Method and system for modeling future action impact in credit scoring
First Claim
1. A method for implementation by one or more data processors comprising:
- generating, by at least one data processor, a predictive model from a sample population based on;
a predictive snapshot gathered at a past sample scoring date, the predictive snapshot comprising a credit score;
a performance snapshot gathered at a sample performance date subsequent to the scoring date, the performance snapshot representing one of a good performance and a bad performance; and
intermediate information gathered at a sample intermediate date between said scoring date and said performance date, the intermediate information representing an action of an individual out of the sample population at the sample intermediate date, the performance being in response to the action of the individual out of the sample population, wherein a time period between the past sample scoring date and the sample intermediate date is a predetermined first time interval;
inputting, by at least one data processor, a profile of a consumer to a software implementation of said generated predictive model executing on a computing device;
determining, by at least one data processor, a current credit score on current date;
simulating, by at least one data processor using the generated predictive model, an impact on the consumer'"'"'s profile of likely future actions of the consumer, the likely future actions performed on a future intermediate date, the likely future actions causing the impact on a future performance date, the simulating comprising;
computing, by at least one data processor, a capacity index that rank-orders consumers according to the impact of the likely future actions, the capacity index representing a capacity of a consumer to take additional debt without defaulting later, the capacity being represented as a second score;
adjusting, by at least one data processor, said second score to control for covariate effects; and
outputting, by at least one data processor, said adjusted score,wherein the generated predictive model predicts a statistical interaction of the impact of the likely future actions with the likely future actions.
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Abstract
A method and system for predicting impact of future actions on subsequent performance involves developing a prediction model that predicts a statistical interaction of performance expectation with likely behavior. In one embodiment, sensitivity to new, post-scoring date credit behaviors in the analytic solution greatly improves snapshot score predictions. The modeling approach involves multiple snapshots: predictive and performance snapshots, plus an intermediate snapshot shortly after the predictive snapshot to quantify interim behavior. Predictive interaction variables are calculated on the predictive data using simulated profiles before and after an action.
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Citations
21 Claims
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1. A method for implementation by one or more data processors comprising:
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generating, by at least one data processor, a predictive model from a sample population based on; a predictive snapshot gathered at a past sample scoring date, the predictive snapshot comprising a credit score; a performance snapshot gathered at a sample performance date subsequent to the scoring date, the performance snapshot representing one of a good performance and a bad performance; and intermediate information gathered at a sample intermediate date between said scoring date and said performance date, the intermediate information representing an action of an individual out of the sample population at the sample intermediate date, the performance being in response to the action of the individual out of the sample population, wherein a time period between the past sample scoring date and the sample intermediate date is a predetermined first time interval; inputting, by at least one data processor, a profile of a consumer to a software implementation of said generated predictive model executing on a computing device; determining, by at least one data processor, a current credit score on current date; simulating, by at least one data processor using the generated predictive model, an impact on the consumer'"'"'s profile of likely future actions of the consumer, the likely future actions performed on a future intermediate date, the likely future actions causing the impact on a future performance date, the simulating comprising; computing, by at least one data processor, a capacity index that rank-orders consumers according to the impact of the likely future actions, the capacity index representing a capacity of a consumer to take additional debt without defaulting later, the capacity being represented as a second score; adjusting, by at least one data processor, said second score to control for covariate effects; and outputting, by at least one data processor, said adjusted score, wherein the generated predictive model predicts a statistical interaction of the impact of the likely future actions with the likely future actions. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. An apparatus for modeling future action impact in credit scoring comprising:
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a computing device, said computing device comprising a processing component and a storage component; and computer-readable instructions residing in said storage component which, when executed by said processing component instruct said processor to perform operations comprising; generating a predictive model from a sample population based on; a predictive snapshot gathered at a past sample scoring date, the predictive snapshot comprising a credit score; a performance snapshot gathered at a sample performance date subsequent to the scoring date, the performance snapshot representing one of a good performance and a bad performance; and intermediate information gathered at a sample intermediate date between said scoring date and said performance date, the intermediate information representing an action of an individual out of the sample population at the sample intermediate date, the performance being in response to the action of the individual out of the sample population, wherein a time period between the past sample scoring date and the sample intermediate date is a predetermined first time interval; inputting a profile of a consumer to a software implementation of said generated predictive model executing on a computing device; determining a current credit score on current date; simulating, using the generated predictive model, an impact on the consumer'"'"'s profile of likely future actions of the consumer, the likely future actions performed on a future intermediate date, the likely future actions causing the impact on a future performance date, the simulating comprising; computing a capacity index that rank-orders consumers according to the impact of the likely future actions, the capacity index representing a capacity of a consumer to take additional debt without defaulting later, the capacity being represented as a second score; adjusting said second score to control for covariate effects; and outputting said adjusted score. - View Dependent Claims (11, 12, 13, 14, 15)
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16. A non-transitory computer-readable storage medium having computer-readable instructions for simulating impact of future events on a consumer'"'"'s profile embodied therein, said computer-readable instructions comprising instructions for:
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generating a predictive model from a sample population based on; a predictive snapshot gathered at a past sample scoring date, the predictive snapshot comprising a credit score; a performance snapshot gathered at a sample performance date subsequent to the scoring date, the performance snapshot representing one of a good performance and a bad performance; and intermediate information gathered at a sample intermediate date between said scoring date and said performance date, the intermediate information representing an action of an individual out of the sample population at the sample intermediate date, the performance being in response to the action of the individual out of the sample population, wherein a time period between the past sample scoring date and the sample intermediate date is a predetermined first time interval; inputting a profile of a consumer to a software implementation of said generated predictive model executing on a computing device; determining a current credit score on current date; simulating, using the generated predictive model, an impact on the consumer'"'"'s profile of likely future actions of the consumer, the likely future actions performed on a future intermediate date, the likely future actions causing the impact on a future performance date, the simulating comprising; computing a capacity index that rank-orders consumers according to the impact of the likely future actions, the capacity index representing a capacity of a consumer to take additional debt without defaulting later, the capacity being represented as a second score; adjusting said second score to control for covariate effects; and outputting said adjusted score. - View Dependent Claims (17, 18, 19, 20, 21)
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Specification