Risk & Business Magazine Moody Insurance Spring 2017 | Page 28

ANALYTICS & NUMBERS
Why The Numbers Matter
Analytics & Insurance
I
n this age of information overload, it is important to
identify the right data and apply the correct assumptions
to answer the right questions. Insurance agents are
increasingly applying advanced analytical methods to
client data to assist clients in making better strategic
decisions about the risks they face. The rise of analytic tools in
corporate insurance is making a significant difference in the way
risks are understood, measured, mitigated, and transferred.
Historically, companies have received professional, fact-
based, decision-making approaches from trusted advisors
such as management consultants, bankers, and lawyers. They
traditionally have not received the same level of decision-
making support from the insurance industry. But with risk
analytics now being used in insurance buying decisions, this will
benefit companies in three main ways: by providing them with
information about their risks that is equal to the information
insurance markets possess, by giving them the tools with which
to make strategic decisions, and by providing a clear decision
trail and logic that will stand up to scrutiny by ownership.
The main aim of Moody Insurance is to support stronger
insurance-buying decisions by our clients. One of the ways we
do this is by demonstrating how effective insurance can be as
a hedge to protect corporate financial performance. Analytics
have helped Moody’s clients make informed decisions along
the risk spectrum as they grow, allowing them to choose large
deductibles and captive-type programs if the numbers make
sense compared to the amount of risk they are taking on.
Through analysis of client and industry data in benchmarking
areas like limits, deductibles, and claims costs, we can help
clients plan for a rainy day and make sure their companies not
only pay the most efficient amount of premium dollars but also
have enough in insurance limits to allow them to go forward.
This is a different way of thinking about insurance.
One of the best uses for risk analytics is to identify where the
biggest risks and failure points are for an organization before
a major event even happens. Risk analytics can be used by
management to make it aware that, at some point, its business is
likely to go through a financial downturn and therefore, make it
better prepared to take adequate measures.
Companies can use risk analytics to support insurance-buying
decisions in the way they would any other investment—by
John Wilson is Moody Insurance Agency’s President of Commercial
Insurance. He brings a strong background in construction that mirrors
Moody’s own, as well as significant litigation experience, which gives him
a unique perspective on managing complex risks for our clients.
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BY: JOHN WILSON
MOODY INSURANCE
performing a return-on-investment analysis. With a data-based view
of risk, return versus the risk can be analyzed, allowing for financial-
based decision making concerning the best decisions regarding limits
and deductibles.
It’s only a matter of time before risk modeling becomes an integral part
of corporate insurance buying for all sizes of companies. This will be
driven by ownership and management who will increasingly demand
that insurance buyers demonstrate that risk management investments
and insurance decisions have been made with analytical thought.
Insurance is a hedge and, as such, can be applied to any investment
decision where there is an insurable risk. It’s a great new frontier for
insurance. The big game changer will come when risk analytics are
integrated with company financials and applied to strategic decision
making. We believe this is the next step forward in insurance: where
the insurance industry will offer the same level of data-based decision
making we currently see in the banking and management consulting
fields. +