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The nature of this bias is illustrated in Table 26 which summarizes the reasons for the rejection of 1,713 personal loan applicants by a metropolitan bank. The first two rea- sons—too much borrowing and weak statement—account for about 50 percent of the total number of rejections and suggest that the vocational and financial characteristics of these prospective borrowers were unsatisfactory. Rejections of this nature might well be expected to bias the sample. On the other hand, rejections for "failure to mention existing loans with other members," a reason which presumably indi- cates dishonesty or irresponsibility, may not bias the sample appreciably; and the same may be true of the last four. | Credit Reporting Customer Payment Data Impact on Customer Payment Behavior and Furnisher Costs and Benefits March 2009 By Michael Turner Ph.D. Robin Varghese Ph.D. Patrick Walker M.A. and Katrina Dusek M.A. Research Assistance Adam Rodman INFORMATION policy institute PE RC RESULTS AND SOLUTIONS Copyright 2009 PERC Press. Chapel Hill North Carolina. USA All rights to the contents of this paper are held by the Political Economic Research Council PERC . No reproduction of this report is permitted without prior express written consent of PERC. To request hardcopies or rights of reproduction please call 1 919 338-2798 x803. Credit Reporting Customer Payment Data Impact on Customer Payment Behavior and Furnisher Costs and Benefits By Michael Turner Ph.D. Robin Varghese Ph.D. Patrick Walker M.A. and Katrina Dusek M.A. Research Assistance Adam Rodman March .
