CUSTOMER STORIES
GXBank Processes Customer Cases 6x Faster with the AI Data Cloud
As Malaysia’s first digital bank, GXBank is on a mission to provide accessible financial services to all citizens, including the underserved. By leveraging the Snowflake AI Data Cloud, the bank built a lean, scalable architecture to enhance operational efficiency and power its forward-looking, data-rich risk models.
6xImprovement in average case processing time
1 minTo review cases, down from 20 minutes previously
Industry
Financial ServicesLocation
MalaysiaStory highlights
- A more modern, scalable data foundation: Snowflake's unified platform fundamentally inverted the traditional banking model by replacing an expensive legacy system with a more lean, scalable architecture, shifting GXBank from a "backward-looking and data-blind” risk model to a "forward-looking and data-rich” risk model.
- Greater cost and resource efficiency: The ability of the Snowflake platform to separate compute and storage helped GXBank overcome the challenge of volatile data volumes, which previously led to costly over-provisioning. This has helped the team implement cost optimizations from day one.
- Faster case processing, happier customers: GXBank accelerated its average case processing time sixfold, which has enhanced the customer experience and made internal workflows more efficient.
Video Transcript
GXBank serves all Malaysians, including the underserved, to get access to the financial services that they need. We disrupt with intent, and our ambition is actually to build a new way of banking for Malaysians.
So being the first digital bank, everything is the first time for us. So we need to be really innovative, especially with the rise of Gen AI. Data and AI is no longer an option. It is actually a fundamental necessity to ensure the success of any business as well as a digital bank.
So we leverage on data and AI that power by Snowflake to make our bank more accessible, secure, and trustworthy. Snowflake data and AI met all our requirements perfectly. Snowflake data was a unified platform. It can separate, compute, and service separately, which helps our data science team to focus on doing more data innovation.
The volume of data is very volatile, and it's very difficult to predict. So sometimes when we have a very successful campaign, you know, volume goes up, and the volume of data come down as fast as it went up. So typically we would have over-provisioned in terms of compute or storage costs. So a cloud solution is a great solution to help us overcome these challenges.
Snowflake data platform helps us to schedule and manage different workloads across data warehouse, data lake, as well as AI and machine learning project, which is very valuable and which helps us to run all this seamlessly in a single platform.
We achieve greater operational efficiencies by using Snowflake data. It helps to improve the average processing case time by six times, which we have reduced the review time from 15 to 20 minutes to now one to three minutes. So it fundamentally inverts the traditional banking model from expensive legacy system to a more lean and scalable architecture. It also change from backward-looking and data-blind risk to a more forward-looking and data-rich risk model.
The strategic services from Snowflake help us to do the cost optimization from day one, as well as help the team to build skillset which is required to support and operationalize the Snowflake platform. Snowflake empower our team to turn data from a foundational asset to a strategic engine. It also help us to accelerate our mission to serve the financially underserved customer with intent and integrity.
