Return on investment: the cost vs cost savings of risk management technology

“You can have the best risk management processes and controls within your industry, but unless you can articulate that and evidence that to the insurance market, it can be ineffectual.”

These are the words of Uniting Church in Australia (UCA) head of risk and insurance Christian Mathis, who, by his own admission, used to go to the insurance market “with his fingers crossed”.

Fast forward five years and UCA has gone from “worst in class to best in class” when it comes to the quality and scope of risk profiling data, resulting in a 30% saving this year to its property insurance programme.

Key to that transformation has been the implementation of a new risk management information system (RMIS) platform, which has allowed Mathis and his team to change the way it gathers and analyses data for its risk management and risk transfer programmes.

UCA is an umbrella organisation which, in addition to churches, owns and operates child care centres, aged care facilities, schools and hospitals, and runs range of social justice programmes such as foster care services and supervised injection centres.

It’s a complex organisational structure, with each arm of the business having its own unique nuances with regards to risk and insurance.

When Mathis joined UCA in 2010, he says the organisation desperately needed to reposition its risk profile.

“I knew when I first got into the role that for me to reestablish and reengage the insurance market we would have to have good quality information and data. One of my first projects was to think about what information we needed in the medium to long term to not only provide to the insurance market, but also for the sort of reports that I believe our internal boards and stakeholders should have,” he says.

After a tender process UCA opted for an RMIS platform owned by software company Ventiv Technology, that enables a company to centralise and streamline its risk management and insurance data, create reports and automate manual processes.

Prior to implementing the technology, for example, risk data for insurance renewals was gathered by a paper-based questionnaire that was sent out to the various UCA boards and entities for completion. About 30% of the surveys were filled in and returned, Mathis says, with varying levels of buy-in from the different arms of the business.

“When we used to take that information to the insurance market we did it with our fingers crossed,” he says.

Today, tailored questionnaires are distributed electronically to UCA’s 600+ entities, with different questions asked of each part of the organisation. The success rate of the questionnaires is now more than 90%, Mathis says, “and that gives us confidence in what we declare to insurers”.

A Lloyd’s broker by trade, Mathis says he has witnessed first-hand a significant change over the past 10-15 years in how a risk is presented to insurers.

“In my old days at Lloyd’s you could get away with some claims stats, a (placement) slip and a basic risk profile. But underwriters today require not just loss experience but they want evidence of that and they want to challenge it and they want to be able to ask further questions,” he says.

This was highlighted in UCA’s most recent property insurance renewal.

Previously the asset schedule for UCA’s property insurance programme was simply a listing of all of the group’s different properties – schools, churches, aged care homes and more were all lumped into the one portfolio.

“Year on year the portfolio’s pricing had stayed very stable and it was locked into one particular market,” explains UCA’s broker Penny Wasik, specialty divisional manager at JLT.

“There was very scant risk information. So if you were going to market to try and create a compelling story about the organisation to insurers, it was actually quite difficult to do so,” she says.

Last year, however, JLT was able to break down UCA’s asset schedule into separate portfolios, resulting in a 30% saving to the group’s property insurance spend.

“By having quality and granular information, and now having it for several years, we were able to do some really sophisticated analysis and present an alternative structure to the market that enabled us to unlock those discounts and attract other markets to the table that ordinarily wouldn’t have been interested,” Wasik says.

“We were able to cut up the asset schedule into various pools and compare how those pools of assets perform from a claims perspective. You can get a lot smarter about how you structure a policy; you may have different excesses for different pools of asset classes that reflects how they each perform, and you can be much smarter about where deductibles should really be.”

The granularity of the data also enables clients to make more informed decisions about self-insurance, Wasik says.

“The more confident you can be in your under-excess loss profile, the more confident you can be about taking on greater levels of self insurance, whether that be taking higher excesses or whether that’s looking at a captive situation or some other self-insurance vehicle,” she says.

Mathis agrees.

“Information and data, providing it’s complete and accurate, is absolutely the life blood of making those decisions. You can’t make decisions in terms of risk transfer, strategy and service provider unless you have that information. It’s part of our arsenal,” he says.

UCA also now offers its insurers the option to have regular lists of notifications against certain policies away from the renewal process.

Most organisations don’t offer that, Wasik says.

“It’s the notifications that insurers are really interested in because it shows a pattern. Some clients take the view that they’d rather keep those to themselves until they turn into claims, but UCA don’t; they’re very transparent.

“That has given the market a lot of confidence to be able to do things from both a pricing and coverage perspective that they ordinarily would not,” she says.

Mathis says he only expects insurers’ demands for quality data and information to increase.

“Insurance data is the life blood from which risk transfer strategies are not only set but ultimately measured and assessed. Whether you are focused upon the remarketing of a particular risk class, the calculation of optimal self-retentions or development of risk allocation strategies such decisions must be made where the accuracy of underlying data is undisputed,” he says.