We're embedding AI across customer journeys and core systems: DBS Bank India’s CTO

Indian banking’s digital transformation has moved into a more pragmatic phase—one where artificial intelligence is shifting from pilots to production, core systems are being modernised without disruption, and resilience matters as much as speed. At DBS Bank India, technology investments over the past two years have been guided by a clear philosophy: apply advanced technologies in ways that are responsible, explainable and deeply human-centric. In this interview with TechCircle, Ramesh Mallya, Chief Technology Officer, DBS Bank India, explains how AI, cloud-native platforms and incremental core modernisation are delivering measurable impact across customer experience, risk management and internal productivity—while keeping trust at the centre.

Which technology bets made by DBS India over the last 18–24 months have delivered the clearest impact?

Over the past eighteen to twenty-four months, DBS Bank India’s technology investments have been anchored in outcomes, with a strong focus on applying advanced technology in ways that are practical, scalable and human-centred. This reflects our ambition to be a Gen AI-enabled bank with a heart.
Artificial intelligence has delivered the most visible impact. On the customer side, AI enables more contextual engagement by analysing behavioural and transactional signals to deliver timely, relevant nudges and recommendations. The intent is to strengthen everyday interactions rather than create novelty. Conversational AI has improved service responsiveness, allowing customers to resolve routine queries around the clock, while ensuring human support remains central for complex needs.

Operationally, AI has strengthened decision-making across risk and credit. Advanced application scorecards and transaction-based profiling models support earlier identification of potential stress, enabling more proactive engagement. These models operate with low autonomy and clear human oversight, ensuring AI augments judgment rather than replaces it. This aligns with our Responsible AI principles and the PURE framework, where AI is purposeful, understandable, respectful of data and explainable.
Gen AI co-pilots have also streamlined workflows such as fixed deposit processing and document handling, significantly reducing manual effort while retaining maker–checker controls. Alongside AI, virtualisation has played a critical but largely invisible role by enabling scalability, resilience and faster deployment—ultimately translating into more reliable services.

Indian banking still runs on complex legacy systems. How has DBS balanced modernisation with uninterrupted service?

Continuity of service is fundamental to trust, and core modernisation at DBS Bank India is undertaken incrementally. Legacy systems are progressively decomposed into smaller services that can be modernised independently. This allows new capabilities to be introduced in a controlled manner, tested rigorously and deployed without disrupting critical customer journeys.
Strong DevOps practices support this approach, with automation across testing, deployment and monitoring. Changes are introduced gradually and observed closely. Continuous monitoring, including predictive and anomaly-detection capabilities, helps identify potential issues early and address them before customers are impacted. This reflects a philosophy of responsible innovation—balancing speed with resilience.

AI is moving from pilots to production across banks. Where is DBS India seeing real gains?

DBS Bank India focuses on use cases where value and responsibility coexist. AI is embedded across customer journeys, operations and decision support, delivering gains in experience, consistency and speed. Customer engagement has benefited from AI-enabled personalisation and conversational interfaces that improve relevance and responsiveness. Internally, AI-driven co-pilots have streamlined processes and reduced manual effort while maintaining appropriate controls. Across deployments, the emphasis remains on alignment with the PURE framework and reinforcing trust among customers and employees.

As digital channels scale, how has DBS evolved its cybersecurity posture?

As our digital footprint has expanded, cybersecurity is embedded by design. Security considerations are integrated early into how platforms, APIs and AI systems are built and deployed.
Cloud environments follow a zero-trust mindset, with continuous verification, strong access controls and layered protections. APIs are secured through robust gateways, encryption and continuous monitoring, enabling participation in connected ecosystems. AI introduces new risks, so its use is governed by responsible design and continuous oversight, while AI itself is also used defensively to detect anomalies and emerging threats earlier.

How critical are cloud-native and data platforms to speed and personalisation?

Cloud-native and data platforms form the foundation of DBS Bank India’s ability to innovate with speed and care. Cloud-native architecture enables faster development and deployment while maintaining resilience as usage scales. Data platforms bring together information across channels to create a holistic understanding of customers, supporting contextual rather than generic personalisation. The use of data and AI is guided by a clear intent to remain helpful, respectful and transparent.

How has DBS driven digital adoption within large Indian teams?

Technology transformation at DBS Bank India is treated as a people journey as much as a technical one. Adoption has been driven by building understanding and confidence rather than mandating change. Leaders play an active role in setting direction and modelling responsible technology use. Continuous learning initiatives build digital and AI literacy across roles, while agile ways of working are supported through cross-functional teams, clear ownership and a culture that values learning and iteration.

Looking ahead, what are the key technology priorities for DBS India?

Looking ahead, DBS Bank India will continue to balance innovation with responsibility. Deepening the use of AI and Gen AI to deliver more proactive, insight-led experiences remains a priority, guided by Responsible AI principles. Strengthening cloud-native architecture and the data fabric will support scalability and faster experimentation, alongside sustained investment in building a future-ready workforce.