Read how data-driven insights can help organizations uncover new approaches to their key challenges and deliver new innovations faster.
Agentic AI in insurance has potential to transform insurance. Read four use cases.
Banks have reshaped their operations over the past 50 years. What used to move in cycles now shifts in real time. Risk compounds quickly. Fraud adapts. And customers don’t compare their bank to another bank anymore – they compare it to every digital experience they’ve ever had. The technology has
Asset and liability management (ALM) is still a cornerstone of banking. But when market conditions shift quickly, as they increasingly do, it no longer reflects how banks actually experience and manage risk, capital and profitability. The environment has changed. Volatility is now persistent rather than episodic. Regulatory expectations continue to
There’s a new reality. Managing, organizing and analyzing data alone is no longer enough. What really matters is how decisions are made, governed and executed. To be successful, enterprises need a unified approach that allows decisions to sit at the center, bringing people, systems and data together. While there are
Insurance is a business built on trust. Each policy represents a promise that insurers must be able to explain, defend and ultimately fulfill. When you add in AI becoming more embedded in underwriting, pricing, claims and customer engagement, that promise is being mediated by data and algorithms. An IDC report,
Advanced AI technology is transforming how governments think, work and solve problems. With new terminology and evolving tools, understanding AI can feel overwhelming. Before diving into new applications, it helps to build a strong foundation in its core concepts. This overview breaks down three of today’s most prominent AI capabilities: machine learning,
Many conversations about AI agents focus on models and frameworks. But when organizations attempt to deploy agents in real operational environments, a different challenge quickly emerges. How agents reliably and securely access enterprise data. Without reliable access to relevant data, AI agents struggle to support operational decisions. Whether diagnosing equipment
Governance, risk and compliance (GRC) has evolved beyond a control mechanism or regulatory safeguard. In today’s environment, it forms the operational backbone of effective corporate management – enabling organizations to identify risks early, meet regulatory expectations reliably, and ensure that decisions and processes remain transparent and traceable. Yet many organizations still
A nagging question remains after asking, “What’s next after zero-click search?” How do frontier models – like OpenAI’s o3 series or Google’s Gemini 3 – learn? Garbage in, garbage out Large language models (LLMs) learn from massive amounts of text data, including billions of words, public information, and, you guessed it,
For 50 years, SAS has worked alongside organizations trying to solve some of the most complex challenges in health care. Over that time, the tools have evolved dramatically. The industry has moved from paper records and mainframes to cloud platforms, AI models and genomic datasets spanning millions of data points.
