Ray O'Brien is Chief Operation Officer at Quantexa. He is an international business leader, board member, independent director, and advisor with a unique mix of expertise in Data, Analytics, Technology, Risk and Finance. Ray chatted with us about what is behind what he calls the “third industrial revolution.” He delves into how machine learning has changed the capacity for projects to do things that historically many couldn’t afford before. Ray provides his thoughts on how data and analytics are growing every day and affecting relationships among businesses and consumers.
3 Takeaways:
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Key Quotes:
I really can't state [enough] how important it is to try and get a global view, to get out of your home country, and to work in different countries around the world to experience cultures and experience different peoples of different backgrounds, because it's so much value to you in your career to understand different viewpoints and not just be monoculture.
Some of my proudest moments [have been] watching people who I've managed, grow and become self-sufficient and basically overtake me, and become incredible valuable assets to whatever organization they're working for. I really do love watching people grow and become their best.
In very simple terms, if you imagine you're a water company in the UK. If you go bankrupt on a Friday, the water still flows on a Monday, because you're regulated to make sure that there is a company with enough capital in it to keep the water flowing and to make sure that that water has an operational process, no matter what happens to that company. The same will happen to cloud providers. They're becoming too critically important for national and countries. They will become utilitized and they will have to be regulated like a utility.
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Best Career Advice:
Get a global view outside of where you live. Gaining experiences from different people, cultures, and backgrounds can provide you a lot of value in your career. This will allow you to have a lot of different perspectives that can help you throughout business interactions.
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Bio:
Ray O'Brien
Chief Operation Officer at Quantexa
Ray is Chief Operation Officer at Quantexa. He is known to inspire business growth through innovative thinking, strategy and a global perspective. Ray is an international business leader, board member, independent director, and advisor with a unique mix of expertise in Data, Analytics, Technology, Risk and Finance. Ray is a proven influencer who makes an impactful difference operating with Boards and C-Level decision makers.
Ray graduated from University College Dublin in 1989 with a degree in mathematics and computer science. He joined Kleinwort Benson as an equities trading systems developer and in 1991 moved to Nomura, within futures and options trading. Two years later, he joined risk at Banque Paribas, before moving to the risk area at Deutsche Bank in 1997.
In 2001 Ray left Deutsche Bank to form a risk management consultancy based in London and Germany that included among its customers: Royal Bank of Scotland, Deutsche Bank, Merrill Lynch, Credit Suisse and HSBC.
In 2004 Ray joined HSBC as a member of the executive committee for HTS Global Banking & Markets (HTS GB&M). Ray has managed a number of business areas within HTS GB&M, including Global Transaction Banking, Global Banking, Operations, Risk and Finance software and change delivery. Ray moved to the Global Risk function in 2012 and became the Global Risk COO and Global Head of Risk Analytics. In June 2021 Ray left HSBC and started the life of a Pluralist.
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For more information:
LinkedIn: https://www.linkedin.com/in/ray-o-brien-a8079a1b8/?originalSubdomain=uk
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About the Hosts
Matthew O'Neill is a husband, dad, geek and Industry Managing Director, Advanced Technology Group in the Office of the CTO at VMware.
You can find Matthew on LinkedIn and Twitter.
Brian Hayes is an audiophile, dad, builder of sheds, maker of mirth, world traveler and EMEA Financial Services Industry Lead at VMware.
You can find Brian on LinkedIn.
[00:00:00] Ray O'Brien: “It's a fundamental shift in terms of technology, hardware, data availability, and then packaged analytics to allow you to do much more forward-looking analytics than we've ever done in the past. So, that's the fundamental revolution we're going through right now.”
[00:00:24] Matthew O'Neill: Welcome to Don't Break the Bank Run It and Change It - our podcast for curious minds in the financial services industry. I'm Matthew O'Neill. And together with my co-host Brian Hayes we've both worked for over 30 years in banking and banking IT before joining VMware.
In today’s episode, we speak with Ray O'Brien. He is Chief Operation Officer at Quantexa. He is an international business leader, board member, independent director, and advisor with a unique mix of expertise in Data, Analytics, Technology, Risk and Finance. Ray is a proven influencer who makes an impactful difference operating with Boards and C-Level decision makers.
Ray chatted with us about what is behind what he calls the “third industrial revolution.” He delves into how machine learning has changed the capacity for projects to do things that historically many couldn’t afford before. Ray provides his thoughts on how data and analytics are growing every day and affecting relationships among businesses and consumers. He also describes how cloud providers and their services might need to be regulated in the future, especially as it relates to the financial industry.
Great to have you with us today. Thank you very much, Matt. Can you give us a quick intro about you and what you do?
[00:01:27] Ray O'Brien: Sure. So hi everybody.
[00:01:28] Ray O'Brien: I'm Ray O'Brien. I'm the COO contact. Also work with a number of other tech companies. And before that, I was HSBC for 17 years where I was co risk and compliance and also global head of analytics for that lots of other banks in my career. So about 30, 35 years in financial services, hopefully we'll be working for another bank again,
[00:01:50] Matthew O'Neill: Matt, right?
[00:01:51] Matthew O'Neill: From a career perspective, how did you end up here? How did you get started? It's quite a journey to become a COO. So,
[00:01:56] Ray O'Brien: uh, did computers and Matson college in Dublin [00:02:00] went over to London. Was actually going join aerospace, but my brother convinced me to try out financial services. It was late eighties and I joined Benson to digitize stock exchange, and I built data feeds in and stock the days there were still job and brokers and all those type of things for all those very old people on the call, but then went to Japan with Noora.
[00:02:28] Ray O'Brien: Did derivatives still in technology then came back to Europe, worked for Riva amazing lunches. Paraba. Now that was Paraba capital markets before BMP bought them, got more and more senior in it became, um, department head. And then the math side of my brain came across that and I, uh, went over and did some trading for a while.
[00:02:51] Ray O'Brien: So credit routes and asset swaps and things like that. And being a quant on the training floor at Peral, then I joined [00:03:00] Dutcher bank. And I was with Duche bank from about mid nineties to about 2001 that was through the phase of enormous growth of Dutch bank, lots of mergers and acquisitions. And my role was to try and integrate them, to build some kind architecture out of the investment bank of Dutch bank as a group.
[00:03:21] Ray O'Brien: Then the.com boom hit the first one. I think we're in the second one at the moment. And I set up my own company like everybody else, and I did consultancy and, uh, risk management services and technology for a number of financial institutions did that for about three, four years. And then I joined HSSBC and I was at HSSBC for 17 years, started as a kind of a CIO in the investment bank then became COO of the transaction bank, COO of risk and compliance did the DPA was global head of analytics for HSSBC lots and lots of different roles.
[00:03:58] Ray O'Brien: And I [00:04:00] decided to retire and leave. And that was it. I. Going to pull up my shoes and sit on a nice beach and relax, and then wish from Xa who's the CEO convinced me to be the COO. So I joined, I knew contactor for many years. It was on the board of contactor because HSSBC was one of the original investors in context.
[00:04:24] Ray O'Brien: And I knew the team here. So I joined as the COO. I'm a complete fool match.
[00:04:35] Matthew O'Neill: that's not a thing you've ever been called. You've been called a lot of things in my ear, in my earshot, but that was not one of them.
[00:04:40] Ray O'Brien: lovely. Lovely. Does everybody knows myself and Matt used to work with each other at HSBC. That's why we know each other.
[00:04:47] Ray O'Brien: We did.
[00:04:48] Matthew O'Neill: We did for a long time. Um, so what, looking back then, what would you say was your career defining moment?
[00:04:54] Ray O'Brien: There's a couple of aspects that I would say to people who are starting their careers to really look at, [00:05:00] but the first one is international. I got lucky early on and did traveling worked abroad?
[00:05:05] Ray O'Brien: And I really can't state how important it is to try and get a global view to get out of your home country and to work in different countries around the world and to experience cultures and experience different peoples of different backgrounds, because it's so much value to you in your career to understand different viewpoints and not just be monoculture.
[00:05:26] Ray O'Brien: The second was a very, very wise person once said to me, uh, a very famous. It wasn't a gentleman myself, but he was using this person as a reference. And he said, I was reading an X 20. Book, Matt. I dunno if you remember X, one of those networking nately I do yes, indeed. Now you're showing your age. Anyway, I was reading book and I was learning new protocol for God know, and I was enjoying myself and I was deep, deep into tech.
[00:05:57] Ray O'Brien: I could learn every packet. There was, this guy came up and [00:06:00] he says, what are you reading? I says, oh, this nice book. And he says, why are you reading? I said, uh, you know, it's the new thing that's gonna get big. And, uh, I really believe it's L
[00:06:13] Ray O'Brien: he said to years, why don't this book handed book? And I looked said, really? He said, it never changes. And if you learn that book and you just learn it once. Your value will be enormous to an organization. And he gave me a quote from Bloomberg and this is, uh, Mike Bloomberg, uh, famous billionaire, as we all know, we love him can hate him, but he's very famous.
[00:06:44] Ray O'Brien: And his quote is there's a lot of people in this business who know more about finance than I do. There's a lot of people in this business know more about technology than I do, but there's nobody who knows more about both than I do. And that's the key which has guided my career, [00:07:00] learn both technology and the business.
[00:07:01] Ray O'Brien: If you have both of those, you are the junction point. You are the person, you are the enabler. You are the interface. You are the go between to the business. You can help construct new financial services and. Basically where I have tried to manage my career towards
[00:07:22] Matthew O'Neill: fabulous. And I can see that I can see that.
[00:07:25] Matthew O'Neill: That's that's really cool. So, so Ray, then what would you say has been your proudest moment from a professional perspective?
[00:07:31] Ray O'Brien: Proudest moment? I think it's some of the big go watching things that you've created go live and be implemented around the. And, and watch people using them, going into an office and say somebody using a system or a process that you've designed and you've built and just looking at them, they know that you're the one who actually built it and just watching them use it and happy with the [00:08:00] user process.
[00:08:00] Ray O'Brien: So those are some of my proudest moments. I think the second thing would be around people, developing people. Some of my most proudest moments is watching people who I've managed grow. And become self-sufficient and basically overtake me and it's become incredible valuable assets to whatever organization they're working for.
[00:08:25] Ray O'Brien: And I, I really do love watching people grow and become their best. So it's. Implementations getting something done and its people. Yeah.
[00:08:36] Matthew O'Neill: Fabulous. Fabulous. Let let's move on
[00:08:41] Ray O'Brien: man. And I did a real deep dive. All
[00:08:43] Brian Hayes: right.
[00:08:44] Ray O'Brien: Uh, let's get into it. We'll find out everything there is to know.
[00:08:48] Matthew O'Neill: Okay then Ray. So. We started a conversation, uh, a few episodes ago around, around data and the world of data and data ethics and AI ML and those sorts of things.
[00:08:59] Matthew O'Neill: And, and I think we're [00:09:00] far from done in the topic. So really wanting to get your take on, on what's what's new and going on in the world of data analytics.
[00:09:07] Ray O'Brien: Wow. That's a vast topic, which I probably could spend hours on that but what's going on? So we are going through the third industrial Revolut. We are watching data become a valuable asset, more valuable than other assets.
[00:09:27] Ray O'Brien: Why is that? There's a couple of changes. The first one hardware has got commoditized, got sheep. You've seen the cloud providers. You've seen VMware. You've seen all these organizations build. Hardware technology infrastructure, which allows you to have massive storage and massive amounts of analytics. The second thing you've seen is data provision.
[00:09:58] Ray O'Brien: So not just your [00:10:00] internal data, but external data, bringing those both together and allowing you to do some kind of forward looking analytics, conceptual analytics around bringing together about internal, external. So to give you a simple example, 20, 30 years ago, when people used to come to me in large financial institutions and say, look, I wanna do this project.
[00:10:23] Ray O'Brien: I'd look at them, but you know, do you realize the cost of that to that's just how many CPUs and hardware we'd need? We don't have the data assets. We would reject the projects. We wouldn't. The mats hasn't really changed. People say machine learning, Ray artificial intelligence that stuff's been around since the seventies.
[00:10:42] Ray O'Brien: Yeah. We've got some new machine learning techniques, tailored things, but honestly, the concept's been there since the seventies. Fact earlier what's changed is the capacity to do these kinda projects and stand up analytical environments and [00:11:00] do trials and POCs and innovation. And to try things out that we just couldn't afford to do historically.
[00:11:08] Ray O'Brien: So it's a fundamental shift in terms of technology, hardware, data availability, and then. You know, packaged analytics to allow you to do much more forward looking analytics than we've ever done in the past. So I that's the fundamental revolution we're going through right now.
[00:11:29] Brian Hayes: I just wanna continue that theme really.
[00:11:31] Brian Hayes: So what are some of the more interest these cases that you are now beginning to work on across Fs or otherwise that you, that you can tell us?
[00:11:40] Ray O'Brien: There's many, many different use cases that I could talk to you about. Uh, it all depends what your definition of interesting is. let, lemme, let me give you a selection of things which are amusing.
[00:11:55] Ray O'Brien: So one of the things that you're trying to do is predict people's behavior. [00:12:00] Our company's behaviors, our transactional behaviors, and you're trying to forward, you're trying to forecast and forward luck on these things. And so what you do is you bring together large data sets. You bring together drivers of that data.
[00:12:14] Ray O'Brien: Matts is unethical Matts basically just brings data together and gives you an answer. So it causes you problems. So, let me give you a simple example in, in the insurance field, did you know in the UK that you should not distinguish between male and female drivers on insurance premiums? Because it's bias.
[00:12:41] Ray O'Brien: It's gender bias now, actually, statistically, it's been proven. Female drivers are safer than male drivers, and I've got thes and show you that. So really women in the UK are subsidizing men in terms of driving insurance [00:13:00] premiums. Interesting. Now imagine mat environment, you bring data together and you're running analytics and you're an insurance company.
[00:13:11] Ray O'Brien: The first thing you notice. Is the drivers of pink cars are much less risky than drivers of red cars. And if you think about that for a Bobbi, you. Okay, so you weren't allowed to distinguish between male and female, uh, drivers, but the color of the car is very correlated and yeah, there'll be some edge cases, but it does give you a good indicator of what kind gender potentially is in that.
[00:13:40] Ray O'Brien: And you'll be amazed. You will actually get a lower premium on a pink car than you will on a red. Because it's a second order correlation that brings into ethics. And the ethics here is that you shouldn't have gender bias, but the second order of the analytics, the mats itself has [00:14:00] figured out the color car is correlated and is using that to drive the underlying gender bias.
[00:14:06] Ray O'Brien: So you've got to start factoring these things out of your analytics, because I said at the start. Math is biased. It just does whatever the data tells you. Uh it's so you have to put in these ethical rules into your dataset to try and reduce the amount of bias that's happening in the, so that that's one simple application is how do I do an insurance premium in the UK?
[00:14:32] Ray O'Brien: That absolutely doesn't look at male, female, but actually there's lots of second order correlated. Data points, which actually does that as well. Now, extrapolate that in your brain, Brian and Matt, and you can see the problem
[00:14:51] Ray O'Brien: unbiased, a
[00:14:56] Brian Hayes: bias. A moment is quite a top theme. [00:15:00] I don't suppose for a moment we've resolved that issue. People have really resolved
[00:15:06] Ray O'Brien: that. No, let me give you another example. Let's pick China this time in China, there is, uh, web based apps where it's on your phone and you got a lovely little app and you can borrow money on and app within seconds, maybe not seconds, but 30 seconds a minute or two, you get approved.
[00:15:28] Ray O'Brien: Part of that onboarding process and that loan application. This is, it's not Western banks, it's Chinese banks. They switch on the camera on your phone and they look at your eyes to look at the no amount of blinking you're doing. What they're basically doing is a lie detector test on your eyes to see if you're being honest, it's actually pretty accurate.
[00:15:53] Ray O'Brien: It seems there is a massive correlation and the amount of blinking you do to whether you're, uh, lying or not. And [00:16:00] it rejects applications based on the amount on your I movements and blinking. Now, imagine implementing that in the west. Imagine us sitting here in the UK and we're a financial institution and we switch on the camera off somebody's phone to spot.
[00:16:18] Ray O'Brien: Could you imagine the backlash? Can you imagine the privacy conversation you would have, you might be mathematically correct. And it is actually quite a good SI way of detecting something, but ethically it's very, very. Damaging and difficult to do something like that. So there's loads of these use cases out there where you watch other countries and what they do and you go, oh, that's interesting.
[00:16:44] Ray O'Brien: But I don't think we can implement something like that in this country. There's some fascinating use cases. Did I get you on blinking now? Matthew, you did. And
[00:16:53] Matthew O'Neill: now I, and my eye's only a little bit runny. I sure you, and ,
[00:16:59] Brian Hayes: it's one of those [00:17:00] things. Why, you know, is there a reason you can't blink and you can't use to start blinking, blinking, blinking?
[00:17:04] Brian Hayes: When was the last time you didn't blink?
[00:17:07] Ray O'Brien: I think probably you don't blink at all. That's probably a good test as well. . But what, what I'm, what I'm saying to you is that you've got traditional analytical use cases, but you've got all these other use cases that potentially could be done. Um, and so analytics is growing every day.
[00:17:25] Ray O'Brien: You've heard of deep learning. You've heard of unsupervised learning, which is probably the. Where mats get the biggest and where the algorithms really start growing on their own. Very difficult to implement unsupervised learning and deep learning, because you have to put guide rails in place. You have to make sure what you've implemented.
[00:17:49] Ray O'Brien: Won't deviate from some kind of standard structural way of doing. And if they easily can deviate, you've all heard about the Microsoft chat [00:18:00] bot that was on the web that they had to bring down because God bless this planet. A couple thousand people decided to make it a. Racist by feeding it standard conversations to make it curse and do racist remarks.
[00:18:17] Ray O'Brien: Cause it was learning from the data feeds and literally a couple thousand people spent all night feeding this chat, terrible language so that it started responding back in a similar way and, and portal Microsoft had to switch. And, and there's all these kind of use cases where you, where you look it at the start you're going, oh, that's wonderful.
[00:18:41] Ray O'Brien: And
[00:18:45] Ray O'Brien: people feeding it. You don't a couple people will, you know, overnight to basically train it to. Be abusive, which is what they did. And it's, it's amazing how these things can [00:19:00] deviate from. You've gotta create very tight control rules around how they're used and switch them off automatically when they start deviating.
[00:19:09] Ray O'Brien: So I
[00:19:09] Matthew O'Neill: was gonna ask you, is it easy to get it wrong? You know, it's this algorithm plus data set equals model and how. How easy is it to get, get it wrong. And how do you prove the model is good, but I think no matter how good you've made it, it didn't sound like it was something that was being done commercially to disadvantage Microsoft.
[00:19:27] Matthew O'Neill: It was just people. Being stupid with it. Right. And
[00:19:31] Ray O'Brien: having fun and, you know, being silly, probably a bunch of teenagers and having a laugh, they succeeded. Yeah. Yeah. I, I, if you look at let's services algorithms, let's take some of those autonomous algorithms and you've, you've heard of the, some of the stock market crashes that have happened.
[00:19:52] Ray O'Brien: Cause these algorithms went outta. They tripped. And they literally just did either the sell or the buy [00:20:00] to, to tune up millions of trades in nanoseconds before they could be switched off. And so what the regulators are doing is making all the investment banks who have these kind, or the hedge funds have these kinda algorithms have to have automatic switch offs, fail safes that.
[00:20:20] Ray O'Brien: If it goes past a certain boundary, certain number of transactions, certain price point, stop, just stop. There's something potentially this bot and you've safeguards science fiction. Now you remember the, the three laws of robotics and the, the rules about the three laws. And if you think about those three laws, it's the same with bots.
[00:20:49] Ray O'Brien: It's. If there's something I can switch yourself off, there's just something wrong here. Uh, you're past your boundaries and yeah, maybe, maybe it is Greg, but [00:21:00] it's too extreme. The educator is too much. You need to switch off for a while. Uh, while it reconsiders, that's fine for financial trading, but, but imagine driving a car and it switches off, then you've got a real problem.
[00:21:12] Ray O'Brien: So the, the, the area that is really difficult is the autonomous vehicles and some of those kinda decisions. I honestly do not know how they can make an ethical decision, you know, do I divert and kill one person or, or swear to the right kill two people. What's the ethical decision one versus two. I don't think there is.
[00:21:31] Ray O'Brien: What, so how does the machine decide? What is the course of action? I mean, some of those autonomous vehicles and, and their abilities. Make the right decision. I I'm lost in terms of how they will actually do it. I'm a, I'm a great believer of artificial intelligence that aids a human and helps a human win, their role, but being completely autonomous that's when I'm going.
[00:21:56] Ray O'Brien: Oh, I'm not 100% sure. So if I'm, if I'm [00:22:00] building a system metric that helps you with decisioning, that helps you make a, do your job better, quicker, faster, easier. Replacing you completely, ah, not sure
[00:22:14] Matthew O'Neill: now. So I think it's that thing of augmented for is a better approach. Yes. Because you, you, you still leave the decision in the one.
[00:22:22] Ray O'Brien: Exactly. So let take another example of surgery doctors. They now have AI that augments surgical procedures. Where the computer is aiding the doctor in terms of incisions, where to go next, et cetera. Amazing technology. Doesn't replace the surgeon. It helps the surgeon aids, the surgeon. It tells him where the next cut should.
[00:22:53] Ray O'Brien: Potentially be, but it's the surgeon who makes the cut. And that, to me, if somebody asks me, what's the difference between [00:23:00] independent versus augmented, I always give the surgeon example of, do you really wanna be in a surgery where it's just a robot doing it? Or do you wanna have the surgeon there who's been guided needed?
[00:23:12] Ray O'Brien: Let's go back to technology. It
[00:23:14] Brian Hayes: is, it's all about technology, but it's also around the. Integration of that technology in everyday life. The example you give in 10, 15 years time, there will probably be many, many other examples and it will be the norm, right? It would you, you know, would you rather be seen by a doctor or a bot?
[00:23:35] Brian Hayes: You know, a bot can
[00:23:35] Ray O'Brien: see you now at a lot of bots can diagnose early stage cancer and all these things much better than a. You know, they have incredible accuracy on some of these things these days, just on skin, tone, color, all these kind of things. Right. So you're right Brian, but where, where do you decide that you don't need a doctor anymore?
[00:23:55] Ray O'Brien: And that it's just a bot doing it and may, and maybe we've seen that in financial [00:24:00] services. Right? So if you member Matthew, the old days, you'd. The old captain Maning branch manager, in your bank who would know your name? You know, I started my
[00:24:10] Matthew O'Neill: career in branch banking. I, you know, I started my career there, you banking.
[00:24:15] Matthew O'Neill: And so ,
[00:24:16] Ray O'Brien: but you know, your customer, the person comes in on a regular basis, you know exactly what the financial details, his, his, or her standing in the community, et cetera. And therefore. When the person comes in and ask for a loan or a mortgage or whatever it is, you can have a good, proper conversation.
[00:24:38] Ray O'Brien: You've
[00:24:49] Ray O'Brien: 40 years digital banking, everything automated KYC process are really difficult these days because financial institutions don't know their customers. [00:25:00] It's all been digitized. And so that's why they have all these extra checks and controls in place because there is no more the captain Mannering knowing the community, making those kind of lending decisions it's being done by computers and the decision points are based on.
[00:25:21] Ray O'Brien: Data around people or organizations you've taken the human brain of Mannering and you've tried it to, into computers and there's pro and cons for that pros in terms of speed and how quickly you can do things. And the cost the is, do you really know the customer? You know, is your data points really that accurate about an individual or a company to make those kind of decisions?
[00:25:49] Ray O'Brien: How often do you get it wrong? And that that's why data is becoming so important.
[00:25:52] Matthew O'Neill: I agree with you. I I'm, I'm asked a lot about, you know, the topic of, you know, digital first banking and branches. And [00:26:00] is there a future in branches? And you speak to a lot of folks about, well, when was the last time you went to a branch?
[00:26:06] Matthew O'Neill: Do you know your branch manager? Do you even know their name? And that whole relationship banking thing is no longer there. It's just totally you can phone up. You can do it online. Your risk is assessed. A decision is made and there's no autonomy in the branch for that.
[00:26:24] Ray O'Brien: That can lead to big issues, right?
[00:26:26] Ray O'Brien: If you look financial crime, money laundering, those kind elements, it allows, or it facilitates those things to more than rigid structures where they would know the individual quicker, quicker, or faster. But as you know, if you talk to most people these days, they don't particularly wanna go into a branch.
[00:26:53] Ray O'Brien: They're very happy with their app on their phone. And they're very happy with that digital banking service. And [00:27:00] they accept that a lot of the key decisions about their lives have been made on data points. Now, instead of humans with algorithms that we've built to allow some kind of, you know, distinction and demarcation about whether this is a good risk or a bad risk and et cetera, et.
[00:27:18] Ray O'Brien: This space
[00:27:18] Matthew O'Neill: then who, who leads the world in this, you know, geographically or industry, or for what purpose are we heading to a heading to, or are already in a minority report situation? You know, where how's this, you know, where does this really fit? And, and who's leading
[00:27:32] Ray O'Brien: the way. Minority port is a great one.
[00:27:35] Ray O'Brien: I keep getting asked, you know, Ray, uh, you know, when am I gonna see that visualization of everything, the ISD in that space. And that's in of doing that and conceptual decisioning around datapoint who is in the lead geograph. I'd have to say [00:28:00] China, China, more advanced in, uh, their decisioning analytics and their AI down the west.
[00:28:08] Ray O'Brien: I'm afraid at the moment, if you look at the advances they've done, because I suppose they. Aren't as regulated and they're allowed to do things more than Western they've. They've made incredible advances in the last 10, 20 years. I mean, don't get me wrong if you look at America, west coast, incredible work, but I think China's slightly ahead on artificial intelligence, especially in the financial services space.
[00:28:39] Ray O'Brien: If I look at sectors, I probably pick. Retailer. So advanced compared to financial services. If you look at retailers, look at the analytics, they use to figure out what a customer wants next. It's incredible analytics and they've been [00:29:00] doing it for years. If you look at their real time distribution analytics and things like that, their customer benefits, analytics, et cetera.
[00:29:09] Ray O'Brien: The other area is the gaming industry, the analytics and the gaming industry around their user behaviors. Incredible real time behavior. They can spot Matt that you've been X number of hours on a game. They actually make the difficulty level a little bit harder to get you off the game, cuz they know after a certain point of time that you're actually gonna reject.
[00:29:32] Ray O'Brien: So they want you to leave with a reasonable experience and to. Optimal amount of time. They've got all these algorithms running in the background that you're not even aware about watching your behavior and how you're doing on, on a game. It's it's credible. So I, I honestly think financial services is way behind some of these things.
[00:29:52] Ray O'Brien: If I look at some of the other sectors and some of the analytics they're using, especially around customer behavioral analytics, [00:30:00] some really deep, beautiful models in some of the other areas. If I take, uh, things like. Operations analytics and operational resilience, things like that. Yeah. Just, just look at the airline industry, nuclear industry automotive industry, and then start comparing that to financial services.
[00:30:21] Ray O'Brien: Come on. Are you kidding me? Are you really gonna say an operations unit and a bank is as good as. Really, you know, if you look at the signal engineering they've been doing for so long, I mean, they invented six Sigma for God's sake and you look at the things that they've done. There's whole degrees. Now in those manufacturer engineering that you can do in college, I, I haven't seen a financial operations degree yet.
[00:30:52] Ray O'Brien: so don't wrong. If I look at investment, I look at some analytics and the algorithms there. Yeah. The [00:31:00] nanosecond type stuff pretty far advanced, but I look at some of the other areas of financial service. Yeah. Some of these other sectors, much more. In the world
[00:31:10] Brian Hayes: where, you know, media is king and communications is, is overtaking compi.
[00:31:16] Brian Hayes: I'm not sure anyone's gonna be incentivized to go and do a three year degree in post trade settlement. You know that that's, you'd have to
[00:31:27] Ray O'Brien: call it something.
[00:31:30] Brian Hayes: You'd have to call. You'd definitely have to call it something else. Yeah. What did you blockchain in there somewhere? Where did you stick a digital in there?
[00:31:38] Brian Hayes: TPL. We studied. Yeah, we, we studied digital T plus, there you go. That's what we did. Yeah. Maybe
[00:31:46] Ray O'Brien: plus three to T plus one. I remember that Brian . Yeah. Yeah, exactly. Yeah. But if you look at the, how clunky those are and the operational design and also the signal. Now let's take [00:32:00] operational resilience. You know, my risk hat for a moment, very much a theme, especially geopolitical moment around resilience.
[00:32:11] Ray O'Brien: Actually it needs
[00:32:15] Ray O'Brien: signals. Don't design those signal. Even when we build the processes, you can imagine a nuclear power plant where there's no control center. There's no dashboard to tell you how the pipes are doing. And there's somebody going around with a white coat and a clipboard with a tap hammer, tap in the different pieces of in the, in the nuclear factory.
[00:32:39] Ray O'Brien: I mean, you'd shut the bloody thing down. You'd go. Are you kidding me? No ways does that should be allowed right now. Now show me in a bank, Brian, where there's. Control center, where you're getting signals from all the different operational processes, not just about something going wrong, but predicting it's gonna go cause that's proper signal [00:33:00] engineering.
[00:33:00] Ray O'Brien: That's where you use the analytics it's on that prediction industries have been doing that for years. Other industries banking way behind on some of these things. But you would've thought
[00:33:14] Matthew O'Neill: you would've thought in the assessment of credit risk. That that is something that would've been there
[00:33:20] Ray O'Brien: that's fair on credit risk, but even credit risk, right?
[00:33:24] Ray O'Brien: It was for years around financials. Your balance sheet, your spreading, and how is a financial organization or a human being, what they're financials. It didn't really look at behavioral analytics or network analytics to really give you more better predictions on credit. It really does use financials as its driver.
[00:33:48] Ray O'Brien: Now it's changing now. You're seeing a lot of the new CoBank and the new lenders really beginning to bring in behavioral and network analytics into that credit decision. [00:34:00] To allow them a much more accurate predictive model when for the last, what, 40 50 years, Matthew, all we did was use financials. We didn't do a sentiment score of Matthew in terms of before we, we lent them money, you know, there was no negative news scraping.
[00:34:18] Ray O'Brien: There was no none of these other kind of external data that we now have that we can. Which is completely changing, uh, some of these aspects. So even something like credit, which hasn't been around for a long, long time is fundamentally changing in the new dynamic and the new paradigm around data analytics.
[00:34:37] Ray O'Brien: Cause you've got these external data sources, which are supplementing the historic to create something new and more.
[00:34:48] Ray O'Brien: I see the future really well. What do you have a crystal ball? What's gonna happen? Listen, if you know something, you gotta tell me
[00:34:57] Matthew O'Neill: Ray then. So what do you think will be one of the most [00:35:00] significant game changing technologies for 22, 22 and beyond. And, and how do you think that's gonna help or hinder financial service?
[00:35:08] Ray O'Brien: I'm gonna talk about, uh, a technology which has ran for a long time, but I'm beginning to see more and more acceleration of adoption and that's cloud, I'll talk it in the vein of financial services, which is, you know, my home sector let's put it that way. It was introduced a number of years ago, actually VMware, where one of the first companies in that space in terms of virtualizing.
[00:35:33] Ray O'Brien: And allowing companies to have virtual hardware, mostly OnPrem in those days. And then it started moving to third parties and you, the big players started investing and we know the three big Western players, you know, Google, Amazon, and, uh, Microsoft. And of course I forget IBM and a couple of others, and they invested enormous of money to build out these data centers around the world.
[00:35:58] Ray O'Brien: And to get to start [00:36:00] in the old days, used to data center outsourcing you remember that old term where we used to talk about data center outsourcing. We used to give it to like an IBM or a Sunguard or something like. And it used to be something quite boring down the back that technology did. And the CEO, the bank wasn't really involved that much.
[00:36:22] Ray O'Brien: And the regulator wasn't really involved that much. As long as we showed, you know, how we could keep operational integrity, then it changed. New words started being used and the regulators got involved and they got worried and scared and they slowed things. And I can't blame them because they were watching the whole world moving core infrastructure onto the cloud.
[00:36:49] Ray O'Brien: And they were watching countries. Let's take the UK critical infrastructure to run the country onto these cloud [00:37:00] providers. And they got worried about it cause of the concentration risk because of the security risk. Because the operational resilience, cetera, cetera words that you have heard from regulators around the world, from any person who's
[00:37:19] Ray O'Brien: migration's
[00:37:29] Ray O'Brien: I think cloud providers are going to become. Like an electricity company, a water company, they're utility player, and they'll regulated like a utility. So Matt, very terms. If you're water company in the, the, to,
[00:37:51] Ray O'Brien: if you bankrupt on a Friday, the water still flows on a Monday. Because you're regulated to make sure that there is a company with enough [00:38:00] capital in it to keep the water flowing and to make sure that that water has an operational process, no matter what happens to that company, the same will happen to cloud providers.
[00:38:13] Ray O'Brien: They're becoming too critically important for national and countries. They will become U tool ized and they will have to be regulated. Like a utility. So Google goes down in the morning in California, the data center in the has and have the I, all the hardware to allow that legal entity to continue. So my prediction, it's not more of a technology prediction.
[00:38:46] Ray O'Brien: I'm telling you what I'm saying to you is I think you're gonna see a change around cloud provisions as a service where these big tech companies will be regulated like utilities. [00:39:00] It's
[00:39:00] Matthew O'Neill: a very interesting prediction. And I think that you can see a lot of signs there for that.
[00:39:04] Brian Hayes: It's, it's interesting because I think this.
[00:39:07] Brian Hayes: You, you mentioned the term rate that we get asked about a lot about concentration risk and actually our customers haven't defined their. Version of cons concentration risk used to be supply risk, used to be platform risk used to be. In fact, it's all of those things, but from a regulatory perspective, it's, it's the regulator saying, oh, actually I don't want every mortgage process in the UK in the same cloud.
[00:39:35] Brian Hayes: So the regulator would take a very different view on that. And I'm painting an extreme obviously to, to make the point. But I like you think that. Cloud, particularly for financial services will become regulated to what degree we'll wait and see. And actually what normally happens there, I say, um, is there's a significant failure somewhere.
[00:39:57] Brian Hayes: And then through failure [00:40:00] oversight is applied. We've all been around long enough to have seen it before. So it's, as long as it doesn't happen to me, I'm okay. Cause I don't mind it happening to my mate down the road in that other bank. But then I'm gonna see the repercussions because we'll get a, we'll get the equivalent of the good old fashioned dear chairman letter.
[00:40:18] Brian Hayes: Right. You know, from the regulator. So I, I absolutely think at some point that will happen. I think the regulator struggles at the moment to intervene on that basis. Cuz there hasn't been that market.
[00:40:32] Ray O'Brien: No, no, I agree. I think a market event will accelerate the process and now
[00:40:36] Matthew O'Neill: it's time for the lightning round.
[00:40:39] Matthew O'Neill: Uh, we usually call it the lightning
[00:40:41] Ray O'Brien: round. Okay. Welcome to the super awesome bonus lightning round. The lightning round begins now.
[00:40:50] Matthew O'Neill: This part of the conversation was recorded after we'd originally chatted with Ray, but we've got him back to find out more about who he is and what he likes as usual. Ray, you can take a pass, [00:41:00] but we'll probably have some fun at your expense later. Um, Brian, wasn't able to join us on this round, but I will do my best to get to the bottom of things with you, Ray.
[00:41:07] Matthew O'Neill: So let's get to the first. Just to get things going then what would be a, a favorite book or movie? I'm gonna
[00:41:13] Ray O'Brien: pick a movie and I'm gonna pick a ground hope day. I just like that movie it's kind of completed circular and also you can sit there and imagine yourself in those circumstances. And what would you do with internally?
[00:41:27] Ray O'Brien: Eternity that it's, uh, it's a great thing to think about. Uh, and it's a, it's a very easy going movie that you can watch multiple times I'm with you
[00:41:36] Matthew O'Neill: on that. And there's a few times I've thought I could do with that either for completing a task I've got to do or for learning the piano. I mean, what are amazing?
[00:41:44] Ray O'Brien: One of the tasks. Yes
[00:41:46] Matthew O'Neill: but not anymore. Okay. If you had a time machine, would you go back in time or into the
[00:41:51] Ray O'Brien: future? Oh, that's good. That's very good. Ooh, which would I go? I think I would like to go forward in time. [00:42:00] Cause I am a firm believer of some things which are completely science fiction today, but I really think will actually happen.
[00:42:09] Ray O'Brien: So one of the things I think will happen is the internet will eventually allow. Humans to upload their consciousness and we will have computers powerful enough to mimic the human brain. If you have that, then all of a sudden you have a virtual consciousness and you have a of yourself. Wow. That's true.
[00:42:33] Ray O'Brien: Digital twin. A true digital twin. Exactly. Wow. That would be incredible. Then you could just download yourself onto, into wet grown bodies. Uh, your consciousness would remain infinite. And sometimes I think about this and I going, are we one of the last generations who will actually die? Um, and you know, you could get.
[00:42:57] Ray O'Brien: Quite, uh, fascinated this stuff. Yeah. This [00:43:00] lots of time. Of course, it's not true yet, Matt, but if you look at where we're going, if you look at quantum computing, if you look at how fast they will work and what they will be capable of doing, and then you also look at. how much we can replicate the human brain today and how quickly we're advancing that space with AI and everything else.
[00:43:22] Ray O'Brien: I'm actually a believer. I'm a believer that it will happen at some stage. So I'd like to go forward in time. For that moment, because that will change completely aging. That's deep. That's
[00:43:34] Matthew O'Neill: probably the deepest answer we've had to that question. And, uh, sorry so that no, no, no, that, that is fabulous. And, um, I think that's something, um, yeah, maybe we can be chatting over a glass of wine on that.
[00:43:45] Matthew O'Neill: Uh, yes, indeed, indeed. And in the future. So that's a good one. Okay. So, uh, morning or evening, evening,
[00:43:50] Ray O'Brien: I'm an evening person. Math I've found my whole life difficult, getting up in the. And evenings. I am normally the last person at the bar that, wow. Okay.
[00:43:59] Matthew O'Neill: That's a different [00:44:00] story. Tea or coffee?
[00:44:02] Ray O'Brien: Coffee. I'm addicted to espresso and, uh, drink way too many of them.
[00:44:08] Ray O'Brien: Okay. All right. Still or sparkling. Still.
[00:44:12] Matthew O'Neill: Yeah. Yeah. You know, I kind of knew that was gonna be, I, I knew that was . Um, so if you could have dinner with anyone dead or alive, who would it be? Oh, that
[00:44:23] Ray O'Brien: amazing question. So many people to choose from. Who'd you pick. Einstein for his intelligence, Oscar wild for his witnesses.
[00:44:32] Ray O'Brien: Jesus, that'd be an interesting one.
[00:44:38] Ray O'Brien: I dunno. Very hard to choose one. No, no, that's a good, like I'd probably pick Oscar wild, cuz I do like a, a good enjoyable dinner. That and he would, he would keep the conversation going.
[00:44:50] Matthew O'Neill: Uh, and to be fair, sometimes we say, if you have three people at dinner party, so there you go. I think we can, we can do that.
[00:44:56] Ray O'Brien: Your three together would be very interesting. there you go. [00:45:00]
[00:45:00] Matthew O'Neill: oh yeah. And your role in there could just be antagonist to see who's gonna say what you're expecting them to say. It's going, you could be quite good. What piece of career advice do you wish you'd given to your younger self? Don't be
[00:45:11] Ray O'Brien: afraid. Try out things, give it a.
[00:45:15] Ray O'Brien: be more experimental and allow yourself to have more volatility in your career and in, and in your aspirations and try things more. I think people get stuck in a rut in jobs they're comfortable, but they're not happy. And I, if I look at my younger self, I could have maybe moved on quicker in some places and done things differe.
[00:45:43] Matthew O'Neill: All right. Good, nice. Um, okay. There, so this one, we always try and ask, uh, when was the last time you used cash? Um, and, and what was it for?
[00:45:53] Ray O'Brien: Beautiful question Ireland last weekend for a pint in a packed pub [00:46:00] because the machine had broken on the couch. lucky you had some cash. Exactly. And there was an awful lot of people in that pub who didn't
[00:46:09] Brian Hayes: right.
[00:46:11] Brian Hayes: Oh, my goodness.
[00:46:12] Matthew O'Neill: Um, okay, so wacky question. If you're an ice cream, what flavor would
[00:46:16] Ray O'Brien: you be? My favorite flavor is Min's chocolate chip, but I dunno if I wanna be a Min's chocolate chip. That's a very, that's the thing
[00:46:24] Matthew O'Neill: is difference between favorite is, would you
[00:46:26] Ray O'Brien: like to be yeah, yeah. Might actually wanna be a vanilla.
[00:46:30] Ray O'Brien: But maybe that's a bit boring. Mm. Maybe maybe vanilla would sorted caramel.
[00:46:39] Matthew O'Neill: chewy or crunchy, sorted caramel.
[00:46:41] Ray O'Brien: Oh, uh, crunch, crunch it up. Crunch. There you go. There you go. There you go. Nice question. .
[00:46:51] Matthew O'Neill: So what was your most memorable technology experience and.
[00:46:56] Ray O'Brien: I would say it was [00:47:00] many years ago at EMC. I went to co and they presented to me the virtualization of a data center and discs and CPUs.
[00:47:12] Ray O'Brien: And I sat there going that this will never take off. Doesn't make any sense at all. and I remember it was the whole weekend and by the second day I was looking okay, oh my God, this is the future. This is gonna completely revolution. A whole way that we do te. That was many, many years ago, Matt, if only I had invested in some of those companies, indeed, along the way, including the one you're working for today.
[00:47:35] Ray O'Brien: Yeah. Uh, it's incredible. What has happened in that space? It's probably in my view, one of the biggest technology achievements was the virtualization of infrastructure. Well, we wouldn't have a cloud without one. Wouldn't have a clap without it, indeed. Um, so, uh,
[00:47:51] Matthew O'Neill: look, you, you know, you, you are widely traveled, uh, like, uh, like we are, so, um, what's the weirdest food
[00:47:57] Ray O'Brien: you've eaten Vietnam, [00:48:00] uh, snakes.
[00:48:01] Ray O'Brien: Yeah. Uh, I'm not sure they were poisonous, but they did skin the snakes and I, I didn't, I swear, I didn't ask for it. Uh, I wouldn't have, uh, but I came a live stake and they skinned it in front of us and I, oh my God. And they then of course, made us eat a piece of it. Uh, once we had been cooked. Yes. Yes. Just not, not appetizing.
[00:48:22] Ray O'Brien: Not nice. No, no, no, no math, just, no,
[00:48:26] Matthew O'Neill: I think some things are on that. No list snake soup in Hong Kong was always, um, you know, it is a local favorite, but it just wasn't mine. Okay. So, um, last two, um, Best professional development book you've ever read. I'm gonna say a
[00:48:41] Ray O'Brien: controversial thing and say that I don't really read them.
[00:48:43] Ray O'Brien: Yeah, I'm gonna to say it simple as that. No, it's not, not my thing.
[00:48:46] Matthew O'Neill: That's fair enough. All right. I'm gonna ask you a different question instead then if you had to delete all but three apps from your smartphone, which ones would you keep?
[00:48:54] Ray O'Brien: Oh, very good. Very good map. Have to have my banking app. Uh, there's a lot of [00:49:00] financial stuff.
[00:49:00] Ray O'Brien: I do my email app. I have to have some communication and probably one of my texting apps. Yeah. So communication and one finance there, you go's one of apps that I've just got rid of though. I know I've got way too many apps on
[00:49:17] Matthew O'Neill: your phone. I no. Got that problem. And, and every now and then I think I'm gonna do, I'm gonna purge it.
[00:49:22] Matthew O'Neill: Yeah. But it's the same, it's the same thing. You know, there was a time when you used to manage your hard disc and now yes, that that's just not, that's just not good effort, right?
[00:49:31] Ray O'Brien: It is laziness. Isn't it.
[00:49:34] Matthew O'Neill: right. Final question. And this is Brian's favorite and, and we asked this of everybody you have to sing karaoke, which song do you.
[00:49:42] Ray O'Brien: Oh, wow. You're bringing me back to my Memorial days. I would probably actually pick an Irish song cause I know the words too, and I probably pick, uh, seven drunk nights. Wow. Cause I do a good rendition and I don't really need the music in the background and I can do it sober and drunk.[00:50:00]
[00:50:01] Ray O'Brien: all
[00:50:01] Matthew O'Neill: right. Well we add that onto, uh, our conversation. About the future. Um, Ray, thank you so much for coming back and, and, uh, and, and going through these with us, hopefully it wasn't too daunting. Um, I really appreciate it as, as always. Thank you so much.
[00:50:16] Ray O'Brien: I really wanna say thank to both of yous, uh, a pleasure, uh, see you soon.
[00:50:23] Matthew O'Neill: To keep up with Ray. Please follow him on LinkedIn. You'll have links in our show notes as always. If we can help you in any way, please talk with your VMware account team or you can connect with us on LinkedIn, just search for Brian Hayes or Matthew ane at VMware. You can also follow me on Twitter at Matthew and our podcast on Twitter at DB TB pod.
[00:50:45] Matthew O'Neill: You can find our show notes at don't break the bank podcast dot. And if you like our podcast and could leave us a review and comment on apple podcasts, that'd be really appreciated. If you have any ideas, future episodes, or wish to appear as a future guest, please do get in touch. We hope you can [00:51:00] join us again.
[00:51:00] Matthew O'Neill: Next time please do take care.