>> live from New York. It's the Q covering AWS Global Summit 2019 brought to you by Amazon Web service, is >> welcome back here in New York City on stew Minimum. My co host is Corey Quinn. In the keynote this morning, Warner Vogel's made some new announcements what they're doing and also brought out a couple of customers who are local and really thrilled and excited to have on the program the C i O and E V P from Finn Ra here in New York City. Steve Randall, thanks so much for joining us. You're welcome. Thank you. All right, so, you know, quite impressive. You know when when I say one of those misunderstood words out there to talk about scale and you talk about speed and you know, you were you know, I'm taking so many notes in your keynote this 1 500,000 compute note. Seven terabytes worth of new data daily with half a trillion validation checks per day, some pretty impressive scale, and therefore, you know, it's I t is not the organ that kind of sits in the basement, and the business doesn't think about it business and I t need to be in lobster. So, you know, I think most people are familiar with in Rome. But maybe give us the kind of bumper sticker as Thio What dinner is today and you know, the >> the organization. Yeah, I started it Fender and 2013. I thought I was gonna come into a typical regulator, which is, as you alluded to technologies, kind of in the basement. Not very important, not strategic. And I realized very quickly two things. Number one, The team was absolutely talented. A lot of the people that we've got on her team came from start ups and other technology companies. Atypical financial service is and the second thing is we had a major big data challenge on our hands. And so the decision to go to the cloud S I started in March 2013. By July of that year, I was already having dialogue with our board of directors about having to go to the cloud in orderto handle the data. >> Yeah, so you know, big data was supposed to be that bit flip that turned that. Oh, my God. I have so much data to Oh, yea, I can monetize and do things with their data. So give us a little bit of that, That data journey And what? That that you talk about the flywheel? The fact that you've got inside Finneran. >> Yeah. So we knew that we needed the way were running at that time on data warehouse appliances from E, M. C. And IBM. And which a data warehouse appliance. You go back 10 15 years. That was where big data was running. But those machines are vertically scalable, and when you hit the top of the scale, then you've got to buy another bigger one, which might not be available. So public cloud computing is all about horizontal scale at commodity prices to things that those those data data warehouse appliance didn't have. They were vertical and proprietary, inexpensive. And so the key thing was to come up to select the cloud vendor between Google, IBM, You know, the usual suspects and architect our applications properly so that we wouldn't be overly vendor dependent on the cloud provider and locked in if you will, and that we could have flexibility to use commodity software. So we standardized in conjunction with our move to the public cloud on open source software, which we continue today. So no proprietary software for the most part running in the cloud. And we were just very smart about architect ing our systems at that point in time to make sure that those opportunities prevailed. And the other thing I would say, this kind of the secret of our success Is it because we were such early adopters we were in the financial service industry and a regulator toe boots that we had engineering access to the cloud providers and the big, big date open source software vendors. So we actually had the engineers from eight of us and other firms coming in to help us learn how to do it, to do it right. And that's been part of our culture ever since. >> One thing that was, I guess a very welcome surprise is normally these keynotes tend to fall into almost reductive tropes where first, we're gonna have some Twitter for pet style start up talking about all the higher level stuff they're doing, and then we're gonna have a large, more serious company. Come in and talk about how we moved of'em from our data center into the cloud gay Everyone clap instead, there was it was very clear. You're using higher level, much higher level service is on top of the cloud provider. It's not just running the M somewhere else in the same way you would on premise. Was that a transitional step that you went through or did you effectively when you went all in, start leveraging those higher service is >> okay. It's a great question. And ah, differentiator for us versus a lot. A lot of the large organizations with a legacy footprint that would not be practical to rewrite. We had outsourced I t entirely in the nineties E T s and it was brought back in source in in house early in this decade. And so we had kind of a fresh, fresh environment. Fresh people, no legacy, really other than the data warehouse appliances. So we had a spring a springboard to rewrite our abs in an agile way to be fully cloud enabled. So we work with eight of us. We work with Cloudera. We work with port works with all the key vendors at that time and space to figure out how to write Ah wraps so they could take most advantage of what the cloud was offering at that time. And that continues to prevail today. >> That that's a great point because, you know so often it's that journey to cloud. But it's that application modernization, that journey. Right. So bring us in little inside there is. You know how it is. You know, what expertise did Finn Ra have there? I mean, you don't want to be building applications. It is the open stuff source. The things wasn't mature enough. How much did they have toe help work, you know, Would you call it? You know, collaboration? >> Yeah. The first year was hard because I would have, you know, every high performance database vendor, and I see a number of them here today. I'm sure they're paddling their AWS version now, but they had a a private, proprietary database version. They're saying if you want to handle the volumes that you're seeing and predicting you really need a proprietary, they wouldn't call it proprietary. But it was essentially ah, very unique solution point solution that would cause vendor dependency. And so and then and then my architects internally, we're saying, No way, Wanna go open source because that's where the innovation and evolution is gonna be fastest. And we're not gonna have vendor Lock in that decision that that took about a year to solidify. But once we went that way, we never looked back. So from that standpoint, that was a good bad, and it made sense. The other element of your question is, how How much of this did we do on our own, rely on vendors again? The kind of dirty little secret of our beginnings here is that we ll average the engineer, you know, So typically a firm would get the sales staff, right. We got the engineers we insisted on in orderto have them teach our engineers how to do these re architectures to do it right. Um and we use that because we're in the financial service industry as a regulator, right? So they viewed us as a reference herbal account that would be very valuable in their portfolio. So in many regards, that was way scratch each other's back. But ultimately, the point isn't that their engineers trained our engineers who trained other engineers. And so when I when I did the, uh um keynote at the reinvented 2016 sixteen one of my pillars of our success was way didn't rely overly on vendors. In the end, we trained 2016 1 5 to 600 of our own staff on how to do cloud architectures correctly. >> I think at this point it's very clear that you're something of an extreme outlier in that you integrate by the nature of what you do with very large financial institutions. And these historically have not been firms that have embraced the cloud with speed and enthusiasm that Fenner has. Have you found yourself as you're going in this all in on the cloud approach that you're having trouble getting some of those other larger financial firms to meet you there, or is that not really been a concern based upon fenders position with an ecosystem? >> Um, I would say that five years ago, very rare, I would say, You know, we've had a I made a conscious effort to be very loud in the process of conferences about our journey because it has helped us track talent. People are coming to work for us as a senior financial service. The regulator that wouldn't have considered it five years ago, and they're doing it because they want to be part of this experience that we're having, but it's a byproduct of being loud, and the press means that a lot of firms are saying, Well, look what Fender is doing in the cloud Let's go talk to them So we've had probably at this 50.200 firms that have come defender toe learn from our experience. We've got this two hour presentation that kind of goes through all the aspects of how to do it right, what, what to avoid, etcetera, etcetera. And, um, you know, I would say now the company's air coming into us almost universally believe it's the right direction. They're having trouble, whether it's political issues, technology dat, you name it for making the mo mentum that we've made. But unlike 45 years ago, all of them recognize that it's it's the direction to go. That's almost undisputed at this point. And you're opening comment. Yeah, we're very much an outlier. We've moved 97 plus percent of our APS 99 plus percent of our data. We are I mean, the only thing that hasn't really been moved to the cloud at this point our conscious decisions, because those applications that are gonna die on the vine in the data center or they don't make sense to move to the cloud for whatever reason. >> Okay, You've got almost all your data in the cloud and you're using open source technology. Is Cory said if I was listening to a traditional financial service company, you know, they're telling me all the reasons that for governance and compliance that they're not going to do it. So you know, why do you feel safe putting your your data in the cloud? >> Uh, well, we've looked at it. So, um, I spent my first year of Finn run 2013 early, 2014 but mostly 2013. Convincing our board of directors that moving our most critical applications to the public cloud was going to be no worse from the information security standpoint than what we're doing in our private data centers. That presentation ultimately made it to other regulators, major firms on the street industry, lobbyist groups like sifma nephi. AP got a lot of air time, and it basically made the point using logic and reasoning, that going to the cloud and doing it right not doing it wrong, but doing it right is at least is secure from a physical logical standpoint is what we were previously doing. And then we went down that route. I got the board approval in 2015. We started looking at it and realizing, Wait a minute, what we're doing here encrypting everything, using micro segmentation, we would never. And I aren't doing this in our private data center. It's more secure. And at that point in time, a lot of the analysts in our industry, like Gardner Forrester, started coming out with papers that basically said, Hey, wait a minute, this perception the cloud is not as safe is on Prem. That's wrong. And now we look at it like I can't imagine doing what we're doing now in a private data center. There's no scale. It's not a secure, etcetera, etcetera. >> And to some extent, when you're dealing with banks and start a perspective now and they say, Oh, we don't necessarily trust the cloud. Well, that's interesting. Your regulator does. In other cases, some tax authorities do. You provided tremendous value just by being as public as you have been that really starts taking the wind out of the sails of the old fear uncertainty and doubt. Arguments around cloud. >> Yeah, I mean, doubts around. It's not secure. I don't have control over it. If you do it right, those are those are manageable risks, I would argue. In some cases, you've got more risk not doing it. But I will caution everything needs to be on the condition that you've got to do it right. Sloppy migration in the cloud could make you less secure. So there there are principles that need to be followed as part of >> this. So Steve doing it right. You haven't been sitting still. One of the things that really caught my attention in the keynote was you said the last four years you've done three re architectures and what I want. Understand? You said each time you got a better price performance, you know, you do think so. How do you make sure you do it right? Yet have flexibility both in an architect standpoint, and, you know, don't you have to do a three year reserves intense for some of these? How do you make sure you have the flexibility to be able to take advantage of you? Said the innovation in automation. >> Yeah. Keep moving forward with. That's Ah, that's a deep technical question. So I'm gonna answer it simply and say that we've architected the software and hardware stack such. There's not a lot of co dependency between them, and that's natural. I t. One on one principle, but it's easier to do in the cloud, particularly within AWS, who kind of covers the whole stacks. You're not going to different vendors that aren't integrated. That helps a lot. But you also have architect it, right? And then once you do that and then you automate your software development life cycle process, it makes switching out anyone component of that stack pretty easy to do and highly automated, in some cases completely automated. And so when new service is our new versions of products, new classes of machines become available. We just slip him in, and the term I use this morning mark to market with Moore's Law. That's what we aspire to do to have the highest levels of price performance achievable at the time that it's made available. That wasn't possible previously because you would go by ah hardware kit and then you'd appreciate it for five years on your books at the end of those five years, it would get kind of have scale and reliability problems. And then you go spend tens of millions of dollars on a new kit and the whole cycle would start over again. That's not the case here. >> Machine learning something you've been dipping into. Tell us the impact, what that has and what you see. Going forward. >> It's early, but we're big believers in machine learning. And there's a lot of applications for at Venera in our various investigatory and regulatory functions. Um, again, it's early, but I'm a big believer that the that the computer stored scale, commodity costs in the public cloud could be tapped into and lever it to make Aye aye and machine learning. Achieve what everybody has been talking about it, hoping to achieve the last several decades. We're using it specifically right now in our surveillance is for market manipulation and fraud. So fraudsters coming in and manipulating prices in the stock market to take advantage of trading early days but very promising in terms of what it's delivered so far. >> Steve want to give you the final word. You know, your thank you. First of all for being vocal on this. It sounds like there's a lot of ways for people to understand and see. You know what Fenner has done and really be a you know, an early indicator. So, you know, give us a little bit. Look forward, you know what more? Where's Finn Ra going next on their journey. And what do you want to see more from, You know, Amazon and the ecosystem around them to make your life in life, your peers better. >> Yes. So some of the kind of challenges that Amazon is working with us and partnering Assan is getting Ah Maur, automated into regional fell over our our industries a little bit queasy about having everything run with a relatively tight proximity in the East Coast region. And while we replicate our data to the to the other East region, we think AIM or co production environment, like we have across the availability zones within the East, would be looked upon with Maur advocacy of that architecture. From a regulatory standpoint, that would be one another. One would be, um, one of the big objections to moving to a public cloud vendor like Amazon is the vendor dependency and so making sure that we're not overly technically dependent on them is something that I think is a shared responsibility. The view that you could go and run a single application across multiple cloud vendors. I don't think anybody has been able to successfully do that because of the differences between providers. You could run one application in one vendor and another application in another vendor. That's fine, but that doesn't really achieve the vendor dependency question and then going forward for Finn or I mean, riel beauty is if you architected your applications right without really doing any work at all, you're going to continuously get the benefits of price performance as they go forward. You're not kind of locked into a status quo, So even without doing much of any new work on our applications, we're gonna continue to get the benefits. That's probably outside of the elastic, massive scale that we take advantage of. That's probably the biggest benefit of this whole journey. >> Well, Steve Randall really appreciate >> it. >> Thank you so much for sharing the journey of All right for Cory cleanups to minimum back with lots more here from eight Summit in New York City. Thanks for watching the cue

>> live from Washington D. C. It's the Cube covering a ws public sector summit by Amazon Web services. >> Hello, everyone. Welcome back to the cubes Live coverage of a ws Public Sector summit here in our nation's capital. I'm your host, Rebecca Knight. We're joined by Raghu Rahman. He is the director of Fin Row, the Financial Industry Regulatory Authority. Thank you so much for coming on the Cube >> fighter back. Good afternoon, but happy to be here. >> So we're angry. This is the 10th annual public sector. Somebody should have said so Tell us a little bit about Finn Ra and what you do. They're >> sure Fender itself is the financial industry Regulatory authority way our private sector, not for profit institutions. Our mission is investor protection on market integrity. Way our member funded on DH. We have a member driven board board of directors and we engage in ensuring that all the stock market operations in the U. S. Capital markets play with rules. So that's the essence of who we are. >> And all of those stakeholders have a vested interest in making sure their rivals are also playing bythe. So you're here giving a presentation on fraud detection, using machine learning and artificial intelligence. That's right. What was So what were you saying? >> So, Brenda, we have a very deliberate technology strategy on We constantly keep pace with technology in order to affect our business in the best possible way, way. Always are looking for a means to get more efficient and more effective and use our funding for the best possible business value so to that, and wear completely in the cloud for a lot off our market regulation operations. All the applications are in the clouds. We, in fact, we were one of the early adopters of the cloud. From that perspective, all of our big data operations were fully operational in the cloud by 2016 itself. That was itself a two year project that we started in 40 14 then from 2016 were being working with machine language on recently. Over the past six months or so, we've been working with neural networks. So this was an opportunity for us to share what? Where we have bean, where we're coming from, where we're going with the intent that whatever we do by way of principles can be adopted by any other enterprise. We're looking to share our journey on to encourage others to adopt technology. That's really what why we do this >> and I want to dig into the presentation a little bit. But can you just set the scene for our viewers about what kinds of how big a problem fraud is with these financial institutions and how much money is on the table here? >> Well, I don't want to get you to the actual dollar figures, because each dimension off it comes up with a different aspect to it. Waken say that in full in federal, we have a full caseload year after year, decade after decade that end up with multiple millions of dollars worth of fines just on the civil cases alone. And then there are, of course, multibillion dollar worth problems that we read in the media cases going as far back as Bernie Madoff. Case is going through the different banking systems so that our various kinds of fraud across the different financial sectors, of course, we're focused on the capital markets alone. We don't do anything with regard to banking or things of that nature, But even in our own case, we franchise composed of nearly 33 100 people on all of us, engaging the fulltime task of ensuring that markets are fair for the investors on for the other participants, it's a big deal. >> So in your in your presentation, you told the story of two of your colleagues who are facing different kinds of challenges to sort to make your story come alive. Tell our viewers a little bit about about their challenges. >> We spoke about Brad, who is an expert. He's an absolute wizard when it comes to market regulation, and he's being doing this for a long time on DH What I shared with the members of the audience earlier today. Wass He can probably look ATT market, even data on probably tell you what the broker had for breakfast. >> That >> scary good on. We also shared the story about Jamie, who is in the member supervision division offender, a wicked, smart and extensive experience. So these are the kind of dedicated people that we have a fender on guy took up to Rhea life use cases sort of questions that they face. So in the case of Brad, it is always a question of Hey, we're good. But how do we get better? What is the unknown unknown there? The volume of transactions in the market keeps going up. How do we then end up with a situation where we can do effective surveillance in the market on detect the behaviors that are not off interest that are not for doctor? That might be even. Don't write manipulated. How do we make sure that way? Got it all, so to speak? That's Brad's thing. >> That idea about these? No, these unknown nun note Because we know we have no no known unknowns with the unknown unknowns are even scarier. >> Exactly. They are, and we want to shed light on that for ourselves and make sure that the markets are really fair for everybody to operate him. That is where use of the latest technologies helps us get better and better at it. To reduce the number of unknown unknowns to shed light on the entirety of market activities on toe, perform effective surveillance. So that was a just off our conversation today. How we have gotten better in the past 45 years, how machine language machine learning based technologies have helped us how artificial intelligence that we started working with specifically, neural networks have started helping us even further. >> Okay, okay. And then Jamie had a problem, too. >> In Jimmy's case. Member supervision, if you will. The problem is off a different context and character. They're still volumes of data. We still receive more than 1,000,000 individual pieces of document every year that we work with. But in her case, the important aspect of it is that it is unstructured data. It makes sense to humans. It is in plain English, but the machines, it's really difficult. So over the past two years, way have created an entirely new text analytics platform on that helps us parts through hundreds of thousands of different documents. Those could come from e mails it to come from war documents, spreadsheets, evenhanded and documents. We can go through all of those extract meaningful information, automatically summarized them, even have measures off confidence that the machine will imprint upon it to say how confident I am. I that this is off relevance to you. It will imprint that. And then it represented Jamie for her toe. Use her judgment and expertise to make a final call. One thing that we are really conscious about is way. Don't let algorithms completely take everything through. We always have a human. So we think of a I as really assistive intelligence on. We bring that to a fact for our business, >> and I think that that's a really key there, too, for the for the employees is to know that this is this is this's taking away some of their more manual, more boring tests and actually freeing them up to do the more creative, analytical problem solving >> you hit you. I think you hit that nail right on the head. All the tedious work the machine bus on. Then it leaves humans to do like you said, Absolutely the creative, the inter toe on the final judgment call. I think that's a great system. >> How much to these solutions cost way >> generally are not pricing these things individually, however overall, one of the things that we did with the cloud was actually reduce our overall cost ofthe technology. So from that perspective, we don't look at Costas, the primary driver, although many times these things do end up costing less than the prior system that we would be in. However, the benefits that offer to our clientele, the benefit that it offers to our business, to the people that are investors in the stock market, that is tremendous, and that has a lot of value for us. >> So what is next for Finneran? I mean, this is This is a really moment for so many industries in terms of the the rise of cyber threats, the end and fraud being such a huge problem. Privacy thes air the financial services industry more than, I guess maybe is equal to healthcare. This's really sensitive stuff we're talking about here. What what are some of the things that you have on the horizon? What are some of the things that you're hearing from your members? >> So all of our members treat data security really, really special on really carefully on wear, very deliberate and very conscious about how we treat the data that is interested to us way have to obligations. One is to treat it securely. The other is to extract appropriate insights from it because that's the purpose of why we're being interested with the data. Wait, take both of those dimensions very seriously. Way have an entire infrastructure organization. It's composed off experts in the field way, headed by a chief information security officer with a large team that looks at multi layered security right from the application defending itself all the way to perimeter security. We go off that we have extensive identity and access management systems. We also have an extensive program to combat insider tracks. So this type of multi layer security is what helps us keep the data secure. >> And >> every day we do notice that there are additional track factors that get exposed. So we keep ourselves on the edge in terms ofthe working with all the vendors that we partner with in working with the latest technologies to protect our data as an example, all of our data in the cloud is completely encrypted with high encryption, and it is encrypted both at rest. I'm during flight so that even in the rare case that someone has access to something is gibberish. So that's the intent of the encryption himself. So that is the extent to which we take things very seriously. >> I want to ask you to, but the technology backlash that we're seeing so much and you're you live here so you really know about the climate that does that technology industries, air facing for so long. They were our national treasure and they still are considered it all in a lot of ways. The Amazons, the Googles, the facebooks of the world. But now we have a presidential candidates calling for the break up of big tech and and they And there's been a real souring on the part of the public of concerns about privacy. How What are your thoughts? What are you seeing? What are you hearing on the ground here in D. C? >> With specifically with regard to where we operate from Infanta? We've tried not to access or use any data. That is not for regulatory purpose. Wear Very careful about it. Way don't sprawl across and crawl across social media just on a general fishing expedition. We try not to do that. All of the data that we take in store on operate technology upon we are entitled to use it for by policy are my rules are my regulation for the specific purpose off our regulator activities. We take that very seriously. We try not to access data outside off what we have need for on. So we limit ourselves to the context and that, if you look at, is really what the public is trying to tell us, don't take our data and use it in ways that we did not really authorize you to do. So So the other thing is that franchise on our profit, not for not for profit institutions. We really have absolutely no interest beyond regulatory capability to use the data. We absolutely shut it down for any other use way are not so that way. We are very clear about what our mission is. Where we use our data, why we use it and stop. >> Great. Well, Raghu, thank you so much for coming on the Cube. It's been a pleasure talking to you. >> Thank you. Thank >> you. I'm Rebecca Knight. Please stay tuned for more of the cubes. Live coverage of the es W s public Sector summit here in Washington. D c. Stay tuned. >> Oh,