Methods and systems for anomaly detection in small datasets

Data processing: financial – business practice – management – or co – Automated electrical financial or business practice or... – Finance

Reexamination Certificate

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C705S037000

Reexamination Certificate

active

07729964

ABSTRACT:
A technique for detecting anomalous values in a small set of financial metrics makes use of context data that is determined based upon the characteristics of the target company being evaluated. Context data is selected to represent the historical values of the financial metric for the target company or the simultaneous performance of peer companies. Using the context data, an anomaly score for the financial metric is calculated representing the degree to which the value of the financial metric is an outlier among the context data. This can be done using an exceptional statistical technique. The anomaly score can be used to evaluate the risks associated with business transactions related to the target company.

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