In February, Snowflake forged a partnership with BlackRock’s Aladdin unit to launch the Aladdin Data Cloud. That partnership paved the way for a broader Financial Services Data Cloud launch. The general idea is that financial services firms can combine their data with third party data on Snowflake’s platform to test and adjust models, market to clients and manage risk. At a high level, Snowflake’s Financial Services Data Cloud combines the company’s governance tools, industry-specific datasets and clients’ first party data. The win for customers such as Western Union is that they can consolidate data warehouse infrastructure, deploy digital business models and leverage technologies such as machine learning better. “We have SageMaker that’s currently being used for our machine learning models,” said Mazzaferro. “We use Snowflake to train the models with our actual historical data sets and then we actually deploy those models.” Mazzaferro added that Western Digital’s data team is largely decentralized but can overcome silos with one version of data within Snowflake. Overall, Snowflake said it has 57% of the financial services companies in the Fortune 500 as customers. “We’ve seen 100% year over year revenue growth within the financial services industry. The turning point of adoption was demand for personalized experiences and digitization.” Snowflake’s Financial Services Data Cloud includes: Ultimately, Snowflake’s Financial Services Data Cloud can win more customers as long as it can aggregate data in one place for various use cases. Typically, financial services pay for data feeds that reside in different applications and data warehouses. And with multiple industry partners, Snowflake can fast track data consolidation. Going forward, you can expect Snowflake to take its learnings from financial services and apply it to other industries.
