Fair Isaac Corporation

Ethan J Dornhelm

Lu Gao

Jane Sherman

Radha Chandra

Erik Franco

Brendan Alexander Lacounte

Michael Steele

Yan Wei

Tracy Backes

Andrew Leverentz

Sharon Hatcher Tilley

Jeffrey Jue

Edward Koichi McAvoy

Joanne Gaskin

Data can be accessed from a plurality of disparate data sources from at least one database. A plurality of test models can be automatically built by a model building engine. Each test model can have predetermined predictive variables. A final set of predictive variables can be determined by a variable selector from the predetermined predictive variables in the plurality of test models by comparing the predictive power of the predictive variables across the plurality of test models. A master dataset can be generated from the disparate data sources. A master model can be built from the master dataset. The master model can combine the final set of predictive variables from the plurality of disparate data sources. The master model can characterize a quantitative estimate of the probability that an entity will display a defined behavior. Related apparatus, systems, techniques, and articles are also described.

Automatic modeling farmer

A strategic default score is determined for an entity that characterizes a likelihood of the entity voluntarily electing to default on a loan. Data characterizing credit data and valuation data of an asset owned by the entity is received. Using the received data, the strategic default score is generated which characterizes a likelihood of the entity to voluntarily elect to default on the loan when the entity is capable of paying-off the loan. Provision (e.g., display, transmission, storage, etc.) of the strategic default score is then initiated. Related apparatus, systems, techniques and articles are also described.

Strategic loan default scoring

A system and method is provided that provides tools to consumers to help consumers understand their credit scores and how to take action to improve their credit scores. A system and method for each of and for a combination of a score estimating tool, a best action simulation tool, an easy error correction tool, and a score improvement tool are provided.

System and method for helping consumers understand and interpret credit scores

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San Rafael, CA, United States of America

Ethan J Dornhelm