HARTFORD FINANCIAL SERVICES ANNUAL MEETING MARCH 29, 2005

CALL PARTICIPANTS

• Kimberly Johnson The Hartford Financial Services Group Head of Investor Relations

• Lizabeth Zlatkus The Hartford Financial Services Group EVP & CFO, Hartford Life

• Daniel Guilbert The Hartford Financial Services Group AVP, Risk Management/Hedging & Hartford Life

• David Braun The Hartford Financial Services Group SVP & Chief Risk Officer Hartford Investment Management Company

• Ernie McNeill The Hartford Financial Services Group VP and CAO, Hartford Life

• Jim Trimble The Hartford Financial Services Group VP and Chief Actuary, Hartford Life

• Vic Severino The Hartford Financial Services Group SVP and CIO, Hartford Life

• Vanessa Wilson Deutsche Bank Analyst

• Jeff Shuman KBW Analyst

• Jason Booker Analyst

• Steven Gavios Genus Associates Analyst

• Ken Crawford Citigroup Asset Management Analyst

• Eric Burke Lehman Brothers Analyst

PRESENTATION

Kimberly Johnson: We'll get our session started today. My name is Kim Johnson, and I head Investor Relations at The Hartford. And on behalf of the Life Company management team and our Income management team, I want to welcome you here to our half-day session focused on hedging and risk management.

Last December 2003, we had a Life Company Investor Day. And at that point in time, we discussed, in fairly good detail, the approach that we're using for our hedging programs. And this morning, you'll get a chance to understand how we've evolved from that point in time, what's changed, what we've learned, and how we're doing the business today.

Before we get into that agenda, I've got a couple of things. First off, I'd ask that your cell phone ringers off. So if you've been on the phone, please do that for all of us. I'd also like to introduce the newest member of our IR team at The Hartford, Greg Schroeder. Greg is in the back of the room. He just joined us from Nationwide. So in your weatherproof packets today, you have a business card from both Greg and myself. So if there is any follow-up after today's session, we'd appreciate getting a call for either of us, and we should be able to help you out.

Also, before we get into the agenda, we've got the obligatory Safe Harbor. I'd like to remind you that we will make certain statements during this meeting that should be considered forward-looking statements as defined in the Private Securities Litigation Reform Act of 1995. These include statements about The Hartford's future results of operations. We caution investors that these forward-looking statements are not guarantees of future performance, and actual results may differ materially. Investors should consider the important risks and uncertainties that may cause actual results to differ, including those discussed in The Hartford's Annual Report on Form 10-K filed on February 28, 2005 and other filings we make with the SEC. We assume no obligation to update this presentation or our forward-looking statements, made during the meeting.

The discussion of The Hartford's financial performance during this meeting includes financial measures that are not derived from generally accepted accounting principles. Information regarding these non-GAAP financial measures is provided in the "Investor Financial Supplement" for the fourth quarter of 2004, which is available for review in the "Investor Relations" section of our website, at "thehartford.com."

With that, I'm going to introduce the CFO of the Life Company, Liz Zlatkus, who will host today's meeting.

Lizabeth Zlatkus: Hey. Good morning everybody. Did everybody get their coffee? I'm really excited this morning, because I have the best job of all this morning. I get to introduce really an outstanding group of people. We probably would bring the individuals that actually do the hedging everyday and are involved in really all of our risk management in terms of equity hedging and equity risk at the Life Company.

We have a panel up here. First, we're going to hear from Dan Guilbert. Dan has been working with The Hartford for over nine years, and he's been involved in hedging from day one. He really is extremely educated, and you're going to hear from him that he's involved in this on a daily basis and has a great team of people working underneath him. We're then going to hear -- he's really involved in the liabilities side. He works literally daily, often times many times a day. That's David Braun and his team. Dave works at HIMCO. He came to us probably years ago, has many years of experience in kind of capital markets, and he's just done a phenomenal job on the assets side of the hedging. So we're really pleased to hear from David. And again, both David and Dan are backed up by a very extraordinary team of talented individuals back at The Hartford.

We're then going to hear from Ernie McNeill. Many of you didn't meet him. Earlier in '04, he was the individual -- he's our Chief Accounting Officer, who talks about FSU3-1, another very technical data for Hartford. And Ernie is the individual at The Hartford Life that really helps that accounting policy and also involves in all of the financial reporting (inaudible) at The Hartford. So he's going to go over the accounting for us in our hedging program.

And then we're going to hear from Jim Trimble. Jim Trimble has been with us for close to 30 years. He is now the Chief Actuary of Hartford Life. He took that role of Craig Raymond, who you all know took on the Chief Risk Officer of Hartford Financial Services Group. And we're also going to have Craig come up for Q&A. Many of you know Craig. He's been the face of the lot of the hedging questions and very and still involved today but has taken that kind of higher role looking at risk across the entire enterprise. And we're really pleased to have someone as Jim's caliber to take on and play his role.

Jim was most recently before that the Head of Product Development and was then out to explore our international operation. He's going to cover our Japan product and how the risks of that product look. He's also going to cover a small portion on C3 Phase II. So, certainly, he's the individual that knows a lot about the Japan products and clearly helps develop it. And then we're going to talk a little bit about technology.

I wanted to introduce some other individuals, who are not going to up at the panel, because we're running out of room. But Dick Sabarino is the Head of our Chief Installation Officer at The Hartford Life, and he's been with us for many years and previously was on Wall Street. He's just done a phenomenal job with his team on the technology front, and I think you're going to hear some very exciting things that we've developed that really give us a strategic competitive advantage. I'm going to have Dick stand just in case you have any technology questions. He's going to be able to answer them. So there is Dick. Everybody else will be up on the stage, so you'll be able to see them. Combined the team that I just introduce has over 130 years experience in the financial services industry.

I think what's really important to also know there is not only as this team involved again many people underneath them. We have spent millions of dollars both on technology and investment in our hedging and risk analytics. But also we have routinely get-together, I guess, with this team, Craig, David Johnson, Tom Marra, obviously myself, John Walters.

And those are a very routine process where the very senior executives of Hartford Life get together and talk about our hedging program, talk about how we're evolving, think about product development, the risks involved in really our products across the spectrum. So this morning, obviously, is primarily about hedging. We are going to be talking about some other analytics when we talk about, for example, our technology.

And with that, I'm going to turn it over to Dan Guilbert, who is going to start off our day. Dan?

Daniel Guilbert: Thanks, Liz. The focus of my presentation will be on four main items. I'm going to discuss the Principal First business mix and some contractholder experience. I'll also discuss how we look at risk and hedging, in general. I'd get into the actual performance of the hedging program in 2004 and also what to expect, going forward.

First off, just from a definitions perspective, I want to describe Principal First, which is all we know is the Guaranteed Minimum Withdrawal Benefit, or GMWB. Principal First was launched in August of 2002, as sales ramped up very quickly and really set the pace for the industry in the last couple of years. In fact, all of the top 15 (inaudible) writers now offer GMWB (inaudible).

Our version of a GMWB Principal First really has a few distinct features. First off, the fundamental of guarantees that you'll get your money back. The mechanism for getting your money back is by taking up to 7% annual withdrawals. The fee that we charge is 50 basis points, and also the client has a benefit of reset. For up to every five years, they can reset how much remaining benefit they have and also the max amount they can take on an annual basis.

With the lots of competitor variations, I could spend an hour discussing the range. But just in summary, some of the main variations are typically regarding the amount of annual withdrawal that you can take. There is also variation on the remaining benefit amount. In some cases, it is more frequent than every five-year step-up or in some cases a guaranteed step-up. And the fees levels also vary throughout the industry. We also offered our own variation, I think, for 1st of November last year, 2004, with the launch of Principal First Preferred. And I'll obviously discuss that a little bit more later on.

Just to try to put Principal First in context. What we want to do is look at how Principal First sits within the overall individual annuity book. So let's look at the left. What you see is that Principal First is about $30 billion, and that's around 27% of the overall individual annuity book. The rest of the book is made up of fixed annuities at about 10% and non-Principal First variable annuities for the remaining 63%.

If you look just on the left side and you focus on Principal First, the two sections we have there -- and the gold is reinsured Principal First, which is about 40% of Principal First. The remaining piece is the hedge book, which is on what I'll spend a lot of time discussing today.

And that book is about 60% of Principal First or 16% of the overall annuity book. For us, again, just to try to put in context, the very rapidly growing piece, back in 2004. The utilization rate was around 75% for new contracts, but still we have a lot of balance in the overall annuity book.

If you take just the hedged Principal First slides, which is around 18 billion, and you focus on that for a second, what we're trying to show here is how in or out of the monies the Principal First contracts are. Just from a definitions perspective, we're defining money in this by looking at every civil contract that we have and looking at the relative account value versus the remaining benefit. To the extent that a contract has more account value than remaining benefit, we're calling that "out of the money." To the extent it has less, "in the money."

And as you can see, by and large, the book is out of the money, which is great for us from a risk perspective; 59% of the book is between 0 and 10% out of the money, and 40% is more than 10% out of the money. If you just look at the overall blended money in this level, it'd be around 9 or 10% out of the money for the book. This is actually as of 12/31/04. And year-to-date, the market is down a little bit; still that overall blended percent hasn't changed too much. What we liked about this is it tells us once again that we're in a favorable risk position. Thanks to the market performance over last couple of years.

I'm now going to move a little bit more into the contractholder experience itself rather than just the business mix. We actually like talking about this. We feel like this is a larger advantage of The Hartford. Basically, we have one of largest variable annuities books in the industry. We have about $100 billion of variable annuities, right now. We also have the largest GMWB book in the industry, about $30 billion, including both the hedged and reinsured pieces. So that gives us a lot of information that we'd like to use actively.

For instance, we know that Principal First contractholders typically have very similar demographic characteristics as the rest of the variable annuity book in terms of age, fund mix, and other criteria. The only reason we know that is because we have all the data to check that and understand how Principal First contracts look versus other variable annuity contracts. We have over 1.4 million annuity contracts in force, right now, 300,000 Principal First contracts, and well over 15 years of variable annuity experience. We'd like to use all this information actively.

For Principal First business, specifically, one of the things we do is we have automated daily and monthly reports that basically give us trend information in terms of behaviors, such as how they're moving their funds, have they taken withdrawals or locked in, etceteras.

We have these automated reports on a daily and monthly basis. And what that allows us to do is really understand the trends and also the actual for expected relationships. So we compare the actual experience from peers versus what we use in our pricing analysis and other risk analysis, and that's very powerful for us.

Additionally, this allows us to do a lot of ad-hoc analysis. If we see a trend that we don't like, we can easily drill into it, understand what's driving the behavior, and then use that information in a proactive manner.

Another thing we do is we actually look at experience in a very granular fashion. And what I mean by that is that we actually look across all the different contracts and really understand what is driving the experience.

For just to use a simple example, we might look at the overall book and say that the withdrawal rate could be 2%, for example, for Principal First but wouldn't stop there. What we would want to understand is what is driving the withdrawal rates, who is taking withdrawals, why are they taking them, and how we can use that in our model, which is really the most important thing for us so that we understand the risks.

So the key point here is that we have lots of data, we'd like to use it, and we'd really like to make sure that we can use appropriate data into information, which we use in our assumptions, and, therefore, improve our estimates in our risk analysis.

I just mentioned that we really like to use our in-force information and experience. I'm actually going to give you a prime example. In the first quarter of this year, 2005, we're actually going to be making a change to our withdrawal function. Exact details are proprietary, which is that at a high level what we're able to do is use both Principal First and non-Principal First variable annuity data to come up with a much better and more granular assignment withdrawal activity.

This would give us a much better approach or more accurate approach, going forward, and allow us to more accurately map that experience. The net gain impact of that would be relatively small, after-tax and after-DAC in the $2 million to $3 million range. Once again, that puts us in a better position, going forward. We're not going to rest on a low result. We want to continue to look through all the experience, continue to look at all the other assumptions beyond withdrawals, and make sure that we use it actively.

Lastly, we do recognize that there are some limitations. Unfortunately, we don't have 10 years of Principal First experience under different market conditions. So we do a coupe of things to try to compensate for the lack of long-term Principal First experience. First off, what we do is by names behavior all our modeling, we assume that people will behave in their best interest by using the guarantees that the market are down.

A couple of examples could be -- if the markets are down, their account value is relatively low compared to the main benefit. They might take out more withdrawal. They might also lapse their contracts less frequently, because they'd be leaving a valuable guarantee on the table. So we incorporate that sort of logic into all our modeling and make sure we're actively capturing the risk.

Secondly, we do a lot of shock, sensitivities and stress testing of our assumptions so that we understand the range of outcomes to really understand we can be exposed to its contractholder behavior did these when we expected it.

I'm now going to move away from the business mix and the contractsholder experience and talk a little bit more about the risk itself. Risk for us is very multidimensional, and what I mean by that is we look at risks over different time horizons as frequently as daily through our quarterly GAAP earnings, annual statutory surplus volatility and even over the long horizon; 25 years is what we might expect to see in terms of claims and other economic results. We also look at risks across different financial frameworks.

What I mean by that is we look at GAAP results, we look at statutory balance sheet impact, and we also look at the long-term economic and cash flow impact at Principal First. But for us, risk is not just one thing. It's really a metrics, and we need to look across that metrics to really understand what we're exposed to. The reason for that is different products and different barriers in the Principal First or even death benefits for that matter and have different sources of risks. And you really need to understand what's driving your risk and one that can happen in order to design effective risk management programs and hedging programs.

I'll just reference that we like to look at the long-term economic risks, and this graph is just one example of how we look at long-term economic risk. What this is trying to show is a range of Principal First benefit costs across the sarcastic scenarios side. This is just a range, once again, in ranks from the smallest to largest. And just to put some definitions on the table, really to get this analysis, what we did is we loaded a new business population into our pricing model. And that population is consistent with the Principal First business that we actually write, right now.

We used our modeling assumptions that are consistent with all the hedging analysis we do, right now, as well. We then arranged that across the sarcastic scenario set. And the scenario set that we used is actually consistent with all the modeling we're doing right now at C3 Phase II, which really looks at historical returns, volatilities of returns, and that has an extra conservatism at the tail to make sure that things are volatile enough in the worst scenarios.

We then actually calculated claims for the Principal First business. And just to make sure that we're clear, when we say "claims" in this case, what we're talking about is when people -- if someone gives us $100,000 and they're taking 7,000 out, so they can take up the 7,000. When they first are taking their account value out, that's not a claim. They're just taking their money out of that contract. When they run out of account value entirely and their account value goes to zero and they still don't remain benefit and we have to fund that, that's a claim for us. So that's really what we're showing here.

We've discounted all those claims back to time of zero, and we've converted them into basis points. That way you can line them up against fees, indemnity fees, writer fees, and you could really get an understanding of how we're look at this. And the results are basically that, in all but one of the scenarios, the charge, which is the worldwide 50 basis points is in excess of the claims. There is only one scenario where the claims go beyond where we're actually charging our client from a long-term perspective. In fact, in over 75% of the scenarios, the claims are virtually zero. So it's a pretty powerful graph in terms of looking at the long-term risk.

And since this is the only thing you looked at, you might ask the question, "Well, why would you hedge Principal First?" A good question. Well, why do we hedge? Well, sorry for just doing your job. There is lots of short-term volatility and long-term volatility. Just stay on the long-term volatility for a second. That graph is great. We spent a lot of time putting it together. They show the nice range of economic outcomes. But we do recognize the fact that there could be capital markets or policyholders that may be beyond what we currently contemplate. And therefore, we want to make sure that we're funding claims to the extent we can providing adequate cash flows in the future.

Secondly, on the short-term perspective, there could be substantial volatility on both the GAAP and stat side. On a GAAP side, what you have is FAS 133, which really marks to market the liability as if it were a derivative. Therefore, it's using interest rates, implied volatilities, actual market levels, along with all the contractsholder experience. And that valuation, if left unhedged, can be quite volatile. And I'll actually show you a specific illustration of that.

On the statutory surplus side, we also get volatility. The new regulations coming through under C3 Phase II require you to do a sarcastic valuation really focused on the tail risk, and actually new reserve regulations are also just like that. So all these valuations are creating a much more accurate and volatile results on both stat and GAAP side. We want to make sure that we're actively protection ourselves. So in summary, what we really want to do is mitigate some of the short-term GAAP noise and statutory surplus volatility and also ensure favorable long-term economics for the company.

So from a high level -- in terms of the starting on the hedging program actually works with safe and easing derivatives. Some examples of derivatives that we actually used our over the counter options, swap contracts, swift contracts, and really those derivatives are purchased to try to protect the significant adverse market movement.

And fundamentally, the goal is really just that that portfolio derivatives that we hold for the change in our portfolio will approximate changes in liabilities and in our exposure. That's really -- the initial target for us is the GAAP liability, which, as I mentioned, is mark-to- market under FAS 133. But we are also factoring statutory results in our hedge strategy to make sure that we're comfortable with what will happen there. And the issue is really that a GAAP liability does not exactly equal to statutory liability.

And therefore, since they are not exactly equally, cannot hedge both perfectly, simultaneously, but what we can do is greatly dampen the volatility of both as long as strategy contemplates that. But for us once again, what we're really trying to do is mitigate some of the GAAP net income volatility and also reduce some of the statutory capital usage and I'll show you some examples of that as well.

This is my first illustration on a GAAP net income volatility side. What we try to do here is, give you an actual historical market scenario, putting a layer on very conservative policyholder behavior, they are trying to stress test the model to really understand what could happen from a volatility of GAAP earnings perspective.

From a liability assumption perspective, we assume that we wrote 10 billion of business, all on one day in the first quarter of 1995. We then picked the 1995 economic scenario because our product is a five-year reset.

And what happened is, we all know that in the late 90s the market did very well, ramped up quite quickly. We then assumed that every single person elected to reset right on the market peak in early 2000, and thereby, they harvested all the gains in their contract and set a new guaranteed benefit level. As they -- also now the market went down in 2000, 2001 etceteras.

So when I say stress test, it's really extreme stress test. It still gives us really good information. To show the market returns beyond 2004, we just picked the random scenario that was volatile to stuck it on the end.

One other thing about the reset is that our contract allows us to increase seasonal reset. We do not bring that and we do not count that as a benefit in this example. So from a results perspective, as you can see on the graph, it can be quite volatile. I have broken the graph into three pieces, number one, two and three, just like we talk so easily.

Section number one is the bull market that I already described, late 90s, market is doing well. Generally making some pretty good money but still some choppiness. In 1998 a large hedge fund long-term capital management blew off that created spikes in implied volatility, that's some of the noise that you are seeing there.

In the second section, as we all know, once again, the markets dropped in 2000 and 2001, the changes in implied volatility and interest rates, that created some substantial volatility in the second section. In fact, some of the quarterly swings were in the $150 million range. Now it's quite volatile.

In the third section, the market stabilized a little bit. Lots of older people are dying and asking a little bit more and getting a little bit smaller, so things are starting to grind down eventually for some of the contracts going to claims mode in that third piece.

So the summary here is really that unhedged Principal First GAAP volatility to be extremely volatile. And we are going to fix that and speculate some hedging. In this slide, we actually laid on the impact to hedging in the red line.

So the blue line is identical for I just showed in the prior graph and now the red line is that same blue line but with the impact of hedging. And I can see the GAAP earnings have been greatly stabilized and hedging has done a pretty good job here. Just to try to explain, how we go about wearing a hedging in, takes a couple of there.

Really, what we tried to do is embedding for our models, our program is very similar to what we are actually doing on nightly basis in real life, we do all our nightly liability enforce upload. We look at all the liability Greeks and market sensitivities. We then have the information going to the Investment management area. Portfolios are constructed with assets based on market conditions and then we look for places where there is a imbalance and training it further if necessary.

We then repeat that process, everything will be in the model although back in 1995 through the end of the model. That's a very labor intensive and computer intensive effort and gives us a lot of information allows us to really impact that what our hedging would look like, under that's very real historical scenario that has very conservative contractholder assumption.

And the results once again of that is, with hedging, a lot of volatilities are wiped out. The red line is much more stable. It hasn't completely eliminated the volatility though. If you look at the second quadrant, there is still odd times but there is quarterly GAAP earnings noise and that could be expected, hedging is not perfect. Interestingly, the internal rate of return for this valuable annuity business even without hedging, if you go always back to 1995, with over 15% the reason for that is because that business was -- in the right before the bull market and experience the great market return.

So, the overall skill levels are very high relative to the initial acquisition part. Then from a long term profitability perspective that business is great. With hedging, the IRR goes well over 20%. I hope it fairly helped you.

Unidentified Audience Member: (inaudible - microphone inaccessible).

Unidentified Company Representative: In similar way it is -- it is losing money. And I think…

Unidentified Audience Member: (inaudible - microphone inaccessible).

Unidentified Company Representative: This is focusing on, the return of the product including the impact to hedging. I think we'll give some more details in the Q&A, which we will have after.

If you go to the next slide, we got to move off the GAAP earnings and talk a little bit about Statutory Capital Usage. So, the prior graph looks at that one historical scenario and try to paint that picture using one actual historical scenario, what things might look like? This is taking another approach. It's really looking at a sarcastic scenario set there, and trying to understand a range of outcomes across these sarcastic scenarios, in terms of statutory capital usage. I think it's a lot of the same liability assumption for the same 10 billion of new business, the same assumption regarding with what's evolved in (inaudible) rate and no diversification I think is written in one day.

And what the graph is showing is really the annual statutory capital usage in this -- do you understand what I mean by capital usage? We're looking at that in terms of the statutory earnings on the business plus any changes a required capital, needed to back that business by risk prospective.

All the required capital is calculated using the new C3 Phase II methodologies, which once again are quite material than look at the "Tail". The random model across these sarcastic scenarios over 25 years and it grabbed all the annual results and really focused on the first 10 years, the reason we focused in the first 10 years was -- couple of reasons.

First of all, 10 years is a much more tangible risk to rise in terms of understanding what kind of capital you might use.

Secondly, a lot of the worst results in the first 10 years, as the time goes on, the block is more, means, evenly you might pay cash claims in years 10, 15, and 20, you recognize the potential of those claims in the capital much early when the market is down. But the first thing is, it is a great time to look at in Stress Test perspective.

As you saw on the left of the graph, and look at the 50 percentile well that is coming by half the time, we are actually not using capital but generating capital just the way that what we want to do. If you move more towards the right, you see the bar at the 5 percentile for example, that's saying is about a 5% chance that's a $10 billion book, leaves around 125 million of capital any given year. Another point pointing here is that we ran this block in isolation that $10 billion all by itself.

In this C3 Phase II regulation or actually have you run the entire valuable annuity block these company all together, so if you are running the older business and the result in general, will be a lot more same than the one I'm showing you here. This still gives us a nice relative risk metric to compare products to compare different hedge strategies.

But the overall actual results under regulations will not be as severe as this. This still goes beyond our tasks, what we'd like to see for our product sale, so nothing for hedging. So in summary, couple of points once again, this is no aggregation. We'll show you an example about a second, this is no hedging.

We go on to the next slide, with actually laid (inaudible) and estimates for the hedging impact in the red bars. As you can see this is a repeat of the prior graph. The blue lines are the same or the blue bars are the same.

The red bars are estimates for hedging free associates with each of those probabilities and to do that analysis, once again requires us -- from that all our hedging analytics across each of these sarcastic scenarios. Really, run the models again and seeing that are actual performing in the nightly process. This actually requires very sophisticated software and hardware -- with that great support from IT area also if it is done.

Two benefits that you get out of hedging that are shown up in the graph here, in terms of the C3 Phase II are that hedge access themselves. We work more in the markets down and similarly if you're hedging downside benefits.

And this year balance sheet looks better because of more assets. Secondly, we're asking Bill to take credit with in C3 Phase II for the future benefits of hedging, just like he incurred for reinsurance and risk management strategies. Those are both two big guys that hedging gets here. As you can see as well, hedging it not eliminated the volatility, not the flat line but it's greatly reduced our GAAP in the volatility.

The other thing, I want to mention is the aggregation. We have some arrows here. It shows the specific bars, the regulations and probably are not final. We don't want to try specific credit earnings sorts of final regulation, which doesn't exist now. Sounds like we are hopeful it will be adopted by the end of this year but, once again, the benefits will be there. Aggregations, valuing their overall books, the overall valuable annuity book at the same time. We'll make the results better just by virtual doing that, by doing it that way.

Now as much as, we all like to talk about hedging and we are proud of hedging program. We have another important aspect of our risk management program that involves price development.

Early with the slides trying to show is an emphasis on the product development aspect. As I mentioned, Principal First Preferred for the launch in November 2004 and really the key differences from Principal First are that you take 5% withdrawals instead of 7%? And that there is no reset after five years, rather the benefit is revocable after five years, so you can stop paying us fee, the fee is only 20 basis points versus 50 for Principal First.

So this is a similar slide, where we've been showing you. This has no benefits of hedging and just looking at the low risk for Principal First and Principal First Preferred and as you can see, just by product design has greatly dampen the bars. The green bars for Principal First Preferred, is substantially lower. We had a lot less capital. The frequency, of when you actually start using capitals, it's benefiting, actually closer to 10% to that, so contributing capital there. If you go to the right and look at the 5% it's just a fraction of what's Principal First was using from the capital usage prospective. We really like Principal First Preferred from a Risk Management perspective.

In terms of the drivers that makes this graph look so good, on the graph design shows the function in both cases. The 5% withdrawal has a large impact, the reset actually has a substantial impact as well, to the extent that clients cannot step up their benefits and actually pile on to the risk, shows up in the graph. To the extent some companies have even more frequent resets than every five years. I would think, you have even more dramatic impact here or for us, it's pretty dramatic as you can see.

So in summary, you can understand better why we believe the Principal First Preferred or Risk Management perspective, we are still providing great consumer value and you can also see where I let these cross developments as a Risk Management tool.

Just for completeness, we want to show Principal First Preferred with Hedging as we have shown Principal First with Hedging. We kept the graph in the same scale that's why the bars were so small, since they are small compared to Principal First and really the black line is a pretty done a much more comfortable value. Principal First Preferred after Hedging has very little capital usage and that make us very comfortable once again some of the product development in Hedging perspective.

I'm now going to move away from discussing all the potential benefits of Hedging to move - - to actually discussing the actual performance of the Hedging program and what's expect going forward. This is a graph of the monthly performance of the Hedging program in 2004, the line represents the gains and losses created by the liability on a monthly basis in 2004, the bars represents the after tax/DAC net impact of assets and liabilities associated with the Hedge programs, as you can see the line is quite volatile in any given month, it could be in the $40 million to $50 million range, the bars are extremely small in terms of noise, they are more in the 3 to 5 million range in a monthly basis.

So in summary, 2004 Hedging did a great job and a very tight fit. The question is why? Why was the 2004 performance so good? Why was the Hedge so tight? Actually, there are few reasons for this. We executed the Hedge program very well. We diligently monitored the markets, and rebalanced if necessary, so we did our job, which is great. Secondly our markets were not extremely volatile in 2004.

SMP went up by 1%, interest rates and implied volatilities were not extremely volatile in 2004 and that's going to make your overall results not as bad. And then lastly there were no major dislocations. So there was nothing like October 1987 or back the long-term capital management in 1998, or September 11, 2001. There are no major GAAPs in the market, those sorts of GAAP would create more volatility specially, if you are dynamically hedging into the interim balance.

Couple of the observations about this, are that the monthly volatility is more volatile than you see on a quarterly basis that you guys actually see in the financial statements. So the inter-peer volatility is larger and the after tax and after DAC hedge costs in terms of looking at both the potential liabilities and the assets and that costs business is 3 to 4 basis point range, once again in a very same market.

Firstly, this is to what should we expect going forward from Principal First hedging. 2004 was great and the results we are very happy with, but in terms of going forward, we would accept more volatility. There are several reasons for this. First of all, we already mentioned, we look at contract -- contract holder behavior continuously.

We are already -- we are making a change in the first quarter of this year in terms of our withdrawal assumption. We're expect going to forward and we continue to monitor our expense and that we will bring the other changes in any community, a change in any of your liability assumption, that is helpful to create realized gain or loss. And that is helpful to create some volatility going forward and we continue to look at our scale.

Secondly, the Principal First block is being hedged just getting larger every day. The average account value size in 2004 is 12 billion. We can easily double that in 2005. So we had the same relative noise of block that approximately twice the size. We expect approximately twice the absolute level of noise. So that is helpful to create more volatility of the hedge program.

Third, as I've mentioned the market was came in 2004, if we encounter more volatile market condition such as October 1987 or September 11 or even if you look at the 1995 Stress Test Scenario, as I showed you and that's specific stress had there are some quarters where you have a block over the equivalent size that we have now for the quarterly GAAP earnings could be in the 30 to $50 million range after-tax and DAC. So and that was once again a considerable scenario in terms contractholder assumptions. These are scale for some of the volatility under strain conditions that we could see.

Last reason to expect more volatility going forward and ways to continue refinement in the hedge program. Once again we are trying to focus and stabilizing our GAAP earnings and also making sure we understand the impact of statutory surplus, expecting ourselves there and also trying to balance to hedging cost in a smart way in terms of way across our shareholders.

All we want to do is hedge GAAP earnings because these are very tight, but the other two might softer. And we don't want to have we thinks that's potential overall result takes a little bit more balance has a little more balance.

Before we wrap up, I just want to recap with the two main points that I was trying make in my personal presentation. First of all we know our block very well because we study it diligently.

Secondly, we track our contractholder experience every day, we try to understand it and most importantly we try use that experience in a proactive manner in terms of all of our modeling assumptions.

Third we set risk across the variety of time horizon and financial framework. We look at where the risk exists and where we're not comfortable and we design risk management programs, specifically, address the risk that we are not comfortable with.

And last that we're very pleased with our performance of hedging programs thus far. So we would expect more volatility going forward as we counter larger blocks of business and potentially more volatile market.

So with that I will turn over to David Braun, Senior Vice President and Chief Risk Officer of Hartford. As I've mentioned I've worked with Dave for several years and we're actually in right to beginning, helping to build the hedge program and we do talk everyday.

Thank you very much.

David Braun: Thanks, Dan

Kimberly Johnson: On the other thing I forgot to mention, I'd like you, if you would please, to tell -- we've got a story to tell on the liability side, the asset side and our accounting side. So please use a notepad to jot down your questions or slide the pages that you are interested in. This is webcast -- and so when we get to the question and answer session, we will ask you to use the microphone and we will make sure that those that are on the web can hear all the questions and get all the information. Thank you.

David Braun: As Daniel said I am David Braun. I've worked for the investment company and I'm to the asset side hedge, would on the liability side hedge. I am incredibly honored and excited about being here talking with you today about this topics and I've spent a lot of time in my career working on.

In the late 90s just from my background with a variable annuity risk management specialist for consulting firm, and then you can probably imagine during one of those strongest bull markets in history, being the risk management consultant for variable annuity wasn't a very lucrative or rewarding job.

For instance, from my own career, 2000 through 2003 half and then people realized stocks don't just keep going up, we've got to be prudent about the risk management. And that downturn in the stock market really fumbled some of the variable annuity rider to just active market share and did not focus on risk management.

And similarly, eroded those who are very diligent and responsible about risk management like the Hartford; you know, in our purchasing of reinsurance when it was available and then the passion and aggressiveness we threw ourselves in new hedging when the reinsurance side up.

So, that's sort of my background and sort of -- I'm going to talk to you a lot about the asset side of hedging. Dan did a great job showing you a lot of good things about our liability, our book of business, and sort of how hedging helps to substantially mitigate a lot of the GAAP earnings volatility and statutory surplus fluctuations. And I'm going to dig deeper into the capital market side of that and what really goes on, on the asset side of our hedging program.

Lets recap, in Principal First, we've provided a product to the consumer to give them the confident to get back into the equity markets, we give them the return of their principal or return of their stepped up principal, should we experience good growth in the early years.

And in order for us to do that, obviously, there is a risk that we have to pay them claims some day, as Dan describer, once your account while it gets depleted, it s our turn to start paying claims, should we still have the withdrawal benefit left.

Now, in order for us to do that, we have to be responsible, make sure we have a risk management tool that is going to give us gains on the asset side, should these claims however materialize.

And the capital markets provide us with the financial instruments, securities, derivatives that allow us to mitigate those risks, those claims, should they have emerged. Now, very important to note, that the capital markets give us a tool to manage this risk and mitigate the risk.

Capital markets do not give us a silver bullet to completely eliminate all this risk, there will be residual risk. And as Dan's charts showed you, lot of times the hedging looks very well and even under poor scenarios the hedging still provide you substantial protection. But it is unrealistic to expect any hedging program, not just for Hartford, but any hedging program to give a 100% protection in a 100% of the scenarios.

And one of the main reasons why a hedging program you can't expect to be perfect is, some of the dynamics and limitations going on in the capital market that cause that, and I'm going to talk a lot about that later.

But one thing I really want you to takeaway is that the Hartford has a thorough understanding of the risks associated with hedging. We are going into this with eyes wide open. We know hedging is not perfect, it's not the silver bullet, we understand it. We feel the fees we charge for these riders fairly compensate us for taking this risk.

We stimulate this risk to capital market based risk in all of the product development and product pricing works that Dan and Jim Trimble and the rest of the folks in the Life Company do, and all the Dan's risk analysis that he is showing you there and hedging stimulation, he is factoring in all these limitations and dynamics of the capital markets, so that the results he is showing you factor in the fact that this is not a perfect hedge.

So, let's just jump deeper into what's going on with the hedge. I am going to talk a lot about Option Replication, and I don't know if lot of you are familiar with this term, but I know you are all familiar with the term the "Greek" hedging.

And really, I am going to use Option Replication and Greek hedging interchangeably, because in essence, they are the same thing and I'll elaborate more. But there's -- maybe, four questions I want to answer in my presentation here.

One is, what is Option Replication or Greek Hedging; two is, why do we do it; three is, how do we do it; and four, what do we about the residual risks that are leftover once we do it? And I hope I see that in this presentation, and, if not, I'm sure hereby in the Q&A.

So, let something to -- sort of, might be out of word, but why do we do it? The main reason we have to use something like Greek Hedging or Option Replication is because there's no perfect offset to Principal First. There is no one security or one counterparty we can transact with to completely take off the claims with Principal First of our balance sheet. And the reason I say this -- you think about what Principal First is, it's not a pure actuarial risk, it's not a pure capital market risk, it's a hybrid of the two.

So, the strong actuarial component and the strong capital market component, which as a result there is no other counterparty; they are sort of the specialist in both of those. The traditional reinsurers will take the actuarial risk all day long, Wall Street firms will take the capital market risk all day long, but no one's really going to take both. That's where we come into play, and our expertise -- expertise of our actuarial and expertise of our people in the Hartford Investment Company, we think those two brings together where I really see that the managers want to take this risk.

And I look at a couple of reasons why the product is hybrid. It's got long maturity. The capital market view the benefit of fairly exotic. It's got step-up. It's got timing of the withdrawal issues and with the actuarial behavior over those which Dan talked about, the constant (inaudible) data trying to understand our data and come up with dynamic behavior, are driven to anticipate how people are going to behave under various capital market conditions. That's why we need to the Option Replicate.

Now what is Option Replication? Since you can't exactly buy something that moves in 100% lock step at Principal First, we attempt to replicate the Principal First profile. And we do this by purchasing security that we can purchase like options, features and slots, and we them under an asset portfolio that has a similar price sensitivity profile as the liability.

We don't need but I'm going to elaborate a lot of that. Basically this is Greek Hedging. The Greeks are going to tell us how the liability is going to move, and then we set up an asset portfolio that moves in the same way, and gives a complete lock set when we make $1 on the liability or lose $1 on the asset, so it would be neutral. Vice versa, if you lose $1 on the liability or make $1 on the asset, it will be neutral.

Now, on the wide range of market conditions and Option Replication strategy like this, we work very well, and I think Dan showed you that under the -- you know, the past two years, since we've been hedging, it has worked very well.

And even on the stress test, it's a very important -- and Dan showed you some bar charts and line graphs that showed how hedging performed under some pretty bad scenarios. You know, the 1995 to 2001 run up assume everyone reset their options in the market pretty fast. That's a very bad scenario.

And you see the hedging still provide substantial protection, and then we showed you the bars, the capital, the surpluses. You could a see a lot of those were truncated by more than 50%. So, even under the worse scenarios, you know, hedging is going to cut off a significant portion in the tail.

Now, this is a chart, I think, you've all seen from the prior Investor Day, and I'm going to use it here to elaborate on what I mean by Greek Hedging. Basically, going up and down are the Greeks, the three primary Greeks. And then, going across the top are different financial securities that's GMWB in the Greeks.

And my job and the job of my team at HIMCO is to manage the portfolio of those securities going across the top of this table. And thus -- before we jump in what the Greek are, let's recall that. What we're trying to do is set an asset portfolio that has similar price behavior and moving it in its market value to the liability.

But we need sort of a roadmap or crystal to tell us how to set that up. And that's what the Greeks are. The Greeks are -- I could get -- I could really show how nerdy I'm by talking in full detail about the Greeks, but -- so you are not (inaudible). A Greek is just a derivative. Its how does the price change when some of the parameter in the capital markets change. So it tells you what the market value of your liability or your asset is going to do if something in the capital market move.

Let's pick Delta, which is one of the most well-known Greeks. Delta tells me, let's say -- I'm talking about the Delta associated with the S&P 500 -- Delta tells us for every 1% move in the S&P 500 what happens to the liability for Principal First.

So, for instance, let's say Delta is 10; just put a number around it, for every 1% move in the stock market, we're going to make at least $10 on the liability. I then know given that information how my liability is going to behave, what the assets need to do. So, we down at HIMCO set up a portfolio of assets, so they move in the same amount, the $10, but in a different direction. If the liability loses $10, the assets will make $10, and vise versa.

And then, just elaborating on the rest, there were other two primary Greeks. Vega: it's the same exact measure, but -- rather than how does the S&P move, how does the implied volatilities move. Implied volatility is the mean as far as the option pricing, and to follow, the capital market is getting a lot more standstill lately.

Even this morning I was in the room getting ready and CNBC was talking about the lease market which is the exchange hitted (ph), as long as the exchange goes out two years -- equity option market, how low that volatility is now. And, you know, so this is a very important Greek and one of the more challenging to manage. And then, Rho -- it's how does the market by the liability or the asset changes, interest rates change.

Now, these are three primary Greeks, and we spend certainly a lot of time focusing and talking about three primary Greeks. But even more important, more challenging to manage for us than these three Greek, let's call the Cross-Greek. And you know -- I apologize, but let's just talk about the Cross-Greek a little bit. I said the primary Greeks are the first derivative, while the Cross-Greek are the second and third or fourth derivative.

Basically, the Cross-Greeks tell you not how do your liability change when something in the capital market move, but how do the primary Greeks change if something in the capital markets move. Perhaps an example will help, Gamma (ph) is one of more popular Cross- Greek (ph), and I use the term generically, Gamma is just a derivative of Delta.

So if Delta is 10, I told you how your liability is going to move. Gamma tells you how that 10 is going to move. So, Delta is not seeable over all capital market environment. If I miss the 10, which is Delta, could go to 11, it could go to 9, it could go to 13. Gamma is the (inaudible) statistic that helps you predict what your primary or where your Delta is going to go. And then there are other Cross-Greeks; there's a whole array of then that tells you where these three primary Greeks are going to go.

Now before I talk more about some of the challenges and risk of Option Replication, let's first talk about how we do our hedging. And I'll do this by walking this through with today in like of Dan Gilbert and David Braun and our teams.

The process, just like the presentation today, starts with Dan Gilbert and his team. And they work very closely with the information technology folks lead by Vic Severino. Vic is going to talk to you about what a phenomenal job based on building best-in-class infrastructure that allows us to get the information we need to manage the hedge.

Basically, Dan is just seeing one model that over 100,000 (inaudible) run every night, the Greeks -- the Cross-Greek, the market by the liability and decompose the change in our market value that liability based on how everything penned out the prior day in the capital market perspective, and how did our policyholder enforced that move.

So, again, in fact, everyday from our admin system which are earned the number of hundreds of thousands of policyholders. And these closing capital markets data run this thing down on an eight, nine hours.

Myself and my team coming into work in the investment company the next morning, seeing in our inbox is a file from Dan and his team was pretty much every Greek and Cross-Greek we want and all sorts of great information on how the market by the liability behaved over the past 24 hours.

We then take this data compared to the similar statistics on our asset file and we look at that and we compare the Delta's, the Vega's, the Rho's and we figure out whether there is any gaps that exceed in pre-described threshold. And what we do then is, we now know where we need to do the trade, we maybe have too much Delta or too little Delta, we need to go to trade.

We have our trade well lined up and when the capital markets open, we trade, we snap ourselves back to Greek neutral and I'm using that phrase a lot, Greek neutral just means, I setup an asset Delta or Vega or Rho that completely neutralizes my liability Greek, which being hedge.

Another incredibly good thing we do here is, we produce a daily profit and loss statement for the hedge and we don't just say it made a loss 10 times now, we figure out where that 10 grand came from. And literally the buckets we are filling there, you know, everything from S&P beginning movements, the policyholder file changes, the volatility changes, and it's a study that you look at it and this helps us modify our hedge, figure out where we are doing well, where we can improve etcetera.

Now, unfortunately, once we snap back the Greek neutral, we can't just go home for the day as much as we like to. This is because the Cross-Greeks, as I talked about before, they cause the regular Greeks to change, in those times the asset and liability, which do not change at the same way or speed, so we have to sit there and continuously monitor this.

Unfortunately, Dan's team gives us an enormous metrics of Cross-Greeks, and we would leave that up to a (inaudible) or feeding capital markets information. So as the day changes, we use that new information in the capital markets in the Cross-Greek from Dan's team to predict what the real Greeks, the three primary Greeks of the liability look like.

And obviously, we can't swap it at real time, as I said before; it takes nine hours to end the model, such as it is good as it gets from approximation method. And that allows us to figure out what trades we need to make, so by lunch time, the stock market is up 3%, the Greeks in that morning is stale, we use this system to evaluate what the new Greek should look like, we trade based on it.

And then everyday in our rearview mirror we use the Friday's Cross-Greeks to validate how the liability actually moved and behaved and how the Greeks themselves moved. And this gives us a confidence into our Cross-Greeks and our intraday approximation method, it's bottomed-up and rock solid.

Okay, now, we are going to talk more about something, and I've showed you, what we do, why we do, and how we do it? I'm going to talk about the risks and what we do to combat some of the risks. And these risks are not specific to Principal First hedging, these are specific to any Option Replication strategy and the primary risk of any Option Replication or Greek hedging strategy is rebalancing there.

Now, we talked about how you can't just say and forget this thing and its bottomed-up and its rock solid. The Cross-Greeks deviations in actual – from actual to expected policyholder behavior cause the Greeks of the liability to move at a different speed than the Greeks of the asset. Therefore, we need to buy ourselves derivatives throughout the day to maintain our hedge.

Now that buying and selling is what I'm going to referring to is rebalancing. Rebalancing exposes us to two potential costs; the first and more intuitive one is transaction cost. Every time we buy and sale a derivative from Wall Street, some of the Wall Street people I trade with, they are here, they can tell you, we pay them a commission. We pay them a transaction cost either an exclusive commission or in the form of a bid/ask spreads. And those are typically small; if you're doing a lot of frequent trading they can add up.

So the way we view is, we make sure we do a very robust in sale, cost benefit analysis, the frequency of trading, because if there were no transaction cost, you don't want to trade on every pick of the market and always be 100% hedged. In reality, instead of threshold based on a cost benefit analysis that balances this frequency versus transaction costs. And that's intuitive of Option Price Uncertainty.

Now, from the chart, before you saw that we only get Vega from options and the option market times experience supply/demand imbalances. First of all the market, for the most part and over the counter market, there is no website to (inaudible) open interest.

The supply and demand themselves are very hard to pinpoint and understand the dynamic of them and usually there is some sort of political or financial catalyst that causes supply/demand to get out of DAC and thus moves the prices in options. Did you know with any supply/demand inflation, price is a balancing item. Price is the lever that will move to bring supply/demand back to equilibrium.

So the risk here is that should we into rebalance ahead into the supply/demand mismatch being option where we're purchasing could be a different cost then initially. And we're trying to stop in both transactions cost -- let me get to next slide before I jump -- on my own risk.

Basically, the three things we do to combat this risk and they are very important. Now we've talked about how we are going to (inaudible) there is thorough understanding of these risks, the Cross-Greeks and the risk associated with them and the balancing risk completely factored in how we manage our hedge and really this first bullet point should have been elaborated. It really all suspected and how we design our products, how we place our products and how we do our work analysis and overhead with that testing.

We fully understand what's going on there. We know it's not going to perfect. We know what the pressure points are and we are going with eyes wide open and see that it would be fairly compensated for this risk, but be at a lighter side of recharge.

Another thing we do is we're trying to mix this hedge, there're multiple buying hedges it can be. I already talk about how it's going to have rebalancing risk that's the nature of these, but we do think for some proprietary trading strategies and we presume the structure of exotic options from what we -- that gives us more Cross-Greek that allows us to rebalance, it have less, and thus helps us to fight that transaction calls and option price volatility for us.

Another thing we do is in constant communication with the Street going to cover up honestly in the supply/demand dynamics, PDR have got value is in market, PDR -- what's going on in structured parts, where they can help us make our hedge even tighter.

Honestly I answered all of the questions I ask to myself. So I just want recap what hedging is? I'm overtime, I apologize but there is no perfect hedge for Principal First. We therefore force to replicate it using the available instruments that are available in the capital market. We do this by matching the Greek.

We understand the risk associated with this strategy. We feel we've been fairly competitive for this risk and we are continually -- you know, the hedge has performed incredibly well inception a day we're continually refining and improving it and really pushing the limit of what we can do here as to get the things as tight as possible.

With that thank you very much. I have enjoyed this and I look forward to your questions. Thank you.

I think its time for a break, right for few minutes.

(BREAK IN SESSION)

Lizabeth Zlatkus: It's time to bring you all back to your chairs. One thing I just wanted to cover is, because there is a several questions at the Q&A which we wanted to make sure that everybody is going to get the answers too including anyone that's on the call. So before the Q&A begin, we will bring up that chart with the red line that 1995 scenario and cover that again, so it seems to be a little bit of confusion on that particular example.

But I thought, we would go through the accounting, next we're going to have our Chief Accounting Officer, Ernie McNeill come up, and again, remember this will help you kind of see the derivatives points come in -- comes in, what happens to ascribe these, how do the gain and loss work, so will help you go through the income statement and help you think about the accounting, because accounting in and itself is also quite complex.

So we are going to have Ernie come up and will talk about technology and then probably bring that slide up again to cover one more time and then go through the Q&A.

With that, I am going to turn it over to Ernie.

Ernie McNeill: Thank you, Liz. Good morning. My presentation here today is intended really as a refresher as to how the accounting for the Principal First benefit and the related hedging portfolio works, and in the interest of priority, what I want to try to do here this morning is talk first about the Principal First benefit and how we account for that and then move on to discuss with the hedging portfolio.

And I think sometimes there are questions where we really try to look at things in that and it's actually less confusing, I think, it's disaggregate the pieces.

So, if we go on to the next slide, the Principal First benefit is a derivative for GAAP accounting purposes and it's governed by the provisions in FAS 133. Specifically, it's what's known in 133 is an embedded derivative, meaning that it is a contract with the financial instrument, but part of another contract that's not itself the derivative. In this case that contract is a variable annuity contract.

FAS 133 requires that embedded derivatives be bifurcated or separated from their host contract, because the accounting to those derivatives is different from that financial instrument and those really measured at fair value.

The separated derivative that I mentioned has a fair value of zero at inception or in capital market terms its act of money. This is required by FAS 133 as accomplished by first calculating the estimated present value of the benefit that are expected and then attributing or ascribing an equivalent amount of fees from the rider to the derivative. I'll discuss these concepts in greater detail in a few minutes. The rider fees collected in excess of what is needed to cover the cost of the benefit are shown as variable annuity fees on our financial statements, just in the same way that M&E fees show up on our financials.

If we turn to the next slide; we'll see a simple five example of this. As I mentioned earlier, the allocation of fees to the derivative and the base VA contract is determined based on a best estimate of the cost of the Principal First benefits at inception of the contract.

And what I mean by this best estimate is, under FAS 133 this is a valuation of the derivative that is consistent with the way the capital markets would price derivative. So, thinking back to some of things that David talked about in his presentation, this is a valuation consistent with how traded derivatives are priced in the capital markets.

In this example, the Principal First benefits are assumed to cross an annual of 16 basis points of account value, out of the total 50 that we currently charge for the rider. As we'll see in a moment, this 16 basis points becomes a component of the derivative value, remaining 34 basis points out of the original 50 remains with the host VA contract and appears in our financial statement in the same way that M&E fees do.

The final point here on this is that the allocation rate -- the allocation rate of 16 basis points is set by cohort that remains constant for the life of the cohort, and here, a cohort is defined for this purpose, as one fiscal quarter's production. And just to be clear on this point, it's the rider fee that is constant.

And as we'll see in a moment the actual dollar amount of the ascribed fees will fluctuate with the account values and that impact the subsequent valuations of the derivative.

At this point, I would like to take you through an example to show how the Principal First embedded derivative works instead to facilitate this conceptually I have done an analogy to a common derivative in the capital market, the swap contract, something that probably all fairly familiar with.

And basically the exchange here, as we have said before is, that in exchange for an ascribed fees stream we will pay benefits to policyholders in the event that their account values are exhausted in the future. Thus, we have a pay and receive leg of this hypothetical swap.

The receive leg is the fee stream that's collected daily from policyholder account value. Now, the pay leg -- and its fair value -- and this is an important concept for 133, its fair value is the present value of those future fees.

Now, the pay leg is what we owe to the policyholders ultimately if their account values are exhausted, and in this case, the pay leg or in contrast to what happens on the receive side, the pay leg is payable many years in the future when those account values are exhausted. The value of the pay leg is similar to the receive leg is the present value of those future benefits. This difference in timing will be important; we'll see in a moment.

So, continuing with this swap analogy, we see here; and one of the things that's important to notice is that both legs of this swap are variable. A lot of times you have a swap; there was a fixed side and a variable side. In this case, both sides are variable, both sides fluctuate. The swap is mark-to-market each period by recalculating the values of both of the leg.

Now, we called it values of the legs and nothing more than the present value of the amounts assumed these are on the fee side or on the liability side or the benefit side. And they're sensitive to these four factors that we talked about already; market returns, the volatility of market returns, interest rates and policyholder behavior. And while it's obvious that the estimated future benefit fluctuate based on these four factors, it's also important to remember that the present value of the fee stream will change as well.

On the call, I said earlier, that the ascribed fee rate does not change. However, if the account values will fluctuate, the estimated dollar amount of the ascribed fees will change. Now, changes in these factors of each period result in recognition of gains and losses, and this is the mark-to-market process. This is the process of bringing the swap to fair value of each period in our financial statements. And as we'll discuss later, if these gains and losses that we seek to mitigate in the hedging program; and this is what Dan and David talked about earlier.

Continuing with the example, the swap value at any point in time is the net of the values of the pay and the receive legs, the present values of future fees and benefits. As I noted earlier, this value was zero at inception because the estimated present values of the benefits are calculated first, and then, the equivalent amount is stripped away from the VA contract and placed with the derivative.

In our example, this is 16 basis points. So one thing to note about the timing of these pay and receive legs, because we collect the fees daily from the policyholders account value, so if the benefits are payable in the future; in some cases many years in the future, the swap will gradually become a greater and greater liability as time passes, if we hold everything else constant.

If we turn to the next slide, we'll see a numerical example of this, and please don't read too much into these numbers. What I'll try to do here is use very simplified numbers and to some extent exaggerated the amount to make the example little more clear.

So, if we start in that first line there, at inception, we've got a receive leg, that the present value is ascribed fee; a pay leg, that the present value of benefits payable, notice they are same -- they are the same amount, $100. And again, we're calculating the liability first, and then setting the asset equal to the liability.

The next two line shows the daily receive of ascribed fee. So, again, nothing changes in the market, but, all we do is we collect those fees from the policyholder account value. So, if we collect one days work, its 16 basis points. If we do that for a couple of days, you'll see that the net value of the swap goes from zero to a liability, simply, because the collecting on the receive leg have not yet paid anything on the pay leg.

If we drop down to the second part of the slide; the second half of the slide; now we'll start again from zero, but lets see what happens with the effective market movement. On that next line down there, the market drops, and what you see is that there's an impact on both legs of the swap.

As you would expect, the present value of the benefit side increases, and so it went from a 100 to 115. But similarly, there is a drop in the ascribed fees because now the account values have decline, so with the interaction of both factors that creates a realized loss of 25, which you see in the next column.

Now if we take the opposite situation, where the market rises. Now the ascribed fees become valuable, the 100 goes to 110, the 100 on the liability side goes to 90, we have a realized gain and so that's the gain. So it's these types of gains and losses that we are trying to offset with the hedge portfolio.

So let me turn now to the discussion of the hedge portfolio. As I noted a few minutes ago, the hedge portfolio seeks to minimize the GAAP volatility of the Principal First derivatives mark-to-market adjustments each period. This hedge program is an economic hedge, in the sense, that it doesn't qualify for hedge accounting under FAS 133.

As a result, both the changes in the value of the Principal First embedded derivatives and the hedging portfolio are mark-to-market through earning. There is no deferral accounting, as you would get, if there was a qualified hedge under 133.

Like the changes in the embedded derivatives, the mark-to-market on the hedge portfolio creates realized gains and losses, some of what we just saw on the last slide. The other to note that's important is that the cost of the derivatives that we purchased -- that we purchased in the hedge program becomes an asset on the balance sheet. So the assets then are going to be subsequently mark-to-market each period and that will give us gains and losses.

What this slide attempts to do is, build on the example we saw just a few moments ago, which is up at the top in gray. Down at the bottom we've now added a section on the hedge portfolio, so if we start again from the at inception position, it's at the bottom of that top part of the slide. You know if I point myself to make it a little earlier.

Okay. So we are right back where we started. $100 present value of the fees, $100 present value of benefits, zero net swap value. Now what we do is, we go out and we purchase options of $30, so now you can see we have a $30 asset. We spent $30 of cash. Now, let's see what happens, when we have the two same scenarios happen, where the market drops, we watch what happens here, again, what happens these numbers are exactly the same as they were in the example up here.

So, thus, the embedded derivative by itself goes to a negative 25 or $25 liability. But look what's happened now on the hedge portfolio, we've gone from an asset of 30 to an asset of 54. So the gains on the hedging portfolio have offset the losses on the product, resulting a minimal net effect. And this is what David and Dan were talking about earlier.

Similarly, if some market rises, now, again, these are the same impacts on the embedded derivatives, which has gone into an asset position of 20, and now the value of the hedge portfolio drops from 30 to 8, offsetting most of that increase.

Again, I would say, when we look at these numbers, you know, don't read too much into these numbers. This net volatility could be a small gain or small loss. But the point here is, we are really trying to take a result like this to get it down to more of a result like this.

So if we turn to the next slide, we'll see some actual numbers. These were the actual hedge -- these were the actual 2004 full year results for the Principal First program. Starting now at the top, our gross fees collected of 49 million. This is what -- these are the fees that we get off the Rider.

Now, as I mentioned, we currently charge 50 basis points, this will be the analogues number to 50 basis point on our income statement. Then we take out the fees that are ascribed to the derivatives. So again, these are not VA fees, these go into the valuation of the derivatives. So the net fees that we're left with in variable annuity and life fees is the $30 million there. Okay? I would ask you to bear in mind that all of the numbers on this slide are pre-tax and pre-DAC. I did that to keep it as least confusing as possible. But obviously the effects of DAC and tax tend to mute these numbers by the time you get to our income statement.

Meanwhile, what's happening down in realized gains and losses, we see a change in the embedded derivative of $55 and this is a gain. And the reason for the gain is, as we mentioned, the S&P went up significantly, or went up in 2004 so the value of the embedded derivative went to a greater asset position. Similarly, the hedged assets lost money during this period, resulting in a net realized gain of $8 million, again pre-tax, pre-DAC.

In closing what I'd like to do is shift gears a little bit and just mention some of the other -- some of the accounting for the other guarantee features in our VA contracts, aside from Principal First, namely guaranteed minimum death benefits and income benefits. Unlike Principal First, these benefits are not derivatives.

So, as a result, they follow a different accounting model, SOP 03-1. SOP 03-1 does not employ a fair value model so there's no periodic marking to market. Instead, what you do is you come up with your best estimate long term assumptions which again, over time may be subject to unlocking. And our Japan VA product follows this accounting convention.

That concludes my remarks. Thank you for your attention. I look forward to any questions in the Q&A round. It's now my pleasure to introduce Jim Trimble, Hartford Life's vice president and chief actuary.

Jim Trimble: Thank you, Ernie. Good morning. So as I was listening this morning, it occurred to me we probably should have called this Three Actuaries and an Accountant. I'm not sure what that would have done to the -- I'm not sure what that would have done to attendance, so I think it's good we stuck with what we did.

Liz yesterday concluded her remarks by talking about four ways that we manage risk at The Hartford. Those included product design, pricing and underwriting, reinsurance and hedging. This morning, I'm going to talk to you about how we use product design and pricing to control our risks in Japan.

One key point I'd like to make is that we use the same very disciplined approach to product design and pricing in Japan as we use in the United States. Dan talked here earlier about the dynamic lapses, the dynamic assumptions that we use in the models and we use those same stochastic models in Japan.

In fact, our scenarios are provided to us by the same people in David Braun's shop that provide the scenarios for the U.S. and we subject ourselves to the same review by corporate actuarial and at that time it was (inaudible) that's used in the U.S.

My comments this morning are going to focus on our latest Japan variable annuity product, the one with the guaranteed living benefit. Now, one thing I'd like to point out is that in Japan, our guaranteed living benefit is actually a GMIB benefit. It has some features that are like our withdrawal benefit, but technically, and actually in order to comply with some Japanese regulatory requirements, it's a GMIB.

Some of the features that make it that are the minimum 10 year deferral period, it's got a fixed payout period of 15 years typically on the product we usually sell, and importantly, for the product that we typically sell, if a customer chooses the guaranteed annuities rider, the amount of money in the separate account is actually transferred to the general account and it's from there that we pay that fixed benefit.

So it's important to see that The Hartford's risk here is that at the time someone elects the guaranteed annuity rider that the amount in the separate account is not equal to the present value of the future payments we're going to make. Not that we're guaranteeing that we're going to have the whole premium at the end of 10 years, but only that we can fund the present value of those payouts over the payout period.

We do also have a version of the product where the money does stay in the separate account and there, during the annuitization phase, the same investment restrictions that apply during the deferral period also apply in the annuitization period.

While this is a GMIB product, I thought it'd be important to point out some of the differences between our Japan GMIB and some of the typical GMIBs that are offered in the U.S.

In a typical U.S. product, the benefit richness increases over time for the length of the deferral period. For our Japan product, that's not the case. We simply guarantee that the sum of the payments will equal the amount of the initial premium regardless of how long the deferral period lasts. Also, as I said, it's a fixed payout period; it's not a life annuity.

On the next chart I've taken, I guess on your right-hand side, the Japan product chart that Greg Boyko showed you yesterday and I'm comparing that with the U.S. features. What you can see from this chart is that we have used product design to control the policyholder behavior risk for our Japan products.

In both Adagio 10 and Adagio 15, there's a lengthy deferral period before the guaranteed annuity rider can be elected. And, as I said, once that is elected, the payouts are for a fixed amount over a fixed period. For Adagio 10 the payout period is actually 15 years and for Adagio 15 it's a 10-year payout period, so that in each case, at the end of 25 years, the policyholder will get back their premium. Also in Japan, we have no reset provisions and the rider is not revocable.

Finally, for both Adagio 10 and Adagio 15 there are investment restrictions. Basically, a customer who wants these riders chooses a balance fund. For Adagio 10 the balance fund consists of 25% equities and 75% bonds, whereas for Adagio 15 it's a 50/50 equity and bond mix. In both cases, the equities and bonds include both Japanese equities and foreign equities, Japanese bonds and foreign bonds.

On the next chart you'll see that this product has been pretty popular in Japan. In fact, of the 7.3 billion of new variable annuity sales in Japan in 2004, approximately 95% of those sales are by customers who chose the rider.

As a result, by year-end 2004 already over 51% -- about 51% of our assets in Japan are with contracts that have this rider. It's also interesting to note that even though we just introduced the fixed annuity rider in the last quarter of last year that already represents 3% of our assets, so you can see we're growing some good diversification there.

On the following chart I have to admit that there's some things mislabeled so I'm giving you a bit more information than from what I had intended actually. This chart -- the pie chart really refers to our 14.5 billion total inforce and so the net amount at risk here, or the contracts that are in the money include both the GMIB contracts and our older Japan product that we had just a guaranteed minimum death benefit.

I can give you the numbers for just the GMIB contracts as of the end of February. At the end of February for contracts sold with the GMIB rider, about 97% of those contracts are actually out of the money. And of the remaining 2 to 3% that are in the money, the average amount of in the money (inaudible) amount at risk is actually less than 1%.

That gives you a pretty good snapshot of where we are today, but of course the real question is what are the long-range costs of this benefit and that's shown in the next graph. As you can see, in most scenarios we expect the long-term benefit cost to be 0.

And, in fact, in the vast majority of the scenarios we think that the 25 basis points that we're charging for the rider will more than cover the benefit cost. Of course, there is still some tail risk but that's just when you get to the tail. And it strikes me this chart is very similar to the one that Dan showed you from Principal First earlier this morning.

Of course, Dan looked at that chart and said, "Well, why are we hedging in the U.S.?" So I guess that leads to the question, why aren't we hedging in Japan? And maybe that's an answer.

Actually, what I'd like to do is address that question of why aren't we hedging in Japan from the same three points of view that Dan suggested why we are hedging in the U.S., from a GAAP standpoint, a statutory standpoint and from the standpoint of the long term economic risks.

First, let's talk about GAAP. As Ernie pointed out, our guaranteed minimum income benefit is not subject to FAS 133, it's not a derivative contract. Therefore, the GAAP accounting for this benefit is pretty stable. There's minimal GAAP volatility. Interesting, that means that if we choose to hedge this product we will actually be introducing GAAP volatility into our income statement because the hedged assets themselves will be mark to market and will contain some GAAP volatility.

That brings us to statutory. As you know, the laws in Japan regarding statutory reserves and surplus have recently changed. In our latest guidance we told you we expect to contribute in the neighborhood of $100 million of additional capital to Japan -- for our company in Japan as a result of those changes.

Now, we're comfortable that our product will continue to achieve acceptable return levels even with that additional capital. We're also comfortable that we're managing our capital requirements effectively through product refiling and through reinsurance.

Now, it's interesting that because we have to put the additional capital into Japan, we're kind of pre-funding some of the risks, which means it takes out some of the statutory volatility. They're requiring us to put that money in upfront. We're still working through the exact details of how our product refiling and how our reinsurance will work, so I can't show you the exact numbers. But I can tell you that we're comfortable that the resulting impact and the aggregate statutory volatility for the Hartford Life Company is something we're comfortable with.

So if we're not getting hedge for GAAP reasons, we're not getting hedge for stat volatility reasons, that gets us to the long-term economic risks. But as I've already said this morning, we think that our product design effectively really controls a lot of the policyholder behavior risk. Again, we have no reset provision, we have fairly lengthy deferral periods, and again, when somebody does elect the rider, the benefit amounts are fixed both in timing and amount.

So, from policyholder behavior perspective, we've got the risk controls. Of course, there's still the risk that in the tails, the account values will not be sufficient to provide the guarantees because they are going to be affected by equity returns, interest rates and currency movements. Right now, we're comfortable that in the aggregate we can live with that amount of tail risk. However, as we continue to grow the business in Japan, we are considering tail risks and tail hedges and that's something that we look at quite frequently.

I'd like now to turn to a couple of quick comments on C3 Phase II. C3 Phase II is an NAIC initiative concerning the calculation of reserves and risk-based capital that applies to variable annuity contracts and their associated guarantees.

The risk-based capital portion of C3 Phase II is something we expect to be implemented by year-end 2005 and we expect that this will be effective for reserve calculations in 2006. C3 Phase II is a model-based methodology.

You model your variable annuity business over a broad range of stochastically generated scenarios using prudent best estimate assumptions. This model includes all revenue, benefits and expenses, it includes all the assets you currently hold, including your hedge assets, and it should include the impact of reinsurance and your future hedge strategies.

The calculation is what's called the Conditional Tail Expectation Measure, which is a measure of tail risk. Best way to define it is through an example. A CTE 90 calculation means you take the average of the results of the worst 10% of your stochastically generated scenarios and that CTE 90 level is going to be prescribed as what's called the total asset requirement. The reserve calculation is done similarly. It's a CTE 65 calculation, which is the average of the worst 35% of the scenarios. So you set your reserves at the CTE 65 level and then take the difference between CTE 90, which is your total asset requirement, subtract the reserves, and that leaves you with your capital requirement.

The advantages of the C3 methodology are that it aligns the calculation of the reserves and the risk-based capital requirement to the underlying risks much better than any formula can because you're doing it for your own inforce business. You look at your product design, you look at your mix of assets, the age of the policyholders in your particular contracts, and that's much better than any formula approach can ever do. This approach also rewards risk management techniques, such as reinsurance, hedging and product design. And because it's an aggregate approach, this lets companies recognize the benefits of having a wide range of product designs and a wide range of differing guarantees.

C3 Phase II is something The Hartford has actively been involved in, in both the development and the analysis of the proposals and, in fact, we've been already anticipating that and using it in our pricing and in our capital management decisions already.

That concludes my remarks. I'm going to turn the podium back over to Liz for some concluding remarks and followed by the questions and answers. Thank you.

Lizabeth Zlatkus: Okay, we're going to end with some technology discussions. I'm here to talk to you about what is the infrastructure that we need to be able to support all these calculations we've been talking about. And I want to remind everyone that this is the technology that supports all of our risk analytics across the spectrum, so this is not just the technology that supports the hedging program per se.

But what's great about it, it's the technology because the same kind of theory option-based thinking, how we hedge, policyholder optionality, all of that understanding to develop new products and tweak our existing products requires a lot of calculations. And so we need a very robust technology platform to be able to do that.

What I'm real excited to talk about this morning is something called grid technology. And grid technology is something that Hartford employed in 2004. Let me tell you a little bit about it. First of all, what does it really do? If you look down at the bottom there it says it works like a virtual supercomputer. Grid technology allows you to kind of bring together the CPU or computing power of the various computers, whether it be a server or even a desktop PC, and kind of aggregate that CPU and be able to run your analytics across all of those CPUs.

So, for example, if you needed to -- when we started hedging we had about 35 CPUs that we needed to be able to begin our hedging program back in the fall of 2003. We knew that once we got to about 50 to 60 CPUs that we were going to start to have problems in being able to aggregate them. What happens after you get to so many of them is that you have to kind of chunk up your calculations, so you have to kind of break it into pieces. What we need to do both in our product development and our risk analytics and our hedging is to be able to run massive computations all at the same time and look at those interrelationships. So it doesn't work when you're kind of breaking up those calculations into pieces.

Grid computing has allowed us to be able to bring that CPU power together really limitless. So today if you see some of the -- if you can read in your book because you may not be able to read up on the screen, we went from 35 CPUs that we needed to run all of our calculations to now over 350. And remember, it's not just a matter of being able to buy servers or desktops; it's a matter of being able to use them all together. So without grid, we could not be able to tie those 350 CPUs together.

Now, where does grid technology start? Did we come up with the idea ourselves at Hartford Life? Well, unfortunately we can't take credit for it. If you think of grid technology, it has been in use in the academia world. If we go back to the Internet, remember how long the Internet was out there in the academia world? Now, once it got commercial use, it kind of transformed how we really work and live today. Grid technology has been out in the academia world in huge research projects such as particle physics or genetic research where they need massive computations. It's already been out there. But we do think we're the first life insurance company to pioneer it for our ability to do these risk analytics.

If you look at some of the, over on the right, some of the facts, I love pictures. In my mind, the staff that we have at The Hartford is just phenomenal and I like to get updated on what we're doing on technology and I always ask for what -- say that in a picture. If you think about we went from 35 CPUs again to 350, we processed hundreds of millions of calculations a second. Kind of mind-blowing in terms of our sophistication.

The other thing we had to do is not just be able to tie all these CPUs together to again be able to access the computing power, but we also had to run our -- allow our programs to run faster. When we started our risk management in the fall of '03, I remember being so excited because we were able to get our programming to be able to run all of the math calculations and look at the analytics significantly faster than we had first started. But you know what? That turned out not to be fast enough.

So today, with grid technology and as well as some of the refinements we've done to our programming, we can run our analytics 10 to 20 times faster than we could in the fall of '03, which is more than 100 times faster than we started our hedging program -- I mean when we started to develop our hedging program. So 100 times faster.

What about how much data we're really talking about? In one month alone, our hedging process really kind of consumes enough data in one month to fill the Library of Congress.

So sometimes I picture 12 Library of Congresses around (inaudible). And we don't store all that data, so a lot of it's analytic looking at it, and then we don't necessarily keep it all. But it does go to how sophisticated we've really become.

When we talk about 350 CPUs, kind of where do we go next, what grid computing is allowing us to do? We've already prototyped it and we're going to be employing it in 2005. Not only can you access server CPU, but it allows you to access desktop computing power. So we all know oftentimes what our desktop -- even if we're at our computer at our desk, we're not necessarily using much of the computing power. We all know we have so much more computing power on our desktop than most of us ever use. And then oftentimes, of course, we're not using it at all. Nighttime we're not accessing that. Grid computing allows us to kind of capture the CPU power for all the desktops of all our employees.

So when you think about it, it's kind of almost limitless scalability and resiliency because it's not just again a matter of money, so we can save money because we can access desktops versus buying servers, but the ability to aggregate all of that and run simultaneous calculations is the real power of it. So it saves cost, it builds scalability, resiliency. We today run all of our Linux simultaneously across two data centers.

At The Hartford we're very, very diligent and we work with David Johnson to look at our business continuity planning. We have to be able to have failsafe recovery. You heard Dave and Dan every morning and the whole team behind them, wake up every day and they need to have all of those analytics. We can't have any downtime. So today we run over two data centers concurrently. Obviously, in disaster recovery we already have a built-in backup plan.

So we're going to stop there, but we're already starting to talk with technology vendors to harness if we ever have a time where we even need more computing power, which right now we have so much available to us.

But at peak loads or times we may want to come up with new products or look at new regulations that are coming out and we want to do fast calculations, we can then tap into what we call grid technology centers to harvest or borrow the computing power of data centers of technology companies.

So if you think about that, they may have thousands of CPU computing power and we could do it at peak loads. So we don't see the need for it right now, but we want to be prepared for the time that we may want to access additional computing power on top of our own desktops and servers.

So when you think about what we've done to date, where we are going to, we think this is an extraordinary competitive advantage because we absolutely could not run the calculations that you've heard about this morning without being able -- without having employed grid technology.

I'd kind of end with two things. Number one, you certainly see we have gotten a lot of press on this. We do think it's extremely innovative for the life insurance industry. Again, it has been out there in the academia world and also with some pharmaceutical companies as they do genetic research and drug testing. But we're very proud of the financial team under Vic and really works closely and collaboratively.

I'd like to end before we open up for the Q&A to just kind of take a moment and thank certainly all the participants and the members that came up. Hopefully what you saw is an enormous amount of talent and dedication and daily robust monitoring of our hedging programs, using that technology and that knowledge to look across our risk metrics.

And also I want to remind everybody about the team behind them back at Hartford Life and also the senior management team that gets involved in this. I mean it's great to have Craig Raymond, who was very involved in developing the hedging program, move up to The Hartford Financial Services Group, but look at all of our risks across the spectrum, he still brings a lot of insight.

He's involved David Johnson, like I said, Tom Marra, John Walters. So the team of people that are looking at this, monitoring it, thinking about our risk going forward, thinking about our products, looking at C3 Phase II, incorporating that all into our pricing, looking at how we can develop products and how the benefits of aggregation works across the system, the very comprehensive kind of risk management philosophy.

And yesterday I think you heard somewhat redundancy in my comments versus the lines because risk management is integral in the lines as CFO and in charge of a lot of the risk at Hartford Life in terms of kind of on an aggregate basis. It's very much of a team environment and also that was the HFSG group. So hopefully you see the power of the people here, as well as the team behind that.

With that, I'm going to actually go back to the slide -- Caroline, if you can go back to the one that's actually hedged. I think there'll be a lot of questions on this slide, so I thought I'd take a moment before I bring the team up here to answer the Q&A, just go through that red line. First of all, remember this was one scenario. So we -- this was actually going back into that 1995 timeframe, $10 billion written all in one day. And remember, as good as our sales have been, we never wrote 10 billion in one day.

So we don't have any benefits of diversification in terms of when a business comes on the books. We assume everyone started back in 1995, $10 billion, market completely rallied, they all reset on the same day at the (inaudible) market. So five years later they reset. Now, that would mean that all the policyholders would call into Hartford Life and reset on the same day. So we think that's probably improbable.

But what we like to do in our stress testing is to stress test. So it's a nice example of saying, "Well, what if that could happen, they all reset?" You can see a lot of volatility in the GAAP line and (inaudible) volatilities were -- I'm sorry, in the blue line, before hedging and (inaudible) were moving along.

Again, you had a lot of noise because all the policyholders reset and then the market dropped. What happens when you look at the red line, that is all-in profitability. Think of that as kind of an economic all-in P&L. You can see we make a lot of money in the early years and you're absolutely right, the person that asked the question, in the later years that red line is below 0. So we are losing money on that block of business in that example.

Now again, this is not a real life example. It didn't happen. In fact, we didn't have Principal First back in 1995. But in this example, the business would have made a ton of excess profits in the early years with hedging. It would have made -- we would have been in a loss position in some of the later years.

As you may recall, the IRR on the book was about 15% (ph), was above 15% even without hedging. It was even more above 15%, I think Dan mentioned in the 20% with hedging. But it would show that that particular piece of business was at a loss.

Now, it's important to note, though, that even in this scenario we have the rest of the book of business that we're writing new products. And, as you saw with that graph, we have a lot of variable annuity business that doesn't have Principal First. This was just one stress test scenario that we showed. So hopefully that helps clear up some confusion about that.

But with that, I'd like to bring the team up for Q&A and take a moment for everyone to get up. Okay, this is a reminder for the Q&A. I just wanted to remind people that we are -- we do have people on the call, so in order for everyone to hear the questions, if you could -- first of all, we have microphones and I would ask if you could wait till the microphone gets to you and if you could state your name and the company that you're with so that everyone on the webcast is able to hear you.

Okay?

Thank you.

Vanessa Wilson: Vanessa Wilson with Deutsche Bank. On the famous slide with the red line, Liz, how would that have been affected if the market volatility were in a perverse period, say a long term capital scenario over a longer period of time. I'm assuming that this scenario was done assuming the options market was in place, as it was in each of these periods. What if the options market was worse?

Lizabeth Zlatkus: Actually we did. As you remember, when we went out on the curve, also since those years haven't occurred yet, we did do some stress testing on that. But I want to turn it over to Craig to give a little bit more color on that particular example.

Unidentified Company Representative: Thanks, Vanessa. It's really going to be very sensitive to when that happens and in that scenario, you did see that in the early -- you did see that volatility in the late '90s when you did see the disconnect in the market. Even with that, it was a fairly short period of time that...

Vanessa Wilson: ...section two?

Unidentified Company Representative: Well, actually the long-term capital would have been in section one in the late '90s. And that's where you see the blue spikes there at the end of section one because it was a fairly short period of time where we really had the high volatility spikes. If volatility would have stayed high for a longer period of time you would have seen -- actually, once the spike happens and you hedge that, you don't see as -- you don't see the volatility because if volatility's high -- in the results because volatility is high. You see the volatility results as volatility changes.

So if volatility jumped up and stayed up, there would have been more cost to hedging because hedging would have been more expensive in that scenario. But you wouldn't -- just being high doesn't cause the numbers to be as jumpy.

Vanessa Wilson: And then could you just talk through utilization assumption if utilization changed dramatically?

Unidentified Company Representative: As Dan discussed, we have -- we use dynamic, very dynamic assumptions as far as our utilization. So we assume that the more that the benefits get in the money, the more likely it is that the policyholders will utilize the benefit. Less out of the money, less likely they will.

So what you see in this example is as the market's running up, we don't get a lot of utilization of the benefit. As the market dropped and the -- after 2000, the utilization moved up very quickly in this scenario because this really stresses our policyholder behavior, so it's one of the reasons why we like to use this stress example.

So what you'll see in here, what you see in this example is by the time you get out to 2004 or so, we've got just about everybody taking full benefit of the full withdrawals here. So this is - - and correct me if I'm wrong, Dan, but I'm not sure we could stress this any further. That's one of the reasons why we consider this for stress example. By the time you get out after the market's dropped 40, 50%, you've got just about everybody taking full withdrawals. So that's about as bad as it can get.

Unidentified Company Representative: And just to add to that, as Craig was mentioning, the reason that everyone's taking withdrawals in that scenario consistent with our dynamic behavior logic, we assumed everyone was omniscient. They knew the market was at the peak, they all elected the reset, so they were all at the money right at the market peak. When the market subsequently tanked, then that created a large moneyness ratio. That moneyness ratio really drove the behavior.

And, as Craig said, virtually all of them were taking withdrawals after a few years of being that deep in the money. So it was designed specifically not to be an expected here's what hedging would typically look, but rather here's an outlier but let's understand it so we can at least make sure we're comfortable with our results even in outlier.

Jeff Shuman: Jeff Shuman from KBW. I was wondering if we could move forward a couple slides to number 17 where you show the capital usage on a hedged basis for Principal First.

You illustrate the -- you show that 2.5 percentile, which is an interesting point, but it's not too deep in the tail. I'm guessing you're pretty steep out there. If you go out to like the 1 percentile, that capital usage of 130 million, does that incrementally change to 150 million or is it 500 million or how steep are you out there in the tail?

Lizabeth Zlatkus: We certainly have run the scenario. Can everybody hear me? We have run our scenarios out and again, remember that we've run a wide range of scenarios and we have looked at it with hedging and we're comfortable that we can manage the risk within our capital tolerances at the 1% level.

Jeff Shuman: You're not going to give us any idea of the sensitivity out there?

Lizabeth Zlatkus: No, we think that we're showing you -- I mean obviously it gets deeper, but the hedging really does continue to play a very strong role and it continues to work.

Jeff Shuman: I think the tails is what we're all sort of worried about.

Lizabeth Zlatkus: Yes, I agree with that, but again, I think it's a 1%. Clearly after hedging we're still within what's on the chart. So in terms of the scale, we feel very comfortable.

Unidentified Audience Member: I've got two questions. How do you protect against Dr. Evil (ph) or Dr. (inaudible) in the execution? I think the scenario testing assumes flawless execution. I assume Dave and Fred here (inaudible - audio quality) worried about this execution or floods in the area, the system not working (ph). That's question one.

Question two would be to Jim. If you quantified what C3 Phase II impact would be (inaudible - audio quality)?

Lizabeth Zlatkus: I'm going to turn that first question -- I'll answer I think the Dr. Evil secondly. But, Jim, you want to comment on C3 Phase II overall will be positive for The Hartford. But we've been looking and pricing our products underneath -- I mean assuming C3 Phase II for some time (inaudible) have Jim add a little color.

Jim Trimble: Actually, I think Liz has just answered the question. It is overall a positive for us. And except when you get into the really, really bad tails where the negative scenarios and again, the formulas aren't going to work for you, so in a real steep drop, C3 Phase II is going to require more reserves. But overall and certainly where the market is today and where you'd expect it to go, C3 Phase II will be a positive for us. And, as I've said, we've reflected that in our pricing and in our capital management decision.

Lizabeth Zlatkus: Bob, I wasn't sure I understood. You're talking about capital market scenarios that are tail or are you talking about a control weakness in our hedging program?

Unidentified Audience Member: Well, I have to say if someone falls asleep and doesn't execute properly in a very volatile market, I mean there are human beings executing these hedges and human beings can make mistakes. So how do you scenario test the execution risk into the scenario?

Lizabeth Zlatkus: I'm going to take part of that and then I'll turn it over to Craig, and certainly if David wants to make any comments. First of all, remember, I think I stressed a lot this morning, but this is -- we brought up the people that are in charge of a lot of the components of hedging.

We're very excited to have them on our team, but they are backed up both with people underneath them and people above them. This is monitored and the distribution of the data is fairly wide every day. So it's not David Braun can't take a vacation. So certainly we have - - and in fact, he's required to.

So we have people that both from a control environment, we treat this very seriously, just as we have controls under Sarbanes-Oxley, that we're looking at our control environment, our tolerances, what gets reviewed on a daily basis, what gets reviewed on a weekly or monthly basis, to be able to see if -- we see slippage really on a daily basis. So it's a fairly large team that's involved and we do have controls built in.

We are working even with our Board of Directors in terms of what kind of metrics they need to see. So we feel fairly comfortable -- or very comfortable, I should say, that we have the controls in place.

Craig, I don't know if you want to add any color to that.

Unidentified Company Representative: Sure, a couple of comments. As far as controls are concerned, you all heard at lunch yesterday that David likes controls and I work for David, so I like controls. We have -- one thing we have done from the beginning in building this process is built a range of controls into the process.

As you see, there's -- we've got individuals from both Hartford Life's corporate staff as well as the ITD staff as well as our Inco staff and our Hartford Financial corporate staff involved in the process on a daily basis. There is detailed reporting.

I get reports every morning on the hedge position that I look at and those are distributed to a wider group. We monitor this very closely. When anything unusual happens we're getting together on the phone and making sure we discuss it. We have very tight control on the process under which -- under circumstances under which decisions can be made and under which we have to bring in more senior people to be involved in the process. I end up being involved in the process at least on a weekly basis and in times of stress, it could be on a daily basis. It's not dependent on any one individual.

There is backup, there is control, there's tightness. And we actually do realize scenario testing of running through what will -- what would happen if we had this kind of discontinuity, what would happen if something unusual happened, how would we handle that.

As a matter of fact, these guys have been spending a lot of time trying to build that into their scenario testing models to actually see what kind of additional deviations we get under some real life issues happening and how we would recover from that.

So we feel that we put a lot of effort into that and I've got a lot of confidence in not just the people doing this, but the controls we've built around it to make sure that we're not just dependent on one individual doing what they're supposed to do.

Jason Booker: Thanks. Jason Booker (ph) at (inaudible). I had two questions. The first is, yesterday John talked a lot about the arms race with respect to bells and whistles, all the different product features that are being offered in the marketplace today, and I was hoping that the panel could answer for us what un-hedged product features do you think would be most impacted by an adverse dislocation in the capital markets?

Lizabeth Zlatkus: Could you repeat the question again? What -- just say the last part of it.

Jason Booker: What product features scare you guys that competitors are offering? So we're analysts and investors and we want to know where the next problem might be. And I'm assuming that you guys have done all the work on all the product features to know what you guys feel is safe and what you want to offer. So what are the ones that scare you guys that are in the marketplace?

Lizabeth Zlatkus: Again, we're not going to comment on any particular product, but we will say that the reset feature, more frequent resets clearly are costly in terms of hedging and also the optionality of the policyholders, when do they reset. The higher withdrawal rate -- the higher the withdrawal rate, the more costly it is to hedge. I don't know, Dan, if you have any other comments. But clearly, resets and more frequent as well as higher withdrawals are costly.

Daniel Guilbert: I would just extend Liz's comments. The scenario that I showed, the famous 1995 scenario that's been up a couple of times at this point, I think if you had a more frequent reset, it's possible that's not as much of a tail scenario because now what you're dealing with is any given year when the market's doing well, you have people stepping up.

So for us, we have to time it just right to hit that five-year bull market, have everyone step up at the same time, call the call center at the same time, and utilize their benefit. If you have more frequent resets, you have a couple years of a bull market, and you can certainly see results that would be pretty impactful. So I would just echo Liz's comments. That's probably the one that would scare me a bit.

Jason Booker: And then the other question was just on the cost of the grid computing. Can you talk about it in the sense that is this something that you're -- the other top 10 variable annuity players can easily implement at a relatively low cost or is this something that you guys feel like can be a big barrier to entry for others to try to put together?

Lizabeth Zlatkus: We do think it's clearly going to be a barrier to entry, but I'll have Vic Severino give you a little bit more color since he's been in charge of employing it.

Vic Severino: It's actually really not the cost of grid computing that is the issue. Actually, our grid software is not the problem; it's really the expertise to use it. We have people on our staff that have actually many years of experience using grid computing. Getting access to those people, knowing where they are, is really the barrier to entry.

Unidentified Company Representative: Vic, if I could add to that. The other key to this is not just the technology side, but the software side. The biggest challenge to us has been to structure the software so that it can fully take advantage of the grid computing.

The technology platform itself is not, as Vic said, the access to that, but it's using that expertise to help rework the software for us so that we can really take advantage of the speed of the grid. That's really the challenge. And that is a bit of a barrier because it takes an immense amount of expertise and it's taken us a significant amount of investment to get our system structured in a way that we can take advantage of the grid.

Steven Gavios: Steven Gavios (ph) from Genus Associates (ph). Two related questions. Daniel, if I heard your comment properly, under that famous '95 stress test your IRR un- hedged of 15 and your IRR hedged was well north of 20. Can you just conceptually help me understand how that occurred?

I would have thought there'd be (inaudible) to hedging. And second, relatedly, if that's the case, if this thing works so well, then why has Hartford decided to move it's (inaudible) towards the Principal First Preferred, which obviously offers less benefits, less cost?

Lizabeth Zlatkus: I'll give some color and then turn it over to Dan. First of all, I'll leave it to Dan to give you all the details on the IRR, but remember in the early years we really made it kind of excess IRR because of the bull market. So you're getting more fees on variable annuities because the account values are higher.

So the present value of that early higher return you're discounting, and that's worth more than kind of discounting back 20 years later where you're getting some negative return. So from a present value perspective on an IRR basis, you can see how that works.

Conversely, so why do we hedge? I mean a lot of things, there's the statutory volatility, the fact that that was one scenario. Clearly, we thought it was the stress test scenario because it really goes to 10 billion in one day, everybody resetting, works through long-term capital dislocation and a variety of implied loss.

But you could have a scenario where you sell a lot of business over a year period and the market starts falling right away. So again, your present value of your fees off your variable annuity contact is lower.

Dan, do you want to give any additional color in terms of when you ran your IRRs?

Daniel Guilbert: Sure. I think Liz's point on the timing is a good one. It really depends on the particular market path in terms of how it's going to impact your long-term profitability. In this particular example, as we've discussed, the market did great for five years.

So in either case -- or actually in those first five years, until long-term capital blew up, implied volatility is pretty low.

Interest rates are higher than they are right now, so that makes hedging less expensive. And what happened was when long term capital blew up and the market tanked after 2000, after (inaudible) reset at the same point, the hedging program threw off a lot of gains because we were having large increases in liability.

So the large gains, which is doing exactly what it's supposed to do, elevates the overall possibility. So for this one specific scenario, the IRR post-hedging was better. We could run other scenarios where the market went up and just stayed going up and we never paid liabilities or never had claims and the hedging would be a net cost. That's okay because in that scenario we didn't need the hedging to fund those claims.

So it really just depends on the specific market path. In this case it provided gains when it needed to, which is great.

Ken Crawford: Ken Crawford (ph), Citigroup Asset Management. Three questions, please.

Steven Gavios: (inaudible - microphone inaccessible)

Lizabeth Zlatkus: I'm sorry; second question, if you could repeat it again?

Steven Gavios: I'm sorry; if I could follow up. If you aggregate all your scenarios, what's the IRR of hedging versus non-hedging?

Lizabeth Zlatkus: If we aggregate. We run a lot of scenarios. It's overall we think hedging is going to cost us money because when we look at all of our scenarios, and David Braun alluded to, you've got the cost of transaction cost (inaudible), et cetera, so we think net net over a fairly wide range of scenarios, our hedging costs will cost us money in addition to those 16 to 17 basis points for ascribed fees. But, as we know, we have 50 basis points coming in, so it gives us a lot of room to cover our hedging costs over a very wide range of scenarios.

Steven Gavios: Can you give us an order of magnitude, please?

Lizabeth Zlatkus: Again, I'll turn it over to Craig for some color, but under a very wide range we would see our costs of hedging in the 10 to 30 basis point range. That really covers quite a wide range of thousands of scenarios that we've been running, thousands and thousands, I should say. And the 10 to 30 basis points, remember, everything we're doing is in relation to the 50, so that's pre-tax, pre-DAC.

Steven Gavios: I'm sorry, was that 10 to 30 above the 16 or does that include that?

Lizabeth Zlatkus: That would be above the 16, but that's -- the 30 is a pretty high number. That covers quite a stress test scenario. Craig, do you want to add anything to that? It pretty much says you try to make the range wide because there's a lot of market scenarios that we're running as well as a lot of policyholder behavior assumptions that we're using.

Unidentified Company Representative: I think I'd just reiterate that overall there is a slight -- when we look at it over a wide range, we expect that there is some cost to the hedging. We're still comfortable with the pricing at the level we're charging for this benefit with the hedging.

We get a much tighter range of results after we hedge than without hedging. Without hedging, as you saw the volatility -- when we look at the capital costs of the volatility of the statutory results, there's a much wider range of the internal rates of return without the hedging versus when we add the hedging in. And we kind of tighten those results up, the average would be a little bit less but still above our normal pricing expectations. We're much more comfortable with that result.

Steven Gavios: So if you've been so successful in instituting this hedging program, why have you opted to move your marketing emphasis towards this Preferred product?

Lizabeth Zlatkus: First of all, we talked about yesterday that we think that looking at product management is a very effective tool to risk management. So we're looking at a variety of things at any point in time.

Number one, we look at how much of each risk we like to take. That's why we use those product features as well as reinsurance and hedging as an overall comprehensive way to manage our risk.

So first of all, with Principal First Preferred, we do think it's a very good value to the consumer. If you remember that pyramid, consumer value is very important. It's only 20 basis points. It does still give people return of principal.

We think people have been in the market now for a while and we think it's a really good feature, a very good product. So we like both the consumer value aspect of it as well as the risk. We're a very large company. We're selling a lot of business. It helps diversify our risk portfolio.

We do think that our hedging program is very effective, but as some of you guys keep asking us questions about the tails, we recognize that we're running so many scenarios; we're looking at a lot of events. But one reason that you hedge is to be able to make sure that you're mitigating your risk and hedges aren't perfect.

So all of the scenarios that we've given you, we feel very comfortable with our hedge program and the business that we have on the books today. But we do think Principal First helps give us more flexibility in the future by providing a less risky product. And again, providing very good consumer value.

Eric Burke: Thanks, Liz. Eric Burke (ph) from Lehman Brothers.

Lizabeth Zlatkus: And then we're going -- sorry, you're right. I passed over. Sorry about that. Go ahead, Eric, and then I'll make sure you go next.

Eric Burke: First, I was hoping we could return to Vanessa's question and I was hoping I could -- you could help me sort of sharpen my understanding of what happens to earnings in a crisis, to GAAP earnings in a crisis when the cost of buying the options explodes? If I understood you correctly, you're saying that the impact would be stable but dramatic. There would be a significant hit to earnings, but it would be a stable impact. Is that what you're saying would happen in an environment where the price of buying OTC options exploded? Is that -- that's my first question. I'm trying to understand sort of what would happen on the margin to earnings and then subsequent.

Lizabeth Zlatkus: In terms of the cost of the (inaudible) spread is something that kind of occurs every day. So as costs of options go up, that's where we're looking at a very holistic way to do our hedging program.

So, as David Braun alluded to, we are not trying to buy and sell too much. If the cost -- if there's a supply demand inequality at the moment, we -- and again, within tolerances and controls and working with David Johnson and Dave Zimeralski (ph) and a group of people, we may sit on the sidelines for a little bit to kind of avoid too much of a (inaudible) spread. But clearly, if cost of hedging or options go up, it's going to cost us more money and that will come through the gain and loss. David, do you have any -- David Braun, do you have any additional comments you'd like to make?

David Braun: Yes. I think if you're asking if (inaudible) a discreet jump, some sort of catalyst in the capital markets or politically (ph) caused vols (ph) to jump up, the portion of the vol that we have cover with the Vega, we're Vega neutral, would be hedged. Now where the hedge underperformance would start to emerge is the cross Greeks would kick in because you have a disparity between the asset Vega and liability Vega due to that jump.

And at that time you can either go cover it by buying options or you could alter your hedge strategy and focus more on something more liquid. It would really depend on what you think the catalyst that caused that abrupt change in vols could be. Is it temporary, is there panic in the market, stuff like that.

And I do want to reiterate some of the proprietary strategies we're using in our hedge are designed to exactly combat that problem so that we're now forced to mechanically follow a trading algorithm into turbulent markets where we're buying, even though the markets are completely dislocated and irrational. So we're doing everything we can to do a preemptive strike on that scenario.

Eric Burke: One follow-up, one second question and that is that in your accounting discussion, if I understand the example correctly, I think you have running through the P&L not the change in the value of the swap, but the value of the swap itself. I'm referencing slide 43.

Lizabeth Zlatkus: The change in the value of embedded derivative liability runs through gains and losses. It's offset by the change in the value of the hedge assets, which also runs through gains and losses. So the net gain and loss impact is really the difference between the change in the value of the assets minus the change in the value of the liability.

Obviously you saw in '04 where our hedge was very tight, it was very closely matched to GAAP change. So that's why we had very little gain/loss because it's the change in the value of that swap runs through gains and losses.

Unidentified Audience Member: Two questions, please, one again back to slide 15, just a detailed clarification really. As I understood from earlier comments, when you assume omniscience on the part of policyholders and everyone resets at the same level, as you move down towards 2004 nearly -- I believe one of the speakers said nearly everyone exercises. So apparently there's still some sort of irrational (inaudible), assumption involved even with a down market. How much -- what portion of the policyholder population does not book policies (ph)?

Lizabeth Zlatkus: Dan, do you remember when we ran that '95 scenario?

Daniel Guilbert: Exactly how many people weren't taking withdrawals? Well, I'd start off the answer with before 2004 we already had people starting to take withdrawals. Right from the beginning of the model we see them start -- people start taking withdrawals right from the get go and that only accelerates our dynamic (inaudible) withdrawals are one-directional. If the market goes down, they start taking more withdrawals. But we already have a steady base of people who are taking withdrawals right from the get go. I actually don't know the number off the top of my head, but I think the words "vast majority" capture it.

Unidentified Audience Member: ...supposed to be a stress test of a tail event. I mean that's how you all are presenting it. So it does matter whether it's 95% of policyholders or 99% of policyholders.

Daniel Guilbert: I'm not sure the results would be materially different if we had 95 or 99% of people taking withdrawals at that point given the characteristics and depending on what their fund mix was. But those numbers sound like they're in the right ballpark.

Unidentified Audience Member: And would it be correct to assume that a more punitive scenario and even (inaudible) tail scenario would be one which tended to bunch policyholder withdrawal towards the backend of the period of time as opposed to having it as a continuous variable operating throughout the period?

Daniel Guilbert: So assume that no one took any withdrawals for five years and then everyone took withdrawals at the same time?

Unidentified Audience Member: Correct.

Daniel Guilbert: I think that could probably be a little worse. So perhaps this isn't the very end of the continuum of conservatism, but I think it certainly gives us something deep in the tail.

Lizabeth Zlatkus: I think it's important to note that remember, I just want to clarify this is one scenario that we tested. I just want to make sure we're not putting too much emphasis on this one scenario. It was a good example of what we call bull markets hitting the high, everybody resetting, markets falling, long term capital and it was helpful because it really happened in terms of the market scenario, although obviously the policyholder behavior didn't happen because we didn't have Principal First back then. When we run all of our other graphs, our statutory graphs, our claims cost graphs, those run a variety, 250, 500 scenarios.

And then, of course, that's over a very long period of time, 20 years, so you're running in thousands and thousands of scenarios. In those we dynamically stress policyholder behavior to be all of a sudden people start to take withdrawals. So when we say (inaudible) scenarios, again this was just one example (inaudible).

We also have found that it has been true in our policyholder book over the years that when - - people do not always optimize their options. I mean they're really looking to utilize this benefit for long-term retirement.

And I think that's key because this benefit is not -- while people can take withdrawals, we see today that many of them are not. So they're looking to really use this as what I call security and not using it to take advantage of all of the optionality in the product. They're buying an annuity, they want to save for their retirement, they want to have a safety net there. I'm not at all suggesting that some policyholders aren't -- and today are withdrawing the maximum amount, but overall, our overall withdrawal rate today is low.

And we do -- have seen over the years, and that's our expertise in the variable annuity business, that people generally use our products for the long-term nature of them. And we do stress test those environments and we do stress test policyholder behavior onto those other graphs.

Unidentified Audience Member: I'm sorry; the other question that I did want to put was to David Braun on trading costs. Eric had asked about volatility, what might happen in the situation where volatility exploded. I'm wondering a little bit more about your actual trading (inaudible) over your period of experience, I guess about three years, something like that. What's that -- if you turn that into a frequency distribution, how much flatter than the normal curve is that? What does that look like in terms of the high/low? What's the price of liquidity in your strategy, the actual price of liquidity?

David Braun: I'm not quite sure I get the question.

Unidentified Audience Member: Well, many of your available securities in the portfolio of available securities are highly negotiated...

David Braun: Yes.

Unidentified Audience Member: ...subject to changing liquidity in markets. So just in terms of your actual costs over the last couple of years...

David Braun: Okay, I get it.

Unidentified Audience Member: ...what's the high/low, what does the distribution look like?

David Braun: Yes. We've been fortunate in the nearly two years we've been hedging this. The exchange (inaudible) very liquid, very tight transaction costs. The over the counter stuff is what is more variability and for the most part over the past two years while we've been hedging this, that market, there have not been any supply/demand imbalances and there's been a lot of liquidity there. When there's liquidity, the transaction costs are compressed. It's really when there's no liquidity or supply/demand imbalance, transaction costs gap out, as Liz was talking about.

So we've been very fortunate and actually a lot of the proprietary strategies we had used really helped us get through the one or two periods over the past two years where there was a supply/demand imbalance.

If you look at volatility charts, you can see some periods over the past two years vols did jump, meaning supply and demand were out of whack, thus transaction costs gapped out. We actually, because of our strategies, were able to sit through that and wait for the market to calm down.

So I'd say we've been incredibly pleased with the amount of transaction costs we've incurred doing business here. I don't even think it comes close to a basis point on assets for the 17 or 18 billion that we're hedging.

Lizabeth Zlatkus: I think we have time for maybe one other question.

Unidentified Audience Member: Two parts; first is the example you gave after you started '95 and you get five years of accumulating value and that's why you've still got a good IRR, it seems to me the real question is, if you wrote that 10 billion in March of 2000 and (inaudible) fall apart in the stress event, what's the IRR under that scenario over the length of the block?

Second question is, in this stress event when you're rebalancing, are you rebalancing to anticipated change in withdrawal behavior or actual? And the reason I ask the question is if it's anticipated and you anticipate wrong, let's say you anticipate a large amount of withdrawals that don't come through, you may have over-hedged and take a loss, but actually you have to wait to see the actual behavior and you might be too late, in which case you can't get the right hedge on or it's too costly.

Lizabeth Zlatkus: Okay, first of all, in terms of policyholder behavior changes, we do anticipate policyholder behavior changes. But to the extent that policyholder behavior changes differently than we expect, and that does run through the gain/loss because you can't hedge something that you didn't anticipate, so to the extent that again policyholder behavior immediately tomorrow everybody starts withdrawing for some unknown reason, then we're going to have a gain/loss through the example. And clearly, the IRR would be below 15% and a scenario where we showed a lot of business markets drop, lots of people withdrew.

I think what's important to note is that the 50 basis points that we charge covers what we consider a very wide range of scenarios. We have diversification because of the time we're putting on the books. We have diversification because we have a very significant inforce variable annuity book that doesn't have Principal First. We are looking once again to diversify it to lower risk product with the Principal First Preferred. But clearly, if you have a high market, you're selling a lot of business and the market drops, you don't have the reset provision because you're not resetting at a high, but you do have and you assume higher withdrawals.

Those are some of the scenarios that are captured when we talk about a wide range. We capture those kind of starting at a high market dropping. Remember, there's lots of other things that David Braun mentioned that cause cost, the implied volatility, which isn't something that you may think about every day. People tend to watch market levels for their own portfolio of stocks. Not all of us are looking at implied vols every day. But implied vols, cross Greek, all those things we're incorporating on a very comprehensive basis when we look at our tail scenarios and we feel comfortable that our hedging is going to work. Again, no program is -- no hedging program is perfect and that's why we show some of the scenarios where the tails get fatter.

We want to recognize we're going to see more noise going forward and the GAAP income line with three to four basis points of hedging costs in '04 is not something that we think is realistic to assume going forward.

But we feel very comfortable and hopefully we were very educating today. I want to turn it over to Kim Johnson for just some closing statements. Thank you.

Kimberly Johnson: Thanks, Liz. And thanks for joining us today. I hope you'll join me in thanking our speakers for a very (inaudible). I would ask, I know that this is a very complex topic and I'm certainly not the expert in the topic, but I would ask if you would to send or direct your questions through me or through Greg if there's any follow-ups out of today's session.

So thank you very much.