Snowflake：2026年金融服务业数据趋势报告（英文版）（12页）.pdf

1、DATA TRENDS 2026 FINANCIAL SERVICESLeading insights on how agentic AI and data strategy are quickly evolving within the financial services industryTable of ContentsA Year of AI Accountability and Expansion .3Top 3 Data Trends for Financial Services in 2026 .4Trend 1:Dark data moves into the spotligh

2、t .5Trend 2:Governance anchors the intelligence layer .7Trend 3:Semantics bridge the business-to-AI gap .8Entering the Age of Agentic Efficiencies .10Table of Contents|2 DATA TRENDS 2026:FINANCIAL SERVICESA Year of AI Accountability and ExpansionFinancial services institutions are entering a definin

3、g phase of AI adoption one where accountability replaces experimentation.After years of isolated pilots,the mandate has shifted from“proving the tech”to delivering enterprise-scale execution.Institutions are now demanding that AI move the needle on core business metrics:stronger efficiency ratios,sh

4、arper risk management and hyper-personalized growth.AI is no longer an innovation initiative.It is becoming a core operating capability.Yet,as institutions attempt to scale,they are discovering that the barrier to success is rarely a failure of the models themselves,but rather the lack of a unified

5、data foundation beneath them.When AI operates within functional silos retail banking,asset management,risk or claims the resulting intelligence is fragmented.To break through this plateau,industry leaders must rethink what“AI-ready data”actually looks like.Success in this next phase depends on three

6、 fundamental shifts:Dark data moves into the spotlight:Moving beyond structured data to activate the institutional memory hidden in unstructured documents,video and market intelligence.Governance anchors the intelligence layer:Transforming governance from a static audit check into an active AI obser