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How Southeast Asia’s largest bank is riding the AI wave
DBS has scaled its AI capabilities across all parts of its business to deliver tangible outcomes and productivity gains
Artificial intelligence (AI) and generative AI (GenAI) are game changers, and we will see significant developments in the next five years that will fundamentally shape the way we work. The use of AI is not new to DBS, and we have been working with AI for over a decade now.
In the past five years, we have scaled our AI capabilities to make it pervasive across all parts of the bank, delivering tangible outcomes of S$370m for DBS in 2023, more than double that of the previous year. We are confident of growing the economic impact of our AI initiatives in the coming years, affording us greater flexibility to navigate through business and economic cycles.
What’s different with the emergence of GenAI is that we now have the ability to process vast amounts of unstructured data. Coupled with our existing capabilities around structured data, we are well placed to sharpen the outcomes of our current AI use cases while enabling a new class of data-driven use cases.
In our early experiments with GenAI, we came up with over 240 ideas, 15 of which are progressing from experimentation to production. These are broadly focused on three areas of opportunity:
- Driving productivity and efficiency gains by removing toil in the way we work
- Creating value through better customer engagement and new customer propositions
- Creating positive impact to our business model by potentially opening new segments and markets.
Our immediate focus has been on the first category. GenAI is already augmenting the way we work by handling routine tasks, allowing employees to focus on more strategic and value-added activities, such as building deeper customer relationships.
The results are promising. In our corporate call centre, we are using GenAI for call transcription, summarisation, service request generation and knowledge base lookup, reducing the amount of time needed to handle customer requests while improving our response quality.
In institutional banking, we tapped GenAI to help reduce the time needed for relationship managers to fill in the ESG (environmental, social, and governance) risk questionnaire by summarising company reports and prepopulating relevant fields.
GenAI-assisted software development is showing positive results. Through GenAI code and tests generation, we expect significant time savings in software development.
The launch of DBS-GPT, our employee-facing version of ChatGPT, is helping employees with content generation and writing tasks in a secure environment. We are also developing an enterprise knowledge base that will give our employees the ability to search and synthesise unstructured information for various tasks.
Read more about artificial intelligence in ASEAN
- The Sea-Lion large language model was built to cater to the language and cultural diversity of Southeast Asia, which is currently underserved by existing models that mostly originate from the West.
- Google Cloud has teamed up with the Singapore government on a slew of initiatives to drive AI adoption, build an ecosystem of AI startups and expand the pool of AI talent in the city-state.
- Malaysia’s Aerodyne is running its Dronos platform on AWS to expand its footprint globally and support a variety of drone use cases, from agriculture seeding to cellular tower maintenance.
- Healthcare professionals at Singapore’s National University Health System can now summarise patient case notes and predict patient healthcare journeys using a large language model trained by a supercomputer.
As with any new technology, the advent of GenAI brings about a natural sense of curiosity and adjustment for our employees. But change also presents exciting opportunities for growth and innovation. We are determined to bring our employees along by focusing on the synergy between human and AI capabilities to leverage GenAI as a co-pilot.
While GenAI has tremendous potential, there are emergent risks, especially in areas such as data confidentiality, GenAI hallucination, bias, toxicity and cyber security. We will continue to enhance our existing AI and machine learning risk framework to cater for such risks.
We have also set up a responsible AI taskforce comprising senior leaders from multiple disciplines to assess and address these risks prior to any use case being deployed in production. Our existing responsible data use framework for AI continues to provide us with guardrails as we look at new use cases. This framework, called Pure, ensures that our use of data remains purposeful, unsurprising, respectful and explainable for customers. In addition, we are building a technology infrastructure to enable the adoption of large language models in a secure manner.
Concurrently, in Singapore, we worked with the Monetary Authority of Singapore as part of the MindForge consortium to develop a whitepaper that examines the risks and opportunities of GenAI for the financial sector.
We are at a historic cusp in time, and we will all need to navigate how GenAI figures in the way we live and work. On DBS’s end, we have in place a governance structure that will help us balance reaping the benefits of Gen AI while managing the risks of a still-emerging field.
Piyush Gupta is CEO of DBS Bank
