Transformation into a digital bank is a journey with data-related roadblocks that only a data lakehouse could help SCB overcome.
Siam Commercial Bank (SCB) is one of the largest banks in Thailand (and was the first bank in the country), with over 17 million customers and over 3 trillion THB in assets. SCB’s mission is to become a digital bank that can provide effortless and empathetic services with the help of AI.
With a massive shift toward digital behavior among consumers, SCB has been taking steps to stay ahead of this trend for its millions of customers in Thailand.
However, the bank’s outdated technology infrastructure was too complicated to handle the massive influx of data effectively, slowing customer-centric innovation.
SCB realized it needed to modernize its data architecture to achieve its long-term goal of providing customers with seamless digital banking experiences. After migrating to the Databricks Lakehouse, SCB now has a single source of truth for its data and a holistic view into its customers, informing new strategies and solutions that improve operational efficiency and boost customer lifetime value.
Across all aspects of its business, the bank can now modernize the loan process for faster approvals, provide better recommendations to its customers and create a truly personalized digital banking experience on all channels.
Overly complex data lake holds back digital transformation
Digital banking means vast amounts of data — and over the past few years, the amount of data SCB captured has quadrupled, amounting to over 1 billion rows of data ingested daily.
The bank wanted to turn this data into value for its customers, but was encountering roadblocks with its cloud data lake. It was too complex to maintain and couldn’t handle the large scale of data needed to support ML workloads. The complexity also made it harder to onboard new data scientists, with the process taking two to three months for them to start being productive with the data. Compounding this was the fact that some teams were using different tools and platforms (SAS and Teradata), which led to disjointed processes and less collaboration.
“With digital banking, we need to capture vast amounts of data and convert that into new services and capabilities that provide the most optimal digital experience for our customers. That meant we needed something that could handle this data with speed and at scale,” said Dr. Chalee Asavathiratham, Chief Digital Banking Officer at SCB.
They found what they needed in Databricks Lakehouse: a unified platform that was simple to integrate and scale within their Azure infrastructure — a promise the other warehouses and technologies weren’t able to live up to.
Lakehouse provides flexibility to modernize banking
Once the team at SCB migrated to Databricks Lakehouse, they saw big improvements in productivity, onboarding speed and data performance. Fully committed to the lakehouse, SCB is gaining value from nearly every component of the platform:
- It relies on Delta Lake as the single source of truth for all its data.
- Unified governance is established over all its data and AI assets through the use of Unity Catalog.
- The ML team relies on MLflow to improve operational efficiencies in managing experiments, versions and deployments.
- With a complete view of its customers, analysts are able to rely on Databricks SQL to run queries and deliver visualizations to Power BI that impact decision-making.
- Finally, SCB has also adopted Databricks Workflows to more effectively manage production workflows and reduce bottlenecks.
“Databricks’ lakehouse has helped us remove the friction of using data, analytics and AI to provide value to our customers,” said Ramestr Sasirajpornchai, Principal Data Scientist at SCB.
The bank has used the lakehouse to power key innovations in banking, including a modernized loan application process. Historically, people would submit everything in paper form for manual evaluation — a process that could take weeks.
Now, SCB can offer instant loan approvals based on predictive analytics: For high-risk customers, it has a digital system in place to determine risk level and the best collection strategies for each individual; for current bank customers, it can use existing data to predict whether they qualify without the customer submitting any documents.
In addition to the improved loan process, SCB has also tapped into AI and ML to offer more personalized recommendations on investment strategies and new banking products based on customers’ behavior and how likely they are to engage and convert. Now, SCB can realize its vision of providing digital banking with a human touch by using data to personalize the experience across all channels, whether customers are on SCB’s website or mobile app or in person at the bank.
Seamless digital banking for millions of customers
With nearly 15 million digital users, Siam Commercial Bank needed to stay ahead of this incredible volume of data in order to provide the experiences its customers wanted — and it was able to achieve this thanks to Databricks Lakehouse.
In fact, after migrating to the lakehouse, SCB was able to meet its ML requirements, deploying models 62% faster than before. Data unification is also a big factor here, as the team can now onboard new data scientists in two days instead of several months. Not only that, but SCB has realized a THB30 million cost savings by being able to power an in-house engine instead of turning to an outside vendor.
All these improvements directly benefit the end user as well. Siam Commercial Bank can now provide truly frictionless banking to its customers — with the launch of a new loan product, for example, SCB saw the fastest growth in its history, with over 300,000 new customers in seven months. Plus, the company has driven a 2x increase in monthly new bookings of digital loans.
“We’re now able to realize our vision of providing our customers with data-driven, real-time products that elevate their financial well-being,” stated Dr. Asavathiratham. “Databricks Lakehouse has made it easy to apply machine learning to produce wide-scale business impact. And this is only the starting point — we have plans to expand our capabilities with the lakehouse to bring frictionless experiences to everything from business lending to corporate banking.”
