Intelligent CISO Issue 12 | Page 61

OneSpan launches AI-based risk analytics to stop financial fraud neSpan, a global leader in software for trusted identities, e-signatures and secure transactions, has announced the launch of its open API, cloud-based Risk Analytics solution to help financial institutions stop fraud, including account takeover and new account fraud. O Account takeover and new account fraud are the top two types of fraud challenging financial institutions and in the US alone, ID fraud accounted for US$16.8 billion dollars in fraud losses in 2017. Risk Analytics protects against these and other fraudulent activities across online and mobile channels using Machine Learning-based risk analysis, a form of Artificial Intelligence. This analysis identifies fraud in real time, predicts risk levels and takes immediate action when fraud is detected. threats keep evolving, it’s critical for financial institutions to take proactive measures and a layered approach to security to monitor, detect and block fraudulent transactions from happening before they occur, ensuring the best possible experience for the user.” The use of Machine Learning enables risk scoring to streamline processes, reduce operational costs tied to manual review and ultimately improve the user experience through fewer false positives. Risk Analytics is then able to take immediate action to either allow, review or block the transaction, based on intelligent workflows incorporating bank- defined security policies and rules. www.intelligentciso.com | Issue 12 OneSpan CEO, Scott Clements “Wherever money and data flows, fraud will certainly follow,” said OneSpan CEO, Scott Clements. “Real-time fraud detection using advanced, Machine Learning-based risk analytics enables financial institutions to strengthen their security, lower fraud and achieve regulatory compliance.” “While stopping fraud has become increasingly challenging because today’s OneSpan’s Risk Analytics is available now. u 61 During a financial transaction, Risk Analytics collects and analyses data from a variety of sources, including devices, user behaviour, transactions, digital channels and business applications. The solution then scores the user, device and transaction data, and determines the risk associated with that transaction. Julie Conroy, Retail Banking and Payments Research Director, Aite Group, added: “Even as criminals’ attacks on digital channels continue to escalate, financial institutions are under intense competitive pressure to reduce fraud and meet strict regulatory compliance requirements while growing their business.