Looking for patterns in large volumes of data is hardly new for insurance companies. In fact, big data is almost the foundation upon which the insurance industry is built. It’s how decisions are made and policies are determined.
And insurers are not oblivious to how technology can enable this; half of insurance executives are prioritising technology investments to capture new client insights over the next three years.
’90 percent of the world’s data has been created in the last two years,’ says George Lee, CIO at Goldman Sachs. ‘The ultimate question is really what insight and value can we draw from that data.’
Data analytics as we know it today is changing. It is evolving into something more powerful with the advent of machine learning and artificial intelligence. Taking advantage of new technology today can, and will, make a significant difference tomorrow.
Machine learning potential
The opportunity is there, and this is how machine learning will change the insurance industry:
With machine learning, insurers can review and analyse all forms of data, including pictures, videos and audio, to a much higher degree. With this capability, insurers will be able to improve compliance and prevent mis-selling products.
Although they are less reliant on manual processes now, insurance companies rely heavily on people to make decisions and analyse information. With a move towards smarter automation, insurers can save a vast amount of money as these tasks are digitised.
Spending less and improving compliance create a competitive edge for insurers, but machine learning can offer more. Deeper analytics can lead to innovations in products and services that push an insurer ahead of its competitors by optimising their risk profile and pricing policies more effectively.
Further reading: see you can use Azure with machine learning.
When, not if
Adopting machine learning in the insurance industry will do more than provide a competitive advantage – as attractive as that is for insurers. More importantly, it will help to prevent the 350 cases of insurance fraud worth £3.6 million uncovered every day. The number of fraudulent claims is rising every year, and with it the overall cost to insurers.
‘[Fraud mitigation] is where I see insurance applying machine learning, to improve the P&L,’ says Monika Schulze, Global Head of Marketing at Zurich. ‘It is a much faster process and it is easier to reduce errors by using machine learning to process large amounts of data.’
AIG and Zurich are already taking steps to use machine learning in the future. To outperform the competition and battle insurance fraud, it’s not a matter of if fellow insurers should adopt machine learning, but rather when.
Let us know which machine learning aspect is most advantageous to insurance companies. Should you wish to learn more, download this guide on revolutionising the insurance industry ⇓