Tuesday, January 24, 2012

Playground Tales of Risk by a Duck and a Gecko


I was in Macy's earlier this month hunting for end of year closeout deals.  With my selected items, I walked over to the closest checkout counter, which happened to be in the children's department.  In front of the checkout counter was a small display of stuffed animal ducks with a band around its neck that read "Aflac."  There were small ones and larger ones and they were on sale.  The ducks beckoned, "Squeeze Me."  I complied and was amused as it responded in a Gilbert Gottfried derived voice, "Aflac.  AFLAC.  AFLAAAC!"

I was standing next to a small boy, probably about 6, also taking the duck up on its invitation.  He squeezed a few times, selected a larger duck, and ran over to his parents to show them.  He held the duck up into his father's face and squeezed, "Aflac.  AFLAC.  AFLAAAC!"  The boy grinned and his father gently pushed the boy's hand from in front of his face, "Sorry Jr., but at this time, our family is not in need of a stuffed duck that promotes supplemental health insurance."  

I later came to find out that the toy is actually part a fundraising campaign benefiting the children's hospitals around the country.  I was surprised to find out that this has been going on for ten years, which is telling of the last time I was in a mall around the holidays.  But, witnessing the family interaction initiated by the squawking toy, my amusement turned into intrigue of insurance companies marketing directly towards children.  Indeed, prior to and during Gottfried's appearance as a talking duck, he was the voice of several characters in movies and programs geared towards children


This quickly got me thinking about the Geico Gecko.  Part of an extremely large, diverse, and well revered advertising campaign intended to target multiple demographics, the Gecko is warming up to the nation's children.  In 2009, the Gecko teamed up with Disney's animated Frog Prince.  The duo starred in a television campaign together promoting both the movie remake of the children's story, "The Princess and the Frog" and car insurance.  Today, the Gecko can be found entertaining children while touring the nation's zoos.  You and your family can follow him on Facebook.    


While a brand and its recognition have long been pillars of successful marketing, companies have had their fair share of grief for targeting children in reaching their brand loyalty goals.  Cigarettes and fast food come quickly to my mind.  But chastising has come after such products are found to have undesirable social ramifications.  

What ethical dilemmas are present in building brand recognition of insurance companies in children?  Are there foreseeable social ramifications in marketing insurance and risk to children?

In order to be willing to buy insurance products, one must believe the risk that the product is intended to protect against is real and worthy of investment.  The appropriateness of constructing such risks in children's mental models is worthy of public consideration.   

Sunday, January 22, 2012

Quality of Life in the Sunshine State


Despite the countless brochures depicting Florida as the land of extravagance and sunshine, it is quite a stressful place.  Indeed, on a list of the top five most stressful places to work, Florida has won positions #1 (Tampa), #3 (Miami), and #4 (Jacksonville).

In 2009, considering other factors Florida does not show up on the list until position #17, with Tampa.  Miami made that list at #20.

Thursday, January 19, 2012

Modeling Certain Mayhem


In America's deep south, a region not so far away, hides a new foe threatening otherwise intelligent people's ability to decide. The Louisiana Insurance Commissioner, Jim Donelone, has rung the alarm putting homeowners on alert of  "The looming threat of the new cat model, RMS 11".  This is the newest addition in the catastrophe model rogue gallery challenging the gallant efforts of state insurance regulating offices.  The kryptonite in their coding is the incredible capacity to produce scientifically supported uncertainty thereby weakening the ability to control rates by politically hopeful insurance commissioners everywhere.   A past episode between dueling regulating powers and risk predicting machinery demonstrated the societal cost inflicted by these dastardly foes creating uncertainty whenever plugged into a wall.  In 2006, RMS rolled out an arbitrary change to their trusty hurricane catastrophe model in RiskLink 6.0, costing Florida homeowners $82 billion.  Stay tuned to state regulating offices for the latest updates on the battle between man and machine...

In the mean time, let's take a closer look at these new trade secret rascals (Submitted during 2010/2011 to meet 2009 standards).  

New models vary in characterizing the hurricane risk.  

Vertical axis: Probability of landfall; Horizontal axis: Saffir- Simpson Category 1-5
From this view, RMS seems not so different from the other models when considering landfall probabilities for the entire state of Florida.  While model estimates within each category "look" somewhat similar, because they are dealing in percentages they are in fact, substantially different.  

For example, consider a Cat 5 storm, the most damaging.  AIR and EQECAT guess 1% and RMS, ARA, and the state's own Public Model (also known as FIU), guess 2%.  While the difference is only 1% it is also the difference between experiencing a Category 5 landfall in the state of Florida once in 100 years or once in 50 years.  A similar situation exists for a Category 4 storm.  ARA estimates an annual probability of 4% or once in 25 years and RMS and EQECAT estimate 8% or once in about 13 years.  All of these estimates are grounded in "sound science."    

What sort of punch is packed into these probabilities?

There are several time frames by which to measure a probable maximum loss (PML) or how much do you probably stand to lose.  A common time frame is 100 years.  Below is a table showing each new model's estimated 100 year PML. 


According to the suite of models, the 100PML is anywhere between $18 billion and $146 billion.  Now, let's say you are charged with choosing one model on which to base rates (such a scenario is highly unlikely), which one would you choose and how would you make that decision? *Remember, each one is as good as the next.

The decision depends on something other than "facts," it depends on who you are, what you fear, and your goals.  Do you fear insolvency?  Stock holder dissatisfaction?  The cost of living month to month?  Losing an election?  Are you seeking to establish a new national natural disaster insurance regime?  Expand affordable housing mortgage lending?  Enliven fears of climate change? 

Together, these models create a great deal of uncertainty about the risk being insured against.  In the world of insurance, uncertainty about the risk is risk in and of itself.  If uncertainty increases, then the cost will too and vice versa.  So, a reasonable question to ask would be, "Has the modeled risk changed?"

What follows is a comparison of the most recent model reports, submitted over 2010/2011 to meet 2009 standards, and model reports meeting 2008 standards submitted during 2009.  All dollar estimates in reports meeting 2008 Standards have been adjusted for inflation to 2010$. 

When considering landfall probabilities, ARA and RMS have increased the estimate of a Cat 5 landfall by 100% in their most recent submissions.  There are other changes evident here too.     


What do such changes mean for estimated 100 year MPL.  Below is a graph showing estimated loss  changes from 2008 Standards to 2009 Standards as a percentage of 2008's estimate.  We see that overall, changes in estimated loss is fairly small EXCEPT for the Public Model.  They have increased their estimated losses by nearly 40%.  

(Whoa!  Look out Citizen's policyholders, your rates are directly tied to this model.)   

Look at the table below.  Recent estimated losses are fairly consistent with 2008 standards estimates which guessed a range of $20- $140 billion.   


However, if we consider changes in overall model uncertainty from 2008 standards to 2009 standards we see a notable increase of 34% in uncertainty born predominantly by the state's public model.

% change of uncertainty interval from 2008 Standards to 2009 Standards
RMS: 16.23%
AIR: -4.29%
ARA: 2.51%
EQECAT: -13.38%
Public Model: 33.07%


Presented here is only half of the uncertainty machine team as  reinsurers have a whole other set of models up their sleeves.   

If new models guess the same losses but increase uncertainty about those losses is this progress?  I don't think so.  For those familiar with a hurricane forecast, imagine that the skinny black line remained on a a constant path but the white "cone of uncertainty" around it got bigger and bigger.  

(Louisiana does not have its own state funded model.)

Thursday, January 5, 2012

Model Me This...


The NFIP had to borrow from the US Treasury to cover losses during several flood events of 2005 and one Hurricane Ike in 2008.  This is not uncommon in the US, where supposedly, nearly everything disaster related comes from the Treasury.  In a recent report, the research team at the Wharton Center for Risk Management and Decision Processes argued that the reason for this is because the NFIP does not use probabilistic catastrophe models to establish premiums  but instead charges premiums that reflect the average annual year loss.

So the report investigates what would the premiums cost be if the method of calculating premiums were catastrophically modeled in two Texas counties.  Travis County is subject to riverine flood, Galveston County is subject to storm surge. 

They compare unloaded costs and show that "the current unloaded NFIP premiums are 'too high' in some areas and 'too low' in others relative to the probabilistic flood model results."  That is to say, they argue for a change in charges amongst risk groups, but averaging together risk groups in either county shows little difference from NFIP premiums.  For instance, in Travis County the study average is $2.42/ $1000 of property compared to the NFIP average of $2.6.  In Galveston County the study average is $4.7/$1000 of property compared to the NFIP average of $3.8.       

With this in mind it seems unlikely that a change of pricing technique would result in less chance of NFIP deficit considering roughly the same amount of money is collected annually.  What the model seems to most clearly do is change who pays what- which is, in effect, an ethical decision that should be well grounded in actual human political debate.      
The red circle and line is from the report. In reference to the idea that the NFIP is "too high" in some instances. 

I wonder, however, where the $1 increase comes from for Galveston County.  I am inclined to guess that it comes from one or both of two sources.  First, the modeled risk uses predictions of storm surge which are notoriously uncertain.  If, then, using the storm surge predictions increases the uncertainty of losses over that in the historical record, then it would necessitate increases in rates.  The other (obvious to me) possible source of the increase in rate is incorporating climate change assumptions into the model.  It is an interesting choice by the authors, considering the controversy surrounding the issue. The authors, themselves, admit that disaster loss increases are attributed to societal changes.