KPMG modernizes its data estate on Azure Databricks to power AI, analytics and risk models
KPMG LLP moved off legacy on-premises Hadoop infrastructure onto Azure Databricks as the core engine for its data transformation, analytics and AI model development. Over 850 active users leverage Unity Catalog for governed data federation across 500TB+ of data, MLflow for MLOps, and Databricks Assistant for natural-language querying, supporting use cases in engagement risk evaluation, next-best service and forecasting across finance, risk and HR.
Overview
KPMG LLP moved off legacy on-premises Hadoop infrastructure onto Azure Databricks as the core engine for its data transformation, analytics and AI model development. Over 850 active users leverage Unity Catalog for governed data federation across 500TB+ of data, MLflow for MLOps, and Databricks Assistant for natural-language querying, supporting use cases in engagement risk evaluation, next-best service and forecasting across finance, risk and HR.
This entry has 14 published fields tied to exact passages in an immutable source capture.
Inspect the highlighted sourceThe challenge
KPMG's aging Hadoop infrastructure struggled to meet increasing speed-to-market requirements and kept costs prohibitive as data volumes and variety rapidly grew, while the firm needed a platform flexible and agile enough to meet increasing AI demands.
The solution
In 2021 KPMG moved its data operations from on-premises relational databases to Microsoft Azure, adopting Azure Databricks as a core pillar of its cloud data strategy, using Unity Catalog and Delta Sharing for governed data federation, Databricks SQL Serverless for BI/ETL, MLflow for MLOps, Databricks Clean Rooms for collaborative model development, and Databricks Assistant for natural-language querying.
Reported business value
Since moving to Databricks, KPMG has seen increased productivity, faster time to market and increased scale and performance, with more than 850 active users on the platform and over 500TB of data governed under Unity Catalog.
Sources
Open any source and check the claim yourself — that is the point of the register.
This record was researched and written with AI assistance, and its claims were checked against the sources above. (EU AI Act art. 50 transparency notice.)
Other financial services entries in the register.
Navy Federal Transforms Service With AI
Navy Federal Credit Union is reshaping banking for military members by unifying data and leveraging generative and agentic AI on the Databricks Data + AI Platform. By embracing AI-augmented workflows and upskilling teams, Navy Federal delivers customized services while streamlining productivity through responsible change management and data readiness.
Navy Federal Credit UnionDatabricksBanking Innovator bunq Supports Growth, Strengthens Security Using AWS
bunq, a Dutch neobank with over 11 million users across Europe, uses Amazon Bedrock for several generative AI use cases including summarizing new user data with large language models, removing the need for agents to process onboarding documents manually. Using Amazon Bedrock, bunq tripled user support process efficiency while maintaining over 90 percent accuracy. Sensitive data stays within bunq's AWS virtual private cloud, supporting GDPR and PCI DSS compliance alongside tools such as AWS CloudHSM, AWS Security Hub and AWS KMS.
bunq· NetherlandsAmazon Bedrock · AWS CloudHSM · AWS Security Hub +1TBC Bank Operationalizes Trusted Data with Lakebase
TBC Bank, the largest banking group in the Caucasus region, built a Lakehouse on Databricks and adopted Lakebase and Databricks Apps to move from on-premises SQL Server instances and month-long reporting cycles to self-service analytics and AI-driven applications, including a web-based AI chatbot and AutoML-based credit risk scoring. Credit risk model deployment fell from 14 weeks to two days, and more than 600 users regularly query governed data through Genie.
TBC Bank· GeorgiaDatabricks Platform · Lakebase · Databricks Apps +4Worldline enables real-time insights for smarter merchant decisions with Databricks
European payment processor Worldline consolidated data from multiple acquisitions onto a Databricks medallion architecture with Delta Lake and Unity Catalog to unify over 50 billion annual transactions, reducing infrastructure costs by €200,000 per month, lifting team productivity 40%, and increasing scheme reporting speed 93%.
Was this helpful?
Your feedback helps us improve our use case database