Fraud & Risk Breakout Sessions
Learn how professionals from government agencies or leading commercial organisations are managing risk and detecting fraud. Hear about the latest available technologies can increase the effectiveness of investigation processes referring only claims that are likely to be defeated, by scoring the potential risk of every customer.
Speakers and session(s) subject to change.
Some sessions might apply to more than one track.
Click here for the complete agenda
Modeling of retail behaviour: Basel II IRB with Clementine
Jiří Lakosil
Risk Manager
CMSS
Czech Republic
Ondřej Háva
Senior Consultant
SPSS Inc.
Czech Republic
CMSS is a Czech retail bank serving over three million customers. In 2003, the bank began to implement a new risk management practice – Basel II methodology to estimate bank’s credit risk capital. To meet the most advanced IRB method of Basel II they began to implement data mining scoring models following the CRISP-DM methodology. To date, they have developed and evaluated all necessary models and negotiated with the national regulatory council to obtain permission for using IRB.
Along with meeting Basel II criteria, CMSS has also developed scoring models to enhance the credit application process. They are currently about to embark on the deployment phase of this project.
Attend this session to hear about CMSS’ journey which, thus far has saved them over 80 millions Euro, including how they have used SPSS Clementine to:
- Enhance and merge data from existing sources into consistent credit risk database
- Develop statistically- based rating models which enable them to meet regulatory (Basel II) requirements for capital calculation
- Automate on-line loan approving process based on application scorecards
Breakout Session 1: Monday, 14 May 2007
A Flood of Predictions: Using Data Mining to Manage Risk
Tony Hoar
Business Performance Manager
Ben Plastow
Data Quality Analyst
South West
Water
United Kingdom
How do you identify geographical areas most at risk of flooding? That’s a question South West Water (SWW) is answering with the use of the SPSS Clementine data mining workbench. With Clementine, SWW has built a suite of analytical models to better understand and manage risk more proactively. Following a successful implementation, SWW expects to improve the operational targeting of the maintenance teams with the end result being improved blockage detection rates, and reduced flooding incidents. This is expected to give SWW a more comprehensive and proactive approach which will result in improved industry rating and credibility. Attend this session to learn how Clementine can be used to detect risks and allow you to take timely action to prevent unwanted outcomes.
Breakout Session 4: Monday, 14 May 2007
