We're actively engaged in Digital Transformation 2.0: Ayan De of HDFC Life

Technology trends are reshaping the landscape in the insurance sector, and companies like HDFC Life are at the forefront of this revolution. In an exclusive interview with TechCircle, Ayan De, Head of Enterprise Technology, HDFC Life, shared insights about the evolving tech landscape in BFSI sector, the company's upcoming tech plans, and the ongoing Digital Transformation 2.0 at HDFC Life and more. Edited Excerpts:   

According to you what are the key tech trends shaking up insurance and what HDFC Life doing to stay ahead?  

The primary focus is on adopting cloud and hyper-scaling in the public domain. Prominent players in the banking, financial services and insurance (BFSI) sector, such as AWS, Microsoft Azure, and even Oracle, are being considered as potential partners for cloud adoption. This shift is notable among managed service providers (MSPs), reflecting a significant industry trend. Another crucial aspect is better management through predictive analytics and informed business decision-making. This was previously challenging due to the sheer volume of data that needed handling. This management improvement is a widespread development across various industries.  

The third aspect involves emerging technologies like use of gen AI, commonly referred to as ChatGPT. Enterprise-grade technologies, including some offered free of cost, are gaining traction. While currently more oriented towards internal use cases, the industry is exploring external applications, exemplified by tools like Google Bard. The fourth consideration is the integration of IoT and edge computing. With an increasing focus on real-time data processing and decision-making closer to the customer, industries, especially insurance, are leveraging IoT devices. Telemetrics in vehicles and wearables in health insurance are becoming key areas of action, subject to compliance guidelines and data privacy regulations, which will likely gain more clarity in the next 12 to 18 months.  

In summary, the current landscape revolves around cloud adoption, AI/ML, emerging technologies like ChatGPT, and the strategic implementation of IoT and edge computing to enhance real-time decision-making, all within the framework of evolving data privacy regulations.  

Are there any specific areas where your company should invest more effort in digital transformation?  

Every area has specific needs and use cases, but resources are limited, not just in terms of dollars, but also in valuable human skills, especially in cutting-edge technology. We’ve identified certain areas for the next stage of progress, particularly in more advanced underwriting. This is where we evaluate the risk of insuring a life, incorporating additional data points, especially those available in the public domain. Our goal is to use this data to build a comprehensive 360-degree human persona. Based on this understanding, we can then tailor personalised products and services for each customer, recognising the critical importance of every customer to us.  

Understanding insurance can be complex for customers, given the variety of products and the need to align them with individual circumstances. Many customers struggle to articulate their requirements clearly. Here, we aim to leverage available public domain data to speak on behalf of the customer, helping us comprehend their needs better.  

Our focus extends to data utilisation from the public domain, with attention to the recently introduced DPDP regulations. We aim to stitch together all relevant data points, creating a cohesive fabric to define customer personas and, subsequently, offer precisely tailored products.  

Another major focus is distribution. We collaborate with various distributors, from our own agents to banking partners, FinTech operators, and traditional partners. Each operates in a specific market, prompting us to develop customised AI and ML solutions for individual partners. Unlike our previous one-size-fits-all approach, our evolving digital program now tailors automation solutions for each channel based on their unique characteristics and market dynamics.  

How do you view the role of data in your future plans, especially considering the ongoing debate about data scarcity in India? Is this a concern for you, and what are your thoughts on the matter?  

So, in my view, it's not accurate to say that India lacks data. Instead, the challenge lies in the absence of an effective data filtration mechanism. Essentially, we possess a substantial data reservoir, but to utilise it effectively, we need the right filters to segment it appropriately. Despite enterprises and public sector bodies collecting data for decades, the key is finding the right lens and filter to extract relevant data for specific use cases.  

In my industry, the technology landscape has rapidly evolved over the past 15 years. As companies embraced core applications, added wearable technologies, and underwent various transformations, the data journey wasn't uniform across these technological shifts. For instance, when incorporating new layers around existing systems, data services were duplicated. Similarly, expanding services to mobile devices led to data replication, resulting in multiple copies that were challenging to unify.  

In our digital transformation journey spanning the last eight years, we, like others, adopted diverse application stacks. However, the post-Covid realisation emphasized the need for a single source of truth or the industry's “golden copy”. To achieve this, we established enterprise data warehouses and multiple data lakes. Now, our focus is on consolidating these resources, undergoing a comprehensive technology transformation, with data at the core.  

In this new journey, the entire ecosystem is viewed through the lens of big data, ensuring that all data is centralised. This approach simplifies data consumption and collection, turning a perceived problem into an opportunity for a more efficient and streamlined data management process.  

How do you benchmark your tech journey against competitors or industry peers?  

Looking at our scale alone gives you a whole new perspective. Currently, about 70-75% of our workflow operates on various public cloud forms, and we're aiming to increase that to around 88% in the next few years. Achieving this scale is possible due to our ongoing digital transformation efforts. It's not surprising that HDFC Life is seen as the benchmark in the industry.  

Our commitment to innovation and the integration of AI/ML into our daily operations, along with a shift to cloud as our primary infrastructure, reflects the significant progress we've made. I take great pride in the work accomplished in recent years, and this is also attributed to the support from top management, the board, and investors. Their focus ensures that we remain at the forefront of the market. Throughout the company, from top to bottom, there's a clear understanding that embracing technology is the key to sustaining our market leadership in regular business operations.  

Can you share examples of software or platforms developed by external vendors? How often do you engage external consultants for projects, and is it primarily dependent on in-house resources?  

We leverage a mix of readily available technology solutions. For instance, we heavily rely on IBM products and utilise Oracle as one of our databases. We've chosen AWS and GCP for critical partnerships. While we actively engage in R&D and incorporate open source for cutting-edge initiatives, our focus on Business As Usual (BAU) in the enterprise domain leads us to prefer popular commercial choices.  

In the past, we used to heavily rely on external hires. However, we've shifted away from this model and now emphasize developing expertise internally. This ensures that the blueprint is seamlessly integrated into our Intel architecture management.  

How HDFC Life is using generative AI to enhance customer interactions and experiences?  

We're not entirely clear about the benefits of this specific technology. To be honest, we're assessing the technology, its associated advantages, and how it aligns with our core function of offering financial products in a heavily regulated environment. We haven't yet reached a point of 100% confidence in the output of a technology like gen AI. For instance, generating a policy document involves legal considerations, and even a single misplaced word can significantly alter the meaning for both the customer and the creator. Currently, we're focusing on internal use cases that are employee-centric, such as health guidelines for HR and sales teams. However, we're still in the exploration phase, trying to uncover the real benefits of a technology like gen AI.