The Future of Fraud: A cognitive approach

The Future of Fraud: A cognitive approach


For financial institutions and fintechs, adapting quickly is essential to combatting payment fraud, safely introducing new products and responding to sophisticated fraud attacks. Challenged with finite skilled resources, the industry shift is toward ensuring advanced analytics techniques can be integrated into fraud prevention operations to help identify patterns sooner rather than later and more rapidly set into motion the right countermeasures.

This shift to cognitive computing, which is found in IBM Safer Payments, enables fraud-prevention professionals to now have the control to quickly refine models that can defend against constantly changing payment fraud schemes. Machine learning with automated model generation enables swift model iterations, with the user immediately understanding both the lift and impact on false positives. This real-time fraud detection supports any kind of cashless payment system through any interaction channel and helps significantly improve the effectiveness of the skilled fraud and risk professional and data scientist while reducing one’s loss exposure.

Learn how to prevent fraud


Constantin von Altrock, director of counter fraud management at IBM, is recognized as a pioneering inventor, systems architect and top-level manager of developers and experts. von Altrock has extensive research experience augmented by hard-nosed implementation of large-scale systems.

Cherian Abraham, digital payments and commerce executive at Experian, is a C-level advisor with more than 17 years of international technical and business strategy consulting. Abraham advises firms in banking, retail and asset management that seek clarity and insight into myriad business models around payments, fraud and commerce. He founded Drop Labs, a mobile payments and commerce strategy and advisory practice.