The Evolution of BFSI in the Digital Age: From Cloud Migration to Generative AI

In the information age, data is the new oil. How companies use their data is often the difference between a startup that becomes a household name, and one that sinks without a trace. This has never been more true of the booming Fintech sector. Traditional BFSI players have had to learn fast, and adapt even faster, in this new landscape that takes disruptions like AI, Big Data and now generative AI in its stride.

The fourth Leaders' Circle dove deep into Charting the road to digitisation for the BFSI sector. The session brought together Ravi Ramachandran, Partner Engineering- Strategic Partners at Google Cloud, and Vijay Jain, Client Partner - BFSI & Enterprise Vertical - Cloud & Infrastructure Services Business Unit at Persistent with BFSI leaders Ajish Abdul Rehman, SVP & Head of Data Science at Axis AMC; Alok Singh, DVP IT & Infrastructure Manager - Network and Security at Liberty General Insurance and Mayank Sharma, Head - Audit & Controls at IIFL Holdings Limited. The session was moderated by News18's Paromita Chatterjee.

A discussion centered on the journey of BFSI companies in the digital age had to begin with the challenge of making legacy applications cloud-ready. Alok Singh spoke from the experience of being the first general insurance company to move to the cloud. In his experience, the move was a no-brainer as it saved them costs, brought about service improvements, lowered the incidences of issues significantly, improved the ability to quickly go to market, and much more. The challenge, however, came from adapting their applications.

Vijay Jain talked about the headstart that the digital natives have when it comes to digital adoption, as their applications were, like them, born in the cloud. Brick and mortar players have the additional challenge of rewriting their applications to work with the cloud, in addition to competing with new offerings from the digital native competition.

Mayank Sharma, however, sees this more as an opportunity than a threat. Brick and mortar businesses can and do join hands with digital native businesses to create offerings that bring together the best of both, giving customers the ease and flexibility of a digital first approach, and the accessibility of last mile connectivity, should they want a human interface.

In this context, Ravi Ramachandran emphasized the importance of security and data protection in BFSI and how AI can be harnessed to detect and prevent fraud. Alok Singh chimed in, highlighting the need to strike a balance between identifying threats and avoiding false positives, which can lead to much wasted effort and customer stress.

Ajish Rehman pointed out that BFSI's love for data proves to be a huge plus, when applied to the right models. He spoke about a specific challenge that they set out to solve through data, and by breaking silos and creating the right data set, were able to create a model that helped them understand customer behavior in much more depth. The key takeaway of this story however, was the time taken to create this model: just 2 weeks.

Alok Singh chimed in with examples of his own, that allow Liberty General Insurance to create a hyper-personalized car insurance offering, that changes based on the way drivers drive, use and maintain their cars. The model made so much logical sense that host Paromita Chatterjee was ready to change her insurance provider on the spot.

Ajish Rehman, who has also benefited greatly from such personalization, pointed out the challenge of inconsistent skill levels in data science teams. The BFSI sector faces the dilemma of finding the right talent, especially when dealing with data scientists and analysts. The additional challenge comes from the popularity of data science courses which run the spectrum in terms of quality and practical experience of individual graduates.

Vijay emphasized the importance of hands-on experience and a robust understanding of industry-specific needs amongst engineers. Persistent, as a company, addresses skill shortages by recruiting engineers from various industries and providing practical training rather than relying solely on theoretical knowledge.

While all the panelists were keenly aware of a dearth of digitization professionals and their AI counterparts, they all agreed on the need to transition from predictive AI to generative AI. Generative AI offers the potential for more efficient and personalized customer interactions, but is, of course, expensive, largely due to resource costs. However, as Ravi Ramachandran pointed out, in the age of generative AI the new coding language isn't Python, but English itself.

You can catch the entire discussion here[1] , to get up to speed on the latest insights on how the latest technology disruptions are transforming Indian businesses across industries, and powering the next wave of home grown innovation.

Moneycontrol journalists were not involved in the creation of the article.