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A guide on how Predictive Analytics is applied and widely used by organizations such as banks, insurance providers, supermarkets and governments to drive the decisions they make about their customers, demonstrating who to target with a promotional offer, who to give a credit card to and the premium someone should pay for home insurance.

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Introduction Project Planning Sample Selection Gathering and Preparing Data Understanding Relationships in Data Data Transformation (Pre-processing) Model Construction (Parameter Estimation) Validation, Model Performance and Cut-off Strategy Sample Bias and Reject Inference Implementation and Monitoring Multi-model (Fusion) Systems Further Topics Bibliography

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STEVEN FINLAY has worked in the field of predictive analytics for over fifteen years. His research interests cover all areas of predictive analytics, forecasting and data mining. He is currentlya Predictive Analytics Specialist, working for the UK Government, and is a visiting research fellow within the Lancaster University Management School, UK.

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