Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection

Foreword

Fraud will always be with us. It is linked both to organized crime and to terrorism, and it inflicts substantial economic damage. The perpetrators of fraud play a dynamic cat and mouse game with those trying to stop them. Preventing a particular kind of fraud does not mean the fraudsters give up, but merely that they change their tactics: they are constantly on the lookout for new avenues for fraud, for new weaknesses in the system. And given that our social and financial systems are forever developing, there are always new opportunities to be exploited.

This book is a clear and comprehensive outline of the current state-of-the-art in fraud-detection and prevention methodology. It describes the data necessary to detect fraud, and then takes the reader from the basics of fraud-detection data analytics, through advanced pattern recognition methodology, to cutting-edge social network analysis and fraud ring detection.

If we cannot stop fraud altogether, an awareness of the contents of this book will at least enable readers to reduce the extent of fraud, and make it harder for criminals to take advantage of the honest. The readers' organizations, be they public or private, will be better protected if they implement the strategies described in this book. In short, this book is a valuable contribution to the well-being of society and of the people within it.

Professor David J. HandImperial College, London