Data defines the model by dint of genetic programming, producing the best decile table.


GenIQ Articles: Solutions
Bruce Ratner, Ph.D.


    1. Social Marketing Intelligence for Sweeping Improvement in Marketing Campaigns
    2. Model Selection for Credit Card Profitable Approval
    3. Controlling Credit Risk: Building a Not-Yet Popular Forecasting Model
    4. Improve Marketing ROI: Predictive Analytics Using Real-time Data
    5. A Customer Intelligence Model: A New Approach to Gain Customer Insight
    6. Marketing Optimization: Regression-tree Approach for Outbound Campaigns
    7. Identifying Your Best Customers: Descriptive, Predictive and Look-Alike Profiling
    8. Subprime Lender Short Term Loan Models for Credit Default and Exposure
    9. Credit Risk Modeling – A Machine Learning Approach
    10. Latent Class Analysis and Modeling: A Pharmaceutical Case Study
    11. Finding Tax Cheaters Easily
    12. CRM Success with Data Mining
    13. Retail Revenue Optimization: Accounting for Profit-eating Markdowns
    14. Nonprofit Modeling: Remaining Competitive and Successful
    15. Detecting Fraudulent Insurance Claims: A Machine Learning Approach
    16. Demand Forecasting for Retail: A Genetic Approach
    17. CRM: Cross-Sell and Up-Sell to Improve Response Rates and Increase Revenue
    18. Performance Management: Improve It via Machine Learning
    19. Risk Management for the Insurance Industry: A Machine Learning Approach
    20. Credit Scoring: A New Approach to Control Risk
    21. Customer-Value Based Segmentation: An Overview
    22. Trigger Marketing: Predicting the Next Best Offer to Give Customers
    23. Marketing Mix Model: Right Offer, Right Time, and Right Channel
    24. Building a CRM Model for Identifying Profitable Leads: The Genetic Contact-Profit Model
    25. A Machine Learning Approach to Conjoint Analysis
    26. Subprime Borrower Market: Building a Subprime Lender Scoring Model for a Homogeneous Segment
    27. The Financial Services Problem-Solution: Reduce Costs, Increase Profits by Data Mining and Modeling
    28. Retail Revenue Optimization: A Model-free Approach
    29. Fraud Detection: Beyond the Rules-Based Approach
    30. Product Positioning: Predicting the Next Best Offer to Give Customers
    31. Marketing Mix Model: A Genetic Approach
    32. Optimizing Customer Loyalty
    33. Telecommunication Fraud Reduction: Analytical Approaches
    34. The Banking Industry Problem-Solution: Reduce Costs, Increase Profits by Data Mining and Modeling
    35. Fundraising Modeling: Competitive and Successful

For more information about this article, call Bruce Ratner at 516.791.3544 or 1 800 DM STAT-1; or e-mail at br@dmstat1.com.
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