Filed by Fair, Isaac and Company, Incorporated Pursuant
to Rule 425 under the Securities Act of 1933 and
deemed filed pursuant to Rule 14a-6 under
the Securities Exchange Act of 1934

Subject Company: HNC Software Inc.

Commission File No. 333-89268

Date: June 25, 2002

        This filing relates to the proposed merger between Northstar Acquisition Inc., a wholly-owned subsidiary of Fair, Isaac and Company, Incorporated, and HNC Software Inc., pursuant to an Agreement and Plan of Merger, dated as of April 28, 2002. The Agreement and Plan of Merger was filed by Fair, Isaac under cover of Form 8-K on April 29, 2002 and is incorporated by reference into this filing.

        This filing contains forward-looking statements that involve risks, uncertainties and assumptions. All statements other than statements of historical fact are statements that could be deemed forward-looking statements. For example, statements of future product offerings, expected synergies, timing of closing, execution of integration plans and increases in shareholder value as a result of the merger, are all forward-looking statements. Risks, uncertainties and assumptions include the possibility that the market for the sale of certain products and services may not develop as expected; that development of these products and services may not proceed as planned; that the transaction does not close or that the companies may be required to modify aspects of the transaction to achieve regulatory approval; that prior to the closing of the proposed merger, the businesses of the companies suffer due to uncertainty; that the parties are unable to successfully execute their integration strategies, or achieve planned synergies; and other risks that are described from time to time in Fair, Isaac's registration statement on Form S-4 filed May 29, 2002, as amended, and its SEC reports (including but not limited to its annual report on Form 10-K for the year ended September 30, 2001, and subsequently filed reports); and other risks that are described from time to time in HNC's SEC reports (including but not limited to its annual report on Form 10-K for the year ended December 31, 2001, and subsequently filed reports). If any of these risks or uncertainties materializes or any of these assumptions proves incorrect, Fair, Isaac's and HNC's results could differ materially from Fair, Isaac's and HNC's expectations in these statements. Fair, Isaac and HNC assume no obligation and do not intend to update these forward-looking statements.

        Fair, Isaac and HNC have filed with the SEC a definitive joint proxy statement/ prospectus and other relevant materials in connection with the merger. Before making any voting or investment decision with respect to the merger, investors and stockholders of Fair, Isaac and HNC are urged to read this joint proxy statement/prospectus and any other relevant materials filed with the SEC because they contain important information about Fair, Isaac, HNC and the merger. The joint proxy statement/prospectus is being sent to the stockholders of Fair, Isaac and HNC. In addition, the joint proxy statement/prospectus and other relevant materials, and any other documents filed by Fair, Isaac and HNC with the SEC, may be obtained free of charge at the SEC's web site at www.sec.gov. In addition, investors and stockholders of Fair, Isaac may obtain free copies of the documents filed with the SEC by Fair, Isaac by contacting Fair, Isaac Investor Relations, 200 Smith Ranch Road, San Rafael, CA 94903-5551, 415-492-5309. Investors and stockholders of HNC may obtain free copies of documents filed with the SEC by HNC by contacting HNC Investor Relations, 5935 Cornerstone Court West, San Diego, CA 92121, 858-546-8877.

        Fair, Isaac and HNC, and their respective executive officers and directors, may be deemed to be participants in the solicitation of proxies from the stockholders of Fair, Isaac and HNC in favor of the merger. Information concerning the interests of Fair, Isaac's executive officers and directors in the



merger, including their ownership of Fair, Isaac common stock, is contained in its Proxy Statement for its Annual Meeting of Stockholders held on February 5, 2002 and in the joint proxy statement/prospectus. Information concerning the interests of HNC's executive officers and directors in the merger, including their ownership of HNC common stock, is contained in its Proxy Statement for its Annual Meeting of Stockholders held on May 28, 2002 and in the joint proxy statement/prospectus. Copies of such proxy statements may be obtained without charge at the SEC's web site at www.sec.gov.

        * * *

[Transcript of Thomas Weisel Growth Conference held on June 20, 2002]

Tom Ernst:
Thomas Weisel
Partners
  Thanks for joining. This morning, I would like to thank Tom Grudnowski and Ken Saunders. Tom Grudowski is the CEO since 1999 of Fair, Isaac and Company, previously with Anderson Consulting. And Ken is the CFO of HNC Software, joined HNC I believe in 1997, CFO in '99.

Ken Saunders:
HNC Software

 

Correct.

Tom Ernst:

 

And one of the things we look for as analysts are abuses in terms of corporate spending, big fleets of transportation, air fleets. Fortunately, these guys are—their fleet is a motorcycle. I think between the two of you we have too many, a dozen, too many, a little bit more than that. Anyway, Fair, Isaac and Company and HNC have announced their intentions to merge. And so we've got senior executive people. As a background, Tom Grudnowski if you can explain to us, sort of in simple terms, what does your software do, your services do for customers and who are your customers, both Fair, Isaac and HNC.

Tom Grudnowski:

 

We are a predictive software company. And so, we create solutions that require usually three things, some of them model data, from which we can apply some type of equations into some type of software that generates an application solution. So we are a solutions company selling software that does something related to predictions. Of course, the most famous product that we have a very good position in is our credit scoring related products, which involves data from the credit bureaus, software that we create and the distribution of the solutions through a variety of channels. So our customers tend to be banks, credit card companies, B2B companies. We sell our services to banks, to financial institutions, to retailers, to—in the past, primarily the companies that were focused on credit-related types of predictions. Now in the last couple years, we have extended that to a variety of other types of predictions. But, in general, that is what Fair, Isaac does. It has been around for almost 50 years. It was founded by some entrepreneurs who were trying to apply mathematics to helping develop solutions that help companies interact with their customers. So we are big on figuring out how customers behave and writing equations that will predict how a customer will behave, which is a great space to be in these days.

 

 

HNC does the same thing, except in the fraud space. They use data and analytics to make predictions about whether you are a fraudulent character, not whether or not you are going to pay your bills. So a similar technology, background, similar culture. You can see how customers that transcend the financial services space will primarily [probably] sell financial services. HNC has got some beachheads in some other industries which will be very helpful for us—healthcare, government. We are working hard in the government segment on some of this homeland security stuff, etcetera.

Tom Ernst:

 

If you look across both companies, you have got a large number of applications and uses of the technology. Maybe from the HNC side, Ken Saunders, if you can—some of the other types of applications and uses of HNC technology.

 

 

 


Ken Saunders:

 

Sure, as Tom Grudnowski mentioned, we leverage predictive technologies and analytical solutions as well as decision support systems. And the technology, broadly speaking, addresses our customers' problems helping to target the right customer, the prospects, acquiring those customers under the correct terms, and then retaining and managing those customers throughout their life cycle. And just like the Fair, Isaac product, the key to our product is positioning the technologies in key leverage points. HNC, for example, with one of their risk management products for fraud will sift that analytic out in the transaction system. So if you are swiping your credit card or connecting with you cell phone, there is an analytic out there in that transaction stream saying if it is okay to do it or not.

 

 

Also, the predictive technologies are used to review and profile customers with respect to their transactional activity, relative to product offerings, marketing constraints and so forth to create the proper recommendation for an analytic solution, for a cross sell recommendation. So the products span a wide range from targeting through acquisition through fraud and risk management. I think where we were start marrying the companies a little bit is where Fair, Isaac's strength in the credit account management areas and really taking the analytical solutions kind of to the next level in the whole marketing area where we have a smaller segment. They've got a whole operating system around that. So there is quite a few synergistic opportunities within these two companies.

Tom Ernst:

 

Now, both Fair, Isaac and HNC are rather unique for software companies, in the way you engage customers. They pay for your software and the way you build your business model. Can you explain a little bit about how that actually—what's the first of the business model?

Tom Grudnowski:

 

Sure. Fair, Isaac and HNC sell two things. We sell razors and we sell razor blades. Razors are the software platforms that you can plug the analytics, which are the blades, into. And so our real business model is sell as many blades as we can on a transaction basis, rent them effectively, rent the blades. To do that, you have to have lots of software. In the case of Fair, Isaac, we have something called Triad that runs with all the credit card companies. And if you got Triad, that platform, they have it. And you plug in our behavior analytics and you get recurring revenue. So the model is trade software, trade analytics, people's platforms, [Induit] industry. Then keep reselling and recurring transaction-based licenses, if you will, revenue off of those analytics. Interestingly, what is different about this business model is of our revenue about, and these are both companies, a little over 70 percent of our revenue is this recurring blade revenue, not just one-time license fee revenue for the software.

 

 

So we are a software company that sells something that is recurring in nature, not just one-time license fees. And for our business models—for both our business models, we make the most money if we own the platform, we have access to the data and we create the blades. So in the case of fraud and the case of credit, we sort of have all three working together. It's a good thing to have. It is a very profitable—good position. But for us to grow, we are working on ways—blades is still our business. Blades is our core competency. We are working on ways to create blades for other people's platforms besides just our own. And helping other application developers besides us create applications. So part of our growth strategy, is to keep focusing on blades and every once in awhile we will get lucky and get a platform that the industry embraces. But there's lots of companies creating platforms, let's work with those companies to create blades.

Tom Ernst:

 

So you recognize the revenue then in a recurring basis as well?

 

 

 


Tom Grudnowski:

 

Yeah, we're very conservative from an accounting perspective—thank God—these days. It's long-term contracts, recognizing revenue transaction at the time. In the case of Fair, Isaac, we did about 14+ billion transactions last year that we got paid for. Unfortunately, we don't get paid—about $350-360 million this year. So we don't get paid a lot for each transaction if you do the math. But we've literally billed for that many transaction believe it or not—and the exact same model at HNC only around the fraud transactions versus a credit transaction.

Tom Ernst:

 

Can you give us a sense of your control of the market share then of credit transactions and fraud prevention?

Tom Grudnowski:

 

You know, there's really nobody who tries that—we think that our scoring is used probably—we probably have 60-70 percent market share in that credit transaction score business. I don't want to say fraud—it's a big share as well.

Ken Saunders:

 

Fraud is a good 70, 80 percent domestic, 60 percent worldwide with credit card fraud. And then we've expanded the credit card fraud application, the actual product, analytical AP for more broadly into healthcare fraud, which is a new emerging area, telco fraud, insurance fraud. So we have expanded that very broadly. You know, online merchant fraud. So those are new, merger opportunities for HNC. But in the product launch, specifically, in the credit card space we have dominant share.

Tom Grudnowski:

 

And having a dominant market share in a way is sort of—you couldn't deliver the services if you didn't have dominant market share. Our clients like that dominant market share. We are collecting data on credit from everybody, processing it and coming up with these scores, which none of them individually could do on their own, because they don't have all of the data, they just have their data. So the same thing with fraud. So the business model sort of requires you to have a solution that an industry or a group of customers doesn't mind you having data from multiple people in order to deliver the solutions. It is a unique—you sort of have to be—we are—both of us are sort of trusted third parties in these transactions with our customers. We do processing, we do software—and we are trusted.

 

 

We don't own data. All of this data somebody else owns. We are not in the middle of that potential risk area. We just use other people's data to come up with predictive algorithms that they then use to help run their businesses.

Tom Ernst:

 

So with that larger market share really that is what makes this economy work, the credit transactions, credit cards. It is a regular, recurring revenue stream. How do you get beyond sort of the demographic growth of the transactions, what is your strategy as a joint company in the future for driving growth beyond demographics?

 

 

 


Tom Grudnowski:

 

I think both of these companies were formed based on finding a niche and dominating it. I don't think there's really been an analytic software company like either of us that's figured out how to replicate this model, sort of regardless of application area. So our strategy is to be that company that has the business model for analytical software where the intersection of software, data and analytics make the value proposition to the customer viable. So you think by creating a company that has a business model around that we will come up with solutions in a variety of spaces. Customers will come to us and say, gee, why don't you help us with homeland security, for example, like the government is doing. Or why don't you help us in the healthcare field make some predictions that haven't been attempted before, Retail. Cross sell, Marketing. So we dominate two—one could argue, I don't know if there is [incident] but there is lots of spaces where you could go.

 

 

So if you look at growth opportunities, continuing to dominate and grow in those spaces, which has been propelling us at 10 percent, 12 percent growth anyway. If we can add on to that, the new application areas, new geographies, we think that will get us back up to double to the 20-25 percent growth that we think is possible. Quite frankly, even though the economy, you know—the last few years I have been here—it hasn't exactly been bullish, we've at least are growing 10-12 percent as you can see. So most of our software competitors are going the other way. Because of our recurring revenue, because of the focus on value, you know, selling something that is very valuable to a customer on a transaction basis and renting it. You know, capital isn't a problem to us because people, you know, they are buying something—we have a 10-year contract or a 5-year contract for × cents per transaction. We put something in and they pay us on a transaction basis. And they don't spend $25 million with us before they get any benefits. So we are still high on the list of people who are getting service revenue, software revenue, if you will. So far so good.

Tom Ernst:

 

Maybe a good example, visible to people right now is this homeland security. Ken, maybe if you can—I know you are restricted on what you can say about it, but a little bit about what the opportunity might be for HNC and Fair, Isaac now in homeland security.

Ken Saunders:

 

Well, I think that the whole homeland security more broadly kind of view really has to do a lot with trying to identify risk with multiple data sources, without infringing upon individual privacy and rights. And, you know, right now if you walk into an airport you are pretty well infringed by your privacy when you're stripping down. And I think that there—in a very random—and just like the old rules-base systems that were used, frankly, to hunt credit card fraud. They are just antiquated rules set up by one most knowledgeable person. And then to be able to mine data and look for the subtle trends that an otherwise human would never even fathom allows you to more accurately find those needles in a haystack risk and as they emerging. So I think you could apply that today in the airline industry where you have large masses of data happening very real time with a lot of very subtle relationships to be able to identify a large range of different types of risk.

 

 

 


 

 

You know, we were a spinout of TRW from 15 years ago. So we have a lot of roots in the government area; and we have applied and are applying analytics in areas like homeland security with respect to airline risks, where you can score planes and things of that nature to identify risks. We do it in other areas of government work with—you know, looking at gene sequencing and DNA sequencing to understand how to help biotech firms do rapid drug discovery. And that's more of an R&D type of project. So we have about one percent of our revenues has been very devoted to this kind of advanced research work with the government agencies.

 

 

I think the homeland security as an evolving area where I think there will be a lot of opportunity to leverage risk analytics in a wide range of areas. The airline area could be a huge thing if you just think about a few cents per airline ticket with all the travelers daily in the world. You know, that's anywhere from a $50 to $500 million number just depending on the type of—if you figure out the most comparable risk pricing on other types of analytics. We're pretty far away from sizing those dollars for sure, but we are right in the thick of things.

Tom Ernst:

 

So what this is a good example of is growth opportunities in that space. Who is the competition of this kind of solution? What are the other approaches and why do you have an edge?

Tom Grudnowski:

 

Are you talking about homeland in general—

Tom Ernst:

 

In general, but with homeland security as an example, might be helpful.

Tom Grudnowski:

 

I think our business model says if you are focused on the equations as part of the solution, you ought to talk to Fair, Isaac. And we will tell you what data you need and what software you need, as opposed to maybe a more pure software company who will try and sell you a horizontal platform and say, well, you worry about how you implement that. So we would compete with other software companies who have analytic platforms—we would compete with in-house staff, those PhDs and mathematicians who are trying to write these equations. We would compete with consulting firms who would advertise that they have these kind of competencies. But I think our big competitive advantage is we are focused—you know, we have got a bunch of geeky, propeller head PhD guys, who are great math majors and who love to go through data at their computers and sit there all day, you know, cranking out analysis. And that's—the customers that come to us that is where their value, that is where they see us valuable.

 

 

Just one more thing to put in your head when you are trying to figure out how to put us in the software classification. We think in the world of software. Eventually, at the enterprise level it will be recognized that every application has in it a decision management function. And if you take take our application, be it Triad or Falcon, there's an application layer that deals with fraud or credit, but then there's a decision engine layer that deals with how you stick equations into an application, okay. And our core competency is how you do that. And so we have developed a lot of applications because we have to—that was our—we now have this competency in this—what could become a very horizontal requirement over time—that would position Fair, Isaac and HNC very uniquely in the software space as the sort of infrastructure provider for, you know decisioning platforms where you stick equations into. And because our bias is sticking equations into things, we write the software a little bit differently than somebody else whose bias is a user interface or way to access the data more efficiently. I know we have an analytic bias the way we create software.

 

 

 


Tom Ernst:

 

One more question and then I'll open up to the audience for questions. Software mergers and acquisitions have a history of occasionally good, often bad—how do you plan on side-stepping some of the issues that have come up with other mergers in the past?

Tom Grudnowski:

 

You know, I think it's 80 percent bad or something? So, high risk. The reason this isn't risky, relatively speaking, is we're very much alike. We both have recurring revenues [seventy percent]. We both have geeks, that you have to feed and clothe and keep happy—that's a cultural thing you have to know how to do. We both have a scientific heritage, you know, there's lots of innovation that is really the issue. We're both analytical software companies. So I think when you look at how you fit together. It is almost like adding a few more product lines together rather than—you don't have to change the culture. The culture—we are both probably working hard to create sales organizations and marketing organizations—address it as a Siebel or Oracle—you know we are not there yet. So we are working hard on that.

 

 

We have new culture to create—not old culture to break down. So I think culturally, I think we fit very, very well. And of course we have the traditional—that comes from Accenture—I'm used to work programs—a zillion or more programs and how we're going to make this happen in an organized and efficient way. We have about—our shareholder's meeting July 23 for the final vote. We have one issue left we're working with on the Justice Department that should be resolved by then we hope. And between now and then we've made lots of decisions already about management and staff, and what products we're keeping and what products we are getting rid of. So we're well into that analysis already. So I think by the time we hit the ground and close here in a month or so, we'll know what we're doing and we will be off and running pretty quickly.

Ken Saunders:

 

I might just add huge customer acceptance. We have the same customer base at the top tier level who are as excited about this merger as we are. And I think that is very promising. It makes it a little bit easier when your customers are on the same team. And I think to make the acquisition, a merger successful out of the box, there's very little product integration that has to happen in order to maintain the revenue set as they exist today. And there's lots of opportunities to marry different product suites and create new products. The synergistic revenue that we have and really haven't articulated it too much, but the more we time we spend with each other doing integration leg work we are planning on a lot of ideas along the way. So I think those are a couple of practical and operational things, besides cultures and business models that I think will make this one a little bit more easier to do.

Tom Grudnowski:

 

Those are great point. Most of our products still have to be planned together. They are already independent. But they fit the business model that I talked about. So there is not a lot of rewriting or software that we have to do. So I think it is relatively straight forward.

Tom Ernst:

 

Other questions from the audience, yes.

Male Respondent:

 

[Inaudible]

 

 

 


Tom Grudnowski:

 

Yeah, they are totally different products. And the good news is all of our contracts are long term. So the pricing on credit scores, you know, is done. We won't be able to take advantage of any way of raising credit score, the same thing on [trust]. These are long-term contracts we already have. So what the customers like—but the customers know that. So they are not worried about that pressure. What they like, you know, is that they've got a lot of companies with an analytic focus. And so the analytical departments of our customers are happy there is now more resources, more people to talk to, more—let's say different approaches. From the way, our scientists and their scientists approach problems, is a little bit different. That's good. So our customers recognize that. We will probably come up with a broader solution by looking at a different types of technology that we've probably focused on the past.

 

 

So, unfortunately—unfortunately, we don't have the ability to do pricing in a sense, right. So there's not much we can do there. What the synergies will be are in, you know, things like taking their transactions—some of the products that we both have that our customers—they integrate. The customers sort this out usually before the companies do. And so the customers are driving this—hey, what if you take that transaction analysis you do with your [pen] recognition logic, you know, and match that with your regression analysis that you've developed. So they are coming up with ways that we can work together better. So also on a geography basis, we are stronger overseas than they are. There is a great opportunity here to cross sell some product overseas. They've got a little bit bigger presence in Japan—the second largest credit place on earth—the United States and we don't do credits scoring a lot there yet. Big opportunity there to still grow. So I think there'll be some cross selling opportunities as a result of this as well. Most of the synergy in the short term is—that makes this accretive right out of the box—is the fact that we are eliminating a lot—you know, we don't need two G&A groups. So once we put the companies together and we start to sell better I think the revenue synergies will come.

Ken Saunders:

 

I might also add that we already do sell multiple products to the same customer, each of us independently. So you might sell two or three products, and they sell two, three or four products. So now we have six or seven products. And as Tom elaborated earlier, we feel there is not quite but somewhere near incident opportunities to take any reported interaction and add some sort of value. And, lastly, both our products are very much are our value-based offerings. So we have been able to resist a lot of pricing pressure even during the sluggish economy where prices are getting slashed, we're still selling things at 10 to 12 to 1 ROI. And that's what the basis is and that's why we can charge forever on a lot of our value-based pricing. I think that is going to eliminate a lot of that risk.

Tom Grudnowski:

 

Actually, I should probably be a little more aggressive. One of the reasons that I am here, number one, I think that analytics is a huge marketplace potential, as I said earlier, but a lot of times—you dominate the market. We get paid from these huge multibillion dollar companies—pennies. You know, Anderson is getting—these guys are getting big bucks. So our opportunity to continue to look to the value chain and create solutions, you know—here's a perfect example—Fair, Isaac introduced something about two quarters, three quarters ago now called MyFico.com. And what we do on the Internet now is we sell to the consumer. And I think you go on to myfico.com. For $12.95, we'll give you a profile of your score, what you can do make your score better. You know, the score [the others view]. So if you want to get educated on what the banks think about you, for $12.95, we'll educate you on that.

 

 

 


 

 

Well, it is a great service. We had over a million people buy it, you know, over the last two and a half quarters. And this is an example of taking an analytic that we were using over here in the banking world, in the B2B world and applying it, you know, in a new market where we are getting new dollars for a similar technology. So I think there are lots of opportunities in our existing client base to just be creative about how you apply these customer behavior algorithms to other customer behavior as a problem—cross sell, etceteras, there's as many as you can dream up.

Tom Ernst:

 

How big do you think that opportunity is on the consumer side?

Tom Grudnowski;

 

I think that was quoted in the Wall Street. I think that is half a billion to a billion dollar marketplace. And we are only—you know, it is brand new marketplace but it is huge. It is a huge marketplace.

Tom Ernst:

 

Any response out of your bank customers to this, positive or negative?

Tom Grudnowski:

 

The banks love it because—we obviously checked with them first before we did this—the banks like it because they've got the same pressure. They've got the pressure of the public wanting to know, well, how are you judging me. You know, why are you denying me credit or why are you giving me credit. Or why is my interest rate what it is. Or why is my credit card offer what it is. So they now see us as helping them. The real vision of myfico.com is really to be inside the education analytics inside the banks' distribution channels to help them educate their consumers on their credit patterns. So we just did something—a very big announcement with Bank One, Citi is using it. There is other big banks now that are using MyFico inside their architecture to help their customers—help do a better job of customer interaction. So—huge marketplace.

Male Respondent:

 

[Inaudible]

Tom Grudnowski:

 

The answer to the first one is, I think our scoring business tends to grow at about—like fraud—probably in the 10 percent per year level. Because we do 14, 15 billion transactions. They're used so many places. Cars, mortgages, loans, credit, retail credit that—well, when I looked at the data I would probably say, oh, my, god, what is going to happen when this happens. They are used so many places that if one area is down, the other is up. It is just something that has been going up. So I suspect that we're—because it is so ubiquitous, we're somewhat isolated from changing one industry to another. We're lucky, though, because it is so ubiquitous, because it is the same thing in fraud.

 

 

 


 

 

On the sales side, when I first got to Fair, Isaac, and this is still an issue at HNC is the sales force, because it is so much recurring revenue, you know, they are not used to that, you know, deliver every month quarter kind of thing. So what we did is we changed two years ago at Fair, Isaac and no more recurring revenue, you only get paid if you sell something new. And that's doing the same thing with HNC now. So we are trying to build a sales force. That is a little bit more aggressive and motivated and compensated based on what they do for you today, not just what they do for you, you know, 10 years ago. And we are making good progress on that. The hard thing to build in this sales force is sort of this solutions orientation. It is sort of the combination of a consultant's, you know, an analytic mathematician geek, you know, and a strategy guy. You sort have to get all of those together. And so we are working on hiring a lot of consulting people. Actually, we do about, Fair, Isaac now this year about 260 million. We are going to be up to about 60 million of consulting services. So we are almost using consulting services as a way—consulting almost sells as much as sales, right, because the CEO calls up—I have got this big customer acquisition problem. I've got to get my response rate for my credit card mailings up form .5 to .6. If you can do that, that's worth it. You know, $200 million of profit to me next year—can you help me do that? That is a hard thing to do. But we had a lot of people who can work on that problem and try to solve it so.

 

 

So the answer is, our sales organization is becoming, you know, more focused and more consultative over time than just what you think of as a pure sort of software, come in, slam something down and walk out the door. We've got to be a little bit more solutions oriented than that. Two hard things to do though. That takes time. I can't steal people from a lot of other companies to go do that, because there are not a lot of other companies that sell that way.

Tom Ernst:

 

Great. Well, thank you Tom Grudnowski and Ken Saunders for your presentation. And thank you all for coming.