Legacy System Modernization, AI, and Embedded Finance with Mphasis’s Rohit Jayachandran

Episode Overview

Rohit Jayachandran is a seasoned executive with over two decades of experience in the financial services technology sector. He currently serves as the Head of Banking and Financial Services at Mphasis, a leading IT services company specializing in cloud and cognitive services In this role, Rohit leads the Banking & Financial Services industry vertical in North America, focusing on delivering transformative technology and operations capabilities to deepen relationships with marquee clients. His team of highly experienced global client partners delivers transformation, platform-driven modernization, and innovation that supports customers’ strategic growth. 

Before joining Mphasis, Rohit worked in the technology vertical of Bank of New York Mellon, where he was involved in the development of complex trading systems. This experience provided him with a deep understanding of the industry’s unique challenges and opportunities, fueling his passion for transformation through technology. Rohit holds a Master’s degree in Management from S.P. Jain Institute of Management & Research, India, and a Bachelor’s degree in Electrical Engineering from Pondicherry University, India.

Throughout his career, Rohit has demonstrated entrepreneurial instincts, successfully building new regions and capabilities. He has a long track record of leading and acquiring businesses, delivering consistent growth, and establishing Mphasis as a trusted partner in the most competitive markets. His leadership is characterized by a commitment to high-tech solutions, high-touch customer service, and high-trust relationships, principles that have been instrumental in driving the company’s success in the financial services sector.​

Episode Transcript

Kevin Rosenquist: Hello and welcome to Pay Pod, where we bring you conversations with the trailblazers shaping the future of payments and fintech. My name is Kevin Rosenquist and thanks for listening. My guest today is Rohit Jayachandran, senior vice president at Mphasis, a global leader in helping enterprises modernize and innovate through cutting edge technology solutions. Rohit has been at the forefront of digital transformation in finance, tackling everything from legacy system modernization to the rise of AI and embedded finance. In this episode. We’re not just talking about the future of fintech. We’re picking his brain on leadership, co-innovation and what’s next for digital payments and AI. So please welcome Rohit Jayachandran. You’ve navigated both technical and leadership roles at Mphasis. I’m curious, what’s a belief or leadership principle that you’ve held on to throughout your journey that maybe you’ve had to rethink as things have changed?

Rohit Jayachandran: So, I’ve been in the firm for 21 years now.

Kevin Rosenquist: Yeah, a long time.

Rohit Jayachandran: And a lot of the principles that you, that you adopt is also from the experiences you had in the firm.  Should I pay a lot of leadership principles have also come from the experience that I’ve had in the firm.  if you look at,what the way we approach the market and all the stakeholders, whether it’s employees or customers,  we’re known for three things. This week. We are high in tech, which means that having a very engineering mindset to solving problems, having an attitude that you can conquer the world in a very nice way, right? Like, let’s be ambitious about what you’re doing.

Kevin Rosenquist: I like that conquest in a nice way.

Rohit Jayachandran: I think about saying that you have to be an imperialist, but I’m just saying that to you. You just have to be ambitious about what you’re doing. Sure. Be generally ambitious about what you’re doing.  we are high in touch. Which means that white glove service we work with. We work with the best brands. We have the best employees, which means they keep them high touch service and finally, high in trust. When you say you deliver, deliver. Right? Otherwise, don’t say you will deliver. Whether it is for the employees, whether it is for customers in general. Be genuine about what you’re doing right. Be genuine about what you’re doing. So these are the three principles that we stood for as an enterprise. That’s what we all. We all stand by on a daily basis, whether it is customers, whether it’s employees, that’s what that’s what we try to do from these principles. We drive everything else down in terms of we engagement with employees, customers. We have our methods to deal with it, starting from these principles, I guess.

Kevin Rosenquist: yeah. How have you had to change your leadership approach as time has gone on? As far as like, you know, Covid change things, work from home, the, you know, what people expect out of their leaders I feel like has changed. Do you find that it’s is it more difficult? Is it just a matter of pivoting? Like how is it being a leader now as opposed to when you started?

Rohit Jayachandran: I think if you if you go back like a few years. Right. We, we used to do a lot of things.  but it is from a customers whether it is employees. So,  the predominant thing has become focus like just focus on a few things and and do that very well. Right. So that’s that’s one  from a post-Covid perspective, I think engagement with employees have have changed. Engagement with customers have changed. Yeah.  one wins. Once Covid happened, I think we we all very quickly got used to to 2D screen and instead of engaging with people. But all of that’s gone now. Now,  robots are like virtual engagement also in a lot of ways become transactional.  so, so getting back to engaging with people, I think we’re getting back to what we used to do well with engaging with customers and engaging with people and, and in, in person, in a lot of ways. There is nothing to to beat in person engagement while understanding the overall that employees and everybody needs some flexibility in their in their operating methods. But but overall you have to engage.

Kevin Rosenquist: Yeah. Yeah. No I agree I think that there’s obviously a shift. I mean we’re doing you know and it’s technology is great in the fact that you and I can have this conversation from far away from each other. But yeah, I mean with with trying to do business over zoom, over email. It is different than that in person. Yeah. You mentioned touch earlier.

Rohit Jayachandran: Yeah. And how it’s changed for leaders as well. I think earlier we used to show up for everything every meeting. And now we go to a city and meet everybody. So a lot of things have changed for the better. But at the core of it employees want engagement. They want to meet you. They want to meet people. Customers want to meet you want engagement. And that’s the thing that we’re seeing as a theme across all.

Kevin Rosenquist: Yeah I’ve seen that. I feel like a lot of people have said that. It’s almost like it’s shifted to a different way where people want that, that connection. You know, we’re so on our phones, we’re so on zoom and all that stuff.

Rohit Jayachandran: Yeah.

Kevin Rosenquist: Yeah. So one of the things that that Mphasis does is you help modernize legacy systems. A lot of times that can be one of the biggest obstacles in digital transformation. But just just beyond the tech hurdles, you know, what are some unseen challenges that you’ve come across in trying to get companies to modernize and kind of, you know, quote unquote, get with the times?

Rohit Jayachandran: Yeah. So if you look at legacy tech, there are about three, three big challenges that’s sitting there.  one is  everything around,  a retiring workforce and who are, who are skilled in a technology that that the new generation, they don’t want to pick up and, and,  and in a lot of ways,  systems that have not been documented. Right. That’s one, one big issue that’s been there. The second thing is new technology offers a lot more capabilities and a lot more agility in the enterprise.  if you look at what’s important now, speed is important. Velocity of product launches is important. There are a lot of startups coming. There are a lot of fintechs coming. How do banks still focus on creating a very agile, agile enterprise? If you look at legacy technologies and everything that the large enterprises and the large banks have, there are three big, three big challenges that are there today. One predominantly is all around an aging workforce who are trained in technologies that the younger generation doesn’t want to take. Most of these systems are not documented. Everything that’s there is in people’s minds and knowledge. And that’s where a lot of this is happening. Yeah.  The second one is all around new capabilities that have come in.

Rohit Jayachandran: And if you look at everything that’s, that’s that’s come now.  lot more new capabilities that allow you to launch new products at speed and at scale.  if you this day and age, everybody can start a company very quickly with less capital, with quick speed. As a large enterprise and a large bank, how do you compete with them? So what? What becomes extremely important is velocity and speed of product launches. Legacy tech in a lot of ways don’t allow for the speed and velocity of product launches. And finally, the third one is the cost, right? There is a cost of operations. There’s a cost of maintaining that, the cost of running that. How do you change budgets from run the bank or run a firm to change the firm, because you get a lot more growth with spending money on launching the firm? Those are three big challenges that are sitting there. What we’ve done very well is we’ve helped firms make this transformation happen. And we’ve also adopted the newest technology. Everybody focuses on gen AI and Copilot and ability to write code for us. I think a lot of investments that we’ve done is, uh. Can you use Gemini to go learn legacy code?

Rohit Jayachandran: All right.

Rohit Jayachandran: So if you look at it,  that’s been the biggest investor, one of the biggest investments that we’ve we’ve made recently.  can you generate a goal on legacy code and come back with,  with documentation and knowledge which is otherwise there in people’s heads? Mhm.  and if you look at legacy tech also the, the, the longest code in that tent is, is spending time to learn that code.  if people are on the how do you learn. So they’ll be using AI to, to do that. And we’ve had amazing success with with with customers or using AI to learn legacy technology. Yeah.  from there, you look at it, you’ve created the knowledge of the legacy code. From there, you take the knowledge and and forward engineer it to to a target state vision that is, that is very forward looking. So that’s the second grade. And how do you use AI for that? How do you how do you use AI to even forward engineer?  one of the most critical things that we found is that is a knowledge graph that you build to,  to learn legacy code that becomes extremely critical and extremely useful to forward engineer as well. So you’re using AI to learn using using the same knowledge graph you’re trying to forward engineer to into a new future. So that’s that’s a signal to go ahead from a,  from a commercial perspective.

Rohit Jayachandran:   we, we believe in, in the concept of self-funding transformations.  a lot of customers don’t have a big budget.  A lot of these technology transformations that we look at it,  require a lot of investments to make and know, both signing a check and saying, listen, I know tech’s changing. You have to factor in ROI. You have to factor in benefits to the business. So what we try to do is can you do,  self-funding, transformation. Zero cost transformation. Can you look at your existing ops? Can you improve the ops? Find. Invest. Find investments from that that you can use to help the transformation. So a lot of work that we’ve done in. In successfully moving enterprises from legacy to new. We think it’s extremely important. To do that. And the reason why is that it gives a lot of agility for. For the customer. You get to a target state that allows for the speed and velocity of new product development. So you can compete with the smaller firms. The large banks also have the benefit of having a lot. That’s millions of customers at scale. When they solve a problem, they can solve it for millions of customers at scale.

Kevin Rosenquist: Yeah. You brought up a good point too, that everybody wants it to be fast. And, you know, you’ve got you’ve got to make you can’t be down. So you got to make the change fast. But just but just, you know, letting go of those outdated systems or upgrading those outdated systems is just the first step. I mean, the real work starts after the upgrade when you have to implement everything. Is there any 1 or 2 things that you feel like companies underestimate in that post modernization phase? Like they’re like, oh, I didn’t think about that.

Rohit Jayachandran: So,  along with modernization, also comes training talent to operate in new methods of working,  new ways of working. Right. Like, if you look at it,  we’ve gotten involved with multiple firms around,  can you automate the software delivery life cycle? The software engineering process in a way that there’s a lot of automation. So if you start with a vision of, I want to have the best engineering process, the best development pipeline, and if you start with that, you can automate a lot more functions early on in the process. The benefit that you get is you get a lot of improvement in velocity, a lot of reduction in cost, just because you’ve improved or improved a lot of,  automated a lot of functions. A given example, even today,  QA people still have a big role to play in the software engineering process. They have a good role. But the question is, can you engineer QA in the engineering process so you can improve cost and velocity. So those are, those are  those are important things that we look for. I think the, the, the biggest thing is as you, as you think of a post-modernist state, is the vision, the right vision.

Rohit Jayachandran: Do you are you pushing the boundaries of,  to my earlier leadership quality, about being ambitious, about tech technology, to being wanting to conquer the world with technology also meaning that do you do you have a vision for a target state that’s that’s appealing, that that takes the best in class, in, in what everyone else is doing and creating that is extremely important. You might not get there initially, but at least you know why you want to get there. And that future state is also a moving target as more technologies come as different technologies. It is a moving target. You have to keep refreshing that you keep keep refreshing that make the right movements. And your target state can be a journey. It’s always a journey. It’s not,  gone are the days of a,  of a three year program with,  where someone says that give me results at the end of three years. It’s all about iterative movement. It’s all about iterative improvement. It’s all about giving benefits and moving KPIs of business in a very iterative fashion. So that’s the big focus, I guess. Yeah.

Kevin Rosenquist: Yeah. You’re right. I mean, you think about it like I’ve worked at companies where you get the new server, you get the new system, you get the new products in place, and you’re like, we’re good for the next five years or whatever number you want to choose, and then you don’t really get any upgrades for a while nowadays, that’s not going to work. You’re going to be changing constantly to keep up with things.

Rohit Jayachandran: Yeah. And if you look at how Tesla updates software, right. Either everything’s available in the car and it’s a very different method of giving a feature function delivery to, to customers,  in a very iterative progressive way on a, on a regular basis I guess.

Kevin Rosenquist: Mhm. Yeah. Yeah. I’d like to talk about embedded finance a little bit. It’s really changing how non-financial companies offer financial services. When you look at the rise of this trend, what do you think traditional finance institutions could learn from how embedded finance operates, especially as far as customer service goes?

Rohit Jayachandran: So,  embedded finance is increasing is interesting. And it has an,  growth. All of us know that. It’s a big addressable market. It’s growing.  I think where the world’s moving to is is collaboration, competition, all of that happening, happening at the same place, right at the same place at the same time with the same set of partners. Also, in a lot of ways, I think the biggest thing that everybody is seeing who owns the customer journey, who owns the customer, will be the biggest winner in this. And and that’s what everybody is, is trying to do from a from from a financial services perspective, what, what we are seeing is that banks are trying to go where the money is being spent, whether it is loyalty programs, whether it is,  restaurants, whether it is travel,  banks, even financial services firms are also seeing where is money being spent. And, and can we go get some of those addressable markets into, into a traditional bank.  That’s where all of embedded finance also comes. And you, you’re, you’re you’re including finance and in different customer touchpoints, whether it is your whether your,  your environment or whether your, your environment or whether it is in any environment you’re trying to include, um, the banking functionality and banking features that the customers can use.  I think customer experience and who owns the customer experience become extremely important.  the second thing is,  I think the ability for, for banks to try out new firms very quickly becomes extremely important.  which means that there is an idea that a bank can I. Can I try it out quickly? Can I fail fast? Can I move forward very quickly and become important? And finally, the third is do I have a technology estate that I can integrate very well, very fast?  so,  we’ve seen banks do one is acquisition of specialist firms that help with embedded finance.

Rohit Jayachandran:  it could be like a healthcare payments. It could be,  it could be different forms that focus on, on, and on the payment space.  for those companies, what we do is we help with the M&A process, which is the integration of them, bringing them into the fold. And that’s what we do . the second thing that we do a lot of is we, we, we help integrate some of these new tech from an innovation perspective.  a lot of,  a lot of the startups, what they do very well is, is ideas and and technology.  What they really,  struggle with or they could take help with is how does a large enterprise adopt it at scale for millions of customers? It is one thing when you’re doing it for 100,000 customers is another thing to do it with your customers. Yeah. So yeah, we tend to bridge that gap  with, with banks as well, which is can we be the, can we be the integration layer, if I may? Between the startups and between the bank, helping them succeed, helping them be successful with a lot of customers, with millions of customers. That’s a big focus for us. Um, and finally, the third thing is creating the technology estate,  in a way that allows you to, to constantly bring in firms and integrate firms into, into your environment is a big focus for us. So those are the things that we help with in this space.

Kevin Rosenquist: Okay. Yeah. I wanted to also ask you about the Sparkle Innovation Lab. Um, it takes a co-innovation approach with clients.  it’s really cool. I was reading on it, writing up on it. It’s very cool. In what ways has this collaborative model sort of surprised you in terms of generating unexpected solutions compared to maybe traditional R&D?

Rohit Jayachandran:  traditional R&D focuses,  on, On the next generation innovation, what we see are we we we invest a lot in that space. But this focus of sparkle is is contextual innovation specific to customers?  you a lot of customers have their own legacy technologies, have their own investments in new software, their own investments in SDLC processes. A lot of that stuff and this new technology available across sparkle is do contextual innovation for the customer. What we’ve seen with them is,  okay, I want to try out new technology. One. There are 2 or 3 hurdles that come in between. One hurdle is,  is all around. Can I,  from an infrastructure perspective, I take a lot more time to provision and. Okay, I want to test. This can take six months to bring that software in. I’ll take six months to create a new server for that. So that becomes an issue. The second issue, from a contextual innovation perspective, I don’t have the right people. Okay, this is new tech. I don’t have the right skill. I don’t have the right people to to try out this new thing. So that’s why we get involved with sparkle.  and,  sparkle helps with contextual innovation.  we look at the customer roadmap and say, if this is your roadmap, here’s the innovation that’s happening around your roadmap, right. And if this is innovation around your image, by the way, you will take a lot of time to try this out. Can I try this out in my environment? And by the way my environment I can mimic your environment in, in Mphasis, which means that the same version of software, the same hardware in which all the innovation idea in an environment that resembles a customer environment as much as possible. and with cloud,  it also allows us to share data as well, because in a, in a very secure way that becomes useful. It’s been going on for five years and I can’t be more excited about the success it’s given.

Kevin Rosenquist: It’s also.

Rohit Jayachandran:  we,  if you do 100 innovation ideas, ten go into production, which is a good number, and we manage our number.  we,  the reason why we manage the number is if everything goes into production, you’re not being ambitious enough. If I say to you, if nothing goes into production, which means that you’re you’re becoming a forward looking R&D shop, which is, again, not not so. So we manage a number well because we want to make sure the right we’re making the right impact with with customer customers love it. And the general feedback that you,  that they do is that they give us is one of the biggest CIOs told us that do more sparkle. Good for you. Good for us because you’re innovating. We are innovating as a partnership. It does a lot of good things for all of us.

Kevin Rosenquist: You mentioned how things like Co-innovation tends to produce more immediate solutions. Is it hard to manage that? That tension between delivering quick, iterative wins and aiming for that long term disruptive innovation?

Rohit Jayachandran: In fact, sparkles enables that iterative improvement of technology because your teams are doing what they’re doing in terms of delivering what they have to do to make sure your milestones are met, your business is moving forward. This is a parallel track where you’re innovating separately with the customer, but the customers are collaborative, very collaborative, but separately with the customer. And then you bring it in. And if you if it’s successful, you bring it in. So in a lot of ways it is a, it’s a, it’s you’re testing the idea. You’re, you’re making sure that you’re, you’re doing it in a, you’re not distracting the teams with the new idea. And if it’s successful, you, you, you bring it into the mainstream and then you say, okay, let’s bring it into the mainstream in a lot of ways. It enables adoption of new tech without distracting day to day milestones and deliveries of project teams. The way we think about it.

Kevin Rosenquist: Okay. All right. Yeah. It’s really cool. Really cool thing. Like I said, I was reading up on it a little bit before this, and it’s really cool. I wanted to talk a little bit about just kind of general AI with you. There’s so much hype around AI and blockchain. What’s a problem in fintech or payments that you think is still waiting for the right solution, something that the industry hasn’t really cracked yet?

Rohit Jayachandran: Yeah, we think of blockchain and AI very differently. Blockchain has been there for a while.  and it works well for the right use case.  blockchain requires collaboration between entities who otherwise are not in the same space in the same organization construct, which means centralization, which means you need a lead partner to, to create and adopt blockchain. it does not work in oligopolistic markets because no one wants to take the lead. Everybody has got an equal share. So there are specific use cases where blockchain works very well. Uh and you need a lead partner and a lead sponsor for blockchain. In a lot of ways we think  centrally it works well when there is a central industry body mandating it because then everybody adopts and then, of course, collaboration. It’s not your competitor. It’s not your competitors creating it. It’s about industry body that’s creating it. So blockchain is anonymous in a lot of ways for us as needing to collaborate, needing to centralize between entities that otherwise don’t collaborate.  AI is the democratization of innovation. It is completely on the other, other spectrum. So blockchain needs a right use case. If a lot of use cases fit and right, everything you do in financial services will have some AI in it. Ai helps you to touch everything. So that way it’s very different. Blockchain and AI. Blockchain needs a right use case. Most use cases fit AI to a point. So that way it is very different. One of the big use cases that we are focusing on from a blockchain perspective is deep care financing.

Rohit Jayachandran: It doesn’t require too much collaboration. It needs some collaboration and doesn’t require too much collaboration. It helps bank to lend to supply chain finance organizations much deeper in the supply chain, which otherwise they wouldn’t approach. So that way a lot of people have benefits from that use case. So with blockchain we focus on point examples that fits the narrative of blockchain With. I,  I just touches everything that we’re doing now, right? Everything that we’re doing now touches. If you take customer experience as a concept, if a customer goes to a branch vis a vis, call a contact center vis a vis look online, are you able to give this? Are you able to transition the same context between all of it? Yeah. Are you able to service a customer with the right channel at the at the right for the right request?  there might be a certain customer service request that you want them to talk to an agent because it’s a it’s an offer opportunity. It’s a next best action opportunity. There’s stuff like update my address where you don’t want them to call you. You just want them to do conversation. Like I they just want you to go digital. Yeah. So all of that becomes extremely into how are you able to manage customer service?  we’re seeing customers do that.  how are you able to manage customer service across all,  all channels?  does your branch teller see the same thing that your digital channel sees? Does your conversational AI see exactly what everybody else sees? So.

Rohit Jayachandran: So that’s become,  interesting?  that’s been a big focus where a lot of customers are, are,  investing right now, which is,  on the customer experience side.  but blockchain, if you look at it,  with AI, you could touch the entire customer experience with, with blockchain. What you’re doing is you’re looking for the right use case.  If you look at the bank’s purpose of, of serving a lot of customers at the right risk, at the right risk profile, at the right cost point, AI helps with all of it. If you if you look at embedded finance, it helps you approach a lot of customers. If you look at managing risk, you’re able to approach a lot of customers because you didn’t understand risk as much as what you’re understanding now, right? If you look at the customer experience, you’re able to from a cost perspective, you’re able to drive cost,  you’re able to drive channels in the right channels and the right across service requests. So I is exciting because we think it will touch everything. Blockchain is exciting for a different reason. You need to find the right use case and the right use case is the killer. It’s a killer combination. So that way we think about it as very differently. Blockchain in AI both have its own purpose. We were excited in both texts for different reasons.

Kevin Rosenquist: I think it’s a really good way to look at it. Yeah. You’re right. Like you do. It’s you kind of have to fit blockchain technology into what you’re doing. Whereas AI is just you, it’s everywhere. And that’s what brings me curious. Is there anything that you think in the, in the, you know, as far as the future of digital payments and finance that I won’t touch? Is there anything that you think that will remain unchanged over, over the next, I don’t know, decade. You know. Yeah.

Speaker3: That’s everything. No.

Rohit Jayachandran: To touch everything. You just touch everything. If you look at payments, also one of the biggest issues with payments is legacy tech. Yeah. Right.  you’ve got multiple standards, multiple regions, multiple jurisdictions, multiple regulations and regulations. Is a is a big space that we are using a lot of,  a lot of AI to help it.  a lot of focus for us is,  can you, in an automated way, look at regulations and automatically generate rules from, from the regulations. So,  across a lot of complex problems there are in the payment space in AI enables make it a bit more easier across everything. We think of AI as an enabler to touch every use case in a and help solve that use case in a bit more easier way, in some cases a lot more easier and some cases a bit more easier way. That’s the way we think about AI. We don’t think about blockchain like that.

Kevin Rosenquist: Yeah. Yeah. Very true, very true. Yeah. Well it’s certainly, uh it’s been an exciting time and,  yeah. Who knows where it’s going to go from here. I mean, it’s just it changes by the day and to your point about regulations too. I mean, that’s that’s a tough that’s a tough thing because it’s, that’s constantly changing and it’s going to keep changing, you know, as, as AI regulations start to come down from, from different, you know, from different governments and, and, and we’re I feel like the US is a little late on a lot of that too, as far as the regulations go.

Rohit Jayachandran: Well, that and if you look at a lot of the sanctions and screening and AML and all of that, typically a lot of compliance processes has maker checker, QA, QC. Right. It’s a lot of cost. It’s a lot of infrastructure that you’re creating to enable this. Can you take the maker and can you remove the maker out of the chain and make it a digital workup. Mhm. When I say digital worker it’s an LLM that that has that’s like a person. The difference is that the LLM doesn’t need to go to bed. It’s working all the time.

Kevin Rosenquist: It’s all no lunch breaks. Yeah.

Rohit Jayachandran: And then you.

Rohit Jayachandran: And then there’s a checker as well. There’s a lot of explainability with this because regulators look for explainability. This process allows for explainability because you’re only replacing the maker. The rules are defined in your environment. You know exactly what the maker is doing. Then you have a human in the loop checkup. You’re not taking the human out of the loop. We’re human in the loop checker. Then there’s a QA and A and a QC process after that. So if you look at payments and sanctions and money laundering and AI is something that space. So we just think that it’s going to be there everywhere. It’s about having the right firm being able to have the right guardrails, the right tooling, the right infrastructure to enable it. We see 2025 as a year when a lot of this comes live. Now, the most mature from what we’ve seen is creating a backlog of a lot of these AI right now.  The creating backlog, the 2024 was a year of testing,  making sure that we were creating the tooling, the guardrails, and the base infrastructure to make it successful. Within 25 onward, they start launching. And it will be time for mass adoption as we think it is.

Kevin Rosenquist: Wow.

Kevin Rosenquist: That’s not far away.

Kevin Rosenquist: Far, far away at all.

Kevin Rosenquist: No, no. Well, well, it’ll be interesting to see what happens. Well, Rohit, thank you so much for being here. I really appreciate your time and knowledge. And yeah, I love to keep up with everything you guys are doing over at Mphasis.

Rohit Jayachandran: Thank you so much Kevin. It’s been wonderful chatting to you today.