Databricks Accelerates Vertical Industry Push With New Financial Services Offering

Systems integrator partners, including Deloitte and Avanade, are playing a key role in Databricks’ vertical sector offensive by providing use-case solutions, implementation services and industry expertise for financial services, banking and insurance companies.

Data analytics technology developer Databricks is accelerating its push to deliver its data lakehouse platform for vertical industry applications, launching the Databricks Lakehouse for Financial Services and working with system integration partners to develop industry-specific solutions and services.

The new offering comes a little more than a month after the company launched Databricks Lakehouse for Retail, aimed at retailers and consumer goods manufacturers, with editions for the healthcare and media sectors under development.

“This is how we go to market now. This a huge focus for the company and how it is going to deliver for our customers going forward. It’s going to become increasingly vertical and sector-focused,” said Junta Nakai, global head of financial services and sustainability GTM at Databricks, in an interview with CRN.

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Databricks offers its Databricks Lakehouse Platform for a range of data, analytics and AI tasks and promotes the data lakehouse concept as an alternative to traditional data warehouse systems. The platform incorporates the Delta Lake open-source data management and storage technology developed by Databricks’ founders.

The new financial services edition of Databricks Lakehouse targets customers in banking, insurance and capital market sectors. It adds industry-specific technical content to the platform including solution accelerators – software code for financial service use cases such as fraud detection and sustainability – and connectors to data sets and third-party data providers commonly used by the industry, Nakai said.

Databricks Lakehouse for Financial Services supports real-time analytics, business intelligence and AI tasks on all data types within multi-cloud environments, according to Databricks. The company expects customers to use the platform for a range of applications including compliance and regulatory reporting, risk management, fraud detection and open banking.

“Financial services is one of our fastest growing verticals,” Nakai said, adding that Databricks has more than 600 customers in the industry.

Despite the huge investments financial services companies make in IT most are actually behind other verticals in such areas as data analytics and AI because the industry is highly regulated and operates complex IT systems that are slowed down by legacy technology, Nakai said.

“The Lakehouse for Financial Services will help them come up that curve and really leverage the power of this platform more quickly,” he said. “All this is about driving consumption and making it easier for our customers in financial services to adopt a lakehouse platform.”

The channel plays a significant role in Databricks’ vertical industry offensive, including the focus on financial services. The company announced that it is working with systems integrators, including Deloitte and Avanade, that have a presence and deep expertise in the industry.

“They have experience implementing data lakehouses in very governed environments, in a highly regulated industry,” Nakai said of Deloitte, Avanade and other systems integrators. Databricks is also launching go-to-market initiatives with the partners.

Systems integrators are also playing a role with Databricks in jointing developing the solution accelerator software that runs on the Lakehouse for Financial Services platform.

Avanade Risk Management, for example, rapidly deploys data into value-at-risk models to help financial service companies reduce regulatory and operational compliance risks. Deloitte FinServ Governed Data Platform helps financial service companies met regulatory requirements by creating a “single source of truth” of data for data analytics, AI/ML tasks, robotic process automation and natural language processing.

Other available industry data model frameworks, partner solutions and use cases available for the Databricks platform cover post-trade analysis and market surveillance, transaction enrichment, regulatory reporting, and fraud detection and prevention with predictive analytics, Databricks said.

As part of the push into the financial services arena, Databricks is also working with ISVs and data service providers such as FactSet and TickSmith, in some cases utilizing Databrick’s Delta Sharing open-source data sharing protocol, unveiled in June 2021, that’s part of the broader Delta Lake project. Nakai said the focus there is to help customers with efforts to “monetize their data assets.”

(Databricks Ventures, the company’s venture investment arm, has made an investment in TickSmith, Databricks said.)

And Databricks is working with industry consortiums such as FINOS (the FinTech Open Source Foundation) and with exchanges like NASDAQ to integrate Delta Lake with their initiatives.

Databricks recently hired Michael Hartman, previously executive vice president of North American financial services at Salesforce, as the company’s new senior vice president of regulated industries, overseeing such verticals as financial services, healthcare and the public sector.

Fast-growing Databricks has raised $3.5 billion in funding, including $1.6 billion in a funding round in August 2021 that put the San Francisco-based company’s valuation at $36.4 billion. Some anticipate an IPO from the company in 2022.

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Tips on how to authenticate a document by comparing handwriting.

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Stylistic Analysis

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In some cases, all of it taken together can’t solve a historical puzzle. For example, there are five known manuscript copies of the Gettysburg Address. Testing has proved that all are authentic Lincoln documents. But it will never prove, definitively, which of the five Lincoln actually read from at Gettysburg.

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