TMBThanachart Bank invests in smarter personalization with advanced analytics on Databricks
Thai bank TMBThanachart migrated its in-house Delphi personalization engine to Azure Databricks with Unity Catalog and Lakeflow Jobs, reaching 5.5 million customers (up from 500,000), achieving a 10x increase in targeted offer capacity and 2x faster digital sales growth, while cutting insight latency from two days to under one.
Overview
Thai bank TMBThanachart migrated its in-house Delphi personalization engine to Azure Databricks with Unity Catalog and Lakeflow Jobs, reaching 5.5 million customers (up from 500,000), achieving a 10x increase in targeted offer capacity and 2x faster digital sales growth, while cutting insight latency from two days to under one.
This entry has 14 published fields tied to exact passages in an immutable source capture.
Inspect the highlighted sourceThe challenge
TTB's on-premises data infrastructure limited personalized products and services to just 500,000 customers, with batch processing causing a two-day data latency lag, shared resource constraints raising system breakdown risk, and numerous dependencies making the architecture too inflexible to quickly deploy new features.
The solution
TTB migrated their in-house Delphi personalization engine to a unified lakehouse on Azure Databricks, integrating with Google Cloud Pub/Sub and Azure Event Hub, adopting Unity Catalog for centralized data governance across teams and partners, and using Databricks Lakeflow Jobs to orchestrate and automate data pipelines, enabling real-time processing for hyperpersonalized recommendations, fraud detection and propensity scoring.
Reported business value
Personalized products and services now reach 5.5 million customers, up from the previous 500K limit, with TTB achieving a 10x increase in card generation capacity for highly targeted offers and a 2x acceleration in digital sales growth, while insight latency dropped from two days to about one day and TTB reached 100% adoption of 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 UnionDatabricks
Banking 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