摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
Share of Wallet (“SOW”) is a modeling approach that utilizes various data sources to provide scores that describe a consumers spending capability, tradeline history including balance transfers, and balance information. Share of wallet scores can be used as a parameter for determining whether or not to accept and/or guarantee a check. The share of wallet can be used to calculate a risk value of a customer. For example, the scores can weight one or more factors related to the check writer and differentiate between a low-risk customer and a high-risk customer.
摘要:
Commercial size of spending wallet (“SoSW”) is the total business spend of a business including cash but excluding bartered items. Commercial share of wallet (“SoW”) is the portion of the spending wallet that is captured by a particular financial company. Commercial SoW is a modeling approach that utilizes various data sources to provide outputs that describe a company's spend capacity. These outputs can be appended to data profiles of customers and prospects and can be utilized to support decisions involving prospecting, new account evaluation, and customer management across the lifecycle. Company financial statements are utilized to identify and calculate total business spend of a company that could be transacted using a commercial credit card. A spend-like regression model may then be developed to estimate annual commercial SoSW value for customers and prospects within a credit network.
摘要:
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.
摘要:
The spend capacity of a consumer typically increases as the number of consumers in the household increases, since the consumer can draw on the spending power of other consumers in the household. The size of wallet of the household is thus a better indicator of the consumer's spend capacity than an individual size of wallet. All consumers in a given household can be aggregated based on, for example, their address of record. Duplicate tradelines within each household are removed from consideration in a size of wallet estimate. A spend capacity is then estimated for each tradeline using calculations derived from a consumer behavior model. The spend capacities for all tradelines in the household are combined to determine a household size of wallet. Each consumer in the household is then tagged with the household size of wallet, rather than their individual size of wallet.