Kpmg Llp

Vishnu Muralidharan

Marisa Ferrara Boston

Christopher Wicher

Raghuram Srinivas

Seth Harsh

Matthew Thomas Ardinger

Ryan John Temple

A system and method of processing source data that includes table data by converting the table data into machine encoded text data having associated therewith text coordinate data having a Y-axis component and an X-axis component, and then generating from the machine encoded text data a plurality of pixels along the Y-axis component and the X-axis component. The system then performs a clustering technique on the plurality of pixels to generate a plurality of clusters of pixels based on similar attributes, and classifying each of the plurality of clusters of pixels as a selected row of the table and as a selected column of the table, thus making available the information encoded in the table for subsequent processing.

Converting table data into component parts

The invention relates to a computer-implemented system and method for grading of a loan using chained confidence scoring. The method may comprise the steps of: scanning documents within a credit file for the loan, extracting attributes from the scanned documents and from electronic documents in the credit file, calculating a plurality of calculated attributes based on the extracted attributes, calculating a loan risk rating based on the calculated attributes and the extracted attributes, calculating an aggregated confidence value associated with the calculated loan risk rating, and enabling a user to modify the loan risk rating, the aggregated confidence value, and a number of chained confidence values. The confidence values input by the user are used as training data to train a chained confidence model and the chained confidence model is used to calculate the aggregated confidence value in connection with the automated grading of a loan.

Loan audit system and method with chained confidence scoring

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Woodbridge, NJ, United States of America

Vishnu Muralidharan