Like an Oklahoman megafarmer being approached by a fracking company, most ecommerce companies don't know how much potential value they are sitting on. Data mining has been touted as the new oil rush for some 15 years now, but the methods of refining the crude, raw data are still being discovered, as are the mechanisms we can fuel with it. Many ecommerce companies are familiar with applying the data they harvest from their incoming traffic to functions like customer segmentation and targeted marketing. Of course, these are ideas that are at the top of the profit yield checklist, but part of generating an impressive profit is also mitigating losses to fraud – an increasing concern year on year. Regardless of what security provider you turn to, the layers of protection that it delivers will start with data.

As fraud, waste, and abuse (FWA) cost government agencies and private companies billions each year, artificial intelligence (AI) has transformed how organizations prevent, monitor, and respond to FWA activity, powering advanced analytics, repeatable processes, and workflow automation and orchestration tools. Indeed, AI offers a wealth of tactics for combatting fraud, such as advanced authorization for credit card transactions, deep learning to combat false positives, and behavioral analytics. However, here we explore another facet of AI's fraud-fighting potential: helping all of the pieces work in concert towards a "fused" FWA solution. Fraud targeting and tactics have grown more sophisticated--and expansive--in recent years. The rapid proliferation of apps, payment platforms, and digital assets entering the financial services ecosystem has often outpaced regulatory oversight, and many of these channels have become a magnet for illicit activity.

Machine learning plays a pivotal role in effective fraud prevention systems. In this article, learn how machine learning can significantly improve your business' ability to stop fraud attacks. With the recent surge in e-commerce usage globally, the possibility of an online fraud attack is at an all-time high. This would represent an 18% increase in fraud losses compared to the US$17.5 billion recorded in 2020. Customers want to have the assurance that they can purchase products without experiencing a false decline, and merchants want to feel that they can trust the legitimacy of new incoming transactions.

Many elements contribute to the expanding fraud problem that online companies must contend with. These include: new criminal tactics, prolific growth of Internet-able and commerce capable devices, payment platforms offering an array of payment types, and the growing scale of data breaches globally. At the forefront of this escalation is online fraud. Online fraud has realized a rapid rise as consumers have migrated towards online for their purchasing needs and, subsequently, fraudsters have followed the money. And because fraudsters don't comply to any set rules, their tactics are aimed at exploiting opportunities for the least amount of effort with the greatest gains.

Feedzai is announcing a $50 million Series C this morning led by an unnamed VC with additional capital from Sapphire Ventures. The six year old startup builds machine learning tools to help banks and merchants spot payment fraud. In today's rapidly maturing world of fintech, Feedzai is trying to thread the needle between turnkey solution and customizable platform. With 60 clients including major financial institutions like Capital One and Citi, Feedzai remains optimistic that allowing savvy customers to build on top of its service is the key to longevity. Feedzai's platform is specifically designed to help mitigate payment fraud.