Dataiku & Snowflake

The Financial Services Data Cloud brings together Snowflake’s platform capabilities - across Data Engineering, Data Lake, Data Warehouse, Data Science, Data Applications, and Data Sharing - with relevant third-party marketplace data, industry solutions, core applications, and partners in order to address workflow challenges and achieve business objectives for the Financial Services industry.

Dataiku is the platform for Everyday AI, enabling data experts and domain experts to work together to build AI into their daily operations. Together, they design, develop and deploy new AI capabilities, at all scales and in all industries. Organizations that use Dataiku enable their people to be extraordinary, creating the AI that will power their company into the future.

More than 500 companies worldwide use Dataiku, including leaders across industries including life sciences, logistics, retail, manufacturing, energy, financial services, software, and technology. With a strong focus on the Global 2000, Dataiku also supports non-profits and academic institutions through its AI-for-Good initiatives.

Snowflake enables every organization to mobilize their data with Snowflake’s Data Cloud. Customers use the Data Cloud to unite siloed data, discover and securely share data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single data experience that spans multiple clouds and geographies. Thousands of customers across many industries, including 510 of the 2022 Forbes Global 2000 (G2K) as of July 31, 2022, use Snowflake Data Cloud to power their businesses. Learn more at snowflake.com.

Company Insights

Insurers can enhance customer experience and competitive edge with generative AI

AI is no longer a technology of the future, but an established tool assisting workflows across multiple industries including insurance, and helping businesses to bolster their competitive edge.

How can insurers achieve data democratisation at scale while delivering business value?

Achieving data democratisation at scale requires an intricate balance of trust, collaboration and accountability, with the right guardrails set in place. How can insurers build a culture of collaboration while ensuring trust as they look to maximise value as a data-driven enterprise?

How AI is unlocking valuable opportunities in the insurance industry

From claims processing and forecasting to customer experience, cloud is enabling new, innovative applications of AI to empower insurers to scale at speed and prioritise value-added activities. How will AI transform the insurance sector as these capabilities develop and expand?

Insurance enterprises must harness the powers of data collaboration to achieve their commercial potential

Growth in advanced analytics is reshaping the insurance sector and compelling insurers to reimagine their business approach in a digital-first economy. To maximise commercial advantage, they need to leverage cloud data platforms combined with cross-persona AI platforms to break down silos and improve data-driven decision-making and collaboration.

White Papers

Fueling Innovation in Insurance With AI

Innovation is difficult to achieve within established financial services companies, namely insurance firms, as evidenced by excessive levels of paperwork and processes customers are required to complete to make a claim or sign up for a new policy. This white paper plants the seeds as to why a data science platform is no longer a nice-to-have, but rather a necessity to weather times of uncertainty and disruption.

Insurance Data Trends: How data and analytics continue to transform the insurance industry

Insurance companies that want to thrive in today’s aggressive global business landscape need to leverage data and analytics better than ever before. Insurance providers must know more about the marketplace than their competitors, have the ability to share and leverage information internally and externally with simplicity and ease, and integrate analytics insights into every step of the decision-making lifecycle.

AI in Insurance: Top Use Cases, Challenges, and Trends

In the past few years, the pace and scale of data science, machine learning, and ultimately AI adoption has accelerated to enhance or reinvent the processes core to the insurance business. This white paper explores some of the up-and-coming use cases, challenges that traditional insurance companies face in implementation of those use cases, and ways to address those challenges to be successful in the race to AI. It also explores trends in how successful companies are executing on AI initiatives.

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