| SGF |
2020 |
Pricing Life Insurance Contracts with Early Exercise Features Using Neural Networks |
Helgard Raubenheimer |
source |
9 |
| SGF |
2017 |
Shipping Container Roulette [presentation] |
Dan Tamburro |
source |
29 |
| SGF |
2016 |
Evolving Fraud Types: Can Your Application Keep Up? |
Gordon Robinson |
source |
11 |
| SGF |
2011 |
An Insurance company implementing Personal Loan marketing campaigns using SAS Marketing Automation |
Young Chun Kim |
source |
5 |
| SGF |
2010 |
An Analytical Approach to Determining Customer Value in the Property and Casualty Insurance Industry |
Roosevelt Mosley |
source |
20 |
| SUGI |
2003 |
The Horror of Bad Data Quality |
Henri Theuwissen, Nancy Croonen |
source |
7 |
| SEUGI |
2001 |
Preventing surrender by holders of life insurance policies [presentation] |
Gerhard Braas |
source |
20 |
| SUGI |
2001 |
Catch the Errors Early - On Generating Checking Routines Automatically |
Markku V. Suni |
source |
4 |
| SEUGI |
1998 |
Database marketing applications in the Italian banking sector |
Alberto Saccardi, Guido Cuzzocrea |
source |
8 |
| SEUGI |
1998 |
SAS data mining and neural networks: Powerful and efficient tools for customer-oriented pricing and target marketing in deregulated insurance markets |
Stefan Lecher |
source |
8 |
| SEUGI |
1995 |
AMIS: Developing a Data Warehouse for Actuaries |
Jan Willem van der Grijp |
source |
10 |