What factors drive personal loan fraud? Evidence from Germany

Based on a data set of nearly 43,000 personal loan applications from Germany, this paper empirically determines key factors of application fraud such as, for instance, the sales channel or the loan amount. This is done univariately as well as by employing a logistic regression, which is found to be a statistically significant approach for profiling loan application fraudsters. Besides in-sample and out-of-sample verifications, we also prove the economic significance of our results by developing a fraud management framework taking the fraud rate, the average default cost due to fraud as well as the fraud screening costs into account.     

Der Fragebogen Karls des Grossen

A document compiled by Charlemagne in the year 811 can be viewed as a precursor to the structured survey and thus as a part of the very beginnings of empirical social research. Charlemagne intended to use the list, which resembles a discussion guide employed in an intensive interview, to exert moral pressure on the secular and clerical leaders of his realm, who were gathered for a parliamentary assembly. At the same time, however, it is also evident that at least some of the questions were designed to gather information on the mood of the population throughout the empire. These questions were probably passed on to the sovereigns and clerics in the provinces. Another document from the year 811 would seem to indicate that answers to similar lists of questions did in fact arrive at the emperor’s court. Both documents attest to a means of gathering information that could be viewed as the first attempt to conduct at an opinion survey.     

A sociometric status index without subgroup membership bias

Sociometric status is a widely used indicator to assess what is called popularity of a person within a group. The purpose of this paper is to show that status as defined by known indices may be biased whenever there are subgroups unequal in size within the total group and within-group choices are more probable than between-group choices. The problem of subgroup membership bias may be solved, however, by a simple linear transformation.     

Goodness-of-Fit Tests for the Gamma Distribution Based on the Empirical Laplace Transform

We propose a class of goodness-of-fit tests for the gamma distribution that utilizes the empirical Laplace transform. The consistency of the tests as well as their asymptotic distribution under the null hypothesis are investigated. As the decay of the weight function tends to infinity, the test statistics approach limit values related to the first non zero component of Neyman's smooth test for the gamma law. The new tests are compared with other omnibus tests for the gamma distribution.     

Redundant observations at testing i.i.d. random variables

n = 2 and 3. Here we characterize all testing problems with i.i.d. random variables where an additional observation fails to improve the power. Received: August 31, 2000; revised version: January 10, 2001