Readily Integrate Real-time Fraud Detection within IBM Z-based Payment Systems without Impacting SLAs
Detecting fraud within payment systems is one of the top challenges for IT organizations. Integrating fraud detection applications with payment systems can be complex and impact SLAs. IBM and TAS/Mantica have just simplified this effort.
IBM has partnered with TAS/Mantica to bring together the power of their Adaptive Intelligence Platform and Fraud Protection Solution with IBM Watson Machine Learning for z/OS. This impressive combination helps organizations monitor and detect payment fraud in real-time, before a transaction completes, with minimal impact to SLAs.
TAS/Mantica models can be readily deployed through the Watson Machine Learning for z/OS scoring service. The sophisticated models can help organizations drastically reduce the implementation effort of a customized fraud prevention/detection system.
Watson Machine Learning for z/OS scoring includes RESTful APIs and Java and CICS integration that benefit from the high security and performance of the IBM Z platform. Mantica Spark and customized machine learning models, ported to Watson Machine Learning for z/OS, enable scoring directly within an IBM Z application. IBM testing showed performance, measured against different CPU capacity, revealed single-digit millisecond response times and a complete exploitation of available specialized engines. The solution also maintains model quality and performance over time as new fraud patterns emerge.
Join this IBM webinar to learn how these innovative technologies help deliver valuable insight, at the point of transaction, by readily deploying fraud detection models within IBM Z transactional payment applications.
The webinar will be presented by Eberhard Hechler, Executive Architect, IBM and special guest speaker Amedeo Borin, CEO Mantica Italia.