You can't make brokers more loyal; just less promiscuous

Apr 20, 2012

"I don’t think I was constructed to be monogamous. I don’t think it’s the nature of any man to be monogamous…" Marlon Brando

What is the nature of the relationship with a broker?  It isn't as simple as saying the 'broker is the customer', because there are some clear differences. The broker stands or falls by his expert buying skills and he also has to look after his own interests, those of his client and and, yes, even those of the underwriters.


The upshot is that 'loyalty' isn't a particularly helpful term - brokers are pre-programmed not to be loyal.  The best that you can hope for is to reduce the tendency to promiscuity and in so doing reap benefits of more concentrated, durable set of relationships with your brokers.

Why you need to start thinking about promiscuity:

Less promiscuous brokers:

  • Give you more repeat business
  • Show you the best business first
  • Award a higher % of business that you quote
  • Recommend you

In low promiscuity scenarios it is easier to:

  • Develop stronger relationships
  • Communicate more effectively
  • Value the broker relationships you have more - so building further loyalty and trust

If insurers can understand and predict broker behaviour they would improve performance by adapting their approaches to promiscuity reduction.

Over the past few months we set out to see if we could find evidence that might help this predictive understanding.  We analysed our large London Market survey data sets (5000+ data points) looking particularly at how brokers behave 'en masse' to identify any interesting behavioural patterns.

The first finding was that on average any given broker uses 11 insurers - competitive certainly - but we also found that this promiscuity number varies significantly from insurer to insurer.

For some, the promiscuity number is as high as 20 and for others as low as 6.

From this we created a Promiscuity Index which, when broken down by business line, seems to correlate well with insurers strengths.

To understand what was behind the varying levels of promiscuity we conducted correlation analysis to find the drivers of low promiscuity.

There were four strong drivers and we can now map these onto performance measure to show how insurers can reduce promiscuity.

We will be publishing more on this in the next month or so.