Insurance Claim Outlier Detection with Kernel Density Estimation
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United States of America Patent
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Issued Date -
Dec 3, 2015
app pub date -
May 29, 2014
filing date -
May 29, 2014
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Abstract
Data is received that comprises a data set characterizing a plurality of insurance claims. Thereafter, a density function of the data set is estimated using kernel density estimation. At least one claim having at least one outlier variable is then identified using the density function. Data is then provided (e.g., displayed, stored, loaded into memory, transmitted to a remote computing system, etc.) that characterizes the at least one identified claim as likely being fraudulent or erroneous. Related apparatus, systems, techniques and articles are also described.
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