Brought to you by:

A slow, careful march towards the data revolution

Right now the amount of digital data in the world – and the ability to process and analyse it – is growing exponentially. That data is coming from multiple and expanding sources as homes, workplaces, cars, fridges, TVs, microwaves, wristwatches and any number of other devices become digitally enabled.

A new Swiss Re Sigma report says the amount of worldwide data will grow by 27% to 175 zettabytes in six years. To understand that figure, think about how much your terabyte hard drive holds, and then multiply that by 175 billion.

Property and casualty insurers have an opportunity to unlock that untapped potential across the insurance value chain. Yet the report makes clear that the industry is still taking baby steps into the field of data analytics.

Most insurers are only at the early stages of building the foundation for analytics initiatives, the report says. Data siloes still exist, and the industry has been slower than most at adopting new technologies.

Insurers are also aiming for the low-hanging fruit, like using data to analyse claims and underwriting, or for “narrow use cases that can be operationalised quickly so that value add is easier to demonstrate.”

But the industry is starting to realise there are greater opportunities to be had. Last year British insurance giant Lloyd’s said the data explosion from the growth of the Internet of Things will lead to a radical change in risk assessments, with prices and policies based on real-world performance. About 25 billion devices will be connected to the internet by the end of next year.

Most insurers are planning some kind of initiative around data and analytics, and the report lays out four specific ways that P&C insurers can make a real difference to their businesses: consumer behavioural analysis, improving loss ratios through better risk selection and pricing, using analytics to automate underwriting and claims processing and using data to target untapped markets.

Some insurers are applying behavioural analysis, in the first stage of the insurance cycle – targeting customers. The changes are small, but have big payoffs, the report says.

QBE has used open data as well as internal data to identify profitable target customers and improve their bidding and engagement. The subtle rewording of a button on a website can lead to significant increases in clicks. Insurers are also starting to identify context-specific drivers of insurance-related behaviour.

The second area where insurers can improve is in underperforming insurance classes. Data analytics can help investigate trends in loss drivers and uncover reasons for poor profitability.

Swiss Re singles out Axa XL, which has been using publicly available data to develop better insights about the risks its commercial clients face and more accurately predict future claims and identify attractive risk profiles. Interviews with industry executives reveal that insurers are targeting a 2-5% improvement in loss ratios, according to the report.

Insurers are also using data analysis in the back-office, to automate claims and underwriting management processes, or using bots to cross-check customer emails with claims records, or to review policy wordings.

The fourth area of opportunity is to mine data to reveal unmet needs for new insurance products. Data analytics can help build detailed risk evaluation models where insurers lack underwriting expertise, the report says.

Insurers moving into SME product lines could amalgamate fragmented data sources to assess the different risks faced by small business in different industries and compare the risks with its existing portfolios. Insurers are using this approach for cyber, leveraging data analytics to construct risk profiles in the absence of historical data, the report says

The report believes the outlook for the industry is promising, but there are significant challenges in being able to make use of the data that is now becoming available. Personal lines insurance is some distance ahead of commercial lines on this, because of its access to better data quality and higher transaction volumes.

“There needs to be more investment of time and resources on data curation. Many new data sources are not created for insurance, and owners of the data may neither understand insurance nor how to make the data usable for insurers,” Swiss Re Head of Insurance Risk Research Daniel Ryan says.

The report warns that the benefits of using data analytics are not immediate. Insurers shouldn’t expect an impact on the bottom line before three to five years.

Deploying analytics is just as difficult as any technology implementation at a large company, and legacy systems, organisational inertia, and cost pressures all contribute to a drawn-out timeframe.

Analytics capability will be essential for competitive advantage, but its true potential will only be realised when the industry develops enabling infrastructure, resources, and knowledge, the report says.

To read the full report, click here.