Patent Application
20080059364
A general architecture that implements various features of specific embodiments of the invention will now be described with reference to the drawings. The drawings and the associated descriptions are provided to illustrate embodiments of the invention and not to limit the scope of the invention. Throughout the drawings, reference numbers are re-used to indicate correspondence between referenced elements. In addition, the first digit of each reference number indicates the figure in which the element first appears.
Systems and methods are described in connection with a financial trustworthiness assessment service that provides an assessment of an individual's financial trustworthiness. The financial trustworthiness assessment is based, at least in part, on transaction-level financial information associated with the individual, as well as on other data associated with the individual that may be financially-based or otherwise indicative of financial trustworthiness.
In various preferred embodiments, the financial trustworthiness assessment service is able to access transaction-level data such as records of check, debit card, credit card, and money order transactions, or remittance transactions, which may be more readily available for individuals with little or no credit histories. This kind of transaction-level data may be available from, among other sources, a check authorization database, such as one that can is maintained for the purpose of determining the risk of accepting a given check or other promissory payment and for authorizing or declining the promissory payment. For purposes of this disclosure, a “point of sale” or “remittance” may include, but is not limited to, any of the following: a physical location at which a purchase, payment, or other financial transaction takes place; a non-physical, computer-assisted “location” at which a purchase, payment, or other transaction takes place, such as at a web site of an Internet or other network-accessible online merchant, or a non-physical, telephone-assisted “location” at which purchases, payments, and other types of financial transactions may take place over the telephone.
Furthermore, in preferred embodiments, the financial trustworthiness assessment service also uses data available from a variety of other sources in order to assess the financial trustworthiness of an individual, as will be described herein in greater detail.
By using data about point-of-sale transactions, remittances, and other financial relationships in which an individual participates, along with credit information and/or publicly available information about the individual, embodiments of the financial trustworthiness assessment service can provide an assessment of the individual that may be more inclusive of a broad spectrum of the individual's financial behaviors, and thus more accurate, than one based on credit information alone, especially for individuals with “thin” credit files.
A financial trustworthiness assessment that is based in part on transaction-level data can help more quickly identify and confirm potential risk in a situation in which, for example, an individual with a history of paying credit accounts on time begins paying the accounts late. While this behavior alone may not immediately trigger a lowered assessment of financial trustworthiness in a conventional credit-based assessment system, having the benefit of additional transaction-level data allows for a more accurate assessment of the individual's current financial trustworthiness, such as when the transaction-level data shows that the individual has also been engaging in point-of-sale transactions that signal risk—such as purchasing groceries on a credit card that has almost reached its maximum.
Further benefits of embodiments of the systems and methods will be apparent to one of skill in the art upon reading the following description with reference to the figures.
Furthermore, the modules may be hosted by one or more processor-based platforms, such as those implemented by Windows-based and/or UNIX-based operating platforms and may utilize one or more conventional programming languages such as DB/C, C, C++, UNIX Shell, and Structured Query Language (SQL) to accomplish methods in accordance with the invention, including system functionality, data processing, and communications between functional modules.
As depicted in
The client 105 may be an individual, a business, or other entity that is interested in obtaining an assessment of the subject's financial trustworthiness. For example, the client may be a prospective landlord, employer, or other entity considering accepting a promissory payment from the individual or otherwise extending credit or financial trust to the subject.
Additionally, the client 105 may contract with the service 100 to receive multiple assessments in response to multiple assessment requests, for an agreed upon, regularly paid, fee. In other embodiments, the financial assessment service 100 may provide assessments to individuals and entities with whom the service 100 does not have a pre-established relationship, such as to clients who pay for the assessments on a request-by-request basis.
For simplicity of description, a single client 105 is depicted as communicating with the financial trustworthiness assessment service 100. However, the service 100 preferably provides financial trustworthiness assessments to many clients 105, as will be clear to one of skill in the art upon reading the disclosure herein. Thus, description of the client 105 is to be understood as pertaining to one or to a plurality of clients 105.
The client 105 may communicate with the financial trustworthiness assessment service 100 using any of a variety of communication technologies. For example, the interaction between the client 105 and a client interface 110 of the financial trustworthiness assessment service 100 takes place, in one embodiment, using a communications medium, such as the Internet, which is a global network of computers.
In other embodiments, the communications medium can be any communication system including, by way of example, dedicated communication lines, telephone networks, wireless data transmission systems, two-way cable systems, customized computer networks, interactive kiosk networks, automatic teller machine networks, interactive television networks, and the like.
In some embodiments, the client 105 may communicate using a computer terminal, including, for example, a cash register terminal, payment terminal, mobile phone, or RFID in communication with one or more peripheral devices that allow for the automatic input of data such as scanners for electronically reading driver's license, other identification card, social security number, check MICR or other identification, biometric data, and the like. In other embodiments, the client 105 may communicate using a computer terminal, such as a payment terminal, that accepts manual input of driver's license information or MICR information without using a peripheral device.
The client interface 110 provides a query interface that allows the client 105 to submit a financial trustworthiness assessment request to the service 100.
The client 105 sends to the financial trustworthiness assessment service 100 a request that provides identifying information about the subject. For example, the client 105 may provide one or more of the following types of identifying information about the subject: name, birth date, driver's license number, social security number, other identification number, address, phone number(s), employer, school, account number(s), photograph, biometric data, signature, other scanned data, and the like. In various embodiments, other types of information, such as identifying information about the client 105 may be sent to the financial trustworthiness assessment service 100 with the request.
In some embodiments, the client 105 may also send additional information about the request itself. For example, in embodiments in which different types of assessments may be offered, as will be described with reference to
The client interface 110 of the financial trustworthiness assessment service 100 receives the request information from the client 105 and passes the information to a financial trustworthiness assessment engine 120. The financial trustworthiness assessment engine 120 uses the identifying information together with data from a wide variety of data sources to generate an assessment of the subject's financial trustworthiness. With reference to the embodiment depicted in
In various embodiments, the financial trustworthiness assessment engine 120 may perform the requested assessment using one or more statistical or other modeling methods, decision tree or other rule-based or classification systems, calculation scorecards, fuzzy logic systems, neural networks, or a combination of the above and/or other decision-making systems. For example, models may be built on historical financial data to predict what behaviors or combinations of factors may be indicative of financial risk.
Embodiments of the financial trustworthiness assessment engine 120 may use information about the type of assessment being requested to identify an associated scorecard or other system for weighting the various types of data to be used in the selected assessment. For example, a pre-employment financial trustworthiness assessment may assign extra weight to information received from the Department of Motor Vehicles and assign less weight to credit-related information about a potential employee. In some embodiments, types of assessment may also be categorized based on a level of expense associated with obtaining the information for the assessment and performing the assessment. In some embodiments, information a type of assessment being requested may be explicitly provided to the financial trustworthiness assessment service 100 with a given request, while in other embodiments, requests from a given client 105 may always be associated with a given type of assessment. In other embodiments, other methods of assigning an assessment method to a given assessment request may be used.
Embodiments of the financial trustworthiness assessment engine 120 may perform the assessment based, at least in part, on data sources that may be stored, entirely or in part, locally within computer processors and/or associated storage devices associated with the financial trustworthiness assessment service 100. The financial trustworthiness assessment engine 120 may, additionally or alternatively, perform the assessment based, at least in part, on data sources that may be stored externally to the financial trustworthiness assessment service 100.
The check authorization database 125 includes data about consumers who use checks and/or debit cards to make payments. For example, the check authorization database 125 may store data about consumers who pay with checks or debit cards for purchases at merchant points-of-sale, for payment of utility bills or other remittances, for purchasing money orders, and the like. The check authorization database 125 may store information about the consumers' check-writing and payment history. The information may be used as part of a check authorization system in conjunction with models or rules built to predict which checks will be returned for initial non-payment, as well as which checks will be returned and never paid, for recommending to a client whether or not to accept a proffered check or debit-card payment.
In conjunction with the financial trustworthiness assessment engine 120 depicted in
The financial trustworthiness assessment engine 120 in
In various embodiments, the repository of consumer transaction-level data 130 stores data about individual consumer transactions. For example, the repository of consumer transaction-level data 130 may store information about a date, a time, a place of transaction, an amount of transaction, a type of transaction, and payment history associated with the transaction, as well as other related information. In various embodiments, the repository of consumer transaction-level data 130 may include information about check and debit card transactions, as well as transactions paid using a credit card, a money order, money transfer or other payment instruments. Unlike data sources that providing information about consumer accounts at the account-level, which includes data such as current balance, average balance, number of late payments within a recent time period, and the like, the repository of consumer transaction-level data 130 includes more detailed information on how, where, and when funds from a subject's account were spent. Such detailed information allows the financial trustworthiness assessment engine 120 to perform assessments that may include a comparison of one transaction on a given day to other transactions in the same day or an analysis of transaction patterns over a time span, such as, for example, over a three-month period. For example, using data from the repository of consumer transaction-level data 130 and/or the check authorization database 125, the assessment engine 120 may identify a subject's pattern of much increased check-writing activity over the last thirty days, or, even more significant from a risk perspective, over the last sixty days or even life of the account or the subject. The assessment engine 120 may identify, not only that a subject's credit card was used six times in one day, but also the type of merchant where the card was used, and whether or not the purchases represent above-average transactions for the subject.
In preferred embodiments, the repository of consumer transaction-level data 130 is updated with data obtained from a wide variety of transactors 135, such as retailers and other merchants, utility companies and other remittance providers and/or billers, property management companies, and financial, mortgage or lending services. The transactors 135 provide frequent updates about their transactions to the financial trustworthiness assessment service 100.
In the embodiment depicted in
In some embodiments of the service 100, the financial trustworthiness assessment engine 120 uses information from one or more repositories of information about other types of financial accounts. For example, data about mortgages, loans, and/or other types of financial accounts associated with the consumer may provide additional useful information for making an assessment of the consumer's financial trustworthiness.
In some embodiments of the service 100, the financial trustworthiness assessment engine 120 receives information from the repository of credit rating data 150 that may include data available from one or more credit bureaus 155, such as, but not limited to, Experian, Equifax, TransUnion, or a third-party provider of consumer credit-related data. It should be noted that while the repository of consumer credit rating data is depicted in
In some embodiments of the system, the financial trustworthiness assessment engine 120 stores in the assessment repository 115 results of a financial trustworthiness assessment of a subject. The financial trustworthiness assessment engine 120 may also access the stored information upon receiving a request to perform a subsequent financial trustworthiness assessment of the subject. Information about the subject and about previously performed financial trustworthiness assessments of the subject stored in the assessment repository 115 may allow the financial trustworthiness assessment engine 120 to identify and analyze changes and/or patterns in the subject's financial behaviors over time that may be indicative of a change in financial trustworthiness, such as may occur in connection with loss of a job, or a “mid-life crisis.”
Current legislation, such as federal legislation including the Fair Credit Reporting Act (FCRA) and Fair and Accurate Credit Transactions (FACT) Act provides limitations on how, where, and for what purpose certain types of consumer credit-related data may be stored and used, and may thus impose limitations on what data may be stored in the assessment repository 115 and how it may be used. For example, such legislation may impose limitations on whether information about past assessments performed at the request of different clients 105 may be stored separately per client, or mixed. Preferences of the client 105 and/or of the financial trustworthiness assessment service 100 may also affect such a determination, as provided for within the bounds of the law.
The availability of data that allows for an analysis of changes and/or patterns in the subject's financial behaviors over time may also allow the financial trustworthiness assessment engine to identify indications of stolen identity and/or other fraud when the subject's current financial activity is compared to past financial activity.
In addition to the data repositories 115, 125, 130, 140, 147, and 150 described above, which are depicted in
Although with respect to
As depicted in
The above-described examples of the use of transaction-based information 210, 220, 230, 240, 247 as factors in a financial trustworthiness assessment determination 200 rely upon a comparison of the transaction data with other known data. In other embodiments of a financial trustworthiness assessment determination 200, the transaction-level data may alternatively or additionally be used in conjunction with an assessment scorecard to provide the determination 200. These and other uses of the transaction-level data will be familiar to one of skill in the art after reading the disclosure contained herein. Furthermore, as will also be familiar to one of skill in the art after reading this disclosure, in various embodiments, many other types of data may be obtained from the transaction-level data that allow for an assessment 200 of the subject's financial trustworthiness.
In addition, as was described with reference to
In various embodiments of the systems and methods disclosed herein, as will be described with reference to
In block 420, the financial trustworthiness assessment service 100 accesses the check authorization database 125 that includes, among other types of information, information about DDA-related financial transactions in which the subject participated. The financial trustworthiness assessment service 100 may also access additional information about the subject from a wide variety of other sources of consumer information 115, 125, 130,140,150, 160, 165.
In block 430, the financial trustworthiness assessment engine 120 of the financial trustworthiness assessment service 100 receives the data from the check authorization database 125 and other data sources 115, 130, 140, 150, 160, 165 accessed in block 420 and uses the data to perform a financial trustworthiness assessment of the subject.
In block 440, the financial trustworthiness assessment service 100 reports the results of the assessment to the client 105. As was described with reference to
Furthermore, the results of the assessment may be transmitted to the client using any of a variety of communications media, including, but not limited to, an email message, a text message, a web page or other computer-viewable message, a telephone message or other audible message, and a postcard or letter that may be sent by way of the postal service or other delivery service.
For example, the assessment service 100 may agree to provide assessments that are customized to the preferences of the client 105. The customized assessments may draw upon data sources agreed upon by the client 105 and the financial trustworthiness assessment service 100 and/or may include assessment techniques agreed upon by the client 105 and the financial trustworthiness assessment service 100, as will be described in greater detail below. Furthermore, a given client 105 may request that different types of financial trustworthiness assessment determination methods are used for different types of requests and/or under different circumstances.
Referring now to the flowchart of
In block 415, the financial trustworthiness assessment service 100 identifies the sources to use for the assessment and the type(s) of assessment to perform. In some embodiments, information used by the financial trustworthiness assessment service 100 to identify the sources and type(s) of assessment to perform are included in the request from the client 105. For example, the request may be transmitted to the financial trustworthiness assessment service 100 by way of a web page that allows the client 105 to select from amongst a set of data sources and/or from amongst a set of assessment techniques. In other embodiments, the financial trustworthiness assessment service 100 relies, in whole or in part, on stored data that provides instructions for carrying out the assessment request for the client 105.
In block 425, the financial trustworthiness assessment service 100 accesses the identified data sources, including the check authorization database 125 that includes, among other types of information, information about financial transactions in which the subject participated. The financial trustworthiness assessment service 100 may also access additional identified sources of consumer information 115, 125, 130, 140, 150, 160, 165 that are appropriate for the current assessment request.
In block 435, the financial trustworthiness assessment engine 120 performs the financial trustworthiness assessment. Examples of assessment methods that may be used by the financial trustworthiness assessment engine 120 include, but are not limited to, rule-based decisioning methods as well as various types of statistical modeling. In addition, combinations of rule-based methods and modeling methods may be used together to generate the desired financial trustworthiness assessment.
To illustrate, one example of a rule-based assessment method could include the following instruction: “Use credit bureau information if the check account is less than thirty days old and no check writing history is available.”
Embodiments of statistical modeling assessment methods may use linear regression, neural nets, and the like, to create various models for determining financial trustworthiness based on the available data about the subject.
In some embodiments, assessment methods that combine statistical modeling methods with rule-based or other decision-making methods may be used. One example of a first combination assessment method may include the following instruction: “If the potential credit amount is greater than $10,000, use Score Model ABC, else use Score Model XYZ.”
A second type of combination assessment method determines which data sources and methods to use based on an initial assessment of the subject and on costs associated with various candidate assessment methods. One example of such a cost-based combination assessment method may include the following instruction: “Use low-cost rules to categorize the subject as ‘good’ or ‘bad.’ Then, only if the subject is categorized as ‘bad,’ perform further assessment, which may be more costly, by calculating a score for the subject.”
The blocks of the embodiments of the process 400 for performing a financial trustworthiness assessment, as depicted in
As will be familiar to a practitioner of skill in the art, the flowcharts of
While certain embodiments of the invention have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the invention. Indeed, the novel methods and systems described herein may be embodied in a variety of other forms; furthermore, various omissions, substitutions and changes in the form of the methods and systems described herein may be made without departing from the spirit of the invention. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the scope and spirit of the invention.
