Rapid innovation – from the prototyping of products and services through to validation and then into the market at scale – is a fundamental pillar of digital transformation. The challenge for many organisations is first identifying what those opportunities for new products and services are.
That’s where a data-driven approach to innovation can pay dividends. Underpinned by the wealth of data that’s generated, digital technologies such as artificial intelligence (AI) and intelligent process automation enable new ways of understanding customer behaviours and needs – often in real-time. In turn that data-driven insight reveals the kinds of products, services and experiences that customers value enough to pay for. Organisations can then be more proactive in offering tailored products to customers as and when they need them.
The important role of data in digital transformation is highlighted in the Cognizant report The Work Ahead – 40 months of hyper-digital transformation by the Center for the Future of Work. In that research, 82 per cent of executives forecast that Big Data and business analytics will have the biggest impact of all digital technologies between 2020 and 2025. These data insights can help to serve customer better; but all need to be compliant as well.
These digital technologies will have a major impact in particular on insurance companies. The move from an agency model to a digital platform is already one of the most anticipated moves in the sector. At the same time, risk and cyber threats have to be taken seriously in what is a highly regulated industry. The good news: those challenges are nothing new for a sector that is used to protecting and developing large data sets and dealing with complex regulations.
There are many possibilities for this kind of data-driven innovation to transform the insurance market. The Internet of Things (IoT) and sensor-derived data offers the potential to tailor proposals for customers. Access to data on the everyday life of policy holders also enables insurance companies to estimate risk for life and property insurance products more accurately.
This availability of real-time data is also supporting the growing market for a whole new range of micro insurance products. Unlike traditional annual or lifetime policies, micro insurance products can be enabled by data analytics and intelligent automation to rapidly underwrite protection against a specific event or need for a certain period of time, such as a one-off car journey.
In the insurance sector, this level of responsiveness also needs to be integrated into core products so that insurers can react quickly to changing user behaviour. An obvious example is for health insurance, where the real-time data from wearables could allow policies to be re-evaluated on the fly in response to the activity levels of the user. Car insurance is another example. Data from cars could be used to reward better driving behaviour by rewarding it with new deals or contracts.
One key element in the data-driven design of new products and services, that it is important not to underestimate is behavioural economics. This is where human understanding and psychology add context to the insights from Big Data to analyse decision-making and why consumers choose one product over another. Throw these together in real time and it is possible to monitor customers’ behaviour after they have bought an insurance product. In turn, this enables even more responsive and data-driven innovation in product development.
Ultimately, data underpins much of the shift to digital for insurance and many other sectors. This data-driven insight will mean shorter decision-making cycles and provide endless possibilities to track user behaviour. And that means technology is now not only supporting back-end processes but enabling rapid and responsive product innovation and opening up entirely new revenue streams.
With more flexible offerings, insurance companies have more access to their clients than ever before. Huge opportunities await.
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