Computer-implemented systems and methods for integrated model validation for compliance and credit risk
First Claim
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1. A computer-implemented method for validating a credit risk model, comprising:
- accessing, using one or more data processors, historical loan performance data including a plurality of records, wherein a record includes a plurality of borrower attributes and a default attribute associated with a loan, wherein the default attribute identifies whether a borrower defaulted on making payments associated with the loan, and wherein the plurality of borrower attributes includes both quantitative and qualitative components;
dividing, using the one or more data processors, each of the borrower attributes into a plurality of borrower attribute levels, wherein dividing the qualitative components includes quantizing the qualitative components into a discrete number of levels;
combining two or more borrower attribute levels;
generating, using the one or more data processors, a handle data structure including one record for each combination of borrower attribute levels, wherein the handle data structure represents a set of unified metrics including all possible combinations of covariate patterns, wherein the handle data structure is associated with a joint distribution of risk characteristics, and wherein a default probability is assigned to each record using default attributes from the historical loan performance data;
generating, using the one or more data processors, a credit risk model, wherein the credit risk model associates a risk level measurement with each record in the handle data structure; and
performing one or more validation operations on the credit risk model to determine whether the credit risk model is acceptable for use in a production environment.
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Abstract
Computer-implemented systems and methods are provided for model validation of a model for compliance and credit risk. Model input, output, and processing validation areas are contained on a computer system. A handle data structure connects the model validation areas with handles that comprise a unified metric. A handle represents combinations of covariate patterns and describes the joint distribution of risk characteristics.
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Citations
69 Claims
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1. A computer-implemented method for validating a credit risk model, comprising:
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accessing, using one or more data processors, historical loan performance data including a plurality of records, wherein a record includes a plurality of borrower attributes and a default attribute associated with a loan, wherein the default attribute identifies whether a borrower defaulted on making payments associated with the loan, and wherein the plurality of borrower attributes includes both quantitative and qualitative components; dividing, using the one or more data processors, each of the borrower attributes into a plurality of borrower attribute levels, wherein dividing the qualitative components includes quantizing the qualitative components into a discrete number of levels; combining two or more borrower attribute levels; generating, using the one or more data processors, a handle data structure including one record for each combination of borrower attribute levels, wherein the handle data structure represents a set of unified metrics including all possible combinations of covariate patterns, wherein the handle data structure is associated with a joint distribution of risk characteristics, and wherein a default probability is assigned to each record using default attributes from the historical loan performance data; generating, using the one or more data processors, a credit risk model, wherein the credit risk model associates a risk level measurement with each record in the handle data structure; and performing one or more validation operations on the credit risk model to determine whether the credit risk model is acceptable for use in a production environment. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23)
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24. A system for validating a credit risk model, comprising:
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one or more processors; one or more computer-readable storage mediums containing instructions configured to cause the one or more processors to perform operations including; accessing historical loan performance data including a plurality of records, wherein a record includes a plurality of borrower attributes and a default attribute associated with a loan, wherein the default attribute identifies whether a borrower defaulted on making payments associated with the loan, and wherein the plurality of borrower attributes includes both quantitative and qualitative components; dividing each of the borrower attributes into a plurality of borrower attribute levels, wherein dividing the qualitative components includes quantizing the qualitative components into a discrete number of levels; combining two or more borrower attribute levels; generating, using the one or more data processors, a handle data structure including one record for each combination of borrower attribute levels, wherein the handle data structure represents a set of unified metrics including all possible combinations of covariate patterns, wherein the handle data structure is associated with a joint distribution of risk characteristics, and wherein a default probability is assigned to each record using default attributes from the historical loan performance data; generating, using the one or more data processors, a credit risk model, wherein the credit risk model associates a risk level measurement with each record in the handle data structure; and performing one or more validation operations on the credit risk model to determine whether the credit risk model is acceptable for use in a production environment. - View Dependent Claims (25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46)
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47. A computer-program product for validating a credit risk model, tangibly embodied in a non-transitory machine-readable storage medium, including instructions executable to cause a data processing apparatus to:
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access historical loan performance data including a plurality of records, wherein a record includes a plurality of borrower attributes and a default attribute associated with a loan, wherein the default attribute identifies whether a borrower defaulted on making payments associated with the loan, and wherein the plurality of borrower attributes includes both quantitative and qualitative components; divide each of the borrower attributes into a plurality of borrower attribute levels, wherein dividing the qualitative components includes quantizing the qualitative components into a discrete number of levels; combine two or more borrower attribute levels; generate, using the one or more data processors, a handle data structure including one record for each combination of borrower attribute levels, wherein the handle data structure represents a set of unified metrics including all possible combinations of covariate patterns, wherein the handle data structure is associated with a joint distribution of risk characteristics, and wherein a default probability is assigned to each record using default attributes from the historical loan performance data; generate, using the one or more data processors, a credit risk model, wherein the credit risk model associates a risk level measurement with each record in the handle data structure; and perform one or more validation operations on the credit risk model to determine whether the credit risk model is acceptable for use in a production environment. - View Dependent Claims (48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69)
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Specification