Fair Isaac Corporation

Lu Gao

Ethan J Dornhelm

Radha Chandra

Brendan Alexander Lacounte

Erik Franco

Jane Sherman

Chisoo Lyons

Bogdan Eugen Popescu

Joanne Gaskin

Yan Wei

Tracy Backes

Andrew Leverentz

Eric C Wells

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 decision model is applied to a set of current data from a mortgage portfolio to generate a first portfolio metric. The decision model is formed from a network of a plurality of predictive models that are trained on historical data derived from a plurality of mortgage account profiles for a plurality of mortgages within the mortgage portfolio. One or more of the predictive models is an action-based predictive model allowing modification of at least one attribute affecting performance of the mortgage portfolio. One or more of the attributes can be modified and a second portfolio metric can then be optimized, using the decision model, in light of at least one constraint (which can be user-defined). Related techniques, apparatus, systems, and articles are described.

Optimizing portfolios of financial instruments

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American Canyon, CA, United States of America

Lu Gao