>> Announcer: From the Corinium Chief Analytics Officer Conference Spring, San Francisco It's theCUBE. >> Hey welcome back, everybody, Jeff Frick here with theCUBE. We're in downtown San Francisco at the Corinium Chief Analytics Officer Spring Event about a hundred CAO's as opposed to CDO's talking about big data, transformation and analytics and the role of analytics and a lot of practitioners are really excited to have our next guest. He's up from Mexico City, it's Jose Murillo. He's the chief analytics officer from Banorte. Jose, great to see you. >> Thank you for having me, Jeff. >> Absolutely, so for people that aren't familiar with Banorte give us a quick overview. >> Banorte's the second largest financial group in Mexico. We, for the last, during the last three years were able to leapfrog city bank. >> Congratulations, and as we were talking before we turned the cameras on, you and your project had a big part of that. So before we get in it, you are a chief analytics officer. How did you come in, what's the reporting structure, how do you work within the broader spectrum of the bank? >> Well I moved to Banorte like about five years ago from, I was working at the central bank where I spent about 10 years in the MPC, the Monitor Policy Committee, and I was invited by initially by the president of the board and when the new chief operating officer was named he invited me to, to lead a new analytics business unit that he wanted to create. And that's the way that I arrived there. >> Okay so you report in to the COO. >> He's the COO/CFO, so he's not only a very smart guy but a very powerful guy running the organization. >> And does the CIO also report to him? >> The CIO, the CDO, the CMO report to him. >> Okay so you have a CDO as well Chief Data Officer. >> We have a CDO who I work very close with him. >> We could go for a long time I might not let you leave for lunch. So I'm just curious on the relationship between the CDO and the CAO, the data officer and the analytics officer. We often hear one or the other, it's very seldom that I've heard both. So how do you guys divide and conquer your responsibilities? How do you parse that out? >> I guess he provides the foundation that we need to find analytics projects that are going to transform the financial group and he has been a very good partner in providing the data that we need and basically what we do as the CAO we find those opportunities to improve the efficiency, to bring the customer to the center, and be able to deliver value to our stakeholders. >> Right, so he's really kind of giving you the infrastructure if you will, of making that data available, getting it to you from all various sources, et cetera, that then you can use for your analytics magic on top. >> Exactly >> Okay, so that's very good, so when we sat down you said an exciting report has come out from, I believe it was HBR, about the tremendous ROI that you guys have realized. So you tell the story better than I, what did they find in your recent article? >> Well in the recent article from the Harvard Business Review is how Banorte has made its analytics business unit pay off. And what we have found in the past two and a half years is we've been able to deliver massive value and by now we have surpassed a billion dollars in net income creation. From analytics projects made on cost saving strategies and revenue generating projects. >> So you paid for yourself just barely >> Yeah. >> No I mean that's such a great story, just barely 'cause it's so it's so important. So as you said, that billion dollars have been realized both in cost savings but more importantly on incremental revenue and that's really the most important thing. >> Exactly >> So how are you measuring that ROI? >> So basically the way we measure it is on cost saving strategies that are related to a risk operational and financial cost. It's the contemporary news effect. And that can be audited. And on the other side, on revenue generating projects, the way we do it is we estimate the customer lifetime value, which is nothing else than the net present value of the relationship with our customers, so we need to estimate survival rates plus the depth of the relationship with our customers. >> So I just love, so you're doing all kinds of projects, you're measuring the value of the projects. What are some of the projects that had a high ROI that you would've never guessed that you guys applied some analytics to and said wow, terrific value relative to what we expected. >> Let me tell you about two types of projects. The first project that we started on was on cost of risk cutting strategies. And we delivered massive value and very quickly. So that helped us gain credibility. And the way we do it, we did it, is like to analyze a dicing of the data where we had excessive cost of risk. And in the first year, actually, that was the first quarter of Operations, we yielded about a 25% incremental value to the credit card business. And after that, we start to work with them and started the discovery data process. And from there, we were able to optimize analytically the cross cell process. And that's a project that has already a three year maturity. And by this time, we are able to sell, without having any bricks or mortars, about 25% of the credit cards sold by the financial group. If we were a territory within the financial group, we would be the largest one with 400 basis points lower on cost of risk, 30% more on activation rates. And it's no surprise that the acquisition cost is 30% less, vis-a-vis our most efficient channel. >> Right, I just want to keep digging down into this, Jose, there's a lot of this stuff to go. I mean, you've been issuing cards forever. So was it just a better way to score customers, was it a better way to avoid the big fraud customers, was it a better way to steal customers maybe from a competitor with a competitive rate that you can afford, I mean, what are some of the factors that allowed you to grow this business in such a big way? >> I guess it's something that has been improving during the first three years. The first thing is that we made like, a very simple cascade on seeing why we were not that efficient cross cell process. And we kind of fixed every part of it. Like on the income estimation models that we had, and we partner with the risk department to improve them. Up to the information that we had on our customers to contact them, and we partner with data governance to improve those. And finally, on the delivery process and all the engaging process with the customers. And it seemed that we were going to find something that was going to be more costly, but it was something that we had at the center of the customers so that it was more likely for them to go and pick up the card and we deliver it to their homes. And finally, that process was much more efficient and the gains that we had, we shared them with our customers. And after three years, we've done things with artificial intelligence to have much better scripts so that we are better able to serve our customers. We do a lot of experimentation, experimentation that we didn't do before. And we use some concepts from behavioral economics to try to explain much better the value proposition to our customers. >> So I just, I love this point, is that it was a bunch of small, it was optimizing lots of little steps and little pieces of the pie that added up to such a significant thing, it wasn't like this magic AI pixie dust. >> Initially, it as a big bang, and then it has been something incremental that has since, it's a project that at the end of the day, we own, and it's something that we are tracking. We are willing to put all the effort to have all the incremental efficiency within the process. >> So people, process, and technology, we talk about, those are the three pieces always to drive organizational change. And usually, the technology is the easy part, the hard part is the people and the process. So as you and your team have started to work with the various lines of businesses for all these different pieces. Promotional piece, customary attention piece, risk and governance piece, cross sale pice, how has their attitude towards your group changed over time as you've started to deliver insight and all this incremental deltas into their business. >> I guess you are hitting just on the spot. Building the models is the easy part. The hard part is to build the consensus around, to change a process that has run for 20 years, there's a lot of inertia. >> Right, right. >> And there are a lot of silos within organizations. So initially, I guess, the credibility that we gained initially helped us move faster. And at the end of the day, I think what happens is the way that we are set up is that the incentives are very well aligned within the different units that need to interact in the sense that we are a unit that is sponsored by the, corporately sponsored, and we make it easier for our partners to attain their goals. So that's, and they don't share the cost of us, so that helps. >> And those are the goals they already had. So you're basically helping them achieve their objectives that they already had better and more efficiently. >> Yeah, and you are pointing out correctly, it's the people, and besides the math, it's a highly, you could say diplomatic or political position in the sense that you need to have all the different partners and stakeholders aligned to change something that has been running for 20 years. >> Right, right. And i just love it, it's a ton of little marginal improvements across a wide variety of tough points, it's so impactful. So as you look forward now, is there another big bang out there, or do you just see kind of this constant march of incremental improvement, and, or are you just going to start getting into more different businesses or kind of different areas in the bank to apply the same process, where do you go next? >> Well, we started with the credit card business, but we moved toward the verticals within the financial group. From mortgages, auto loans, payroll loans, to we are working with the insurance company, the long term savings company. So we've increased the scope of the group. And we moved not only from cost to revenue generating projects. And so far, it has been, we have been on an exponential increase of our impact, I guess that's the big question. The first, we were able to do 46 times our cost. The second year, we made 106 times our cost, the third year, we are close to 200 times our cost with an incremental base. And so far, we've been on this increasing slide. At some point, it's, I guess, we are going to decelerate, but so far, we haven't hit the point. >> Right, the law of big numbers, eventually, you got to, eventually, you'll slow down a little bit. All right, well Jose, I'll give you the last word before we sign off here. Kind of tips and tricks that you would share with a peer if we're sitting around on a Friday afternoon on a back porch. You know, as you've gone through this journey, three and a half years and really sold you and your vision into the company, what would you share with a peer that's kind of starting this journey or starting to run into some of the early hurdles to get past. >> I guess there are two things that I could share. And once you have built a group like this and you have already, the incentives aligned and you have support from the top in the sense that they know that there's no other way they want really to compete and be successful, and suppose that you have all these preconditions set up and suddenly, you have a bunch of really smart people that are coming to a company, so you need to focus on ROI, high ROI projects. I;s very easy to get distracted on non-impactful projects. And I guess, the most important thing is that you have to learn to say no to a lot of things. >> Speaking my language, I love it. Learn to say no, it's the most important thing you'll ever, all right, well Jose, thanks for spending a few minutes and congratulations on all your success, what a great story. >> Thank you for having me, Jeff. >> Absolutely, he's Jose, I'm Jeff, you're watching theCUBE from the Corinium Chief Analytics Officer Summit in downtown San Francisco. (electronic music)