Agentic AI is transforming insurance operations, from claims and underwriting to risk and service, enabling measurable efficiency, growth, and customer impact.
Beyond long-standing relationships with traditional intermediaries, successful banking organizations today need to work in an agile and secure way with partner organizations in an emerging range of new scenarios.
The opportunity to embed technology directly into products and services is evolving how financial institutions deliver value - enabling new business models and disrupting established markets.
Today at Sibos, Microsoft and Bank of America Merrill Lynch announced a collaboration on blockchain technology to fuel transformation of trade finance transacting.
Key Enablers for Successful Transformation.
As financial services business leaders come together in Geneva for Sibos 2016, Microsoft is demonstrating how digital transformation holds countless possibilities for the industry.
How do you get the business value you need out of big data?.
As the workforce evolves, the financial services industry is seeing significant generation and demographic shifts, representing an increasingly diverse workforce with very different motivations and expectations.
Big Compute delivers modelling, simulation, data gathering and analytics capabilities that are transforming the way insurers do business.
Financial institutions have the opportunity to tap into their vast historic and transactional data assets from multiple lines of business and combine them with new external sources such as social media to gain deep insight about their customers, their business, their risks, and their regulatory compliance.
Microsoft Services promotes the standardization offered by the BIAN model and collaborates with the industry to deliver innovative products that enhance the customer experience.
Explore how digital transformation is enabling financial institutions to garner actionable insight from vast data streams.
Leading insurers are harnessing the analytical and intelligence capabilities of Microsoft R Server, SQL Server 2016 and Microsoft Azure to deliver faster results from increasing volumes of data.
