Patent Publication Number: US-2015073977-A1

Title: Merchant tracking and analysis tool

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is a continuation of and claims priority to U.S. patent application Ser. No. 12/475,908, filed Jun. 1, 2009, and entitled “MERCHANT TRACKING AND ANALYSIS TOOL,” the disclosure of which is incorporated by reference herein in its entirety and made part hereof. 
    
    
     FIELD OF THE INVENTION 
     Aspects of the invention generally relate to tracking and analyzing merchant transactions on a store basis. 
     BACKGROUND 
     In order to determine the viability of financing a merchant, a financial institution, e.g., a bank, often analyzes the merchant&#39;s productivity on total sales rather than comparable store sales. However, total sales may not be an accurate indicator of the merchant&#39;s financial health. A merchant may increase the number of stores in order to increase the total sales while the same store sales decrease. For example, the merchant may saturate a geographical area with stores so that the merchant&#39;s own stores are competing with each other. Such a scenario may be indicative of a poor financial situation that a financial institution typically wants to avoid. 
     Even if a merchant provides sales information, a bank is often aware of the information only after the merchant publically releases it. Consequently, a bank may first recognize that the merchant has financial problems only after investing in the merchant. Moreover, merchants that are privately-held may not publically release sales information at all. 
     BRIEF SUMMARY 
     Aspects of the invention address one or more of the issues mentioned above by disclosing methods, computer readable media, and apparatuses for processing transaction data using a store number that is associated with a merchant. By analyzing sales of a merchant by store, a financial institution, e.g., a bank, can better assess the financial health of a merchant. The financial institution can subsequently evaluate different value propositions that may be offered to the merchant or a consumer. 
     With another aspect of the invention, transaction data for a merchant is accessed. The store numbers are extracted for the transaction entries so that a performance metric can be determined by store locations of the merchant. Consequently, a financial institution can determine the financial health of the merchant based on individual stores rather than on the total sales of the merchant. 
     With another aspect of the invention, different value propositions can be offered by a financial institution to a merchant or a consumer of the merchant. The different value propositions can be evaluated using an analysis of the transaction data. Value propositions may include merchant line management, merchant prospecting, customization of consumer rewards, and product tie-ins with merchants. 
     With another aspect of the invention, transaction data for different merchants and different geographic areas can be compared to identify potential customers for a financial institution. 
     Aspects of the invention may be provided in a computer-readable medium having computer-executable instructions to perform one or more of the process steps described herein. 
     These and other aspects of the invention are discussed in greater detail throughout this disclosure, including the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The present invention is illustrated by way of example and not limited in the accompanying figures in which like reference numerals indicate similar elements and in which: 
         FIG. 1  shows an illustrative operating environment in which various aspects of the invention may be implemented. 
         FIG. 2  is an illustrative block diagram of workstations and servers that may be used to implement the processes and functions of certain aspects of the present invention. 
         FIG. 3  shows a system for accessing and analyzing transaction data in accordance with an aspect of the invention. 
         FIG. 4  shows a flow diagram for processing sales data for different store locations of a merchant in accordance with an aspect of the invention. 
         FIG. 5  shows a flow diagram for analyzing sales data in accordance with an aspect of the invention. 
         FIG. 6  shows a flow diagram for extracting store number information form transaction data in accordance with an aspect of the invention. 
     
    
    
     DETAILED DESCRIPTION 
     In accordance with various aspects of the invention, methods, computer-readable media, and apparatuses are disclosed in which transaction data is processed using store numbers of a merchant. A financial institution, e.g., a bank, may consequently evaluate different value propositions that nay be offered to the merchant or a consumer. 
     According to aspects of the invention, the financial viability of a merchant may be assessed using merchant store numbers for associated transactions. Consequently, a financial institution can examine merchant performance with internal proprietary data with lesser reliance on external sources. Analyzer  303  can track consumer spending at same stores and gauge a company&#39;s performance ahead of their financial releases. Based on this information, a financial institution can make strategic decisions regarding risk assessment and line management to determine a line of credit that can be offered to the merchant. 
     With an aspect of the invention, same-store-sales over time can be tracked. Same-store-sales may measure the growth in sales of stores that have been open for a year or more. Retailers can increase their revenue either by increasing revenues at an existing store or by opening new stores to increase volumes. Rising comparable sales may indicate that sales are rising at the same set of stores without the added cost of opening a new store. Merchants and store numbers that cease appearing in transaction data may indicate potential distress for the merchant. Additionally, new merchants can be identified as new stores and associated business names start to appear in transaction data. 
       FIG. 1  illustrates an example of a suitable computing system environment  100  (e.g., for supporting system  300 , process  400 , process  500 , and process  600  as shown in  FIGS. 3 ,  4 ,  5 , and  6 , respectively) that may be used according to one or more illustrative embodiments. The computing system environment  100  is only one example of a suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality of the invention. The computing system environment  100  should not be interpreted as having any dependency or requirement relating to any one or combination of components shown in the illustrative computing system environment  100 . 
     The invention is operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well known computing systems, environments, and/or configurations that may be suitable for use with the invention include, but are not limited to, personal computers, server computers, hand-held or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like. 
     With reference to  FIG. 1 , the computing system environment  100  may include a computing device  101  wherein the processes discussed herein may be implemented. The computing device  101  may have a processor  103  for controlling overall operation of the computing device  101  and its associated components, including RAM  105 , ROM  107 , communications module  109 , and memory  115 . Computing device  101  typically includes a variety of computer readable media. Computer readable media may be any available media that may be accessed by computing device  101  and include both volatile and nonvolatile media, removable and non-removable media. By way of example, and not limitation, computer readable media may comprise a combination of computer storage media and communication media. 
     Computer storage media include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media include, but is not limited to, random access memory (RAM), read only memory (ROM), electronically erasable programmable read only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and that can be accessed by computing device  101 . 
     Communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. Modulated data signal is a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media. 
     Computing system environment  100  may also include optical scanners (not shown). Exemplary usages include scanning and converting paper documents, e.g., correspondence, receipts, and the like to digital files. 
     Although not shown, RAM  105  may include one or more are applications representing the application data stored in RAM memory  105  while the computing device is on and corresponding software applications (e.g., software tasks), are running on the computing device  101 . 
     Communications module  109  may include a microphone, keypad, touch screen, and/or stylus through which a user of computing device  101  may provide input, and may also include one or more of a speaker for providing audio output and a video display device for providing textual, audiovisual and/or graphical output. 
     Software may be stored within memory  115  and/or storage to provide instructions to processor  103  for enabling computing device  101  to perform various functions. For example, memory  115  may store software used by the computing device  101 , such as an operating system  117 , application programs  119 , and an associated database  121 . Alternatively, some or all of the computer executable instructions for computing device  101  may be embodied in hardware or firmware (not shown). 
     Database  121  may provide centralized storage of transaction data (e.g., sales data for different merchants for different store locations). Processor  103  may access transaction data from database  121  (corresponding to database  301  as shown in  FIG. 3 ) and process the transaction data by store number as performed by transaction analyzer  303  as further discussed. Processor  103  may further evaluate different value propositions as performed by evaluator  305 . 
     Computing device  101  may operate in a networked environment supporting connections to one or more remote computing devices, such as branch terminals  141  and  151 . The branch computing devices  141  and  151  may be personal computing devices or servers that include many or all of the elements described above relative to the computing device  101 . Branch computing device  161  may be a mobile device communicating over wireless carrier channel  171 . 
     The network connections depicted in  FIG. 1  include a local area network (LAN)  125  and a wide area network (WAN)  129 , but may also include other networks. When used in a LAN networking environment, computing device  101  is connected to the LAN  825  through a network interface or adapter in the communications module  109 . When used in a WAN networking environment, the server  101  may include a modem in the communications module  109  or other means for establishing communications over the WAN  129 , such as the Internet  131 . It will be appreciated that the network connections shown are illustrative and other means of establishing a communications link between the computing devices may be used. The existence of any of various well-known protocols such as TCP/IP, Ethernet, FTP, HTTP and the like is presumed, and the system can be operated in a client-server configuration to permit a user to retrieve web pages from a web-based server. Any of various conventional web browsers can be used to display and manipulate data on web pages. The network connections may also provide connectivity to a CCTV or image/iris capturing device. 
     Additionally, one or more application programs  119  used by the computing device  101 , according to an illustrative embodiment, may include computer executable instructions for invoking user functionality related to communication including, for example, email, short message service (SMS), and voice input and speech recognition applications. 
     Embodiments of the invention may include forms of computer-readable media. Computer-readable media include any available media that can be accessed by a computing device  101 . Computer-readable media may comprise storage media and communication media. Storage media include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, object code, data structures, program modules, or other data. Communication media include any information delivery media and typically embody data in a modulated data signal such as a carrier wave or other transport mechanism. 
     Although not required, one of ordinary skill in the art will appreciate that various aspects described herein may be embodied as a method, a data processing system, or as a computer-readable medium storing computer-executable instructions. For example, a computer-readable medium storing instructions to cause a processor to perform steps of a method in accordance with aspects of the invention is contemplated. For example, aspects of the method steps disclosed herein may be executed on a processor on a computing device  101 . Such a processor may execute computer-executable instructions stored on a computer-readable medium. 
     Referring to  FIG. 2 , an illustrative system  200  for implementing methods according to the present invention is shown. As illustrated, system  200  may include one or more workstations  201 . Workstations  201  may be local or remote, and are connected by one of communications links  202  to computer network  203  that is linked via communications links  205  to server  204 . In system  200 , server  204  may be any suitable server, processor, computer, or data processing device, or combination of the same. Server  204  may be used to process the instructions received from, and the transactions entered into by, one or more participants. 
     Computer network  203  may be any suitable computer network including the Internet, an intranet, a wide-area network (WAN), a local-area network (LAN), a wireless network, a digital subscriber line (DSL) network, a frame relay network, an asynchronous transfer mode (ATM) network, a virtual private network (VPN), or any combination of any of the same. Communications links  202  and  205  may be any communications links suitable for communicating between workstations  201  and server  204 , such as network links, dial-up links, wireless links, hard-wired links, and the like. Connectivity may also be supported to a CCTV or image/iris capturing device. 
     As understood by those skilled in the art, the steps that follow in the Figures may be implemented by one or more of the components in  FIGS. 1 and 2  and/or other components, including other computing devices. 
       FIG. 3  shows system  300  for accessing and analyzing transaction data in accordance with an aspect of the invention. System  300  includes transaction database  301  that stores transaction information. Database  300  may store transaction history including debit card, credit card, bill payment history entries for customers of a financial institution. From the entries, analyzer  303  analyzes the customer transaction information, where a customer may be a consumer of various merchants and where a merchant may also be a customer or a potential customer of the financial institution. Consequently, as will be further discussed, value proposition evaluator  305  uses the results of the analysis to evaluate different value propositions for consumers and merchants. The financial institution may use the customer transaction information to track merchant store information for different store locations over a desired time. 
     Transaction information in database  301  may be characterized by substantial variation in entering business names in transaction data. For example, a merchant or business is often suffixed by the store number in the business name field. Consequently, identifying store numbers may be very useful in conducting analyses with an added layer of specificity. This specificity is important because knowledge of different merchants is often limited to publicly available reports. 
     Using store number information, analyzer  303  can internally track performance of public or private companies based on a performance metric (e.g., the same-store sales metric). A performance metric may be gauged for a store location in different ways, including the amount of sales, frequency of purchases, and the number of participating households. Based on store information, analyzer  303  can analyze local businesses and determine popular new stores, products and merchants so that a financial institution can provide targeted offerings to customers and potential customers. 
     Analyzer  303  may remedy a gap in internal data elements, and consequently provide improvements to existing analytics as well as create new opportunities for a financial institution. 
     Analyzer  303  may provide information based on merchant names, associated store numbers, geographic information, and a time element (e.g., time duration) for tracking merchants and trending analyses. Popularity and growth of this store may be measurable through transaction parameters including the transaction volume and number of households visiting the store. Consequently, analyzer  303  may provide real time insights using actual dollar spending at a store rather than relying on survey-based insights. 
     Analyzer  303  includes a merchant tracking and a geographic tool that may use an intelligent algorithm to track merchant store information over time using the database  301 . Analyzer  303  may extract the associated store number from database  301  as will be further discussed with  FIG. 6 . Traditional systems often perform an analysis of a merchant&#39;s productivity based on their total sales rather than comparable store sales. However, total sales are typically a much looser indicator of company health. 
     Analyzer  303  may also utilize a geographic capability that tracks merchants by location. Analyzer  303  may utilize proprietary bank data for determining and tracking store numbers associated with different businesses in conjunction with geographic information. Consumer transaction data from database  301  may provide a wealth of information regarding consumer spending patterns at different retail stores that is not utilized with traditional systems. Using the transaction details, analyzer  303  can locate new businesses as well as specific store numbers associated with the businesses where the transactions occur. 
     Analyzer  303  may extract sales information with the associated store numbers of a merchant from transaction data using process  600 , as shown in  FIG. 6 , as will be discussed. Analyzer  303  is a merchant tracking and a geographic tool that may use an intelligent algorithm to track merchant store information over time using database  301 . Database  303  may store proprietary consumer transaction information of a financial institution. Analyzer  303  can track new store openings or store closings by merchant and by geography. This information may be used in detecting merchant expansion or contraction as a growth and profitability indicator of specific businesses or as a growth indicator of a local economy. Based these indicators, analyzer  303  can prospect initiatives geared towards businesses or consumers or conduct risk assessment and business credit line management. Value proposition evaluator  305  may also evaluate strategic tie-ins with local and new merchants with varied product offerings. 
     Analyzer  303  may support functions that include tracking comparable stores/same store spending over time. Same-store-sales measure the growth in sales of stores that have been open for a year or more. Retailers may increase their revenue either by increasing revenues at an existing store or by opening new stores to increase volumes. Rising comparable sales often mean that sales are rising at the same set of stores without the added cost of opening a new store. Same-store-sales may be a useful metric in analyzing the financial health of a merchant. Using data from database  301 , analyzer  303  can track consumer spending at same stores and gauge a merchant&#39;s performance prior to financial releases. Based on this information, the financial institution can make strategic decisions regarding risk assessment and line management. 
     Analyzer  303  can also assist in identifying new merchants as their new stores and associated business names start to appear in transaction data. Analyzer  303  can also track merchants and store numbers that have ceased appearing in transaction data, thus indicating potential financial distress. This capability helps in identifying viable merchants that are potential customers of the financial institution. A value proposition may consequently be offered to the merchant. 
     Analyzer  303  can analyze store openings in conjunction with location. Analyzer  303  can keep track of new locations where a merchant may be expanding into or locations from which they are contracting. If analyzer  303  determines that new merchants are emerging or that existing merchants are opening more stores in a location, analyzer  303  may detect growth in local business or gain in popularity of a merchant&#39;s products, thus providing insights into location-based economic, demographic and social trends. Consequently, analyzer  303  provides opportunities for prospecting consumers in that location as well as developing tie-ins with the new businesses to offer different products to the consumers including debit or credit product rewards, and discount offerings. 
     Analyzer  303  can also detect first-mover merchants, who are often market leaders. Detecting early entrants or first providers of a new technology or product may be very useful in recognizing new and potential markets. First-movers often capture the largest market share as first entrants and are thus good candidates for tie-ins and hybrid product offerings. 
     Analyzer  303  can also track over time how rapidly a merchant&#39;s stores expand, multiply and sustain in order to perform a comparative analysis of growth across different kinds of merchants offering a different set of products or competing products. Such information may be useful in forecasting merchant performance, comparing competing merchants while making credit offering decisions, and making realistic assessments of a merchant&#39;s credit needs. 
     Analyzer  303  can analyze how rapidly a merchant loses its share as a competitor opens stores close to the merchant&#39;s stores. Conversely, analyzer  303  can detect how quickly the merchant gains market share as it opens new stores near its competitors. 
     Analyzer  303  can also conduct complementary store analysis. Analyzer  303  can specifically detect stores of non-competing merchants that tend to cluster together in different locations. The financial institution can then offer consumers rewards for bundling their shopping at both stores, thus enhancing transaction volume for the financial institution as it motivates consumers to shop with multiple merchants using the same payment vehicle through the bank. 
     Analyzer  303  can also analyze market structure and changes in industry concentration ratios as merchants in an industry open more stores and expand. Concentration ratio may be specified as the percentage of market output (revenue) generated by n largest merchants in an industry. High concentration ratios indicate lesser competition in an industry. Analyzer  303 , in conjunction with industry level macro data, can analyze economic trends in an industry. The financial institution can also enter into strategic pricing decisions for product tie-ins with companies based on the knowledge of their market positions and the current industry market structure. 
     Analyzer  303  can also analyze if a merchant cannibalizes its own sales by opening numerous stores in the same or around the same location. While opening new stores can add to revenue, too many stores opened around the same location may be chasing the same consumers while adding to cost of maintenance, resulting in a negative impact on the merchant&#39;s profits. 
     Analyzer  303  can also track consumer migration. Analyzer  303  can determine whether consumers are noticeably migrating to a different store (i.e., different store number) of the merchant. 
     Analyzer  303  can track merger and acquisition activity and determine how new subsidiaries have improved or affected performance of a merchant. Similarly, analyzer  303  can track merchant tie-ins and determine their performance. 
     Analyzer  303  may be used in conjunction with the transaction recurrence engine (not explicitly shown in  FIG. 3 ) to locate recurring transactions at a store level (corresponding to a store number). This approach provides an opportunity for recurrent transaction analysis, in which recurrent transaction trends can be compared at a store level for specific merchants. For example, system  300  may determine whether there is a store level difference in the sales of a particular product so that the financial institution can enter appropriate tie-ins. 
     The results of analyzer  303  can subsequently be used by evaluator  305  to evaluate different value propositions  351 - 357  to determine what value propositions may be offered to consumers and merchants. For example, consumers may be encouraged to generate more transactions with one or more merchants and lines of credit may be offered to credit-worthy merchants. 
     Different value propositions may be assessed by evaluator  305 , including: line management assessment  351 , merchant prospecting  352 , consumer prospecting  353 , customize consumer rewards  354 , product tie-ins opportunities with merchants  355 , cross-sell opportunities  356 , and monitoring growth in local economies  357 . 
     For example, tracked performance of a private company may be evaluated. A private company typically does not report financial returns. Evaluator  305  can identify opportunities in values propositions for line management (value proposition  351 ) and prospecting merchants (value proposition  352 ) with the added advantage of less reliance on third party reports. Also, publicly traded companies usually report their total revenues and same-store sales periodically. Tracking a merchant&#39;s performance prior to public disclosure may provide a significant opportunity for line management as well as prospecting. 
     Evaluator  305  can assess whether to offer targeted rewards to consumers based on how the merchant-store mix is clustered at the consumer&#39;s location. Consequently, customized reward programs (value proposition  354 ) may be selected based on determined metrics. Optimizing consumer satisfaction by providing consumers with customized products that cater to specific needs and shopping patterns may improve relationship with the consumers. For example, the tendency of a set of consumers to shop with store ##1 of a first merchant and store ##5 of a second merchant may indicate that these stores are potentially located in the same area or conveniently located with respect to each other. Evaluator  305  can then assess whether to offer or prospect consumers in that area with rewards when they shop at both these locations within a predetermined time duration (e.g., during the same day). This approach may ensure that a financial institution&#39;s service is utilized in a common merchant-mix of consumer purchases while enhancing transaction volumes and the footprint of the financial institution. 
     Consumers may also receive favorable cross sell offers based on evaluator  305  evaluation of value proposition  356 . By generating cross-sell opportunities, consumers become more loyal with the institution&#39;s payment product in much of their retail purchases. 
     In conjunction with information on location, analyzer  303  may perform detailed location-based analyses about local economies, the structure of an industry, competition between stores or merchants, and so forth. For example, if a merchant is expanding rapidly into a location, system  300  may detect a growth in local business or increased popularity of the merchant&#39;s product, thus providing location-based insights on economic, demographic and social trends. Also, system  300  may detect if certain merchants are losing share to a competitor. These analyses may offer a great opportunity to prospect consumers (value proposition  353 ) in that location as well as developing tie-ins with local businesses (value proposition  355 ) to offer various consumer credit or debit products, discount offerings, reward products, and the like. These analyses may also assist in determining the best location for opening new ATMs as well as prospecting deposits customers based on information regarding popular stores and local economy at different locations. 
     Analyzer  303  may assist a financial institution (e.g., a bank) in prospecting merchants (value proposition  352 ) and line management and risk assessment of merchants (value proposition  351 ) who bank with the financial institution. For example, if a merchant has a low risk assessment with a total sales of $1,000,000 per month, a bank may offer a $1,000,000 credit line. If the merchant has a medium risk assessment, then the bank may offer only a $500,000 credit line. However, if the merchant has a high risk assessment, the bank may not offer any credit line at all. 
     With an aspect of the invention, system  300  enables a financial institution to partner with prospective establishments (e.g., merchants) in order to improve pricing offerings, thus enhancing profitability for the financial institution as well as for the financial institution&#39;s customers. Moreover, risk detection process may be enhanced. 
     With another aspect of the invention, system  300  provides a technique for locating market leaders who offer new products, e.g., providers of a new technology or a new carbon offset product. Creating tie-ins with associated businesses may secure the footprint of the financial institution in new and upcoming markets. As new markets and consumer needs evolve, system  300  enhances the capability to track trends and to enable the financial institution to stay ahead of its competition. 
       FIG. 4  shows flow diagram  400  for processing sales data for different store locations of a merchant in accordance with an aspect of the invention. In step  401 , analyzer  303  accesses database  301  and extracts a merchant names and associated store numbers from accessed transaction entries (e.g., debit card, credit card, or bill payment entry). Analyzer  303  further extracts sales data, e.g., total sales, for the particular store location (as identified by the store number). Analyzer  303  determines whether sales data should be extracted for another store of the merchant in step  405 . When sales data has been extracted for the different stores of the merchant, analysis of the sales data is analyzed in step  407  as further discussed in  FIG. 5 . 
       FIG. 5  shows flow diagram  500  for analyzing sales data in accordance with an aspect of the invention. In step  501 , analyzer  303  compares a store location for a merchant for different timeframes in order to determine a sales trend. For example, the sales trend may be increasing when comparing one month to another. Analyzer  303  may also compare different store locations of the merchant in step  503 . For example, some stores may have high sales figures while other stores have poor sales figures. A large variance for sales among the different store locations may be indicative of an underlying financial problem for the merchant. Analyzer  303  may further compare store locations for different merchants in the same geographic area in step  505 . For example, large discrepancies for different merchants in the same area may indicate that one merchant is performing either poorly or well with respect to the other merchants in the area. Relative performance may be an good indicator of the merchant&#39;s financial viability. The results of the analyses in steps  501 ,  503 , and  505  may be subsequently used by evaluator  305  to evaluate different value propositions that may be offered to merchants and consumers by the financial institution. 
       FIG. 6  shows flow diagram  600  for extracting store number information from transaction data in accordance with an aspect of the invention. The extracted store number then can be used by processes  400  and  500  as previously discussed. In step  601 , analyzer  303  extracts store numbers and raw transaction data from transaction entries. In step  603  merchant names are identified from raw consumer transaction data (e.g., StoreName ##135). In step  605 , analyzer  303  passes the raw business name data through a merchant name analysis in order to detect the store number portion and to separate it from the store name. For example, in the above example, “StoreName” is recognized as the store name while “135” is recognized as the store number. Analyzer  303  then extracts the store number in step  607 . Analyzer  303  may add location and geographic information to enable localized analysis in step  609 . Analyzer  303  may insert the processed information back to database  301  in step  611  in order to perform merchant and consumer prospecting and line management and risk analysis. 
     Aspects of the invention have been described in terms of illustrative embodiments thereof. Numerous other embodiments, modifications and variations within the scope and spirit of the appended claims will occur to persons of ordinary skill in the art from a review of this disclosure. For example, one of ordinary skill in the art will appreciate that the steps illustrated in the illustrative figures may be performed in other than the recited order, and that one or more steps illustrated may be optional in accordance with aspects of the invention.