Deriving insight from claims data

We all now live in a world where we’re constantly consenting to our data being collected, tracked and monitored. Information is uploaded into spreadsheets, databases and bespoke systems from which all sorts of reports can be created.

But data on its own, without any context, is of limited value. Data provides answers to the ‘how many’ or ‘% increases’ questions but not the more interesting ‘why’ or ‘what does that mean for me’ questions.

For risk managers it’s the answers to the ‘why’ and ‘what does that mean for me’ questions which really make the difference.

Understanding the factors as to why claims happen enable the risk manager to take action to better mitigate and manage the business’s risks. Simply having a plethora of uncontextualised claims data and then being left to interpret what that data means for their business is unhelpful.

However, providing real risk management insight really does have a significant impact and enables risk managers to reduce not only the frequency of claims but just as importantly, the cost of claims.

In practical terms this means identifying the root causes of losses and the factors which impact the claims costs. This is done through taking the claims data and overlaying it with key facts about the business and the industry sector.

With the use of good technology this data can be analysed and can reveal surprising results.

A lesson in data analytics 

One example of this came to light when we undertook a review of one of our client’s management information with the aim of redesigning it to be more informative. The client was a national civil engineering company.

We took all their claims data and split it into regions to reflect the company’s structure. We then interrogated the types of losses in each area and also included information from their subcontractor network.

By working with the client, we were able to quickly identify previously uncaptured factors which were having an adverse effect on the frequency and average claims cost.

We found that there was a very high number of claims for cable strikes and injuries arising from potholes, particularly in one region. To understand why this might be we looked at the data for the various subcontractors in that area as that seemed to be the only variable compared to other regions. And herein lay the answer: one subcontractor was working in such a way that a very high proportion of losses could be attributed to them.

The risk manager took this data to an operational board meeting and was able to pinpoint exactly where the problem was. This was unheard of as the claims data had never been interrogated in this way before and it had just been accepted that this level of claims was inevitable across a business of their size and nature.

The risk manager was then able to work with their operational colleagues to remove the subcontractor from their network. This had an immediate effect, saving them 20% of their indemnity spend – which of course goes straight to the company’s bottom line – a win-win for the risk manager and the business. 

Spotting areas of weakness

Using the same data analytics techniques, we worked with a travel business and were able to identify specific hotels across their global network which were generating the most claims.

We identified that just 3% of the hotels in their network were responsible for creating 19% of their claims which was obviously disproportionate. The company then chose not to renew their contract with these hotels the next year which immediately improved their claims ratio.

It’s often simple fixes which can make a big difference, but the key is identifying these simple operational challenges. If we can help reduce the frequency of claims and manage the cost of claims, then this is a huge benefit to every business.

Of course, it’s vital to have your good technical claims handling, but to get true value from your claims management supplier, risk managers should be demanding risk insight, not just data.

Paul White is CEO of Sedgwick International in the UK