Patent Publication Number: US-2016247224-A1

Title: System for resolving claims

Description:
This application is a continuation of U.S. patent application Ser. No. 14/319,542, entitled “System for Resolving Transactions,” filed Jun. 30, 2014, inventors Imrey et al., which is a continuation of U.S. patent application Ser. No. 11/256,405, entitled “System for Resolving Transactions,” filed Oct. 19, 2005, inventors Imrey et al., which claims the benefit of U.S. Provisional Patent Application 60/620,131, “Debt Settlement Computer System and Method,” filed Oct. 19, 2004, all of which are incorporated herein by reference. 
    
    
     COPYRIGHT PROTECTION 
     A portion of the disclosure of this patent document contains material that is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure in its entirety and in the form as it appears in documents published or released by the U.S. Patent and Trademark Office from its patent file or records, but otherwise reserves all copyright rights whatsoever. 
     BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The present invention relates in general to systems and methods for processing and resolving transactions, and more specifically to systems and methods for collecting debt and/or managing information relating to debt or resolving claims using a computer network. 
     2. Description of the Related Art 
     Certain types of financial transactions, and particularly the resolution of such financial transactions, entail complex, time consuming, and frequently expensive methods directed toward gathering information and facilitating resolution of the financial transaction. For example, debt resolution tends to require investigating the ability of the debtor to satisfy the debt, the terms under which the debt may be settled to the satisfaction of the creditor, and collection of the debt by typically telephoning or otherwise personally contacting the debtor and facilitating the resolution of the debt. Complexities arise in the debt resolution setting when certain restrictions are put in place, such as an inability for a debt collector to leave appropriate messages for the debtor at his or her place of work, issues regarding who may obtain a credit report and under what conditions a credit report may be obtained, and so on. 
     Another transaction resolution scenario involves the field of insurance claim settlements. Again, resolution of an insurance claim requires investigation or projection into the amount the claimant is willing to accept, the amount the insurer is willing to offer, and a mechanism for getting the insurer representative and the claimant to resolve the transaction. Typically the insurer&#39;s representative and the claimant and/or her representative meet face to face or by telephone to negotiate and settle on a satisfactory sum, based on a variety of factors including but not limited to the severity of the harm, the financial position of the claimant, the cost of financing the settlement, and other relevant factors. 
     Regarding debt settlement, the most effective method of debt recovery has in the past been via a direct phone call from the creditor (or its agency) to the debtor. This is perceived by debtors to be generally intrusive and hostile, as the creditor attempts to enforce collection of the debt through certain relatively intimidating verbal tactics. 
     The individual collector is typically paid on a commission, i.e. receives payment based on the amount collected from the debtor. Payment on a commission basis can be contradictory to the goals of the creditor and the abilities of the debtor to pay since the collector wants the highest amount paid to enhance her individual commissions, while the creditor seeks the highest overall recovery on the portfolio. Regarding the dichotomy between collecting the highest amount from an individual debtor and a highest overall recovery, a creditor can often recover more debt by recovering 30% of a $100 million portfolio at 70% settlement terms ($21 million) than by recovering 20% of the same $100 million portfolio at 90% ($18 million). Thus the use of overly aggressive tactics to collect one portion of a debt that adversely affect a creditor&#39;s ability to collect another portion of the debt, through word of mouth or other means, can limit the total overall recovery by the creditor. 
     Typical costs for recovering debt via collectors include salaries, commissions and operating and infrastructure costs (e.g., electricity, office space, furniture, desktop equipment and support, telephony equipment, operation and support, administrative support personnel, and accounting, etc.). Salaries and commissions are required not only for collecting the debt, but investigating the borrower and her ability to pay. 
     Debt collection is generally performed by entities that did not provide the funds but purchase the debt for a sum of money. These entities function solely for the purpose of collecting the debt, and as such have certain rights and restrictions on operation. When one of these entities seeks to collect a debt, the longer a debt remains delinquent, the debt increases due to interest fees and penalties. The overall the probability of recovery decreases over time. Large segments of debt fall “out of statute” and become legally unrecoverable after 7 years. Thus, contacting debtors and settling accounts must occur within specified time frames. A further complication is that debt buyers and sellers may not actively pursue accounts during the purchase, hold and sale of a debt portfolio. 
     Once an entity has purchased a debt and sends out notices of delinquency, the entity or its agency tries to contact the debtor, typically via expensive outbound dialer campaigns involving recorded messages. Changes in contact information present a significant problem in collecting a debt in today&#39;s society. Current skip-tracing information providers such as Lexis-Nexis, Accurint, TransUnion, Experian, and Equifax return current phone numbers on only 25% of the accounts submitted. Thus, an average of 75% of the skip-traced debtors cannot be contacted via telephone. Current phone numbers must first be dialed in order to determine whether the telephone number is active and still used by the original debtor. Telephone numbers are constantly being reassigned and the cost of calling changed numbers remains high and is extremely inefficient. 
     In general, collectors typically have available the threat of litigation, posting of derogatory information on the debtor&#39;s credit bureau, and the offer of settlement at a reduced amount as their primary tools when dealing with the debtor. Collection practices generally are not optimized for best overall return. Rules of thumb are used for settlement amounts based on general past experience, but typically require some amount of investigation to, for example, establish whether reporting delinquent status to a credit bureau will have a measurable effect on a debtor and/or the ability for the debtor to pay a particular amount over time. The expense of the collection process does not allow for a great deal of tuning of the settlement offer to the individual debtor. 
     In other transaction resolution scenarios, including but not limited to insurance claim settlement, charitable pledging, political fundraising, and the like, certain activities are required that can increase costs and require personal presence, such as a person calling another on a telephone, as well as ascertaining ability or willingness to pay or be paid a certain amount, and so forth. Such requirements can be inefficient and in certain instances difficult, cumbersome, or outright unavailable. 
     In light of the above, it would be desirable to have a system and method that improves transaction resolution, such as debt settlement and collection processes, over systems and methods previously employed for such purposes. 
     SUMMARY OF THE INVENTION 
     According to one aspect of the present design there is provided an apparatus for resolving a claim owed, the apparatus comprising a server arrangement comprising means for transmitting a communication to a claimant using one of a number of available communication channels inviting the claimant to contact the server arrangement for the purpose of attempting to settle the claim, an information seeking module configured to obtain claimant financial information from a source other than the server arrangement and the claimant in response to the claimant contacting the server arrangement, a rules based decision module configured to employ only extracted data identified as pertinent to the claimant from obtained claimant financial information, the extracted data extracted in accordance with rules established by a party responsible for satisfying the claim available to the rules based decision module, and analyze the extracted data in order to determine a potential resolution strategy for the claim comprising a plurality of individualized claim settlement offers determined specifically for the debtor based on the extracted data identified as pertinent, and a memory configured to maintain information related to the claim and the rules employed by the rules based decision module. The server arrangement is configured to offer the claimant a plurality of claim settlement options determined specifically for the claimant determined based on the extracted data, and the server arrangement is further configured to attempt to obtain agreement from the claimant to settle the claim. 
     According to a further aspect there is provided an apparatus for resolving a claim owed, comprising a server arrangement comprising a claimant financial information seeking module configured to obtain claimant financial information from a financial information source other than the server arrangement and the claimant in response to the claimant contacting the server arrangement, a decision module configured to employ only extracted data identified as pertinent from obtained claimant financial information, the extracted data extracted in accordance with a set of rules established by an insurer and process the extracted data identified as pertinent to determine a potential resolution strategy for the claim owed, and means for contacting the claimant by transmitting a communication to the claimant inviting the claimant to contact the server arrangement for the purpose of resolving the claim owed using one of a number of available communication channels, and a memory configured to maintain information related to the claim owed and the set of rules established by the insurer. The server arrangement is configured to offer the claimant a plurality of claim settlement options determined specifically for the claimant determined based on the extracted data. 
     According to a further aspect there is provided an apparatus for resolving a claim, comprising a server arrangement comprising a communications module configured to transmit, using one of a number of available communication channels, a communication inviting a claimant to contact the server arrangement for the purpose of attempting to resolve the claim, a credit information seeking module configured to obtain credit information for the claimant in response to the claimant contacting the server arrangement, and a rules based engine configured to employ only extracted data identified as pertinent from obtained claimant account information, the extracted data extracted in accordance with rules established by an insurer, and determine a plurality of individualized transaction settlement offers determined specifically for the claimant depending on financial status of the claimant, and a memory configured to maintain information related to the claim owed and the rules employed by the rules based engine. The server arrangement is configured to provide the plurality of individualized transaction settlement offers to direct the claimant to a resolution of the claim owed based on the rules and the credit information for the claimant. 
     These and other advantages of the present invention will become apparent to those skilled in the art from the following detailed description of the invention and the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       For a more complete understanding of the present disclosure, reference is now made to the following figures, wherein like reference numbers refer to similar items throughout the figures: 
         FIG. 1  illustrates a computer system for use in accordance with one embodiment of the present transaction resolution design; 
         FIG. 2  is a logical representation of software modules executed by the server of  FIG. 1  in accordance with one embodiment of the present design; 
         FIG. 3A  illustrates a process flow for debt collection in accordance with one embodiment of the present design; 
         FIG. 3B  is an alternate process flow for the present design; 
         FIG. 4  illustrates an architectural representation of the debtor interaction side of one embodiment of the present design, implemented on a Microsoft platform; 
         FIG. 5  is one embodiment of a creditor system architecture; 
         FIG. 6  shows an alternate embodiment of system operation representing an embodiment of the present design; 
         FIG. 7  illustrates an embodiment of a payment partner server transaction flow; 
         FIG. 8  is one embodiment of the general concept of mapping source data to dictionaries using schemas; 
         FIG. 9  illustrates a general creditor/credit agency workflow in accordance with the present design; 
         FIG. 10  is a general debtor workflow in accordance with the present design; 
         FIG. 11  shows an internet browser screen shot having settlement items particular to a credit bureau; 
         FIG. 12  presents a general set of settlement terms for a particular creditor or credit agency; 
         FIG. 13  illustrates a settlement dictionary, including in this embodiment an option to create and edit debt settlement items and assign tags, such as XML tags, to match source data; 
         FIG. 14  represents a general format for reports, specifically reporting collection statistics for a debt portfolio; 
         FIG. 15  illustrates a general blank form including fields that may be filled with settlement offer data and presented to a creditor for purposes of issuing settlement offers; 
         FIG. 16  shows a portfolio manager and illustrates the concept of OrgUnits; 
         FIG. 17  is shows a rule manager for a portfolio created by the system; 
         FIG. 18  illustrates the concept of child portfolios; 
         FIG. 19  shows a dictionary manager screen; 
         FIG. 20  is a screen shot of a selected dictionary including attributes; 
         FIG. 21  illustrates a screen shot viewable by a debtor/user; and 
         FIG. 22  is an alternate embodiment of the use of settlement terms, including rules, used to form offers to debtors for the embodiment presented. 
     
    
    
     The exemplification set out herein illustrates particular embodiments, and such exemplification is not intended to be construed as limiting in any manner. 
     DETAILED DESCRIPTION OF THE INVENTION 
     The following description and the drawings illustrate specific embodiments sufficiently to enable those skilled in the art to practice the system and method described. Other embodiments may incorporate structural, logical, process and other changes. Examples merely typify possible variations. Individual components and functions are generally optional unless explicitly required, and the sequence of operations may vary. Portions and features of some embodiments may be included in or substituted for those of others. 
     In general, the present design includes a system and method for resolving transactions, including but not limited to resolving debts, resolving insurance settlement claims, establishing charitable donations, and the like, by providing an automated information collection system that collects information about one party, parses and/or operates on the information collected based on a set of rules established by the other party, and presents certain offers to an individual based on the information collected and parsed. The offers and information are typically provided via a computer network, such as over the Internet, typically via an encrypted connection. The individual may then elect one of the options presented or may refuse, whereupon certain additional information may be solicited and/or entered and the transaction moved further toward resolution. Even in instances where the transaction is not resolved using the present design, the information received can be useful in determining the ability and willingness of both parties to resolve the transaction and can indicate the next logical steps to resolving the transaction, such as initiating litigation or refraining from resolving the transaction altogether. The present design thus automates the overall transaction resolution process, and can reduce the costs, time, and complexities associated therewith at terms acceptable to the parties to the transaction. 
     Whereas previous systems have been offered that enable an online presentation of offers to suit a need, such as an individual contacting a website to obtain car insurance or a mortgage, those types of designs have typically presented a variety of offers to a user without any information regarding the user being sought regarding the user before presenting offers. While those types of sites may request input from the user, no external investigation or information seeking occurs before the three offers from three different lenders, for example, are presented to the user. The present design not only seeks relevant external information pertinent to the user and/or the transaction, but the present design also resolves an existing difference of opinion regarding the transaction. The present design contemplates two parties having different positions regarding an existing transaction, such as a debt, insurance settlement, or other two party type of transaction. 
     The present design brings the two parties together with the ability for one party to employ a set of rules in a rules based engine to form an offer set to resolve the transaction. The present design thus automates resolution of the transaction using information externally obtained regarding the transaction and/or user in a rules based engine having rules provided in part based on desired negotiation rules for one party. 
     The elements that implement the various embodiments of the present system and method are described below, in some cases at an architectural level and in others at a logical level. Many elements may be configured using well known structures. The functionality and processes herein are described in such a manner to enable one of ordinary skill in the art to implement the functionality and processes within the architecture. 
     The processing described below may be performed by a single platform or by a distributed processing computer platform. In addition, such processing and functionality can be implemented in the form of special purpose hardware or in the form of software or firmware being run by a general purpose or network processor. Data handled in such processing or created as a result of such processing can be stored in any type of memory as is conventional in the art. By way of example, such data may be stored in a temporary memory, such as in the RAM of a given computer system or subsystem. In addition, or in the alternative, such data may be stored in longer term storage devices, such as magnetic disks, rewritable optical disks, and so on. For purposes of the disclosure herein, a computer-readable media may comprise any form of data storage mechanism, including existing memory technologies as well as hardware or circuit representations of such structures and of such data. 
     The techniques of the present system and method might be implemented using a variety of technologies. For example, the methods described herein may be implemented in software running on a programmable microprocessor, or implemented in hardware utilizing either a combination of microprocessors or other specially designed application specific integrated circuits, programmable logic devices, or various combinations thereof. In particular, the methods described herein may be implemented by a series of computer-executable instructions residing on a storage medium such as a carrier wave, disk drive, or other computer-readable medium. 
     Further, while primarily described herein with respect to an exemplary system and method for resolving transactions in a debt settlement scenario, the invention and disclosure herein are not intended to be so limited. As noted, the present design may be employed in a variety of scenarios, further including but not limited to insurance claim settlements, charitable contributions, and so forth. 
     As used herein, the term “entity” refers to an individual, corporation, partnership, or other type of legal entity. A specific embodiment of the system and method as described below is sometimes referred to as an “Intelligent Debt Settlement system” or an “IDS system”, or even simply as an “IDS”. 
     The system may be operated online, or via the Internet, as a web-based platform for creditors or their agents (including, for example, debt collection companies, collection agencies, and legal representatives) that allows debtors to settle accounts online at any time of day. Debtors may log into or connect to the system and settle accounts from the privacy of their home or office without the inconvenience of calling the collections department or a collection agency and talking to a collector. The system enables a creditor to create debt settlement terms online, using his own decision criteria, thus helping both the debtor and the creditor/collection agency more rapidly reach a mutually beneficial resolution online without involving the agency&#39;s collectors. 
     When the debtor engages in an online session, the system may acquire certain credit information, including but not limited to a credit report. Based on the credit information so located and collection criteria predefined by the creditor, the creditor/collection agency may determine the settlement offers available to the debtor based on the debtor&#39;s ability to pay. The debtor may choose a most desirable settlement offer in a less adversarial environment. The system may be employed to process payments using online bill paying techniques, and the system may update credit bureaus with current information, such as actual settlement of the debt. The system may send notification to all appropriate parties memorializing the transaction. The system may provide creditor information so that a creditor may view and manage real-time portfolio settlement parameters online. 
     The system generally may be implemented using open standards. The system may be, for example, built in Microsoft Visual Studio .NET and SQL Server 2000 and may be fully XML compliant. The system may run in a secure data center and may be enabled as a web service to provide the technology foundation for its strategic enterprise partners. 
     End users of the system may include delinquent consumer debtors with access to the Internet. For purposes of defining the entities potentially using and/or associated with the system, such parties may include “creditors,” namely entities that loan money to other entities, such as individuals, and are owed money by these “debtors.” Entities may include banks, credit unions, and other lending institutions, but also may include others who provide money, goods, and/or services to entities, such as attorneys, physicians, and so forth. A “primary creditor” is a creditor having an internal collection facility or capability. In this scenario, “debtors” are those entities who have incurred the debt from the creditors. Individuals, partnerships, corporations, government entities, and virtually any person or business structure may become a debtor. A “collection agency” collects on behalf of a primary creditor, typically for a percentage of the fees recovered. A “collection discounter” typically purchases debt and collects that debt internally, or in-house. A collection discounter is independent of the creditor or primary creditor, while a collection agency is typically an agent of the creditor or primary creditor. 
     A logical overview of the system is illustrated in  FIG. 1 . From  FIG. 1 , a computer system  100  includes a server  102  used generally for transaction resolution. Server  102  may be in communication over a communication network  110  with a debtor device  106  such as, for example, a personal computer or PDA. Creditor server  104 , operated for or on behalf of a creditor (e.g., a creditor of a debtor operating debtor device  106 ) may be connected by a communication network  108  to server  102 . Collection software  120 , which may be existing software used by a creditor, runs on creditor server  104 . Credit bureau server  116  communicates with server  102  over communications network  107 . Payment partner server  114  communicates with server  102  over communications network  109 . 
     Communication networks  107 ,  108 ,  109  and  110  may be, for example, the Internet or a local or wide area network. An application program, for example an Internet browser or another application to provide a graphical or other user interface to a debtor, may run on debtor device  106  and provide access by the debtor to server  102 . A debtor account on server  102  may be activated or accessed, for example, using logon information provided by the debtor. 
     Server  102  may execute software  112 , described in more detail below. Information regarding debtors, for example associated with debts held by the creditor operating creditor server  104 , may be stored in account/transaction database  118  accessible by server  102 . Note that other information may be obtained by the server either from internal or external sources to facilitate the transaction and to enable application of the rules described below with respect to software  112  to the data received in order to present the user with an offer set. Examples of information sought include information related in some manner to the user or the transaction, such as macroeconomic data, financial information, transaction information, personal information, or other pertinent data. For example, if a creditor in a debt transaction wishes to extend a time period for settling a debt when a user/debtor lives in a geographic area suffering from a natural disaster, the system may obtain the conditions of the area where the debtor lives. Such information seeking may be done based on the rules presented or separate from the rules presented. Such information may be obtained from, for example, the account/transaction database  118 , from the creditor server  104 , or from some additional remote source not illustrated in  FIG. 2 , such as a publicly accessible weather server or financial data server. 
     Software  112  may interact with collection software  120  so that debtor-related data is synchronized between server  102  and creditor server  104 , such as in a real-time or secure batch process. 
     In general, the system illustrated in  FIG. 1  operates to get the debtor and creditor or creditor representative/agent together to process the transaction, typically by offering a certain number of options to the debtor based on rules established by the creditor, wherein the information provided by the creditor may be parsed and processed to establish the options made available to the debtor. Server  102  may hold or have access to certain information but may functionally operate to hold information, collect information, and manage contact between the debtor operating debtor device  106  and creditor server  104 , credit bureau server  116 , and payment server  114 . 
       FIG. 2  illustrates the logical arrangement of software modules that may be executed by server  102  as part of software  112 . Some or all of these logical modules could, for example, be distributed across multiple servers. Debtor interface  222  may provide an interface to debtors using debtor device  106  and provide information provided from such debtors to decision engine  206 . Credit bureau module  202  may obtain credit reports from credit reporting bureaus for the debtor currently accessing server  102 . 
     Credit reports typically come to either an entity investigating credit or an individual requesting a credit report in a form having significant amounts of information, including but not limited to account entities such as credit card issuers, auto and home loan creditors, and may include information such as payments made or missed, judgments, bankruptcies, and other pertinent information. In certain instances, a credit rating or credit score is computed and provided. Typically the report includes the person or entity&#39;s name, and other identifying characteristics, such as an address, telephone number, birth date, birth place, social security number, or other personal information. For persons or entities having significant activity, such a credit report can include hundreds or even thousands of individual pieces of information. 
     Credit reports are generally distributed in a format particular to their issuer. For example, Credit Report Bureau A may provide a script or other data format, such as a series of records, that includes (in order) Last Name, First Name, Middle Name, Current Street Address, Current City, Current State, Current Zip Code, Current Telephone Number, Bankruptcies, Date of Bankruptcy, Court of Bankruptcy, Account Name, etc. Credit Report Bureau B may provide a different script or other data format that includes First Name, Middle Name, Last Name, Current Area Code, Current Telephone Number, Current Street Number, Current Street, Current Unit Number, Current State, Current Zip Code, Credit Score, Account Name, Account Status, Payment By Month on Account, and so forth. While the same general information may be included, the format and ordering may be completely different, and different entries may be present. The result is a different credit report for each issuer. 
     The system  100  obtains the credit report in the form provided by the credit bureau server  107  at the credit bureau module  202 . Typically credit bureau identification information is provided with the credit report, such as the credit report is provided by Credit Report Bureau A. Alternately, the credit bureau module  202  may be instructed to obtain a credit report from Credit Bureau A on individual X and may contact the credit bureau server  116  to obtain the credit report. At that point, credit bureau module  202  would know the credit bureau server being contacted, i.e. that of company A, and would be able to forward that information to parser module  204  if not present in the credit report. 
     Simply put, credit bureau module  202  receives a request, typically from the decision engine  206 , to obtain a credit report from credit bureau A. Credit bureau module  202  then obtains the credit report from the credit bureau server  116  for credit bureau A, and may perform some level of functionality on the report received, such as converting the report into a format usable by parser module  204  or locating certain limited information. In general, credit bureaus generate information and reports in a consistent manner and format, and thus a report from a bureau will adhere to a predefined format. If this format changes, such as by adding new fields or data, that information may be accommodated by changing the expected parameters within credit bureau module  202  or parser module  204 . 
     The credit bureau module  202  combined with parser module  204  may perform certain functionality, while certain functions are performed by the credit bureau module  202  and others by the parser module  204 . In general, however, the parser module takes the information received in the form of a credit report and parses the information into useful information to the system, and discards any unnecessary information. The information extracted depends on the situation, but may be appreciated and understood beforehand, such as retaining the individual&#39;s first and last names but discarding current street address. The result of information parsing may be a set of information in a desired format that can be operated upon by other modules in the system. 
     The system may parse information based on the rules generated for the particular creditor or credit agency. For example, if a certain creditor only wishes to offer a transaction based on an individual&#39;s credit score, bankruptcy history, and current bank balance in all accounts, only that information may be extracted by the credit bureau module  202  and the parser module  204 . Thus the system parses information based on the report provided in combination with the rules established by either the creditor/credit agency or optionally by the party maintaining the software  102 . Rules for individual creditors may form part of the schemas  216  and/or dictionary  214  and thus may be available to the parser module, either via the decision engine  206  or independent of the decision engine (not shown). 
     As an example, credit bureau A may provide a credit report electronically in a particular format. The credit bureau module  202  may receive the credit report knowing it is from credit bureau A. The credit report may have been generated as a result of an inquiry by creditor or credit agency P. Thus the credit bureau module  202  and parser module  204  may know that a credit report from credit bureau A is being parsed for the benefit of creditor or credit agency P. With this information, the parser may acquire from the credit report only that information needed based on the rules for creditor or credit agency P. Based on the rules generated for creditor or credit agency P, the only inputs required to perform the rules may be number and dates of bankruptcies, delinquent payments more than 60 days on at least two accounts, amount of money available in all known bank accounts, and credit score. Based on the inputs required for the rules, the parser may then extract the required information from the credit bureau A report. 
     Alternately, a uniform set of rules may be developed wherein the information retrieved may be a general or universal set of information independent of creditor or credit agency. For example, the parser may universally retrieve credit score, funds available in all bank accounts, identification information, total number of delinquent payments, number and dates of bankruptcies, and total credit available for an individual. While this information may be located in different places in credit reports from credit bureaus A, B, C, and so forth, this type of information is typically available in a standard credit report and may be extracted from a bureau&#39;s credit report. 
     Note that while certain examples are provided here and throughout this document, these examples are meant to be illustrative and not limiting as to the functionality of the present system and method. Other examples and implementations are possible and this document should not be limited by the examples presented. 
     The result from parser module  204  is a set of information parsed from a particular credit report for a particular entity that may include only that information pertinent to a particular creditor or credit agency. 
     In other words, parser module  204  may parse information from a credit report for processing and decision-making by decision engine  206 . More specifically, parser module  204  may extract and calculate user or creditor/credit agency defined credit report items and current account data, and then submit both the calculated bureau and account data to decision engine  206  for decision making processing. 
     Decision engine  206  may compute, calculate and generate multiple settlement offers for the debtor based on information received from the individual&#39;s credit report, including, for example, the debtor&#39;s ability to pay and the debtor&#39;s bank and credit card account history. This history may be determined, for example, by accessing account/transaction database  118  using decision engine  206 . Account/transaction database  118  may contain information about particular debtors either acquired by means independent of those modules shown in  FIG. 1 , or from the modules provided such as credit bureau server  116 , payment partner server  114 , or from the debtor via debtor device  106 . Information may include, but is not necessarily limited to, previous information obtained about a particular debtor either from a credit bureau or otherwise, such as payment history, credit score, bankruptcies, delinquent payments, and so forth, as well as identifying information. In the vent certain information is unavailable at a later date, any information about debtor stored on the account database may be used where appropriate. Further, if a debtor logs onto the system and selects or refuses to select certain options presented, that information can be maintained for, at the very least, access times and accessing URLs by the debtor where appropriate. Debtor interface  222  may also assist in providing this history data to decision engine  206  by accessing account/transaction database  118 . 
     Debtor interface  222  serves two functions: providing an interface to the debtor directly, such as during an online session, and possibly accessing the account database where appropriate. A typical session will be prompted by notifying the debtor in some fashion, such as by prerecorded telephone message, letter, or possibly electronic contact such as email or text messaging. The debtor may then access an established web site typically controlled and/or operated by the owner/operator of server  102 . The user may log into the site using standard, typically secure Internet protocols, such as by the user/debtor logging into the web site, essentially connecting the debtor with the system  100  via the debtor interface  222 . The debtor may be presented with a series of identification questions, establishing the user&#39;s identity including but not limited to providing a social security number, answering questions that collectively only the correct user/debtor might know, such as “When is your birthday,” “At which branch did you open your Bank of America account,” and “What is the last name of the attorney that represented you in your  1994  bankruptcy?” The user may need to answer a series of questions to establish identity. Additionally, the user/debtor may be provided a code when he or she is initially contacted, such as when the debtor receives a letter, email, text message, or telephone message, and the user/debtor may be asked to provide that code in addition to answering other pertinent identification questions. Once debtor interface  222  identifies the user to a satisfactory degree, where satisfactory is determined by the situation and the desire of the credit agency or entity controlling or maintaining the server  102 . More security may be needed in extreme cases. Other methods of authentication may be used, including but not limited to voice recognition hardware and software, fingerprint recognition, and so forth, to decrease likelihood of an errant identification. 
     Once a user has been verified or authenticated, the fact that the debtor has logged onto the system is noted and may be stored, such as in the account/transaction database  118 . The user/debtor may identify the debt for which he or she is inquiring, typically by selecting from a menu which may contain one or more debts available to be settled. At that point, one of two things may happen. If a credit report is available and has been parsed by parser module  204 , the decision engine may recognize the debt as being associated with a creditor and may obtain the applicable creditor rules and decision criteria and compute a set of offers to present to the user/debtor, such as by presenting a set of options on screen to the debtor. If the credit report has not been received and parsed, the user may be told to wait for a reasonable amount of time, such as a few minutes. Otherwise, if the credit report may not be obtained and parsed within a reasonable amount of time, the user may be told to return at a specified time or thereafter. For example, a message may be transmitted to the debtor/user that at least one settlement offer is being prepared and the debtor/user should log back on after 4:00 p.m. EST. The user may be provided with a session code or password(s) so that she does not need to go through the identification process questioning again. 
     If the decision engine  206  has available parsed credit report information, either upon authentication of the user/debtor or after the user/debtor has reconnected via debtor interface to the system, the decision engine  206  may obtain schemas, rules, and a dictionary appropriate for the creditor/credit agency or other entity seeking resolution of the debt transaction. The decision engine  206  relies on dictionary  214  and schemas  216  in presenting the set of options or decisions to the user/debtor. In this context, a schema is a structured framework of rules appropriate to the situation. As an example, a schema may be associated with creditor/credit agency X, and may include rules such as: 
     “Only offer a maximum of three options to any debtor at any one time” 
     “If the user/debtor has incurred more than one bankruptcy in the last ten years, the only offer made available will be payment of between 100% and 90% of the debt” 
     “Offers made will only be available at the time of initial logon, and if the debtor/user logs out or loses connection for any reason, the only offer made available upon subsequent logon will be payment of between 100% and 90% of the debt” 
     “If the debtor/user has a credit score over 650, the debtor/user will be offered three options initially, including (1) an offer to settle immediately for 100% of the outstanding debt, (2) an offer to finance 100% of the debt over 12 monthly installments at 8% interest per annum, and (3) an offer to finance 100% of the debt over 24 monthly installments at 10% interest per annum. The debtor/user will be presented with a statement that agreeing to settle the debt under option (1) will not materially affect his/her credit score, but options (2) and (3) will cause a report of a late payment to be reported to all appropriate credit bureaus. If the debtor does not accept any of options (1), (2), and (3), then offer the user/debtor a second set of options including one option, settlement of 90 percent of the debt with a statement that such payment may be made immediately but will be reported as ‘deficient’ to all appropriate credit bureaus” 
     “If the debtor/user has a credit score over 675, and has a ratio of this debt to money available in all accounts of less than 5 percent, and the ratio of all other outstanding debt to money available in all accounts is less than 25 percent, then make four offers to the debtor user: (1) an offer to settle for 90 percent of the outstanding debt, with no report made to credit bureaus; (2) an offer to settle for 85 percent of the debt for 12 payments at 10 per cent annually, with a delinquency report to credit bureaus; (3) an offer to settle for 80 percent of the debt for 24 payments at 12.5 percent annually, with a delinquency report to credit bureaus; and (4) an offer to settle for 50 percent of the debt paid immediately, and the remaining 50 percent financed over 12 months at 5 percent per annum, with no report made to credit bureaus.” 
     As may be appreciated from the foregoing, the rules and schemas may be generated to include virtually any set of rules and conditions and may be very complex. The set of rules and schemas in schema module  216  may be provided by the creditor/credit agency, or the entity controlling the server  102 , or a combination of both. For example, creditor B may desire a set of schemas to apply under certain conditions, including applying financing terms at specific percentage rates per annum. The entity maintaining the server may automatically increase the percentages by 0.25 percent to be allocated to the entity maintaining the server. Alternately, the entity maintaining the server may dictate that due to certain regulations in specific jurisdictions, under no circumstances may a debtor in a particular jurisdiction be offered a settlement that includes a financing percentage rate of over 25 percent. Certain creditors may only offer general guidelines for settlement offers, and the entity maintaining the server  102  may implement the guidelines and establish the rules and schemas. 
     For example, a creditor may simply indicate a desire to make exactly three offers to every debtor/user, including one offer for 100 percent of the outstanding debt and two financing offers with percentage rates and terms based on the debtor/user&#39;s credit score, with lower rates for higher credit scores. The entity maintaining server  102  can take this information and create rules and schemas implementing the desires of the creditor and can implement a rate scheme based on debtor/user credit score, with specific restrictions for jurisdictions having maximum interest rate requirements. For example, if the debtor/user has a credit score of under 500, the financing rate for both offers may be 25 percent, with different terms; if over 500 but less than 650, then 10 percent for 12 months and 12 percent for 24 months are offered; if over 650 but less than 750, then 6 percent for 12 months and 8 percent for 24 months; and if over 750, then 5 percent over either 12 or 24 months. 
     Reporting to credit bureaus may be offered if desired, and rates and conditions may change periodically, thereby requiring a change to schemas or the data used to apply the rules. For example, if a schema contains a rule using the prime lending rate to determine financing terms, the prime rate may be implemented in the system, such as in the dictionary  214 , and changed periodically, or the decision engine may obtain the prime rate constantly through some type of interface to a device that provides the prime rate updated periodically. 
     Decision engine  206  is therefore typically a rules-based engine that uses rules previously defined, for example, by the administrator of server  102  or another entity having a business or other relationship to server  102 . The rules used by engine  206  may therefore also include information defined by creditors in creditor decision criteria  212 , and the decision engine  206  may be interactive, meaning that persons external to the decision engine  206  may provide information that may be used to present offers via the debtor interface  222 . 
     Thus the overall functionality of decision engine is to interact with the debtor via debtor interface  222 , and once the debtor is authenticated, obtain the parsed credit information for the user and any information about the debtor from the account/transaction database  118 . Based on the specific debt owed, the decision engine uses dictionary  214 , schemas  216 , and creditor decision criteria  212  to prepare a set of offers to the debtor, the set including at least one offer. The offers are then conveyed to the user via the debtor interface  222  and the debtor may select one for resolution of the transaction. 
     The rules used to generate the set of offers by decision engine  206  therefore may include, for example, a large number of various mathematical, logical, or other functions that use data associated with the debtor as operands. Data could include debtor information provided by a creditor such as, for example, size of the debt, the date the debt was created, and the last payment date. Other information used by these functions and other rules may include data obtained from a credit report obtained for a debtor such as, for example, the debtor&#39;s current credit score. 
     Dictionary  214  generally represents a translator of terms employed within the credit report, schemas, and creditor decision criteria. For example, one credit report may use the term “Last Name” while another credit report may call the field “Surname,” essentially meaning the same thing. The dictionary provides for translation of terms received from credit reports or within creditor schemas to a term that can be recognized by decision engine  206 . Another example would be a credit report containing the field “last delinquent payment,” used by decision engine as “date of last delinquency” and contained in other credit reports as “last missed payment,” “most recent unfulfilled obligation,” etc. In addition to converting from one set of terminology to another, conversions and other translation parameters may be included in dictionary  214 , such as when an interest rate is provided as a monthly rate, conversion may be provided to an annual rate. Translations and dictionary entries may be provided for translations between credit reports, rules within schemas, and internal variables employed by the decision engine  206 . In general, the decision engine may obtain rules and schemas from creditor decision criteria  212  and/or schemas  216  and credit reports from parser module  204  and credit bureau module  202  and may translate them into a format usable by decision engine  206 . 
     Schemas  216  may be used to import source data, for example, provided from creditor server  104 , to server  102 . Schemas may be, for example, edited using a schema editor, known to those skilled in the art, that may run on server  102  and be accessible by a creditor using the system  100 . Such an editor may alternately run separately from the system and may enable providing an edited schema to the system  100 . Source data, namely the source of data for the schemas, such as rules, criteria, and other information typically originates with a computer system or server maintained by a creditor, such as creditor server  104 . Source data usually has very different data structures depending on the creditor system provides the data, and thus data received by the server may be converted before being stored as a schema. 
     Dictionaries may be produced or augmented using client specific schemas, where dictionaries are used to translate information from one form or version to another. Schemas may be analyzed and depending on the terms, terminology, formats, and aspects employed in the schema, certain translations or conversions may be offered in the dictionary. Such analysis is typically performed offline by a human but can in certain limited circumstances be automated. Source data may be processed through a schema  216  to create one or more different rules dictionaries (e.g., one or more of dictionaries  214 ). ETL (extend, transfer, and load) processing may be done on these source data files as part of this importing. One or more source data files may be selected for processing by a particular schema. The choice of the source data file(s) and the schema can result in the production of different dictionaries  214  where each dictionary may have different rules and field types. 
     Dictionaries  214  may include definitions (as mentioned above) that include, for example, both offer variables and guidelines, where guidelines may be offered as part of a dictionary  214 , schema  216 , or creditor decision criteria  212  or other appropriate location in the server  102 . Guidelines may be defined requirements that a debtor&#39;s profile must meet in order for a certain offer or set of offers to be made. Offer variables may be functions used to generate offers based on, for example, predefined mathematical functions. For example, a certain offer may require that a debtor live in a particular state and the offer may be generated based on a mathematical formula that uses, for example, the size of the debt and the number of days since the last payment. The offer variables may include adjustments to basic default values where such adjustments are governed by a rule. For example, where an offer variable sets a value (e.g., “Expiration (days)=25”), a rule such as, for example, “If Accrued Interest&gt;=1000 then Value(Expiration (days))=37”, can be used to create an adjustment of the initial value of 25 if the defined condition is satisfied by the data corresponding to the debtor. These rules may be housed in the dictionary  214 , but are more typically included as part of creditor decision criteria  212  or schemas  216  and may be located in other positions within the server  102 . 
       FIG. 8  illustrates one embodiment of the general concept of mapping source data to dictionaries  214  using schemas  216 . Each schema  216  is defined to match up to data produced by a different source, such as a financial institution or other creditor or credit agency. A schema imports and transforms source data into one or more selected dictionaries  214 . Mapping may occur using a schema map. Fields of source data are typically different from the final fields desired in the dictionaries  214 . For example, source data may include fields such as “prime lending rate” having four digits while the server  102  operates using a field called “prime rate” having five digits. The schema may map prime lending rate into prime rate and add a 0 to the value provided. 
     Source data may be mapped to more than one dictionary, and two or more source data files may be mapped to a common dictionary. Using formulas in the schema map, certain pieces of source data may become calculated or derived values that may be placed into many different fields in the one or more dictionaries  214 . 
     The server may alternately create a second dictionary as a standalone dictionary or a copy of a first dictionary, where the second dictionary may be edited to have rules different from the first dictionary. In addition, the mapping process discussed above can be used to export data from a dictionary, for example, by creating a schema that transforms dictionary data into an export data file. 
     Settlement offers will vary by debtor. The settlement offers may, for example, present differently structured financial terms to the debtor. Offers may include a discounted lump sum immediate payment and a monthly payment amount financed at a stated interest rate. 
     Creditor decision criteria  212  represents information (e.g., stored in memory accessible by server  102 ) that may be used by decision engine  206  in generating settlement offers. Criteria  212  may be information previously provided by one or more creditors each independently accessing server  102  using its own creditor server  104 . Criteria  212  may be stored as a set of rules that decision engine  206  follows in generating offers. 
     The various rules used by decision engine  206  also may be optimized by performing analytics on the rules and the corresponding collection results achieved. Rules may be optimized for a particular creditor, for a given set of debtors, or for other specific situations. 
     As an example, optimization may take into account recovery rates if desired by the creditor/credit agency or entity controlling or operating server  102 . If a recovery rate for a group of debts is approaching 100 percent, the offers made to remaining debtors may change in some manner, such as reducing the financing rates or offering 90 percent settlement offers rather than 100 percent settlement offers. Conversely, if the recovery rate approaches 0 percent or is down from that desired, higher finance rates or an inability to finance may be offered, or offering only 100 percent settlement offers rather than 90 percent settlement offers. Other optimizations of rules may be provided. 
     Recovery manager  208  is an optional aspect of the design wherein a creditor may have specified that debtor offers be reviewed and/or approved by a collector or supervisor, for example, designated by the creditor. As part of the foregoing transaction resolution process, a creditor may log onto server  102  in order to see, for example, a queue of alternative offers being presented by debtors. The creditor may approve, disapprove, or otherwise initiate an action for a particular debtor. 
     It should be noted that while the logical representation presented in  FIG. 2  of the software illustrates various blocks, modules, and components, the lines of demarcation between the various components are not hard and fast, and certain functionality may be performed by various components, including single components or combinations of components, and the functionality described herein is not a hard and fast set of requirements. For example, decision engine  206  may simply apply the rules and schemas to the parsed credit report from parser module  204 , and recovery manager  208  may develop and present the offers to the user/debtor via debtor interface  222 . 
     Payment processor  210 , also an optional component, may execute some or all of the payment processing and accounting functions of the collection and recovery process. The user/debtor, as noted previously, may select a settlement offer that includes payment terms financed over a period of time, or other type of structured settlement. Payment processor  210  may enable the user/debtor to utilize multiple forms of payment, which may increase the debtor&#39;s ability to pay his debt. For example, payment processor  210  may enable a specified sum to be charged to a credit card, ATM card, or bank account periodically. Payment processor  210  may also manage the distribution of payments and/or credits to any party (e.g., any party related to the original debt transaction of the debtor and/or the settlement transaction handled by server  102 ). Payment distribution may be based on portfolio distribution rules stored, for example, on server  102  and accessible by payment processor  210 . For example, if a credit card issuer receives 4 percent of a transaction and the remaining 96 percent is split as 2 percent to the entity operating the server  102  and 98 percent to the creditor/credit agency for any debts in a group paid by credit card, the payment processor allocates 4 percent, 1.92 percent, and 94.08 percent to the credit card issuer, entity operating the server  102 , and creditor/credit agency, respectively. Thus the functionality of payment processor  210  is to divide the payments received in any form and distribute the payments received according to a set of predetermined rules. In order to perform this functionality, payment processor  210  may interact with payment partner server  114 , where payment partner server represents, for example, a server operating at a bank, credit card issuer, or other entity, and may be used to process the transaction selected by the debtor/user and divide the payment made immediately and thereafter among the appropriate parties according to a set of established rules. The rules may be located in schemas  216 , or other appropriate part of the system, including but not limited to recovery manager  208  or payment processor  210 . 
     The present system affords the ability, within server  102  and in association and via software  112 , to establish divisions within payment partners, creditors, credit agencies, and so forth, in the form of units called OrgUnits, or units within an organization. An organization, such as a credit agency, may be broken into various divisions or units, such as collections, financing, accounting, and so forth, and even broken down within those divisions or units into sub-units. The present system establishes those OrgUnits and enables rules to be applied by an individual OrgUnit or collectively for all OrgUnits. Payments may be made to or allocated to individual OrgUnits in an organization. 
     Portfolio distribution rules typically are general ledger (G/L) Account distribution rules. Each OrgUnit may have 2 or more charts of accounts (typically a cash-basis Trust Chart and an accrual-basis Operational Chart). When an online payment is received by an OrgUnit via the payment processor  210 , distribution rules defined for each Chart of Accounts generally specify how the payment is to be applied to Fees, Principal and Interest balances, and in which order. Additionally, the same distribution rule may specify a “split” transaction, for example debiting Accounts Receivable and crediting Revenue in the accrual Operational Chart. Account Distributions define all in-flows and out-flows of money to the system  100 . Furthermore, within the portfolio manager  220 , accounting rules may be bound to Portfolio Lifecycle Events, such as Paid-in-Full, or Promise-to-Pay, thus binding specific pools of debt to specific contractual arrangements governing that debt within the system  100 . Portfolio manager  220  may therefore receive information related to a resolved transaction and, once the payment has been processed by payment processor  210 , account for those distributions to each OrgUnit for each dollar received and paid. Certain accounting rules may be employed to appropriately allocate the distributions between OrgUnits. 
     Reporting engine  218  collects information regarding the debt, the actions of the debtor, the offers made, the offer accepted, the payment made and any payments to be made in the future, and other relevant information computed within the system and provided by the system and can compile the information as desired in a report format, such as in a spreadsheet or other document form. For example, a creditor/credit agency can receive a report, either on demand or periodically, of the amount of a debt pool settled, the terms of settlement including payments received, the form in which they were received, and future payments to be received on particular dates. The result is a generally configurable set of reports that may be generated by the reporting engine  218  for the benefit of creditors, credit agencies, the entity or entities controlling the server  102 , and any other appropriate entity having an interest in the transactions resolved by the system  100 . 
     The reporting engine  218  may therefore generate and optionally send periodic reports (e.g., daily, weekly or monthly) to some or all authorized parties. Reporting engine  218  may communicate with, for example, payment processor  210  to obtain debt status information and recovery manager  208  to access, for example, creditor predefined rules governing the reporting of information. 
     Portfolio manager  220  may provide debt balance management and the migration and/or sales of debt portfolios to other entities. Debt balance management in this situation is again guided by rules, such as payment of taxes to governmental entities by specific OrgUnits, payments by OrgUnits to other entities or OrgUnits of prearranged quantities, such as rents, fees, dues, or other inter-entity transactions, and other relevant payments as dictated by rules maintained on the system  100 . 
     The functions of portfolio manager  220  therefore may be based on rules including information from creditor decision criteria  212 . As a further example, portfolio manager  220  may group debts by sub-portfolios for sale based on a predetermined set of criteria (e.g., established by a creditor). In this manner, portfolios may be sold or transferred between entities or OrgUnits if they fit predetermined criteria. Such an arrangement may include credit agency A providing a rule that it would be willing to take on a debt portfolio from a creditor (not another credit agency) if the amount due in the entire portfolio is between $1 million and $5 million and the average credit score for all borrowers is over 625 and no debt is over 120 days delinquent. Credit agency A may specify a rule that it would purchase such a debt portfolio by paying the creditor 20 cents per dollar of debt owed. Thus rules are used to manage the portfolio using portfolio manager  220 . 
     A general process flow is illustrated in  FIG. 3A , while an alternate process flow is presented in  FIG. 3B . From  FIG. 3A , point  301  indicates that the creditor or credit agency may synchronize current account data for all debts and debtor information with the server  102 . Point  302  indicates that the creditor or credit agency can manage, segment, distribute, and transfer debt portfolios based on established rules and approval for such transactions, either between entities or between OrgUnits. 
     The debtor may be offered an incentive from the creditor to settle the debt. The debtor may be offered such incentives using, for example, print mail, telephone, or electronic mail. As noted, the debtor is known to the creditor or its assignee or agency, and the creditor/assignee/agency typically has some form of contact information for the debtor. While persons may have relocated or provided incorrect contact information, point  303  indicates an attempt by the creditor/assignee/agency to contact the debtor in the manner suggested. Typically the debtor may be provided with a web site and a code, and a certain number of debtors may respond to such a solicitation. Alternately, the debtor may contact the creditor/assignee/agency and indicate an interest to resolve the debt, at which time the debtor may be provided with information for contacting or logging onto the server  102 . Thus various means of establishing contact with the debtor may be employed, with the end result being the debtor being provided with contact information for contacting server  102 . 
     Once a debtor logs onto, for example, a website hosted by server  102  and authenticates himself or herself, the software  112  may request a credit report for the debtor identified using credit bureau module  202  at point  304 . As credit reports can typically only be obtained with specific permission from an authorized entity, the credit report request may be deemed by the credit bureau as a request associated with the creditor of the debtor (or with the creditor&#39;s collection agency) when requested by the credit bureau module  202  from credit bureau server  116 . The credit report may be obtained in this manner, and data from the credit report may be parsed by parser module  204  and used by decision engine  206  as described above at point  305 . 
     At point  306 , settlement offers may be presented to the debtor on, for example, a webpage. Offers are calculated by the decision engine  206  as discussed above, according to the parsed information from the credit report and the rules established by the creditor or credit agency. An example of a set of offers to a debtor is presented in  FIG. 6 . Each offer may have an expiration date associated therewith and an icon or button for the debtor to select to enable acceptance of a particular offer. 
     At point  307 , the webpage generated by server  102  may also present, for example, an icon or button for the debtor to click to indicate a desire to negotiate other terms with the creditor using server  102 . Terms of such a negotiation may be specified by the creditor or credit agency and/or entity controlling the server. For example, a creditor may not wish to offer an ability to negotiate. Credit agency A may offer the user/debtor one attempt to negotiate, while credit agency B offers three opportunities to negotiate. 
     Negotiation enables the user to set terms according to his or her desires, and thus makes available to the debtor various appropriate fields, such as in an HTML web page having data entry fields, for data such as amount user/debtor is willing to pay now, amount per month user/debtor is willing to pay per month over the next 12 months, 24 months, etc., interest rate desired, term desired for repayment, and so forth. Terms offered should be consistent. As an example, the user may be willing to pay a certain amount over a number of months and may wish to make an arrangement that accomplishes this goal. If the two offers initially made are to pay $500 per month over 12 months and $275 per month over 24 months, the debtor may consider these offers difficult or impossible but may be willing to pay $150 per month for a number of months. The user may then enter the amount he is willing to pay and request or specify the term for payments. Alternately, if one initial offer is to settle the debt for 20% of the amount outstanding to be paid immediately and financing the remaining 80% over three years at 8% interest per annum, that information may be entered. 
     The response from the system  100 , specifically server  102 , depends on the rules established for negotiation. If rules are established to accept an offer of 20% now and 80% over three years at 8% interest per annum, the server indicates that the transaction is resolved and proceeds to request information to obtain the 20%, such as by credit card or from bank account. In most circumstances, the user/debtor is not allowed to go back to the initial offer or offers, and will lose the successive opportunities presented once the user/debtor requests further negotiation. 
     If rules are established to operate on the negotiation offer presented by the user/debtor, then the decision engine may evaluate the negotiation offer with the assistance of the modules of  FIG. 2  to determine a response. For example, if 20% now, 80% over 3 years at 8% is received, the decision engine  206  may obtain rules and/or schemas that indicate the creditor has specified on a “first round” of negotiation, no offer of under 50% immediate payment is acceptable, but if an offer of less than 50% immediate payment is received, the decision engine and other modules are to offer 50% immediate payment and 50% financed at either a 12 or 24 month term at 10%. These counteroffers may be made to the user. 
     The user/debtor may select an option and resolve the transaction or alternately the server  102  may indicate the offer made by the user/debtor is acceptable to the creditor/credit agency based on the rules provided. At that point, as indicated at point  308 , the user/debtor may pay using selected forms of payment and may schedule any agreed upon payments and the form of payment for future payments. 
     As may be appreciated, at a certain point resolution may be impossible; the user/debtor and the creditor/credit agency rules may not resolve the transaction. At that point, the user/debtor may be presented with an indication that no resolution has been reached and that the user/debtor may contact the credit agency by telephone to further discuss resolution. In any event, the interactive online session at this point includes data that can be saved and used to further negotiations or make decisions based on the likelihood that the transaction can be resolved successfully. If the distance between positions is significant, the credit agency may decide to initiate litigation without further discussions, while another agency may be willing to split the difference and further negotiate by phone or by using the system with different rules. A set of rules and schemas for subsequent offers may be available to enable the user/debtor to logon and further seek to resolve the transaction. 
     Alternately, if negotiation is offered, the user may be presented with the offer in an editable format and may edit the offer presented in an attempt to resolve the transaction. 
     If a user/debtor elects to negotiate or offer different settlement terms, the user/debtor may alternately be placed into a collector queue, such as in a chat room or other online device/tool, where the queue may be monitored by a creditor or credit agency having access to server  102 . The user/debtor may be notified that his offer has been placed into a queue and that the debtor will be notified (e.g., via chat, test message, or email) when a creditor decision on the offer made has occurred. 
     If the transaction has been resolved, point  309  indicates the system may process the transaction via a third-party trust account partner. The third party trust account partner is an entity established to oversee and maintain transactions on behalf of the creditor such that the entity operating or controlling the server  102  does not need to be directly involved in the handling of funds. Certain laws may prohibit an entity from maintaining funds in trust for the creditor, banks, and so forth, and thus a third party trust account partner may be employed, but this is optional. Further, if the entity operating or controlling the server is a bank or other permissible holder of funds, a partner may not be needed or desired. At point  310 , the system may distribute funds according to distribution rules as discussed above, such as by using payment processing discussed with respect to payment processor  210 . Accounting entries may be posted at point  311 , and reports generated at point  312 . 
       FIG. 3B  illustrates an alternate general flow diagram for the overall system. Point  351  establishes the rules for each appropriate creditor/credit agency and does so by OrgUnit. Point  352  loads the debt portfolio onto system  100 . At point  353 , the user may be notified of the opportunity to settle an outstanding debt. At point  354 , the user/debtor logs onto the system  100  and is authenticated at point  355  and selects a debt at point  356 . At point  357 , the server  102  seeks to obtain a credit report for the user using credit bureau module  202 , and optionally seeks information regarding the debtor from the account/transaction database  118 . Depending on the amount of time required to obtain the credit report, the server  102  may either indicate that the user/debtor may return at a certain time and seek the credit report and parse the data before that time, or may obtain the credit report and parse the data using parser module  204 . Once the data has been parsed and the user/debtor is available, point  358  causes the decision engine  206  to obtain the appropriate rules for the debt selected, optionally based on the parsed information, and may also obtain schemas and dictionary terms as well as creditor decision criteria if any exists separate from the foregoing. Based on the schemas, rules, parsed credit information, and other appropriate information available from parts of the system  100 , the decision engine prepares a set of offers including at least one offer at point  359 . The system presents the offer to the user/debtor at point  360 . At point  361 , the user either selects an offer or selects negotiation if it is offered. If negotiation is available and selected, the user/debtor is able to enter her offer at point  362 . At point  363 , the decision is evaluated, typically by the decision engine  206  but potentially by a creditor/credit agency representative or other entity, and the counteroffer is either accepted or a further offer is made. At this point, the system cycles back through making an offer based on the rules, evaluating the availability of negotiation and allowing the user/debtor to make a counteroffer if available. The net result as shown at point  364  is either resolution or stalemate. If resolution occurs, payment processing occurs at point  365 , and reporting may occur as required at point  366 . As may be appreciated, other aspects discussed herein, such as modifying rules based on portfolio activity, may occur though not shown in  FIG. 3B . 
       FIG. 4  illustrates an architectural representation of the debtor interaction side of the present design, implemented on a Microsoft platform. The debtor system  400  employs object oriented programming and SQL database operation to effectuate the functionality described above. In general, objects are created or received and operated on while periodically, as necessary, obtaining data for purposes of applying schemas and rules and presenting offers to the user/debtor. The architecture is split into various tiers interconnected with a web server that enables access from the outside world via the internet. 
     From  FIG. 4 , web server  401  includes an ASP.NET web application  402  used to interface all appropriate debtor functionality with the internet, such as allowing the debtor to contact the server  102  and interact with the server for purposes of authentication, etc. ASP.NET web applications are typically known to those skilled in the art. Many of the functions of the debtor interface  222  are performed by web server  401 . An object proxy  403  is provided to provide the data to and from the web server  401  and the other tiers in the system to effectuate the functionality described herein. The debtor system components beyond web server  401  comprise object tier server  410 , data tier server  420 , and bureau tier server  430 . The object tier creates and receives/translates objects for interfacing with the debtor/user via the web server  401 . 
     Object tier  410  comprises object service  411  and decision engine  412 . Object service  411  receives objects and can query the data tier or translate the object as necessary and provide the object to decision engine  412 . Much of the functionality of decision engine  206  may be performed by decision engine  412 , including assembling the rules and schemas and applying the rules and schemas to parsed credit report information to develop the set of offers made to the user/debtor and subsequent negotiations, if any. As shown, object tier  410  interfaces with both data tier  420  and bureau tier  430  to perform the requisite functionality. The decision engine  412  may seek rules and other information from data tier  420 , as may the object service  411 . Data tier  420  comprises SQL server  421 , typically a SQL server having access to all the rules, schemas, dictionaries, and other data noted above that is stored for use in creating the offers, managing the debt portfolios, and so forth. The object tier  410  further interfaces with bureau tier  430 , typically comprising a payment service module  431  used to establish payments resultant from successful transaction resolutions. 
     Payment service module  431  queues and processes payment transactions, routing them to an appropriate Third Party Payment Processor gateway based on the method of payment (i.e., ACH, CC, etc.), and further based on any contracts or arrangements established between the trust partner OrgUnit and the creditor/credit agency OrgUnit. Creditor/credit agency OrgUnit A may arrange to process credit card payment transactions through one third party payment processor while processing ACH payments through another. The system may enable a creditor/credit agency to dynamically select a payment partner by displaying to the creditor/credit agency OrgUnit the available Trust Partner OrgUnits and their respective Trust and Payment Processing service offerings. The creditor/credit agency can select a Trust Partner and applies for specific payment services. The Trust Partner may then approve or decline the application. Payment service applications may be supplemented by questionnaire data. Approvals and contract variables such as discount rate, transaction fees, start-up costs, and so forth, may employ decision engine  206  according to rules set up for approvals and contracts, and may result in a payment service contract. Once these contracts are established, the user is presented with payment methods for debt resolution depending on the active payment service contracts the creditor/credit agency OrgUnit has established. 
     Bureau server  430  further includes bureau web service module  432 , used to obtain the data from the credit bureau, such as a credit report, when necessary and provide the credit report for the debtor/user when appropriate. The bureau web service module  432  interfaces with the parser service module  433 . The bureau web service module  432  performs much of the functionality described with the logical credit bureau module  202 , while the parser service module  433  performs much of the functionality associated with parser module  204  in the logical representation of the present design. The ABS queue processor  434  queues the requests for credit reports and distributes them to the appropriate user/debtor. Hence much of the functionality shown in this  FIG. 4  performs the logical functions shown in  FIG. 2  performed by decision engine  206 , parser module  204 , credit bureau module  202 , creditor decision criteria  212 , debtor interface  222 , dictionary  214 , and schemas  216 . 
       FIG. 5  illustrates the creditor system architecture  500 , again including a server tier  501 , object tier  510 , data tier  520 , and bureau tier  530 . Creditor system architecture may be maintained separate from any creditor but operates on the creditor side of the transaction resolution process, essentially maintaining creditor data and effectuating creditor related functionality in the transaction. Again, a Microsoft platform employing OOP and SQL is shown in this embodiment. The creditor side enables the creditor, credit agency, or other entity possessing the debt to provide information and enable interfacing with the debtor side of system  100  and facilitate resolution of the transaction. The creditor architecture  500  performs the functions needed for the creditor, such as gathering creditor and debtor data, preparing data used in providing offers, and informing the creditor of transaction resolutions and status, and in certain cases preparing reports where desired. 
     As with the debtor architecture of  FIG. 4 , the creditor architecture includes an ASP.NET web application  502  and an object proxy  503  in server tier  501 . In addition, the server tier  501  includes FTP components and a data receiver. A creditor, such as a bank, may maintain an FTP site that includes data, rules, or other appropriate information useful in effectuating the transaction resolution process discussed. In order to maintain a level of uniformity, the FTP site file folders  504  maintain at least a list, and in some circumstances the entire file, of data used in the transaction resolution procedure. The presence of these folders can facilitate obtaining the rules, schemas, accounts, debts, and so forth used by the system  100 . A creditor data receiver  505  is provided in server tier  501  to write received data to the creditor&#39;s FTP site folders. Alternately, the creditor data receiver may transmit packages of data directly via email or a secure web service to other components of the system  100 . The FTP site file folders  504  and creditor data receiver  505  enable advantageous connections directly to and from the creditor, and receive data from and transmit data to creditor agent  512 . 
     Object tier  510  comprises a creditor object service  511  and creditor agent  512 . Data objects are received by and transferred from this tier. The creditor object proxy  503  may receive and transmit objects for processing or after processing for use on the debtor side of the system architecture. The creditor agent  512  creates and encrypts data exports bound for creditors, transmits encrypted files to the creditor data receiver  505  running on the server tier  501 . Data tier server  520  again maintains a database and data interaction occurs on this tier  520  using SQL server  521 . Data is of course related to the creditor and creditor related data is retrieved and transmitted using this SQL server  521 . Bureau tier server  530  comprises agent automation service  531 , which executes scheduled events, such as open of day, close of day, end of month, and other processing and accounting requirements. The agent automation service  531  communicates with external payment processors and other appropriate devices to monitor active transaction status, download batch reports, and perform other creditor related functions. The transaction state may be updated in SQL server  521 , creating change logs and current status. The bureau tier server  530  may communicate with the object tier server  510  using MSMQ (Microsoft Message Queuing) notifications to prepare and export data packages. Agent automation service is less extensive on the creditor side than the functions performed in the debtor bureau tier server  430 , and simply automates scheduled events for assessing status and preparing information relating to reports. 
       FIG. 6  illustrates an alternate embodiment of system operation, or the decision flow, specifically including many of the logical software components of system  100 . From  FIG. 6 , credit bureau  601  represents the credit bureau from which credit reports may be obtained, generically representing all credit bureaus that may be contacted by the system  100 . Operation is sequential through the numbers encircled, and decision flow operation is generally directed by bureau server  602 . The first process is to login and obtain a token for a session for purposes of authenticating the session, where the session is on the bureau server  602 . This information passes to both bureau server  602  and decision engine build profile module  603 . Process  2  obtains an extract list, or a list of data to be extracted, while point  3  obtains a report list, or a list of data to be reported by server  602 . The extract list and report list are typically credit bureau specific, and these decisions are generally as discussed with respect to credit bureau module  202  and creditor decision criteria  212  above. For example, an extract list for credit bureau A may include the information stored as rules and/or schemas including credit score, debtor first name, debtor last name, most recent bankruptcy filed, number of payments made more than two months delinquent, total cash on hand in all accounts, etc. The report list may be the information to be reported to the credit bureau, such as successful transactions, resolved debts, payment arrangements, and so forth. 
     Decision flow essentially proceeds from point  4 , posting a request, generally a request for a credit report from a particular credit bureau, potentially based on the extract list and possibly the report list. At point  5 , the bureau login is obtained by the bureau server  602  from RDBMS (relational database management system)  604 . Point  6  inserts the request in the bureau server queue, relying on the RDBMS  604  for present queue information and data relating to entry of additional requests in the queue. Once the bureau server  602  has the queue information, it sends a request, by MSMQ or other appropriate transmission mechanism, to the bureau server queue  605 . Bureau server queue  605  may be executed in a desired order, and eventually the request made results in a credit report being obtained from credit bureau  601 . Once the bureau server queue  605  has obtained the credit report, point  8  indicates that the data is transmitted to parser  606  for parsing the relevant data from the credit report received. Block  607  represents the parser execution logic. Once the parsing has occurred, a report-notify indication is provided from parser  606  to bureau server  602  at point  9 . Armed with the parsed information, bureau server  602  then transmits at point  10  a request to get results to decision engine build profile module  603 . Decision engine build profile module  603  builds a profile of the debtor based on the parsed credit bureau information or credit report, the extract list, report list, and relational database entries. The decision engine build profile module  603  at point  11  may update the particular debtor profile if certain credit information has become available, entering the additional information in the RDBMS  604 . 
     The decision engine decide module  608  combined with the decision engine build profile module  603  generally forms the decision engine  206  in  FIG. 2 . The decision engine decide module  608  may produce a set of criteria or offer specifics approved by the creditor/credit agency based on the circumstances presented. Decision module  609  essentially receives the information and provides/converts the information received into specific offers, and provides the decision in the form of decision results, typically in MSMQ but potentially in other message formats. 
     While shown as two separate modules (decision engine decide module  608  and decision module  609 ) in  FIG. 6 , referring to  FIG. 2 , the decision engine  206  contains the Decide function. Thus the two modules  608  and  609  illustrated in  FIG. 6  could be combined into a single decision module. Note that  FIG. 6  illustrates various subfunctions within the decision engine  206 , including BuildProfile, which communicates with the real-time external data source module, and the aforementioned Decide, which applies the rules to the compiled profile, generating offers as a result. 
     The MSMQ decision results message from decision module  609  is provided to fill request offers module  610 , wherein fill request offers module  610  is an offer database holding the offers previously made and queues the set of offers for transmission to the user/debtor. The user/debtor receives the set of offers via consumer ASPX pageload module  611 , which loads the pages for transmission to the user/debtor. Any responses are received by the system at the consumer ASPX pageload module  611 , which may transmit the received response in MSMQ or other appropriate message format to fill request offers module  610 . At this point, when an offer or set of offers or other selection offered on the page has been acted upon by the user/debtor, and the decision received may be transmitted from fill request offers module  610  to decision module  609  and to decision engine decide module  608 . The result is an appropriate action (negotiate, consider the transaction resolved, negotiation/session terminated, etc.) according to the rules established, including the possibility of transmitting further sets of offers where approved. Note that RDBMS  604  may be updated by process results from fill request order module  610 , namely results of approval and resolution of transaction, negotiation/session terminations, etc. 
       FIG. 7  illustrates a payment partner transaction flow  700  implemented, for example, using payment partner server  114 . The third party payment partner supplies functions such as ACH (automated clearing house) processing, funds clearing and disbursement services to creditors/clients. The third party payment partner receives funds on behalf of clients, such as banks, credit grantors and collection agencies, and holds and/or clears funds on behalf of clients. The system  100  can deposit funds into a third party payment partner&#39;s trust account by submitting all transactions electronically via the internet, for example. The client-creditor can interface with the third party payment partner using the system by specifying rules and schemas according to which the terms, conditions and fees of the third party payment partner is to handle funds. For example, if the funds are to be held for 3 days or until approval has been received from the creditor before being transferred to account J, the third party payment partner holds and acts on the funds according to the rules provided. Again, rules may be implemented by the entity maintaining the server  102  separate from the creditor, credit agency, or payment partner, such as governmental regulations, usury requirements, and other appropriate data. 
     The third party payment partner typically can process debit cards, Master-Money cards, ACH, EFTs, and can originate transactions on behalf of clients-creditors as instructed by the client and/or its customers, can hold funds received from client&#39;s customers on behalf of the client for a fixed amount of time, such as up to 30 days, and can distribute funds to client accounts according to a client&#39;s electronic instructions, based upon electronic distribution rules maintained on the system and set up by or on behalf of the client. 
     Stepping through  FIG. 7 , the user/debtor employs his or her user interface device  106  to provide a payment, such as in the form of an EFT or credit card information at point  1 . Server  102  receives this payment input and forwards the transaction to payment partner server  114  at point  2 . The payment partner server issues an authorization request requesting authorization from the appropriate debt vehicle, such as the checking account, savings account, credit card issuer, and so forth, or account  701 , at point  3 . Point  4  is an authorization response, either authorizing the transaction or denying the transaction. If the transaction is denied, the payment partner server may transmit this information to server  102 , which may act according to predetermined rules in situations where payment is refused, such as by altering the offer to only payments made over time, refusing to produce any further offers and terminating the session, or other desired action. Whether or not the transaction is approved, point  5  indicates that the transaction result is provided to the user/debtor by server  102 . If the transaction is approved, payment partner server  114  provides a settlement request at point  6  to a bin account provider or merchant account provider, and an indication of money deposited is made by the provider  702 . Any fees to any related party are allocated at point  8 , where a related party  703  is a party related to the resolved transaction, including but not limited to the entity maintaining the server  102 . Point  9  indicates that certain disbursements may be requested by the server  102  to payment partner  114  on a periodic basis, such as weekly or monthly, and point  10  indicates monies are deposited into client accounts  704  or creditor accounts  705  according to the rules established. 
     Offers are not limited to simply financial terms. Each offer or set of offers discussed above may also include non-financial terms such as the offer of a free product or service or, for example, some other type of convenience or right. The offering of these non-financial offers may be governed by one or more rules considered by decision engine  206 . For example, if a free product is offered for resolution of the transaction at 95% of the outstanding debt, a user/debtor owing $1000 may be presented with a set of offers including an offer to resolve the transaction for $950 plus a free version of his credit report, and this data may be presented to the user/debtor for selection. 
     As an option that may be used with the system  100  presented above, a user/debtor interacting with server  102  may improve his credit score substantially in real-time while online with server  102 . For example, the user/debtor may make a payment on a debt using the system  100 . The payment is received and acted upon as shown in  FIG. 7 , and thus server  102  has approval of the funds being available and transferred. From  FIG. 1 , server  102  may report the satisfaction of payment to creditor server  104  and/or credit bureau server  116 . Upon receiving a report that a debt has been satisfied, the credit bureau server  116  may take payment of that debt into account and may recalculate the credit score based on the user/debtor&#39;s current score. Computation of a credit score takes into account a variety of factors and different credit bureaus may compute different credit scores with identical data, but in general satisfaction of an outstanding debt is a positive factor that may increase a user/debtor&#39;s credit score. If the credit score can and has been calculated, the credit bureau server may transmit the updated credit score back to the server  102  for transmission and display to the user via debtor device  106 . Alternately, the server  102  may understand generally how payment of a debt may affect credit score and may compute a provisional or temporary credit score for the user/debtor based on the amount of debt satisfied and the conditions of satisfaction (immediate payment, payment over time, etc.). For example, if based on an entire credit history having a few delinquent debts and one bankruptcy five years previously, the debtor&#39;s credit score is 612, satisfaction of an outstanding $2000 debt may raise this credit score. For example, if payment of an outstanding debt for a debtor having a total outstanding debt of between $20,000 and $30,000 and a credit score between 610 and 620 typically raises the credit score by four points, the server  102  or the credit bureau server  116  may indicate that the user&#39;s credit score either may or will increase to 616. 
       FIG. 9  illustrates a general creditor/credit agency workflow for the embodiment disclosed with respect to, for example,  FIGS. 1 and 2 . Point  901  establishes the creditor/credit agency account with server  102  and establishes a general set of defaults for the creditor. Point  902  configures settlement terms for the creditor/credit agency, such as by either providing them verbally to an entity that can translate them into server appropriate terms, such as APX, scripts, or other appropriate settlement terms. Point  903  uploads the debt portfolio, typically from creditor server  104  to server  102  via communications medium  108 . The portfolio includes all debts and identifying information relevant to the debts, potentially including but not limited to debtor name, account number, debt amount, date incurred, and so forth. Debtor addresses may be uploaded at point  904 , again from creditor server  104  to server  102 . An optional portfolio rating may be provided at point  905  to rate the portfolio using an established rating system. For example, a portfolio may be rated with letter grades (A, B, C, D, etc.) with A being the best portfolio by some subjective measure. Number ratings may also be employed (1 for high risk, 2 for medium risk, 3 for low risk, for example) or other rating. These ratings may be used in certain subsequent rules when developing offer sets. For example, a high risk portfolio may be granted a minimum financing rate of 12 percent per annum, while a low risk portfolio may be granted a minimum financing rate of 8 percent. These ratings may change as desired. Point  906  indicates a communication with the debtors, such as by mail, email, text message, recorded phone message, or other means, thereby initiating contact with the debtor and beginning the transaction resolution using the current system  100 . Note that debtor addresses may be periodically updated, portfolios re-rated, and letters sent by the creditor/credit agency, the entity maintaining the server  102 , or other appropriate and/or authorized entity. 
       FIG. 10  illustrates a general debtor workflow. At point  1001 , a debtor receives a letter or other communication providing the web site of the server, perhaps identifying a specific debt or creditor, and perhaps providing a key word or password or code know to and enabled to be used at the web site of the server  102 . The debtor at point  1002  may log onto the web site, using his key word, password, or code as appropriate. In certain circumstances and jurisdictions, an individual or entity may need to approve an entity such as a creditor, credit agency, or entity maintaining server  102  obtaining his credit report. In such case, a credit report may be approved by the user indicating the obtaining entity is authorized to obtain a credit report on his behalf, shown as an option at point  1003 . Rules may be established when a user does not allow a credit report to be obtained, or no credit report is available, wherein, for example, no offers are to be made, or alternately, only a limited set of offers (such as 100 percent of debt outstanding) may be presented. These rules are established by either the creditor/credit agency or entity controlling server  102 . After a period of time, which may be short or long depending on circumstances, the user/debtor may receive and view offers at point  1004 . The user/debtor may select the best offer at point  1005 , and may pay debt at point  1006 . An option that may be made available is for the user to view his/her credit report, by purchasing it or other available options, and may view his or her credit score in certain instances if offered at point  1007 . 
     To provide a general feel for the type of screens that may be encountered/used by the entities accessing the system, a general set of screen shots is presented in  FIGS. 11-22 . These screen shots represent a general illustration of the present design, but alternate views, information, and layouts could be presented, and thus the screen shots presented here are not intended to be limiting. 
       FIG. 11  shows an internet browser having settlement items particular to a credit bureau. In general, the bureau mapping function is being addressed in this screen, namely how the credit bureau module  202  obtains the credit report from the credit bureau  116 . The bureau mapping screen  1101  indicates the bureau name, the type of report, an extract list, and provides a listing on the right side of the bureau items to be extracted from the report retrieved (number of negative trades, number of trades, high credit, etc.) An operator at this screen can select from the available fields on the left side of the screen, selecting the fields he or she wishes to include from the credit bureau module and potentially parse using credit bureau module  202  and parser module  204 . Again, schemas express shared vocabularies and allow machines to carry out rules. The schema for this creditor may include the rules to extract the desired information from a credit report. 
       FIG. 12  presents a general set of settlement terms for a particular creditor or credit agency. Screen  1201  includes the entity name (creditor/credit agency), and includes different levels of rules, such as a 87 percent settlement and a 90 percent settlement. Offer variables include expiration of 30 days or 25 days in the two circumstances, and guidelines include rules wherein if the current debt balance to the creditor is greater than or equal to $500.00, the amount can be paid off at 97 percent over 30 days. If the accrued interest is greater than or equal to $1000.00. If the charge off amount is greater than or equal to $5000.00 then the value offered is 80 percent. The offers and guidelines  1202  can be altered, and terms added, removed, or changed depending on the desires of the creditor/credit agency or other entity. Effective dates and expiration dates can be provided. Note that an option to add terms to a dictionary is provided in screen  1201 . 
       FIG. 13  illustrates a settlement dictionary  1301 , including in this embodiment an option  1302  to create and edit debt settlement items and assign tags, such as XML tags, to match source data. The various debt settlement items in this view include, under the specific creditor and the dictionary “Debt,” the entries Account Status, Accrual Interest, Age, and so forth, each representing a dictionary term that can be matched to a credit report entry or other database entry. Point  1302  includes the item or tag, for example in XML format, its type, and point  1303  indicates that the item “Age” can be created using a formula, such as “Current Date” minus “Debt Date.” 
       FIG. 14  represents a general format for reports, specifically reporting collection statistics for a debt portfolio. In this view, at point  1401 , the date and time are provided, the number of accounts in the portfolio, the total debt amount, number of accounts that have settled, percentage of accounts settled, amount of debt settled, percentage of all debt settled, resolution amount, percentage of total debt settled, percentage of settled debt settled, total collected, and percentage of transaction resolution amount. Reports can be provided in various formats. 
       FIG. 15  illustrates a general blank form including fields that may be filled with settlement offer data and presented to a creditor for purposes of issuing settlement offers. Inputs may include account number, status, name, original creditor, principal balance, current balance, sets of available settlements, proposals received from debtors, and counter offer. The screen shot of  FIG. 15  may be presented to a creditor if the creditor wishes to have an ability to dynamically make settlement offers to the debtor. In this view, four editable fields are presented as well as two calculated fields. A creditor/credit agency having the screen of  FIG. 15  before her may know the specifics of the debt and the state of negotiations to date, and may enter a down payment, a term, an interest rate, and an expiration rate, which may be received by server  102  and presented to the user/debtor via debtor device  106 . The “calculate” option calculates the monthly rate and total of debt paid using a specific term and interest rate entered, while “Submit to Debtor” allows the creditor/credit agency to send the offer to the creditor via server  102 . Note that if the offer violates any rules for the creditor/credit agency, such as being too low an interest rate for the circumstances presented, the server  102  may present the creditor/credit agency with a warning. Again, the offers correspond to the set of rules, wherein one rule may be that offers submitted by a live person via an interface such as that shown in  FIG. 15  override all other rules. 
       FIG. 16  illustrates a portfolio manager and shows the concept of OrgUnits. In  FIG. 16 , Test Master is a portfolio of Test Region, which is a sub-OrgUnit of First Performance. Test Master includes various settlement dictionaries and portfolios, and to the right is the OrgUnit, portfolio name, number of accounts, assigned total, adjusted total, number settled, assigned settled, and payments received. This enables a user to create a new portfolio or modify an existing portfolio. As noted, sub-OrgUnits can inherit the properties of parent OrgUnits.  FIG. 17  shows a rule manager for the portfolio created, where rules can be added to a portfolio as desired. For example, for OrgUnit Test Region, Portfolio name Test Master, rules can be created for settling debt or transferring debt, such as the portfolio cannot offer an interest rate of less than 8 percent per year and can be sold to an entity offering over 50 cents on the dollar. 
       FIG. 18  illustrates the concept of “Child Portfolios,” where additional portfolios may be added. In this view, FPGroup 2, FPGroup 22, and FPGroup3 are child portfolios of Test Master. Child portfolios may inherit the attributes and rules of the parent portfolio, and may have different or additional rules. Child portfolios enable categorization and metrics to be measured for sub-segments of portfolios, and can portray a better picture of the debt settlement position for the portfolio.  FIG. 19  shows a dictionary manager screen, where a dictionary may be imported for a portfolio. In this instance, 30, 60, and 90 day dictionaries are available, where the time period represents the delinquency time of the debts in the portfolio. These dates can represent maximum, minimum, average, or other time periods of delinquency. For example, for a debt over 30 days old, the 30 day dictionary may apply, where such a dictionary may enable certain options and rules that the 90 day dictionary does not include. The concept of Import and Target dictionaries are shown in  FIG. 19 , where an import dictionary may be imported from another OrgUnit, for example, or from a remote location. A target dictionary may represent potential dictionaries applicable to the specific debt portfolio and may apply only to that debt portfolio. 
       FIG. 20  shows a selected dictionary, here the import dictionary, and its attributes, namely that it is shared by seven accounts and may be set as exclusive to this portfolio. If the dictionary is set exclusive, aspects may be changed for this dictionary and not applied to the other six accounts. 
       FIG. 21  illustrates a screen shot  2101  viewable by a debtor/user. The individual&#39;s name is presented here, as is the creditor, reference number, purchase date, principal, contact information (with options to update the information) and notably two options for settlement. In this view, the balance due is $1153.85, and the transaction resolution offer set includes an offer to pay $84.62 now, expiration date Apr. 21, 2004, or pay $230.77 now and $81.15 monthly for 12 months, interest rate of 10 percent. The second offer in the offer set expires on Apr. 6, 2004. The user may accept either offer in the offer set, or may select an option to submit her own offer for consideration. Again, this offer to enable the user to submit an offer depends on the rules established for the creditor, credit agency, debtor, and transaction to be resolved. 
     A second screen shot of settlement terms is presented in  FIG. 22 . From  FIG. 22 , offer variables and guidelines, each a different set of rules, are presented. The offer is simply one of 90 percent settlement  2201 . The requirements in this instance are if the user/debtor is employed, then Value is set equal to 10, and the Downpayment is equal to 90, a 90 percent settlement, at point  2202 . Guidelines establish that the number of days to collect is less than 30, meaning the 90 percent must be collected within 30 days. Note that the 90 percent offer expires at 7 days. Effective dates and cancellation dates are provided. This version may be presented to either a creditor or the entity maintaining the server, and terms may be entered and/or changed as desired. 
     Alternate Transaction Resolution Scenarios 
     While the foregoing generally discusses resolving transactions with respect to a specific debt settlement scenario, the invention is not so limiting. In particular, the present system may be employed, including the rules, schemas, dictionaries, modules, servers, and components to resolve other types of transactions. 
     For example, the present system and general methodology may be employed to seek and obtain charitable donations. Obtaining credit reports may or may not be practical in such a situation, but general information may be obtained about the contributor using different sources. As with the prior system, certain contributors may be provided with a web site address and may be provided with a numeric indicator, such as a contributor number. Such a contributor may have a history of contributing certain amounts to various institutions and may therefore have a profile available. 
     Generally, the contributor may log in to the web site maintained by a charity or group of charities using debtor device  106  and may log into server  102 . The server may rely on account/transaction database  118  for information on the user/contributor. Alternately, if external information may be obtained on the user/contributor from an external source, such as a credit bureau, database containing personal data, or internet source, such a source may be utilized to augment the profile of the individual. The user/contributor may be asked to respond to certain questions, such as income level, current home address, or current business address and position. Rules may then be applied by the server as described above to develop a set of offers, where offers may include a one-time gift or a payment option, possibly including free offers with each offer. For example, if absolutely nothing is known about a contributor, and the contributor does not provide significant substantive information in response to questions, such as refusing to specify income level, a default level of participation may be provided, such as options of $25, $50, $100, $250, or $500, or payments of $25 or $50 per month for a year. However, if certain information is known, the individual may be presented with different offers. For example, if the individual earns over $150,000 per year and is known to have made contributions to the present charity of over $1000 over the past year and other charities over $1000 in the past year, this may trigger a rule. For example, if the user/contributor has contributed more than $500 but less than $2000 over the past year and has a stated annual income of over $100,000, the server  102  may present the user/contributor with options of $500, $1000, $2000, and $5000 for immediate contribution, with his/her name mentioned as a bronze, silver, gold, and platinum contributor, respectively, in an annual charity publication. The user can select one of these, or an alternative selection, where the user/contributor may enter additional information, may be provided. For example, if the user/contributor wishes to specifically contribute $1500, she may enter that amount, or may enter a desired amount of $150 per month for 12 months. Subsequent rules may come into play, but generally the amount contributed may be accepted and the transaction resolved. Payment may be made as stated previously, where the charity stands in the place of the creditor in the foregoing description. Note that certain modules in the embodiment of  FIG. 2  may be unnecessary or have different functionality. If a credit bureau is not contacted but the accounts database  118  or other charity relevant database is contacted, credit bureau module  202  and parser module  204  seeks the information requested from the relevant data source and may parse the information obtained. Further, a debt portfolio manager  220  in this instance may be a charitable contribution manager, enabling contributions to be allocated to appropriate recipients according to predetermined rules. 
     An alternate example is a settlement of an insurance claim. In the present system  100 , the user may be an individual or entity having a claim or rights to a claim, or appropriate representative, called here the claimant. The user/claimant may log into the server  102 , and the server may be connected to, for example, a credit bureau server  116  and account/transaction database  118  or other external database or source of data. In this scenario, the account database may include previous settlement offers made to the user/claimant, financial information about the claimant obtained from legal sources, severity of the injury/accident, or other relevant information. Based on the information available, as well as any history of claims paid for similar claims typically available in account/transaction database  118 , the server may prepare a set of insurance settlement offers according to rules established by the insurer. For example, if the injury is a death of a person with no immediate family, aged 58, caused by a car accident, the claimant may be offered $500,000 now, or $30,000 per year for 20 years, or $25,000 per year for 30 years. According to the rules presented by the insurer, the claimant may be entitled to accept the settlement or may provide alternate terms. The aspects of the current design dealing with payment (ETF, credit card payments, etc.) would typically not be required, but once the transaction is resolved according to the rules provided and the agreement obtained, the payment may be authorized and paid by a third party or by the creditor as appropriate. The information regarding resolution, such as the fact that the claim has been settled and the portfolio of claims and reports, may be generated where appropriate. 
     Other examples of resolving transactions and/or claims owed may be realized using the current design. 
     Thus according to one embodiment there is provided an apparatus for resolving a claim owed, the apparatus comprising a server arrangement comprising means for transmitting a communication to a claimant using one of a number of available communication channels inviting the claimant to contact the server arrangement for the purpose of attempting to settle the claim, an information seeking module configured to obtain claimant financial information from a source other than the server arrangement and the claimant in response to the claimant contacting the server arrangement, a rules based decision module configured to employ only extracted data identified as pertinent to the claimant from obtained claimant financial information, the extracted data extracted in accordance with rules established by a party responsible for satisfying the claim available to the rules based decision module, and analyze the extracted data in order to determine a potential resolution strategy for the claim comprising a plurality of individualized claim settlement offers determined specifically for the debtor based on the extracted data identified as pertinent, and a memory configured to maintain information related to the claim and the rules employed by the rules based decision module. The server arrangement is configured to offer the claimant a plurality of claim settlement options determined specifically for the claimant determined based on the extracted data, and the server arrangement is further configured to attempt to obtain agreement from the claimant to settle the claim. 
     According to a further embodiment there is provided an apparatus for resolving a claim owed, comprising a server arrangement comprising a claimant financial information seeking module configured to obtain claimant financial information from a financial information source other than the server arrangement and the claimant in response to the claimant contacting the server arrangement, a decision module configured to employ only extracted data identified as pertinent from obtained claimant financial information, the extracted data extracted in accordance with a set of rules established by an insurer and process the extracted data identified as pertinent to determine a potential resolution strategy for the claim owed, and means for contacting the claimant by transmitting a communication to the claimant inviting the claimant to contact the server arrangement for the purpose of resolving the claim owed using one of a number of available communication channels, and a memory configured to maintain information related to the claim owed and the set of rules established by the insurer. The server arrangement is configured to offer the claimant a plurality of claim settlement options determined specifically for the claimant determined based on the extracted data. 
     According to another embodiment, there is provided an apparatus for resolving a claim, comprising a server arrangement comprising a communications module configured to transmit, using one of a number of available communication channels, a communication inviting a claimant to contact the server arrangement for the purpose of attempting to resolve the claim, a credit information seeking module configured to obtain credit information for the claimant in response to the claimant contacting the server arrangement, and a rules based engine configured to employ only extracted data identified as pertinent from obtained claimant account information, the extracted data extracted in accordance with rules established by an insurer, and determine a plurality of individualized transaction settlement offers determined specifically for the claimant depending on financial status of the claimant, and a memory configured to maintain information related to the claim owed and the rules employed by the rules based engine. The server arrangement is configured to provide the plurality of individualized transaction settlement offers to direct the claimant to a resolution of the claim owed based on the rules and the credit information for the claimant. 
     By the foregoing description, an improved system and method for transaction resolution have been described. The improved system and method may be substantially or completely internet based such that the user can access the settlement server to resolve transactions, such as manage debt, from a platform providing, for example, Internet browsing capabilities. 
     The foregoing description of specific embodiments reveals the general nature of the disclosure sufficiently that others can, by applying current knowledge, readily modify and/or adapt the system and method for various applications without departing from the general concept. Therefore, such adaptations and modifications are within the meaning and range of equivalents of the disclosed embodiments. The phraseology or terminology employed herein is for the purpose of description and not of limitation.