Delivering a fast response to customers in disaster zones

Farmers Mutual leverages its customer data for better decision making and reporting

A much valued New Zealand customer for some years, insurance company Farmers Mutual Group (FMG), takes advantage of the classic end-to-end SAS solution for managing all its non-financial accounting business needs – from data warehousing and data extraction through to business analytics and a web interface for executive level reporting and general information delivery. SAS provides FMG with the ability to leverage their data for an accurate view of the customer, enabling better decision making and reporting.

FMG's origins go back to 1905 when a group of New Zealand farmers banded together to establish their own company catering for specific rural community needs and to lower their insurance premiums. The organisation has remained a Mutual one to this day and now provides a fully comprehensive range including home, life and motor vehicle insurance.

... by the end of that Saturday, by the end of day-two we were in a position to extract almost all the critical information to give to management.

Craig Skett
Manager, Business Information & Analysis Services

Insurance customer faces major emergency situation

The SAS solution was put to the test in extreme circumstances on Saturday September 4th 2010 when Craig Skett – FMG's Manager, Business Information & Analysis Services, and his team – became part of a concerted drive to help provide a speedy reaction to policy holders who might have been affected by the earthquake that struck at 4.35AM that day. The 7.1 magnitude earthquake's epicentre was in a rural area 40 kilometres west of Christchurch in the South Island and FMG's concern was understandable given that a large number of customers in its client base were likely to have been affected.

Within two hours of the earthquake striking, and as it was deemed safe to do so, FMG Assessors were headed towards the affected area. In addition – and thanks to the quality and currency of its SAS database – FMG's General Manager, Advice & Insurance, knew who his most at-risk policy holders were and chartered a helicopter to get to them quickly. In parallel, the company's contact centre was fully staffed and remained so throughout the weekend and beyond.

SAS solution plays vital part in fast response to disaster

And this is where Craig Skett and his team – as well as their SAS-aligned database and analysis tools – came into play.

He explained, "We were well placed to bring technology to bear, following the earthquake. Using SAS, we had been developing our analytics capability over the previous four years. This now includes regular KPI reporting, being able to quickly produce different cuts of accurate customer lists, and conducting complex analysis models around pricing and forecasting."

At nine o'clock that Saturday morning, FMGs head office asked for the call center to be supplied with contact details of every policy holder who might have been impacted, with the objective of quickly contacting them. In addition to making it clear to those people that their insurer intended getting ahead of the game – rather than wait for them to call in – it was obviously important for the company to be able to estimate its exposure to claims as soon and as accurately as possible.

Analytics to identify likely claimants: continuously update financial exposure

Learning from radio and television news reports where damage was understood or thought to have occurred – including remote areas difficult to access – the team began an extraction and analysis drive that recognized that conventional telephone or internet contact might not be possible given the likely destruction of landline and wireless infrastructure. Alongside this, types of risk were analyzed based on news reports about damage to buildings and other property, including livestock. Miraculously, there were no casualties but the subsoil liquefaction that results from earthquakes rendered large areas of grazing pasture unusable.

This intelligence, plus numbers for possible consequential loss through business interruption, was needed in order for FMG to understand where it stood both financially and in respect of customer contact. In New Zealand, certain types of insurance cover are supplemented by the Government's Earthquake Commission scheme and this, too, had to be factored into the calculations.

The findings were also used to populate and keep updated a visual map of the South Island topography so that everyone in the company could see at a glance on the SAS web platform which areas were going to need the most urgent attention.

Understandably proud of what his and the call centre teams achieved, Skett says that while the overall picture was, "Only rather sketchy by the end of that Saturday, by the end of day-two we were in a position to extract almost all the critical information to give to management. This was the stand-out achievement and we couldn't have done it without the SAS software. I can't imagine how long it would have taken without SAS."

He added, "Things started getting back to business-as-usual on the Monday", and "In the days and weeks that followed, we were providing the claims department with continuous updates for planning purposes".

Challenge

SAS became part of a concerted drive to help provide a speedy reaction to FMG's policy holders who might have been affected by the earthquake that struck Christchurch on Saturday September 4, 2010.

Solution

SAS provides FMG with the ability to leverage their data for an accurate view of the customer, enabling better decision making and reporting.

Benefits

Within two hours of the earthquake striking, and as it was deemed safe to do so, FMG Assessors were headed towards the affected area. In addition – and thanks to the quality and currency of its SAS database – FMG's General Manager, Advice & Insurance, knew who his most at-risk policy holders were and chartered a helicopter to get to them quickly. In parallel, the company's contact centre was fully staffed and remained so throughout the weekend and beyond.

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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