Prevent Fraud with AI
Mike McNamara
According to a recent study, credit card fraud in the United States is expected to reach $12 billion in 2020. Rules-based expert systems currently used to catch fraud have become too easy to beat. In addition to combating fraud, financial services institutions are also challenged to make the right credit decisions, improve risk management, enable fast, insightful trading, and develop personalized services—all while elevating the customer’s experience.
The financial services sector generates a wide variety of data types. Analysis can include transaction history data from banks, smartphone data, real-time structured and unstructured data, a client’s behavior, location, and buying habits, and speech data from banking call centers. The different data types contribute to different aspects of financial services, including credit decisions, risk management, fraud prevention, trading, measures against money laundering, and personalized banking.
To address these challenges, the financial services industry is increasingly relying on artificial intelligence (AI) and machine learning (ML) technologies. With NetApp® ONTAP® AI, banks and other financial institutions can leverage the deep insights gained from AI and ML operations to improve their defenses against fraud and better serve their customers.
ONTAP AI combines NetApp cloud-connected all-flash storage with NVIDIA servers for a high-performance, easily scalable solution that is proven to handle workloads such as credit risk assessment, large trade execution, natural language processing, fraud prevention, and cybersecurity.
AI can be a powerful tool in reducing risk, eliminating fraud, and protecting customer endpoints. To be successful, you need a data management solution that can keep up. ONTAP AI gives you all the performance you need to feed, train, and operate your applications so they can quickly and accurately detect illegal or suspicious financial activity.
With data coming in from multiple, disparate sources such as smartphones, call centers, earnings call transcripts, SEC filings, and more, financial institutions must find a way to harness and extract the most value from it as quickly as possible. That requires powerful AI capabilities that reach from the edge to the core to the cloud.
NetApp ONTAP AI Reference Architecture for Financial Services Workloads offers guidelines for customers who are using ONTAP AI to build an AI infrastructure for financial sector use cases. The document focuses on addressing the challenges in the training phase.
Mike McNamara
Mike McNamara is a senior leader of product and solution marketing at NetApp with 25 years of data management and data storage marketing experience. Before joining NetApp over 10 years ago, Mike worked at Adaptec, EMC and HP. Mike was a key team leader driving the launch of the industry’s first cloud-connected AI/ML solution (NetApp), unified scale-out and hybrid cloud storage system and software (NetApp), iSCSI and SAS storage system and software (Adaptec), and Fibre Channel storage system (EMC CLARiiON). In addition to his past role as marketing chairperson for the Fibre Channel Industry Association, he is a member of the Ethernet Technology Summit Conference Advisory Board, a member of the Ethernet Alliance, a regular contributor to industry journals, and a frequent speaker at events. Mike also published a book through FriesenPress titled "Scale-Out Storage - The Next Frontier in Enterprise Data Management", and was listed as a top 50 B2B product marketer to watch by Kapos.
