Jpmorgan Chase Bank, N.a.

Leonidas Tsepenekas

Daniele Magazzeni

Freddy Lecue

Sanjay Kariyappa

Methods and systems for using a non-linear machine learning model to generate explanations that relate to decisions made by the model and for repairing such explanations in order to improve quality and accuracy of model outputs are provided. The method includes: receiving a data set that corresponds to attributes that pertain to a decision to be made; inputting the data set to a machine learning model; generating a baseline decision that corresponds to an output of the model with respect to data set; computing, based on the baseline decision, an explanation that relates to at least one of the attributes; estimating one or more errors associated with the explanation; and computing, based on the estimated error(s), at least one repair that corresponds to a modification of the explanation, and a cost for repairing the explanation.

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College Park, MD, United States of America

Leonidas Tsepenekas