Saul R. Conceptual Variable Design for Scorecards...Model-Building Process 2025

Textbook in PDF format

Embark on a journey through the intricate landscape of predictive modeling, where the fusion of conceptual clarity and robust statistical techniques creates powerful tools for decision-making. This book distills years of experience into a standardized methodology that empowers professionals across industries—from banking to telecommunications—to construct scorecards that predict outcomes with precision and confidence.
In a world driven by data, the ability to transform complex information into actionable insights is paramount. This is your essential guide to mastering the art and science of model building. With practical examples, real-world case studies, and step-by-step guidance, this book is not just a resource—it's a roadmap to success in the rapidly evolving field of analytics. By focusing on reducing operational risk, you’ll be equipped to make informed decisions that safeguard your organization’s future.
Whether you’re a seasoned data scientist or just starting your journey, Conceptual Variable Design for Scorecards will provide you with the knowledge and skills to thrive in an era where data-driven decisions are the key to competitive advantage. Join the ranks of forward-thinking professionals who are redefining the future of risk management and predictive analytics. Your journey begins here.
Preface
Conceptual Representations
Conceptual Modeling
Balance Equation
Ratios
Time and Behavioral Patterns
Additional Variables
Things to Know About ABTs
Target Population
The ABT-Building Process
A Brief Introduction to the Use of SAS Enterprise MinerTM
Partitioning
Univariable Analysis
Collinearity Analysis
Weight of Evidence
Multivariable Selection Methods
Experimental Design and Hyperoptimization
The Main-Effects Model
The Scoring Process
Closing Thoughts