Systems and methods for identifying financial relationships
First Claim
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1. A method comprising:
- receiving, at a computer-based system for credit data analysis comprising a processor and a tangible, non-transitory memory, credit reporting data relating to a tradeline;
parsing, by the computer-based system, the credit reporting data to yield primary debtor data and secondary debtor data,wherein the primary debtor data identifies a primary debtor and wherein the secondary debtor data identifies a secondary debtor, andwherein a debtor entity comprises the primary debtor and the secondary debtor;
linking, by the computer-based system, the tradeline both with the primary debtor data and with the secondary debtor data,wherein the linking comprises combining, by the computer-based system, a subset of the primary debtor data and the secondary debtor data using a fingerprinting function to yield a tradeline fingerprint,wherein the subset comprises at least one data field of the primary debtor data and at least one data field of the secondary debtor data,wherein the fingerprinting function is at least one of;
a hash function, a checksum function, or a randomization function;
querying, by the computer-based system, a data store for the tradeline fingerprint,wherein the tradeline fingerprint identifies a household tradeline data setassociated both with the primary debtor and with the secondary debtor;
identifying, by the computer-based system, any balance transfers within the household tradeline data set;
discounting, by the computer-based system, an amount of the balance transfers from any spending identified in the household tradeline data set; and
determining, by the computer-based system, a purchasing ability of the debtor entity based on the household tradeline data set, the discounting, and a model of consumer spending patterns derived from individual and aggregate consumer data.
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Abstract
Improved systems and methods are provided for identifying financial relationships. In particular, financial relationships may be identified by associating tradelines with one or more people who sign or co-sign on the tradeline. In various embodiments a method is provided comprising, receiving, at a computer-based system for credit data analysis comprising a processor and a tangible, non-transitory memory, credit reporting data relating to a tradeline, parsing, by the computer-based system, the credit reporting data to yield primary debtor data and secondary debtor data, and linking, by the computer-based system, the tradeline with the primary debtor data and the secondary debtor data.
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Citations
19 Claims
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1. A method comprising:
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receiving, at a computer-based system for credit data analysis comprising a processor and a tangible, non-transitory memory, credit reporting data relating to a tradeline; parsing, by the computer-based system, the credit reporting data to yield primary debtor data and secondary debtor data, wherein the primary debtor data identifies a primary debtor and wherein the secondary debtor data identifies a secondary debtor, and wherein a debtor entity comprises the primary debtor and the secondary debtor; linking, by the computer-based system, the tradeline both with the primary debtor data and with the secondary debtor data, wherein the linking comprises combining, by the computer-based system, a subset of the primary debtor data and the secondary debtor data using a fingerprinting function to yield a tradeline fingerprint, wherein the subset comprises at least one data field of the primary debtor data and at least one data field of the secondary debtor data, wherein the fingerprinting function is at least one of;
a hash function, a checksum function, or a randomization function;querying, by the computer-based system, a data store for the tradeline fingerprint, wherein the tradeline fingerprint identifies a household tradeline data set associated both with the primary debtor and with the secondary debtor; identifying, by the computer-based system, any balance transfers within the household tradeline data set; discounting, by the computer-based system, an amount of the balance transfers from any spending identified in the household tradeline data set; and determining, by the computer-based system, a purchasing ability of the debtor entity based on the household tradeline data set, the discounting, and a model of consumer spending patterns derived from individual and aggregate consumer data. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A method comprising:
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identifying, by a computer-based system for credit data analysis comprising a processor and a tangible, non-transitory memory, tradeline data associated with a primary debtor in a data store containing credit bureau data; combining, by the computer-based system, a subset of the tradeline data using a fingerprinting function to yield a tradeline fingerprint, wherein the subset comprises at least two data fields of the tradeline data associated with the primary debtor and wherein the fingerprinting function is at least one of;
a hash function, a checksum function, or a randomization function;querying, by the computer-based system, the data store for the tradeline fingerprint to retrieve a secondary debtor associated with the tradeline fingerprint; querying, by the computer-based system, the data store for primary debtor data relating to the primary debtor and secondary debtor data relating to the secondary debtor; querying the data store for tradelines associated with the primary debtor and the secondary debtor, wherein the querying yields a household tradeline data set associated both with the primary debtor and with the secondary debtor; identifying, by the computer-based system, any balance transfers within the household tradeline data set; discounting, by the computer-based system, an amount of the balance transfers from any spending identified in the household tradeline data set; and determining, by the computer-based system, a purchasing ability of a debtor entity comprising the primary debtor and the secondary debtor based on the household tradeline data set, the discounting, and a model of consumer spending patterns derived from individual and aggregate consumer data. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A method comprising:
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receiving, at a computer-based system for credit data analysis comprising a processor and a tangible, non-transitory memory, credit reporting data relating to a tradeline; parsing, by the computer-based system, the credit reporting data to yield primary debtor data and secondary debtor data, wherein the primary debtor data identifies a primary debtor and wherein the secondary debtor data identifies a secondary debtor, and wherein a debtor entity comprises the primary debtor and the secondary debtor; linking, by the computer-based system, the tradeline both with the primary debtor data and with the secondary debtor data, wherein the linking comprises combining, by the computer-based system, a subset of the primary debtor data and the secondary debtor data using a fingerprinting function to yield a tradeline fingerprint, wherein the subset comprises at least one data field of the primary debtor data and at least one data field of the secondary debtor data, and wherein the fingerprinting function is at least one of;
a hash function, a checksum function, or a randomization function;querying, by the computer-based system, a data store for the tradeline fingerprint, wherein the fingerprint identifies a household tradeline data set associated with the primary debtor and the secondary debtor; estimating, by the computer-based system, credit-related information of the debtor entity based on the household tradeline data set, a previous balance transfer, and a model of consumer spending patterns, wherein the credit-related information comprises a spend amount associated with the debtor entity; and offsetting, by the computer-based system, the previous balance transfers from the estimated credit-related information. - View Dependent Claims (14, 15, 16, 17, 18, 19)
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Specification