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The Executive Office of the U.S. Attorneys defined “major cases” as those where: (a) the amount of fraud or loss was $ 100,000 or more, or (b) the defendant was an officer, director or owner (including shareholder), or (c) the scheme involved multiple borrowers in the same institution, or (d) involved other major factors.
The Office of Thrift Supervision was created in 1989 by the Financial Institutions Reform, Recovery and Enforcement Act (FIRREA). It assumed the regulatory responsibilities that previously rested with the Federal Home Loan Bank Board.
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In California these referrals are termed “priority referrals”, but the definition is almost identical.
The process by which cases of thrift fraud are uncovered and prosecuted often begins with the filling of a criminal referral, either by examiners from a regulatory agency or by individuals at the institution itself. The referral is then forwarded to the FBI and to the U.S. Attorney's Office for investigation. After review, the U.S. Attorney's Office may seek an indictment; if so, the case proceeds to federal court. While many cases are brought through this process, a previous study (Pontell, Calavita and Tillman,Fraud in the Savings and Loan Industry) found that a substantial number of thrift fraud indictments are initiated against persons never named in a criminal referral. This occurs when, in the course of an investigation, the FBI or the U.S. Attorney's Office discover evidence of crimes committed by individuals not named in referrals and seek an indictment based on that evidence. For example, in Texas, where a total of 1,515 individuals were cited as suspects in referrals, we discovered that approximately one-third of the 348 individuals indicted were not named in criminal referrals. In California, the proportion was even higher. There, 1,344 individuals were cited as suspects in referrals and 304 individuals were listed in the indictment file. Of the 304 individuals who were indicted, 206 (68%) did not appear in the criminal referral data base. In short, in both states many more individuals were cited as suspects in referrals than were indicted. But, of those indicted, a substantial proportion had not been cited in referrals. This means that criminal referrals by no means represent the population of al suspected S&L crimes. Rather, both the incidents described in the referrals and the events that form the basis for the indictments can be assumed to be overlapping subsets of the population of all alleged incidents of thrift-related fraud. We had no a priori reason to believe that the two subsets of suspected crimes differed in any substantive way - that the suspected crimes that form the basis for indictments against individuals not cited in referrals differed significantly from the suspected crimes described in the referrals. Yet, the nature of the data pointed to a potential problem of sample selection bias. To test for the influence of sample selection bias on our analysis, we followed the procedures outlined by Richard Berk [“An Introduction to Sample Selection Bias in Sociological Data,”American Sociological Review 1983 (48),386–398]. First, a subset of indicted individuals from the indictment files for whom complete information was available (N = 370) was selected. A dichotomous variable was created in each file indicating whether the individual had been cited in a criminal referral. This variable was then regressed on the major independent variables used in the main analysis producing a correction or “hazard” term, a quantity indicating the likelihood that the individual would have been cited in a referral and thus the likelihood that he or she would have appeared in the sample. This variable was then entered as a regressor into the equations that form the main analysis. These “corrected” models revealed no substantive differences from the “uncorrected” models. With one exception, none of the coefficients gained or lost significance. Thus, we decided that sample selection processes had not seriously biased our sample. For this reason, here we report the results from the uncorrected models.
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