Benford’s Law, Data Mining, And Financial
Fraud: A Case Study In New York State
Medicaid Data
Author(s)
B. Little, R. Rejesus, M. Schucking & R. Harris
Abstract
Benford’s Law was first described by an astronomer in 1881, but physicist Frank
Benford lent his name to the property in a mathematical treatise published in
1938. Behaviour of numbers described by the Law defies intuition,
demonstrating that one is the most frequent (30.1%), and nine is the least
frequent (4.6%). The property holds for a wide variety of numbers, including but
not limited to: stock indices, river lengths, road numbers, etc. Departures from
the classic Benford distribution are linked to anomalies, specifically in financial
data where the property has been successfully employed in financial audits. The
limitation of Benford’s Law is that it identifies a relatively large pool of
\“candidate” anomalies that must be manually evaluated. In the present analysis
of Medicaid data, multivariate cluster analysis in multiple tandem analyses is
used to winnow the number of anomalies to a pool of high probability anomalies
for evaluation. This approach makes the application of Benford’s Law more
practical.
Keywords: Benford’s Law, cluster analysis, ensemble multivariate technique.
Keywords
Benford’s Law, cluster analysis, ensemble multivariate technique.
Related Book
Other papers in this volume
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