# US 8,543,499 B2 · Reducing risks related to check verification > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 8,543,499 B2 - Document ID: US8543499B2 - Status: Granted - Kind: B2 - Application number: 11/615,747 - Filed: 2006-12-22 - Published: 2007-07-19 - Granted: 2013-09-24 - Earliest claimed: 2004-10-29 - Assignees: American Express Travel Related Services Company, Inc. - Applicants: Kathleen Haggerty; Benedict O. Okoh; Chao M. Yuan - Inventors: Kathleen Haggerty; Benedict O. Okoh; Chao M. Yuan - Web page: https://patentgrep.com/patent/US8543499B2 ## CPC - G06Q 40/03: Credit; Loans; Processing thereof - G06Q 20/102: {Bill distribution or payments} - G06Q 40/00: Finance; Insurance; Tax strategies; Processing of corporate or income taxes - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract 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. ## Claims ### Claim 1 A computer-based method comprising: modeling, by a computer-based system for reducing merchant risks comprising a processor and a tangible, non-transitory memory, consumer spending patterns using individual and aggregate consumer data, including tradeline data, internal customer data, and consumer panel data to produce a model of consumer spending patterns, wherein the computer-based system comprises a processor and a tangible, non-transitory memory, and wherein the model is stored in the memory of the computer-based system; estimating, by the computer-based system, a credit-related characteristic of the customer based on tradeline data of the customer, identified balance transfers of the customer, and the model of consumer spending patterns offsetting, by the computer-based system, the previous balance transfers from the estimated credit-related characteristic; determining, by the computer-based system, a risk value of the customer based on the estimated credit-related characteristic; and making a check acceptance decision based on the determined risk value. ### Claim 2 (depends on 1) The method of claim 1, wherein said determining comprises: determining whether the customer is a high-risk customer or a low-risk customer. ### Claim 3 (depends on 2) The method of claim 2, wherein said making comprises: accepting the check when the customer is a low-risk customer; and declining the check when the customer is a high-risk customer. ### Claim 4 (depends on 1) The method of claim 1, wherein said determining comprises: weighting at least one factor relating to the customer's cheek based on the estimated credit characteristic; and calculating a risk value based on the weighted factor. ### Claim 5 (depends on 4) The method of claim 4, wherein factors relating to the customer's check include: velocity, prior activity, the customer's presence in check databases, size of the check, prior had check activity by geographic location, and prior bad check activity by merchant location. ### Claim 6 (depends on 1) The method of claim 1, wherein the credit-related characteristic is at least one of: a size of the customer's spending wallet, a size of the customer's revolving spending, a size of the customer's transacting spending, a share of wallet size for a particular spend category, a spend capacity of the customer, or an amount of balance transfers transacted by the customer. ### Claim 7 An apparatus comprising: a processor for reducing merchant risks; and a tangible, non-transitory memory in communication with the processor, wherein the memory stores a plurality of processing instructions for directing the processor to: model consumer spending patterns using individual and aggregate consumer data, including tradeline data, internal customer data, and consumer panel data; estimate a credit-related characteristic of the customer based on tradeline data of the customer, identified balance transfers of the customer, and the model of consumer spending patterns, wherein the credit-related characteristic comprises a spend amount associated with the individual consumer; offset the previous balance transfers from the estimated credit-related characteristic; determine a risk value of the customer based on the estimated credit-related characteristic; and make a check acceptance decision based on the determined risk value. ### Claim 8 (depends on 7) The apparatus of claim 7, wherein said instructions for directing the processor to determine a risk value comprise instructions for directing the processor to: determine whether the customer is a high-risk customer or a low-risk customer. ### Claim 9 (depends on 8) The apparatus of claim 8, wherein said instructions for directing the processor to make a check acceptance decision comprise instructions for directing the processor to: guarantee the check when the customer is a low-risk customer; and decline to guarantee the check when the customer is a high-risk customer. ### Claim 10 (depends on 7) The apparatus of claim 7, wherein said instructions for directing the processor to determine a risk value comprise instructions for directing the processor to: weight at least one factor relating to the customer's check based on the estimated credit characteristic; and calculate a risk value based on the weighted factor. ### Claim 11 (depends on 10) The apparatus of claim 10, wherein factors relating to the customer's check include: velocity, prior activity, the customer's presence in check databases, size of the check, prior bad check activity by geographic location, and prior bad check activity by merchant location. ### Claim 12 (depends on 7) The apparatus of claim 7, wherein the credit-related characteristic is at least one of a size of the customer's spending wallet, a size of the customer's revolving spending, a size of the customer's transacting spending, a share of wallet size for a particular spend category, a spend capacity of the customer, or an amount of balance transfers transacted by the customer. ### Claim 13 An article of manufacture including a computer readable medium having instructions stored thereon that, in response to execution by a computing device for reducing merchant risks, cause the computing device to perform operations comprising: modeling consumer spending patterns using individual and aggregate consumer data including tradeline data, internal customer data, and consumer panel data; estimating a credit-related characteristic of the customer based on tradeline data of the customer, identified balance transfers of the customer, and the model of consumer spending patterns, wherein the credit-related characteristic comprises a spend amount associated with the individual consumer; offsetting the previous balance transfers from the estimated credit-related characteristic; determining a risk value of the customer based on the estimated credit-related characteristic; and making a check acceptance decision based on the determined risk value. ### Claim 14 (depends on 13) The article of manufacture of claim 13, further comprising determining whether the customer is a high-risk customer or a low-risk customer. ### Claim 15 (depends on 14) The article of manufacture of claim 14, further comprising guaranteeing the check when the customer is a low-risk customer; and declining to guarantee the check when the customer is a high-risk customer. ### Claim 16 (depends on 13) The article of manufacture of claim 13, further comprising weighing at least one factor relating to the customer's check based on the estimated credit characteristic; and calculating a risk value based on the weighted factor. ### Claim 17 (depends on 16) The article of manufacture of claim 16, wherein factors relating to the customer's check include: velocity, prior activity, the customer's presence in check databases, size of the check, prior bad check activity by geographic location, and prior bad check activity by merchant location. ### Claim 18 (depends on 13) The article of manufacture of claim 13, wherein the credit-related characteristic is at least one of: a size of the customer's spending wallet, a size of the customer's revolving spending, a size of the customer's transacting spending, a share of wallet size for a particular spend category, a spend capacity of the customer, or an amount of balance transfers transacted by the customer.