Tag Archives: underwriting

Premium Optimization

price_optimization

Price optimization is not a new concept, though it is receiving increasing attention in the insurance industry.  Ushered in with the era of “big data” and “predictive analytics” commercial enterprises of all stripes now have the ability to refine pricing on the fly in order to extract every available ounce of economic value from their customers.  At its heart, price optimization involves charging higher prices to customers who are able and willing to bear the additional cost, whether they realize it or not.  Herein lies the rub.

Two customers may purchase an identical product or service but one customer pays more simply because data analytics indicated that the customer was less likely to shop around or otherwise balk at the higher price.  The customer paying the higher price may not even know (probably doesn’t) that they just paid a higher price for the identical product compared to other customers.  The use of price optimization on insurance premiums has all the makings of the credit-score-as-a-rating-factor controversy, if not more.  Opponents of credit score premium rating argue that the credit score is not related to the cost of risk associated with insuring a particular individual – except that there is statistical evidence that it is.  Circular arguments ensue.

However, price optimization is a cat of another stripe.  Suppose an insured is charged more premium than would otherwise be charged simply because data analytics indicate that the customer is likely to accept and pay the premium based on the data model showing that last year’s rate increase did not cause the customer to move his business.  What does that customer’s propensity to stay with the insurer in spite of a rate increase have to do with the customer’s risk of loss?  Nothing, as far as I know.  So price optimization boils down to charging more premium because, well, we can…. at least that’s what the predictive models tell us.

And why shouldn’t the insurance industry avail itself of all the technology and knowledge that other industries are using to their advantage?  Online retailers and travel providers (especially airlines) have been doing this very same thing for quite some time.  Ever heard of “yield optimization” in the airline industry?  When was the last time you thought that airfares made any sense whatsoever, let alone resemble the actual cost of each passenger mile flown?  So perhaps the insurance industry should use the same defense I used with my parents when I was a teenager, “Gee mom, everyone else is doing it!”

I am reluctant to get on the price optimization bandwagon, for the same reason that the “Gee mom, everyone is doing it” defense didn’t work for me a few decades ago.  The frequent retort from mom was, “And if everyone jumped off a bridge, would you?”  I suspect that price optimization is going to encounter greater regulatory resistance than credit scores (it already has in several states) and the cost of risk justification is far more tenuous.  Even in the absence of regulatory concerns, the insurance industry might want to avoid becoming addicted to price optimization such that it begins to overshadow prudent underwriting and risk-based pricing.  Imagine a world where insurance premium optimization data models become so accurate and reliable that they begin to supplant underwriting principles and the computer models start engaging in cut-throat price optimization pricing that become increasing devoid of links to the actual cost of risk.  I would hope that regulators would step in before it went that far, but after 2007-2009 (and the subsequent knee-jerk reactions), I have no illusions of what regulators will and will not do.

In the end, I just have a bad feeling about “optimized” insurance premiums.  The insurance industry doesn’t need another reason for consumers to dislike and mistrust the industry.  I’d rather focus resources on improved cost of risk predictive modeling to better fit pricing to each insured’s risk profile, and let the airlines incur consumer wrath for playing these sorts of pricing games.  Serves them right for treating us like cattle.

Wanted: Cyber Insurance

wanted-cyber_insurance

Staying with the theme of last week’s post – which was an exercise in exasperation over the ongoing stream of high-profile data breaches – I decided to examine the insurance industry’s readiness/appetite to respond to this risk.  My conclusion?  The demand for cyber insurance is clearly surpassing the available capacity for such coverage.  That conclusion certainly isn’t a surprise to anyone, and the reasons given for limited cyber insurance capacity are logical.  Nevertheless, your humble blogger senses that there is reason to be concerned that the nascent cyber insurance market may not develop as risk managers hope and expect.

Insurance Journal reports that there are just a few insurers cautiously wading into the cyber insurance market at this time, and that their offerings are limited by policy exclusions and low limits of insurance.  Insurance buyers are seeking far more coverage than the insurance industry is ready and able to supply at this time, reportedly because the actuarial data is insufficient to properly model cyber risk and to price the risk appropriately.  More time and data is needed, experts say.  Red flag alert.

Underwriting more conventional risks such as property losses caused by fires and storms, or liabilities for slips/falls, will clearly benefit from mounds of historical data.   Fires, storms, and slip/fall hazards present relatively stable risks.  One can argue the nuances, such as improvement of flooring technology to reduce slips/falls, and better fire protection systems, but the inherent nature of fire, slips/falls, etc. are fairly constant.  Personally, I am not convinced that the cyber actuaries and underwriters are going to find anything close to a stable risk model for the cyber risk insurance products they are working on.

If we have learned nothing else over the past 20 years, we have learned that “internet time” passes by very quickly.  Just as we become comfortable and proficient with the latest technology, obsolescence sets in.  In my past life as a software developer, I spent a fair amount of time with my fingers in source code and I know just how quickly those coding skills atrophy simply because of the swift passage of time that brings about new software tools, methods, and insights.  The basis of many cyber risks is in the billions of lines of source code throughout our systems.  It stands to reason that just as the insurance industry grows comfortable with the cyber risk threat from an actuarial and modeling perspective, the target will have moved as the software and systems rapidly evolve – frequently with insufficient time to harden and protect the code from the creative attacks of hackers.

There should also be some concern over the extent to which cyber risk is or is not an insurable risk according to the textbook definition.  The insurance industry functions best when the law of large numbers can work across a multitude of similar exposure units, and when losses are independent and not catastrophic.  Geographic concentration of a book of business without adequate reinsurance in hurricane-prone locations has killed some insurance carriers in the past.  What might a particularly nefarious and unanticipated piece of viral source code do to the Fortune 500 and their cyber insurers if it proliferates through a common and previously unknown code vulnerability in common platforms such as Oracle databases or Cisco routers?

Cyber insurance is in great demand, and the headlines provide witness to why this is so.  The unanswered question remains, to what extent can and will the insurance industry have the capacity to meet this demand or will alternative risk management techniques be forced to fill the gap?  The cyber insurance market may well be even more challenging than the terrorism risk insurance market.

We live in interesting times.

Underwriter? What’s that?

underwriting

I have a soft spot for the underwriting profession, primarily because that’s where my own career got started.  It has to be one of the least understood professions out there.  My own story is typical.  My senior year at Michigan State University (Go Spartans!) was filled with on-campus interviews with a variety of companies and job types.  With an undergraduate degree in Socioeconomics (a blend of political science and economics), I wasn’t sure what sort of job awaited me.  What I had going for me was a strong set of analytical and communication skills.  As it turns out, that skill-set is well suited to insurance underwriting.  But I didn’t know that then.  When I interviewed with CIGNA (back when they were still in the property and casualty insurance business) I had to do some fast research to have the slightest clue about the job for which I was interviewing.

So what does an insurance underwriter do?  At the very heart of the job, it comes down to deciding which risks the insurance company will accept and at what price/terms.  Staff underwriters typically work in an insurance company home office and set guidelines for the types of risks that are acceptable to the company.  Line underwriters apply those guidelines to the individual risk applications that they underwrite.  That is an oversimplification of the job because underwriting requires thorough analysis of risks, interaction with insurance agents, loss control, claims, management, and more.  Creativity and problem-solving skills are paramount because some risks may not be acceptable upon first review but creative application of loss control measures and insurance contract modifications can make it possible to accept a challenging risk.  A win-win-win for the insurer, the agent, and the insured.

Rather than reinvent the wheel, take a look at this description of effective underwriting.  I remember my early days as a brand new property and casualty insurance underwriter, and the relationships that I built with many commercial insurance agents.  They knew that I was a “newbie” and I appreciated their patience with me, and many of them took the time to contribute to my early career education.  An experienced underwriter is like gold to an agent because they have the stories and insights that help agents to write more business that fit within the underwriting appetite of the insurer.  I moved on to an underwriting/marketing staff position, and then jumped over to a corporate risk management position before launching my own business.  I didn’t spend enough time in my underwriting job to develop the kind of deep expertise that makes an underwriter extremely valuable.  I respect the underwriting professionals who have developed that kind of expertise and make the industry work so well for the insurers, agents, and insureds.  It’s a little-understood job, but a very rewarding and valued job.  Go kiss an underwriter today.