CW Innovation Awards: Making AI pervasive

At DBS, data and artificial intelligence (AI) has been key in driving digital transformation across the bank, generating more than S$370m of incremental economic benefits in revenue growth or expenses saved last year.

The bank’s success is underpinned by its AI Industrialisation Programme, an organisation-wide initiative aimed at driving the pervasive use of AI and machine learning (ML) across its business, reducing the effort and cost of doing so, and delivering economic results.

Besides developing centralised frameworks to guide DBS’s AI strategy and governance, including operational processes and training requirements, the programme also led to the creation of reusable AI assets to support over 350 AI use cases powered by more than 800 AI and ML models.

The use cases span various functions across DBS’s consumer and institutional banking businesses, as well as those of support teams such as finance, HR and legal.

For example, by leveraging AI and customer science, DBS’s customer experience teams have been able to identify customer pain points the moment they occur and initiate service recovery in an initiative dubbed Negative Customer Impact (NCI).

NCI also identifies “silent sufferers” – customers who may experience issues but did not contact the bank. This has allowed DBS to be more proactive in improving customer experience and rectifying customer issues before they occur.

Another notable AI use case is fraud detection. By deploying AI and ML models, DBS Bank has been able to improve its fraud detection rate by proactively detecting scams and complex transactions, apart from those surfaced through detection rules.

Transactions scored as high-risk by ML models are withheld while low-risk ones alerted by detection rules are automatically released. Coupled with human intervention, prioritised alerts have enabled DBS to focus on the most relevant information to mitigate fraud.

Building a strong data foundation has been key to DBS’s AI industrialisation programme. To that, it has developed a central data platform called Advancing DBS with AI (ADA) that provides data ingestion, security, storage, governance, visualisation and analytics model management capabilities.

Currently housing about 90% of DBS’s most frequently used data, ADA has made data more discoverable, along with security, privacy and quality-by-design capabilities to mitigate the risks of AI and deliver quality results.

To future-proof employees with data analytics and AI skills, DBS has also developed a training curriculum that caters to different knowledge and skill levels across the bank – from novices whose day-to-day roles do not require them to have much interaction with data analytics, to data experts looking to sharpen their skills.

Employees have options to learn at their own pace and select what they need to improve on from a range of online courses, workshops and community programmes. Since 2021, more than 9,000 DBS employees have taken upskilling courses in data and AI.

Implementing an AI industrialisation programme has taught DBS some invaluable lessons. These include securing buy-in from all staff, building a strong roadmap that outlines clear processes, investing in cutting-edge technology and having strong executive leadership.