Warnings About Financial Institutions and Derivatives

Risks of Financial Institutions
The nature of a financial institution is that there are a lot of ways to go to hell in a bucket. You can push credit too far, do a dumb acquisition, leverage yourself excessively---its not just derivatives [that can bring about your downfall].

Maybe it's unique to us, but we're quite sensitive to financial risks. Financial institutions make us nervous when they're trying to do well.

We're exceptionally goosey of leveraged financial institutions. If they start talking about how good their risk management is, it makes us nervous.

We fret way earlier than other people. We've left a lot of money on the table through early fretting. It's the way we are -- you'll just have to live with it.

Derivatives
The system is almost insanely irresponsible. and what people think are fixes aren't realy fixes. It's so complicated I can't do it justice here - but you can't believe the trillions of dollars involved. You can't believe the complexity. You can't believe how difficult it is to do the accounting. You can't believe how big the incentives are to have wishful thinking about values and wishful thinking about ability to clear.

People don't think about the consequences of the consequences. People start by trying to hedge against interest rate changes, which is very difficult and complicated. Then, the hedges make the [reported profits] lumpy. So they use the new derivatives to smooth this. Well, now you've morphed into lying. This turns into a Mad Hatter's Tea Party. This happens to vast, sophisticated corporations.

Somebody has to step in and say, "We're not going to do it - it's just too hard."

I think a good litmus test of the mental and moral quality at any large institutions [with significant derivative exposure] would be to ask them, "Do you really understand your derivatives book?" Anyone who says yes is either crazy or lying.

It's easy to see [the dangers] when you talk about [what happened with] the energy derivatives - they went kerflooey. When [the companies] reached for the assets that were on their books, the money wasn't there. When it comes to financial assets, we haven't had any such denouement and the accountings hasn't changed so the denouement is ahead of us.

Derivatives are full of clauses that say if one party's credit gets downgraded then it has to put up collateral. It's like margin - you can go broke [just putting up more margin]. In an attempt to protect themselves, they've introduced instability. Nobody seems to recognize what a disaster of a system they've created. It's a demented system. 

In engineering people have a big margin of safety. But in the financial world, people don't give a damn about safety. They let it balloon and balloon and balloon. It's aided by false accounting. I'm more pessimistic about this than Warren is.

Accounting for Derivatives
I hate with a passion GAAP [Generally Accepted Accounting Principles] as applied to derivatives and swaps. JP Morgan sold out to this type of accounting to front-end revenues. I think it's a disgrace.

It's bonkers, and the accountants sold out. Everyone caved, adopted loose [accounting] standards, and created exotic derivatives linked to theoretical models. As a result, all kinds of earnings, blessed by accountants, are not really being earned. When you reach for the money, it melts away. It was never there.

It [accounting for derivatives] is just disgusting. It is a sewer, and if I'm right, there will be hell to pay in due course. All of you will have to prepare to deal with a blowup of derivative books.

Likelihood of a Derivatives Blowup
We tried to sell Gen Re's derivatives operations and couldn't, so we started liquidating it. We had to take big markdowns. I would confidently predict that most of the derivatives books of [this country's] major banks cannot be liquidated for anything like what they're carried on the books at. When the denouement will happen and how severe it will be, I don't know. But I fear the consequences could be fearsome. I think there are major problems, worse than in the energy field, and look at the destruction there.

I'll be amazed if we don't have some kind of significant [derivatives-related] blowup in the next five to ten years.

I think we're he only big corporation in America to be running off its derivative book.

It's a crazy idea for people who are already rich -  like Berkshire - to be in this business. It's a crazy business for big banks to be in.

Yo would be disgusted if you had a fair mind and spent a month really delving into a big derivative operation. You would think it was Lewis Carroll. You would think it was the Mad Hatter's Tea Party. And the false precision of these people is just unbelievable. They make the worst economics professors look like gods. Moreover, there is depravity augmenting the folly. Read the book F.I.A.S.C.O., by law professor and former derivative trader Frank Partnoy, an insider account of the depravity of derivative trading at one of the biggest and best-regarded Wall Street firms. This book will turn your stomach.

Well here’s a story where the tradeoff for speed and efficiency caused a massive stock dump erroneously.

Apparently, many traders use automation software that trolls the Web for news stories and then, depending on what it finds, executes stock trades automatically. It was United Airline’s bad luck that an old article about its 2002 bankruptcy-court filing showed up on Google’s news service and somehow made it to the list of most popular stories. In one of a series of mistakes here, the story had no date on it – which means Google’s algorithm for assessing popularity didn’t have a way to exclude it as an “old” story – OR (because there are conflicting accounts) the South Florida Sun-Sentinel actually put “today’s” date on the page that the story appeared on. This got picked up by the Income Security Advisors newsletter and sent over to Bloomberg News as a one-line brief. Plus there’s the inevitable conspiracy theory that people manipulated the web traffic for this story to adversely affect UAL. Regardless, on Monday afternoon, the stock plunged 76% in less than a day.

But the real problem here is the growing use of automated programs to trigger stock trades without any human interaction – instead based on news headlines and earnings data. According to the Wall Street Journal, these automated programs were responsible for a very surprising 25% of NYSE trades in the last week of August.

I’m sure we’ll hear more as the lawyers are now involved trying to figure out who should get the blame.

It's become a big deal in IT security, too. Many corporate customers are demanding ROI models to demonstrate that a particular security investment pays off. And in response, vendors are providing ROI models that demonstrate how their particular security solution provides the best return on investment.

It's a good idea in theory, but it's mostly bunk in practice.

Before I get into the details, there's one point I have to make. "ROI" as used in a security context is inaccurate. Security is not an investment that provides a return, like a new factory or a financial instrument. It's an expense that, hopefully, pays for itself in cost savings. Security is about loss prevention, not about earnings. The term just doesn't make sense in this context.

But as anyone who has lived through a company's vicious end-of-year budget-slashing exercises knows, when you're trying to make your numbers, cutting costs is the same as increasing revenues. So while security can't produce ROI, loss prevention most certainly affects a company's bottom line.

And a company should implement only security countermeasures that affect its bottom line positively. It shouldn't spend more on a security problem than the problem is worth. Conversely, it shouldn't ignore problems that are costing it money when there are cheaper mitigation alternatives. A smart company needs to approach security as it would any other business decision: costs versus benefits.

The classic methodology is called annualized loss expectancy (ALE), and it's straightforward. Calculate the cost of a security incident in both tangibles like time and money, and intangibles like reputation and competitive advantage. Multiply that by the chance the incident will occur in a year. That tells you how much you should spend to mitigate the risk. So, for example, if your store has a 10 percent chance of getting robbed and the cost of being robbed is $10,000, then you should spend $1,000 a year on security. Spend more than that, and you're wasting money. Spend less than that, and you're also wasting money.

Of course, that $1,000 has to reduce the chance of being robbed to zero in order to be cost-effective. If a security measure cuts the chance of robbery by 40 percent -- to 6 percent a year -- then you should spend no more than $400 on it. If another security measure reduces it by 80 percent, it's worth $800. And if two security measures both reduce the chance of being robbed by 50 percent and one costs $300 and the other $700, the first one is worth it and the second isn't.

The Data Imperative

The key to making this work is good data; the term of art is "actuarial tail." If you're doing an ALE analysis of a security camera at a convenience store, you need to know the crime rate in the store's neighborhood and maybe have some idea of how much cameras improve the odds of convincing criminals to rob another store instead. You need to know how much a robbery costs: in merchandise, in time and annoyance, in lost sales due to spooked patrons, in employee morale. You need to know how much not having the cameras costs in terms of employee morale; maybe you're having trouble hiring salespeople to work the night shift. With all that data, you can figure out if the cost of the camera is cheaper than the loss of revenue if you close the store at night -- assuming that the closed store won't get robbed as well. And then you can decide whether to install one.

Cybersecurity is considerably harder, because there just isn't enough good data. There aren't good crime rates for cyberspace, and we have a lot less data about how individual security countermeasures -- or specific configurations of countermeasures -- mitigate those risks. We don't even have data on incident costs.

One problem is that the threat moves too quickly. The characteristics of the things we're trying to prevent change so quickly that we can't accumulate data fast enough. By the time we get some data, there's a new threat model for which we don't have enough data. So we can't create ALE models.

But there's another problem, and it's that the math quickly falls apart when it comes to rare and expensive events. Imagine you calculate the cost -- reputational costs, loss of customers, etc. -- of having your company's name in the newspaper after an embarrassing cybersecurity event to be $20 million. Also assume that the odds are 1 in 10,000 of that happening in any one year. ALE says you should spend no more than $2,000 mitigating that risk.

So far, so good. But maybe your CFO thinks an incident would cost only $10 million. You can't argue, since we're just estimating. But he just cut your security budget in half. A vendor trying to sell you a product finds a Web analysis claiming that the odds of this happening are actually 1 in 1,000. Accept this new number, and suddenly a product costing 10 times as much is still a good investment.

It gets worse when you deal with even more rare and expensive events. Imagine you're in charge of terrorism mitigation at a chlorine plant. What's the cost to your company, in money and reputation, of a large and very deadly explosion? $100 million? $1 billion? $10 billion? And the odds: 1 in a hundred thousand, 1 in a million, 1 in 10 million? Depending on how you answer those two questions -- and any answer is really just a guess -- you can justify spending anywhere from $10 to $100,000 annually to mitigate that risk.

Or take another example: airport security. Assume that all the new airport security measures increase the waiting time at airports by -- and I'm making this up -- 30 minutes per passenger. There were 760 million passenger boardings in the United States in 2007. This means that the extra waiting time at airports has cost us a collective 43,000 years of extra waiting time. Assume a 70-year life expectancy, and the increased waiting time has "killed" 620 people per year -- 930 if you calculate the numbers based on 16 hours of awake time per day. So the question is: If we did away with increased airport security, would the result be more people dead from terrorism or fewer?

Caveat Emptor

This kind of thing is why most ROI models you get from security vendors are nonsense. Of course their model demonstrates that their product or service makes financial sense: They've jiggered the numbers so that they do.

This doesn't mean that ALE is useless, but it does mean you should 1) mistrust any analyses that come from people with an agenda and 2) use any results as a general guideline only. So when you get an ROI model from your vendor, take its framework and plug in your own numbers. Don't even show the vendor your improvements; it won't consider any changes that make its product or service less cost-effective to be an "improvement." And use those results as a general guide, along with risk management and compliance analyses, when you're deciding what security products and services to buy.

This essay previously appeared in CSO Magazine.

In their eyes, we were not earning money for the bank. Worse, we had the power to say no and therefore prevent business from being done. Traders saw us as obstructive and a hindrance to their ability to earn higher bonuses. They did not take kindly to this. Sometimes the relationship between the risk department and the business lines ended in arguments. . . .

Tactfully explaining why we said no was not our forte. Traders were often exasperated as much by how they were told as by what they were told.

At the root of it all, however, was—and still is—a deeply ingrained flaw in the decision-making process. In contrast to the law, where two sides make an equal-and-opposite argument that is fairly judged, in banks there is always a bias towards one side of the argument. The business line was more focused on getting a transaction approved than on identifying the risks in what it was proposing. The risk factors were a small part of the presentation and always “mitigated”. This made it hard to discourage transactions. If a risk manager said no, he was immediately on a collision course with the business line. The risk thinking therefore leaned towards giving the benefit of the doubt to the risk-takers.

Collective common sense suffered as a result. Often in meetings, our gut reactions as risk managers were negative. But it was difficult to come up with hard-and-fast arguments for why you should decline a transaction, especially when you were sitting opposite a team that had worked for weeks on a proposal, which you had received an hour before the meeting started. In the end, with pressure for earnings and a calm market environment, we reluctantly agreed to marginal transactions.

• Would You Know a Good decision if You Saw One?
• Decision Making Under Uncertainty

Continuing the rapid consolidation or maybe the swallowing of the DLP market McAfee while announcing flat earnings today also announced that they were acquiring Reconnex for 46 million in cash. That just about does it in the DLP market with most of the pots having found a cover.  Congrats to all of the folks at Reconnex!

Continuing the rapid consolidation or maybe the swallowing of the DLP market McAfee while announcing flat earnings today also announced that they were acquiring Reconnex for 46 million in cash. That just about does it in the DLP market with most of the pots having found a cover.  Congrats to all of the folks at Reconnex!

So I got my iPhone 3G on Friday morning and have been using it for a few days now. I have never used one before, don't use an iPod or even a Mac computer.  The iPhone was incredibily easy to use and without using and manuals quickly had a most everything working and downloaded a bunch of apps from the app store. 

Over all, the iPhone just is really nice to use and in many ways very easy, polished and intuitive. In other ways, it is still missing some key features in my book:

1. Sort and filter email be date, sender, etc.
2. Select more than one mail at a time to delete, move, copy.  Yes I know you can go to edit and select messages to work on, but you still have to select them one at a time. In Windows Mobile you can just run your finger over multiple messages to complete this.
3. Deleting duplicate contacts in bulk.  Doing them one at a time is just painful
4. A task manager. I would like to see some list that shows me which apps are running, how many resources they are using, battery usage and stuff like that.  Also to shut down running apps
5. Better calendar integration. I tried to click on and open calendar items, but just does not seem to work.
6. The battery sucks! I am not getting more than about 6 to 7 hours of battery time. I think I have to turn off the push for my Exchange email.  This is much less that I was getting on my Windows Mobile phone.

I do like the phone, the iPod MP3 and camera and the overall "feel" of the phone. Went to the Apple store in the maill (which was jam packed) and bought a rubberized case, but was unable to get a phone car charger for it yet.  I ordered one for 5 bucks on Amazon and will see it if works.

All in all, things are OK but I am going to withhold my final verdict for a while yet.