Is having a good solvency Policy as Intelligent for Business as it is for Life?


The news earlier this year that AMP has surrendered its title as Australia’s biggest life insurer,  as it battles a surge in policy lapses and claims. Read more:

Over 20 years ago from the late 1980’s to the mid 90’s financial management of back office processes in a Life and General insurance office, was part of my job.  That was to ensure business processes were in place so policy reserves were sustained and costs ratios were managed. Weakened reserves are always a concern.

For giants like AMP likewise it is no light weight issue. In the mid 90’s when our company had seen incredible organic and strategic growth the high new business acquisition cost had also weakened as this strained our reserves.

High cost items at the time included simple things like the telephone bill. Phone unit costs today are 100th the cost  of then. Given there were no IP internet phones back then to reduce this cost we needed to setup our own.

We did this by negotiating a deal with our Telco for fixed bandwidth data and voice lines for our country wide communications . This extended to the field sales force and agencies and to our central underwriting and support center in Melbourne, that serviced all agents and policy holders nation-wide.

With a cap on one major variable the only risk was a penalty that applied if our overall usage went over the contracted bandwidth limit. So to manage this we also logged and priced all calls for recharge to back office cost centers using basically what was our own internal telephone exchange.

We rarely went into penalty unless we had a campaign, but we needed this unit costing internal cost allocation purposes too. 

I recall once getting pages of print of the calls our internal staff made . In one month typically around 40000 calls were made by around 1200 staff.

With the technology then it was not simple to do analysis direct from the transaction database, like now.  Even so,  when I found the internal cost allocation in my own finance office was high, I decided to take a look and see what it told me about our activity.

A printout I got summarized calls and cost of every person in the company. It seemed odd as I scanned each page that so many people had exactly the same money of around 80 dollars of local calls; which tallied to over 300 people.  I was curious so I checked a few months and I found similar patterns. Curiously each month was a slightly different, like 84.60,  81.00,  85.05,  85.84,  87.75. 

I also notice exactly half that amount e.g.. like 42.30 repeating for a smaller numbers of people.  Putting 2&2 together it was easy to see that working days was the variable for one or two calls per day for these groups. Curious too was the callers were mostly  IT or back office people who had no external dealings. What it did told me was the habits of our teams seemingly were focused on work. My colleagues laughed when I told them I knew at least 40 % of the company rang their spouse or a friend at least once or twice a day,  the second to perhaps say they heading home.

I wondered then if we should incentivize our in-house people to use the phone more  to introduce friends to our products and services.

Our internal system was quite sophisticated and could show costed times and the number called by each by person. It was like the Telco’s do now to itemize your bill for you . In our case we masked the last digits for privacy reasons.

As a data source long before sophisticated business intelligence tools,  we used the likes of Lotus 123 and paper based printouts with a calculator  Even then we used mainframe power to first do the heavy lifting With that capability we could summarized and analysis large data volumes including our sales production and policy data. So matching phone log , with area codes, in our then state of the ark ICL mainframe policy management system was often queued.

This crude use of this type of business intelligence, commonplace today in higher forms, let us gain huge insights on concentrations of activity and the best performing agents and markets.

These insight in the early 90’s also lead us to an ambitious project to set up one of the first laptop based online policy generator systems We stared this by issuing one to each top performing agent. Using a client’s phone to dial a local ISP modem could let the agent submit and issue a policy there and then online across our Intranet. Mind you, laptops too were new and truly ground breaking stuff. And would you believe the purchase criteria for the laptop for our initial order of 1000 was not the cost at over $7500 each, It was the battery life. 

As a traditional conservative life office this type of cut and thrust thinking began to transform it into a modern pace -setting performer that challenge giants of that time, namely AMP and National Mutual. At that time too we were also involved in leading the whole emerging revolution of dismantling traditional silo based business thinking as we entered into cross selling and started setting up affiliations with the banks. Around 1993 we actually bought The State Bank of NSW ourselves to cross sell what is now referred to as Bancassurance business. That was shortly before the Commonwealth Bank (Australian largest bank) then bought us.

They were strategically smarter than us. When they saw what we were doing, we became a prize. And having deeper pockets and our back door being left open with the weakened reserves, they simply slipped in and took us.

If only we had the capability to do what we can do now to dig into the data we had.  Then with that elastic power a well aimed slingshot would have seen us the winners outsmarting the Goliath that actually swallowed us up.

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