Databricks Launches Lakehouse for Financial Services

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(Dennis Diatel/Shutterstock)

Databricks first launched its Lakehouse architecture in 2017, combining elements of data warehouses, data lakes, and streaming data analytics in a move that paid off, both literally and figuratively. , over the next few years as Databricks racked up billions in funding and ever-higher valuations. Today, the company is unveiling its latest Lakehouse product: Lakehouse for Financial Services, aimed at fintech users in the banking, insurance and capital markets industries.

The company says Lakehouse for Financial Services supports real-time analytics, business intelligence, and AI capabilities on “all types of data” through a multi-cloud environment. There are, according to the statement, specific solutions included for important financial use cases such as regulatory compliance and reporting, post-trade analysis, risk management, fraud detection and open banking.

Databricks also highlighted two sets of integrations: first, the integration between Lakehouse for financial services and Legend, a project to create an open ecosystem for financial data; second, the integration between Databricks’ Delta Sharing functionality and financial data providers such as Nasdaq, Factset and Intercontinental Exchange.

“For financial services institutions around the world looking to modernize and innovate, the two most important assets are no longer its capital or its size, but its data and its people,” said Junta Nakai, vice president Databricks regional. “The Databricks Lakehouse for Financial Services brings these two essential resources together in a secure, collaborative, and open-source data platform that enables ISPs to harness data across clouds and drive innovation with AI.”

As part of the release, Databricks touts partnerships with financial advisory firms like Avanade and Deloitte. (The latter’s governed data platform FinServ, for example, is a cloud-based, regulatory-compliant platform for financial institutions.) They also highlighted work with TD Bank, which uses Databricks on Microsoft Azure to enable richer analytics.

“At TD, our data and analytics capabilities are critical to innovating for our customers in new and meaningful ways,” said Jeff Martin, Senior Vice President of Enterprise Platforms at TD Bank. “By consolidating our data on the Microsoft Azure cloud platform and leveraging Databricks, we are improving and evolving the customer experience and supporting the development of new products.”

Databricks has also added a new executive to fuel this expansion into fintech, as well as “other regulated industries” like public sector labor and healthcare: Michael Hartman, the new SVP of Regulated Industries.

The Lakehouse for Financial Services announcement follows Databricks’ announcement of Lakehouse for Retail just a month ago. Lakehouse for Retail provides features such as real-time streaming data ingestion, demand forecasting, recommendation engines, and more.

Last August, Databricks closed a $1.6 billion Series H funding round, which earned it a valuation of $38 billion.

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