How insurance companies use big data

As an industry that requires a large amount of data from each client, the insurance industry is learning to leverage this data and use it to their - and their clients’ - advantage.

Thanks to their increased digital interaction with consumers, insurance companies are accumulating a large amount of consumer data. This data helps insurers understand how their consumers live, which in turn helps them to assess the different categories of consumers risk more accurately. Applying analytical techniques when processing this data allows insurers to derive insightful and relevant business intelligence; this called big data.

What is the purpose of the data?

Data is a valuable commodity in the insurance industry. It directs the precise process of assessing risk and, ultimately, determines the price of clients’ insurance premiums. More detailed data informs individual risk profiles for each consumer, allowing the insurer to completely customise the process of determining an insurance premium.

Being able to track how consumers drive their cars and protect their belongings makes it easier to predict how they will behave in the future. This puts the insurer in a better position than ever before to correlate premiums with risk in a more efficient way – an enormous advantage to the industry.

Considering how competitive the insurance industry is, being able to set a better price based on a more specific risk profile creates an important competitive business advantage. It also offers consumers a more customised insurance experience.


Vehicle tracking using a telematics device is a great example of using data to determine more individualised risk profiles. These devices allow insurers – with the permission of the insured consumers – to gather information that helps them determine a more exact level of risk posed by the ‘tracked’ driver. Using this information, the insurer can assess the chance of the driver in question being involved in an accident or having their car stolen – all based on their past driving performance. Factors such as the speed they drive, the areas they tend to drive in and the distances covered every day are taken into account.

Drivers under 25 years old typically pay more for their car insurance as this age group traditionally has a higher-risk profile than older drivers. Theoretically, a telematics device would be able to track a younger driver who does not behave similarly to their high-risk age group and prove that driver to be a lower risk, qualifying them for a lower premium despite their young age.  

Fraud detection

Fraud is a major problem in the insurance industry, these days big data is being used to combat this with real-time analysis and alerts.

The large amounts of data at their disposal at the underwriting stage of a policy allows insurers to assess, with reasonable accuracy, which applicants have a higher likelihood to commit fraud.


Data can also benefit the marketing of insurance products and services. Data offers insurers the opportunity to better understand their clients and they use this information to offer products and services that appeals to individual profiles and is more suited to the different life stages of the insured.

Aside from more efficiently priced premiums and reduction in fraud, big data enables insurers to improve their overall customer service and support by better understanding their clients and not treating all clients exactly the same. This more accurate segmentation of markets - thanks to big data - is leading the way to improved customer service and more client-centric products and services.