1. Hutch Carpenter
Description of HERC project at eFinance
Project: Revamp credit scorecards for Hertz Equipment Rental Corp.
Hertz Equipment Rental Corp. (HERC) is an industry leader in
construction equipment rental (pumps, lifts, backhoes, etc.).
In 2003, HERC engaged eFinance to improve and automate
their credit scorecards. Their business objectives were:
● Fast decisions to customers
● Establish a rigorous credit score for each customer
● Reduce writeoffs
● Reduce costs to provide credit assessments
Core need: External and internal scorecards
HERC needed scorecards for two situations. When a customer was new, they needed external
scorecards. These scorecards would be based on Dun & Bradstreet credit information. When
credit decisions were needed for existing customers (e.g. increased limits, collections handling),
internal scorecards would leverage internal transaction and payment data.
Key elements of the project
HERC provided access to a large set (hundreds of thousands) of data: customer accounts,
rental information, payment information, writeoffs. We worked with D&B to pull historical credit
file information for customers at the time their accounts were opened.
Linear regression was used. While logistic regression was better suited (i.e. measuring a binary
outcome: writeoff or not), at the time the need for expedited work required reducing the learning
curve for new tools. I knew linear regression well, and it would provide analysis comparable to
logistic. Similarly, Microsoft Access was used to run data analysis, as I did not know SQL.
Key activities during the project included:
● Determine what outcomes were to be measured
● Hypothesizing which factors would produce better predictive results
● Creating new data for use in the analysis
● Transforming data to make it more useful
● Running correlations on data from six months prior to assess predictive ability
● Analyzing regression results and iterating the models to improve them
● Adjusting data sets based on outliers and demographic characteristics
● Running models generated from one sample on a control group to assess their integrity
● Working closely with HERC executives to incorporate their insights and to ensure buyoff
on the final models
Hutch Carpenter eFinance HERC Project 1