Data Mining for Intelligence, Fraud & Criminal Detection

Fraud and related crime can be a dry topic. But equally, money underpins the significant majority of other crimes. It follows that most criminal investigators and analysts ought to have a sound knowledge and understanding of how fraud and related financial crimes work. The author has done an excellent job at making this topic very approachable for both those new to it and those not so new. The author includes substantial coverage of AMLCTF issues and addresses local, national and transnational criminal activity. Areas covered include warranty fraud, Medicare fraud, expense fraud, cheque kiting, bait & switch, tax fraud, identity fraud, drug trafficking finance and terrorism. Indeed, there is something in this book to interest almost every criminal investigator. That said, no book can be all things to all men, and some areas inevitably have to miss out. I would personally have liked to see some coverage of divorce fraud, as it is a growth area for lawyers, but it is still niche so perhaps in the next edition. I would also have liked a bit more variety in the illustrations that the author used. Perhaps the use of different analytical software packages to break up the monotony. I would also have liked to have seen some coverage of computer forensics, data mining and 'big data' visualization, as these are emerging fields and arguably define the future of "advanced analytics". But, again, perhaps these will receive coverage in the next edition. And there needs to be a next edition, because this is an area of crime that is continually changing. But these are very minor issues, especially when compared to the overall quality of the content of the book. I envisage this book becoming a definitive text, much like many of the well known legal texts that have gone on to have multiple editions published over many decades. This book is worth every one of its five stars.

Christopher Westphal has created a very engaging and informative book about various ways that criminals lie, cheat, and steal, and he has presented some intriguing suggestions for how to catch them. While many of his sidebars about topics like social security numbers, ICD9 codes, and vehicle identification numbers (VINs) are pulled almost word-for-word from the Web, it is convenient to have the information in one easy-to-read source, and the links are cited if you want to dig more deeply into a topic. I highly recommend the book for anyone interested in learning about fraud detection. However, I only give the book four stars out of five because despite the subtitle, there are absolutely no advanced analytics in the book. In fact, there are no analytics in the book beyond querying a database. There is a common refrain that goes, "Data mining is NOT querying and reporting." Thus, I would even question the use of the term "data mining" in the title. Data mining does include visualization of data, and this is where the book excels. The visual displays of data certainly enhance the learning experience. However, the visuals usually just represent summary statistics extracted from a relational database. If you look for evidence of "advanced analytics" in the index, you will struggle. None of the following common advanced analytic techniques are mentioned in the index, and I could find no mention of them in the text as well: decision trees (recursive partitioning), neural networks, generalized additive models, case-based reasoning, regression models, MARS, LARS, support vector machines. Some data mining references will pick one technology, like decision trees, and focus on that one technique. I could not identify a single advanced analytic technique anywhere in the book, and certainly not in the index. Even the generic terms "supervised learning" and "unsupervised learning" are nowhere to be found. I looked at the index online at Amazon before I bought the book, so I am not surprised nor disappointed with what I received. In fact, I had relatively low expectations for the book, but found Westphal more than delivered in describing details of warranty fraud, money laundering, gift card fraud, and many other fraud topics. I am an expert on insurance fraud detection, and I found Westphal to be well informed in that area. Furthermore, I found the book to be ENTERTAINING, a rarity in a book with "data mining" in the title. I have found many analytic experts who struggle in applying analytics because they do not understand the business problem. I would recommend the book for anyone with analytical skills who is new to any of the areas that Westphal addresses. In summary, if the book had a more accurate title, I would probably give it five stars.

This book is a must-have for anyone in the business of preventing, detecting, and investigating financial crimes. Mr. Westphal is a pioneer in the data mining/fraud analytics industry and I HIGHLY recommend this book. He clearly illustrates the value of this technology, and uses excellent illustrations so that even an industry newcomer can relate.

I have no opinion on this.

Can not find read aloud on iPad kindle. On menu just show pages. Please do suggest for this requirement. Regards

The book reviews variuos complete examples about how to prepare real "data mining for intelligence" in your specific case. Very interesting book for this area. Marty Mallavibarrena (Senior ITC Expert, Spain/Europe)