In today’s dynamic business landscape, numerous organizations are transitioning to the Snowflake Data Cloud, seeking more agile, secure and efficient solutions to manage and activate customer data. Yet, the timelines and engineering resources needed to support implementation haven’t always kept pace with the increased market demand, impeding innovation.

As an industry built on data, financial services has always been an early adopter of AI technologies. In a recent industry survey, 46% of respondents said AI has improved customer experience, 35% said it has created operational efficiencies, and 20% said it has reduced total cost of ownership. Now, generative AI (gen AI) has supercharged its importance and organizations have begun heavily investing in this technology.

With the integration of BigQuery and Document AI, you can extract insights from document data and build new large language model (LLM) applications.

Vertex AI transcription models in BigQuery let you transcribe speech files and combine them with structured data to build analytics and AI use cases.

Your company collects huge amounts of data about everything from customer transactions to supplier contracts to system performance. This valuable resource becomes even more valuable when you combine it with data about financial market and economic trends, consumer spending, regional demographics and other elements that provide broader context and insights for your business decisions.