 Live from Cambridge, Massachusetts, extracting the signal from the noise, it's theCUBE, covering the MIT Chief Data Officer and Information Quality Symposium. Hi, buddy, we're back in Cambridge, Massachusetts at MIT. This is theCUBE's SiliconANGLE Wikibon's continuous coverage of the MIT IQ Information Quality Chief Data Officer Symposium. It's a mouthful, but it sort of underscores the transition that's happening in this community. I'm Dave Vellante, joined by my co-host, Sam Caham. We're really thrilled to have Jim Gilligan here as the President and CEO of Blue Cross Life Insurance Company of Canada. Jim, welcome. Thanks very much. Of course, we know Blue Cross around here as the health insurer. Right. Your life insurance, explain that. Well, in Canada, the Blue Cross plans across Canada are organized geographically, and each of them has a license that's provided by the provincial governments, and they're all not-for-profit licenses which restrict the business they can do. So in order for them to compete effectively in the group space, they need to have not just the health ability, but also a life ability. So what they've done is invested their capital together and formed a for-profit company, and that's Blue Cross Life, and that's what we do. So we basically provide the life and disability product for the Blue Cross plans, most of the Blue Cross plans in Canada, and they are our distributors. They're also our shareholders. They also sit on my board, and I also outsource my operations to them, so it's quite an integrated operation. So, I'm going to get right to that chase. The CEO, the buck stops with you. When people come to you and talk about an ROI that relates to protecting data or risk, I mean, you have to do it, but you don't love to do it. Doug Laney's coming on later. He's got a new methodology that Gartner's putting forth around the business value of data. In the last three to five years, the notion of data has flipped from one of a liability that has to get managed to one of an asset that you can leverage. What about that balance? How do you see that? I wonder if you could describe your perspectives on that. Well, for us, it's really important because we're a regulated entity, and so we have a single prudential regulator in Canada, and they require us to have reserves at a certain level. They require us to have financial information done in a certain way, and in our organization, which is highly complex, so we have data coming in from all of these Blue Cross plants across the country, and in some cases, they're coming in from three or four different source points from those locations. So, for us, data management is critical, and if it's not, then we have to wind up being the people that clean the data up and have to move on, which is entirely inefficient for us to do. So, for us, it's important because at the end of the day, we're a regulated entity, and we have to be sure that we've got our reserves right, and we have our financial reporting correct. Okay, so that compliance, that's the cost of doing business. It is. But there's still a flip side of that coin, which is how do I get more value out of all this data? And that conversation has been accelerating lately, hasn't it? It has, and it's interesting you mentioned that because I was speaking to a group of mostly actuaries in the spring in New York, and we were talking about stress testing, and we were getting into the minutia of this, and I'm not an actuary myself, but it's something that I know just a little bit about, enough to be dangerous, I guess. But in any case, during the course of the discussion, I realized that their focus was very much centered on the efficacy of the models that they have and kind of whether they're doing the things that they would like it to do. And I realized that there was a point that perhaps they were missing, and I raised that to them and said, you know, you may have models that work, and models that do what you want them to do, but unless they're actually bringing value to the decision makers at the board and the C-suite layers, then you may have a problem there. And I mentioned that in the wake of the 2008 financial crisis, a lot of, I shouldn't say a lot, but some boards, particularly in the financial services area, found out certain things that they really didn't know were going on before, but the technical and financial people in the organization stood up and said, but we told you those things. Those things were actually in the reports that we gave to you. So I suspected some of the problem there was around governance, but clearly also, there was a disconnect between the kind of work that was being done with the data at the technical level and how that was being fed into the, I'll call it the decision-making ecosystem, so that at the end of the day, at the board level, they were actually getting information that was of value to them and would support the decisions that they were making. So that's a process and a communication gap, right? Very much so, and you know, I suspect that you could put all of those things under the umbrella of governance, but clearly data quality and data management has to flow through that ecosystem ultimately to a situation where the board or the C-suite is getting real value for that and they're able to make the kind of decisions that they can live with in the future. One of the interesting things about the life business too is the fact that the focus, the horizon is so long and a lot of businesses, the decisions you make in year one, you may know by the end of year one or year two or year three whether or not they were good decisions you made. A lot of cases in the life business, you won't know till year 15, year 20, or perhaps even year 30 whether the decisions you made in year one were the right decisions. And I know that the superintendent of financial institutions in Canada has said that, of all the financial services companies that they regulate, the life insurance is the one that gives them the most challenge just because of the gap there between when they make the decisions and when the final result comes in. So I'm picturing a triangle. You've got consistency, you've got quality and you've got timeliness. As a CEO, what would you rather have? Consistency, quality or speed? We can pick two, yeah. Well, I think you need consistency and quality. I think those are the most important. Speed becomes an issue at some point but when you're looking at reserves and that's the big thing, it's capital. And the life insurance business is all about having sufficient capital, being able to deploy that capital. And you don't want to put too much capital in because then you're talking about ROI before. If you haven't done a good job in, for example, establishing the correct reserves, then you may be deploying more capital than you have to to support the liabilities that you have into the future. Conversely, if you don't do a good job at doing that, then you don't have sufficient capital and then the enterprise may not survive. So that's the real issue that you have, I think, in the life business is that it's important to have the right information that gets there because it will affect you as it relates to your cost of capital. It's interesting, I was going to ask you, I'm going to ask you as well. Take it off. How data has changed that business and you're talking about sort of the back end mechanics of how you deploy capital. Has data changed that aspect of the business as well? Has data changed sort of the front end of the business in terms of how you underwrite insurance? There's no question. And that's very much in motion right now, the front end. And I think that a lot of insurance companies are struggling on the individual space to find and kind of reinvent the demand for life insurance. And it's very much a cultural issue and it's something that in most of the traditional, mature markets like North America, there's issues there. There's challenges because the young people are just not culturally kind of oriented toward buying life insurance. Unlike the third world and the emerging economies where you find tremendous demand for life insurance. And that's why a lot of the big life companies now are focusing their capital and their attention on the Asian market because countries like China and India have tremendous growth opportunities for them. But I think in the more mature markets, that data and the quality of the data and the kind of insights that you can find are really critical for reinventing that very mature and very traditional life business. So first of all, first question is why is that dynamic different and safe for instance overseas? That's a good question. And I think that's in part a function of what we see about millennials. And I think that you'll see in most life companies that almost a disproportionate focus on understanding what's going on with the millennials. Even on the group side today, what you find is that in group benefits, what the companies are doing is pushing the decisions on benefits down to the individual employees. So whereas a generation ago, the companies would say we're providing you a life benefit worth a certain amount of money. Today what they're saying is, we're giving you a certain amount of money and a basket of goods that you can choose which things you want. And what we're finding is that they're not always choosing life insurance. And so that's very interesting and it's a challenge to the life companies that see that. Then as I say, the sense is that there's a very big cultural aspect to that as it relates to the millennials and what's important to them, what they value. Life is different than other types of insurance. I mean auto insurance, you have to have it. That's right. Now we're mandating, you've got health insurance. That's right. Life is an option. And you've got a lot of competitive alternatives. And is one of the ways to breathe new life to maybe make that a more attractive, longer term investment for folks? Absolutely, and that's one of the things that particularly the larger companies are looking at is how can we show this as something that would be beneficial as an investment. But I think that even that is a bit of a challenge because the focus that the millennials seem to have is very short-sighted. Like it's, they don't quite see out beyond maybe 10, 15 years. What's your angle on this, young man? Yeah, you're young, but what do you think? So this is really interesting to me. So I've had people try to pitch life insurance amongst my friends into other millennials and a way that is really effective I've seen is doing it as long-term investments. So as a counter to the traditional 401K, so right now I'm in that decision myself. I'm trying to decide if I should do the 401K or do a life insurance policy. So it's really interesting. I wanna have you say a pitch, any millennial out there, what is the pitch? Why should we go for life insurance? Well, that's really interesting because we've had those discussions about I've been at conferences where if you talk to a broker, what the story that they give to the young people, it's the same story that they were giving to young people 20, 30, 40 years ago, that it's about security. That if you're going to get married and that's another thing that has changed is that you don't have people getting married at an early age like perhaps you did a generation or two ago. And so the security aspect doesn't resonate as much now with people because there's a lower incidence of marriage at those younger ages. But that's the interesting point that the message really hasn't changed as far as that goes. And I think that you're right, Sam, that the insurance companies have now kind of pushed their focus more to the investment side so that they could make some connection there on a longer-term investment rather than purely security. But I think that's one of the reasons why the life companies are struggling is because they haven't necessarily changed with that. That over the years, as the demand for insurance from those younger age groups started to go down, they weren't really sure how to deal with that. And I think that, as I say, I think that's still an issue because the message is fundamentally the same that it provides security and that's not always something that resonates with this group of people. Well, it's a marketing challenge slash opportunity as well. We heard Sandy Pendlin yesterday saying that the information that you get from peer groups is actually a better predictor than if you're trying to go after individuals. So how has data affected the marketing aspects of your business? I think that's something that the companies are just now coming to grips with is to see how that will be impacted by that kind of thing, the social physics, as Sandy talks about. And I think that that's something that we'll be looking to see the results of in the coming years because it's a shame in some respects because it is a great product and it's something that's existed for so long but the people, the young people, they culturally just don't see it the same way and the message hasn't resonated as much in the past. Do you have a chief data officer in your organization? We don't but it's something that we have an operations area and I've frankly taken more of a lead in that because of the complexity of the organization where we've had to have the interaction with all the other Blue Cross plans. So I've tended to take that role and try to shepherd the message out to those Blue Cross plans about the importance of the quality of the data and how it impacts the information that they get back and ultimately sustaining the enterprise really. So you're the de facto data sawer? I'm the chief proselytizer for good data. So are you considering putting in that function or it sounds like it's a challenge because you need somebody who's got the purview of the entire organization and good jobs and authority to make stuff happen. I think that it's something that will likely evolve that will start on the operations side and as the organization perhaps grows or it becomes more complex. I think complexity is a big issue too. It's not simply the volume of data but it's the complexity of the data. So we have transactions that are seemingly quite simple. So we have relationships with our Blue Cross plans. They have relationships with clients but then it becomes more complex because they say, well, we want to reinsure only these types of transactions at this kind of situation. So we're basically dealing with exceptions. Where our whole lives revolve around exceptions. So exceptions mean a much greater challenge to manage the quality of that data. So I think that you're right. Over time we'll have to focus more on the quality and perhaps have leadership in a CDO. But I think what will drive that, not so much volume but it will be the complexity of the transactions that we have. So Jim, you're here, you're speaking to the panel this afternoon, maybe set that up for audience. So the panel was kind of a work in progress. I was contacted late for it but my idea for the panel was to focus on that idea of the ecosystem of decision making where you'd focus not simply on the quality of the data at the front end but also looking at how that impacts your decision making at the back end. And I hope to have a few CEOs sit on there but we kind of got started late. So I'm going to speak a little bit about that and set the stage for Ricardo Baron who's actually someone who works for Swiss Re, global reinsurance company, actually the largest reinsurance company in the world. And he heads up the big data analysis group for the Americas for Swiss Re based out of our monk. So he's going to speak about how they manage the quality of the data as it relates to their big data initiatives and talking about how they bring in both the internal data but also the external data and the challenges around managing the quality of the external data. And then as well you're going to bring a perspective of CEO perspective with the value of that data. Absolutely, at both the C-suite level but also the board. And I think that's something that's really important because the board only meets certain number of times a year and these aren't people who when they get together understand right away all the complexities and the intricacies of the business. So it's really important to understand clear, simple kind of messages that have to get to them. And although it has to be founded on quality data you have to be sure that you're giving them data that will lead them in the right direction. Excellent. All right Jim, well listen, thanks very much for coming on theCUBE. Thank you. Enjoy it. Thanks for being here anytime. Yeah. All right, keep right there. We'll be back with our next guest right after this. This is theCUBE. We're live from MIT in Cambridge. We'll be right back.