AI, Cloud, and the Future of Banking: Gunjan Kumar, NatWest

In an exclusive interview, Gunjan Kumar, Global Head of Digital Platforms and India Head for Wealth CDIO of NatWest, shares deep insights into the evolving landscape of banking technology. From the rise of AI and cloud computing to the challenges of modernizing legacy infrastructure, Kumar reflects on how regulatory compliance, cybersecurity, and talent upskilling are shaping the future of financial services.

Excerpts:

DQ: You have significant experience in the private banking sector. How has the Indian banking landscape evolved in terms of technology adoption?

Gunjan Kumar: There are three key dimensions to this transformation.

The first is technology adoption. Historically, digital channels were secondary to in-branch or phone-based services. However, digital platforms have now become the primary method of engagement for most customers. This shift has been driven by banks' increasing willingness to adopt and integrate new technologies.

The second dimension is scale. Platforms such as UPI have demonstrated that large-scale digital infrastructure is not only possible but sustainable. UPI now facilitates billions of transactions, surpassing the combined volume of major card networks. The scale of experimentation and adoption in India is unmatched, enabling rapid learning and growth.

The third dimension is the evolution of customer segments, particularly in private banking. In the past, private banking was synonymous with premier services. Today, it represents a distinct segment with specific asset thresholds and offerings. This redefinition has expanded the scope of services and enabled banks to cater to a more diverse clientele.

DQ: As digital transformation accelerates, how can banks ensure compliance with regulatory frameworks while also safeguarding digital infrastructure against cyber threats?

Gunjan Kumar: Technology adoption must be approached with caution and discipline. The benefits are significant, but so are the risks. When we began adopting cloud technologies, we implemented them incrementally, guided by use-case validation and careful monitoring.

We employ mechanisms such as phased rollouts and A/B testing to introduce new technologies. This allows us to evaluate performance and customer response before scaling further.

Moreover, the banking sector operates under extensive regulation, which is both necessary and appropriate. Financial institutions are entrusted with individuals’ life savings, and any experimentation must occur within clearly defined guardrails. Regulatory oversight from central banks, such as the Reserve Bank of India, ensures that innovation is conducted responsibly, with customer safety as the highest priority.

DQ: Could you expand on the impact of country-specific regulations on technology adoption, particularly in areas such as cloud computing and data analytics?

Gunjan Kumar: Regulations are foundational to any technology decision. Institutions must first ensure that all initiatives comply with the laws and policies of the jurisdictions in which they operate.

In the case of NatWest, being a UK-headquartered bank, we adhere to data protection and privacy regulations such as the GDPR. Compliance precedes any technology implementation, and it is not negotiable.

Once regulatory alignment is established, the focus shifts to adopting and optimizing the technology within those parameters. This ensures that customer interests are protected and that the institution maintains its license to operate. Enforcement mechanisms, including financial penalties, reinforce the importance of compliance and encourage responsible innovation.

DQ: At the beginning of our conversation, you mentioned artificial intelligence. How is AI being leveraged in the banking sector, particularly for predictive risk management and fraud detection?

Gunjan Kumar: If you step back and leave AI out of the equation for a moment, you begin to understand how critical these processes are in the current banking setup. At its core, banking is about trust—either a customer deposits money expecting it to grow, or they borrow money based on our assessment of their ability to repay. In both cases, risk is a central theme.

Now, managing that risk—both from the customer’s and the bank’s perspective—is where the real challenge lies. Without AI, we’re still dealing with vast amounts of data. With over 19 million customers banking with us, the volume of available data is enormous. Historically, we’ve relied on manual models and analytics to understand what’s working and what’s not. But processing that much information manually is nearly impossible.

This is where AI, big data, and advanced analytics come in. These technologies help us look at multiple dimensions of risk—beyond what a human analyst could evaluate—and derive more accurate insights and predictions. Essentially, AI enhances risk profiling, improves accuracy, and supports smarter, faster decision-making.

DQ: How important is it to upskill banking professionals today, especially with the rise of technologies like AI and ML?

Gunjan Kumar: There’s been a fundamental shift in what it means to be a banking professional today. Growing up, a banker was someone who sat at a branch, reconciled ledgers, and evaluated a person’s eligibility for a loan. That image has changed drastically.

Take private banking as an example. It’s now heavily relationship-oriented. Clients expect their bankers to offer advice, track performance, and help with portfolio strategy. Domain knowledge remains essential, but technology has become equally critical in amplifying that expertise.

So, being the best in your domain isn’t enough anymore. The professionals making the biggest impact are those who blend strong domain knowledge with technological fluency. Continuous learning is non-negotiable.

A good example is call summarization. A banker might spend 30 minutes discussing investments with a client. Instead of manually capturing insights, AI tools can now summarize that conversation, suggest next steps, and even highlight opportunities. It frees up the banker to focus on high-value engagements. This shift isn’t limited to banking—it applies to every industry. Without technological literacy, you risk falling behind in an increasingly digital world.

DQ: There’s been tremendous progress in digital banking—net banking, UPI, and more. But many banks still rely on legacy infrastructure. How can banks modernize while ensuring business continuity?

Gunjan Kumar: That’s a very relevant question. Let’s go back in time—there was a period when banking was entirely manual. I remember going to branches with my father and seeing everything logged in physical ledgers. Then came computers, and the goal was to digitize those ledgers.

At that time, banks adopted what was then cutting-edge technology—perhaps dBase or similar systems. But since then, the technology landscape has evolved dramatically. Today, we can do things much faster, more efficiently, and with much better scalability—not just because banks are innovating, but because they now operate within a rapidly evolving tech ecosystem.

Take our recent collaboration with OpenAI, for example. We are able to tap into specialized external capabilities and bring innovation into the bank at scale. That’s a strategic advantage.

Modernization today is not optional, it’s imperative. But the key is doing it without disrupting customer experience. We don’t want to tell our customers, “We’re modernizing for six months, please go back to visiting branches.” That’s not acceptable.

Modernization has to be phased thoughtfully. Customers should be given the option to migrate gradually, ensuring minimal disruption. How you communicate and manage this transition is vital. For instance, we notify our customers in advance of new feature rollouts or changes, informing them of any potential service interruptions.

Ultimately, people welcome better banking experiences. The secret lies in bringing them along on the journey not imposing change, but co-navigating it with them.

DQ: While modernization is essential, many banks still cling to legacy systems. What challenges prevent them from making a full transition?

Gunjan Kumar: It’s not just about limitations; it’s about context. Most large banks have technology stacks that have evolved over 30 to 35 years, if not longer. These systems were fit for their purpose when built, and over time, layers of regulatory and functional updates have been added. So, what you’re looking at today is a robust yet intricate ecosystem built over decades.

Now, expecting to flip a switch and move to a modern system instantly is unrealistic. The real barriers are two-fold. First, the investment, moving from legacy to modern infrastructure is a massive financial and resource undertaking. Second, the risk if something goes wrong, it can severely disrupt services or, in extreme cases, bring the bank to a standstill. We've seen public examples of modernization failures where customers were locked out for days.

Because of this, banks are cautious. They need meticulous planning to ensure the transition doesn't break what’s already working. For some, sticking to legacy systems seems like the safer route—at least in the short term.

DQ: What role does cloud computing play in modernizing financial platforms like trading systems? How does it enhance efficiency?

Gunjan Kumar: When cloud computing first entered the scene, many of us were skeptical. We had our own data centers, managed our own servers, so why pay someone else? But over time, it became clear that cloud providers offer massive advantages in scale, agility, and security.

The economics of scale are a big win. Giants like Amazon, Google, or Microsoft have invested heavily in infrastructure. Banks can now leverage their capabilities—spinning resources up or down as needed—without the burden of managing physical hardware.

But there's a caveat: cloud works best when it's fully adopted. If you're partially modernized, with half of your processes still on-prem and the rest in the cloud, you create complexity. Network hops, data latency, and integration issues can actually lead to a worse experience than having everything in one place.

To fully benefit, banks must approach cloud not as a buzzword or checkbox but as a strategic tool. Done right, cloud computing offers elasticity, resilience, and access to cutting-edge innovations—without the operational burden.

DQ: What key technology trends do you foresee shaping banking in the next five years?

Gunjan Kumar: Several trends are emerging, but I’d start with AI and ML. We’re at a stage with these technologies that feels similar to when cloud first came out, uncertainty, experimentation, and then, rapid adoption. The difference is that AI is evolving much faster.

Today, use cases like fraud detection, predictive risk profiling, and customer personalization are already live and delivering results. Customers may not see the AI behind the scenes, but they experience better, faster, more tailored services. Similarly, we’re seeing the rise of Copilot-style tools for employees improving how we code, test, and make decisions.

The second trend is digital-first banking. We're beyond asking what percentage of customers use digital channels it's now 80–90% or more. The next frontier is hyper-personalization at scale. With AI and data capabilities, we can democratize financial advice, offering portfolio insights not just to premium clients but to every customer.

Lastly, regulatory evolution will play a crucial role. As technologies evolve, regulators like the RBI and international bodies must stay ahead. Laws like GDPR are a start, but the pace of change is intense. We need stronger public-private partnerships to ensure innovation doesn’t outpace governance.

DQ: You mentioned the democratization of financial advice. Could you elaborate on how AI enables that?

Gunjan Kumar: Traditionally, services like global advisory or bespoke investment planning were limited to high-net-worth individuals. That was largely due to resource constraints, each customer required a dedicated Relationship Manager.

Now, with AI and large-scale data processing, we can simulate advisory functions digitally and at scale. Customers can receive relevant, contextual financial insights based on their goals, behaviors, and market trends without needing a physical interaction. It’s a transformation in inclusivity. We’re getting closer to a future where every customer is treated like a premium customer, thanks to intelligent automation.

DQ: Any final thoughts on how banking professionals should adapt to this rapidly changing environment?

Gunjan Kumar: The definition of a “banker” has changed. It’s no longer just about domain expertise, it’s about combining that with technological fluency. Whether it's understanding data, applying AI tools, or collaborating with cloud platforms, today’s professionals must constantly evolve.

Continuous learning isn’t optional anymore. It’s the differentiator between staying relevant and being left behind. The future belongs to those who can marry banking fundamentals with technological agility.

DQ: You rightly emphasized the need for modernization in today’s landscape. But what are the key limitations that are still holding banks back from moving away from legacy systems?

Gunjan Kumar: It’s not so much about limitations, it’s about context. Many banking systems have evolved over the last 30 to 35 years. The original architecture was built on the best technologies available at the time, and over the years, layers were added in response to new regulations, changing customer needs, and operational requirements.

So, what you see working today is the result of decades of continuous development. Expecting this complex structure to transition overnight to a modern stack is unrealistic. Modernization requires significant investment, and perhaps more importantly, comes with the risk of failure. We've seen high-profile modernization failures where systems went down for extended periods, even bringing institutions to the brink. The fear of disruption, both operational and reputational, makes banks cautious.

What often holds organizations back is twofold: the scale of investment required, and the apprehension about what might happen if the transition is not executed flawlessly. Many institutions are therefore opting for careful planning and phased approaches, rather than wholesale change.

DQ: What role does cloud computing play in modernizing trading platforms or financial systems? How does it improve efficiency?

Gunjan Kumar: Cloud computing offers scalability, cost efficiency, agility, and security, advantages that are hard to ignore. Initially, there was skepticism. When cloud providers like Azure first came in, many wondered: Why pay someone else to do what we already do in our own data centers?

But over time, it became evident that cloud providers bring specialization at scale. Their investments in infrastructure, security, and innovation far outpace what a single organization can do. The model allows us to access best-in-class infrastructure on demand, without the burden of maintaining it.

However, there's a caveat. The cloud works best when adopted holistically. Partial adoption, with some infrastructure on-premises and some on cloud, introduces complexities. You get network hops, sequence issues in processing, and often a worse experience than having everything either on-prem or fully on cloud.

So yes, cloud has been a game-changer, but to realize its full potential, organizations must align it with complete modernization strategies, not just tick the “cloud” checkbox.

DQ: In the next five years, what are the key technology trends you foresee in the banking technology sector?

Gunjan Kumar: There are three major trends I’d highlight.

1. AI and Machine Learning (AI/ML):
AI/ML is at the stage where cloud computing was a decade ago, but it's moving at a much faster pace. What was once seen as futuristic is now driving real, tangible use cases. From fraud detection to hyper-personalization and predictive risk profiling, AI is making services more intelligent and seamless, often in ways the customer doesn’t even notice.

We’re also using AI to empower our teams, Copilot-like tools are assisting with coding, testing, and productivity. The scope here is immense, and the evolution will continue rapidly.

2. Digital as the Default Channel:
We’re beyond asking whether customers bank digitally, nearly everyone does. The next challenge is to improve digital advice and service delivery. Can we make financial advisory services accessible to all, not just the affluent few? With AI and scalable infrastructure, I believe we can democratize financial advice.

3. Regulatory Evolution:
Regulations are becoming more dynamic, and their pace of change is hard to keep up with. Whether it's GDPR or local mandates from central banks like the RBI, the regulatory landscape must now anticipate technology shifts, not just react to them. That’s where stronger public-private collaboration becomes vital.

DQ: Is there anything else you’d like to add, something important we may not have covered?

Gunjan Kumar: Yes, cybersecurity. It's the single biggest threat and priority in banking. As we shift towards non-physical channels- PINs, biometrics, passwords- we expose ourselves to higher risks of fraud and impersonation.

There are three stakeholders in this space:

1. The individual: Customer awareness is key. As banks and governments, we must take responsibility for educating people on how to protect themselves online.

2. The government: Regulators need to enforce stress testing, enable ethical hacking, and ensure systems are resilient. They can compel banks to stay proactive.

3. Financial institutions: As banks, we must stay ahead. Technologies like AI help us serve customers better, but the same tools can be weaponized by bad actors. Impersonation using AI is a growing risk. Quantum computing, when it arrives, could render current password systems obsolete. We need to start thinking about what the next paradigm of authentication looks like.

Public-private partnership is vital here. Often, the first point of contact for fraud victims is the local police or community support. The awareness and response must begin at the grassroots level and scale up through institutional safeguards.