The Data Intelligence Platform for Financial Services
Key takeaways
- Databricks positions its Data Intelligence Platform as an open lakehouse that unifies data and AI for financial services.
- The ebook claims measurable gains such as 4.5x higher app engagement, 83% lower costs, 90% fraud-model accuracy, and 10x faster business requests.
- Customer examples span banking, payments, capital markets, and fraud prevention, including HSBC, Discovery Bank, Coastal Community Bank, Techcombank, AME Digital, FactSet, and Deutsche Börse.
- Databricks says the platform supports security, compliance, governance, and real-time monitoring while still enabling personalization and AI development.
What is the Databricks Data Intelligence Platform for financial services?
Databricks says its Data Intelligence Platform is an open lakehouse architecture and unified data platform for financial services that handles all data types. It combines data and AI so banks, payments companies, capital markets firms, and insurers can turn raw information into actionable insights, build intelligent applications, and scale AI-driven decisions. Databricks says it was valued at $62 billion in 2024 and was recognized as a leader in the Gartner® Magic Quadrant™ for Data Science and Machine Learning and for Cloud Database Management Systems (DBMS).
How does Databricks say financial services firms can grow while also improving efficiency?
Databricks says financial services firms can use the same platform to identify new revenue streams, enhance customer experiences, accelerate product innovation, reduce costs, and automate processes. The ebook links growth and efficiency across multiple use cases: Discovery Bank used data, actuarial science, behavioral economics, AI, and machine learning to create hyper-personalized experiences; FactSet used Databricks’ consumption-based model and open architecture to reduce costs by 83%; and Deutsche Börse used Databricks to centralize 400 terabytes of daily data and speed publishing on Databricks Marketplace by 4-8x.
How does Databricks help banks and payments companies grow?
Databricks says banks and payments companies can grow by using real-time analytics to deepen customer engagement, modernize products, and scale digital-first services. The ebook gives several examples:
- Coastal Community Bank reduced 48-hour risk and compliance processes to 30 minutes using near real-time data and scaled from 40,000 local customers to approximately 6 million customers through its partner ecosystem.
- HSBC, on Microsoft Azure, reduced complex analytics processing time from 6 hours to 6 seconds, consolidated 14 databases into a single Delta Lake, and improved engagement on the PayMe app by 4.5x; the app became the #1 app in Hong Kong with a 60% market share.
- Discovery Bank reduced data processing from 9 hours to less than 10 minutes, accelerated data product creation by 5x, achieved a 40% uplift in customer engagement impact, and reported more than 500% return on investment.
How does the Data Intelligence Platform help with fraud prevention and financial crime use cases?
Databricks says the Data Intelligence Platform helps financial institutions detect, model, and block fraud faster by unifying siloed data and using real-time analytics and machine learning. Techcombank, Vietnam’s largest private financial institution, serves more than 15.3 million customers across 315 branches and used Databricks to unify data and advance AI capabilities for fraud detection and risk modeling. AME Digital, operating in the second-largest fraud market in the world, achieved 90% accuracy in its fraud prevention models, reduced job execution times by 85%, and cut operational costs by 34%. The ebook also cites BAI research showing that 84% of digital banking customers have experienced first- and/or third-party fraud.
What does the ebook say about improving risk, compliance, and security with Databricks?
Databricks says the Data Intelligence Platform helps financial institutions strengthen risk management, regulatory compliance, reporting, and cybersecurity with advanced analytics and real-time monitoring. The ebook says Coastal Community Bank reduced risk and compliance processes from 48 hours to 30 minutes using near real-time data, and Databricks says it completed the Financial Security Institute’s Security and Safety Assessment to demonstrate alignment with rigorous security and regulatory standards required by financial institutions globally. The platform is also positioned as a way to modernize governance because it combines analytics and intelligent applications with multi-dimensional customer signals and AI models tuned to each business.
How does Databricks improve efficiency and lower costs for financial firms?
Databricks says its open architecture, unified analytics, and consumption-based model can reduce costs, speed processing, and improve productivity across financial operations. FactSet used Databricks’ consumption-based payment model and open architecture to reduce costs by 83%, helped by faster processing times and auto-scaling clusters during data spikes. Raiffeisen Bank International used Databricks and Fivetran to transform data architecture across 12 countries in eight months, boosted multi-channel marketing performance by 60%, and expanded data consumption from 30 to 350 users. ABN AMRO built a money-laundering risk platform in five weeks and now handles business requests 10 times faster than with its legacy system.
What does the ebook say about capital markets use cases?
Databricks says capital markets firms can use the Data Intelligence Platform to centralize market data, simplify operations, speed insights, and support better surveillance and fraud detection. Deutsche Börse used Databricks to centralize 400 terabytes of daily data and streamline more than 230 pipelines, which produced 2-4x faster insights and 4-8x faster publishing on Databricks Marketplace. The transformation reduced workflows from days to minutes and enabled secure data clean rooms. The ebook also says 64% of capital markets firms are experimenting with generative AI, have proofs of concept underway, or have generative AI on their 2024/25 roadmap, and that 93% of exchanges, trading systems, and data providers now offer cloud-based data and services.
What does the ebook say about insurance?
Databricks says the Data Intelligence Platform helps insurers improve risk assessment, claims processing, and customer engagement. The ebook frames insurance as another area of digital transformation where big data, AI, and analytics can improve decision-making and customer experience.
Which financial institutions trust Databricks?
The ebook says HSBC, Mastercard, AXA, FactSet, and S&P Global trust the Databricks Data Intelligence Platform. Databricks uses those customers to support its claim that the platform works at scale in a highly regulated sector and can support banking, payments, capital markets, and insurance use cases.
Frequently asked questions
How is Databricks supposed to help a financial services firm grow while also improving efficiency?
Databricks says the same Data Intelligence Platform can support both growth and efficiency by unifying data, enabling AI, speeding analytics, and automating work. The ebook ties that to outcomes such as better customer engagement, faster product creation, lower costs, and more responsive operations.
What does this ebook say about unifying data and AI on Databricks for banks, payments companies, and fintechs?
The ebook says Databricks uses an open lakehouse architecture and a unified data platform to handle all data types and connect data with AI. Databricks says that approach helps financial institutions democratize analytics, build intelligent applications, and use multi-dimensional customer signals with AI models tuned to their business.
Are there real customer examples in the ebook showing Databricks being used in financial services?
Yes. The ebook cites Coastal Community Bank, HSBC, Discovery Bank, Techcombank, AME Digital, Raiffeisen Bank International, ABN AMRO, FactSet, and Deutsche Börse, along with broader customer trust from HSBC, Mastercard, AXA, FactSet, and S&P Global.
How does the Data Intelligence Platform help with fraud prevention and financial crime use cases?
Databricks says the platform helps financial institutions unify siloed data, analyze large volumes in real time, and use machine learning to detect and block fraud faster. The ebook says AME Digital reached 90% accuracy in fraud prevention models, while Techcombank used Databricks to advance fraud detection and risk modeling.
What does the ebook say about improving risk, compliance, and security with Databricks?
Databricks says the platform strengthens risk management, regulatory compliance, reporting, and cybersecurity through advanced analytics and real-time monitoring. The ebook also says Databricks completed the Financial Security Institute's Security and Safety Assessment and that Coastal Community Bank cut risk and compliance processing from 48 hours to 30 minutes.
Can Databricks help financial institutions modernize their data operations without hurting governance and control?
Yes. The ebook says Databricks helps firms modernize data operations while improving governance, compliance, and control through a unified analytics platform. Examples include ABN AMRO building a money-laundering risk platform in five weeks and FactSet reducing total cost of ownership by 83% while improving data governance.
Why would a financial services company consider Databricks instead of keeping data and AI on separate platforms?
Databricks argues that keeping data and AI together on one platform reduces complexity and makes it easier to move from raw information to actionable insights. The ebook says that unified approach can support faster analytics, lower costs, better customer experiences, and more scalable AI development.