Opinion: Big data demands brokers go back to basics

Opinion: Big data demands brokers go back to basics

Opinion: Big data demands brokers go back to basics

Ansvar CEO Andrew Moon, pictured, discusses why old-school broking skills are increasingly important in the age of big data.

Big data is revolutionising many industries, including our own. Insurance companies locally and around the world are looking at ways to fine tune their analytical abilities.  There’s never been a better opportunity to deliver innovation with the advances of big data for understanding and delivering insurance services that are more precise, and more scientifically aligned with the client’s risk register.  

This topic is coming up increasingly, as recently as a conversation I had this week with Rob Whelan, the CEO of the Insurance Council,  and the adaptation of the insurance industry to this new world of data offers the opportunity to transform our approach to the way we provide risk management for our clients.

In commercial insurance, brokers and their insurance provider partners will have the capacity to explore and understand our risks in the most granular detail. With the sheer volume of data available comes the challenge of managing the extreme velocity at which data is emerging.

Looking at personal lines, no longer will premiums be calculated on such general attributes as postcode or claims history. Insurers will have the ability to work on an individual basis – they will know exactly where the premises are, its condition and the risks associated with it, and they will assess the insurance risk accordingly. In other words, in every instance the approach to risk cover will become bespoke.

It is ironic that despite the rich data available today, we are still starved of true insight.  The industry’s next real challenge is to find the means to achieve that insight. I think we need to move fast in this direction otherwise the avalanche of data heading our way may swamp us..

To take advantage of the growing swirl of data, we need to know how to capture this data, selectively store and manipulate the data via analytics and ultimately extract and apply these insights to improve the way we respond and provide risk solutions.  It will add a layer of precision and offer us the ability for greater fact-based analysis of client needs, and more informed pricing for the spectrum of risks we can afford to underwrite.

I believe data visualisation will help our industry to navigate the volume of data available. However, in order to do so we need a far greater bespoke approach to insurance selling than before. In order to do this we need to get to know our customers so much better.

Where does this leave brokers? Of course, there is a risk that customers simply start relying on technology to point them in the direction of the right insurer. However, I believe there will always be a demand for a human element in insurance, provided it’s an interaction that adds value - and that’s where the need to practice the true art of brokering comes in.

Price hunting will be the commodity service that falls by the wayside. Only brokers who can understand bespoke risk and achieve a fit with the right insurer will succeed. The role of broker will increasingly be that of matchmaker. The data that follows is the fertile ground on which we can build improved and greater valued relationships with our customers. That’s what best quality brokering has always been about.

Click here to read how retailers are taking advantage of big data in the insurance space.

1 Comments
  • TMS 22/09/2013 10:07:04 AM
    Big data has its benefits in many industries, but the danger is in insurance relying solely on big data to make its decisions, and also enforce its assumptions. Yes, good for estimating insurance risk (ie, which areas would be prone to flooding, bush-fire risk) from big analyses. No, not good for declaring the insurance risk based on buying patterns.

    For example, statistically I'm a higher car insurance risk because I'm a male P-plater. Never mind that I stick to the limit, obey the rules (moreso than than some drivers long since off their P's), don't tailgate and indicate when I change lanes.

    According to the linked article, I'm a bigger insurance risk because I like spirits, eat pasta, and fill up the tank on a tuesday night. This is extrapolated, how? Assumptions derived from data that has nothing to do with driving on the road.

    But big data isn't the be-all and end-all, and like all well-purposed inventions is open to misuse. More than just the broking, the industry needs to look at other ways to give value to its customers.
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