Snowflake Summit 2025 | Bibhu Patnaik & Shailender Sidhu, Deloitte

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Bibhu Patnaik

AI & Data Principal

Deloitte

Shailender Sidhu

AI & Data Principal, Financial Services Industry

Deloitte

Deloitte clears a faster AI path for banks with a governed data platform

Financial institutions are rapidly moving to reimagine their operations with generative artificial intelligence, which begins with a governed data platform. But these organizations aren’t chasing hype: They’re demanding measurable value.Deloitte’s Bibhu Patnaik and Shailender Sidhu talk with theCUBE about overcoming legacy data silos and accelerating AI adoption.Deloitte Consulting LLP’s data leaders say clients want more than strategies — they expect accelerated delivery, real-time insight and a measurable return on investment

play_circle_outline Deloitte's Innovative Partnership with Snowflake Revolutionizes Financial Services Industry Through Data Harmonization and Process Re-imagination

play_circle_outline Importance of quality data for AI and analytics in financial institutions.

play_circle_outline Financial Executives Embrace Cloud: How Deloitte Drives Value with Expertise and Innovation

play_circle_outline Acceleration of data modernization and AI adoption in banking industry.

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Bibhu Patnaik & Shailender Sidhu, Deloitte

Bibhu Patnaik

AI & Data Principal Deloitte

Shailender Sidhu

AI & Data Principal, Financial Services Industry Deloitte

In this interview from Snowflake Summit 2025, Bibhu Patnaik, partner in Deloitte’s banking and capital markets practice, and Shailender Sidhu, partner and leader of Deloitte’s financial services Industry AI and data business, join theCUBE’s Dave Vellante and John Furrier to explore how data-driven disruption is reshaping financial services. The discussion spans today’s dual mandate of defensive compliance and offensive growth, revealing why forward-thinking banks are doubling down on AI-powered insights, agentic re-imagination and hyper-personalized customer ... Read more

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What are some challenges that banks are facing in terms of data management and regulatory oversight, and how is Snowflake helping to address these challenges? add

What is the importance of quality data in AI and analytics? add

What are some driving factors that move companies towards a modernization journey, specifically focusing on cloud technology adoption? add

What are some observations regarding the current trends in data AI and agentic investment in the marketplace? add

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Bibhu Patnaik & Shailender Sidhu, Deloitte

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Rebecca Knight

>> Hello everyone, and welcome back to theCUBE's live coverage of the Snowflake Summit 2025 here at the Moscone Center. I'm your host, Rebecca Knight, alongside my co-host and analyst, co-founder of theCUBE, Dave Vellante. I would like to introduce our next guest. They are Shailender Sidhu, AI and Data Principal Financial Services Industry at Deloitte. Shailender, welcome to theCUBE.

Shailender Sidhu

>> Thank you very much.

Rebecca Knight

>> And Bibhu Patnaik, AI and Data Principal at Deloitte. Thank you so much for coming on theCUBE.

Bibhu Patnaik

>> Thank you very much-

Rebecca Knight

>> We're excited to have you....

Bibhu Patnaik

>> for having us.

Rebecca Knight

>> So, this is really a question for both of you, but I'm going to direct it at you Shailender first. Why don't you start by telling our viewers a little bit about how Deloitte is working with Snowflake, and specifically how it's working to bring more value to financial services clients?

Shailender Sidhu

>> Yeah, absolutely. I think when you talk about financial services industry, you think about banking, capital markets payments, talk about insurance and other sectors within that industry. And I think with the changes that are happening, data and AI are becoming critical for all aspects of business. Whether they're the defensive agenda of these organizations, the offensive agenda or the disruptive agenda. So we are partnering very closely with Snowflake to bring this innovative thinking, the re-imagined way of thinking about processes to our customers. And that's driving value for our customers, and also driving growth for every stakeholder in the ecosystem.

Bibhu Patnaik

>> Yeah. I would add a few things that I'm seeing in the market as well with our clients. Traditionally, especially in the banking space, we see a lot of these data silos, and that has been there forever. And now they are moving, as they're growing in their asset size, they're getting more into a regulatory oversight area. So it's bank categorization is changing from a category IV to a category III. Which means, you need to have a governed data platform which is scalable, reconciled to the ledger, et cetera. And that's where Snowflake shines, and that's where we are partnering with Snowflake to create that governed data platform ecosystem. A single source of truth which people can rely on mainly from a financials and regulatory purposes as well.

Dave Vellante

>> Financial services market is the best market. It's probably the hardest because they're so demanding. But they've got money, in the money business, and they have the skills. Now, we heard early on in the cloud days, we're never going to put our data in the cloud. And of course you well know. all the banks, have excellent cloud operational models. They still got a bunch of data on prem. We can come back and talk about that. But to your point, they've got these data silos. And we see that Snowflake was nowhere three or four years ago in AI. You come to these conferences, they never talked about ML, very rarely. And they've gone from nowhere to a leader. People say, "Well, how'd do that?" Well, they've got good data to operate on. So, what are the steps that these financial institutions are having to take to de-silo and bring AI? Are they just basically taking AI to that data that's already in Snowflake? Are they bringing in other data? What does that all look like?

Bibhu Patnaik

>> Yeah. I can give a couple of examples where the pattern that I see is actually getting data together first. because if you look at it, quality of data is very important. You can have AI, but if AI is on bad quality, it doesn't really give you the value. So the good thing is, Snowflake has really invested in actually creating that common data layer, if you will, on cloud, and having a good quality data that can add value when we bring in AI and analytics to it. And that's where my clients are moving towards. And as you said, it has been traditionally data, data analytics, AI to it. And now, people are moving more towards agentic solutions. And you can only have that value we have when you have good quality data. I think that's where we are seeing clients move towards.

Shailender Sidhu

>> And that's a great point, if I can add to that. I think the challenge is not having data. The challenge is how do you stitch the data together which creates meaningful insights?. Bibhu mentioned the point about agents or agentification of processes. Now in banking, let's say we talk about commercial customer onboarding, it's a pretty painful process. How can you solve that process and make it more efficient? And you can do that by putting these AI agents. But for them to be very effective and the process to be re-imagined, they need good data, good quality data to make those right decisions, to increase the developer or the endless productivity as part of it. And we are seeing a similar pattern using these integrated data sets around claims processing, or underwriting 360, are the other areas where we are seeing a value. And finally, in payments industry we are seeing a lot of opportunities around data monetization. Which again is a function of creating those integrated data sets to drive value for their customers.

Dave Vellante

>> Snowflake has made the point that they have to be increasingly in the full life cycle of data. Not just when it gets into Snowflake, but when data is created. Now, that's not necessarily their expertise. I presume that's where you come in, you've got this data, I think it's data as a service. I learned about that a little bit at Google Cloud Next. So help us understand where Deloitte enters the picture, presumably early on at the board level, but help us think through how that partnership fuses.

Shailender Sidhu

>> And the whole journey for data as a service started a few years back. And that was based on our collective experience in the market, where to do an enterprise, a line of business, or a corporate function data transmission was pretty painful long-term journey. So our focus was, how do we remove some of those pains from these journey for our clients? And that was how the data as a service concept started. And what we have done is, we have built this asset, this accelerator, which is GenAI enabled, which focuses on the different aspects of data architecture, data management, and data governance. Whether it is lineage, whether it's canonical data structures, whether it is around data mapping, those are the pains we are removing from the ecosystem for our clients. So it accelerates the journey for them, it reduces the risk, and also brings time to market to the .

Dave Vellante

>> Yeah. So you've got the framework, you have the experience, you know financial services in and out. Like you said, you de-risk that for clients.

Bibhu Patnaik

>> Yeah. And I would also say that more and more when we talk to the executives, they want to see value soon. Gone are the days where two years of data modernization program and they see value post that. They need to see the value soon, and the investment that they're making, how it is giving them the returns. Data service actually is very helpful in that, because we can accelerate entire snowflake ecosystem in a very fast manner, so that they can see the value soon. And that's where we have seen successes with our clients as well.

Rebecca Knight

>> So in this push, as you said, they want to see value yesterday. How is this affecting their mindset? Especially as I'm thinking about how clients are rethinking their data strategies as these cloud capabilities are evolving. Do you see changes in how they approach the work, and their mindset going into it?

Bibhu Patnaik

>> Yeah. I would say, there are certain driving factors that will move them towards a modernization journey, specifically cloud. Like Shailender mentioned, either it is a defensive agenda of regulatory oversight, risk reduction, et cetera, or an offensive agenda where they want to move more towards customer profitability, marketing, et cetera. Both of those areas, the scalability of the platform, the speed to market of the platform, and the analytics that can be generated to achieve these two areas, the executives have started seeing that. And that is what is driving that mindset of adopting cloud. Earlier there was a little bit of resistance, you know, "Hey, shall we do it? Shall we do it now?" But these are the two driving forces, if you will, that is helping them move their mindset towards adopting Snowflake as well.

Shailender Sidhu

>> And I think the next-gen technology, the executives are more encouraged, that with these next-gen technologies, more can be achieved with the foundational stuff, with the components that Snowflake and other hyperscalers offer. And I think that's kind of driving the mindset shift that, "Okay, you know what? We can then get something early." I'll give you an example. Model risk management in banks is a 9 to 12 month kind of journey. And now there are banks who are accelerating that process because of this next-gen technologies, because of good quality data or data infrastructure which is available for them. And also the governance aspect of it. Data governance is better enabled through some of this technologies which Snowflake and other vendors provide.

Dave Vellante

>> I mean, banks are like pro-athletes. They're like hyper competitive. And if you could double your revenue per employee with a capital allocation, they're going to do that. Because like we said before, they have the capital. So I'm curious as to how you're enabling that. In other words, the agentic piece that you just talked about, there's some prerequisites, and there's a lot of agent washing going on. So, one of the prerequisites, you got to have governance, you got to have trusted data, all that stuff. But you also have to have that data harmonized. If humans have to do that harmonization, that slows the whole cycle down. So technology presumably can help do that. What I mean is, so that revenue is revenue, it's not bookings, it's not ARR, it's not quarterly revenue, it's fiscal year, whatever, you're not arguing about that. So where are the banks in the financial institutions on that journey of creating that harmonization capability? And I'm curious to what you think where Snowflake is on that journey? Because they're evolving from data warehouse to values moving up the stack. Hopefully that makes sense.

Shailender Sidhu

>> No, it makes sense. Two years back, my answer would have been very different. I think the technology, the investments, the innovation that has happened, both from product companies and from within the bank to accelerate some of this. And this is either driven through the defensive posture, which is regulators, the risk organization within the bank, they are driving some of the change. Or to your point about offensive agenda, which is, I have to be competitive in the market. I have to be differentiated in the market, that is driving the change. So from my vantage point, we feel pretty optimist that now is a time for data AI agentic. The acceleration that we are seeing in the marketplace is immense. Almost every client of ours is investing heavily towards the data AI and agentic side. And yeah, I think things have changed. The tailwind is behind this paradigm and this innovative thinking.

Bibhu Patnaik

>> And I would say that the pace at which innovation is happening, I think adoption or at least the mindset of adoption is kind of catching on as well. Good example is, one of my client is looking at all the back office operations that they have been doing all these years. The amount of money that they spent on those manual processes, they're really thinking to just reimagine that through agents. Like earlier, those kind of discussions was not even happening. Now with the innovation and the technology, which is there right now with Snowflake, Cortex, AI, et cetera, they're really thinking about that foundation setup on data, so that it's good quality data that you can tap into. But then also re-imagining business processes through agents is what we are seeing in the market.

Dave Vellante

>> Well, it wasn't even possible years ago. I mean, you do some RPA. And I'm sure many of them have. Well actually, what's happening with the RPA? Are they using that as plumbing and the agents are talking to the bots?

Bibhu Patnaik

>> That is correct. So, there are many patterns that we see. Some clients who have not even adopted RPA, they have been still very much behind the curve. Now they are leapfrogging, they are moving outside of their comfort zone and talking about agents. And then there are people who have gone to RPA and then IPA, which is the Intelligent Process Automation. And now they are using that as a platform to then identify the solutions. Again, it has been so new in the last six months that there's an old traction. We have been, by the way, as a firm investing in agents, and thinking about a multi-agent system, et cetera, for more than a year. And that's where-

Rebecca Knight

>> So how is that working in the sense of, you're helping your clients re-imagine these business processes while you are also doing that too? Is that giving you ideas about, "Here's how we can be creative and innovative here"?

Bibhu Patnaik

>> Yeah. So, two ways that we have at least tried out. And I'd love Shailender to chime in as well. Understanding the client and client processes, we have done that very well over the years. Now we are translating that expertise into how to do that efficiently through agents. That's one. Second, there are many things that we do for ourselves. So we creating agents for Deloitte, for Deloitte. So using that experience and taking that to our clients is another kind of success that we have seen as well. So investing in that pretty early, obviously technologies like Snowflake really supercharges that. But the thinking around re-imagining business process, breaking it down to the right agents, et cetera, has been something that we have seen a lot of success in as well.

Shailender Sidhu

>> And you had asked a question earlier that the product vendors provide a solution, the clients have a need. Where does NSI or Deloitte play a role? And I think that's where we play the role, is the industry expertise, the ability to creatively think about this re-imagined way of running your processes, your analytics, your AI agenda. And we as a firm are investing heavily into some of this future thinking, whether it's through our product, whether it's through our solution prints. So we are bringing that acceleration to our clients, and to our product vendor partners, so that the value is kind of realized across the entire ecosystem, across the entire continuum within this.

Dave Vellante

>> So, our North Star vision is that, people want a digital representation of their business. And so that systems of agency can do much more than you can with your current labor force. And to do that, we envision this kind of real-time operation. And we think that there needs to be this 4D map of the business, where you've got people, places and things and processes, something that you just mentioned. And that 4D map doesn't really exist in a lot of businesses today. And I know we're talking, it'll take the better part of a decade we understand to evolve. But it starts with, what's happening today with these systems of agency? And then you're getting more and more data, and you're harmonizing that data, you're integrating the processes that are trapped inside of applications and so forth. So does that North Star make sense to you guys? Is that type of journey that you see your customers on in Deloitte itself?

Shailender Sidhu

>> Yeah. Yeah. I think absolutely it makes sense to us. And the common factor, or the lowest common denominator in all of this is data. Because data is what stitches your processes, your systems, your people, your technology together. And I think we believe that to my point earlier about agents. End of the day, agents are nothing but a way to drive insights from the data. That's what they are sitting on, they are based on the context, based on the data sets, they're driving those insights which can inform a certain process or a decision in the process. So yeah, I think we feel that way. We see it that way. And I think we feel that data, and highly governed and quality data is going to drive some of that change.

Dave Vellante

>> But a blocker is that the data, oftentimes the data, the metadata, the business process logic, is locked inside of applications which creates these silos. You have Celonis suing SAP, because they can't get access to the data. So it's really unclear how that's all going to play out. Are we going to have stovepipe systems of agency, or are we actually going to break down those barriers?

Bibhu Patnaik

>> Yeah. So, I'll break it down into two components that I see. One, as you said, harvesting the data from all of these applications and having a single foundation of data which is with the right metadata or with right glossary, definitions, et cetera. Understanding of data is very critical, and that becomes the foundation. And with good quality, by the way. And then on the second side, looking at every single business process. Whether it is an origination, whether it is a servicing, whether it is onboarding, how to break it down into components, which can be agentified if you will. And then marrying that together, is how I see clients being successful. So those will be two areas that I would focus on as well.

Shailender Sidhu

>> And in multi-agent systems, end of the day, it's also those connectors. You mentioned Google Next earlier. But the whole concept behind that is that you have a multi-agent ecosystem, which you have connectors to let's say, ASIPI or an Oracle, where ServiceNow, which play a different role in the end-to-end process. So how do you now start uncovering those data silos, and start putting in access, or enabling access to that, to these connectors or the agents sitting on top of those connectors?

Dave Vellante

>> I like to think of them, I mean, there's the technology vendor side of me that says, whoever owns those, that harmonization layer and the agenda control framework, they're going to make a lot of money. Others will do just fine too. But even more importantly, the customers like Deloitte and your customers who can figure that out first are going to do really, really well. We wrote a piece, we were talking about why Jamie Dimon is Sam Altman's biggest competitor, because his two exabytes of data are never going to get into the internet and trained by LLMs. And that data is so much more valuable. I don't know. Mark Benioff said it's a $14 trillion TAM. I can't even get that around my head.

Rebecca Knight

>> And Jamie Dimon's not going anywhere. He just said he's not retiring.

Shailender Sidhu

>> He's not retiring. Absolutely. I think the amount of momentum, especially around this new paradigm, agents and data over the last three quarters is a markable shift. We have banks who are original banks, who haven't invested in a lot of technology innovations, and this is a discussion topic there as well. So, it's an opportunity for them to be earlier leapfrog some of the innovation they did not do, for example, towards a better way of, more optimized way of running their business.

Rebecca Knight

>> Excellent. A terrific note to end on. Shailender, Bibhu, thank you both so much for coming on theCUBE,-

Shailender Sidhu

>> Thank you so much for having us....

Rebecca Knight

>> a great conversation.

Shailender Sidhu

>> Thank you.

Bibhu Patnaik

>> Thank you very much, yeah, thanks a lot.

Rebecca Knight

>> I'm Rebecca Knight, for Dave Vellante. Stay tuned for more of theCUBE's live coverage of Snowflake Summit. You're watching theCUBE, the leader in enterprise tech news and analysis.