>>live from Las Vegas. It's the Q covering AWS executive. Something brought to you by extension. >>Welcome back, everyone to the cubes. Live coverage of the ex Censure Executive Summit here at AWS. Reinvent I'm your host, Rebecca Knight. We have two guests for this segment. We have Satya Adric, Carl Adder Gala. Sorry, He is the VP single family technology at Fannie Mae. Thanks so much for coming on the show. Satya >>glad to be here. >>And we have Dave Baldwin, VP Architecture, Cloud Engineering at Fannie Mae. Thank you so much for coming on the show D thanks >>for having us. >>So we're talking today about transforming the mortgage industry through through the cloud. Fannie Mae is obviously a foundational part of the US home mortgage industry, and it's been around for a long time. But at a time right now, where there is just so much tremendous change going on in the industry, particularly with the emergence of fintech and other push button mortgage providers, talk a little bit about the last 3 to 5 years. In terms of the changes, you've seen two to the business. You want to start? >>Yeah, I will. So So when we look at the industry changes. What Fannie Mae does is mostly in the secondary market, so our core business hasn't changed from the point of taking the lone synchronizing and selling. However, in the mortgage industry, when we talk about the bar or experience and then the lenders how they have improved the experience across the board, I think is it has been a huge shift right three years ago. The discussion has bean always about Hey, can we do more reliably? Can we do more faster? Right? Those were the conversations, but now the expectations off our lenders and bottles have significantly increased. Right now, they're talking about user experience. How can we meet our bar or where they are, Right. So the lenders have got a lot of expectations on us in terms of how do you feel? Feel that that is the first biggest change in the realm off several of these, right? The 2nd 1 ese, the data has become the currency now, right? It has significantly improved our posture around finding about, um, their assets that income, their employment. Right. So you guys may have seen a lot off David surgeon. It is a product that we have launched in that well, so data revolution has been a big change. And then how we're utilizing that to serve Margaret's industry, our lenders and borrowers, thereby we also reduce the risk within the industry. Right? So those two have bean huge changes. Then there is a technology revolution in terms off AP eyes, Microsurgery says. How do I plug and play? How do we reduce my cost when I'm locking a bottle or two alone? Right. And these are the things that are lenders have bean pushing us on right? Reduced the cycle from somebody coming to the application to taking a loan, closing alone and delivering to Fannie Mae. Shrink the timeline and in doing it, reduce our costs. Right? So these are being like more and more expectations Have bean really set from the border for a few from the lender point of view on Fanny me and all our innovation. Our transformation is all about meeting them and also setting standard for them. What is great in this industry and that's that's what has been going on in the last 3 to 5 years. >>Yes, and that you just laid out a tremendous number of trends and all this disruptive change when you were trying to meet these new expectations from your lenders and your borrowers. Dave. What? What are the in making this journey to, from to to say, I'm sorry from to the Cloud, How are you thinking about these challenges ahead at a time where the user experience is so important? Data is currency and this technology revolution, >>well, it's a big change and, you know, and it's a change across people, process and technology. So if you think about it, what we've done is we've started to trade a new operating model, which really is a lot more engaging, and and it requires an uptick, a scale and really ah, a new way of working right. We've even gone as far as to introduce lean management in a tools and processes. But if you think about it, the people definitely have to change. If you think about it from a process point of view, you're you're really looking at reimagining the way some of the mortgage industry works right, because there's a lot of demand for it. At the end of the day, the customer expectations and especially If you go all the way to the borrower, the customer expectations is very different. You know, they're very they they don't understand unnecessarily why they would have to fill out all this paperwork, right? When don't you already have the information? And to sati is point about data. That's why it's so important to get that data together. Because if we can harness it right, then we can truly start to re imagine these processes and make it so much easier for a borrower nor a lender to work together and eventually work with us. So and then finally, you know, from a tech point of view with the introduction of the cloud, you know, that new foundational sort of technology that really gives you something to pivot off, you can really you can really start to take advantage of the micro service architectures and the new technical capabilities that can help make this really right. And so that's That's generally how we look at our digital transformation and and as you start to think about prioritization, how do I move those? How do I think about the applications that are going to change and how they're gonna neither either Transformer moved to the cloud. You really start to think of you know what business value and I'm trying to achieve 1st 2nd 3rd right? And then what applications won't make it, You know, they're gonna be completely redone. And what applications? Frankly, we're gonna have to move along with it to manage some of the dependencies we're going. >>So I think one more point I wanted and Rebecca is that when we look at this B to B businesses, they're very tightly integrated, right? Our companies have been integrated when we are extending out information explained, extending the responses in the past. Anybody talks about experience, right? It is about Hey, there will be there are technological glitches, but you don't want to impact big. That's used to be the norm. Not anymore. I think when we look at now one of the top customer slate, if you blink from the infrastructure layer point of view, there is business loss. People are not just looking for resiliency anymore. People are looking for fault tolerance, especially when it comes to the top to your customers. Right. So I think we can see the underpinning off cloud and also how we architect our applications to meet that kind of need. It's not just about being resilient anymore. Gotta be. You cannot lose a transaction. But I think those things have bean more and more that we're hearing from our customer base, and we feel like the cloud journey is going to be underpinning for these types of expectations from our customers. >>So how do you work with partners like Accenture in AWS? When you embark on this journey and think through the your business imperatives and think through your strategy, >>I think when when we think about our partnership's. First of all, there are a lot of partners that we have and that we've had for years, as we as we really not only do digital transformation, but you got to run the business, too, while you're doing this transformation. And so you know, when you think about it, the way the wake centers worked with us is you know they number one have helped us with a cloud strategy. So that's a very hard thing to Dio because you think about all the different personalities in your organization and all the people that you have to bring together. You know what Accenture helped us with. It is to really level, said everyone and get everybody on the same page in terms of, you know, where we want to go on how we wanna head on this journey. The second thing that they helped us with was really the program management. So that's a huge undertaking to write and given the fact that it's very different and these are new things that we're doing in our firm. It's good to have that external expertise that that sort of done it with other companies and they can bring that to bear with eight of us. You know, eight of us is is one of one of the major providers that we're using. Thio post a lot of our business applications, and if you think about that there, you know we're taking advantage of their technology. We're leveraging some of their pro serve professional service is thio, help us get it right and help us sort of not only with the implementation, but in some cases the governance and control frameworks that are highly regulated. Organization like ours needs So >>and I think if you think about this from the scale point of view, right? Everybody knows there is war for talent, right? We use our partners in terms of how can we scale these things that are new operating models? New technological? Because there is a change curl in bringing up the entire employees based without extent, These guys can be catalyst. In addition to that, they can be scaled provided us, right. I think that's how we can I use these, But it is action generator B s. >>This morning during Andy Jassy fireside chat, he talked a lot about the importance of innovation and experimentation and trying different things. How What's the experience of innovation at Fannie Mae? How do you innovate with partners or just thinking about all of the changed expectations? How do you make sure you are trying to solve the right problems? Describe your process creative process >>again, I think, um, when we I think about this innovation process and how we do water in Fannie Mae right three years ago, it is about Hey, how do we get our employee base to think about the possibilities right on Veran bunch of hackathons innovation days so that you get excitement from the teams, but in the last one and 1/2 year. It's more about innovation that can reap benefits, right? So we call it as focused innovation. We have, ah, clear cut Enterprise Innovation team. And they're on some of these innovation days and whatever have you within the within the firm so that you get the ideas and we have a process called pitch. So all these ideas feeding to lack of a better time a funnel where we have this enterprise innovation groups actually scan through the I. D. S and then can identify what things we can use and where we want to put our innovation investments. Right. So there is, ah, set off funnel requirements and gates we go through to identify Hey, this is where we want to do. And how we do is that Fanny Me is a lot more design thinking shop, right? So customer is at the center of everything. So anything we do, we will have some sort of research first, right with the customers and then how that might push the needle such that it can reach different boundaries through innovation. Right? So our processes cultivated ideas from inside. Also, look at what is happening with the trends. We have a strong strategy group. They're gonna look at this and our innovation team is always on the hunt for Hey, what is happening in industry in the cutting edge, How do you bring these three dimensions and then come up with a bunch of ideas? And then we have a funnel process where we identified what moves? What's this? What stays? Because there are other things that are at play. Is this innovation ready for the market? Now? Does it have to wait that sort of There are so many dimensions that going to that. But we have a structure process, and we have AH, dedicated team who can manage is that yet uses the creativity of the employees to be able to participate in animation. I mean, that's how we have a wall this process from. Think of the possibilities, too focused innovation. >>I think there's one extra point as well, like when it comes to technology side of that, it's it's creating a safe place for people to experiment, right, So we have a sandbox, the environment that we've created, an Amazon there in eight of us, and what we're doing is we're actually releasing some of the controls. I mean, obviously there's security and compliance, but released some of the controls and and just put a few guard rails in place so that people can experiment safely and not impact our firm, you know, in a very negative way. So >>talk about your employees and how they received this, this major transformation, and how are you receiving feedback in terms of their productivity in their engagement with the process? Dave. >>So you know, I would say this. There are lots of different types of employees, right? And like I said earlier, we also have as we're building the new, we also have to continue to support what we're running. So So what we've done is we've actually rolled out on South. We'll talk about it more detail because his team rolled it out. But, you know, but we have rolled out some training. You know, we've created a change management process, an organization right. Working with our human resource is so that we can up left, you know, sort of skills. And that's what I think. What's important is you're not going to be able to find the people out there to do everything that you need to do right. What's really important is creating those opportunities to carry the people that you have in your organization along with you for the journey as they learn you benefit right as an organization. So but salty should talk about some >>of the training. Yeah, so I take your question in two parts one. Is that how the employee base is taking the message of this district transformation or don't have right again? We have a compelling vision and mission like people that fanny man, they what? They take pride in fulfilling the mission. That's that's the 1st 1 along the way, when we crafted our message around why we're doing this. That is a lot more compelling. It is meaningful for our customers, our employees, right? So I think the messaging has been very important. Then, when you look at the things that we're trying to do, our cutting edge right from the employee point, if you it is a lot of excitement, because that keeps them at the cutting edge of what is happening in the world that makes them more marketable, right? Naturally, people are excited about it, but like any transformation, right? There will be camps off who will come across the change car up front like they're catalyst. Right? And then there are some in the middle and summer can a lagging right? But when we look at the entire gambit off the employee base, majority off them are. Hey, we are on board with this. We want to do it. We want to learn, How do we get there? And the company has done several different things to help the employees through this kind of knowledge cover I would call rather than the change career. We have a whole bunch of training plans that we have laid out. People have been wall until early taking. I mean, maybe a classroom training, maybe a self, sir. Uh, type off, download this particular module and then kind of read upon it and then also provide them to practice them with the sandbox. Right? So all these things have been done. I think one challenge we had actually facing now is that we can train them up pretty easily if we haven't put them in a place to practice it. Then it kind of fades away. So we're now kind of trying to see. Okay, let's identify groups off people. Give them a tool where they can assess for them their own self. What I wanted to learn such that I can become that and then be eligible for doing that right so that now they learn. And then they're put in a role on a project that they can actually practice on. So we are in that posture of that right now. So I think, but employee base is really excited about this, >>So I want to. I want to end where we started where Sati described the myriad changes that are taking place in your industry and getting back to your your cause, which is helping the customer buy a home, get it, get it, get it more easily, qualify for a loan. Can you think about the customer experience of the home buying process 3 to 5 10 years from now? And how it will be different as Fannie Mae embarks on this on this cloud journey. Do you want to start David? Just think. Look into your crystal ball >>and it's great. I wish I had a crystal ball. That would be great, but but you know. Look, we're making significant advancements, you know, working, working with our customers, taking that customer first mentality. And, ah, and and, you know, the mortgage industry itself is right for a change. I mean, you know, and and we're in a good position to really help and drive a lot of that. So my expectation, if I were to look out, I would expect to see a world where you know that borrower experience gets a lot better. I mean, one of the things we've learned to our research is that you know what is it? 40% of people actually cry as they're going through the mortgage experience, >>and they're not tears of joy. No, it's actually, you >>know, tougher to get into a tougher to think through the mortgage process, you know, and really take that big leap than it is to, you know, our Cielo tells us all the time than it is to actually apply for college. It z, it's often on bigger life event our goal. How do we make that simpler? How do we make people have a much more pleasant experience? Right? Waken do that with our data. We can make sure that they don't have to fill out those amazing forms. Heck, find the information. Sometimes they don't have it. You know, we're in a better position, right? You know, really? Get Teoh. You know, I can't promise a single click experience, but we're all gonna try to aspire to that, because that's what the customers out there with their cell phones and their technology or used to right. So we've got to get at least somewhere close to being there. >>So in the bottle, it expedient sight. I think we can even now see one tap market. How do we get them right? I think that's probably not too far. It's probably within two or three years. That's if I were to think about that. But if you want to think about 5 to 6 years, 10 years, if I am an individual driving by a home and then take your phone and say, Hey, can I buy this home? That should be able to tell you this is your lender and then go. That's right. And again from Fannie Mae, a point if you re help the lenders and they helped the borrowers threat. So through this transformation, what we're doing is that set up an engine that can be nimble, that can move fast. That runs with the low investment so that if we were to pivot, do things testing, learn and then change your game. We are fully in the position to be able to do that, right So and however fast, fast, you can experiment, those many different ideas will come out, and then some of them will reap fruit. And all of these for two things, like for our customers. How do we benefit our company, Fannie Mae? And how do we move the needle in industry? I think these are the three things that we want to achieve through this transformation. And we're building an engine to be able to do those types of things. I wish I could say this is one thing we would do. That's not what we're trying to do. Being a position where we can move quickly, we can lead industry. We can set the standard and then make good for the good for the American house. So that's all stories. >>Exciting times. Thank you so much. Both for coming on the Cube. Satti on Dave. Thank you. I'm Rebecca night. Stay tuned for more of the cubes. Live coverage of the Ex Censure Executive Summit coming up in just a little bit.

>> From the Corinium Chief Analytics Officer Conference Spring San Francisco, it's The Cube >> Hey welcome back, Jeff Frick with The Cube We're in downtown San Francisco at the Corinium Chief Analytics Officer Spring event. We go to Chief Data Officer, this is Chief Analytics Officer. There's so much activity around big data and analytics and this one is really focused on the practitioners. Relatively small event, and we're excited to have another practitioner here today and it's Kevin Bates. He's the VP of Enterprise Data Strategy Execution for Fannie Mae. Kevin, welcome. >> It's a mouthful. Thank you. >> You've got it all. You've got strategy, which is good, and then you've got execution. And you've been at a big Fannie Mae for 15 years according to your LinkedIn, so you've seen a lot of changes. Give us kind of your perspective as this train keeps rolling down the tracks. >> OK. Yeah, so it's been a wild ride I've been there, like you say, for 15 years. When I started off there I was writing code, working on their underwriting systems. And I've been in different divisions including the credit loss division, which had a pretty exciting couple of years back around 2008. >> More exciting than you care to - >> Well, there was certainly a lot going on. Data's been sort of a consistent theme throughout my career, so the data, Fannie Mae not unlike most companies, is really the blood that keeps the entire organism functioning. So over the past few years I've actually moved into the Enterprise Data Division of the company where I have responsibility for delivery, operations, platforms, the whole 9 yards. And that's really given me the unique view of what the company does. It's given me the opportunity to touch most of the different business areas and learn a lot about what we need to do better. >> So how is the perspective changed around the data? Before data was almost a liability because you had to store it, keep it, manage it, and take good care of it. Now it's a core asset and we see the valuations up and down. One on one probably the driver of some of the crazy valuations that you see in a lot of the companies. So how has that added to change and what have you done to take advantage of that shift in attitude? >> Sure, it's a great question. So I think the data has always been the life blood and key ingredient to success for the company, but the techniques of managing the data have changed for sure, and with that the culture has to change and how you think about the data has to change. If you go back 10 years ago all of our data was stored in our data center, which means that we had to pay for all of those servers, and every time data kept getting bigger we had to buy more servers and it almost became like a bad thing. >> That's what I said, almost like a liability >> That's right And as we've certainly started adopting the cloud and technologies associated with the cloud you may step into that thinking "OK, now I don't have to manage my own data center I'll let Amazon or whoever do it for me." But it's much more fundamental than that because as you start embracing the cloud and now storage is no longer a limitation and compute is no longer a limitation the numbers of tools that you use is no longer really a limitation. So as an organization you have to change your way of thinking from "I'm going to limit the number of business intelligence tools that my users can take advantage of" to "How can I support them to use whatever tools they want?" So the mentality around the data I think really goes to how can I make sure the right data is available at the right time with the right quality checks so that everybody can say "yep, I can hang my hat on that data" but then get out of the way and let them self serve from there. It's very challenging, there's a lot of new tools and technologies involved. >> And that's a huge piece of the old innovation game to have the right data for the right people with the right tools and let more people play with it. But you've got this other pesky thing like governance. You've got a lot of legal restrictions and regulations and compliances. So how do you fold that into opening up the goodies, if you will. >> So I think one effort we have is we're building a platform we call the Enterprise Data Infrastructure so for that 85 percent of data at Fannie Mae what we do is loans, we create securities from the loans. And there's liabilities. There's a pretty finite set of data areas that are pretty much consistent at Fannie Mae and everybody uses those data sets. So taking those and calling them enterprise data sets that will be centralized they will be presented to our customers in a uniform way with all of the data quality checks in place. That's the big effort. It means that you're standardizing your data. You're performing a consistent data quality approach on that data and then you're making it available through any number of consumption patterns so that can be applications needed, so I'm integrating applications. It could be warehousing analytics. But it's the same data and it comes from that promise that we've tagged it enterprise data and we've done that good stuff to make sure that it's good, that it's healthy. That we know where we stand so if it's not a good data set we know how to tag it and make it such. For all the other data around we have to let our business partners be accountable for how they're enriching that data and innovating and so forth. But governance is not a - I think in the past another part of your question, governance used to be more of a, slow everybody down but if we can incorporate governance and have implied governance in the platform and then allow the customers to self serve off of that platform, governance becomes really that universal good. That thing that allows you to be confident that you can take the data and innovate with that data. >> So I'm curious how much of the value add now comes from the not enterprise data. The outside the core which you've had forever. What's the increasing importance and overlay of that exterior data to your enterprise data to drive more value out of your enterprise data? >> So that enterprise data like I say may be the 85%, it's just the facts. These are the loans we brought in. Here's how we can aggregate risk or how we can aggregate what we call UPB, or the value of our loans. That is pretty generic and it's intended to be. The third party data sets that our business partners may bring in that they bump up against that data can give them strategic advantages. Also the data that those businesses generate our business lines generate within their local applications which we would not call enterprise data, that's very much their special sauce. That's something that the broader organization doesn't need. Those things are all really what our data scientists and our business people combine to create the value added reports that they use for decisioning and so forth. >> And then I'm curious how the big data and the analytics environment has changed from the old day where you had some PHds and some super bright guys that ran super hard algorithms and it was on Mahogany Row and you put in the request and maybe from down high someday you'll get your request versus really trying to enable a broader set of analysts to have access to that data with a much broader set of tools, enabling a bunch of tools versus picking the one or two winners that are very expensive, you got to limit the seats et cetera. How has that changed the culture of the company as well as the way that you are able to deliver products and deliver new applications if you will? >> So I think that's a work in progress. We still have all the PHds and they still really call the shots. They're the ones that get the call from the Executive Vice President and they want to see something today that tells them what decision they should make. We have to enable them. They were enabled in the past by having people basically hustle to get them what they need. The big change we're trying to make now is to present the data in a common platform where they really can take it and run with it so there is a change in how we're delivering our systems to make sure we have the lowest level of granularity. That we have real time data. there's no longer waiting. And the technology tools that have come out in the past 10 years have enabled that. It's not just about implementing that, making it available to all those Phds. There's another population of analysts that is now empowered where they were not before. The guys that suffered just using excel or access databases that were I would call them not the power users but the empowered analysts. The ones who know the data, know how to query data but they're not hard core quants and they're not developers. Those guys have access to a plethora of tools now that were never available before that allow them to wrangle data from 20 different data sets, align it, ask questions of it. And they're really focused on operations and running our systems in a smoother, lower cost way. So I think the granularity, the timing, and support for that explosion of tools we'll still have the big, heavy SAS and R users that are the quants. I think that's the combination everything has to be supported and we'll support it better with higher quality, with more recent data, but the culture change isn't going to happen even in a few years. It will be a longer term path for larger organizations to really see maybe possibilities where they can restructure themselves based on technology. Right now the technologies are early enough and young enough that I think they're going to wait and see. >> Obviously you have a ton of legacy systems, you have all these tools. You have that core set, your enterprise data that doesn't really change that much. What's the objective down the road? Are you looking to expand on that core set? Is it such a fixture that you can't do anything with it in terms of flexibility? Where do you go from here? if we were to sit down three years from now what are we going to be talking about? >> So two things. One, I hope I'll be looking back with excitement at my huge success at transforming those legacy systems. In particular we have what we call the legacy warehouses that have been around well over 20 years that are limited and have not been updated because we've been trying to retire them for many years. Folding all of that into my core enterprise data infrastructure that will be fully aligned on terminology, on near-real time, all those things. That will be a huge success, I'll be looking back and glowing about how we did that and how we've empowered the business with that core data set that is uniquely available on this platform. They don't need to go anywhere else to find it. The other thing I think we'll see is enabling analysts to utilize cloud-based assets and really be successful working both with our on-premises data center, our own data center-supported applications but also starting to move their heavy running quantitative modeling and all the sorts of things they do into the data lake which will be cloud based and really enabling that as a true kind of empowerment for them so they can use a different sent of tools. They can move all that heavy lifting and the servers they sometimes bring down right now move it into an environment where they can really manage their own performance. I think those are going to be the two big changes three years from now that will feel like we're in the next generation. >> All right. Kevin Bates, projecting the future so we look forward to that day. Thanks for taking a few minutes out of your day. >> Thank you. >> All right, thanks. He's Kevin, I'm Jeff. You're watching The Cube from the Corinium Chief Analytics Officer Event in San Francisco. Thanks for watching. (music)