Zestfinance, Inc.

Bojan Tunguz

Jerome Louis Budzik

Sean Javad Kamkar

Douglas C Merrill

John Candido

Benjamin Anthony Solecki

Jiahuan He

Ozan Sayin

Michael Edward Ruberry

Derek Wilcox

Yachen Yan

Esfandiar Alizadeh

Melanie Eunique DeBruin

Armen Avedis Donigian

Vishwaesh Rajiv

Evan George Kriminger

Lin Song

Eran Dvir

Systems and methods for model evaluation. A model is evaluated by performing a decomposition process for a model output, relative to a baseline input data set.

Systems and methods for providing machine learning model evaluation by using decomposition

Systems and methods for model evaluation. A protected class model that satisfies an accuracy threshold is built by using: data sets for use by a modeling system being evaluated, and protected class membership information for each data set. A target for the protected class model is a protected class membership variable indicating membership in a protected class. Each predictor of the protected class model is a predictor of an evaluated model used by the modeling system. A target of the evaluated model is different from the target of the protected class model. Each predictor is a set of one or more variables of the data sets. For each predictor of the protected class model, a protected class model impact ranking value and a modeling system impact ranking value are determined.

Explainable machine learning financial credit approval model for protected classes of borrowers

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Greencastle, IN, United States of America

Bojan Tunguz