Click here to read ASI\'s Vice President of Healthcare, Paul Marshall, discuss how effective use of risk analysis and predictive modelling can help a captive to stay one step ahead of the market!

1. HEALTHCARE REPORT
Taking the
risk out of risk
management
Paul Marshall of American Safety Insurance Paul Marshall is vice-president, healthcare
explains how effective use of risk analysis and underwriting group with American
Safety Insurance, responsible
predictive modelling can help a captive to for overall business strategies
including overseeing of opera-
stay one step ahead of the market tions, sales, underwriting, risk
management and loss control.
He brings with him 20 years of
experience in the health-
‘S
care liability, risk and claims
cientia potentia est’ is the com- scrutiny. This type of care data had been management industry.
monly coined Latin phrase we difficult and expensive to obtain in the
know as ‘knowledge is power.’ past, requiring consulting firms to harvest
This could be linked to many and organise the data into usable chunks. residential care facilities. The NSRCF,
different businesses and operators, but is The utilisation of now widely publicly the first nationally representative sample
especially relevant to the captive insur- available data will be a key differentiator survey of residential care communi-
ance programme industry. As this form in managing succesful healthcare insur- ties, was conducted between March and
of risk transfer becomes more and more ance captives and programmes. November 2010. Interviewers collected
necessary, every bit of knowledge or ‘risk An example of new published data information on more than 2,300 facilities
data’ has to be exploited for its full poten- that would be valuable for a healthcare and over 8,000 residents. Reports like this
tial in order to stay ahead of the curve and captive’s risk analysis is the upcoming can be invaluable for healthcare captive
execute business decisions as successfully National Survey of Residential Care Facilities managers, giving them a real-time, all-
as possible. I am describing the art of (NSRCF), to be released by the National encompassing view that will allow them to
‘risk analytics,’ and how it can be one of Centre for Health Statistics (NCHS) by shape their insurance program to be right
the most important weapons in a captive the end of the year. Under this umbrella, at the cutting edge of the market.
insurer’s arsenal. the NSRCF will consist of three products:
Senior care Long-Term Services and a methods report (describing how the
Supports (LTSS) is one of the largest NSRCF was conducted), a facility data Risk analytics
growth industries in the US and insurance brief (containing highlights major find- Using timely and informative data in a
programmes that learn how to manage ings on US residential care facilities) and responsive and influential manner, when
these risks will see exponential growth a public-use data file (containing data col- coupled with predictive modelling, help
opportunity. lected about the healthcare facilities). to provide the captive insurance manager
With the 70 million baby boomers start- By April 2012, the NCHS also plans to answers to very important questions about
ing to turn 65, there is a new voracious make available to the public a resident the risk and gives them a much needed
demand for ever increasing healthcare public-use file and a data brief, reporting advantage. The reach of risk analytics
data ‘visibility’ for public review and selected characteristics of residents of US is spreading through expert third-party
WWW.CAPTIVEREVIEW.COM CAPTIVE REVIEW 05

2. healthcare report
“
modelling is the ability to establish more
a captive manager has accurate actuarial reserves. With improved
accuracy in identifying overall risk, carri-
to play to the strength of risk ers can establish and responsibly change
reserves as needed that commensurate
analytics in order to benefit from
with the ever changing underlying risk.
Such financial efficiencies allow an organi-
sation to direct their financial resources to
it, which means being savvy and the most effective point. This helps make
great savings as the captive programme is
quick enough to respond” aimed specifically at the exact areas that
require focus – enabled by risk analytics.
Historically, a large portion of the
insurance programme’s expenses are
service providers, the advantages of such captive to remain viable for the long term. consumed by initial application and risk
sophisticated modelling tools are available For that reason, experienced insustry- underwriting proces. Predictive ‘sales’
to most captives regardless of in-house specific underwriters who understand the modelling can assist in finding suitable
technological expertise or available specific risks are critical. Historically, the accounts much more efficiently than the
capital. theory has been vetted and, throughout traditional approach, which requires
Writing insurance for the healthcare in- many risk industries, predictive modelling underwriting the effort of reviewing and
dustry is becoming increasingly difficult as strategies against traditional underwrit- analysing more than 10-20 accounts
everyday healthcare facilities tweak their ing approaches were found to be more before finding one that fits for the risk
operations to remain profitable under accurate. Essentially, predictive modelling programme’s appetite. This can be viewed
changing medicaid/medicare reimburse- can help eliminate the human and emo- as a sales divining rod, finding the suitable
ment policies along with evolving regula- tional response that naturally occurs in risk with minimum marketing or sales
tory expectations. Over time, rising acuity, the underwriting, loss control, and claim expense outlay.
additional services, and diminished staff- handling process. Risk analytics is not a ‘magic solution’
ing ratios will lead to adverse incidents if With risk analytics, potential claim for a captive insurance programme and
not kept in check. It used to be that these incidents can be rapidly and cost-effec- still requires a great deal of work. While
fluctuations in underlying risk would go tively analysed. At this time, ‘real’ risk is risk analytics and predictive modelling
undetected, but with the utilisation of identified sooner, triaged appropriately, have tremendous advantages to offer
predictive modelling tools and effective and dealt with proactively. Effective risk insurers and risk management organisa-
risk analytics, even subtle changes in staff- analytics can accelerate the acquisition tions, the ultimate value is derived when
ing, acuity and services can be revealed. of knowledge, place claims into proper the experts interpret the information cor-
Predictive modelling provides insurance context, lower claims administration rectly and make the right decisions.
captive programme managers with the costs, and help improve overall outcome. Reading the landscape through ac-
knowledge of any change to risk drivers, Moreover, predictive modelling can chart curate data, analysing trends and acting
thereby allowing the programme leader- the course for improved negotiations with on them accordingly and efficiently, helps
ship to make pre-emptive changes and plaintiffs and, ideally, lower overall settle- insurance captive managers take out some
to manage risk more effectively. For that ments. There are many variables that go of the risk of managing risk.
reason, risk analytics is revolutionising the into each and every case that ultimately ‘Scientia potentia est’, or more simply,
processes and tools employed by insurers determine how it is settled. Once a case ‘in the land of the blind – the one eye is
to more quickly and accurately market, proceeds to court, the deciding factor is king.’
price and underwrite their products. the six or eight people in the jury box.
Once a change to a risk driver is de- How they will decide is extraordinarily
tected, the captive can predict how these unpredictable. With the passage of time,
changes will affect its overall portfolio ex- the cost to settle any case may increase About Asi
posure. From that knowledge, the captive exponentially. Risk analytics and predic- we are a specialty insurance compa-
gains deep insight into actual loss costs tive modelling provide the insurer and ny that provides customised insurance
and can confidently adjust premiums, the defence team with rapid access to the products and solutions to small and
offer feedback regarding risk manage- information needed to manage incidents medium sized businesses in industries
ment, and continually monitor prefer- proactively, triage claims effectively and which we believe are underserved
rably before any loss occurs. Without settle claims before that critical window of by the standard insurance market.
predictive modelling and risk analytics, opportunity closes. we have developed specialised in-
after an account is written, the policy is A captive manager has to play to the surance policies and alternative risk
generally held in status quo with minimal strength of risk analytics in order to transfer products not generally avail-
consideration to any variation in underly- benefit from it, which includes being able to our customers because of
ing risk, until it’s too late and a major loss savvy and quick enough to respond. This the unique characteristics of the risks
develops. also includes being flexible enough with involved and the associated needs of
With improved risk data management, the tailoring and implementation of a the insureds. we currently specialise
insurers can lower overall costs, charge predictive model to match the flexibility in developing and underwriting these
adequate premiums, reduce claims, gain of risk analytics as predictive modeling products for environmental risks, resi-
competitive advantage, and ultimately, tools are available for any step along the dential and commercial construction
increase their market share. It all starts continuum, including marketing analytics, companies, specialty programs, fully-
with underwriting the data. Every expo- underwriting, risk management, and loss funded policies and other specialty
sure must be analysed to establish the mitigation. classes of risks.
appropriate premium in order for the Another advantage of predictive
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