Fraud detection is of great importance to financial institutions. This paper is concerned with the problem of finding outliers in time series financial data using Peer Group Analysis (PGA), which is an unsupervised technique for fraud detection. The objective of PGA is to characterize the expected pattern of behavior around the target sequence in terms of the behavior of similar objects, and then to detect any difference in evolution between the expected pattern and the target. The tool has been applied to the stock market data, which has been collected from Bangladesh Stock Exchange to assess its performance in stock fraud detection. We observed PGA can detect those brokers who suddenly start selling the stock in a different way to other brokers to whom they were previously similar. We also applied t-statistics to find the deviations effectively.

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SummaryWe have. id.entified a partial deletiotl of the 8hart arm of chromosome 20 in a .5-ye.0r~-o!d boy from pareu.t~ having norm~! phenotype and ka~otype, Hi~ major anomalies were mild .mer~tal retardation, eongenita! be.art di~sease., chest deformity, s~pina bifido, kyphosco!io~is, inguinal hernia, and preaurjcula.r fistula, Th# c.lin, ic0! findings were tompared with those of two patLe0t~ r~eport~d pre~viou_s!y o~ a partial deletion 20p.T~ activity of adeno.sine deamin.ase in the patJent'~ red blood r162 was within normal range, sugge~sting that the gene. locus for the enzyme, which has been pr~evioosly as_signr to ~hromosom~ 20, may not pre.sent on pl !--*pter of chromosome 20,

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