Assigning Common Law Claims for Fraud

Adaptive Fraud Detection Using Benford's Law

Adaptive Benford’s Law [1] is a digital analysis technique that specifies the probabilistic distribution of digits for many commonly occurring phenomena, even for incomplete data records. We combine this digital analysis technique with a reinforcement learning technique to create a new fraud discovery approach. When applied to records of naturally occurring phenomena, our adaptive fraud detecti...

Using Advanced Analytics to Combat P&C Claims Fraud

Executive Summary Insurance fraud is the second biggest white-collar crime in the U.S. after tax evasion, according to the National Insurance Crime Bureau. As insurers deal with an uncertain economic climate and intense competition, they must also grapple with the increasing incidence and sophistication of fraud, not to mention the resulting losses. The traditional methods of identifying fraud ...

Direct and Derivative Claims in Securities Fraud Litigation

In the typical securities fraud class action under Rule 10b-5, the plaintiff class consists of buyers who seek damages equal to the difference between the price paid for the stock during the fraud period and the lower price that prevails after corrective disclosure. The argument here is that this claim is really an amalgam of direct and derivative claims and that the derivative claims should re...

Improving Fraud and Abuse Detection in General Physician Claims: A Data Mining Study

Background We aimed to identify the indicators of healthcare fraud and abuse in general physicians’ drug prescription claims, and to identify a subset of general physicians that were more likely to have committed fraud and abuse.   Methods We applied data mining approach to a major health insurance organization dataset of private sector general physicians’ prescription claims. It involved 5 ste...

Western Philosophies of Law: the Common Law