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Executives

William J. Lansing - Chief Executive Officer, President and Director

Michael J. Pung - Chief Financial Officer, Chief Investor Relations and Executive Vice President

Analysts

Michael McLaughlin

Fair Isaac Corporation (FICO) Morgan Stanley Technology, Media & Telecom Conference February 27, 2013 7:50 PM ET

Michael McLaughlin

Good afternoon, everybody. Thanks for joining us. My name is Mike McLaughlin with Morgan Stanley's Technology Investment Banking Group. I'm pleased to host today's session with FICO. Before we get started, I would encourage you to refer to the disclosures and cautionary statements on Morgan Stanley's website regarding forward-looking statements and the like. With me here today is Michael Pung, Chief Financial Officer of FICO; and Will Lansing, Chief Executive Officer. This will be interactive, of course. Please ask questions as we go. But why don't we start, Will, if you would offer for these folks a roadmap or schematic of FICO. It's a company that maybe is less well understood than it could be. And how do you think about the basic framework that helps understand the business?

William J. Lansing

So we call ourselves a predictive analytics software company. We're probably best known for FICO Scores, which banks use to evaluate consumer propensity to repay debt. We're about a $750 million business. We've got 3 major chunks of business. The first is the Scores business, which is, as I said, what we're known for. And that breaks into 2 pieces. One piece is selling Scores to credit bureaus who then turn around and sell it to banks, where they apply it to their data and sell it to banks to make origination decisions and then we have the consumer scores business where we sell scores and credit reports directly to consumers. The second big piece of our business is our Applications software business. It's about $0.5 billion business. And that business is primarily, although not exclusively, aimed at financial institutions. We have software that helps with originations. We have software that helps with collections and recovery of debt. We have software that is used in detecting fraud, credit card fraud in transactions in real-time. And we have customer management software into the banks. Then we also have some software that's more in the retail space marketing solutions. We've done a couple of additional acquisitions in the customer contact management space. And then the third big chunk of our business is we refer to it as the Tools business. And that consists of a rules engine, some optimization tools, and typically, that's used in custom analytics solutions where we'll take our tools and then wrap them with some professional services and solve problems, analytic problems for customers in various industries, but mostly financial services on a custom basis. So that's a thumbnail sketch.

Michael McLaughlin

And how would you describe the unifying theme across those 3 buckets and what it is that makes them work together as a whole as opposed to 3 separate businesses?

William J. Lansing

What we're really good at is analytics. So we grew -- our reputation started with this realization 40 or 50 years ago by the founders of the company that instead of having the old-time banker make the credit decisions on the basis of personal knowledge, personal familiarity with the customer, the bank customer, we could reduce some of the creditworthiness judgment to things that could be done with algorithms and analytics and then have much lower cost people make those decisions. And that was really what allowed a lot of the credit industry to develop the way it has in this country. So the analytics scientists are our strength. And from that, we've branched out into these other areas. We've picked up tools and then wrap professional services around analytics. And then the applications are all very analytics-heavy. They're designed to leverage our analytics. We have a lot of patents around it, and we'll talk about the future in a moment. But basically, where we think we're taking the company is leveraging these analytics on top of Big Data and into areas beyond financial services.

Michael McLaughlin

And when you think about that portfolio of businesses, I think it's fair to say that one of those businesses is a highly cash-generative, but GDP-like business. And the other 2 have the potential to grow faster than that and use some of that cash flow in a positive way in terms of investment and new product development. Is that the right way to think of that?

William J. Lansing

That is right. So our Scores business, which is the cash generator, is a very, very high-margin business. It's deeply embedded into the systems of the bank customers who use it. It doesn't grow quickly. It kind of moves with the economy because it's a function of volume, of originations in the credit business with consumer debt. The other 2 businesses are more like software -- more software-business oriented and has lots of growth potential.

Michael McLaughlin

So let's shift to the future then. You've done a couple of acquisitions since you've taken over the CEO role. There's been a good trajectory in terms of performance in stock price. How do you think about starting from this base, this ability to have a lot of free cash flow to use to invest for growth? Do you think about it more in terms of verticals products, delivery mechanisms?

William J. Lansing

It's probably worth taking a step back and looking at the business a couple of years ago. We took a hard look at our business a few years back, and particularly in the wake of the financial downturn when a lot of our business dried up with our bank customers and where originations volume and our Scores business went down. And we made the decision then to focus on a lot of financial engineering frankly around building value for shareholders during tough times for our company. And so we did a few things. We cut cost dramatically and improved margins, and then we took a massive free cash flow and used it to buy back stock. And then we went further and borrowed a lot of money to buy back even more stock. And so over the last 5 or 6 years, we've gone from 60 million shares outstanding to 35 million shares outstanding. We borrowed $500 million to buy back stock at an average of $24 and we sit at $44 today. The -- if you look at last year 2012, we did 9% revenue growth, 29% net income growth and 42% EPS growth. And so we had operating leverage through and margin improvement through cost-cutting and execution, and then we had this extra juice for EPS through stock buyback. We're proud of that record. I mean, I think we've made investors happy over the last couple of years. And at the same time, we feel like that's not a sustainable path for value creation. And so where we're pointed now is to use some of that free cash flow for acquisitions. And frankly, instead of just pressing on margins and net income leverage, we're actually reinvesting in the business in a pretty dramatic way because we're at this point where Big Data, an overused term, but Big Data is opening up all kinds of new opportunities and the ability to do analytics on top of Big Data which ought to be a natural place for us to be a dominant player, is a great big opportunity. And so we're investing in our Applications business, in our Tools business to be well positioned for that. So we have an M&A program on and we have a lot of investment for organic growth.

Michael McLaughlin

Is it most productive to think about the verticals that are priorities for you to grow in or products suites that, how would you think about that?

William J. Lansing

So we think in terms of a multi-part strategy. One part is to diversify beyond the financial services vertical where we're strong. And so we have all this analytic capability. Our solutions are horizontal solutions that play in other industries. And so we are focused on where we can take those analytics to other verticals. We look hard at retail, we look hard at health care as natural opportunities for us. At the same time, we are making product investments that are in the financial services base and outside. We're investing pretty heavily in moving from on-premise software to SaaS or SaaS-enabling all of our products, almost all of our products and we're developing new products that will allow people to leverage our analytic tools in Big Data infrastructure.

Michael McLaughlin

Analytics is a attractive sector, it's a popular sector. Acquisitions, as a general rule, this sector tend to be expensive. Maybe you could describe some of the deals you've done so far as they may be representative of how you approach it both in terms of size, valuation and theme.

William J. Lansing

So the kinds of deals we've done over the last year, I've been CEO for a year and over the last year, we've done 3 deals. They're smaller deals. They are, the way we think about it as we look for either technology tuck-ins or product extensions, things that naturally bolt on to our existing products that our salespeople can sell easily. Or -- and we haven't done any of these but we also look at potential to move into verticals, other verticals where we're not strong. The 3 that we've done, the first one was Entiera, which is a campaign management business. The second, where the goal was to take our very superior analytics and then put a very attractive UI and campaign management tool on top of it, so that retail customers, for example, could use our strong analytics. The second one we did was called the Adeptra, is called Adeptra. That's a customer contact management business. SMS, messages, calls to our customers' customers. The theory there was we're in this analytics business, we produce a decision for our customers and we hand it to them and then they have to do something with it. Sometimes they do something good with it, sometimes they don't. We thought if we took the solution all the way through to execution and to talking to our customers' customer in the most optimized way, we would provide a more robust solution for our customers and kind of close the loop, and that turned out to be true. That's the added benefit of being a very natural product extension for us for our fraud detection business and for our collections and recovery business. And then the third and last one that we just did is called CR Software, that's a collections and recovery business. And it was -- that's a product purchase, product extension. We've got system of record with it which we didn't have before. Good software and we have a very strong market for it and our salespeople can sell it very easily.

Michael McLaughlin

Let me take a breath and see if there's any questions from the audience. If not, I'll keep going. In terms of the -- from the public record, you can more or less determine how big those were. But is that the mode of what you would expect going forward as opposed to big deals or truly tiny deals?

William J. Lansing

We went through a number of years without doing very many deals at all. We are very kind of inwardly focused. And so as we ramp up our M&A activities, we think it's important that we prove to the investor community that we know what we're doing. And so we're taking it, I would say, slowly and going smaller. We're not betting the farm on anything. So far, the 3 that we've done have gone extremely well. Smooth integrations, not a hiccup, just gone really, really smoothly. So that's one reason to do deals of the size that we've done, kind of $100 million size deals. We also have a constraint which is our debt covenants which prevent us from doing anything too big without issuing equity. We are, if you know us, you would know what we are really stingy with our equity. We don't like issuing stock for anything. And not that we never would, but we have a strong bias to doing deals with cash and -- cash and debt which is how we've done the ones today. And that puts kind of a natural ceiling on the size of the deals that we can contemplate. It's not to say we never would do something bigger, but we think twice before we issue stock, and then we think a third time.

Michael McLaughlin

As you think about growth goals for the next few years, your internal goals and the goals that the Street has for you, what part of that would you expect would be due to acquisition-driven versus organic investment versus just the business that you have today growing naturally?

William J. Lansing

We think that our growth is going to come probably in roughly equal parts from M&A and from organic growth. But some of the factors that will influence that split are out of our control. So if the markets get frothy and we can't buy other companies at fair prices, we would be out of that business. We just -- we're not -- it doesn't have to be M&A. We can do a lot of things organically, and we're happy to do that. If we can get a lot of deals, we'll do deals, but if we get the right kind of pricing. On the organic side, we're often faced, that's not unique to FICO, but as an operator, constantly faced with a make buy decision. And it is really typical that we can go buy a company for some amount of money that has revenue and customers and EBITDA or we have a pretty strong development community and smart guys who can build the same thing. And that just means we got to spend P&L dollars today with no return on it that's visible to The Street and wait a year, 15, 18 months to get revenue and to do something with it. And so the way we think about that is we want to do as much of that as we can possibly afford to do without ticking off the investor community. And so just for example, I said 29% net income growth last year. This year, we promised 9% net income growth. And the difference between the 29% last year and the 9% this year is not us off partying, it's us pouring money into development of products for next year. We don't feel comfortable taking that growth rate to zero. We're not comfortable taking it negative. So that's the limit on our organic -- on expanding our organic growth. On the M&A side, we kind of fill up the slack with what free cash flow we have, where we can find deals that are priced right and that meet kind of our investment criteria.

Michael McLaughlin

And what about top line objectives that you've at least communicated to them?

William J. Lansing

Yes. Your top line, we're looking for double-digit revenue growth in some kind of a mix between M&A and organic.

Michael McLaughlin

So the high single-digit, net income growth would reflect the greater investment on a higher top line growth.

William J. Lansing

Exactly.

Michael McLaughlin

Mike Pung, question for you. Buyback has been a big part of the strategy, as Will described, in years past. How do you think about return of capital versus these other needs going forward?

Michael J. Pung

Yes, so as Will mentioned during the recession, we spent a fair amount of time restructuring our internal business and we built a war chest of cash. At its peak, it was almost $500 million of cash around the 2010 timeframe. We took a look at what our alternatives were for using that cash at the time and our shares were being traded at a very steep discount. And our view based on where we saw our business growing simply as a result of an improving economy. And we went essentially all-in with the share repurchase plan. And during that 3-year timeframe, we generated probably $300-plus million of cash, just free cash on our own, and we took $500 million, some off the balance sheet and some off the free cash flow and we got extremely aggressive with the share repurchase plan for other share count down 25% during that 3-year timeframe. And as we were exiting the recession and starting to see improvement across all parts of our business, we were sitting on what still was $250 million of cash with very low leverage, with debt that was laddered out over a 7- to 10-year period of time. So very strong balance sheet as far as the eye could see at that point in time. While we took our share count down as dramatically as we did, obviously, our share price went up quite dramatically over that same timeframe. And the investors that we had during that timeframe appreciated the way in which we were returning cash through the buyback. But really, the desire became more to grow the top line of the business and take advantage of some of the margin leverage that we had created through some of the restructuring we have done. And so as Will came on about a year ago, we were sitting on a couple hundred million dollars of cash, still generating a fair amount and we took a look at our ability to leverage additional incremental revenue, and we compared that back to a share buyback plan in some of the M&A that we were doing and clearly, we made a choice to take most of our free cash flow, not all of it, but most of it, and put it into a growth approach. And so as a result, we still sit on a lot of cash and we still generate a fair amount. We drove our leverage from what was under 2x our EBITDA up to somewhere around 2.3x or 2.4x. So gradually, we brought it up despite the fact that we did $150 million worth of acquisitions. And we have since brought the number down, and we are basically looking at opportunities to continue to grow the top line in '14 and '15 through M&A. And to the degree, those opportunities don't sit there for us, we'll be happy to go back in and buy shares based upon where we're headed.

Michael McLaughlin

And if heard you correctly, your approach to making that decision is very much a return on investment, whether it's buying something, investing organically or buying back stock.

Michael J. Pung

Absolutely. It was a very low risk and a very easy investment for us to make in the $25 share amount to repurchase our own shares and we gladly did that. And we would continue to buy back our shares in lieu of finding an opportunity to grow the top line and ultimately deliver the leverage that we believe exists in the software side.

Michael McLaughlin

Got it. Pause again for any questions from the room. Will, how about helping folks understand the competitive environment across the 3 businesses. Analytics is a big space. If you could maybe be more specific as to who you compete against the most vertical or those product segments.

William J. Lansing

So the Scores business, we sell the Scores through the big 3 credit bureaus to the banks. There are alternatives that credit bureaus themselves have developed a score called VantageScore. It has not gotten a lot of traction and all 3 bureaus still sell FICO Scores happily to the banks. So there's not that much competition around our Scores business. We have a -- we're kind of designed in, in a lot of places.

Michael McLaughlin

And before you go on from there, does that present a risk in your view that investors should be worried about that you're going to be displaced, technology shift that will be step function change in the leadership position with that?

William J. Lansing

The big banks all would like to have other ways of thinking about evaluating risk in addition to our scores. And so they have, the really biggest banks have their own analytics team that are constantly developing their own stuff. They do champion challenger, but they almost always use our stuff. The FICO Scores are very much part of the fabric of the banking industry, and I don't think they're going anywhere anytime soon. So no, I would not call that a big risk. There's some things that are truly low risk. For example, Fannie and Freddie have mandated that FICO Scores have to be part of a mortgage origination. So that puts you in a very low risk territory. But even where it's not a matter of law, as a matter of practice, the Scores are really deeply embedded. So not a lot of risk there. Maybe not a lot of growth either. It might be just GDP growth, but not a lot of risk. On the Applications software business, there is some risk. There's competition that would like -- that we compete in every deal. We compete with others. We have industry-standard, industry-leading software in certain of our categories. So our Falcon fraud detection product looks at 2/3 of the credit card transactions in the world in real-time. It's a big statement. And we're pretty good at identifying fraud and there's not a lot of good reasons to use somebody else. Our stuff works incredibly well. We have fraud down to 7 basis points. And so, yes, there are competitors who would love to displace us and every once in a along while, some bank tries out a competitor's product. But we really do have the dominant product in fraud detection -- credit card fraud detection. Our TRIAD product, customer management product, is kind of an industry standard.

Michael McLaughlin

And be a little more specific what customer management means.

William J. Lansing

This is a product that lets you evaluate your credit relationship with the consumer, when to increase a line, when to shrink a line, when to make additional type of offers. Then we have others that are more competitive, but now seeing the origination space, there are people who compete with us and we're not dominant by any means.

Michael McLaughlin

And then again, sorry, by origination, you mean the software that manage the origination process?

William J. Lansing

Exactly. This is the software that you use to figure out originating auto loans or mortgages, for example. In the collections and recovery space, we have a pretty significant business. We're not the only guys in it, but we're one of the big players there. And then with our recent purchase of Adeptra, we've become, dominant is a wrong word, but that much stronger franchise in collections and recovery. And then, let's see what I missed. The DM, OM, Falcon, TRIAD. I'm missing something.

Michael J. Pung

Marketing business.

William J. Lansing

Oh, yes. We go outside of financial institutions, we have a business around, a product called Analytic Offer Manager and this is true one-to-one marketing. This is where we crunch huge volumes of transaction data for retailers, and point-of-sale data. And on the basis of that, we make recommendations on what offers should be made to the consumer. And this is in the category of every bricks and mortar retailer wants to be able to do for its customers, what Amazon does for its customers. And they need to start to leverage the customer data to do targeted communications, truly targeted, not gross but really targeted so they don't burn out their customers. And so we have the technology for that, and so we're building that. Yes?

Michael McLaughlin

Can you walk me through -- can you explain how the data flows, how it gets from retail to you guys, the decision back, is it capture by their credit bureaus and they...

William J. Lansing

No. So in that case, that's actually -- this is Analytic Offer Manager. We used to call it Retail Action Manager. Now it's Analytic Offer Manager. It's a SaaS product, it's -- we host it. We pull all the transaction data directly from the retailer. It comes to us, we crunch it and then we hand it back to the retailer recommendations on what offer should go to which customers. We call it time-to-event marketing, so we'll tell you exactly -- we'll tell you that Johnny comes in to the store every 6 weeks, this is what he buys when it comes in. He's this price-sensitive, he'll be here in 11 days, 4 days from now, you should send him this offer, priced this way.

Michael McLaughlin

So it's by consumer...

William J. Lansing

One by one by one.

Michael McLaughlin

You don't know, you don't identify an individual consumer and see what retail transactions that individual make?

William J. Lansing

No, we do. We do. It's truly targeted individual consumers.

Michael McLaughlin

But only at that retailer.

Michael J. Pung

Using that retailer's information.

William J. Lansing

At that retailer. At that retailer. Yes, it's for that retailer, it's one by one.

Michael McLaughlin

It's similar to what Square was talking about this morning in that they're trying to leverage their transaction data.

William J. Lansing

I wasn't at the presentation, so I don't know how far they're going with it. The big challenge with the payments processing guys is they tend not to have the SKU level detail in the transaction. So they know what transaction -- now, Square might be different. But at the Visa and MasterCard level, they get the transaction data but they don't get the SKU level data underneath it, which really makes it hard to make deep recommendations. You can do some things with it, but not enough. American Express, by comparison, has the SKU level data inside the transaction. And Square probably does too. Yes?

Michael McLaughlin

One more question. What would be your footprint, what would be your -- are you guys the dominant market players, is this a niche opportunity?

William J. Lansing

Oh, no, no. We're just getting started, so this is foray out of financial services for us. And this is us takes -- so here, you're FICO, you got these fabulous analytics scientists, can do these unbelievably precise predictions about things, typically with a certain amount of overhead, with some costs associated with it, where stakes are high. We have become embedded. Mortgages, you don't want a big mistake down on mortgage. In retail marketing, it was -- it was -- the stakes are much lower, and if we send someone a toothpaste offer instead of a detergent offer it's just like the world's not going to end. And so we did pretty good segmentation, not we, but the industry does pretty good segmentation, pretty crude communications, and that was good enough for many years. That is the state-of-the-art today. It's pretty good segmentation and pretty good communication. But they're competing with Amazon. Amazon, we all know it's like super tailored, refined, precised, no waste, we don't burn up customers, every communication is relevant, every offer matters and these retailers need to get to that point. And so now, it's time for FICO, for Fair Isaac quality analytics to inform these marketing communications. And so that's kind of where we are right now. We're in a couple of retailers, we're not widespread, by any means. That's a new business for us.

Michael McLaughlin

But just to emphasize one point, I think it's key to understand that the relationship of you and the user of this product is direct, that it's not with the bureaus in between...

William J. Lansing

Yes, that's right. That's right.

Michael McLaughlin

Not with any other broker that's providing you the data, your exact relationship.

William J. Lansing

Correct. That's exactly right.

Michael McLaughlin

Did you have a question?

Unknown Analyst

[indiscernible] sorry, just how big are the -- your customers in that segment? I mean...

William J. Lansing

Oh, these are really big. These are your big box guys, really big guys. A deal might be $12 million over -- annually over a number of years. I mean, these are really big. Doesn't have to be -- we're actually trying to get the price of the product down so we can go to a different class of retailer.

Unknown Analyst

And just Big Data. The trouble about these database has been now so much faster than you can carry the information. I mean, you mentioned that they [indiscernible] can do it almost real time. Does that change the opportunities and what impact would that have on analytics and what you do?

William J. Lansing

A pretty big impact, but not as big as some people think. So the way we think about it is we've grown up in a little data world. We grew up in a world where we're constrained and how much data could be stored and manipulated, where there were constraints on the structure of the data that you could look at. It had to all be at the same structure or else you couldn't use it. You typically, you couldn't do it in real time, you couldn't process it fast enough in solid batch. Those are the constraints that are all being relaxed by Big Data. And so now -- and so in a world in which we're constrained that way, the whole goal is, let's find the data set that is the most predictive data set. Let's find how to get the most core value out of little data. And that's how our industry was built. The financial services industry is built around credit bureaus capturing trade line data, which is credit card payment data. They capture that because it's highly predictive of whether you're likely to repay debt in the future. And so that's the data they capture and that's the data that today still informs all these decisions. Now there's other stuff that's supplemented with it. That's kind of a core data set. You go to a Big Data world and suddenly it becomes interesting to add additional data sets, because you can. You can mix and match data from different sources. Admittedly, on the margin, the data has less core value, you have diminishing utility for that data. But any predictive value greater than 0 becomes interesting. So theoretically, we ought to be able to consume wide -- huge volumes of data, wide variety of data and do it all in real time and provide more predictive value than we do today with these limited data sets. The problem is that the industries in which we operate are all built around systems that are pretty much little data systems. And so it's all good and well to talk about a future in which we're going to consume all the data in the ether and give you the best answer possible. We can -- the analytics part of it is not that constrained. The constraint is the way all the data is held and the way these banks operate. There is an extreme, one could imagine an extreme in which you can see -- consume huge volumes of data in all different kinds of forms and then use machine learning to develop points of view about -- to determine the predictive decisions. That's pretty far out, that's really pretty far out. I think the way that this is going to evolve, we'll leverage some of the Big Data opportunity which is mostly around variety, mixing and matching structure and unstructured data, data from different data sets. We'll leverage the fact that the infrastructure allows us to do that now, and we'll use that to make decisions instead of just credit bureau data. And that's where the banks are going, and that's probably where the retailers would go. In some industries, it'll be a little different. I mean, you go to health care and mapping disease markers and you might wind up with machine learning around some of that.

Michael McLaughlin

And with that, we're out of time. Thank you, Will. Thank you, Mike. Hopefully we'll see you all tomorrow.

William J. Lansing

Thank you. You guys are to be commended for coming to the last session and hanging in there. I know you all think FICO's a pretty great opportunity, so I understand why you're here. Thanks.

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