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. 28 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. +