Transformation at DBS Bank

DBS is nominated in the Transformative Innovator of the Year category at the Qorus-Infosys Finacle Banking Innovation Awards 2025. We asked the bank to present its strategy and actions in terms of transformation.


What transformation strategy has your organization led in recent years?

DBS’ award-winning Digital Transformation Journey is underpinned by the Data & AI Industrialisation Programme - a centrifugal force that drives a strong data-driven strategy within the bank – one that is focused on maximising value from data and analytics. 

Its success has enabled innovation at scale with data and AI, across BU/SUs, by creating and providing centralised frameworks, capabilities, tools etc. to units across the bank. A highly successful, it is currently in its 4th phase of delivery:  

Phase 1: Foundation – Standardised practices and templates, Data Science Workbench in place. 

Phase 2: Democratisation – Building enterprise capability with DBS AI Protocol and growing the reusable products and assets repository. 

Phase 3: Industrialisation – Scaling use of AI through self-service infrastructure and use of AI products and assets. 

Phase 4: Unlocking GenAI at scale –Tapping the potential of unstructured data, coupled with structured data, to enable a new class of data-driven use cases.


What prompted this strategic transformation?

Prior to the launch of AI industrialisation, analytics capabilities were only available in small pockets with no centralised thrust on industrialising data and analytics practices for cross learning and collaboration. The programme therefore focuses on three areas: 

- Increase scale and make it pervasive across all parts of the bank 

- Continue to reduce the effort and cost it takes to develop and deploy AI solutions in the background  

- Deliver exponential economic outcomes with these solutions  

As we compete in an AI driven world, the programme builds enterprise data and AI capability, to drive adoption and application of traditional and GenAI use cases across the bank– enabling business models to be built with AI at the center, with the outputs informing processes across the bank.

What have been the most significant changes implemented, and how were they led?

Driven centrally by the DBS Transformation Group, AI Industrialisation is a key management focus that implements shifts across technology, organization, and culture -   

Process:  

- ALAN provides a granular, standardised repeatable approach to deliver business use cases and outcomes in a consistent and sustainable manner.  

- Reusable Assets speed up and simplify required workflows and enforce good software engineering practices through standardisation of code base and data assets.  

- Proprietary PURE framework ensures all our use cases are ethical, lawful, regulatory compliant, aligned with the Bank’s core values and are appropriately owned, approved, and managed against AI model risks.  

Technology:  

- ADA is DBS’ central data platform provides data ingestion, security, storage, governance, visualisation and analytics model management capabilities within DBS.  

People:  

- Data Chapter brings together over 700 deep experts that deliver business outcomes by scaling value for data and AI


What unique or key transformation practices do you follow to ensure success?

DBS’ “agile at scale” approach called "Managing through Journeys" (MtJs) has enabled the bank to unveil real value from Data & AI across the bank.  

- MtJ enable a horizontal organisation construct with cross-functional/inter-disciplinary teams  

- Horizontal squads under MtJs include Data Chapter members and spur the ideation and conceptualisation of GenAI use cases.  

- All MtJs embed AI/ML into our value map drivers, to help optimize decision-making and drive outcomes.  

- Control Towers provide real-time data on business drivers and customer indicators, enabling timely interventions and guide our AI development priorities.  

- This approach allows us to quickly identify high-potential use cases and scale them effectively. 

Today we have over 55 MtJs operating across our three main businesses: Consumer and Private Banking, Institutional Banking and Global Financial Markets. Accounting for over 60% of business revenues and translating into improved customer satisfaction, faster turnaround times and positive revenue impact.

How has your workforce been engaged and transformed through this journey?

Early in our digital transformation, DBS set up a comprehensive programme to equip all employees with the capability to apply data and AI in their daily work and decision-making. 

[Bankwide programmes that drive data literacy amongst employees] 

- Data heroes programme, Data Management modules (Over 126,000 modules completed through our DBS DigiFY platform), PURE training to all new joinees  

[Bespoke Curriculum]  

- Data Chapter Training Curriculum & Analytics Leads Development Programme 

With GenAI, we are providing bankwide access to GenAI Training Curriculum on Fundamental knowledge, GenAI deep-dive (Prompt engineering, DBS-GPT 101) 

- In addition to bespoke customised role based training: For CSOs, Ops servicing & processing, Developers, Relationship Managers etc.  

- Risk awareness & management: Responsible Data Use, AI/ML governance  

In addition, over 90% of our staff has access to DBS-GPT – our in-house version of ChatGPT – which provides them a hands-on experience in a secure environment.

What measurable outcomes demonstrate the success of your transformation?

With AI Industrialisation we have been able to drive data and AI use cases across business units (Consumer Banking Group, Institutional Banking Group, Group Financial Markets) and support units (Legal and Compliance, Audit, Finance, HR, Ops, Risk) to deliver - 

[Growing economic impact y-o-y]

2021: S$75M  

2022: S$178M  

2023: S$370M  

2024: S$750M 

[1500+ AI/ML models, 370+ use cases]  

- Suite of cutting-edge capabilities helping compress time to value from 12-15 months in 2018, down to 2-3 months.  

- Aim to decrease further to 2-3 weeks over the next few years.  

[20 GenAI use cases are progressing from experimentation to production]  

- Successfully implemented GenAI solutions for Customer Service Officers (CSOs), Ops servicing & processing, Developers, Relationship Managers amongst others 

[90% of DBS employees have access to a GenAI tool at work] 

- DBS-GPT (an enterprise version of ChatGPT) is complimented with role-based access to enterprise knowledge