 DEC(SUM((CASE when T1.WORD1 IN (T2.WORD1, T2.WORD2, 
               
            
           
           
               
            
               
                 T2.WORD3, T2.WORD4, T2.WORD5, T2.WORD6, T2.WORD7, T2.WORD8) 
               
            
           
           
               
               
            
               
                   
                 AND T1.WORD1 NOT IN (‘ ’, ‘LLC’, ‘LLP’, ‘CORP’, 
               
            
           
           
               
            
               
                  ‘CORPORATION’, ‘CO’, ‘ORGANIZATION’, ‘ORG’, ‘INCORPORATED’, 
               
               
                  ‘INC’, ‘LAW’, ‘MD’, ‘DDS’, ‘&amp;’, ‘AND’, ‘ASSOC’, ‘ASSOCS’, 
               
               
                  ‘ASSOCOATION’, ‘AT’, ‘DR’, ‘DOCTOR’, ‘/’, ‘|’, ‘#’, ‘+’, 
               
               
                  ‘$’, ‘%’, ‘-’, ‘.’, ‘Ö’, ‘\’) THEN 1 ELSE 0 END) + 
               
            
           
           
               
               
            
               
                   
                  (CASE when T1.WORD2 IN (T2.WORD1, T2.WORD2, T2.WORD3, 
               
            
           
           
               
            
               
                 T2.WORD4, T2.WORD5, T2.WORD6, T2.WORD7, T2.WORD8) 
               
            
           
           
               
               
            
               
                   
                 AND T1.WORD2 NOT IN (‘ ’, ‘LLC’, ‘LLP’, ‘CORP’, 
               
            
           
           
               
            
               
                  ‘CORPORATION’, ‘CO’, ‘ORGANIZATION’, ‘ORG’, ‘INCORPORATED’, 
               
               
                  ‘INC’, ‘LAW’, ‘MD’, ‘DDS’, ‘&amp;’, ‘AND’, ‘ASSOC’, ‘ASSOCS’, 
               
               
                  ‘ASSOCOATION’, ‘AT’, ‘DR’, ‘DOCTOR’, ‘/’, ‘|’, ‘#’, ‘+’, 
               
               
                  ‘$’, ‘%’, ‘-’, ‘.’, ‘Ö’, ‘\’) THEN 1 ELSE 0 END) + 
               
            
           
           
               
               
            
               
                   
                 (CASE when T1.WORD3 IN (T2.WORD1, T2.WORD2, 
               
            
           
           
               
            
               
                 T2.WORD3, T2.WORD4, T2.WORD5, T2.WORD6, T2.WORD7, T2.WORD8) 
               
            
           
           
               
               
            
               
                   
                 AND T1.WORD3 NOT IN (‘ ’, ‘LLC’, ‘LLP’, ‘CORP’, 
               
            
           
           
               
            
               
                  ‘ CORPORATION’, ‘CO’, ‘ORGANIZATION’, ‘ORG’, ‘INCORPORATED’, 
               
               
                  ‘INC’, ‘LAW’, ‘MD’, ‘DDS’, ‘&amp;’, ‘AND’, ‘ASSOC’, ‘ASSOCS’, 
               
               
                  ‘ASSOCOATION’, ‘AT’, ‘DR’, ‘DOCTOR’, ‘/’, ‘|’, ‘#’, ‘+’, 
               
               
                  ‘$’, ‘%’, ‘-’, ‘.’, ‘Ö’, ‘\’) THEN 1 ELSE 0 END) + 
               
            
           
           
               
               
            
               
                   
                  (CASE when T1.WORD4 IN (T2.WORD1, T2.WORD2, T2.WORD3, 
               
            
           
           
               
            
               
                 T2.WORD4, T2.WORD5, T2.WORD6, T2.WORD7, T2.WORD8) 
               
            
           
           
               
               
            
               
                   
                 AND T1.WORD4 NOT IN (‘ ’, ‘LLC’, ‘LLP’, ‘CORP’, 
               
            
           
           
               
            
               
                  ‘CORPORATION’, ‘CO’, ‘ORGANIZATION’, ‘ORG’, ‘INCORPORATED’, 
               
               
                  ‘INC’, ‘LAW’, ‘MD’, ‘DDS’, ‘&amp;’, ‘AND’, ‘ASSOC’, ‘ASSOCS’, 
               
               
                  ‘ASSOCOATION’, ‘AT’, ‘DR’, ‘DOCTOR’, ‘/’, ‘|’, ‘#’, ‘+’, 
               
               
                  ‘$’, ‘%’, ‘-’, ‘.’, ‘Ö’, ‘\’) THEN 1 ELSE 0 END) + 
               
            
           
           
               
               
            
               
                   
                  (CASE when T1.WORD5 IN (T2.WORD1, T2.WORD2, T2.WORD3, 
               
            
           
           
               
            
               
                 T2.WORD4, T2.WORD5, T2.WORD6, T2.WORD7, T2.WORD8) 
               
            
           
           
               
               
            
               
                   
                 AND T1.WORD5 NOT IN (‘ ’, ‘LLC’, ‘LLP’, ‘CORP’, 
               
            
           
           
               
            
               
                  ‘CORPORATION’, ‘CO’, ‘ORGANIZATION’, ‘ORG’, ‘INCORPORATED’, 
               
               
                  ‘INC’, ‘LAW’, ‘MD’, ‘DDS’, ‘&amp;’, ‘AND’, ‘ASSOC’, ‘ASSOCS’, 
               
               
                  ‘ASSOCOATION’, ‘AT’, ‘DR’, ‘DOCTOR’, ‘/’, ‘|’, ‘#’, ‘+’, 
               
               
                  ‘$’, ‘%’, ‘-’, ‘.’, ‘Ö’, ‘\’) THEN 1 ELSE 0 END) + 
               
            
           
           
               
               
            
               
                   
                  (CASE when T1.WORD6 IN (T2.WORD1, T2.WORD2, T2.WORD3, 
               
            
           
           
               
            
               
                 T2.WORD4, T2.WORD5, T2.WORD6, T2.WORD7, T2.WORD8) 
               
            
           
           
               
               
            
               
                   
                 AND T1.WORD6 NOT IN (‘ ’, ‘LLC’, ‘LLP’, ‘CORP’, 
               
            
           
           
               
            
               
                  ‘CORPORATION’, ‘CO’, ‘ORGANIZATION’, ‘ORG’, ‘INCORPORATED’, 
               
               
                  ‘INC’, ‘LAW’, ‘MD’, ‘DDS’, ‘&amp;’, ‘AND’, ‘ASSOC’, ‘ASSOCS’, 
               
               
                  ‘ASSOCOATION’, ‘AT’, ‘DR’, ‘DOCTOR’, ‘/’, ‘|’, ‘#’, ‘+’, 
               
               
                  ‘$’, ‘%’, ‘-’, ‘.’, ‘Ö’, ‘\’) THEN 1 ELSE 0 END) + 
               
            
           
           
               
               
            
               
                   
                  (CASE when T1.WORD7 IN (T2.WORD1, T2.WORD2, T2.WORD3, 
               
            
           
           
               
            
               
                 T2.WORD4, T2.WORD5, T2.WORD6, T2.WORD7, T2.WORD8) 
               
            
           
           
               
               
            
               
                   
                 AND T1.WORD7 NOT IN (‘ ’, ‘LLC’, ‘LLP’, ‘CORP’, 
               
            
           
           
               
            
               
                  ‘CORPORATION’, ‘CO’, ‘ORGANIZATION’, ‘ORG’, ‘INCORPORATED’, 
               
               
                  ‘INC’, ‘LAW’, ‘MD’, ‘DDS’, ‘&amp;’, ‘AND’, ‘ASSOC’, ‘ASSOCS’, 
               
               
                  ‘ASSOCOATION’, ‘AT’, ‘DR’, ‘DOCTOR’, ‘/’, ‘|’, ‘#’, ‘+’, 
               
               
                  ‘$’, ‘%’, ‘-’, ‘.’, ‘Ö’, ‘\’) THEN 1 ELSE 0 END) + 
               
            
           
           
               
               
            
               
                   
                 (CASE when T1.WORD8 IN (T2.WORD1, T2.WORD2, 
               
            
           
           
               
            
               
                 T2.WORD3, T2.WORD4, T2.WORD5, T2.WORD6, T2.WORD7, T2.WORD8) 
               
            
           
           
               
               
            
               
                   
                 AND T1.WORD8 NOT IN (‘ ’, ‘LLC’, ‘LLP’, ‘CORP’, 
               
            
           
           
               
            
               
                  ‘CORPORATION’, ‘CO’, ‘ORGANIZATION’, ‘ORG’, ‘INCORPORATED’, 
               
               
                  ‘INC’, ‘LAW’, ‘MD’, ‘DDS’, ‘&amp;’, ‘AND’, ‘ASSOC’, ‘ASSOCS’, 
               
               
                  ‘ASSOCOATION’, ‘AT’, ‘DR’, ‘DOCTOR’, ‘/’, ‘|’, ‘#’, ‘+’, 
               
               
                  ‘$’, ‘%’, ‘-’, ‘.’, ‘Ö’, ‘\’) THEN 1 ELSE 0 END)), 5, 2) 
               
            
           
           
               
               
            
               
                   
                 as MATCH_CT 
               
            
           
           
               
               
               
            
               
                   
                 FROM 
                 OFTB01.MBOL_BUS_NAME T1, 
               
            
           
           
               
               
            
               
                   
                 OFTB01.MBOL_BUS_NAME T2 
               
            
           
           
               
               
            
               
                   
                 WHERE T1.TRUVUE_ID = T2.TRUVUE_ID 
               
            
           
           
               
               
               
            
               
                   
                 AND 
                 T1.BIN &lt;&gt; T2.BIN 
               
            
           
           
               
               
            
               
                   
                 GROUP BY T1.TRUVUE ID, T1.BIN, T1.SORT_BIN, 
               
            
           
           
               
            
               
                 T1.BUS_NM, T1.WORD_CT, T2.BIN 
               
               
                 ) MATCHES 
               
               
                 WHERE (WORD_CT/2 &lt;= MATCH CT)) 
               
               
                   
               
            
           
         
       
     
       FIG. 7  shows one embodiment of a process for delivering a multiple-business owner list file  450  to a client  164 . Process  700  begins at state  701  where the MBOL database  174  is accessed. As described above, MBOL database  174  may comprise multiple business records  413  along with flagged (dropped) multiple records  411 . In  FIG. 4 , the MBOL database  174  is shown with multiple-business records  413   a  and  413   b.    
     At state  702 , a client consumer file  414  is received. A client consumer file  414  may comprise, for example, a list of consumers for which multiple-business data is desired. The consumers may be identified by name, address, or any other identifying characteristic. 
     The process  700  then continues to state  703  where business owner IDs are associated with the consumers identified in the client consumer file  414 . The consumers are identified with the business owner IDs by matching the data provided for each consumer with data stored by computing system  100 . For example, a name and/or an address may be matched to a file stored in memory  130  or mass storage  120  of the computing device  100 . A skilled artisan will recognize that certain data may not be necessary, and that a number of different logical rules can be implemented to determine when a business owner ID is associated with a consumer in a client consumer file  414 . 
     At state  704 , records in a MBOL database  174  that are associated with the determined business owner IDs from state  703  are extracted. At state  705 , these extracted records are provided to the client. The extracted records may be provided in a multiple-business owner list file  450 . The multiple business owner list file  450  comprises, in some embodiments, a list of multiple-business records  413  or a subset of the data in the multiple-business records  413  grouped according to the business owner ID. In some embodiments, the extracted records may be provided in an electronic or hardcopy report. The extracted records may be provided with a user interface available through a web page. 
       FIG. 8  shows one embodiment of a map  800  that is displayed by a user interface and that may be used to show the relationship between a business owner and multiple businesses. In some embodiments, the user interface is accessible to client  164  using a proprietary software application or a web browser application. The map  800  may be created by accessing data stored in the multiple-business owner list file  450 . Map  800  includes identifying pointers  801  and  802 , which identify the business locations of the businesses identified by the business records  310  and  320  shown in  FIGS. 3B and 3C . Address data may be extracted from the records to identify the geographic location on the map. As shown, business record  300  is not displayed because it is the same business identified by record  310  (even though it is at a different location). In some embodiments, all records are displayed, and those referring to duplicate businesses are identified, such as by a color code. Next to the pointers  801  and  802  are identifying text boxes  811  and  812 . The identifying text box includes a business identification number and the business name. Other data from the business records may be displayed as well, such as a phone number, address, credit data, or the like. 
       FIG. 9  shows another type of report that can be generated according to some embodiments. Report  900  comprises a waterfall report that identifies the number of multiple records  411  filtered and the drop criteria  905  for those records. Report  900  comprises a number of attributes  901  that identify potential drop criteria. As shown, the potential drop criteria are the BIN  911 , the business name  912 , the tax ID  913 , and various combinations of the start year, SIC code, and phone  914 . Each criteria  901  is in an order in which the filter was applied according to the embodiment shown, so that a running count  902  of the records remaining is kept, along with a corresponding percentage  904 . The number of records dropped for each drop criteria  905  is also listed in the report  900 . The drop criteria field  905  provides a textual description of the reason for dropping the records. A total  920  is provided in the report corresponding to the entire filtering process. 
       FIG. 10  shows a distribution report  1000  according to some embodiments. Distribution report  1000  provides the number of owners  1002  and the total number of businesses  1003  broken down by the number of businesses owned  1001  by a business owner. In the example shown, fields  1005  correspond to between two and seven businesses owned by a single business owner. A total field  1006  shows that there are 27,500 total business owners represented by the records in the MBOL database, and those owners own a total of 100,000 businesses. 
     Although the foregoing invention has been described in terms of certain embodiments, other embodiments will be apparent to those of ordinary skill in the art from the disclosure herein. Moreover, the described embodiments have been presented by way of example only, and are not intended to limit the scope of the inventions. Indeed, the novel methods and systems described herein may be embodied in a variety of other forms without departing from the spirit thereof. Accordingly, other combinations, omissions, substitutions and modifications will be apparent to the skilled artisan in view of the disclosure herein.