Predictive analytics allows feds to track outbreaks in real time

Predictive modeling could change the relationship you have with your agent or broker because it changes the complexion of riskiness. This is not only true for workers’ compensation, but commercial and executive coverage as well.

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Currently, agents and brokers respond to insurer underwriting changes, which can happen without warning to them. Insurers are trying to do a better job communicating to their agents and brokers about new underwriting parameters resulting from predictive models.

 If insurers choose to write coverage differently for certain risks or industries, your agent or broker might have to scramble to find a new insurer. As pointed out in a previous blog, predictive models are more sensitive than the traditional experience modifier. Therefore, you could be surprised by the delicacy of insurers’ predictive models compared to the traditional experience modifier.

You might even get new and better service. Agents are increasingly becoming “strategic partners” with their clients. To improve customer retention, these agents try to help clients improve their risk profile. This is already going on in the health insurance arena where agents and brokers are offering wellness and disease management programs to improve the health of their clients’ employees.

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You might even get new and better service.
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Insurers have also developed predictive models to determine which agencies and brokerages more likely to bring in business. So if you like your insurer, you may end up having to use a different agent or broker.

Theoretically, agents and brokers can use predictive modeling to help their customers make better buying choices. Some very progressive agents are initiating their own efforts to identify the cost of an employer’s workers’ compensation risk through predictive modeling. They are recommending initiatives to improve risk and the pre-underwriting phase of buying insurance.

However, most do not have the resources to hire actuaries and statisticians to build models or locate appropriate data sets. And, too many agents and brokers are having difficulty adapting to computer automation. Expect them to ask more detailed questions about your company. This additional information is for the predictive models for underwriting and perhaps premium auditing applications.

Off-the-shelf workers’ compensation predictive modeling products are not yet available to agents and brokers. Until they are, you and your agent may end up at the mercy of predictive models insurers are using.

As I covered last week, predictive modeling is here to stay. We are yet to realize all of its ramifications.

Finally, in comments posted by readers, I asked how soon predictive modeling would affect them. My broad assumption is the larger the insurer you buy coverage from, the sooner and more likely you will be affected by predictive modeling. This is simply because larger insurers have more resources to devote to predictive modeling. But small-to-medium insurers are catching up because they must compete. (For more information, check out my Leader’s Edge article, Modeling the Future, which covers how predictive modeling will affect agents in much greater detail.)

Next Week’s Blog: Predictive Modeling: Opportunities for Self-Insured Employers

This is part III of my series,What Employers Need to Know About Workers’ Compensation Predictive Modeling. To read part I, click here. Part II, click here.

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Below is a response to my blog, “Predictive Modeling Is Here to Stay” in a discussion published on the Linked In group, Workers Compensation Roundtable last week.)

Responder 1: Predictive modeling is particularly useful on smaller policies. An account with millions of dollars in payroll and high premiums generally gets more attention so the quality of information is higher. Given the size, the history is much more predictive of future results. On the smaller accounts, you don’t typically have as high quality information and a lack of data on which to make sound assumptions. You have to underwrite the book more than the individual account. Predictive modeling allows a carrier to do that fairly, as you point out, by find those metrics that are real drivers or results.

Responder 2: Predictive Modeling clearly is being effectively engaged to improve the WC underwriting process. There is also a growing initiative to apply predictive models in the post claim world, using predicted loss costs from FROI data to create triage protocols, severity specific claim handling strategies, managed care referral triggers, and other resource allocation decisions. Finding the Pareto 20% quickly and deploying high case cost mitigation strategies can be achieved with predictive modeling tools. This is an equally important initiative for employers to engage with carriers and vendors managing their WC programs.

Me: Agreed! I will be covering how SI employers can use predictive modeling in a future post.

Responder 3: Annmarie, thanks for your posting. I followed through on your link, then to the other links…the article in Contingencies was hard to read online and I would very much like to see it in an easier to read format. It is my impression that predictive modeling has in effect been in workers comp for decades. What IT has done in the past 5 – 10 years, with more power, more accurate data, and far easier integration of disparate data sources, is to given real meaning to the word “model.” As the phrase goes, “all models are wrong; some are useful.” That is, one has to have the mind set to persistent in trying out different ways of looking into the future, always be willing (and able) to experiment. And this brings up for me the great barrier to predictive modeling in workers comp: the resistance of some claims and underwriting executives to challenge their own ways of predicting, which are crafted over many years and based on very flawed perceptions of reality. They thrive on anecdotes that they will not give up on.

Me: Part of predictive modeling is using new non-insurance-related data sets. This is definitely new. Barriers are being overcome. They must for insurers to stay competitive. One workers’ compensation insurer wrote me after my post asking how small-to-medium-sized carriers are handling predictive modeling when data is limited. More insurance-related data is becoming available. More workers’ compensation carriers are adopting predictive modeling and I will be posting something on this by the end of the week. Sorry about the Contingencies article. I like to refer people to the actual publication’s posting. If you go under my “work samples” tab on my blog, you will also find it there. To save time, I am giving you the link to it below. It is a paper copy I had scanned in. Here’s the link: http://annmariecommunicatesinsurance.files.wordpress.com/2012/01/workerscomppredmod-contingencies2.pdf

You are correct that computer technology is also making predictive modeling more possible. As I am covering in an article yet-to-be published, more carriers are installing new systems that support predictive modeling. Thanks for reading and for your comments! Stay warm!

Responder 4: (Responder 3) is right The “dinosaur” mentality based on years ( actually decades…) of “gut feeling” still prevails out there. It is in claims, sales, loss control, risk management, etc. Part of the problem is that people inherently resist “change”. 

When “the model” does not agree with the “historical perception” then “the model” must be wrong, because the person making that “right / wrong” decision has made those type of decisions based on a “gut feeling” (i.e. – experience) for the past 40 years….. 

When the data CONSISTENTLY swings in favor of “modeling”, then the “gut feeling” as the “primary” critera has to be “repositioned” as a secondary consideration, rather than the primary consideration. In time, as models improve, maybe 95% of WC claims can be successfully “modeled”. The remaining 5% are going to have to be reviewed by a person that determines that the model does not apply to this SPECIFIC claim and maybe a “gut feeling” decision is more appropriate, in this single case. At the end of the day, every claim is unique. 

WC modeling has come a long way in a short time, and like everything, will continue to improve as more valid data is compiled and analyized. You just have to convince “the boss” that the data is more accurate than 40 years of “gut feelings”……

Responder 3: Annmarie, thanks for posting the article in a readable format. It is the best discussion I have ever read on predictive modeling in workers comp. To be sure, you are light on the resistance to modeling such as (one responder) cogently points out. The first serious model I saw as introduced into a workers comp insurer about 2000 and was abandoned eventually because adjusters felt threatened. But your article is a gift to the community. My abiding interest in modeling took me to nutty extremes last September when I visited the grave site of the poet, Rilke, whose poems of 1900-1925 were, I feel, an aesthetic interpretation of modeling, in his case, how you change your whole life, time and again.

Me: Thanks for the compliment on my article.  Just want to address (Responder 3) and (Responder 4). For underwriting purposes, predictive modeling often quantifies what underwriters knew with their gut feeling and that alone is important. But it goes far beyond that. 

Workers’ compensation predictive modeling got started around 12 years ago by the largest wc insurers and applications keep growing. I do not agree that the “dinosaur” mentality is holding back insurers, or not at least like it once did. 

It can’t. There is just too much profit to be made, not to mention all the market segmenting opportunities insurers can use to fine-tune their competitive strategies.

The bandwagon is filling up and nobody wants to be left behind. 

Predictive modeling, as it is now understood, started with Progressive Insurance around 30 years ago. It forever changed how auto, and later other personal lines, would be underwritten by the entire industry. 

It will not take that long for the same to happen with workers’ compensation predictive modeling. Commercial lines actuaries and statisticians have learned a lot from the personal lines experience and there are more tools available. Automation and the latest computer systems support predictive modeling much better than those of the past. Some companies are developing computer systems with predictive modeling in mind. 

The article I posted does cover barriers to predictive modeling, but they are quickly being overcome thanks to good old fashioned profit motive. Workers’ compensation insurance will experience the Progressive Insurance phenomenon. If employers did not have a good enough financial argument for following all the great advice to reduce losses, they do now.

Responder 5: Excellent article. Re: your comment “predictive modeling often quantifies what underwriters knew with their gut feeling and that alone is important” – don’t underestimate the importance of this. Underwriters are trained in the Joe Friday, “just the facts” school and are hesitant to make a decision without something in the file. 

On the claims side, this is also true. I was involved in putting together a very simple model which showed UR denial rates or treating physicians – a simple provider scorecard. When the examiners saw this, they were delighted to have real evidence that Dr. X was a problem.

 Me: Thanks (Responder 5). I have been keeping my focus on predictive modeling as an underwriting/rating application because this is the most common and immediate way employers will notice a difference in premiums based on their experience. Claims predictive modeling is also picking up some speed and we can learn a lot from group health care in this regard. I have more articles coming out on predictive modeling and when they are published, I will share! 
Appreciate all the comments everyone!

(Note: Permission was granted by one of the group’s managers to publish this discussion with the names of commenters removed.)

Credit: Brian Casey

Last week’s blog covered how workers’ compensation predictive modeling will affect premiums. But there is much more employers need to know.

2) Predictive modeling is here to stay. Predictive modeling is well on its way to becoming an insurer best practice. According to a study released by Towers Watson last year, 72 percent of the comp carriers surveyed said they are either engaging in predictive modeling or soon will be. (For more info on the survey, please see my workers’ compensation predictive modeling article.

You can’t blame them really. Insurers engaging in predictive modeling are becoming more profitable more accurate rates, lower losses and better customer retention. Those not yet applying predictive models will have to follow suit to stay competitive. The latest Towers Watson survey is coming out soon and I expect it will show more insurers are pursuing predictive modeling in workers’ compensation. (I’ll let you know when it comes out.

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… insurers engaged in predictive modeling are looking for that “secret sauce”…
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3) Auditing parameters will change. In a perfect world, employers would be completely truthful when applying for insurance and understand the comp classification system to avoid misreporting. But the world is not perfect. The insurance industry estimates that 15 to 20 percent of employers are not paying their fair share for workers’ comp.

Traditionally, larger risks – those paying more than $10,000 in annual premium — got more attention from auditors. Insurers are using predictive modeling to locate employers more likely to need auditing. Using government sources, for example, insurers are looking at wages and employment information to reveal payroll information discrepancies.

Predictive modeling can also reduce the shell game played by shadier employers who change their company name to get a clean experience modifier or switch insurers to hide high-risk jobs under other classification codes.

4) There is a lot of experimenting going on.  Predictive modeling is relatively new to commercial lines. Insurers engaged in predictive modeling are looking for that “secret sauce” that will enable profitability.

This means there is a lot of experimenting going on. Insurers are experimenting by using new types of data as factor proxies.  They are also learning how much weight to give factors, the best combination of factors, and other considerations.

(Note: This is part II of my blog series on What Employers Should Know About Workers’ Compensation Predictive Modeling. To learn how predictive modeling will more accurately reflect an employer’s specific experience, click here.)

Next week’s blog : Predictive Modeling and Your Insurance Agent

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A special “thank you” to Mark Wells for making this blog a “manager’s choice” on LinkedIn’s Work Comp Analysis Group.

If predictive modeling is not already influencing your premiums, chances are it will soon.

Predictive modeling is a statistical approach that looks at traditional variables, such as employer’s history of losses, and adds non-traditional factors, such as the average salary of employees. Just as credit scoring is a proven risk indicator for personal automobile coverage, considering a company’s financial health can indicate the degree of workers’ compensation risk.

Factors, representing colors here, are fed into predictive models.

There’s a lot employers need to know about predictive modeling.

1) Premiums will more accurately reflect each employer’s specific experience. Predictive modeling is a more finely-tuned instrument than traditional pricing approaches. That’s because it gives weight to new and traditional factors.

This is great news for progressive employers doing everything they can to foster a safe and healthy workforce, boost overall morale and help injured workers return to work. Efforts such as more early claims reporting, which helps employees get better medical treatment and heal faster, are more quantifiable through predictive modeling and can positively affect premiums.

Conversely, employers who view comp as a price of doing business are in for unpleasant surprises. They could very well find themselves in the high risk pool.

Traditionally, workers’ compensation insurers priced on a “univariate” classification basis. This means insurers would look collectively at employers and their employees in the same class. An employer’s experience modification factor is then used to reflect its actual risk history.

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Conversely, employers who view comp as a price of doing business
are in for unpleasant surprises.
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Another factor can be the affordability and quality of health insurance coverage. This can determine the incentives for cost shifting medical treatment to workers’ compensation. Healthier employees tend to recover faster, which shortens the duration of workers’ compensation claims. Therefore, initiatives taken to improve employee health, such as wellness programs and disease management, which can help reduce co-morbidities such as diabetes, smoking and obesity, are also possible factors.

Other employer-specific factors that can be fed into predictive models including payment history, loss control initiatives, age of company, average age of workers and length of employment because these have been shown to affect outcomes. Income levels of employees can be an indicator of employee morale based on the assumption that better compensated workers are happier.

Personally, I am excited! Predictive modeling will give employers even more financial incentive to pay attention to employee health and safety on and off the job. That can only be a good thing.

This series is primarily based on articles I have published in two industry magazines. Check them out by clicking here and here.

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Good stuff, but not directly applicable to B2B marketing…

http://blog.hubspot.com/blog/tabid/6307/bid/34032/An-Investigation-Into-the-ROI-of-Direct-Mail-vs-Email-Marketing-DATA.aspx

Profitability is a sensitive subject in workers’ compensation. That is because, with a smattering of exceptions, workers’  compensation is mandated. As heavily-regulated social insurance, its profitability cycles have often been compared to roller coasters — and for good reason.

For a fresh look at workers’ compensation underwriting cycles and their historic causes, check out Workers’ Compensation Insurance Industry Underwriting Results in 2011 (which is also posted at the bottom of this blog). Published in the Workers’ Compensation Resources Research Report, its author, John F. Burton, Jr., graciously shared his December 2012 article with me prior to its release.

Burton is not an actuary, but an economist and  retired professor and CompLand’s senior researcher. As the head of the only National Commission on State Workmen’s Compensation Laws, which stemmed from the Occupational Safety and Health Act in the early 1970s, the depth and degree of his influence on workers’ comp cannot be overstated.

Ultimately, Burton takes readers through underwriting figures galore since 1973. He begins by reporting that the overall operating ratio – the most comprehensive measure of insurer profitability because it includes investment income  – went up from 96.7 in 2010 to 99.8 in 2011. This reflects a downward profitability trend for the past several years and partially explains why employers are seeing premium increases.

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Using A.M. Best figures, Burton’s article is a veritable time machine,
unfolding the drama of the workers’ compensation underwriting cycle.
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An overall operating ratio more than 100 means insurers are losing money even with investment income while an overall operating ratio that is less than 100 means insurers are profitable.  “The overall operating ratio of 99.8 in 2011 means that workers’ compensation insurers made $0.20 of profit per $100 of premiums that year,” Burton said.

Using A.M. Best figures, Burton’s article is a veritable time machine, unfolding the drama of the workers’ compensation underwriting cycle. Insurers have gains and losses and employers’ pay more or less through a parade of political efforts intensifying the twist.

Note that Burton is not using figures from the National Council on Compensation Insurance, Inc. (NCCI), which is the go-to organization for underwriting information in workers’ comp. NCCI tends to stress the combined ratio as a measure of the comp underwriting experience. To Burton, however, the combined ratio alone “represents an incomplete and potentially misleading record” of insurer profitability because it does not include investment income, which averaged almost 15 percent of premium in the seven years from 2005 to 2011.

He insists that he does not want to suggest that $.20 per $100 of premium is an adequate return for workers’ comp insurers. At the same time, he writes,” focusing on the overall operating ratio – and not the combined ratio after dividends — should be the starting point for assessing the profitability of the workers’ compensation insurance industry.”

Maybe so, but how can I resist comparing A.M. Best’s figures with NCCI’s? I’ll post my findings in a future blog after I visit with a couple comp actuaries!

Burton’s piece rightly offers that profitability from investment is an important contributor to overall profitability. He reviews each piece of the overall operating ratio for workers’ compensation and throws in comparisons with other major property/casualty lines.

After demonstrating the true profitability picture, he tries to persuade the reader that there is “little justification” for cutting benefits or tightening compensability now since benefits paid to workers as a percent of payroll have been stable since 2006. This is unlike the period from 1982 to 1992, when the workers’ comp insurance industry saw adverse underwriting results and benefits increases were on the rise.

This of course raises the issues of narrowing compensaibility, which is fodder for another day.

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WCRRRNo5FINAL

Just for fun, but this does explain a few things…

http://www.mediabistro.com/mediajobsdaily/tv-radio-jobs-are-among-top-10-to-most-likely-attract-psychopaths_b13338