
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.
