Authored by CA Technologies senior vice president of Data Science, Revathi Subramanian, the book provides insight into how the use of accurate enterprise-wide data, combined with data-driven fraud detection systems, can have a transformational effect on the banking industry.
It provides tips and insights for fraud management professionals on using technologies like neural network predictive modeling, user behavior-based pattern recognition, and statistical big data analytics, all part of the emerging data science discipline, to reduce the risk of fraudulent activities in their business.
An excerpt reads, “The use of neural network-based behavior models in real time has changed the face of fraud management all over the world. It significantly reduced banks’ fraud exposure in areas where there is a need to react in a split second and stop a transaction before money goes into the hands of a fraudster. By strengthening the data enterprise, great strides can be made toward effective enterprise fraud management.”
“CA Technologies pioneered solutions for protecting eCommerce transactions in real time and has helped banks protect their cardholders and increase the volume of online shopping transactions,” said Subramanian. “I am happy to add my expertise to delivering advanced neural network authentication models that allow banks to invisibly verify the identity of customers while providing a simple, secure online shopping experience which in turn, increases customer acceptance.”
According to a review by Professional Security Magazine Online, “It would be a shame if this book were only read by people in the narrow field of banking fraud management, as the title suggests. Anyone in retail, anyone whose business handles credit cards, can learn from her approach to loss prevention. Sports betting comes to mind, too; by spotting odd and suspicious bets, that are out of the ordinary pattern, and scoring them to give some idea of the risk, you can reduce the bookmaker's exposure to risk - and, as Subramanian points out, it has to be done in a timely manner; it's no good working out that a transaction is suspicious or fraudulent after the event.”
Available today by and published by John Wiley & Sons, “Bank Fraud: Using Technology to Combat Losses” also includes:
• The challenges of fraud detection in a financial services environment
• The importance of data accurately captured, categorized, and stored when using data-driven technology to combat fraud
• The use of statistics, including effective ways to measure losses per account and ROI by product/initiative
• The Ten Commandments for tackling fraud and ways to build an effective model for fraud management
Learn more about CA Technologies neural network models in the “Payment Authentication Using Advanced Models” white paper.