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This is the preliminary program for the 2007 Joint Statistical Meetings in Salt Lake City, Utah.

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Activity Number: 200
Type: Contributed
Date/Time: Monday, July 30, 2007 : 2:00 PM to 3:50 PM
Sponsor: Business and Economics Statistics Section
Abstract - #309388
Title: Statistical Methods for Accounts Receivable Tracking and Forecasting
Author(s): Alejandro Veen*+ and Yasuo Amemiya
Companies: IBM T.J. Watson Research Center and IBM T.J. Watson Research Center
Address: 1101 Kitchawan Road, Yorktown Heights, NY, 10598,
Keywords: Longitudinal forecasting ; conditional logistic regression ; event occurrence prediction ; online tracking system
Abstract:

A business enterprise typically utilizes an IT system to keep track customer invoices and payments. To use the same system for projecting incoming cash flows and directing bill collection efforts, sound statistical analysis procedures need to be implemented. This talk presents such a procedure; in particular, we discuss a method for predicting the occurrence, timing, and amount of bill payment. As part of an online monitoring and tracking system, the method uses a moving time-window of data available in the system and refreshes the results regularly. A case study is presented to illustrate the usefulness of the method.

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Revised September, 2007