New Logo

The CAS has apparently had a new logo created for the organization:

Here's an article about the re-branding: http://www.casact.org/press/index.cfm?fa=viewArticle&articleID=2254


I'm generally not a fan of re-branding efforts, and so far this is no exception. I don't think the new logo is even intelligible to someone who doesn't already expect to see the letters "C.A.S." Why a vague yellow dot instead of a clear white line? Are we planning on joining the NCAA and need to have a third color for our team jerseys? Is it some sort of "Web 2.0" attempt to evoke the ubiquitous "dot-com" concept?

We also have a new tagline, "100 Years of Expertise, Insight & Solutions," which utterly fails to illuminate anything regarding the purpose of our organization as it makes no reference to risk, analysis, applied mathematics, or anything else remotely actuarial (although I do appreciate the ageist jab at the SOA.) It's also sure to infuriate fans of the Oxford comma. Is this a subtle statement by the CAS that we are committed to remaining a U.S.-focused organization? That we've had it with waiting around for Solvency II to sort itself out and are retreating within our own borders? I wonder how Canada feels about this.

All in all, it seems like a brand strategy designed to appeal to members of the organization rather than its customers, which doesn't surprise me since the SOA "general insurance" track no longer guarantees us the custom of every aspiring PC actuary. This is an advertisement directed at the profession rather than the industry in which our profession operates. It's bound to be short-lived, however, since the "100 years" figure will soon be out of date, so perhaps this is intended to be a temporary strategy.

I'm curious how others are reacting to the logo. Are we happy to have something a little more modern and colorful? Is the new tagline seen as effective? To be honest, I can't remember our old tagline, so perhaps that's an automatic improvement.

Speak Your Mind

Given the chatter I've seen regarding the most recent CAS exam sitting, candidates are brimming with feedback, particularly regarding Exams 5 and 7. Consequently, this is a good time to remind you all that the most important part of my job on the Candidate Liaison Committee is not to write humor articles: it's to represent you!

If you want your voice heard, here are the three most important things you can do:

1. Fill out the exam survey - For two years now, I've been true to my promise to read every single word written by candidates in the exam survey forms. Keep filling out those surveys, and I'll keep reading them (and making sure the exam commit reads them, too!)

2. Talk to CAS members - Probably the biggest source of feedback to the CAS leadership is through the grapevine: things they hear or overhear when listening to analysts chatter at the office, remarks made by colleagues, or other water-cooler talk. Don't be afraid to let your boss (or any CAS member you happen to be connected with) know what you think about the process of becoming credentialed.

3. Talk to Join the CLC - The upcoming issue of Future Fellows includes information on the Candidate Representative positions available on the Candidate Liaison Committee. I highly recommend joining. The CLC is hands-down the best option available for candidates to better understand and influence the admissions process.

As always, I'm all ears if you have any questions or comments, or if you simply need to vent. Meanwhile, I hope all the candidates out there enjoy the respite before beginning their studies for the next sitting. Oh yes, and it's time for the interminable wait for exam results. Here's hoping for good news.

ERM Symposium Day 3: General Session V

Last day, last General Session, last session...

General Session V: "Interconnectedness and Contagion in Global Markets: Missed Opportunity"

Panelists: Kimo (sp?), Jim Allison of ConocoPhillips, Allan Mendelowitz of the Federal Housing Finance Board, Adam Litke of Bloomberg, Stuart Wason of OSFI Canada, + one more (PC Guy)

Kimo: The literal interconnectedness of assets, now that the topology is actually known by regulators, isn't significant to explain the amount of contagion seen during the financial crisis. [KR: They've literally mapped this over time, which is pretty cool.]

Jim: Path-dependence relates to contagion. Some exogenous cause is not contagion. Contagion is how an exogenous cause affects entities 1-(i-1) and then that affects entity i.

Allan: Remember that all of this is happening in a fractional-reserve system. Institutions are brought down by liquidity and collateral shortages. One aspect of contagion is Jim's type. The other type is related to the lack of information, where everyone tends to assume the worst, which leads to fire sales. So the perception of a problem is as important as actual problems.

Adam: Over an even longer timeframe, the connections become even more unlikely and unexpected.

Stuart: Insurance doesn't do as much work on interdependencies, but it's applicable to us as well. Contagion risk is less of an issue, although there are examples.

Some PC guy: Insurers look at classes of business. Premiums rise and fall with the general economy, so there's a big connection there. Characterizes asbestos and Sandy as contagions. Asset side is simple though. Simple, carefully managed, liquid, and low-yield.

What about regulatory contagion? Financial crisis resulted in regulations on energy sector.

Jim: I don't like saying that something could not be foreseen. True we didn't, but could we have? In this case, we were indirectly connected to the banks. Banks -> derivatives, derivatives = highly risky, high risk -> regulation. That was the logic of pulling the energy sector into the regulatory response. I wouldn't call it contagion since it hasn't killed us yet.

Central clearing is applied as a way to reduce interconnectedness. Does that create too much systemic risk? Is there a central point of failure?

Jim: Yes, they've been identified as such, but the rationalization is that they are well capitalized and therefore safe. We've heard this argument before. All the eggs are in one basket, so that basket needs to be watched very carefully.

Allan: Contagion is about reducing counterparty risk, not systemic risk. Clearing houses address counterparty risk. I don't see how they improve systematic risk. We're just trading one set of risk for another.

Adam: Clearing houses do provide other benefits, for instance it simplifies the process in a way that reduces operational risk. They also separate direction risk from counterparty risk.

Jim: Still we appreciate having the ability to use clearing houses, because at times we are concerned with removing counterparty risk. But in exchange you pick up liquidity risk. In my industry, we are accustomed to managing counterparty risk, but liquidity risk is something we're less comfortable with. Consequently there is a potential for systemic risk to increase.

 PC guy: Sandy illustrates interconnectedness of bank, insurance, and energy in that insurance losses are mitigated when the power can come on sooner. At one point, a regulator explained his view on rate increases, and while he said that he believes insurers are entitled to reasonable returns, he explicitly said "Do not send me a rate filing that includes a hurricane model, because we don't have hurricanes in this state." The very next week, the governor's mansion was hit by a hurricane. So, what are you going to do about that?

Jim: We discussed giving regulators "big data" to do "big science." What if instead we determined how much/what information on your counterparty is necessary to assess your risk re: that counterparty. I think it might make more sense for each entity to have access to the information (to remove/reduce the information asymmetry) and to each perform their own analysis. Could that reduce the threat to whole system? Could we convince entities to give up that kind of information?

Adam: Regulators can improve the information flow, but so can firms. TBTF is destined to fail because the largest economy will always have the largest firms.

Have business and regulators done enough to prepare for the next crisis?

PC Guy: We are always looking toward the next crisis, but what are we to do when we're regulated into certain assets and certain risks? We have limited ability to do anything to prepare.

Allan: I don't like the term TBTF. TBT-Prosecute, maybe. Better is Too Interconnected to Fail. Look at the car industry. In order to do something about this, the government needs to know what the interconnectedness looks like. During the financial crisis, the government people made all kinds of huge decisions with no data and no evidence. So we need information, we need data standards.

Stuart: Regulators could ask firms to demonstrate how they would manage thing if they were to get into difficulties.

Kimo: I think we're on a good path to understanding interconnectedness. Contagion needs a lot more work. The domino effect isn't known that well for central banks and others. We need formal models for this. For joint-ownership of assets, we don't know anything right now.

End Conference! Thanks for following.

Day 3 Lunch - Sheila Bair

Today's luncheon keynote was a vast improvement over yesterday's gross failure. The speaker was Sheila Bair, former FDIC Chairman. The welcome packet for the seminar included her book, Bull by the Horns. Her most interesting comments to me were:

1. The move in regulation toward using internal models to set capital limits (in banking and in insurance) is in her opinion a bad idea. It creates perverse incentives by penalizing firms with conservative models. Models are going to be biased low when regulators use them directly (and worse: unbiased models won't be produced at all.)

2. Regulators create more and more complexity, and the current path (Basel, etc.) is disastrous because of this. Incomprehensible regulations abound that no one can follow.

3. Valuing assets on a risk-adjusted basis for regulatory purposes has been a disaster. It creates perverse incentives to hold certain assets and report them in a certain way. As a solution, she proposes a return to a simple leverage ratio requirement temporarily until regulators have enough time to develop a better model for risk-valuation of assets.

Overall, it was an interesting talk. I look forward to reading her book.

End Lunch Keynote.

Concurrent Session 4F

"Optimal Growth and Correlation Analysis for PC Insurers"

Last concurrent session...

Dr. Luyang Fu:
Rapid growth is one of the top causes of financial impairment in PC. Growing often means lowering price, looser UW standards, and taking on poorer risks.

"Introduction" slide lists some papers for background reading on the inverse relationship between profitability and growth: Aghion and Stein (2008), Harrington, Danzon, and Epstein (2008), and Ma (2009).

Papers on relationship between policy age and loss ratio: D'Arcy and Doherty (1989; 1990), Cohen (2005), and Wu and Lin (2009).

Papers on optimal growth: D'Arcy and Gorvett (2004) uses a 3-factor econometric model on 14/15 companies. Excluding AIG from the data, he finds that the optimal growth is actually 0%. Including AIG he gets 10%.

Using this model in practice is problematic due to the lack of data and the extreme volatility from removing AIG (parameter risk.) Also the underlying assumptions of the DFA scenarios are iffy. Fu (2012) applies some improvements to the model, but also disadvantages in that it's not stochastic. Equilibrium theory underlies his model. Starts with growth target and % that will be new business to project the combined ratio over a number of years.

Surplus constrains growth, as we know, so there is a limit on the curve. This means that in order to grow faster, CR needs to be lower, and you can draw this "blue line." [KR: see the presentation for formulas. Session is also being recorded.]

Plotting both curves gives you something like the supply and demand curves, yielding the optimal growth. See the Case Study slides for the end results. Note that in the chart of 5-year profits, the column labeled "Year" is supposed to be "Retained Profit." Weight on surplus and the time horizon both make a difference in whether or not growth > 0 is optimal.

Dr. Benedict Escoto (Aon, woot!):
Discussion of correlation/contagion factors. Hierarchical models (Bayes networks) express Y as a function of X. Multivariate distributions with a correlation. Notes that 0 correlation =! independence. Also there are other ways to measure correlation besides the standard Pearson (Cov(X,Y) / SDxSDy.) Copulas (CDF) transform distributions (any monotonic increasing) into a distribution between 0 and 1. Slide 9 shows an interesting example of how even having the perfect underlying distribution can be less effective due to synthesis error. It can work better to use the "wrong" distribution sometimes if it's simpler.

CAT models have traditionally assumed no correlation in severe weather events (non-hurricane.) Tornadoes recently seem to contradict this notion. Traditional model is getting frequency right and severity by layer right, but layer and ground-up CVs are mismatched. Higher layers have more volatility than the traditional model suggests. Using a Gaussian copula [KR: see slides for this formula.] resolves this issue.

Audience question - disconnect between AY CR and CY CR. Does this send false signals about growth?

Luyang: Yes, CY result would be off, particularly if you're under-reserved. It's important to education your executives about the difference between CY and AY.

Luyang's question to Benedict - how often is reinsurance sold in each of these layers versus overall? Does it really matter that we're off on the volatility by layers?

Benedict: Not every reinsurer buys enough layers to solve the problem.

Audience question - how do you parameterize correlations between lines of business?

Benedict: Relatively simple approach. Larger companies with greater diversification in losses are more subject to market risks. We develop a correlation matrix for market risk and layer on top the individual company diversification risk.

End Concurrent Session 4F.

Concurrent Session 3E

"Stories of Risk Culture: the Good, the Bad, the Ugly"

Presenters: John Wengler of Hess and Dragana Pilipovic of Energy Risk WorkDesk

John:
Blame VaR/models/numbers for the crisis? NO. Don't blame the breaks, blame the driver. "St. Francis of Assisi" vision of a risk manager, i.e., highly moral (and associated with martyrdom.) Risk manager should NOT be the most moral person in the organization; he should be like everyone else in the organization.

There's nothing inherently wrong with speculation. We have to have bottom-feeders and vultures, etc. That's how we get functioning markets. See slide 6 for his matrix of the types of risk culture. Individuality versus Community and Order versus Chaos. From this we get "the Accountants," "the Hollywood Agents," "the Commanded and Controlled," and "the Flock" (respectively mapping to: IO, IC, CO, CC.) Then you create a distribution of the organization according to where each person in the organization falls on these axes. The core represents the culture of the organization, but you should have people who go against the core as well, as these people can drive innovation.

Dragana:
Risk management culture needs to be tied to the way the company makes its money. So then the question is: who is motivated naturally within the organization to achieve high-quality risk management? Someone who will stay at the company long-term, who understands the key factors that create success for the company, who answers to the shareholders. Is it about ethics or personality? How does corporate culture motivate? The same person can behave very differently in a different environment.

Focus is on trading. Market making is theoretically risk-neutral (as compared to speculation where you deliberately leave your position unhedged.)  Arbitrage as a strategy does NOT usually mean pure arbitrage (this doesn't happen enough to make enough money.) Statistical arbitrage aims to make money over time. In this case, you do hedge by buying the option and the underlying stock. If you're right about the actual price, eventually you will make money. Finally there's a strategy to just invest in risk-free rates.

In some cases, people say they're doing statistical arbitrage, but when the underlying thing you're betting on is itself risky, it starts to look like speculation. In general, the best traders I've seen have been the best risk managers; in fact, they are risk managers first and traders second.

Natural choices for risk managers include the C-suite and consultants (operation in a competitive consulting market.)

Success stories:

Story 1: Speculative trading shop taking substantial risks. Top trader with decades of experience was not particularly quantitative but did have a good instinctual feel for distributions. He would review the company's book periodically and if he didn't agree with another trader's trade, he would literally take the opposite position in his own book. His focus was on the risk for the total company being at an acceptable level, even if he personally took losses to accomplish that. This shop then had ridiculously stable returns, unlike anything I've ever seen.

Story 2: Volatility arbitrage firm with a head trader who had a quant background, but not a deep understanding. But he valued quants and had as many quants as traders. In this shops, the quants were viewed as the profit-makers, above the traders. Traders were only allowed based on the quants' estimates of volatilities subject to a certain spread. Again a very successful shop.

Story 3: Energy company where CEO and CFO were the top risk managers. Culture started with them and permeated the company. Maintained an appropriate level of trading (under Treasury function) given their level of expertise.

Who is *not* motivated to help the company? Rogue traders, people who just don't realize they lack expertise, C-suites motivated by short-term gains or who are addicted to high returns, or consultants who are loyal to one person and not the company as a whole (because that one person will feed them more business.)

Failure stories:

Story 1: Speculation - Rogue trader takes advantage of "chaos" in the firm to mark his books to his advantage. Really this is a management failure - chaos must be dealt with.

Story 2: StatArb - Assumed mortgage pre-payment rate was fixed, then it suddenly changed. Perhaps couldn't be hedged, but the size of the position could have been managed. In this case, everyone was reviewing and following the model, but this assumption was missed. Consider when assumptions might change.

Story 3: Asset arbitrage failed at a firm where the C-suite (same company as success story!) decided to chase higher returns without acquiring the appropriate in-house expertise. Failed and exited the new business.

Story 4: Market-making - sales-driven organization ended up with negative MTM value on numerous deals. Possible due to IT system.

Story 5: C-suite addiction to higher returns happens frequently. They don't ask how the money is being made. Natural gas spreads, ignoring market liquidity. C-suite approved blowing through the VaR limit multiple times.

Responses to questions from the audience:

John: I don't even like the title CRO, because is implies that risk is a separate function rather than embedded throughout the organization. The best, most thoughtful manager of risk should NOT be the risk manager, it should be the CEO and head trader.

Dragana: The capital issues during the financial crisis were aggravated rather than solved by TBTF. Not that it would have prevented the crisis, but the clean-up would have been more efficient had it been allowed to happen in the free market. Then again it might have prevented it if the risk had been owned by the market (instead of by Fanny/Freddy/gov't.) It may not have made a difference, honestly, if C-levels were caught up in the huge returns. The data was there, showing the risk, but it was ignored.

John: Greenberg at AIG valued the AAA credit rating above all else. After he left, the attitude became "why isn't AA good enough?" But the collateral demands on a AAA versus a AA company are significant. They lost their access to easy credit in addition to having to post margins for losses and collateral on loans. You need to recognize where you're vulnerable. That and you need to recognize when you've been lucky.

Is risk management contrary to human nature?

John: There are some members of the tribe who think long-term, who are managing risk. At the same time, there are cowboys out there.

End session.

ERM Symposium Day 3: General Session IV

Last day, penultimate general session!

General Session IV: "Critical Reflections of the Crisis; International Regulatory Experiences and the Way Forward to a More Robust Financial System"

Dr. Colin Lawrence of the Bank of England, Dr. Allan Malz of the Federal Reserve Bank of New York, John Bilson of the Illinois Institute of Technology

Almost everything said during this panel was said before, particularly in General Session II and in Dr. Lawrence's comments during the "Three Lines of Defense" Seminar (Day 1.) Note that I didn't take notes on the very beginning of this panel, nor on the parts that were redundant.

Allan:
Risk spreads - declined since 2009 but not all the way back to historical levels
Market liquidity - continues to be in poor shape
Implied volatilities - at all-time lows
Why hasn't market liquidity improved with these other variables?

John:
Concerned about the behavior of central banks (increasing the money supply.) We are moving toward a period of higher interest rates. "In economics, everything takes a lot longer to happen than you think it would. When it happens, it happens more quickly than you thought it would." We are seeing inflation in the stock market and housing prices as a consequence of this monetary policy (quantitative easing.) Consequently there is a lot of uncertainty in the financial markets. Which countries are doing best coming out of this crisis? Australia and Canada seem to be doing better, with less central bank interference (although there are other influences in those economies.)

Colin:
Commercial bank profitability declines with interest rate compression. If you raise the interest rates, it's not just the central bank rate, it's the expected inflation on top of that. With high interest rates *and* high unemployment, we'll have high impairments. Forbearance, etc., will result in many more challenges for banks unless they change their controls in advance.

Allan:
We need to remain cognizant of the "human risk," because any adjustment we might make may not play out as expected if people react differently than anticipated. Regarding inflation, at least for the moment expected rates seem well-anchored.

What are implications for risk management practices?

Allan:
Obviously risk managers need to be tracking these regulatory changes. Regulators are looking more at risk-weighted assets, but more than that, we're realizing that simply adding more capital resolves a lot of problems very simply.

What about CVaR? In some cases, we see the CVaR is actually lower than the VaR.

Allan: I've never understood why CVaR is set up as being so much better than VaR. You still need a distribution, and the problem with VaR is that we don't know the distribution. It also doesn't resolve the problem on one-size-fits-all regulation.

John:
There's a fiber-optic cable from Chicago to NY that runs in a straight line instead of along the railways like the old one. Access to this cable costs $1M per year, and it saves you 3-1000ths of a second. That shows how big electronic trading is. Computers are making trades before any human even hears or reacts to news.

Colin:
Liquidity issues make VaR not work when you have concentrated assets. It's a fundamental flaw that's been present for a long time.

End General Session IV.