Guest Speaker:
Transcripts
Welcome to a brand new episode of Tech Lyceum. This is a podcast from Birlasoft where we explore the ideas shaping technology and business. I'm your host, Neerja, and today we are discussing the Gen AI edge, reimagining BFSI through innovation. What does this entail?
Well, let's find out. We have two experts and an exciting chat lined up.
Listen On
Speaker – Neerja - 00:35
First up, we have Ramasubramanian, Senior Vice President, delivery, head financial services and high tech at Birlasoft, Ram is a trailblazing delivery lead driving transformation across the financial services and high tech verticals at Birlasoft, with over two decades of global experience, he has consistently delivered excellence and scaled industrialized delivery models. Ram is recognized for his strategic foresight, customer centric approach and operational discipline. He leads with purpose, empowering high performing teams and inspiring bold innovation and continuous growth. Ram, thank you for joining us, and welcome to the show.
First up, we have Ramasubramanian, Senior Vice President, delivery, head financial services and high tech at Birlasoft, Ram is a trailblazing delivery lead driving transformation across the financial services and high tech verticals at Birlasoft, with over two decades of global experience, he has consistently delivered excellence and scaled industrialized delivery models. Ram is recognized for his strategic foresight, customer centric approach and operational discipline. He leads with purpose, empowering high performing teams and inspiring bold innovation and continuous growth. Ram, thank you for joining us, and welcome to the show.
Speaker – Ram - 01:18
Thank you, Neerja, happy to be part of this.
Thank you, Neerja, happy to be part of this.
Speaker – Neerja - 01:21
Joining Ram is Atul Bansal, Vice President, delivery leader, banking. Atul is a seasoned strategic delivery leader with over 25 years of experience in the BFSI sector. Atul is known for spearheading large scale, multi-million dollar programs with a sharp focus on delivery excellence, operational agility and client trust, From program and project management to application support, he has led high performing global teams and driven real impact through transformation, quality and innovation, a true results driven leader Atul brings deep expertise in navigating change and delivering sustainable value. Atul, welcome to the show. It's great to have you.
Joining Ram is Atul Bansal, Vice President, delivery leader, banking. Atul is a seasoned strategic delivery leader with over 25 years of experience in the BFSI sector. Atul is known for spearheading large scale, multi-million dollar programs with a sharp focus on delivery excellence, operational agility and client trust, From program and project management to application support, he has led high performing global teams and driven real impact through transformation, quality and innovation, a true results driven leader Atul brings deep expertise in navigating change and delivering sustainable value. Atul, welcome to the show. It's great to have you.
Speaker – Atul - 02:07
Thank you, Neerja.
Thank you, Neerja.
Speaker – Neerja –01:50
So, if I may drive the first question to you. Pankaj, very interesting topic we're covering here, and I think we should set the base for it. Q: What are some common challenges that manufacturing companies face during the cloud migration process?
So, if I may drive the first question to you. Pankaj, very interesting topic we're covering here, and I think we should set the base for it. Q: What are some common challenges that manufacturing companies face during the cloud migration process?
Speaker – Neerja - 02:08
So let's dive straight into the conversation and Ram my first question here is for you.
Q: Gen AI is no longer just a buzzword, right? It is entering production across the BFSI landscape in an industry built on precision, compliance and customer trust, what does it really take to move from Gen AI hype to real, responsible impact?
So let's dive straight into the conversation and Ram my first question here is for you.
Q: Gen AI is no longer just a buzzword, right? It is entering production across the BFSI landscape in an industry built on precision, compliance and customer trust, what does it really take to move from Gen AI hype to real, responsible impact?
Speaker – Ram - 02:32
Thanks, Neerja for the question. I would definitely agree it's no longer a buzzword. Right at this point of time, we are seeing large scale implementation across geographies, and the focus to make this an accelerated adoption, there are, you know, few focus areas that I would delve deeper into. First and foremost, generative AI should be aligned to the core business objectives and goals of the organization. It cannot be a standalone initiative just for the fear of missing out, it has to be aligned with strategic imperatives. And this could be, you know, cost reduction, this could be revenue growth, customer experience, or a combination of all of this, right? But it's important that we do a deep dive assessment of what is the problem that we are trying to solve and how generative AI can help solve it, right?
So tying that back to the overall organization's goals and objectives is very essential, right? That's number one.
Number two, there's a need to start small. Early success will give the required motivation. It will also help us measure what we are doing right and what we are not right. And it's important we find the right use case. This could be a high value, low risk category. It could be something like a document summarization. It could be a, you know, customer service or a claims processing, right? But it's important that we find start small and then scale accordingly. BSFI also as an industry, is under a lot of regulation and compliance. So initial momentum is going to be a bit slow, but it is important that we build a comprehensive AI governance framework, which includes auditing of the models, explainability of the model outcomes and bias checks, right? So responsible AI and the governance associated is going to be very, very essential. I would talk about also the legacy nature of many of the BFSI organizations. The system of record has been largely kept in legacy systems, legacy technologies. So it is important how generative AI is going to be built into the enterprise architecture of an organization to keep it decoupled, to keep it not dependent on the specific model and the scalability and adaptability of it is going to be very important. Finding the right talent is going to be very critical for success of generative AI implementation. You need to upskill people. You need to bring in fresh talent, attract a lot of AI, savvy professionals, and we need to bring in a continuous learning culture into the organization. And finally, I would say security should not be an afterthought. It has to be part of the design, and that's going to be very essential for the success of implementing generative AI at scale and achieving the benefits of it. Over to you, Neerja.
Thanks, Neerja for the question. I would definitely agree it's no longer a buzzword. Right at this point of time, we are seeing large scale implementation across geographies, and the focus to make this an accelerated adoption, there are, you know, few focus areas that I would delve deeper into. First and foremost, generative AI should be aligned to the core business objectives and goals of the organization. It cannot be a standalone initiative just for the fear of missing out, it has to be aligned with strategic imperatives. And this could be, you know, cost reduction, this could be revenue growth, customer experience, or a combination of all of this, right? But it's important that we do a deep dive assessment of what is the problem that we are trying to solve and how generative AI can help solve it, right?
So tying that back to the overall organization's goals and objectives is very essential, right? That's number one.
Number two, there's a need to start small. Early success will give the required motivation. It will also help us measure what we are doing right and what we are not right. And it's important we find the right use case. This could be a high value, low risk category. It could be something like a document summarization. It could be a, you know, customer service or a claims processing, right? But it's important that we find start small and then scale accordingly. BSFI also as an industry, is under a lot of regulation and compliance. So initial momentum is going to be a bit slow, but it is important that we build a comprehensive AI governance framework, which includes auditing of the models, explainability of the model outcomes and bias checks, right? So responsible AI and the governance associated is going to be very, very essential. I would talk about also the legacy nature of many of the BFSI organizations. The system of record has been largely kept in legacy systems, legacy technologies. So it is important how generative AI is going to be built into the enterprise architecture of an organization to keep it decoupled, to keep it not dependent on the specific model and the scalability and adaptability of it is going to be very important. Finding the right talent is going to be very critical for success of generative AI implementation. You need to upskill people. You need to bring in fresh talent, attract a lot of AI, savvy professionals, and we need to bring in a continuous learning culture into the organization. And finally, I would say security should not be an afterthought. It has to be part of the design, and that's going to be very essential for the success of implementing generative AI at scale and achieving the benefits of it. Over to you, Neerja.
Speaker – Neerja - 05:26
Thanks, Ram for all of those insights. And Atul, you were part of Birlasoft recent Gen AI innovation sprint spark edge, which focused on the BFSI industry.
Q: What surprised you the most, you know when we talk about the tech, the speed or how real problems translate into solutions.
Thanks, Ram for all of those insights. And Atul, you were part of Birlasoft recent Gen AI innovation sprint spark edge, which focused on the BFSI industry.
Q: What surprised you the most, you know when we talk about the tech, the speed or how real problems translate into solutions.
Speaker – Atul - 05:46
Atul, yeah, sure, Neerja. See, what truly surprised me was the speed with which complex, real world challenges were translated into practical and scalable solutions during Spark edge hackathon. And I would like to site some examples. The first one is agentic banking. Here team built a secure on-prem, LLM agent that could orchestrate banking API based on user query. And that is not just innovation. That is future ready banking architecture in action. The second example is Corp doc AI. So this solution auto generated rich contextual code documentation using chat GPT directly integrating with Bitbucket and Confluence.
It's a game changer for onboarding and compliance, which is a key in the BFS segment. And the third example is app traffic analyzer, which is a Gen AI powered anomaly detection engine for real time app monitoring, and this was a bold step towards building proactive resilience. So yes, while the inherent capability of Gen AI technology is undeniably impressive, but what proved equally remarkable was the accelerated pace from idea to execution, the teams demonstrated exceptional clarity in identifying domain specific and productivity related challenges and in rapidly translating them into AI driven prototypes. This reflects a strong alignment between technological innovation and the business need.
Atul, yeah, sure, Neerja. See, what truly surprised me was the speed with which complex, real world challenges were translated into practical and scalable solutions during Spark edge hackathon. And I would like to site some examples. The first one is agentic banking. Here team built a secure on-prem, LLM agent that could orchestrate banking API based on user query. And that is not just innovation. That is future ready banking architecture in action. The second example is Corp doc AI. So this solution auto generated rich contextual code documentation using chat GPT directly integrating with Bitbucket and Confluence.
It's a game changer for onboarding and compliance, which is a key in the BFS segment. And the third example is app traffic analyzer, which is a Gen AI powered anomaly detection engine for real time app monitoring, and this was a bold step towards building proactive resilience. So yes, while the inherent capability of Gen AI technology is undeniably impressive, but what proved equally remarkable was the accelerated pace from idea to execution, the teams demonstrated exceptional clarity in identifying domain specific and productivity related challenges and in rapidly translating them into AI driven prototypes. This reflects a strong alignment between technological innovation and the business need.
Speaker – Neerja - 07:21
Yeah, thank you Atul and coming to this Ram from intelligent documentation and system monitoring to customer facing AI Co-pilot, right Gen AI is already reshaping the fabric of next gen financial and insurance enterprises.
Q: What excites you most about this entire evolution, and what do you believe it will take for the industry to truly adopt Gen AI as a strategic enabler, rather than just another tool?
Yeah, thank you Atul and coming to this Ram from intelligent documentation and system monitoring to customer facing AI Co-pilot, right Gen AI is already reshaping the fabric of next gen financial and insurance enterprises.
Q: What excites you most about this entire evolution, and what do you believe it will take for the industry to truly adopt Gen AI as a strategic enabler, rather than just another tool?
Speaker – Ram - 07:53
Sure, Generative AI, to me, is just not another tool, right? It is a strategic capability that redefines how BFSI financial services organizations are going to engage, operate and innovate for the next few decades to come. Now, when organizations realize it is no more about efficiency and improvement around efficiency, it is about value addition to the business, that's when the real enablement and adoption starts to, you know, improve. Now, this whole shift from automation to augmentation, right, generative AI is just not about replacing tasks. It's not about making them faster. It is about empowering professionals to work faster and smarter, and it is transforming the sector like none before right?
Now, imagine this a personal copilot sitting next to you, advising you on everything that you do. You can be an investment advisor, you can be an underwriter, or you could just be the end customer looking at getting value from the business. Now all of this package together is what the enablement that we are talking about, right? And we have seen real life examples of this, which reiterates and showcases the value that it brings in. Now you talk about, you know, a large payments network using generative AI to scan millions of transactions on the go, stopping compromise cards at scale, blocking fraudulent transactions. This is the game that you're talking about. It is just not about doing things cheaper it. It is about bringing that strategic value addition to the business life cycle. Right?
We have seen many such examples, whether it is scanning through complex commercial loan agreements, extracting, you know, important classes and reviewing them, which could take lot of manual hours, which could potentially cause a lot of manual errors, are all being completely taken over now, even within Birlasoft, we are also providing such solutions to our customers in the space of claim, submission, fraud, analytics, infrastructure optimization on the IT side. You're looking at agentic AI as a next step beyond RPA right? Now, everything eventually leads to value addition, and this adoption overall will be driven by the logical shift from, you know, looking for efficiency towards driving value creation across the business life cycle. That's how I would summarize. Neerja.
Sure, Generative AI, to me, is just not another tool, right? It is a strategic capability that redefines how BFSI financial services organizations are going to engage, operate and innovate for the next few decades to come. Now, when organizations realize it is no more about efficiency and improvement around efficiency, it is about value addition to the business, that's when the real enablement and adoption starts to, you know, improve. Now, this whole shift from automation to augmentation, right, generative AI is just not about replacing tasks. It's not about making them faster. It is about empowering professionals to work faster and smarter, and it is transforming the sector like none before right?
Now, imagine this a personal copilot sitting next to you, advising you on everything that you do. You can be an investment advisor, you can be an underwriter, or you could just be the end customer looking at getting value from the business. Now all of this package together is what the enablement that we are talking about, right? And we have seen real life examples of this, which reiterates and showcases the value that it brings in. Now you talk about, you know, a large payments network using generative AI to scan millions of transactions on the go, stopping compromise cards at scale, blocking fraudulent transactions. This is the game that you're talking about. It is just not about doing things cheaper it. It is about bringing that strategic value addition to the business life cycle. Right?
We have seen many such examples, whether it is scanning through complex commercial loan agreements, extracting, you know, important classes and reviewing them, which could take lot of manual hours, which could potentially cause a lot of manual errors, are all being completely taken over now, even within Birlasoft, we are also providing such solutions to our customers in the space of claim, submission, fraud, analytics, infrastructure optimization on the IT side. You're looking at agentic AI as a next step beyond RPA right? Now, everything eventually leads to value addition, and this adoption overall will be driven by the logical shift from, you know, looking for efficiency towards driving value creation across the business life cycle. That's how I would summarize. Neerja.
Speaker – Neerja - 10:22
Thanks, Ram. And to your point, it is more than just a tool, and that means technology is only one part of the equation. Real transformation in financial services depends on mindset trust and a culture of continuous innovation. And that brings me to this question for you Atul.
Q: Drawing from your industry experience, including recent innovation sprints, what strategic or cultural shifts do you believe forward thinking banks and insurers must embrace to adopt Gen AI effectively and responsibly?
Thanks, Ram. And to your point, it is more than just a tool, and that means technology is only one part of the equation. Real transformation in financial services depends on mindset trust and a culture of continuous innovation. And that brings me to this question for you Atul.
Q: Drawing from your industry experience, including recent innovation sprints, what strategic or cultural shifts do you believe forward thinking banks and insurers must embrace to adopt Gen AI effectively and responsibly?
Speaker – Atul - 10:59
Yeah, so absolutely you see Gen AI technology is definitely very powerful, but it is not plug and play. So what Spark edge hackathon showed us is that real unlock happen when organizations shift their mindset. So there are learnings which I would like to share.
The first one is speed and experimentation must become part of the culture. So what we have seen that in just 48 hours, teams go from idea to working prototype and solving real problems like agentic banking developers documentation and anomaly detection. And that that is not just tech agility, right? That is a cultural agility. And second, which is non negotiable trust and governance. So in BFSI, where data sensitivity is paramount importance, we need secure, explainable Gen AI system with responsible innovation
And third, cross functional collaboration is key. The best idea came from teams that blended domain, expert, engineer, designer, our quality engineer. It is not just building about Gen AI tools. It is about solving business or IT problems with Gen AI as an enabler. And finally, continuous learning. Right? As you know, Gen AI is evolving very fast, and industry must invest in upskilling, sandboxing and building internal platforms to scale responsibility. So to summarize, yes, Gen AI technology is very compelling, but the true transformation has been driven by shifted mindset, grounded interest openness and a culture of continuous innovation. And this cultural evolution has enabled faster experimentation, cross functional collaboration and the rapid deployment of AI driven solutions that are already delivering measurable impact across key businesses. Thanks.
Yeah, so absolutely you see Gen AI technology is definitely very powerful, but it is not plug and play. So what Spark edge hackathon showed us is that real unlock happen when organizations shift their mindset. So there are learnings which I would like to share.
The first one is speed and experimentation must become part of the culture. So what we have seen that in just 48 hours, teams go from idea to working prototype and solving real problems like agentic banking developers documentation and anomaly detection. And that that is not just tech agility, right? That is a cultural agility. And second, which is non negotiable trust and governance. So in BFSI, where data sensitivity is paramount importance, we need secure, explainable Gen AI system with responsible innovation
And third, cross functional collaboration is key. The best idea came from teams that blended domain, expert, engineer, designer, our quality engineer. It is not just building about Gen AI tools. It is about solving business or IT problems with Gen AI as an enabler. And finally, continuous learning. Right? As you know, Gen AI is evolving very fast, and industry must invest in upskilling, sandboxing and building internal platforms to scale responsibility. So to summarize, yes, Gen AI technology is very compelling, but the true transformation has been driven by shifted mindset, grounded interest openness and a culture of continuous innovation. And this cultural evolution has enabled faster experimentation, cross functional collaboration and the rapid deployment of AI driven solutions that are already delivering measurable impact across key businesses. Thanks.
Speaker – Neerja - 12:56
Thank you Atul and thank you ram for coming on here and taking us through the nuances of this exciting and inevitable transformation.
Thank you Atul and thank you ram for coming on here and taking us through the nuances of this exciting and inevitable transformation.
Speaker- Ram – 13:05
Thank you.
Thank you.
Speaker – Neerja – 13:07
What a powerful discussion today. Ram and Atul have helped us cut through the Gen AI hype and see how it's driving real change in BFSI, from agentic banking to intelligent documentation and anomaly detection, the message is clear.
Gen AI is more than a tool. It is a strategic enabler, as illustrated by both Ram and Atul. But unlocking its full value will take more than just tech. It requires a mindset shift, strong governance and a culture of collaboration and experimentation. Once again, I'd like to thank Ram and Atul for this conversation, and of course, to our listeners, stay curious and ready, because the Gen AI edge is already here. Until next time, it's me Neerja, signing off from Tech Lyceum.
What a powerful discussion today. Ram and Atul have helped us cut through the Gen AI hype and see how it's driving real change in BFSI, from agentic banking to intelligent documentation and anomaly detection, the message is clear.
Gen AI is more than a tool. It is a strategic enabler, as illustrated by both Ram and Atul. But unlocking its full value will take more than just tech. It requires a mindset shift, strong governance and a culture of collaboration and experimentation. Once again, I'd like to thank Ram and Atul for this conversation, and of course, to our listeners, stay curious and ready, because the Gen AI edge is already here. Until next time, it's me Neerja, signing off from Tech Lyceum.
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