IBM's acquisition of IRIS Analytics brings new machine learning-powered fraud detection to the IBM portfolio.
IBM today announced that it has acquired IRIS Analytics
, a privately held company specializing in real-time analytics
to help combat payment fraud.
Based in Koblenz, Germany, IRIS offers a real-time fraud analytics engine that uses machine learning to generate rapid anti-fraud models. It also simultaneously supports the creation and modification of ad-hoc models proven successful on various sized payment platforms, IBM said.
Financial terms of the deal to acquire IRIS Analytics were not disclosed. IRIS Analytics is IBM's first acquisition of 2016.
The IRIS technology acts as a “virtual analyst” to help identify new fraud patterns, and it applies machine learning models to help analysts detect fraud and act quickly to help reduce fraudulent events, the company said. IRIS bridges the gap between expert-driven rules and traditional predictive modeling by applying artificial intelligence and cognitive techniques to partner with human experts in suggesting best- fit analytics interactively. The company’s technology also allows for testing and deploying models with real production data, as it happens and without downtime.
"The cognitive computing approach unleashes a new paradigm in fighting fraud," said Alistair Rennie, general manager, Industry Solutions & Offering Management, IBM. "The combination of IRIS Analytics with IBM's counter fraud technology will help organizations more accurately detect fraud at scale and speed so that they are in a position to implement countermeasures quickly, with more control and transparency, while at the same time assists with dramatically lowering false positives."
Big Blue said only 16 percent of banks polled in a recent global IBM Institute of Business Value
study said they could detect fraud as it is attempted. The study also showed that once new schemes were identified and confirmed, it is estimated that countermeasures typically require longer than four weeks to deploy. Existing fraud detection techniques are constrained by the dependency on specialized “black box” models that are hard to understand, explain, and adapt, IBM said. Moreover, as the payments industry continues to evolve with faster, alternative and mobile payments innovations and the expanding use of chip and PIN systems, fraudsters have become more technologically sophisticated and organized, adapting their fraud techniques more quickly to attack the new systems.
According to IBM, IRIS is in use by leading banks and payment processors throughout the world. For example, the French payment card switch: e-rsb, operated by STET
, uses IRIS for 5.5 billion annual credit and debit card transactions. "With an average response time of less than five milliseconds per transaction even during peak periods when we are processing over 750 transactions per second, IRIS enables us to detect potential fraud without adding any notable overhead to our service,” said Pierre Juhen, deputy CEO of STET.
In addition, STET has been able to respond to newly identified fraud patterns by deploying new countermeasures in a few hours without taking down the system, he said.
“Defenses against financial crime are in critical need of innovation and improvement. As the payments industry evolves with new payments methods such as chip and PIN, mobile payments and immediate payments, the ability for financial institutions to accurately make decisions about what is suspicious and what is legitimate before the payment is executed is required,” said Constantin von Altrock, CEO of IRIS Analytics, in a statement. “The combination of IRIS technology with IBM’s counter fraud capabilities creates a comprehensive solution for real time payment fraud prevention."