Seema Rathor is a Global Banking Industry Product Marketing Manager at SAS specializing, in the financial services industry. Prior to joining SAS, she spent more than 15 years translating business objectives into marketing strategy in roles of increasing complexity at FIS, HSBC Bank, Navy Federal Credit Union, Experian and American Express.
Financial fraud is a high-stakes issue in banking, where schemes are becoming increasingly sophisticated and costly. As a result, detecting anomalies quickly and accurately is a top priority. But traditional data-driven fraud detection models face challenges such as data scarcity, privacy constraints, and model bias. This is where synthetic data
Banks face increasing vulnerabilities, including fraud, cyberattacks, regulatory pressures and rapidly evolving customer behaviors. To remain secure and resilient, financial institutions must do more than simply adopt new technologies – they must build intelligent, adaptive systems. This is where a data and AI platform becomes a critical engine – not
Integrating AI and machine learning into anti-money laundering (AML) and combating the financing of terrorism (CFT) systems has become imperative for financial institutions (FIs) to safeguard their operations, customers and reputation effectively. Sophisticated financial crimes require advanced solutions to detect and prevent fraud. Money laundering, for example, is a financial
The rise of digital banking, driven by tech-savvy consumers, has permanently transformed the financial services landscape. Both individuals and businesses now demand seamless, user-friendly experiences, to manage their finances effortlessly across multiple platforms. Generational shifts in expectations Younger generations, including Gen Z and Millennials, have distinct financial expectations compared to
