New statistical approach proposed to tackle internal fraud
Tests improve on methods to identify anomalous data created by fraudsters
Risk experts have put forward a new way to detect internal fraud within banks, improving on methods that highlight irregularities in data fabricated by dishonest employees.
The technique promises early detection of fraud by comparing multiple samples of data, rather than looking for suspicious patterns in a single, large dataset.
Banks lost $7.3 billion from internal fraud in 2017, data from ORX
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