Abstract: Commercial size of spending wallet (“CSoSW”) is the total business spend of a business including cash but excluding bartered items. Commercial share of wallet (“CSoW”) is the portion of the spending wallet that is captured by a particular financial company. A modeling approach utilizes various data sources to provide outputs that describe a company's spend capacity. Marketing companies that sell lists compile those lists by searching one or more databases for names and/or businesses that match certain criteria. Those marketing companies can use the CSoW/CSoSW modeling approach to show predicted spend and/or revenues for each company on a list. This makes the list more valuable to list buyers.

Abstract: Systems and methods are described that simulate a credit score. The system enables a user to modify a credit data element in order to determine its effect on a credit score. The user can modify the element directly or simulate an action that, if performed, would modify the element. Since the number of possible modifications and actions can be overwhelming, in one embodiment, the system suggests modifications and actions to be simulated. These suggestions can be tailored to a user's goal, such as increasing a credit score by a particular number of points or allocating a particular sum of money in order to maximize a credit score. In one embodiment, the system obtains credit data from multiple credit bureaus and can determine credit scores using different algorithms, such as the different algorithms used by the different credit bureaus.

Abstract: Commercial size of spending wallet (“CSoSW”) is the total business spend of a business including cash but excluding bartered items. Commercial share of wallet (“CSoW”) is the portion of the spending wallet that is captured by a particular financial company. A modeling approach utilizes various data sources to provide outputs that describe a company's spend capacity. Private equity firms and other investors of small businesses can use the CSoW/CSoSW modeling approach to more accurately evaluate small and privately held companies, both during investment and for evaluating prospective investments. Over-the-counter securities trading systems can also use this modeling approach to provide more accurate information and/or rankings of listed companies to their customers.

Abstract: Commercial size of spending wallet (“CSoSW”) is the total business spend of a business including cash but excluding bartered items. Commercial share of wallet (“CSoW”) is the portion of the spending wallet that is captured by a particular financial company. A modeling approach utilizes various data sources to provide outputs that describe a company's spend capacity. A mutual fund rating company can use this CSoW/CSoSW modeling approach to predict the performance of funds that invest in a particular industry or sector. In addition, since mutual funds often provide guidelines for selecting stocks, rating companies can use this modeling approach to predict the performance of companies in a fund's portfolio.

Abstract: Time series consumer spending data, point-in-time balance information, internal customer financial data and consumer panel information provides input to a model for consumer spend behavior on plastic instruments or other financial accounts, from which approximations of spending ability may be reliably identified and utilized to promote additional consumer spending.

Abstract: A system and method is provided to allow a consumer to interactively explore his credit score by submitting hypothetical values based on his actual credit data. The system uses the consumer's real credit data and the submitted hypothetical values to calculate a simulated credit score based on a simulator scorecard. The consumer may then observe the changes in the resultant scores. The system and the scorecard may utilize fewer data elements than a complete credit-worthiness scorecard and may instead focus on the key elements affecting a consumer's credit score. The system may be implemented in part on a web server or as a stand-alone application. The system may also update the score dynamically as the consumer adjusts the hypothetical values or may require the consumer to affirmatively submit the new hypothetical data.

Abstract: Systems and methods are described that simulate a credit score. The system enables a user to modify a credit data element in order to determine its effect on a credit score. The user can modify the element directly or simulate an action that, if performed, would modify the element. Since the number of possible modifications and actions can be overwhelming, in one embodiment, the system suggests modifications and actions to be simulated. These suggestions can be tailored to a user's goal, such as increasing a credit score by a particular number of points or allocating a particular sum of money in order to maximize a credit score. In one embodiment, the system obtains credit data from multiple credit bureaus and can determine credit scores using different algorithms, such as the different algorithms used by the different credit bureaus.

Abstract: Share of Wallet (“SOW”) is a modeling approach that utilizes various data sources to provide outputs that describe a consumers spending capability, tradeline history including balance transfers, and balance information. These outputs can be appended to data profiles of customers and prospects and can be utilized to support decisions involving prospecting, new applicant evaluation, and customer management across the lifecycle. A SOW score focusing on a consumer's spending capability can be used in the same manner as a credit bureau score.

Abstract: Commercial size of spending wallet (“CSoSW”) is the total business spend of a business including cash but excluding bartered items. Commercial share of wallet (“CSoW”) is the portion of the spending wallet that is captured by a particular financial company. A modeling approach utilizes various data sources to provide outputs that describe a company's spend capacity. Private equity firms and other investors of small businesses can use the CSoW/CSoSW modeling approach to more accurately evaluate small and privately held companies, both during investment and for evaluating prospective investments. Over-the-counter securities trading systems can also use this modeling approach to provide more accurate information and/or rankings of listed companies to their customers.

Abstract: Share of Wallet (“SOW”) is a modeling approach that utilizes various data sources to provide outputs that describe a consumers spending capability, tradeline history including balance transfers, and balance information. These outputs can be appended to data profiles of customers and prospects and can be utilized to support decisions involving prospecting, new applicant evaluation, and customer management across the lifecycle. The outputs can be used as attributes to consider in developing a credit bureau scorecard.

Abstract: Commercial size of spending wallet (“CSoSW”) is the total business spend of a business including cash but excluding bartered items. Commercial share of wallet (“CSoW”) is the portion of the spending wallet that is captured by a particular financial company. A modeling approach utilizes various data sources to provide outputs that describe a company's spend capacity. A mutual fund rating company can use this CSoW/CSoSW modeling approach to predict the performance of funds that invest in a particular industry or sector. In addition, since mutual funds often provide guidelines for selecting stocks, rating companies can use this modeling approach to predict the performance of companies in a fund's portfolio.

Abstract: Commercial size of spending wallet (“CSoSW”) is the total business spend of a business including cash but excluding bartered items. Commercial share of wallet (“CSoW”) is the portion of the spending wallet that is captured by a particular financial company. A modeling approach utilizes various data sources to provide outputs that describe a company's spend capacity. A mutual fund rating company can use this CSoW/CSoSW modeling approach to predict the performance of funds that invest in a particular industry or sector. In addition, since mutual funds often provide guidelines for selecting stocks, rating companies can use this modeling approach to predict the performance of companies in a fund's portfolio.

Abstract: A system and method is provided to allow a consumer to interactively explore his credit score by submitting hypothetical values based on his actual credit data. The system uses the consumer's real credit data and the submitted hypothetical values to calculate a simulated credit score based on a simulator scorecard. The consumer may then observe the changes in the resultant scores. The system and the scorecard may utilize fewer data elements than a complete credit-worthiness scorecard and may instead focus on the key elements affecting a consumer's credit score. The system may be implemented in part on a web server or as a stand-alone application. The system may also update the score dynamically as the consumer adjusts the hypothetical values or may require the consumer to affirmatively submit the new hypothetical data.

Abstract: Share of Wallet (“SOW”) is a modeling approach that utilizes various data sources to provide outputs that describe a consumers spending capability, tradeline history including balance transfers, and balance information. These outputs can be appended to data profiles of customers and prospects and can be utilized to support decisions involving prospecting, new applicant evaluation, and customer management across the lifecycle. A SOW score focusing on a consumer's spending capability can be used in the same manner as a credit bureau score.

Abstract: A system and method is provided to allow a consumer to interactively explore his credit score by submitting hypothetical values based on his actual credit data. The system uses the consumer's real credit data and the submitted hypothetical values to calculate a simulated credit score based on a simulator scorecard. The consumer may then observe the changes in the resultant scores. The system and the scorecard may utilize fewer data elements than a complete credit-worthiness scorecard and may instead focus on the key elements affecting a consumer's credit score. The system may be implemented in part on a web server or as a stand-alone application. The system may also update the score dynamically as the consumer adjusts the hypothetical values or may require the consumer to affirmatively submit the new hypothetical data.

Abstract: Share of Wallet (“SoW”) is a modeling approach that utilizes various data sources to provide outputs that describe a consumer's spending capability, tradeline history including balance transfers, and balance information. These outputs can be appended to data profiles of customers and prospects and can be utilized to support decisions involving prospecting, new applicant evaluation, and customer management across the lifecycle. The likelihood of default determined by the SoW model, when applied to a loan portfolio, can reduce the amount of credit enhancement required for an asset-backed securities rating.

Abstract: Systems and methods are described that simulate a credit score. The system enables a user to modify a credit data element in order to determine its effect on a credit score. The user can modify the element directly or simulate an action that, if performed, would modify the element. Since the number of possible modifications and actions can be overwhelming, in one embodiment, the system suggests modifications and actions to be simulated. These suggestions can be tailored to a user's goal, such as increasing a credit score by a particular number of points or allocating a particular sum of money in order to maximize a credit score. In one embodiment, the system obtains credit data from multiple credit bureaus and can determine credit scores using different algorithms, such as the different algorithms used by the different credit bureaus.

Abstract: Time series consumer spending data, point-in-time balance information and consumer panel information provide input to a model for consumer spend behavior on plastic instruments or other financial accounts, from which approximations of spending ability and share of wallet may be reliably identified and utilized to promote additional consumer spending.

Abstract: Time series consumer spending data, point-in-time balance information and consumer panel information provide input to a model for consumer spend behavior on plastic instruments or other financial accounts, from which approximations of spending ability and share of wallet may be reliably identified and utilized to promote additional consumer spending.

Abstract: A system and method is provided to allow a consumer to interactively explore his credit score by submitting hypothetical values based on his actual credit data. The system uses the consumer's real credit data and the submitted hypothetical values to calculate a simulated credit score based on a simulator scorecard. The consumer may then observe the changes in the resultant scores. The system and the scorecard may utilize fewer data elements than a complete credit-worthiness scorecard and may instead focus on the key elements affecting a consumer's credit score. The system may be implemented in part on a web server or as a stand-alone application. The system may also update the score dynamically as the consumer adjusts the hypothetical values or may require the consumer to affirmatively submit the new hypothetical data.