Things have changed in the world of insurance. Everywhere you look, there are seeds of innovation sprouting root and giving rise to NEW propositions, NEW customers, NEW competition and NEW data.

This NEW InsurTech competition is tackling the traditional insurer organisations head-on with clear eyes and a full heart! The InsurTech start-ups are well funded, agile and quickly gaining ground with their new propositions. The most recent example of successful fund raising for an InsurTech start-up is ‘Bought by Many’, raising £7.5m from companies including Munich Re.

‘Bought by Many’ uses social media and search data to offer ‘insight driven insurance’. They’re a great example of NEW competition leveraging the value of NEW data.

The InsurTechs are catching up, gaining significant ground on traditional insurers. What’s their secret? How are they able to achieve this ground so quickly in what has always been a staunch traditional insurer foothold?

One common underlying factor

Their secret ingredient is renegade analysis methodologies of NEW data. This is the one underlying factor which is common across all new start-ups. InsurTechs manage this NEW data in different ways to better understand the customer, tailor their propositions and evolve by means of rapid fire ‘test and learn’.

How do they achieve this, especially considering 44% of InsurTech companies have fewer than 10 employees!

Data in insurance drives insights but how?

It’s not simply a numbers game. In a recent article from Celent’s Nicolas Michellod, he talks about data in insurance not just being about technology. Insurers need to recruit more highly-qualified data experts with different profiles to valuably leverage this NEW data.

We all know and understand the traditional data decision making cycle – data drives insights, which in turn drives better decision making. Traditional insurers and brokers have understood this decision-making cycle for a long time but have struggled to leverage value historically from big data analysis.

One of the challenges is the sheer volume of data – the digital universe is doubling every 2 years!

With ever-increasing, cheaper solutions to store, manage and process data and the rise in computer power, digital business and the internet of things, there’s literally an explosion of data.

How to deal with all this data, bearing in mind most of it will simply be ‘NOISE’? Organisations are trying to increase their capacity to analyse data but without the right data strategy, people or tools, they end up drowning in their own data lakes!

InsurTechs have quickly grasped that things have changed. It’s not enough to follow the traditional models of analysing ‘Big Data’, for them it’s about NEW, SMART and fast data analysis. This is their secret to success.

Being SMART about data

SMART data analysis describes how new organisations can successfully filter their data gathering and analysis into what is specific, measurable, achievable, relevant and timely (SMART).

They start with:

  1. Only the key questions they need answering;
  2. Determine the specific data required to answer those key questions;
  3. Collect and analyse the required data;
  4. Deliver targeted insight.

Sounds simple, but this approach has to be done at pace to be effective – speed is the key!

Insurance can learn from other industries

In the InsurTech world, there’s no room for bureaucracy, lengthy approval and decision making processes.

Other industries have been practising this new, SMART, fast approach to data analysis long before the inception of InsurTech. The McLaren F1 Technology Group have been using their data analysis learnings and innovative ideas to reinvent global companies. They’ve long been a successful net exporter of innovation to the world of business.

Everything McLaren do is linked to one SMART objective – ‘Make the car go faster’. Insurers can learn from this approach and I believe all SMART data analysis should be linked to these 4 core insurer objectives:

  1. Increase profitable growth;
  2. Drive up customer engagement;
  3. Drive down costs;
  4. Strengthen controls.

There’s now a proliferation of new ways to create, capture and analyse data with countless new sources, including ‘on demand’ insurance, usage-based insurance, smart homes, telematics and wearables.

Effectively managing these new data sources is a great opportunity for insurers and brokers to improve risk management, expand insurability and accelerate the development of NEW, novel and personalised propositions.

One way traditional insurers can leapfrog ahead of the NEW competition in an agile fashion is building model offices to capture data, test, learn and make the right decisions quickly.

Things have changed. It’s not about doing the same things better, it’s about doing different things – a theme that InsurTechs have grasped quickly.

How our ICE Analytics solution can help

We’ve built our ICE Analytics solution to be SMART, fast and fit for the future.

Here are five reasons why more insurers are implementing the ICE Analytics solution into their strategies for 2017:

  • Speed of implementation – days not months
  • Single view of your business– consolidated view anywhere, anytime on any device
  • IOT enabled– proven capability in connecting to new data sensors
  • Real Time Reporting – faster insight enabling agile proposition improvements
  • Access to unparalleled insight– predictive and trending analysis driving better decisions

If you’re looking for a Business Intelligence solution that delivers a fast return on investment, or want to build a test and learn model office that’s easy to implement and provides a single view of your business, then talk to the team at ICE InsurTech today.

In the world of data analysis, things have changed – have you?

For more information, contact ICE InsureTech


Bought by Many –

Institute of International Finance (IIF): Innovation in Insurance – How technology is changing the industry, Sept 2016

Celent: Data in insurance is not only about Technology –Nicholas Michellod

McLaren F1 Group –


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